Articles | Volume 24, issue 2
https://doi.org/10.5194/acp-24-869-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-24-869-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Technical note
| 
22 Jan 2024
Technical note |
| 22 Jan 2024
| 22 Jan 2024
Technical note: Emulation of a large-eddy simulator for stratocumulus clouds in a general circulation model
Finnish Meteorological Institute, Helsinki, Finland
CICERO Center of International Climate Research, Oslo, Norway
Jukka-Pekka Keskinen
Finnish Meteorological Institute, Helsinki, Finland
Sami Romakkaniemi
Finnish Meteorological Institute, Kuopio, Finland
Harri Kokkola
Finnish Meteorological Institute, Kuopio, Finland
Petri Räisänen
Finnish Meteorological Institute, Helsinki, Finland
Antti Lipponen
Finnish Meteorological Institute, Kuopio, Finland
Antti-Ilari Partanen
Finnish Meteorological Institute, Helsinki, Finland
Jaakko Ahola
Finnish Meteorological Institute, Helsinki, Finland
Juha Tonttila
Finnish Meteorological Institute, Kuopio, Finland
Muzaffer Ege Alper
Finnish Meteorological Institute, Helsinki, Finland
Hannele Korhonen
Finnish Meteorological Institute, Helsinki, Finland
Tomi Raatikainen
Finnish Meteorological Institute, Helsinki, Finland
Related authors
Kalle Nordling, Nora Fahrenbach, and Bjørn Samset
EGUsphere, https://doi.org/10.5194/egusphere-2024-1068, https://doi.org/10.5194/egusphere-2024-1068, 2024
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
People experience daily weather, not changes in monthly averages. We investigate how the likelihood of events, which occurred once every ten years in the pre-industrial era. We analyze how summertime precipitation and daily maximum temperature events evolve. Our focus is on understanding the role of day-to-day variability in the change in the number of extreme weather days. We find that in most regions, a change in variability is the primary driver for change in summertime extreme precipitation.
Jaakko Ahola, Tomi Raatikainen, Muzaffer Ege Alper, Jukka-Pekka Keskinen, Harri Kokkola, Antti Kukkurainen, Antti Lipponen, Jia Liu, Kalle Nordling, Antti-Ilari Partanen, Sami Romakkaniemi, Petri Räisänen, Juha Tonttila, and Hannele Korhonen
Atmos. Chem. Phys., 22, 4523–4537, https://doi.org/10.5194/acp-22-4523-2022, https://doi.org/10.5194/acp-22-4523-2022, 2022
Short summary
Short summary
Clouds are important for the climate, and cloud droplets have a significant role in cloud properties. Cloud droplets form when air rises and cools and water vapour condenses on small particles that can be natural or of anthropogenic origin. Currently, the updraft velocity, meaning how fast the air rises, is poorly represented in global climate models. In our study, we show three methods that will improve the depiction of updraft velocity and which properties are vital to updrafts.
Kalle Nordling, Hannele Korhonen, Jouni Räisänen, Antti-Ilari Partanen, Bjørn H. Samset, and Joonas Merikanto
Atmos. Chem. Phys., 21, 14941–14958, https://doi.org/10.5194/acp-21-14941-2021, https://doi.org/10.5194/acp-21-14941-2021, 2021
Short summary
Short summary
Understanding the temperature responses to different climate forcing agents, such as greenhouse gases and aerosols, is crucial for understanding future regional climate changes. In climate models, the regional temperature responses vary for all forcing agents, but the causes of this variability are poorly understood. For all forcing agents, the main component contributing to variance in regional surface temperature responses between the climate models is the clear-sky longwave emissivity.
Joonas Merikanto, Kalle Nordling, Petri Räisänen, Jouni Räisänen, Declan O'Donnell, Antti-Ilari Partanen, and Hannele Korhonen
Atmos. Chem. Phys., 21, 5865–5881, https://doi.org/10.5194/acp-21-5865-2021, https://doi.org/10.5194/acp-21-5865-2021, 2021
Short summary
Short summary
Human-induced aerosols concentrate around their emission sources, yet their climate effects span far and wide. Here, we use two climate models to robustly identify the mechanisms of how Asian anthropogenic aerosols impact temperatures across the globe. A total removal of Asian anthropogenic aerosols increases the global temperatures by 0.26 ± 0.04 °C in the models, with the strongest warming taking place over the Arctic due to increased atmospheric transport of energy towards the high north.
Laura J. Wilcox, Zhen Liu, Bjørn H. Samset, Ed Hawkins, Marianne T. Lund, Kalle Nordling, Sabine Undorf, Massimo Bollasina, Annica M. L. Ekman, Srinath Krishnan, Joonas Merikanto, and Andrew G. Turner
Atmos. Chem. Phys., 20, 11955–11977, https://doi.org/10.5194/acp-20-11955-2020, https://doi.org/10.5194/acp-20-11955-2020, 2020
Short summary
Short summary
Projected changes in man-made aerosol range from large reductions to moderate increases in emissions until 2050. Rapid reductions between the present and the 2050s lead to enhanced increases in global and Asian summer monsoon precipitation relative to scenarios with continued increases in aerosol. Relative magnitude and spatial distribution of aerosol changes are particularly important for South Asian summer monsoon precipitation changes, affecting the sign of the trend in the coming decades.
Kalle Nordling, Hannele Korhonen, Petri Räisänen, Muzaffer Ege Alper, Petteri Uotila, Declan O'Donnell, and Joonas Merikanto
Atmos. Chem. Phys., 19, 9969–9987, https://doi.org/10.5194/acp-19-9969-2019, https://doi.org/10.5194/acp-19-9969-2019, 2019
Short summary
Short summary
We carry out long equilibrium climate simulations with two modern climate models and show that the climate model dynamic response contributes strongly to the anthropogenic aerosol response. We demonstrate that identical aerosol descriptions do not improve climate model skill to estimate regional anthropogenic aerosol impacts. Our experiment utilized two independent climate models (NorESM and ECHAM6) with an identical description for aerosols optical properties and indirect effect.
Marje Prank, Juha Tonttila, Xiaoxia Shang, Sami Romakkaniemi, and Tomi Raatikainen
EGUsphere, https://doi.org/10.5194/egusphere-2024-876, https://doi.org/10.5194/egusphere-2024-876, 2024
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
Large primary bioparticles such as pollen can be abundant in the atmosphere. In humid conditions pollens can rupture and release a large number of fine sub-pollen particles (SPPs). The paper investigates what kind of birch pollen concentrations are needed for the pollen and SPPs to start playing a noticeable role in cloud processes and alter precipitation formation. In the studied cases only the largest observed pollen concentrations were able to noticeably alter the precipitation formation.
Timo H. Virtanen, Anu-Maija Sundström, Elli Suhonen, Antti Lipponen, Antti Arola, Christopher O'Dell, Robert R. Nelson, and Hannakaisa Lindqvist
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-77, https://doi.org/10.5194/amt-2024-77, 2024
Preprint under review for AMT
Short summary
Short summary
We find that small particles suspended in the air (aerosols) affect the satellite observations of carbon dioxide (CO2) made by the Orbiting Carbon Observatory -2 satellite instrument. The satellite estimates of CO2 appear too high for clean areas and too low for polluted areas. Our results show that the CO2 and aerosols are often co-emitted, and this is partly masked out in the current retrievals. Correctly accounting for the aerosol effect is important for CO2 emission estimates by satellites.
Anton Laakso, Daniele Visioni, Ulrike Niemeier, Simone Tilmes, and Harri Kokkola
Earth Syst. Dynam., 15, 405–427, https://doi.org/10.5194/esd-15-405-2024, https://doi.org/10.5194/esd-15-405-2024, 2024
Short summary
Short summary
This study is the second in a two-part series in which we explore the dependency of the impacts of stratospheric sulfur injections on both the model employed and the strategy of injection utilized. The study uncovers uncertainties associated with these techniques to cool climate, highlighting how the simulated climate impacts are dependent on both the selected model and the magnitude of the injections. We also show that estimating precipitation impacts of aerosol injection is a complex task.
Kalle Nordling, Nora Fahrenbach, and Bjørn Samset
EGUsphere, https://doi.org/10.5194/egusphere-2024-1068, https://doi.org/10.5194/egusphere-2024-1068, 2024
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
People experience daily weather, not changes in monthly averages. We investigate how the likelihood of events, which occurred once every ten years in the pre-industrial era. We analyze how summertime precipitation and daily maximum temperature events evolve. Our focus is on understanding the role of day-to-day variability in the change in the number of extreme weather days. We find that in most regions, a change in variability is the primary driver for change in summertime extreme precipitation.
Alejandro Baró Pérez, Michael S. Diamond, Frida A.-M. Bender, Abhay Devasthale, Matthias Schwarz, Julien Savre, Juha Tonttila, Harri Kokkola, Hyunho Lee, David Painemal, and Annica M. L. Ekman
Atmos. Chem. Phys., 24, 4591–4610, https://doi.org/10.5194/acp-24-4591-2024, https://doi.org/10.5194/acp-24-4591-2024, 2024
Short summary
Short summary
We use a numerical model to study interactions between humid light-absorbing aerosol plumes, clouds, and radiation over the southeast Atlantic. We find that the warming produced by the aerosols reduces cloud cover, especially in highly polluted situations. Aerosol impacts on drizzle play a minor role. However, aerosol effects on cloud reflectivity and moisture-induced changes in cloud cover dominate the climatic response and lead to an overall cooling by the biomass burning plumes.
Chris Smith, Donald P. Cummins, Hege-Beate Fredriksen, Zebedee Nicholls, Malte Meinshausen, Myles Allen, Stuart Jenkins, Nicholas Leach, Camilla Mathison, and Antti-Ilari Partanen
EGUsphere, https://doi.org/10.5194/egusphere-2024-708, https://doi.org/10.5194/egusphere-2024-708, 2024
Short summary
Short summary
Climate projections are only useful if the underlying models that produce them are well calibrated and can reproduce observed climate change. We formalize a software package that calibrates the open-source FaIR simple climate model to full-complexity Earth System models. Observations, including historical warming, and assessments of key climate variables such as that of climate sensitivity, are used to constrain the model output.
Xiaoxia Shang, Antti Lipponen, Maria Filioglou, Anu-Maija Sundström, Mark Parrington, Virginie Buchard, Anton S. Darmenov, Ellsworth J. Welton, Eleni Marinou, Vassilis Amiridis, Michael Sicard, Alejandro Rodríguez-Gómez, Mika Komppula, and Tero Mielonen
Atmos. Chem. Phys., 24, 1329–1344, https://doi.org/10.5194/acp-24-1329-2024, https://doi.org/10.5194/acp-24-1329-2024, 2024
Short summary
Short summary
In June 2019, smoke particles from a Canadian wildfire event were transported to Europe. The long-range-transported smoke plumes were monitored with a spaceborne lidar and reanalysis models. Based on the aerosol mass concentrations estimated from the observations, the reanalysis models had difficulties in reproducing the amount and location of the smoke aerosols during the transport event. Consequently, more spaceborne lidar missions are needed for reliable monitoring of aerosol plumes.
Andrea Porcheddu, Ville Kolehmainen, Timo Lähivaara, and Antti Lipponen
EGUsphere, https://doi.org/10.5194/egusphere-2023-2635, https://doi.org/10.5194/egusphere-2023-2635, 2024
Short summary
Short summary
This study focuses on improving the accuracy of satellite-based PM2.5 retrieval, crucial for monitoring air quality and its impact on health. It employs machine learning to correct the AOD-to-PM2.5 conversion ratio using various data sources. The approach produces high-resolution PM2.5 estimates with improved accuracy. The method is flexible and can incorporate additional training data from different sources, making it a valuable tool for air quality monitoring and epidemiological studies.
Muhammed Irfan, Thomas Kühn, Taina Yli-Juuti, Anton Laakso, Eemeli Holopainen, Douglas R. Worsnop, Annele Virtanen, and Harri Kokkola
EGUsphere, https://doi.org/10.5194/egusphere-2023-2768, https://doi.org/10.5194/egusphere-2023-2768, 2023
Short summary
Short summary
The study underscores the influence of semi-volatile organic compounds on the formation of secondary organic aerosol (SOA). Our findings demonstrate their considerable impact on climate, emphasizing the necessity to improve their representation in large-scale climate models. This research provides a nuanced perspective on the challenges in modelling, emphasizing the significance of semi-volatile compounds and their volatility distribution in predicting global climate patterns.
Putian Zhou, Zhengyao Lu, Jukka-Pekka Keskinen, Qiong Zhang, Juha Lento, Jianpu Bian, Twan van Noije, Philippe Le Sager, Veli-Matti Kerminen, Markku Kulmala, Michael Boy, and Risto Makkonen
Clim. Past, 19, 2445–2462, https://doi.org/10.5194/cp-19-2445-2023, https://doi.org/10.5194/cp-19-2445-2023, 2023
Short summary
Short summary
A Green Sahara with enhanced rainfall and larger vegetation cover existed in northern Africa about 6000 years ago. Biosphere–atmosphere interactions are found to be critical to explaining this wet period. Based on modeled vegetation reconstruction data, we simulated dust emissions and aerosol formation, which are key factors in biosphere–atmosphere interactions. Our results also provide a benchmark of aerosol climatology for future paleo-climate simulation experiments.
Tuuli Miinalainen, Harri Kokkola, Antti Lipponen, Antti-Pekka Hyvärinen, Vijay Kumar Soni, Kari E. J. Lehtinen, and Thomas Kühn
Atmos. Chem. Phys., 23, 3471–3491, https://doi.org/10.5194/acp-23-3471-2023, https://doi.org/10.5194/acp-23-3471-2023, 2023
Short summary
Short summary
We simulated the effects of aerosol emission mitigation on both global and regional radiative forcing and city-level air quality with a global-scale climate model. We used a machine learning downscaling approach to bias-correct the PM2.5 values obtained from the global model for the Indian megacity New Delhi. Our results indicate that aerosol mitigation could result in both improved air quality and less radiative heating for India.
Jutta Kesti, Ewan James O'Connor, Anne Hirsikko, John Backman, Heikki Lihavainen, Hannele Korhonen, and Eija Asmi
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2022-811, https://doi.org/10.5194/acp-2022-811, 2023
Revised manuscript accepted for ACP
Short summary
Short summary
The study combines aerosol particle measurements at the surface and vertical profiling of the atmosphere with a scanning Doppler lidar to investigate how transport together with boundary layer evolution can affect particle and SO2 concentrations at the surface in the Arabian Peninsula region. The instrumentation enabled us to see elevated nucleation mode particle and SO2 concentrations at the surface when air masses transported from polluted areas are mixed in the boundary layer.
Ville Leinonen, Harri Kokkola, Taina Yli-Juuti, Tero Mielonen, Thomas Kühn, Tuomo Nieminen, Simo Heikkinen, Tuuli Miinalainen, Tommi Bergman, Ken Carslaw, Stefano Decesari, Markus Fiebig, Tareq Hussein, Niku Kivekäs, Radovan Krejci, Markku Kulmala, Ari Leskinen, Andreas Massling, Nikos Mihalopoulos, Jane P. Mulcahy, Steffen M. Noe, Twan van Noije, Fiona M. O'Connor, Colin O'Dowd, Dirk Olivie, Jakob B. Pernov, Tuukka Petäjä, Øyvind Seland, Michael Schulz, Catherine E. Scott, Henrik Skov, Erik Swietlicki, Thomas Tuch, Alfred Wiedensohler, Annele Virtanen, and Santtu Mikkonen
Atmos. Chem. Phys., 22, 12873–12905, https://doi.org/10.5194/acp-22-12873-2022, https://doi.org/10.5194/acp-22-12873-2022, 2022
Short summary
Short summary
We provide the first extensive comparison of detailed aerosol size distribution trends between in situ observations from Europe and five different earth system models. We investigated aerosol modes (nucleation, Aitken, and accumulation) separately and were able to show the differences between measured and modeled trends and especially their seasonal patterns. The differences in model results are likely due to complex effects of several processes instead of certain specific model features.
Silvia M. Calderón, Juha Tonttila, Angela Buchholz, Jorma Joutsensaari, Mika Komppula, Ari Leskinen, Liqing Hao, Dmitri Moisseev, Iida Pullinen, Petri Tiitta, Jian Xu, Annele Virtanen, Harri Kokkola, and Sami Romakkaniemi
Atmos. Chem. Phys., 22, 12417–12441, https://doi.org/10.5194/acp-22-12417-2022, https://doi.org/10.5194/acp-22-12417-2022, 2022
Short summary
Short summary
The spatial and temporal restrictions of observations and oversimplified aerosol representation in large eddy simulations (LES) limit our understanding of aerosol–stratocumulus interactions. In this closure study of in situ and remote sensing observations and outputs from UCLALES–SALSA, we have assessed the role of convective overturning and aerosol effects in two cloud events observed at the Puijo SMEAR IV station, Finland, a diurnal-high aerosol case and a nocturnal-low aerosol case.
Chao Yan, Yicheng Shen, Dominik Stolzenburg, Lubna Dada, Ximeng Qi, Simo Hakala, Anu-Maija Sundström, Yishuo Guo, Antti Lipponen, Tom V. Kokkonen, Jenni Kontkanen, Runlong Cai, Jing Cai, Tommy Chan, Liangduo Chen, Biwu Chu, Chenjuan Deng, Wei Du, Xiaolong Fan, Xu-Cheng He, Juha Kangasluoma, Joni Kujansuu, Mona Kurppa, Chang Li, Yiran Li, Zhuohui Lin, Yiliang Liu, Yuliang Liu, Yiqun Lu, Wei Nie, Jouni Pulliainen, Xiaohui Qiao, Yonghong Wang, Yifan Wen, Ye Wu, Gan Yang, Lei Yao, Rujing Yin, Gen Zhang, Shaojun Zhang, Feixue Zheng, Ying Zhou, Antti Arola, Johanna Tamminen, Pauli Paasonen, Yele Sun, Lin Wang, Neil M. Donahue, Yongchun Liu, Federico Bianchi, Kaspar R. Daellenbach, Douglas R. Worsnop, Veli-Matti Kerminen, Tuukka Petäjä, Aijun Ding, Jingkun Jiang, and Markku Kulmala
Atmos. Chem. Phys., 22, 12207–12220, https://doi.org/10.5194/acp-22-12207-2022, https://doi.org/10.5194/acp-22-12207-2022, 2022
Short summary
Short summary
Atmospheric new particle formation (NPF) is a dominant source of atmospheric ultrafine particles. In urban environments, traffic emissions are a major source of primary pollutants, but their contribution to NPF remains under debate. During the COVID-19 lockdown, traffic emissions were significantly reduced, providing a unique chance to examine their relevance to NPF. Based on our comprehensive measurements, we demonstrate that traffic emissions alone are not able to explain the NPF in Beijing.
Sini Isokääntä, Paul Kim, Santtu Mikkonen, Thomas Kühn, Harri Kokkola, Taina Yli-Juuti, Liine Heikkinen, Krista Luoma, Tuukka Petäjä, Zak Kipling, Daniel Partridge, and Annele Virtanen
Atmos. Chem. Phys., 22, 11823–11843, https://doi.org/10.5194/acp-22-11823-2022, https://doi.org/10.5194/acp-22-11823-2022, 2022
Short summary
Short summary
This research employs air mass history analysis and observations to study how clouds and precipitation affect atmospheric aerosols during transport to a boreal forest site. The mass concentrations of studied chemical species showed exponential decrease as a function of accumulated rain along the air mass route. Our analysis revealed in-cloud sulfate formation, while no major changes in organic mass were seen. Most of the in-cloud-formed sulfate could be assigned to particle sizes above 200 nm.
Petri Räisänen, Joonas Merikanto, Risto Makkonen, Mikko Savolahti, Alf Kirkevåg, Maria Sand, Øyvind Seland, and Antti-Ilari Partanen
Atmos. Chem. Phys., 22, 11579–11602, https://doi.org/10.5194/acp-22-11579-2022, https://doi.org/10.5194/acp-22-11579-2022, 2022
Short summary
Short summary
A climate model is used to evaluate how the radiative forcing (RF) associated with black carbon (BC) emissions depends on the latitude, longitude, and seasonality of emissions. It is found that both the direct RF (BC absorption of solar radiation in air) and snow RF (BC absorption in snow/ice) depend strongly on the emission region and season. The results suggest that, for a given mass of BC emitted, climatic impacts are likely to be largest for high-latitude emissions due to the large snow RF.
Qirui Zhong, Nick Schutgens, Guido van der Werf, Twan van Noije, Kostas Tsigaridis, Susanne E. Bauer, Tero Mielonen, Alf Kirkevåg, Øyvind Seland, Harri Kokkola, Ramiro Checa-Garcia, David Neubauer, Zak Kipling, Hitoshi Matsui, Paul Ginoux, Toshihiko Takemura, Philippe Le Sager, Samuel Rémy, Huisheng Bian, Mian Chin, Kai Zhang, Jialei Zhu, Svetlana G. Tsyro, Gabriele Curci, Anna Protonotariou, Ben Johnson, Joyce E. Penner, Nicolas Bellouin, Ragnhild B. Skeie, and Gunnar Myhre
Atmos. Chem. Phys., 22, 11009–11032, https://doi.org/10.5194/acp-22-11009-2022, https://doi.org/10.5194/acp-22-11009-2022, 2022
Short summary
Short summary
Aerosol optical depth (AOD) errors for biomass burning aerosol (BBA) are evaluated in 18 global models against satellite datasets. Notwithstanding biases in satellite products, they allow model evaluations. We observe large and diverse model biases due to errors in BBA. Further interpretations of AOD diversities suggest large biases exist in key processes for BBA which require better constraining. These results can contribute to further model improvement and development.
Marje Prank, Juha Tonttila, Jaakko Ahola, Harri Kokkola, Thomas Kühn, Sami Romakkaniemi, and Tomi Raatikainen
Atmos. Chem. Phys., 22, 10971–10992, https://doi.org/10.5194/acp-22-10971-2022, https://doi.org/10.5194/acp-22-10971-2022, 2022
Short summary
Short summary
Aerosols and clouds persist as the dominant sources of uncertainty in climate projections. In this modelling study, we investigate the role of marine aerosols in influencing the lifetime of low-level clouds. Our high resolution simulations show that sea spray can both extend and shorten the lifetime of the cloud layer depending on the model setup. The impact of the primary marine organics is relatively limited while secondary aerosol from monoterpenes can have larger impact.
Petri Tiitta, Ari Leskinen, Ville A. Kaikkonen, Eero O. Molkoselkä, Anssi J. Mäkynen, Jorma Joutsensaari, Silvia Calderon, Sami Romakkaniemi, and Mika Komppula
Atmos. Meas. Tech., 15, 2993–3009, https://doi.org/10.5194/amt-15-2993-2022, https://doi.org/10.5194/amt-15-2993-2022, 2022
Short summary
Short summary
The novel holographic imaging instrument (ICEMET) was adapted to measure the microphysical properties of liquid clouds, and these values were compared with parallel measurements of a cloud droplet spectrometer (FM-120) and particle measurements using a twin-inlet system. When the intercomparison was carried out during isoaxial sampling, our results showed good agreement in terms of variability between the instruments. This agreement was confirmed using Mutual and Pearson correlation analyses.
Ralf Döscher, Mario Acosta, Andrea Alessandri, Peter Anthoni, Thomas Arsouze, Tommi Bergman, Raffaele Bernardello, Souhail Boussetta, Louis-Philippe Caron, Glenn Carver, Miguel Castrillo, Franco Catalano, Ivana Cvijanovic, Paolo Davini, Evelien Dekker, Francisco J. Doblas-Reyes, David Docquier, Pablo Echevarria, Uwe Fladrich, Ramon Fuentes-Franco, Matthias Gröger, Jost v. Hardenberg, Jenny Hieronymus, M. Pasha Karami, Jukka-Pekka Keskinen, Torben Koenigk, Risto Makkonen, François Massonnet, Martin Ménégoz, Paul A. Miller, Eduardo Moreno-Chamarro, Lars Nieradzik, Twan van Noije, Paul Nolan, Declan O'Donnell, Pirkka Ollinaho, Gijs van den Oord, Pablo Ortega, Oriol Tintó Prims, Arthur Ramos, Thomas Reerink, Clement Rousset, Yohan Ruprich-Robert, Philippe Le Sager, Torben Schmith, Roland Schrödner, Federico Serva, Valentina Sicardi, Marianne Sloth Madsen, Benjamin Smith, Tian Tian, Etienne Tourigny, Petteri Uotila, Martin Vancoppenolle, Shiyu Wang, David Wårlind, Ulrika Willén, Klaus Wyser, Shuting Yang, Xavier Yepes-Arbós, and Qiong Zhang
Geosci. Model Dev., 15, 2973–3020, https://doi.org/10.5194/gmd-15-2973-2022, https://doi.org/10.5194/gmd-15-2973-2022, 2022
Short summary
Short summary
The Earth system model EC-Earth3 is documented here. Key performance metrics show physical behavior and biases well within the frame known from recent models. With improved physical and dynamic features, new ESM components, community tools, and largely improved physical performance compared to the CMIP5 version, EC-Earth3 represents a clear step forward for the only European community ESM. We demonstrate here that EC-Earth3 is suited for a range of tasks in CMIP6 and beyond.
Jaakko Ahola, Tomi Raatikainen, Muzaffer Ege Alper, Jukka-Pekka Keskinen, Harri Kokkola, Antti Kukkurainen, Antti Lipponen, Jia Liu, Kalle Nordling, Antti-Ilari Partanen, Sami Romakkaniemi, Petri Räisänen, Juha Tonttila, and Hannele Korhonen
Atmos. Chem. Phys., 22, 4523–4537, https://doi.org/10.5194/acp-22-4523-2022, https://doi.org/10.5194/acp-22-4523-2022, 2022
Short summary
Short summary
Clouds are important for the climate, and cloud droplets have a significant role in cloud properties. Cloud droplets form when air rises and cools and water vapour condenses on small particles that can be natural or of anthropogenic origin. Currently, the updraft velocity, meaning how fast the air rises, is poorly represented in global climate models. In our study, we show three methods that will improve the depiction of updraft velocity and which properties are vital to updrafts.
Tomi Raatikainen, Marje Prank, Jaakko Ahola, Harri Kokkola, Juha Tonttila, and Sami Romakkaniemi
Atmos. Chem. Phys., 22, 3763–3778, https://doi.org/10.5194/acp-22-3763-2022, https://doi.org/10.5194/acp-22-3763-2022, 2022
Short summary
Short summary
Mineral dust or similar ice-nucleating particles (INPs) are needed to initiate cloud droplet freezing at temperatures common in shallow clouds. In this work we examine how INPs that are released from the sea surface impact marine clouds. Our high-resolution simulations show that turbulent updraughts carry these particles effectively up to the clouds, where they initiate cloud droplet freezing. Sea surface INP emissions become more important with decreasing background dust INP concentrations.
Kerttu Kouki, Petri Räisänen, Kari Luojus, Anna Luomaranta, and Aku Riihelä
The Cryosphere, 16, 1007–1030, https://doi.org/10.5194/tc-16-1007-2022, https://doi.org/10.5194/tc-16-1007-2022, 2022
Short summary
Short summary
We analyze state-of-the-art climate models’ ability to describe snow mass and whether biases in modeled temperature or precipitation can explain the discrepancies in snow mass. In winter, biases in precipitation are the main factor affecting snow mass, while in spring, biases in temperature becomes more important, which is an expected result. However, temperature or precipitation cannot explain all snow mass discrepancies. Other factors, such as models’ structural errors, are also significant.
Jessica Slater, Hugh Coe, Gordon McFiggans, Juha Tonttila, and Sami Romakkaniemi
Atmos. Chem. Phys., 22, 2937–2953, https://doi.org/10.5194/acp-22-2937-2022, https://doi.org/10.5194/acp-22-2937-2022, 2022
Short summary
Short summary
This paper shows the specific impact of black carbon (BC) on the aerosol–planetary boundary layer (PBL) feedback and its influence on a Beijing haze episode. Overall, this paper shows that strong temperature inversions prevent BC heating within the PBL from significantly increasing PBL height, while BC above the PBL suppresses PBL development significantly through the day. From this we suggest a method by which both locally and regionally emitted BC may impact urban pollution episodes.
Antti Lipponen, Jaakko Reinvall, Arttu Väisänen, Henri Taskinen, Timo Lähivaara, Larisa Sogacheva, Pekka Kolmonen, Kari Lehtinen, Antti Arola, and Ville Kolehmainen
Atmos. Meas. Tech., 15, 895–914, https://doi.org/10.5194/amt-15-895-2022, https://doi.org/10.5194/amt-15-895-2022, 2022
Short summary
Short summary
We have developed a machine-learning-based model that can be used to correct the Sentinel-3 satellite-based aerosol parameter data of the Synergy data product. The strength of the model is that the original satellite data processing does not have to be carried out again but the correction can be carried out with the data already available. We show that the correction significantly improves the accuracy of the satellite aerosol parameters.
Jutta Kesti, John Backman, Ewan J. O'Connor, Anne Hirsikko, Eija Asmi, Minna Aurela, Ulla Makkonen, Maria Filioglou, Mika Komppula, Hannele Korhonen, and Heikki Lihavainen
Atmos. Chem. Phys., 22, 481–503, https://doi.org/10.5194/acp-22-481-2022, https://doi.org/10.5194/acp-22-481-2022, 2022
Short summary
Short summary
In this study we combined aerosol particle measurements at the surface with a scanning Doppler lidar providing vertical profiles of the atmosphere to study the effect of different boundary layer conditions on aerosol particle properties in the understudied Arabian Peninsula region. The instrumentation used in this study enabled us to identify periods when pollution from remote sources was mixed down to the surface and initiated new particle formation in the growing boundary layer.
Ian Boutle, Wayne Angevine, Jian-Wen Bao, Thierry Bergot, Ritthik Bhattacharya, Andreas Bott, Leo Ducongé, Richard Forbes, Tobias Goecke, Evelyn Grell, Adrian Hill, Adele L. Igel, Innocent Kudzotsa, Christine Lac, Bjorn Maronga, Sami Romakkaniemi, Juerg Schmidli, Johannes Schwenkel, Gert-Jan Steeneveld, and Benoît Vié
Atmos. Chem. Phys., 22, 319–333, https://doi.org/10.5194/acp-22-319-2022, https://doi.org/10.5194/acp-22-319-2022, 2022
Short summary
Short summary
Fog forecasting is one of the biggest problems for numerical weather prediction. By comparing many models used for fog forecasting with others used for fog research, we hoped to help guide forecast improvements. We show some key processes that, if improved, will help improve fog forecasting, such as how water is deposited on the ground. We also showed that research models were not themselves a suitable baseline for comparison, and we discuss what future observations are required to improve them.
Anton Laakso, Ulrike Niemeier, Daniele Visioni, Simone Tilmes, and Harri Kokkola
Atmos. Chem. Phys., 22, 93–118, https://doi.org/10.5194/acp-22-93-2022, https://doi.org/10.5194/acp-22-93-2022, 2022
Short summary
Short summary
The use of different spatio-temporal sulfur injection strategies with different magnitudes to create an artificial reflective aerosol layer to cool the climate is studied using sectional and modal aerosol schemes in a climate model. There are significant differences in the results depending on the aerosol microphysical module used. Different spatio-temporal injection strategies have a significant impact on the magnitude and zonal distribution of radiative forcing and atmospheric dynamics.
Maria Sand, Bjørn H. Samset, Gunnar Myhre, Jonas Gliß, Susanne E. Bauer, Huisheng Bian, Mian Chin, Ramiro Checa-Garcia, Paul Ginoux, Zak Kipling, Alf Kirkevåg, Harri Kokkola, Philippe Le Sager, Marianne T. Lund, Hitoshi Matsui, Twan van Noije, Dirk J. L. Olivié, Samuel Remy, Michael Schulz, Philip Stier, Camilla W. Stjern, Toshihiko Takemura, Kostas Tsigaridis, Svetlana G. Tsyro, and Duncan Watson-Parris
Atmos. Chem. Phys., 21, 15929–15947, https://doi.org/10.5194/acp-21-15929-2021, https://doi.org/10.5194/acp-21-15929-2021, 2021
Short summary
Short summary
Absorption of shortwave radiation by aerosols can modify precipitation and clouds but is poorly constrained in models. A total of 15 different aerosol models from AeroCom phase III have reported total aerosol absorption, and for the first time, 11 of these models have reported in a consistent experiment the contributions to absorption from black carbon, dust, and organic aerosol. Here, we document the model diversity in aerosol absorption.
Anu Kauppi, Antti Kukkurainen, Antti Lipponen, Marko Laine, Antti Arola, Hannakaisa Lindqvist, and Johanna Tamminen
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2021-328, https://doi.org/10.5194/amt-2021-328, 2021
Revised manuscript not accepted
Short summary
Short summary
We present a methodology in Bayesian framework for retrieving atmospheric aerosol optical depth and aerosol type from the pre-computed look-up tables (LUTs). Especially, we consider Bayesian model averaging and uncertainty originating from aerosol model selection and imperfect forward modelling. Our aim is to get more realistic uncertainty estimates. We have applied the methodology to TROPOMI/S5P satellite observations and evaluated the results against ground-based data from the AERONET.
Kalle Nordling, Hannele Korhonen, Jouni Räisänen, Antti-Ilari Partanen, Bjørn H. Samset, and Joonas Merikanto
Atmos. Chem. Phys., 21, 14941–14958, https://doi.org/10.5194/acp-21-14941-2021, https://doi.org/10.5194/acp-21-14941-2021, 2021
Short summary
Short summary
Understanding the temperature responses to different climate forcing agents, such as greenhouse gases and aerosols, is crucial for understanding future regional climate changes. In climate models, the regional temperature responses vary for all forcing agents, but the causes of this variability are poorly understood. For all forcing agents, the main component contributing to variance in regional surface temperature responses between the climate models is the clear-sky longwave emissivity.
Xiaoxia Shang, Tero Mielonen, Antti Lipponen, Elina Giannakaki, Ari Leskinen, Virginie Buchard, Anton S. Darmenov, Antti Kukkurainen, Antti Arola, Ewan O'Connor, Anne Hirsikko, and Mika Komppula
Atmos. Meas. Tech., 14, 6159–6179, https://doi.org/10.5194/amt-14-6159-2021, https://doi.org/10.5194/amt-14-6159-2021, 2021
Short summary
Short summary
The long-range-transported smoke particles from a Canadian wildfire event were observed with a multi-wavelength Raman polarization lidar and a ceilometer over Kuopio, Finland, in June 2019. The optical properties and the mass concentration estimations were reported for such aged smoke aerosols over northern Europe.
Twan van Noije, Tommi Bergman, Philippe Le Sager, Declan O'Donnell, Risto Makkonen, María Gonçalves-Ageitos, Ralf Döscher, Uwe Fladrich, Jost von Hardenberg, Jukka-Pekka Keskinen, Hannele Korhonen, Anton Laakso, Stelios Myriokefalitakis, Pirkka Ollinaho, Carlos Pérez García-Pando, Thomas Reerink, Roland Schrödner, Klaus Wyser, and Shuting Yang
Geosci. Model Dev., 14, 5637–5668, https://doi.org/10.5194/gmd-14-5637-2021, https://doi.org/10.5194/gmd-14-5637-2021, 2021
Short summary
Short summary
This paper documents the global climate model EC-Earth3-AerChem, one of the members of the EC-Earth3 family of models participating in CMIP6. We give an overview of the model and describe in detail how it differs from its predecessor and the other EC-Earth3 configurations. The model's performance is characterized using coupled simulations conducted for CMIP6. The model has an effective equilibrium climate sensitivity of 3.9 °C and a transient climate response of 2.1 °C.
Antti Arola, William Wandji Nyamsi, Antti Lipponen, Stelios Kazadzis, Nickolay A. Krotkov, and Johanna Tamminen
Atmos. Meas. Tech., 14, 4947–4957, https://doi.org/10.5194/amt-14-4947-2021, https://doi.org/10.5194/amt-14-4947-2021, 2021
Short summary
Short summary
Methods to estimate surface UV radiation from satellite measurements offer the only means to obtain global coverage, and the development of satellite-based UV algorithms has been ongoing since the early 1990s. One of the main challenges in this development has been how to account for the overall effect of absorption by atmospheric aerosols. One such method was suggested roughly a decade ago, and in this study we propose further improvements for this kind of approach.
Antti Lipponen, Ville Kolehmainen, Pekka Kolmonen, Antti Kukkurainen, Tero Mielonen, Neus Sabater, Larisa Sogacheva, Timo H. Virtanen, and Antti Arola
Atmos. Meas. Tech., 14, 2981–2992, https://doi.org/10.5194/amt-14-2981-2021, https://doi.org/10.5194/amt-14-2981-2021, 2021
Short summary
Short summary
We have developed a new computational method to post-process-correct the satellite aerosol retrievals. The proposed method combines the conventional satellite aerosol retrievals relying on physics-based models and machine learning. The results show significantly improved accuracy in the aerosol data over the operational satellite data products. The correction can be applied to the existing satellite aerosol datasets with no need to fully reprocess the much larger original radiance data.
Joonas Merikanto, Kalle Nordling, Petri Räisänen, Jouni Räisänen, Declan O'Donnell, Antti-Ilari Partanen, and Hannele Korhonen
Atmos. Chem. Phys., 21, 5865–5881, https://doi.org/10.5194/acp-21-5865-2021, https://doi.org/10.5194/acp-21-5865-2021, 2021
Short summary
Short summary
Human-induced aerosols concentrate around their emission sources, yet their climate effects span far and wide. Here, we use two climate models to robustly identify the mechanisms of how Asian anthropogenic aerosols impact temperatures across the globe. A total removal of Asian anthropogenic aerosols increases the global temperatures by 0.26 ± 0.04 °C in the models, with the strongest warming taking place over the Arctic due to increased atmospheric transport of energy towards the high north.
Terhikki Manninen, Kati Anttila, Emmihenna Jääskeläinen, Aku Riihelä, Jouni Peltoniemi, Petri Räisänen, Panu Lahtinen, Niilo Siljamo, Laura Thölix, Outi Meinander, Anna Kontu, Hanne Suokanerva, Roberta Pirazzini, Juha Suomalainen, Teemu Hakala, Sanna Kaasalainen, Harri Kaartinen, Antero Kukko, Olivier Hautecoeur, and Jean-Louis Roujean
The Cryosphere, 15, 793–820, https://doi.org/10.5194/tc-15-793-2021, https://doi.org/10.5194/tc-15-793-2021, 2021
Short summary
Short summary
The primary goal of this paper is to present a model of snow surface albedo (brightness) accounting for small-scale surface roughness effects. It can be combined with any volume scattering model. The results indicate that surface roughness may decrease the albedo by about 1–3 % in midwinter and even more than 10 % during the late melting season. The effect is largest for low solar zenith angle values and lower bulk snow albedo values.
Antti Ruuskanen, Sami Romakkaniemi, Harri Kokkola, Antti Arola, Santtu Mikkonen, Harri Portin, Annele Virtanen, Kari E. J. Lehtinen, Mika Komppula, and Ari Leskinen
Atmos. Chem. Phys., 21, 1683–1695, https://doi.org/10.5194/acp-21-1683-2021, https://doi.org/10.5194/acp-21-1683-2021, 2021
Short summary
Short summary
The study focuses mainly on cloud-scavenging efficiency of absorbing particulate matter (mainly black carbon) but additionally covers cloud-scavenging efficiency of scattering particles and statistics of cloud condensation nuclei. The main findings give insight into how black carbon is distributed in different particle sizes and the sensitivity to cloud scavenged. The main findings are useful for large-scale modelling for evaluating cloud scavenging.
Juha Tonttila, Ali Afzalifar, Harri Kokkola, Tomi Raatikainen, Hannele Korhonen, and Sami Romakkaniemi
Atmos. Chem. Phys., 21, 1035–1048, https://doi.org/10.5194/acp-21-1035-2021, https://doi.org/10.5194/acp-21-1035-2021, 2021
Short summary
Short summary
The focus of this study is on rain enhancement by deliberate injection of small particles into clouds (
cloud seeding). The particles, usually released from an aircraft, are expected to enhance cloud droplet growth, but its practical feasibility is somewhat uncertain. To improve upon this, we simulate the seeding effects with a numerical model. The model reproduces the main features seen in field observations, with a strong sensitivity to the total mass of the injected particle material.
Jonas Gliß, Augustin Mortier, Michael Schulz, Elisabeth Andrews, Yves Balkanski, Susanne E. Bauer, Anna M. K. Benedictow, Huisheng Bian, Ramiro Checa-Garcia, Mian Chin, Paul Ginoux, Jan J. Griesfeller, Andreas Heckel, Zak Kipling, Alf Kirkevåg, Harri Kokkola, Paolo Laj, Philippe Le Sager, Marianne Tronstad Lund, Cathrine Lund Myhre, Hitoshi Matsui, Gunnar Myhre, David Neubauer, Twan van Noije, Peter North, Dirk J. L. Olivié, Samuel Rémy, Larisa Sogacheva, Toshihiko Takemura, Kostas Tsigaridis, and Svetlana G. Tsyro
Atmos. Chem. Phys., 21, 87–128, https://doi.org/10.5194/acp-21-87-2021, https://doi.org/10.5194/acp-21-87-2021, 2021
Short summary
Short summary
Simulated aerosol optical properties as well as the aerosol life cycle are investigated for 14 global models participating in the AeroCom initiative. Considerable diversity is found in the simulated aerosol species emissions and lifetimes, also resulting in a large diversity in the simulated aerosol mass, composition, and optical properties. A comparison with observations suggests that, on average, current models underestimate the direct effect of aerosol on the atmosphere radiation budget.
Xiaoxia Shang, Elina Giannakaki, Stephanie Bohlmann, Maria Filioglou, Annika Saarto, Antti Ruuskanen, Ari Leskinen, Sami Romakkaniemi, and Mika Komppula
Atmos. Chem. Phys., 20, 15323–15339, https://doi.org/10.5194/acp-20-15323-2020, https://doi.org/10.5194/acp-20-15323-2020, 2020
Short summary
Short summary
Measurements of the multi-wavelength Raman polarization lidar PollyXT have been combined with measurements of pollen type and concentration using a traditional pollen sampler at a rural forest site in Kuopio, Finland. The depolarization ratio was enhanced when there were pollen grains in the atmosphere, illustrating the potential of lidar to track pollen grains in the atmosphere. The depolarization ratio of pure pollen particles was assessed for birch and pine pollen using a novel algorithm.
Eemeli Holopainen, Harri Kokkola, Anton Laakso, and Thomas Kühn
Geosci. Model Dev., 13, 6215–6235, https://doi.org/10.5194/gmd-13-6215-2020, https://doi.org/10.5194/gmd-13-6215-2020, 2020
Short summary
Short summary
This paper introduces an in-cloud wet deposition scheme for liquid and ice phase clouds for global aerosol–climate models. With the default setup, our wet deposition scheme behaves spuriously and better representation can be achieved with this scheme when black carbon is mixed with soluble compounds at emission time. This work is done as many of the global models fail to reproduce the transport of black carbon to the Arctic, which may be due to the poor representation of wet removal in models.
Johannes Quaas, Antti Arola, Brian Cairns, Matthew Christensen, Hartwig Deneke, Annica M. L. Ekman, Graham Feingold, Ann Fridlind, Edward Gryspeerdt, Otto Hasekamp, Zhanqing Li, Antti Lipponen, Po-Lun Ma, Johannes Mülmenstädt, Athanasios Nenes, Joyce E. Penner, Daniel Rosenfeld, Roland Schrödner, Kenneth Sinclair, Odran Sourdeval, Philip Stier, Matthias Tesche, Bastiaan van Diedenhoven, and Manfred Wendisch
Atmos. Chem. Phys., 20, 15079–15099, https://doi.org/10.5194/acp-20-15079-2020, https://doi.org/10.5194/acp-20-15079-2020, 2020
Short summary
Short summary
Anthropogenic pollution particles – aerosols – serve as cloud condensation nuclei and thus increase cloud droplet concentration and the clouds' reflection of sunlight (a cooling effect on climate). This Twomey effect is poorly constrained by models and requires satellite data for better quantification. The review summarizes the challenges in properly doing so and outlines avenues for progress towards a better use of aerosol retrievals and better retrievals of droplet concentrations.
Philip Goodwin, Martin Leduc, Antti-Ilari Partanen, H. Damon Matthews, and Alex Rogers
Geosci. Model Dev., 13, 5389–5399, https://doi.org/10.5194/gmd-13-5389-2020, https://doi.org/10.5194/gmd-13-5389-2020, 2020
Short summary
Short summary
Numerical climate models are used to make projections of future surface warming for different pathways of future greenhouse gas emissions, where future surface warming will vary from place to place. However, it is so expensive to run complex models using supercomputers that future projections can only be produced for a small number of possible future emissions pathways. This study presents an efficient climate model to make projections of local surface warming using a desktop computer.
Nick Schutgens, Andrew M. Sayer, Andreas Heckel, Christina Hsu, Hiren Jethva, Gerrit de Leeuw, Peter J. T. Leonard, Robert C. Levy, Antti Lipponen, Alexei Lyapustin, Peter North, Thomas Popp, Caroline Poulsen, Virginia Sawyer, Larisa Sogacheva, Gareth Thomas, Omar Torres, Yujie Wang, Stefan Kinne, Michael Schulz, and Philip Stier
Atmos. Chem. Phys., 20, 12431–12457, https://doi.org/10.5194/acp-20-12431-2020, https://doi.org/10.5194/acp-20-12431-2020, 2020
Short summary
Short summary
We intercompare 14 different datasets of satellite observations of aerosol. Such measurements are challenging but also provide the best opportunity to globally observe an atmospheric component strongly related to air pollution and climate change. Our study shows that most datasets perform similarly well on a global scale but that locally errors can be quite different. We develop a technique to estimate satellite errors everywhere, even in the absence of surface reference data.
Laura J. Wilcox, Zhen Liu, Bjørn H. Samset, Ed Hawkins, Marianne T. Lund, Kalle Nordling, Sabine Undorf, Massimo Bollasina, Annica M. L. Ekman, Srinath Krishnan, Joonas Merikanto, and Andrew G. Turner
Atmos. Chem. Phys., 20, 11955–11977, https://doi.org/10.5194/acp-20-11955-2020, https://doi.org/10.5194/acp-20-11955-2020, 2020
Short summary
Short summary
Projected changes in man-made aerosol range from large reductions to moderate increases in emissions until 2050. Rapid reductions between the present and the 2050s lead to enhanced increases in global and Asian summer monsoon precipitation relative to scenarios with continued increases in aerosol. Relative magnitude and spatial distribution of aerosol changes are particularly important for South Asian summer monsoon precipitation changes, affecting the sign of the trend in the coming decades.
Jessica Slater, Juha Tonttila, Gordon McFiggans, Paul Connolly, Sami Romakkaniemi, Thomas Kühn, and Hugh Coe
Atmos. Chem. Phys., 20, 11893–11906, https://doi.org/10.5194/acp-20-11893-2020, https://doi.org/10.5194/acp-20-11893-2020, 2020
Short summary
Short summary
The feedback effect between aerosol particles, radiation and meteorology reduces turbulent motion and results in increased surface aerosol concentrations during Beijing haze. Observational analysis and regional modelling studies have examined the feedback effect but these studies are limited. In this work, we set up a high-resolution model for the Beijing environment to examine the sensitivity of the aerosol feedback effect to initial meteorological conditions and aerosol loading.
Jaakko Ahola, Hannele Korhonen, Juha Tonttila, Sami Romakkaniemi, Harri Kokkola, and Tomi Raatikainen
Atmos. Chem. Phys., 20, 11639–11654, https://doi.org/10.5194/acp-20-11639-2020, https://doi.org/10.5194/acp-20-11639-2020, 2020
Short summary
Short summary
In this study, we present an improved cloud model that reproduces the behaviour of mixed-phase clouds containing liquid droplets and ice crystals in more detail than before. This model is a convenient computational tool that enables the study of phenomena that cannot fit into a laboratory. These clouds have a significant role in climate, but they are not yet properly understood. Here, we show the advantages of the new model in a case study focusing on Arctic mixed-phase clouds.
Konstantinos-Matthaios Doulgeris, Mika Komppula, Sami Romakkaniemi, Antti-Pekka Hyvärinen, Veli-Matti Kerminen, and David Brus
Atmos. Meas. Tech., 13, 5129–5147, https://doi.org/10.5194/amt-13-5129-2020, https://doi.org/10.5194/amt-13-5129-2020, 2020
Short summary
Short summary
We intercompared three cloud spectrometers ground setups in conditions with frequently occurring supercooled clouds. The measurements were conducted during the Pallas Cloud Experiment (PaCE) in 2013, in the Finnish sub-Arctic region at Sammaltunturi station. The main meteorological parameters influencing the spectrometers' performance was the wind direction. Final recommendations and our view on the main limitations of each spectrometer ground setup are presented.
Innocent Kudzotsa, Harri Kokkola, Juha Tonttila, Tomi Raatikainen, and Sami Romakkaniemi
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-851, https://doi.org/10.5194/acp-2020-851, 2020
Publication in ACP not foreseen
María A. Burgos, Elisabeth Andrews, Gloria Titos, Angela Benedetti, Huisheng Bian, Virginie Buchard, Gabriele Curci, Zak Kipling, Alf Kirkevåg, Harri Kokkola, Anton Laakso, Julie Letertre-Danczak, Marianne T. Lund, Hitoshi Matsui, Gunnar Myhre, Cynthia Randles, Michael Schulz, Twan van Noije, Kai Zhang, Lucas Alados-Arboledas, Urs Baltensperger, Anne Jefferson, James Sherman, Junying Sun, Ernest Weingartner, and Paul Zieger
Atmos. Chem. Phys., 20, 10231–10258, https://doi.org/10.5194/acp-20-10231-2020, https://doi.org/10.5194/acp-20-10231-2020, 2020
Short summary
Short summary
We investigate how well models represent the enhancement in scattering coefficients due to particle water uptake, and perform an evaluation of several implementation schemes used in ten Earth system models. Our results show the importance of the parameterization of hygroscopicity and model chemistry as drivers of some of the observed diversity amongst model estimates. The definition of dry conditions and the phenomena taking place in this relative humidity range also impact the model evaluation.
Maria Filioglou, Elina Giannakaki, John Backman, Jutta Kesti, Anne Hirsikko, Ronny Engelmann, Ewan O'Connor, Jari T. T. Leskinen, Xiaoxia Shang, Hannele Korhonen, Heikki Lihavainen, Sami Romakkaniemi, and Mika Komppula
Atmos. Chem. Phys., 20, 8909–8922, https://doi.org/10.5194/acp-20-8909-2020, https://doi.org/10.5194/acp-20-8909-2020, 2020
Short summary
Short summary
Dust optical properties are region-dependent. Saharan, Asian, and Arabian dusts do not pose similar optical properties in terms of lidar ratios; thus, a universal lidar ratio for dust particles will lead to biases. The present study analyses observations over the United Arab Emirates, quantifying the optical and geometrical extents of the aerosol layers in the area, providing at the same time the Arabian dust properties along with chemical analysis of dust samples collected in the region.
William Wandji Nyamsi, Antti Lipponen, Arturo Sanchez-Lorenzo, Martin Wild, and Antti Arola
Atmos. Meas. Tech., 13, 3061–3079, https://doi.org/10.5194/amt-13-3061-2020, https://doi.org/10.5194/amt-13-3061-2020, 2020
Short summary
Short summary
This paper proposes a novel and accurate method for estimating and reconstructing aerosol optical depth from sunshine duration measurements under cloud-free conditions at any place and time since the late 19th century. The method performs very well when compared to AErosol RObotic NETwork measurements and operates an efficient detection of signals from massive volcanic eruptions. Reconstructed long-term aerosol optical depths are in agreement with the dimming/brightening phenomenon.
Anton Laakso, Peter K. Snyder, Stefan Liess, Antti-Ilari Partanen, and Dylan B. Millet
Earth Syst. Dynam., 11, 415–434, https://doi.org/10.5194/esd-11-415-2020, https://doi.org/10.5194/esd-11-415-2020, 2020
Short summary
Short summary
Geoengineering techniques have been proposed to prevent climate warming in the event of insufficient greenhouse gas emission reductions. Simultaneously, these techniques have an impact on precipitation, which depends on the techniques used, geoengineering magnitude, and background circumstances. We separated the independent and dependent components of precipitation responses to temperature, which were then used to explain the precipitation changes in the studied climate model simulations.
Thomas Kühn, Kaarle Kupiainen, Tuuli Miinalainen, Harri Kokkola, Ville-Veikko Paunu, Anton Laakso, Juha Tonttila, Rita Van Dingenen, Kati Kulovesi, Niko Karvosenoja, and Kari E. J. Lehtinen
Atmos. Chem. Phys., 20, 5527–5546, https://doi.org/10.5194/acp-20-5527-2020, https://doi.org/10.5194/acp-20-5527-2020, 2020
Short summary
Short summary
We investigate the effects of black carbon (BC) mitigation on Arctic climate and human health, accounting for the concurrent reduction of other aerosol species. While BC is attributed a net warming effect on climate, most other aerosol species cool the planet. We find that the direct radiative effect of mitigating BC induces cooling, while aerosol–cloud effects offset this cooling and introduce large uncertainties. Furthermore, the reduced aerosol emissions reduce human mortality considerably.
Giulia Saponaro, Moa K. Sporre, David Neubauer, Harri Kokkola, Pekka Kolmonen, Larisa Sogacheva, Antti Arola, Gerrit de Leeuw, Inger H. H. Karset, Ari Laaksonen, and Ulrike Lohmann
Atmos. Chem. Phys., 20, 1607–1626, https://doi.org/10.5194/acp-20-1607-2020, https://doi.org/10.5194/acp-20-1607-2020, 2020
Short summary
Short summary
The understanding of cloud processes is based on the quality of the representation of cloud properties. We compared cloud parameters from three models with satellite observations. We report on the performance of each data source, highlighting strengths and deficiencies, which should be considered when deriving the effect of aerosols on cloud properties.
Andrew M. Sayer, Yves Govaerts, Pekka Kolmonen, Antti Lipponen, Marta Luffarelli, Tero Mielonen, Falguni Patadia, Thomas Popp, Adam C. Povey, Kerstin Stebel, and Marcin L. Witek
Atmos. Meas. Tech., 13, 373–404, https://doi.org/10.5194/amt-13-373-2020, https://doi.org/10.5194/amt-13-373-2020, 2020
Short summary
Short summary
Satellite measurements of the Earth are routinely processed to estimate useful quantities; one example is the amount of atmospheric aerosols (which are particles such as mineral dust, smoke, volcanic ash, or sea spray). As with all measurements and inferred quantities, there is some degree of uncertainty in this process.
There are various methods to estimate these uncertainties. A related question is the following: how reliable are these estimates? This paper presents a method to assess them.
Stephanie Bohlmann, Xiaoxia Shang, Elina Giannakaki, Maria Filioglou, Annika Saarto, Sami Romakkaniemi, and Mika Komppula
Atmos. Chem. Phys., 19, 14559–14569, https://doi.org/10.5194/acp-19-14559-2019, https://doi.org/10.5194/acp-19-14559-2019, 2019
Short summary
Short summary
Measurements of the multiwavelength Raman polarization lidar PollyXT have been combined with measurements of pollen type and concentration using a traditional pollen sampler at the rural forest site in Vehmasmäki, Finland. High particle depolarization ratios were observed during an intense pollination event of birch pollen occasionally mixed with spruce pollen. Our observations illustrate the potential of the particle depolarization ratio to track pollen grains in the atmosphere.
Santtu Mikkonen, Mikko R. A. Pitkänen, Tuomo Nieminen, Antti Lipponen, Sini Isokääntä, Antti Arola, and Kari E. J. Lehtinen
Atmos. Chem. Phys., 19, 12531–12543, https://doi.org/10.5194/acp-19-12531-2019, https://doi.org/10.5194/acp-19-12531-2019, 2019
Short summary
Short summary
Atmospheric measurement data never come without measurement error. Too often, these errors are neglected when researchers make inferences from their data. We applied multiple line-fitting methods to simulated data mimicking two central variables in aerosol research. Our results show that an ordinary least squares fit, typically used to describe relationships, underestimates the slope of the fit and that methods taking the measurement uncertainty into account performed significantly better.
David Neubauer, Sylvaine Ferrachat, Colombe Siegenthaler-Le Drian, Philip Stier, Daniel G. Partridge, Ina Tegen, Isabelle Bey, Tanja Stanelle, Harri Kokkola, and Ulrike Lohmann
Geosci. Model Dev., 12, 3609–3639, https://doi.org/10.5194/gmd-12-3609-2019, https://doi.org/10.5194/gmd-12-3609-2019, 2019
Short summary
Short summary
The global aerosol–climate model ECHAM6.3–HAM2.3 as well as the previous model versions ECHAM5.5–HAM2.0 and ECHAM6.1–HAM2.2 are evaluated. The simulation of clouds has improved in ECHAM6.3–HAM2.3. This has an impact on effective radiative forcing due to aerosol–radiation and aerosol–cloud interactions and equilibrium climate sensitivity, which are weaker in ECHAM6.3–HAM2.3 than in the previous model versions.
Emilio Cuevas, Pedro Miguel Romero-Campos, Natalia Kouremeti, Stelios Kazadzis, Petri Räisänen, Rosa Delia García, Africa Barreto, Carmen Guirado-Fuentes, Ramón Ramos, Carlos Toledano, Fernando Almansa, and Julian Gröbner
Atmos. Meas. Tech., 12, 4309–4337, https://doi.org/10.5194/amt-12-4309-2019, https://doi.org/10.5194/amt-12-4309-2019, 2019
Short summary
Short summary
A comprehensive comparison of more than 70 000 synchronous 1 min aerosol optical depth (AOD) data from 3 Global Atmosphere Watch precision filter radiometers (GAW-PFR) and 15 Aerosol Robotic Network Cimel radiometers (AERONET-Cimel) was performed for the four
nearwavelengths (380, 440, 500 and 870 nm) in the period 2005–2015. The goal of this study is to assess whether their long term AOD data are comparable and consistent.
Kalle Nordling, Hannele Korhonen, Petri Räisänen, Muzaffer Ege Alper, Petteri Uotila, Declan O'Donnell, and Joonas Merikanto
Atmos. Chem. Phys., 19, 9969–9987, https://doi.org/10.5194/acp-19-9969-2019, https://doi.org/10.5194/acp-19-9969-2019, 2019
Short summary
Short summary
We carry out long equilibrium climate simulations with two modern climate models and show that the climate model dynamic response contributes strongly to the anthropogenic aerosol response. We demonstrate that identical aerosol descriptions do not improve climate model skill to estimate regional anthropogenic aerosol impacts. Our experiment utilized two independent climate models (NorESM and ECHAM6) with an identical description for aerosols optical properties and indirect effect.
Erika Toivonen, Marjo Hippi, Hannele Korhonen, Ari Laaksonen, Markku Kangas, and Joni-Pekka Pietikäinen
Geosci. Model Dev., 12, 3481–3501, https://doi.org/10.5194/gmd-12-3481-2019, https://doi.org/10.5194/gmd-12-3481-2019, 2019
Short summary
Short summary
We evaluated the skill of the road weather model RoadSurf to reproduce present-day road weather conditions in Finland when driven by a high-resolution regional climate model. Simulated road surface temperatures and conditions were compared to observations between 2002 and 2014 at 25 Finnish road weather stations. RoadSurf accurately captured the main characteristics of road weather conditions. Thus, this model can be used to study the future scenarios of road weather in the study area.
Olli-Pekka Tikkanen, Väinö Hämäläinen, Grazia Rovelli, Antti Lipponen, Manabu Shiraiwa, Jonathan P. Reid, Kari E. J. Lehtinen, and Taina Yli-Juuti
Atmos. Chem. Phys., 19, 9333–9350, https://doi.org/10.5194/acp-19-9333-2019, https://doi.org/10.5194/acp-19-9333-2019, 2019
Short summary
Short summary
We assessed how well the organic aerosol particle composition and viscosity can be captured by optimizing process models to match particle evaporation data. We performed the analysis for both artificial and real evaporation data and tested two optimization algorithms. Our findings show that the optimization method yields a good estimate for the studied properties. The timescale of the evaporation data and particle size was found to be important in identifying the volatility of organic compounds.
Stephanie Fiedler, Stefan Kinne, Wan Ting Katty Huang, Petri Räisänen, Declan O'Donnell, Nicolas Bellouin, Philip Stier, Joonas Merikanto, Twan van Noije, Risto Makkonen, and Ulrike Lohmann
Atmos. Chem. Phys., 19, 6821–6841, https://doi.org/10.5194/acp-19-6821-2019, https://doi.org/10.5194/acp-19-6821-2019, 2019
Ina Tegen, David Neubauer, Sylvaine Ferrachat, Colombe Siegenthaler-Le Drian, Isabelle Bey, Nick Schutgens, Philip Stier, Duncan Watson-Parris, Tanja Stanelle, Hauke Schmidt, Sebastian Rast, Harri Kokkola, Martin Schultz, Sabine Schroeder, Nikos Daskalakis, Stefan Barthel, Bernd Heinold, and Ulrike Lohmann
Geosci. Model Dev., 12, 1643–1677, https://doi.org/10.5194/gmd-12-1643-2019, https://doi.org/10.5194/gmd-12-1643-2019, 2019
Short summary
Short summary
We describe a new version of the aerosol–climate model ECHAM–HAM and show tests of the model performance by comparing different aspects of the aerosol distribution with different datasets. The updated version of HAM contains improved descriptions of aerosol processes, including updated emission fields and cloud processes. While there are regional deviations between the model and observations, the model performs well overall.
Mona Kurppa, Antti Hellsten, Pontus Roldin, Harri Kokkola, Juha Tonttila, Mikko Auvinen, Christoph Kent, Prashant Kumar, Björn Maronga, and Leena Järvi
Geosci. Model Dev., 12, 1403–1422, https://doi.org/10.5194/gmd-12-1403-2019, https://doi.org/10.5194/gmd-12-1403-2019, 2019
Short summary
Short summary
This paper describes the implementation of a sectional aerosol module, SALSA, into the PALM model system 6.0. The first evaluation study shows excellent agreements with measurements. Furthermore, we show that ignoring the dry deposition of aerosol particles can overestimate aerosol number concentrations by 20 %, whereas condensation and dissolutional growth increase the total aerosol mass by over 10 % in this specific urban environment.
Harri Kokkola, Thomas Kühn, Anton Laakso, Tommi Bergman, Kari E. J. Lehtinen, Tero Mielonen, Antti Arola, Scarlet Stadtler, Hannele Korhonen, Sylvaine Ferrachat, Ulrike Lohmann, David Neubauer, Ina Tegen, Colombe Siegenthaler-Le Drian, Martin G. Schultz, Isabelle Bey, Philip Stier, Nikos Daskalakis, Colette L. Heald, and Sami Romakkaniemi
Geosci. Model Dev., 11, 3833–3863, https://doi.org/10.5194/gmd-11-3833-2018, https://doi.org/10.5194/gmd-11-3833-2018, 2018
Short summary
Short summary
In this paper we present a global aerosol–chemistry–climate model with the focus on its representation for atmospheric aerosol particles. In the model, aerosols are simulated using the aerosol module SALSA2.0, which in this paper is compared to satellite, ground, and aircraft-based observations of the properties of atmospheric aerosol. Based on this study, the model simulated aerosol properties compare well with the observations.
Scarlet Stadtler, Thomas Kühn, Sabine Schröder, Domenico Taraborrelli, Martin G. Schultz, and Harri Kokkola
Geosci. Model Dev., 11, 3235–3260, https://doi.org/10.5194/gmd-11-3235-2018, https://doi.org/10.5194/gmd-11-3235-2018, 2018
Short summary
Short summary
Atmospheric aerosols interact with our climate system and have adverse health effects. Nevertheless, these particles are a source of uncertainty in climate projections and the formation process of secondary aerosols formed by organic gas-phase precursors is particularly not fully understood. In order to gain a deeper understanding of secondary organic aerosol formation, this model system explicitly represents gas-phase and aerosol formation processes. Finally, this allows for process discussion.
Robin G. Stevens, Katharina Loewe, Christopher Dearden, Antonios Dimitrelos, Anna Possner, Gesa K. Eirund, Tomi Raatikainen, Adrian A. Hill, Benjamin J. Shipway, Jonathan Wilkinson, Sami Romakkaniemi, Juha Tonttila, Ari Laaksonen, Hannele Korhonen, Paul Connolly, Ulrike Lohmann, Corinna Hoose, Annica M. L. Ekman, Ken S. Carslaw, and Paul R. Field
Atmos. Chem. Phys., 18, 11041–11071, https://doi.org/10.5194/acp-18-11041-2018, https://doi.org/10.5194/acp-18-11041-2018, 2018
Short summary
Short summary
We perform a model intercomparison of summertime high Arctic clouds. Observed concentrations of aerosol particles necessary for cloud formation fell to extremely low values, coincident with a transition from cloudy to nearly cloud-free conditions. Previous analyses have suggested that at these low concentrations, the radiative properties of the clouds are determined primarily by these particle concentrations. The model results strongly support this hypothesis.
Ian Boutle, Jeremy Price, Innocent Kudzotsa, Harri Kokkola, and Sami Romakkaniemi
Atmos. Chem. Phys., 18, 7827–7840, https://doi.org/10.5194/acp-18-7827-2018, https://doi.org/10.5194/acp-18-7827-2018, 2018
Short summary
Short summary
Aerosol processes are a key mechanism in the development of fog. Poor representation of aerosol–fog interaction can result in large biases in fog forecasts, such as surface temperatures which are too high and fog which is too deep and long lived. A relatively simple representation of aerosol–fog interaction can actually lead to significant improvements in forecasting. Aerosol–fog interaction can have a large effect on the climate system but is poorly represented in climate models.
Martin G. Schultz, Scarlet Stadtler, Sabine Schröder, Domenico Taraborrelli, Bruno Franco, Jonathan Krefting, Alexandra Henrot, Sylvaine Ferrachat, Ulrike Lohmann, David Neubauer, Colombe Siegenthaler-Le Drian, Sebastian Wahl, Harri Kokkola, Thomas Kühn, Sebastian Rast, Hauke Schmidt, Philip Stier, Doug Kinnison, Geoffrey S. Tyndall, John J. Orlando, and Catherine Wespes
Geosci. Model Dev., 11, 1695–1723, https://doi.org/10.5194/gmd-11-1695-2018, https://doi.org/10.5194/gmd-11-1695-2018, 2018
Short summary
Short summary
The chemistry–climate model ECHAM-HAMMOZ contains a detailed representation of tropospheric and stratospheric reactive chemistry and state-of-the-art parameterizations of aerosols. It thus allows for detailed investigations of chemical processes in the climate system. Evaluation of the model with various observational data yields good results, but the model has a tendency to produce too much OH in the tropics. This highlights the important interplay between atmospheric chemistry and dynamics.
Joni-Pekka Pietikäinen, Tiina Markkanen, Kevin Sieck, Daniela Jacob, Johanna Korhonen, Petri Räisänen, Yao Gao, Jaakko Ahola, Hannele Korhonen, Ari Laaksonen, and Jussi Kaurola
Geosci. Model Dev., 11, 1321–1342, https://doi.org/10.5194/gmd-11-1321-2018, https://doi.org/10.5194/gmd-11-1321-2018, 2018
Short summary
Short summary
The regional climate model REMO was coupled with the FLake lake model to include an interactive treatment of lakes. Using this new version, the Fenno-Scandinavian climate and lake characteristics were studied. Our results show that overall the new model version improves the representation of the Fenno-Scandinavian climate in terms of 2 m temperature and precipitation and that the model can reproduce surface water temperature, ice depth and ice season length with reasonably high accuracy.
Antti Lipponen, Tero Mielonen, Mikko R. A. Pitkänen, Robert C. Levy, Virginia R. Sawyer, Sami Romakkaniemi, Ville Kolehmainen, and Antti Arola
Atmos. Meas. Tech., 11, 1529–1547, https://doi.org/10.5194/amt-11-1529-2018, https://doi.org/10.5194/amt-11-1529-2018, 2018
Short summary
Short summary
Atmospheric aerosols are small solid or liquid particles suspended in the atmosphere and they have a significant effect on the climate. Satellite data are used to get global estimates of atmospheric aerosols. In this work, a statistics-based Bayesian aerosol retrieval algorithm was developed to improve the accuracy and quantify the uncertainties related to the aerosol estimates. The algorithm is tested with NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data.
Lukas Pichelstorfer, Dominik Stolzenburg, John Ortega, Thomas Karl, Harri Kokkola, Anton Laakso, Kari E. J. Lehtinen, James N. Smith, Peter H. McMurry, and Paul M. Winkler
Atmos. Chem. Phys., 18, 1307–1323, https://doi.org/10.5194/acp-18-1307-2018, https://doi.org/10.5194/acp-18-1307-2018, 2018
Short summary
Short summary
Quantification of new particle formation as a source of atmospheric aerosol is clearly of importance for climate and health aspects. In our new study we developed two analysis methods that allow retrieval of nanoparticle growth dynamics at much higher precision than it was possible so far. Our results clearly demonstrate that growth rates show much more variation than is currently known and suggest that the Kelvin effect governs growth in the sub-10 nm size range.
Petri Räisänen, Risto Makkonen, Alf Kirkevåg, and Jens B. Debernard
The Cryosphere, 11, 2919–2942, https://doi.org/10.5194/tc-11-2919-2017, https://doi.org/10.5194/tc-11-2919-2017, 2017
Short summary
Short summary
While snow grains are non-spherical, spheres are often assumed in radiation calculations. Here, we replace spherical snow grains with non-spherical snow grains in a climate model. This leads to a somewhat higher snow albedo (by 0.02–0.03), increased snow and sea ice cover, and a distinctly colder climate (by over 1 K in the global mean). It also impacts the radiative effects of aerosols in snow. Overall, this work highlights the important role of snow albedo parameterization for climate models.
Maria Filioglou, Anna Nikandrova, Sami Niemelä, Holger Baars, Tero Mielonen, Ari Leskinen, David Brus, Sami Romakkaniemi, Elina Giannakaki, and Mika Komppula
Atmos. Meas. Tech., 10, 4303–4316, https://doi.org/10.5194/amt-10-4303-2017, https://doi.org/10.5194/amt-10-4303-2017, 2017
Laura Rontu, Emily Gleeson, Petri Räisänen, Kristian Pagh Nielsen, Hannu Savijärvi, and Bent Hansen Sass
Adv. Sci. Res., 14, 195–215, https://doi.org/10.5194/asr-14-195-2017, https://doi.org/10.5194/asr-14-195-2017, 2017
Short summary
Short summary
This paper provides an overview of the HLRADIA shortwave (SW) and longwave (LW) broadband radiation schemes used in the HIRLAM numerical weather prediction (NWP) model and available in the HARMONIE-AROME mesoscale NWP model. The advantage of broadband, over spectral, schemes is that they can be called more frequently within the NWP model, without compromising on computational efficiency. Fast physically based radiation parametrizations are also valuable for high-resolution ensemble forecasting.
Sami Romakkaniemi, Zubair Maalick, Antti Hellsten, Antti Ruuskanen, Olli Väisänen, Irshad Ahmad, Juha Tonttila, Santtu Mikkonen, Mika Komppula, and Thomas Kühn
Atmos. Chem. Phys., 17, 7955–7964, https://doi.org/10.5194/acp-17-7955-2017, https://doi.org/10.5194/acp-17-7955-2017, 2017
Short summary
Short summary
Surface topography affects aerosol–cloud interactions in boundary layer clouds. Local topography effects should be screened out from in situ observations before results can be generalised into a larger scale. Here we present modelling and observational results from a measurement station residing in a 75 m tower on top of a 150 m hill, and analyse how landscape affects the cloud formation, and which factors should be taken into account when aerosol effect on cloud droplet formation is studied.
Anton Laakso, Hannele Korhonen, Sami Romakkaniemi, and Harri Kokkola
Atmos. Chem. Phys., 17, 6957–6974, https://doi.org/10.5194/acp-17-6957-2017, https://doi.org/10.5194/acp-17-6957-2017, 2017
Short summary
Short summary
Based on simulations, equatorial stratospheric sulfur injections have shown to be an efficient strategy to counteract ongoing global warming. However, equatorial injections would result in relatively larger cooling in low latitudes than in high latitudes. This together with greenhouse-gas-induced warming would lead to cooling in the Equator and warming in the high latitudes. Results of this study show that a more optimal cooling effect is achieved by varying the injection area seasonally.
Päivi Haapanala, Petri Räisänen, Greg M. McFarquhar, Jussi Tiira, Andreas Macke, Michael Kahnert, John DeVore, and Timo Nousiainen
Atmos. Chem. Phys., 17, 6865–6882, https://doi.org/10.5194/acp-17-6865-2017, https://doi.org/10.5194/acp-17-6865-2017, 2017
Short summary
Short summary
The dependence of solar-disk and circumsolar radiances on ice cloud
properties is studied with a Monte Carlo radiative transfer model. Ice
crystal roughness (or more generally, non-ideality) is found to be the
most important parameter influencing the circumsolar radiance, and ice
crystal sizes and shapes also play significant roles. When comparing
with radiances measured with the SAM instrument, rough ice crystals
reproduce the measurements better than idealized smooth ice crystals do.
Antti Arola, Thomas F. Eck, Harri Kokkola, Mikko R. A. Pitkänen, and Sami Romakkaniemi
Atmos. Chem. Phys., 17, 5991–6001, https://doi.org/10.5194/acp-17-5991-2017, https://doi.org/10.5194/acp-17-5991-2017, 2017
Short summary
Short summary
One of the issues that hinder the measurement-based assessment of aerosol–cloud interactions by remote sensing methods is that typically aerosols and clouds cannot be measured simultaneously by passive remote sensing methods. AERONET includes the SDA product that provides the fine-mode AOD also in mixed cloud–aerosol observations. These measurements have not yet been fully exploited in studies of aerosol–cloud interactions. We applied SDA for this kind of analysis.
Juha Tonttila, Zubair Maalick, Tomi Raatikainen, Harri Kokkola, Thomas Kühn, and Sami Romakkaniemi
Geosci. Model Dev., 10, 169–188, https://doi.org/10.5194/gmd-10-169-2017, https://doi.org/10.5194/gmd-10-169-2017, 2017
Short summary
Short summary
Novel techniques for modelling the aerosol–cloud interactions are implemented in a cloud-resolving model. The new methods improve the representation of the poorly constrained effects of cloud processing, precipitation and the wet removal of particles on the aerosol population and the associated feedbacks. The detailed representation of these processes yields more realistic simulation of the evolution of boundary layer clouds and fogs, as compared to results obtained using more simple methods.
Tomi Raatikainen, David Brus, Rakesh K. Hooda, Antti-Pekka Hyvärinen, Eija Asmi, Ved P. Sharma, Antti Arola, and Heikki Lihavainen
Atmos. Chem. Phys., 17, 371–383, https://doi.org/10.5194/acp-17-371-2017, https://doi.org/10.5194/acp-17-371-2017, 2017
Short summary
Short summary
We have measured black carbon aerosol properties in northern India at two sites: the first site is located at the polluted Indo-Gangetic Plain, while the second site is at the Himalayan foothills in a significantly cleaner environment. The observations show a clear difference in black carbon concentrations, but individual aerosol particles seem to be similar in both sites. Indirect evidence suggests that the particles are highly irregular resembling freshly emitted soot.
Olli Väisänen, Antti Ruuskanen, Arttu Ylisirniö, Pasi Miettinen, Harri Portin, Liqing Hao, Ari Leskinen, Mika Komppula, Sami Romakkaniemi, Kari E. J. Lehtinen, and Annele Virtanen
Atmos. Chem. Phys., 16, 10385–10398, https://doi.org/10.5194/acp-16-10385-2016, https://doi.org/10.5194/acp-16-10385-2016, 2016
Short summary
Short summary
In-cloud measurements of aerosol hygroscopicity and cloud droplet activation were conducted in Kuopio, Finland. According to the observations, the less hygroscopic accumulation mode particles were present in the non-activated aerosol, whereas the more hygroscopic particles were scavenged into cloud droplets. The results illustrate the sensitivity of cloud droplet formation to varying chemical composition and highlight the need for proper treatment of anthropogenic aerosols in CCN predictions.
Tero Mielonen, Anca Hienola, Thomas Kühn, Joonas Merikanto, Antti Lipponen, Tommi Bergman, Hannele Korhonen, Pekka Kolmonen, Larisa Sogacheva, Darren Ghent, Antti Arola, Gerrit de Leeuw, and Harri Kokkola
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2016-625, https://doi.org/10.5194/acp-2016-625, 2016
Revised manuscript not accepted
Short summary
Short summary
We studied the temperature dependence of AOD and its radiative effects over the southeastern US. We used spaceborne observations of AOD, LST and tropospheric NO2 with simulations of ECHAM-HAMMOZ. The level of AOD in this region is governed by anthropogenic emissions but the temperature dependency is most likely caused by BVOC emissions. According to the observations and simulations, the regional clear-sky DRE for biogenic aerosols is −0.43 ± 0.88 W/m2/K and −0.86 ± 0.06 W/m2/K, respectively.
Jani Huttunen, Harri Kokkola, Tero Mielonen, Mika Esa Juhani Mononen, Antti Lipponen, Juha Reunanen, Anders Vilhelm Lindfors, Santtu Mikkonen, Kari Erkki Juhani Lehtinen, Natalia Kouremeti, Alkiviadis Bais, Harri Niska, and Antti Arola
Atmos. Chem. Phys., 16, 8181–8191, https://doi.org/10.5194/acp-16-8181-2016, https://doi.org/10.5194/acp-16-8181-2016, 2016
Short summary
Short summary
For a good estimate of the current forcing by anthropogenic aerosols, knowledge in past is needed. One option to lengthen time series is to retrieve aerosol optical depth from solar radiation measurements. We have evaluated several methods for this task. Most of the methods produce aerosol optical depth estimates with a good accuracy. However, machine learning methods seem to be the most applicable not to produce any systematic biases, since they do not need constrain the aerosol properties.
N. I. Kristiansen, A. Stohl, D. J. L. Olivié, B. Croft, O. A. Søvde, H. Klein, T. Christoudias, D. Kunkel, S. J. Leadbetter, Y. H. Lee, K. Zhang, K. Tsigaridis, T. Bergman, N. Evangeliou, H. Wang, P.-L. Ma, R. C. Easter, P. J. Rasch, X. Liu, G. Pitari, G. Di Genova, S. Y. Zhao, Y. Balkanski, S. E. Bauer, G. S. Faluvegi, H. Kokkola, R. V. Martin, J. R. Pierce, M. Schulz, D. Shindell, H. Tost, and H. Zhang
Atmos. Chem. Phys., 16, 3525–3561, https://doi.org/10.5194/acp-16-3525-2016, https://doi.org/10.5194/acp-16-3525-2016, 2016
Short summary
Short summary
Processes affecting aerosol removal from the atmosphere are not fully understood. In this study we investigate to what extent atmospheric transport models can reproduce observed loss of aerosols. We compare measurements of radioactive isotopes, that attached to ambient sulfate aerosols during the 2011 Fukushima nuclear accident, to 19 models using identical emissions. Results indicate aerosol removal that is too fast in most models, and apply to aerosols that have undergone long-range transport.
Zak Kipling, Philip Stier, Colin E. Johnson, Graham W. Mann, Nicolas Bellouin, Susanne E. Bauer, Tommi Bergman, Mian Chin, Thomas Diehl, Steven J. Ghan, Trond Iversen, Alf Kirkevåg, Harri Kokkola, Xiaohong Liu, Gan Luo, Twan van Noije, Kirsty J. Pringle, Knut von Salzen, Michael Schulz, Øyvind Seland, Ragnhild B. Skeie, Toshihiko Takemura, Kostas Tsigaridis, and Kai Zhang
Atmos. Chem. Phys., 16, 2221–2241, https://doi.org/10.5194/acp-16-2221-2016, https://doi.org/10.5194/acp-16-2221-2016, 2016
Short summary
Short summary
The vertical distribution of atmospheric aerosol is an important factor in its effects on climate. In this study we use a sophisticated model of the many interacting processes affecting aerosol in the atmosphere to show that the vertical distribution is typically dominated by only a few of these processes. Constraining these physical processes may help to reduce the large differences between models. However, the important processes are not always the same for different types of aerosol.
A. Laakso, H. Kokkola, A.-I. Partanen, U. Niemeier, C. Timmreck, K. E. J. Lehtinen, H. Hakkarainen, and H. Korhonen
Atmos. Chem. Phys., 16, 305–323, https://doi.org/10.5194/acp-16-305-2016, https://doi.org/10.5194/acp-16-305-2016, 2016
Short summary
Short summary
We have studied the impacts of a volcanic eruption during solar radiation management (SRM) using an aerosol-climate model ECHAM5-HAM-SALSA and an Earth system model MPI-ESM. A volcanic eruption during stratospheric sulfur geoengineering would lead to larger particles and smaller amount of new particles than if an volcano erupts in normal atmospheric conditions. Thus, volcanic eruption during SRM would lead to only a small additional cooling which would last for a significantly shorter period.
A. M. K. Hansen, J. Hong, T. Raatikainen, K. Kristensen, A. Ylisirniö, A. Virtanen, T. Petäjä, M. Glasius, and N. L. Prisle
Atmos. Chem. Phys., 15, 14071–14089, https://doi.org/10.5194/acp-15-14071-2015, https://doi.org/10.5194/acp-15-14071-2015, 2015
Short summary
Short summary
This paper presents the first study of the hygroscopic properties of limonene derived organosulfates (L-OS 250). The results showed that L-OS 250 particles are weakly hygroscopic and able to activate into cloud droplets. Particles of L-OS 250 mixed with ammonium sulfate were much more hygroscopic than expected from model parametrizations and the ZSR mixing rule, indicating that solubility and non-ideal droplet interactions could be important for the hygroscopic properties of the mixed particles.
R. Pirazzini, P. Räisänen, T. Vihma, M. Johansson, and E.-M. Tastula
The Cryosphere, 9, 2357–2381, https://doi.org/10.5194/tc-9-2357-2015, https://doi.org/10.5194/tc-9-2357-2015, 2015
Short summary
Short summary
We illustrate a method to measure the size distribution of a snow particle metric from macro photos of snow particles. This snow particle metric corresponds well to the optically equivalent effective radius. Our results evidence the impact of grain shape on albedo, indicate that more than just one particle metric distribution is needed to characterize the snow scattering properties at all optical wavelengths, and suggest an impact of surface roughness on the shortwave infrared albedo.
A. Arola, G. L. Schuster, M. R. A. Pitkänen, O. Dubovik, H. Kokkola, A. V. Lindfors, T. Mielonen, T. Raatikainen, S. Romakkaniemi, S. N. Tripathi, and H. Lihavainen
Atmos. Chem. Phys., 15, 12731–12740, https://doi.org/10.5194/acp-15-12731-2015, https://doi.org/10.5194/acp-15-12731-2015, 2015
Short summary
Short summary
There have been relatively few measurement-based estimates for the direct radiative effect of brown carbon so far. This is first time that the direct radiative effect of brown carbon is estimated by exploiting the AERONET-retrieved imaginary indices. We estimated it for four sites in the Indo-Gangetic Plain: Karachi, Lahore,
Kanpur and Gandhi College.
J. Joutsensaari, P. Yli-Pirilä, H. Korhonen, A. Arola, J. D. Blande, J. Heijari, M. Kivimäenpää, S. Mikkonen, L. Hao, P. Miettinen, P. Lyytikäinen-Saarenmaa, C. L. Faiola, A. Laaksonen, and J. K. Holopainen
Atmos. Chem. Phys., 15, 12139–12157, https://doi.org/10.5194/acp-15-12139-2015, https://doi.org/10.5194/acp-15-12139-2015, 2015
Short summary
Short summary
Global warming will induce large-scale insect outbreaks in boreal forests. Our results from field and laboratory experiments, satellite observations and global-scale modelling suggest that more frequent insect outbreaks, in addition to temperature-dependent increases in VOC emissions, could result in substantial increases in biogenic SOA formation and therefore affect both aerosol direct and indirect forcing of climate at regional scales. This should be considered in future climate predictions.
O. Kemppinen, T. Nousiainen, S. Merikallio, and P. Räisänen
Atmos. Chem. Phys., 15, 11117–11132, https://doi.org/10.5194/acp-15-11117-2015, https://doi.org/10.5194/acp-15-11117-2015, 2015
Short summary
Short summary
Combinations of simple mathematical model shapes called ellipsoids are used in many remote sensing and modeling applications to denote dust particles. In this study we investigate how accurately various physical parameters can be retrieved by using ellipsoids. The results show that using ellipsoids can lead to wrong results, while at the same time seeming like they work well. This means that extreme care should be used when using ellipsoids for dust, and extra validation measures should be used.
T. Raatikainen, D. Brus, A.-P. Hyvärinen, J. Svensson, E. Asmi, and H. Lihavainen
Atmos. Chem. Phys., 15, 10057–10070, https://doi.org/10.5194/acp-15-10057-2015, https://doi.org/10.5194/acp-15-10057-2015, 2015
Short summary
Short summary
We have measured atmospheric aerosol composition by using a Single Particle Soot Photometer (SP2) in the Finnish Arctic during winter 2011-2012. SP2 can give detailed information about mass distributions and mixing state of refractory black carbon (rBC). The measurements showed varying rBC mass concentrations, but relatively constant rBC core size distributions and mixing state parameters. On average, 24% of all particles contain rBC and the observed rBC cores are always thickly coated.
M. A. Thomas, M. Kahnert, C. Andersson, H. Kokkola, U. Hansson, C. Jones, J. Langner, and A. Devasthale
Geosci. Model Dev., 8, 1885–1898, https://doi.org/10.5194/gmd-8-1885-2015, https://doi.org/10.5194/gmd-8-1885-2015, 2015
Short summary
Short summary
We have showed that a coupled modelling system is beneficial in the sense that more complex processes can be included to better represent the aerosol processes starting from their formation, their interactions with clouds and provide better estimate of radiative forcing. Using this model set up, we estimated an annual mean 'indirect' radiative forcing of -0.64W/m2. This means that aerosols, solely by their capability of altering the microphysical properties of clouds can cool the Earth system.
P. Räisänen, A. Kokhanovsky, G. Guyot, O. Jourdan, and T. Nousiainen
The Cryosphere, 9, 1277–1301, https://doi.org/10.5194/tc-9-1277-2015, https://doi.org/10.5194/tc-9-1277-2015, 2015
Short summary
Short summary
While snow grains are distinctly non-spherical, spheres are often assumed in radiative transfer calculations. Here, angular scattering measurements for blowing snow are used to select an optically equivalent snow grain shape model. Parameterizations are then developed for the asymmetry parameter, single-scattering co-albedo and phase function of snow. The parameterizations will help to improve the treatment of snow in radiative transfer applications, including remote sensing and climate models.
J. Tonttila, E. J. O'Connor, A. Hellsten, A. Hirsikko, C. O'Dowd, H. Järvinen, and P. Räisänen
Atmos. Chem. Phys., 15, 5873–5885, https://doi.org/10.5194/acp-15-5873-2015, https://doi.org/10.5194/acp-15-5873-2015, 2015
J.-P. Pietikäinen, K. Kupiainen, Z. Klimont, R. Makkonen, H. Korhonen, R. Karinkanta, A.-P. Hyvärinen, N. Karvosenoja, A. Laaksonen, H. Lihavainen, and V.-M. Kerminen
Atmos. Chem. Phys., 15, 5501–5519, https://doi.org/10.5194/acp-15-5501-2015, https://doi.org/10.5194/acp-15-5501-2015, 2015
Short summary
Short summary
The global aerosol--climate model ECHAM-HAMMOZ is used to study the aerosol burden and forcing changes in the coming decades. We show that aerosol burdens overall can have a decreasing trend leading to reductions in the direct aerosol effect being globally 0.06--0.4W/m2 by 2030, whereas the aerosol indirect radiative effect could decline 0.25--0.82W/m2. We also show that the targeted emission reduction measures can be a much better choice for the climate than overall high reductions globally.
M. Dalirian, H. Keskinen, L. Ahlm, A. Ylisirniö, S. Romakkaniemi, A. Laaksonen, A. Virtanen, and I. Riipinen
Atmos. Chem. Phys., 15, 3815–3829, https://doi.org/10.5194/acp-15-3815-2015, https://doi.org/10.5194/acp-15-3815-2015, 2015
C. Andersson, R. Bergström, C. Bennet, L. Robertson, M. Thomas, H. Korhonen, K. E. J. Lehtinen, and H. Kokkola
Geosci. Model Dev., 8, 171–189, https://doi.org/10.5194/gmd-8-171-2015, https://doi.org/10.5194/gmd-8-171-2015, 2015
Short summary
Short summary
We have integrated the sectional aerosol dynamics model SALSA into the European scale chemistry-transport model MATCH. The combined model reproduces observed higher particle number concentration (PNCs) in central Europe and lower concentrations in remote regions; however, the total PNC is underestimated. The low nucleation rate coefficient used in this study is an important reason for the underestimation.
H. Vuollekoski, M. Vogt, V. A. Sinclair, J. Duplissy, H. Järvinen, E.-M. Kyrö, R. Makkonen, T. Petäjä, N. L. Prisle, P. Räisänen, M. Sipilä, J. Ylhäisi, and M. Kulmala
Hydrol. Earth Syst. Sci., 19, 601–613, https://doi.org/10.5194/hess-19-601-2015, https://doi.org/10.5194/hess-19-601-2015, 2015
Short summary
Short summary
The global potential for collecting usable water from dew on an
artificial collector sheet was investigated by utilising 34 years of
meteorological reanalysis data as input to a dew formation model. Continental dew formation was found to be frequent and common, but daily yields were
mostly below 0.1mm.
J. Tonttila, H. Järvinen, and P. Räisänen
Atmos. Chem. Phys., 15, 703–714, https://doi.org/10.5194/acp-15-703-2015, https://doi.org/10.5194/acp-15-703-2015, 2015
E. M. Dunne, S. Mikkonen, H. Kokkola, and H. Korhonen
Atmos. Chem. Phys., 14, 13631–13642, https://doi.org/10.5194/acp-14-13631-2014, https://doi.org/10.5194/acp-14-13631-2014, 2014
Short summary
Short summary
Marine clouds have a strong effect on the Earth's radiative balance. One proposed climate feedback is that, in a warming climate, marine aerosol emissions will change due to changing wind speeds. We have examined the processes that affect aerosol emissions and removal over 15 years, and high-temporal-resolution output over 2 months. We conclude that wind trends are unlikely to cause a strong feedback in marine regions, but changes in removal processes or transport from continental regions may.
P. Räisänen, A. Luomaranta, H. Järvinen, M. Takala, K. Jylhä, O. N. Bulygina, K. Luojus, A. Riihelä, A. Laaksonen, J. Koskinen, and J. Pulliainen
Geosci. Model Dev., 7, 3037–3057, https://doi.org/10.5194/gmd-7-3037-2014, https://doi.org/10.5194/gmd-7-3037-2014, 2014
Short summary
Short summary
Snowmelt influences greatly the climatic conditions in spring. This study evaluates the timing of springtime end of snowmelt in the ECHAM5 model. A key finding is that, in much of northern Eurasia, snow disappears too early in ECHAM5, in spite of a slight cold bias in spring. This points to the need for a more comprehensive treatment of the surface energy budget. In particular, the surface temperature for the snow-covered and snow-free parts of a climate model grid cell should be separated.
L. Q. Hao, A. Kortelainen, S. Romakkaniemi, H. Portin, A. Jaatinen, A. Leskinen, M. Komppula, P. Miettinen, D. Sueper, A. Pajunoja, J. N. Smith, K. E. J. Lehtinen, D. R. Worsnop, A. Laaksonen, and A. Virtanen
Atmos. Chem. Phys., 14, 13483–13495, https://doi.org/10.5194/acp-14-13483-2014, https://doi.org/10.5194/acp-14-13483-2014, 2014
Short summary
Short summary
Positive matrix factorization (PMF) was applied to the unified high-resolution mass spectra organic species with NO+ and NO2+ ions from the measurement in a mixed region between the boreal forestland and the urban area. The PMF analysis succeeded in separating the mixed spectra into three distinct organic factors and one inorganic factor. The particulate organic nitrate was distinguished by PMF for the first time, with a contribution of one-third of the total nitrate mass.
A.-I. Partanen, E. M. Dunne, T. Bergman, A. Laakso, H. Kokkola, J. Ovadnevaite, L. Sogacheva, D. Baisnée, J. Sciare, A. Manders, C. O'Dowd, G. de Leeuw, and H. Korhonen
Atmos. Chem. Phys., 14, 11731–11752, https://doi.org/10.5194/acp-14-11731-2014, https://doi.org/10.5194/acp-14-11731-2014, 2014
Short summary
Short summary
New parameterizations for the sea spray aerosol source flux and its organic fraction were incorporated into a global aerosol-climate model. The emissions of sea salt were considerably less than previous estimates. This study demonstrates that sea spray aerosol may actually decrease the number of cloud droplets, which has a warming effect on climate. Overall, sea spray aerosol was predicted to have a global cooling effect due to the scattering of solar radiation from sea spray aerosol particles.
K. Tsigaridis, N. Daskalakis, M. Kanakidou, P. J. Adams, P. Artaxo, R. Bahadur, Y. Balkanski, S. E. Bauer, N. Bellouin, A. Benedetti, T. Bergman, T. K. Berntsen, J. P. Beukes, H. Bian, K. S. Carslaw, M. Chin, G. Curci, T. Diehl, R. C. Easter, S. J. Ghan, S. L. Gong, A. Hodzic, C. R. Hoyle, T. Iversen, S. Jathar, J. L. Jimenez, J. W. Kaiser, A. Kirkevåg, D. Koch, H. Kokkola, Y. H Lee, G. Lin, X. Liu, G. Luo, X. Ma, G. W. Mann, N. Mihalopoulos, J.-J. Morcrette, J.-F. Müller, G. Myhre, S. Myriokefalitakis, N. L. Ng, D. O'Donnell, J. E. Penner, L. Pozzoli, K. J. Pringle, L. M. Russell, M. Schulz, J. Sciare, Ø. Seland, D. T. Shindell, S. Sillman, R. B. Skeie, D. Spracklen, T. Stavrakou, S. D. Steenrod, T. Takemura, P. Tiitta, S. Tilmes, H. Tost, T. van Noije, P. G. van Zyl, K. von Salzen, F. Yu, Z. Wang, Z. Wang, R. A. Zaveri, H. Zhang, K. Zhang, Q. Zhang, and X. Zhang
Atmos. Chem. Phys., 14, 10845–10895, https://doi.org/10.5194/acp-14-10845-2014, https://doi.org/10.5194/acp-14-10845-2014, 2014
S. V. Henriksson, J.-P. Pietikäinen, A.-P. Hyvärinen, P. Räisänen, K. Kupiainen, J. Tonttila, R. Hooda, H. Lihavainen, D. O'Donnell, L. Backman, Z. Klimont, and A. Laaksonen
Atmos. Chem. Phys., 14, 10177–10192, https://doi.org/10.5194/acp-14-10177-2014, https://doi.org/10.5194/acp-14-10177-2014, 2014
M. S. Johnston, S. Eliasson, P. Eriksson, R. M. Forbes, A. Gettelman, P. Räisänen, and M. D. Zelinka
Atmos. Chem. Phys., 14, 8701–8721, https://doi.org/10.5194/acp-14-8701-2014, https://doi.org/10.5194/acp-14-8701-2014, 2014
H. Portin, A. Leskinen, L. Hao, A. Kortelainen, P. Miettinen, A. Jaatinen, A. Laaksonen, K. E. J. Lehtinen, S. Romakkaniemi, and M. Komppula
Atmos. Chem. Phys., 14, 6021–6034, https://doi.org/10.5194/acp-14-6021-2014, https://doi.org/10.5194/acp-14-6021-2014, 2014
S. Romakkaniemi, A. Jaatinen, A. Laaksonen, A. Nenes, and T. Raatikainen
Atmos. Meas. Tech., 7, 1377–1384, https://doi.org/10.5194/amt-7-1377-2014, https://doi.org/10.5194/amt-7-1377-2014, 2014
G. W. Mann, K. S. Carslaw, C. L. Reddington, K. J. Pringle, M. Schulz, A. Asmi, D. V. Spracklen, D. A. Ridley, M. T. Woodhouse, L. A. Lee, K. Zhang, S. J. Ghan, R. C. Easter, X. Liu, P. Stier, Y. H. Lee, P. J. Adams, H. Tost, J. Lelieveld, S. E. Bauer, K. Tsigaridis, T. P. C. van Noije, A. Strunk, E. Vignati, N. Bellouin, M. Dalvi, C. E. Johnson, T. Bergman, H. Kokkola, K. von Salzen, F. Yu, G. Luo, A. Petzold, J. Heintzenberg, A. Clarke, J. A. Ogren, J. Gras, U. Baltensperger, U. Kaminski, S. G. Jennings, C. D. O'Dowd, R. M. Harrison, D. C. S. Beddows, M. Kulmala, Y. Viisanen, V. Ulevicius, N. Mihalopoulos, V. Zdimal, M. Fiebig, H.-C. Hansson, E. Swietlicki, and J. S. Henzing
Atmos. Chem. Phys., 14, 4679–4713, https://doi.org/10.5194/acp-14-4679-2014, https://doi.org/10.5194/acp-14-4679-2014, 2014
H. Kokkola, P. Yli-Pirilä, M. Vesterinen, H. Korhonen, H. Keskinen, S. Romakkaniemi, L. Hao, A. Kortelainen, J. Joutsensaari, D. R. Worsnop, A. Virtanen, and K. E. J. Lehtinen
Atmos. Chem. Phys., 14, 1689–1700, https://doi.org/10.5194/acp-14-1689-2014, https://doi.org/10.5194/acp-14-1689-2014, 2014
T. Korhola, H. Kokkola, H. Korhonen, A.-I. Partanen, A. Laaksonen, K. E. J. Lehtinen, and S. Romakkaniemi
Geosci. Model Dev., 7, 161–174, https://doi.org/10.5194/gmd-7-161-2014, https://doi.org/10.5194/gmd-7-161-2014, 2014
A. Lipponen, V. Kolehmainen, S. Romakkaniemi, and H. Kokkola
Geosci. Model Dev., 6, 2087–2098, https://doi.org/10.5194/gmd-6-2087-2013, https://doi.org/10.5194/gmd-6-2087-2013, 2013
A. I. Partanen, A. Laakso, A. Schmidt, H. Kokkola, T. Kuokkanen, J.-P. Pietikäinen, V.-M. Kerminen, K. E. J. Lehtinen, L. Laakso, and H. Korhonen
Atmos. Chem. Phys., 13, 12059–12071, https://doi.org/10.5194/acp-13-12059-2013, https://doi.org/10.5194/acp-13-12059-2013, 2013
C. E. Chung, H. Cha, T. Vihma, P. Räisänen, and D. Decremer
Atmos. Chem. Phys., 13, 11209–11219, https://doi.org/10.5194/acp-13-11209-2013, https://doi.org/10.5194/acp-13-11209-2013, 2013
G. S. Stuart, R. G. Stevens, A.-I. Partanen, A. K. L. Jenkins, H. Korhonen, P. M. Forster, D. V. Spracklen, and J. R. Pierce
Atmos. Chem. Phys., 13, 10385–10396, https://doi.org/10.5194/acp-13-10385-2013, https://doi.org/10.5194/acp-13-10385-2013, 2013
J. Tonttila, P. Räisänen, and H. Järvinen
Atmos. Chem. Phys., 13, 7551–7565, https://doi.org/10.5194/acp-13-7551-2013, https://doi.org/10.5194/acp-13-7551-2013, 2013
S. Lance, T. Raatikainen, T. B. Onasch, D. R. Worsnop, X.-Y. Yu, M. L. Alexander, M. R. Stolzenburg, P. H. McMurry, J. N. Smith, and A. Nenes
Atmos. Chem. Phys., 13, 5049–5062, https://doi.org/10.5194/acp-13-5049-2013, https://doi.org/10.5194/acp-13-5049-2013, 2013
V.-M. Kerminen, M. Paramonov, T. Anttila, I. Riipinen, C. Fountoukis, H. Korhonen, E. Asmi, L. Laakso, H. Lihavainen, E. Swietlicki, B. Svenningsson, A. Asmi, S. N. Pandis, M. Kulmala, and T. Petäjä
Atmos. Chem. Phys., 12, 12037–12059, https://doi.org/10.5194/acp-12-12037-2012, https://doi.org/10.5194/acp-12-12037-2012, 2012
Related subject area
Subject: Clouds and Precipitation | Research Activity: Machine Learning | Altitude Range: Troposphere | Science Focus: Physics (physical properties and processes)
Machine-learning-based investigation of the variables affecting summertime lightning occurrence over the Southern Great Plains
Siyu Shan, Dale Allen, Zhanqing Li, Kenneth Pickering, and Jeff Lapierre
Atmos. Chem. Phys., 23, 14547–14560, https://doi.org/10.5194/acp-23-14547-2023, https://doi.org/10.5194/acp-23-14547-2023, 2023
Short summary
Short summary
Several machine learning models are applied to identify important variables affecting lightning occurrence in the vicinity of the Southern Great Plains ARM site during the summer months of 2012–2020. We find that the random forest model is the best predictor among common classifiers. We rank variables in terms of their effectiveness in nowcasting ENTLN lightning and identify geometric cloud thickness, rain rate and convective available potential energy (CAPE) as the most effective predictors.
Cited articles
Abdul‐Razzak, H. and Ghan, S. J.: A parameterization of aerosol activation 3. Sectional representation, J. Geophys. Res.-Atmos., 107, 4026, https://doi.org/10.1029/2001JD000483, 2002. a, b
Abdul-Razzak, H., Ghan, S. J., and Rivera-carpio, C.: A parameterization of aerosol activation: 1. Single aerosol type, J. Geophys. Res., 103, 6123–6131, https://doi.org/10.1029/97JD03735, 1998. a
Adler, R. F., Gu, G., and Huffman, G. J.: Estimating climatological bias errors for the Global Precipitation Climatology Project (GPCP), J. Appl. Meteorol. Clim., 51, 84–99, https://doi.org/10.1175/JAMC-D-11-052.1, 2012. a
Ahola, J., Raatikainen, T., Alper, M. E., Keskinen, J.-P., Kokkola, H., Kukkurainen, A., Lipponen, A., Liu, J., Nordling, K., Partanen, A.-I., Romakkaniemi, S., Räisänen, P., Tonttila, J., and Korhonen, H.: Technical note: Parameterising cloud base updraft velocity of marine stratocumuli, Atmos. Chem. Phys., 22, 4523–4537, https://doi.org/10.5194/acp-22-4523-2022, 2022. a, b, c, d, e, f, g, h, i, j, k, l, m
Besombes, C., Pannekoucke, O., Lapeyre, C., Sanderson, B., and Thual, O.: Producing realistic climate data with generative adversarial networks, Nonlin. Processes Geophys., 28, 347–370, https://doi.org/10.5194/npg-28-347-2021, 2021. a
Bogenschutz, P. A., Gettelman, A., Morrison, H., Larson, V. E., Craig, C., and Schanen, D. P.: Higher-order turbulence closure and its impact on climate simulations in the Community Atmosphere Model, J. Climate, 26, 9655–9676, https://doi.org/10.1175/JCLI-D-13-00075.1, 2013. a
Boucher, O., Randall, D., Artaxo, P., Bretherton, C., Feingold, G., Forster, P., Kerminen, V.-M., Kondo, Y., Liao, H., Lohmann, U., Rasch, P., K. Satheesh, S., Sherwood, S., Stevens, B., and Zhang, X.: Clouds and Aerosols, Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, http://www.ipcc.ch/pdf/assessment-report/ar5/wg1/WG1AR5_Chapter07_FINAL.pdf (last access: 5 May 2023), 2013. a
Bougiatioti, A., Nenes, A., Lin, J. J., Brock, C. A., de Gouw, J. A., Liao, J., Middlebrook, A. M., and Welti, A.: Drivers of cloud droplet number variability in the summertime in the southeastern United States, Atmos. Chem. Phys., 20, 12163–12176, https://doi.org/10.5194/acp-20-12163-2020, 2020. a
Brenowitz, N. D., Beucler, T., Pritchard, M., and Bretherton, C. S.: Interpreting and Stabilizing Machine-Learning Parametrizations of Convection, J. Atmos. Sci., 77, 4357–4375, https://doi.org/10.1175/JAS-D-20-0082.1, 2020. a
Bretherton, C. S., Henn, B., Kwa, A., Brenowitz, N. D., Watt-Meyer, O., McGibbon, J., Perkins, W. A., Clark, S. K., and Harris, L.: Correcting Coarse-Grid Weather and Climate Models by Machine Learning From Global Storm-Resolving Simulations, J. Adv. Model. Earth Sy., 14, e2021MS002794, https://doi.org/10.1029/2021MS002794, 2022. a
Cesana, G. V. and Del Genio, A. D.: Observational constraint on cloud feedbacks suggests moderate climate sensitivity, Nat. Clim. Change, 11, 213–218, https://doi.org/10.1038/s41558-020-00970-y, 2021. a
Cess, R. D., Potter, G. L., Blanchet, J. P., Boer, G. J., Del Genio, A. D., Déqué, M., Dymnikov, V., Galin, V., Gates, W. L., Ghan, S. J., Kiehl, J. T., Lacis, A. A., Le Treut, H., Li, Z.-X., Liang, X.-Z., McAvaney, B. J., Meleshko, V. P., Mitchell, J. F. B., Morcrette, J.-J., Randall, D. A., Rikus, L., Roeckner, E., Royer, J. F., Schlese, U., Sheinin, D. A., Slingo, A., Sokolov, A. P., Taylor, K. E., Washington, W. M., Wetherald, R. T., Yagai, I., and Zhang, M.-H.: Intercomparison and interpretation of climate feedback processes in 19 atmospheric general circulation models, J. Geophys. Res.-Atmos., 95, 16601–16615, https://doi.org/10.1029/JD095iD10p16601, 1990. a, b
Chang, P., Zhang, S. Q., Danabasoglu, G., Yeager, S. G., Fu, H. H., Wang, H., Castruccio, F. S., Chen, Y. H., Edwards, J., Fu, D., Jia, Y. L., Laurindo, L. C., Liu, X., Rosenbloom, N., Small, R. J., Xu, G. P., Zeng, Y. H., Zhang, Q. Y., Bacmeister, J., Bailey, D. A., Duan, X. H., DuVivier, A. K., Li, D. P., Li, Y. X., Neale, R., Stossel, A., Wang, L., Zhuang, Y., Baker, A., Bates, S., Dennis, J., Diao, X. L., Gan, B. L., Gopal, A., Jia, D. N., Jing, Z., Ma, X. H., Saravanan, R., Strand, W. G., Tao, J., Yang, H. Y., Wang, X. Q., Wei, Z. Q., and Wu, L. X.: An unprecedented set of high-resolution earth system simulations for understanding multiscale interactions in climate variability and change, J. Adv. Model. Earth Sy., 12, e2020MS002298, https://doi.org/10.1029/2020MS002298, 2020. a
Cheng, T., Peng, Y., Feichter, J., and Tegen, I.: An improvement on the dust emission scheme in the global aerosol-climate model ECHAM5-HAM, Atmos. Chem. Phys., 8, 1105–1117, https://doi.org/10.5194/acp-8-1105-2008, 2008. a
Cheruy, F., Chevallier, F., Morcrette, J.-J., Scott, N. A., and Chédin, A.: Une méthode utilisant les techniques neuronales pour le calcul rapide de la distribution verticale du bilan radiatif thermique terrestre, CR. Acad. Sci. II B, 322, 665–672, 1996. a
Chevallier, F., Chéruy, F., Scott, N. A., and Chédin, A.: A Neural Network Approach for a Fast and Accurate Computation of a Longwave Radiative Budget, J. Appl. Meteorol., 37, 1385–1397, https://doi.org/10.1175/1520-0450(1998)037<1385:ANNAFA>2.0.CO;2, 1998. a
Conibear, L., Reddington, C. L., Silver, B. J., Chen, Y., Knote, C., Arnold, S. R., and Spracklen, D. V.: Statistical emulation of winter ambient fine particulate matter concentrations from emission changes in China, GeoHealth, 5, e2021GH000391, https://doi.org/10.1029/2021GH000391, 2021. a
Donner, L. J., O'Brien, T. A., Rieger, D., Vogel, B., and Cooke, W. F.: Are atmospheric updrafts a key to unlocking climate forcing and sensitivity?, Atmos. Chem. Phys., 16, 12983–12992, https://doi.org/10.5194/acp-16-12983-2016, 2016. a
Elsaesser, G., O’Dell, C., Lebsock, M., and Teixeira, J.: Multisensor advanced climatology mean liquid water path L3 monthly 1 degree × 1 degree V1, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/MEASURES/MACLWPM, 2016. a
Fuchs, H., Kedem, Z. M., and Naylor, B. F.: On Visible Surface Generation by a Priori Tree Structures, SIGGRAPH Comput. Graph., 14, 124–133, https://doi.org/10.1145/965105.807481, 1980. a
Gettelman, A., Hannay, C., Bacmeister, J. T. Neale, R. B., Pendergrass, A. G., Danabasoglu, G., Lamarque, J.-F., Fasullo, J. T., Bailey, D. A., Lawrence, D. M., and Mills, M. J.: High climate sensitivity in the Community Earth System Model version 2 (CESM2), Geophys. Res. Lett., 46, 8329–8337, https://doi.org/10.1029/2019GL083978, 2019.
Glassmeier, F., Hoffmann, F., Johnson, J. S., Yamaguchi, T., Carslaw, K. S., and Feingold, G.: An emulator approach to stratocumulus susceptibility, Atmos. Chem. Phys., 19, 10191–10203, https://doi.org/10.5194/acp-19-10191-2019, 2019. a, b
Golaz, J., Larson, V. E., and Cotton, W. R.: A PDF-based model for boundary layer clouds. Part I: method and model description, J. Atmos. Sci., 59, 3540–3551, https://doi.org/10.1175/1520-0469(2002)059<3540:APBMFB>2.0.CO;2, 2002. a
Golaz, J.-C., Salzmann, M., Donner, L. J., Horowitz, L. W., Ming, Y., and Zhao, M.: Sensitivity of the aerosol indirect effect to subgrid variability in the cloud parameterization of the GFDL atmosphere general circulation model AM3, J. Climate, 24, 3145–3160, https://doi.org/10.1175/2010JCLI3945.1, 2011. a, b, c, d
Grabowski, W. W.: Towards Global Large Eddy Simulation: Super-Parameterization Revisited, J. Meteorol. Soc. Jpn Ser. II, 94, 327–344, https://doi.org/10.2151/jmsj.2016-017, 2016. a
Grabowski, W. W. and Smolarkiewicz, P. K.: CRCP: A cloud resolving convection parameterization for modeling the tropical convecting atmosphere, Physica D, 133, 171–178, https://doi.org/10.1016/S0167-2789(99)00104-9, 1999. a
Guelle, W., Schulz, M., Balkanski, Y., and Dentener, F.: Influence of the source formulation on modeling the atmospheric global distribution of sea salt aerosol, J. Geophys. Res., 106, 27509–27524, https://doi.org/10.1029/2001JD900249, 2001. a
Guo, H., Golaz, J., Donner, L. J., Ginoux, P., and Hemler, R. S.: Multivariate Probability Density Functions with Dynamics in the GFDL Atmospheric General Circulation Model: Global Tests, J. Climate, 27, 2087–2108, https://doi.org/10.1175/JCLI-D-13-00347.1, 2014. a
Guo, Z., Wang, M., Larson, V. E., and Zhou, T.: A cloud top radiative cooling model coupled with CLUBB in the Community Atmosphere Model: Description and simulation of low clouds, J. Adv. Model. Earth Sy., 11, 979–997, https://doi.org/10.1029/2018MS001505, 2019. a
HAMMOZ consortium: ECHAM-HAMOZ model data, https://redmine.hammoz.ethz.ch/projects/hammoz/, last access: 4 April 2023a. a
HAMMOZ consortium: https://redmine.hammoz.ethz.ch/attachments/download/291/License_ECHAM-HAMMOZ_June2012.pdf, last access: 4 April 2023b. a
Han, Y., Zhang, G. J., Huang, X., and Wang, Y.: A Moist Physics Parameterization Based on Deep Learning, J. Adv. Model. Earth Sy., 12, e2020MS002076, https://doi.org/10.1029/2020MS002076, 2020. a
Heinold, B., Tegen, I., Schepanski, K., and Banks, J. R.: New developments in the representation of Saharan dust sources in the aerosol–climate model ECHAM6-HAM2, Geosci. Model Dev., 9, 765–777, https://doi.org/10.5194/gmd-9-765-2016, 2016. a
Hoose, C., Kristjánsson, J. E., Iversen, T., Kirkevåg, A., Seland, Ø., and Gettelman, A.: Constraining cloud droplet number concentration in GCMs suppresses the aerosol indirect effect, Geophys. Res. Lett., 36, L12807, https://doi.org/10.1029/2009GL038568, 2009. a
Jansson, F., van den Oord, G., Pelupessy, I., Grönqvist, J. H., Siebesma, A. P., and Crommelin, D.: Regional Superparameterization in a Global Circulation Model Using Large Eddy Simulations, J. Adv. Model. Earth Sy., 11, 2958–2979, https://doi.org/10.1029/2018MS001600, 2019. a
Jian, B., Li, J., Zhao, Y., He, Y., Wang, J., and Huang, J.: Evaluation of the CMIP6 planetary albedo climatology using satellite observations, Clim. Dynam., 54, 5145–5161, https://doi.org/10.1007/s00382-020-05277-4, 2020. a
Jing, X., Suzuki, K., and Michibata, T.: The key role of warm rain parameterization in determining the aerosol indirect effect in a global climate model, J. Climate, 32, 4409–4430, https://doi.org/10.1175/JCLI-D-18-0789.1, 2019. a, b, c, d
Kawai, H. and Shige, S.: Marine Low Clouds and their Parameterization in Climate Models, J. Meteorol. Soc. Jpn. Ser. II, 98, 1097–1127, https://doi.org/10.2151/jmsj.2020-059, 2020. a, b, c
Khairoutdinov, M. and Kogan, Y.: A New Cloud Physics Parameterization in a Large-Eddy Simulation Model of Marine Stratocumulus, Mon. Weather Rev., 128, 229–243, https://doi.org/10.1175/1520-0493(2000)128<0229:ANCPPI>2.0.CO;2, 2000. a, b, c
Khairoutdinov, M. F. and Randall, D. A.: Cloud resolving modeling of the ARM summer 1997 IOP: Model formulation, results, uncertainties, and sensitivities, J. Atmos. Sci., 60, 607–625, https://doi.org/10.1175/1520-0469(2003)060<0607:CRMOTA>2.0.CO;2, 2003. a
Khairoutdinov, M., Randall, D., and DeMott, C.: Simulations of the Atmospheric General Circulation Using a Cloud-Resolving Model as a Superparameterization of Physical Processes, J. Atmos. Sci., 62, 2136–2154, https://doi.org/10.1175/JAS3453.1, 2005. a
Kloster, S., Feichter, J., Maier-Reimer, E., Six, K. D., Stier, P., and Wetzel, P.: DMS cycle in the marine ocean-atmosphere system – a global model study, Biogeosciences, 3, 29–51, https://doi.org/10.5194/bg-3-29-2006, 2006. a
Kokkola, H., Kühn, T., Laakso, A., Bergman, T., Lehtinen, K. E. J., Mielonen, T., Arola, A., Stadtler, S., Korhonen, H., Ferrachat, S., Lohmann, U., Neubauer, D., Tegen, I., Siegenthaler-Le Drian, C., Schultz, M. G., Bey, I., Stier, P., Daskalakis, N., Heald, C. L., and Romakkaniemi, S.: SALSA2.0: The sectional aerosol module of the aerosol–chemistry–climate model ECHAM6.3.0-HAM2.3-MOZ1.0, Geosci. Model Dev., 11, 3833–3863, https://doi.org/10.5194/gmd-11-3833-2018, 2018. a, b, c
Lamarque, J.-F., Bond, T. C., Eyring, V., Granier, C., Heil, A., Klimont, Z., Lee, D., Liousse, C., Mieville, A., Owen, B., Schultz, M. G., Shindell, D., Smith, S. J., Stehfest, E., Van Aardenne, J., Cooper, O. R., Kainuma, M., Mahowald, N., McConnell, J. R., Naik, V., Riahi, K., and van Vuuren, D. P.: Historical (1850–2000) gridded anthropogenic and biomass burning emissions of reactive gases and aerosols: methodology and application, Atmos. Chem. Phys., 10, 7017–7039, https://doi.org/10.5194/acp-10-7017-2010, 2010. a
Lauer, A., and Hamilton, K.: Simulating clouds with global climate models: A comparison of CMIP5 Results with CMIP3 and satellite data, J. Climate, 26, 3823–3845, https://doi.org/10.1175/JCLI-D-12-00451.1., 2013. a
Lee, H.-H., Bogenschutz, P., and Yamaguchi, T.: Resolving away stratocumulus biases in modern global climate models, Geophys. Res. Lett., 49, e2022GL099422, https://doi.org/10.1029/2022GL099422, 2022. a
Lilly, D. K.: Models of cloud-topped mixed layers under a strong inversion, Q. J. Roy. Meteor. Soc., 94, 292–309, https://doi.org/10.1002/QJ.49709440106, 1968. a
Loeb, N. G., Doelling, D. R., Wang, H., Su, W., Nguyen, C., Corbett, J. G., Liang, L., Mitrescu, C., Rose, F. G., and Kato, S.: Clouds and the earth’s radiant energy system (CERES) energy balanced and filled (EBAF) top-of-atmosphere (TOA) edition-4.0 data product, J. Climate, 31, 895–918, https://doi.org/10.1175/JCLI-D-17-0208.1, 2018. a
Lohmann, U., Stier, P., Hoose, C., Ferrachat, S., Kloster, S., Roeckner, E., and Zhang, J.: Cloud microphysics and aerosol indirect effects in the global climate model ECHAM5-HAM, Atmos. Chem. Phys., 7, 3425–3446, https://doi.org/10.5194/acp-7-3425-2007, 2007. a
Lohmann, U.: Global anthropogenic aerosol effects on convective clouds in ECHAM5-HAM, Atmos. Chem. Phys., 8, 2115–2131, https://doi.org/10.5194/acp-8-2115-2008, 2008. a
Lohmann, U. and Hoose, C.: Sensitivity studies of different aerosol indirect effects in mixed-phase clouds, Atmos. Chem. Phys., 9, 8917–8934, https://doi.org/10.5194/acp-9-8917-2009, 2009. a
Lohmann, U. and Neubauer, D.: The importance of mixed-phase and ice clouds for climate sensitivity in the global aerosol–climate model ECHAM6-HAM2, Atmos. Chem. Phys., 18, 8807–8828, https://doi.org/10.5194/acp-18-8807-2018, 2018. a, b
Lohmann, U. and Roeckner, E: Design and performance of a new cloud microphysics scheme developed for the ECHAM general circulation model, Clim. Dynam., 12, 557–572, https://doi.org/10.1007/BF00207939, 1996 a
Lohmann, U., Feichter, J., Chuang, C. C., and Penner, J. E., Prediction of the number of cloud droplets in the ECHAM GCM, J. Geophys. Res., 104, 9169–9198, https://doi.org/10.1029/1999JD900046, 1999. a
Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J., Maycock, T., T. Waterfield, O. Y., Yu, R., and Zhou, B. (Eds.): Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, https://doi.org/10.1017/9781009157896, 2021. a
Matsui, H. and Moteki, N.: High sensitivity of Arctic black carbon radiative effects to subgrid vertical velocity in aerosol activation, Geophys. Res. Lett., 47, e2020GL088978, https://doi.org/10.1029/2020GL088978, 2020. a, b
Ming, Y., Ramaswamy, V., Donner, L. J., Phillips, V. T., Klein, S. A., Ginoux, P. A., and Horowitz, L. W.: Modeling the interactions between aerosols and liquid water clouds with a self-consistent cloud scheme in a general circulation model, J. Atmos. Sci., 64, 1189–1209, https://doi.org/10.1175/JAS3874.1, 2007.
Muhlbauer, A., McCoy, I. L., and Wood, R.: Climatology of stratocumulus cloud morphologies: microphysical properties and radiative effects, Atmos. Chem. Phys., 14, 6695–6716, https://doi.org/10.5194/acp-14-6695-2014, 2014. a
Mülmenstädt, J., Nam, C., Salzmann, M., Kretzschmar, J., L’Ecuyer, T. S., Lohmann, U., Ma, P.-L., Myhre, G., Neubauer, D., Stier, P., Suzuki, K., Wang, M., and Quaas, J.: Reducing the aerosol forcing uncertainty using observational constraints on warm rain processes, Sci. Adv., 6, eaaz6433, https://doi.org/10.1126/sciadv.aaz6433, 2020. a
Neubauer, D., Lohmann, U., Hoose, C., and Frontoso, M. G.: Impact of the representation of marine stratocumulus clouds on the anthropogenic aerosol effect, Atmos. Chem. Phys., 14, 11997–12022, https://doi.org/10.5194/acp-14-11997-2014, 2014. a, b
Neubauer, D., Ferrachat, S., Siegenthaler-Le Drian, C., Stier, P., Partridge, D. G., Tegen, I., Bey, I., Stanelle, T., Kokkola, H., and Lohmann, U.: The global aerosol–climate model ECHAM6.3–HAM2.3 – Part 2: Cloud evaluation, aerosol radiative forcing, and climate sensitivity, Geosci. Model Dev., 12, 3609–3639, https://doi.org/10.5194/gmd-12-3609-2019, 2019. a, b
Nordling, K.: Codes for generating ECLAIR emulator (v1.0.2), Zenodo [code], https://doi.org/10.5281/zenodo.10208603, 2023. a
Nordling, K.: Technical note: Emulation of a large-eddy simulator for stratocumulus clouds in a general circulation mode, Finnish Meteorological Institute, ITO/ILM/Ilmastojärjestelmätutkimus yhteiset, http://urn.fi/urn:nbn:fi:att:c6c6c7b3-38d1-47f8-9c46-fe5761554bea, last access: 27 November 2023. a
O'Gorman, P. A. and Dwyer, J. G.: Using Machine Learning to Parameterize Moist Convection: Potential for Modeling of Climate, Climate Change, and Extreme Events, J. Adv. Model. Earth Sy., 10, 2548–2563, https://doi.org/10.1029/2018MS001351, 2018. a
O'Hagan, A.: Curve fitting and optimal design for prediction, J. Roy. Stat. Soc. B, 40, 1–24, 1978. a
O’Hagan, A.: Bayesian analysis of computer code outputs: A tutorial, Reliab. Eng. Syst. Safe., 91, 1290–1300, https://doi.org/10.1016/j.ress.2005.11.025, 2006. a
Parishani, H., Pritchard, M. S., Bretherton, C. S., Wyant, M. C., and Khairoutdinov, M.: Toward low-cloud-permitting cloud superparameterization with explicit boundary layer turbulence, J. Adv. Model. Earth Sy., 9, 1542–1571, https://doi.org/10.1002/2017MS000968, 2017. a
Partanen, A.-I., Kokkola, H., Romakkaniemi, S., Kerminen, V.-M., Lehtinen, K. E. J., Bergman, T., Arola, A., and Korhonen, H.: Direct and indirect effects of sea spray geoengineering and the role of injected particle size, J. Geophys. Res.-Atmos., 117, D02203, https://doi.org/10.1029/2011JD016428, 2012. a, b
Rasmussen, C. E. and Williams, C. K. I.: Gaussian Processes for Machine Learning, The MIT Press, https://doi.org/10.7551/mitpress/3206.001.0001, 2005. a
Rasp, S., Pritchard, M. S., and Gentine, P.: Deep learning to represent subgrid processes in climate models, P. Natl Acad. Sci. USA, 115, 9684–9689, https://doi.org/10.1073/pnas.1810286115, 2018. a
Reichstein, M., Camps-Valls, G., Stevens, B., Jung, M., Denzler, J., Carvalhais, N., and Prabhat: Deep learning and process understanding for data-driven Earth system science, Nature, 566, 195–204, https://doi.org/10.1038/s41586-019-0912-1, 2019. a
Romakkaniemi, S., McFiggans, G., Bower, K. N., Brown, P., Coe, H., and Choularton, T. W.: A comparison between trajectory ensemble and adiabatic parcel modeled cloud properties and evaluation against airborne measurements, J. Geophys. Res.-Atmos., 114, D06214, https://doi.org/10.1029/2008JD011286, 2009. a, b
Rosenfeld, D., Zhu, Y., Wang, M., Zheng, Y., Goren, T., and Yu, S.: Aerosol-driven droplet concentrations dominate coverage and water of oceanic low-level clouds, Science, 363, eaav0566, https://doi.org/10.1126/science.aav0566, 2019. a
Saffin, L., Lock, A., Tomassini, L., Blyth, A., Böing, S., Denby, L., and Marsham, J.: Kilometer-scale simulations of trade-wind cumulus capture processes of mesoscale organization. J. Adv. Model. Earth Sy., 15, e2022MS003295, https://doi.org/10.1029/2022MS003295, 2023. a
Schultz, M. G., Stadtler, S., Schröder, S., Taraborrelli, D., Franco, B., Krefting, J., Henrot, A., Ferrachat, S., Lohmann, U., Neubauer, D., Siegenthaler-Le Drian, C., Wahl, S., Kokkola, H., Kühn, T., Rast, S., Schmidt, H., Stier, P., Kinnison, D., Tyndall, G. S., Orlando, J. J., and Wespes, C.: The chemistry–climate model ECHAM6.3-HAM2.3-MOZ1.0, Geosci. Model Dev., 11, 1695–1723, https://doi.org/10.5194/gmd-11-1695-2018, 2018. a, b
Seifert, A. and Beheng, K. D.: A double-moment parameterization for simulating autoconversion, accretion and selfcollection, Atmos. Res., 59–60, 265–281, https://doi.org/10.1016/S0169-8095(01)00126-0, 2001. a, b, c
Sherwood, S. C., Bony, S. and Dufresne, J.-L.: Spread in model climate sensitivity traced to atmospheric convective mixing, Nature, 505, 37–42, https://doi.org/10.1038/nature12829, 2014.
Siebesma, A. P., Jakob, C., Lenderink, G., Neggers, R. A. J., Teixeira, J., Van Meijgaard, E., Calvo, J., Chlond, A., Grenier, H., Jones, C., Köhler, M., Kitagawa, H., Marquet, P., Lock, A.P., Müller, F., Olmeda, D. and Severijns, C.: Cloud representation in general-circulation models over the northern Pacific Ocean: A EUROCS intercomparison study, Q. J. Roy. Meteor. Soc., 130, 3245–3267, https://doi.org/10.1256/qj.03.146, 2004. a
Siebesma, A. P., Soares, P. M. M, and Teixeira, J.: A combined eddy-diffusivity mass-flux approach for the convective boundary layer, J. Atmos. Sci., 64, 1230–1248, https://doi.org/10.1175/JAS3888.1, 2007. a
Slingo, J. M.: The development and verification of a cloud prediction scheme for the ECMWF model, Q. J. Roy. Meteor. Soc., 113, 899–927, https://doi.org/10.1002/qj.49711347710, 1987. a
Smith, R. N. B.: A scheme for predicting layer clouds and their water content in a general circulation model. Q. J. Roy. Meteor. Soc., 116, 435–460, https://doi.org/10.1002/qj.49711649210, 1990. a
Stan, C., Khairoutdinov, M., DeMott, C. A., Krishnamurthy, V., Straus, D. M., Randall, D. A., Kinter, J. L., and Shukla, J.: An ocean-atmosphere climate simulation with an embedded cloud resolving model, Geophys. Res. Lett., 37, L01702, https://doi.org/10.1029/2009GL040822, 2010. a
Stevens, B. and Seifert, A.: Understanding macrophysical outcomes of microphysical choices in simulations of shallow cumulus convection, J. Meteorol. Soc. Jpn. Ser. II, 86A, 143–162, https://doi.org/10.2151/jmsj.86A.143, 2008. a, b
Stevens, B., Moeng, C.-H., and Sullivan, P. P.: Large-Eddy Simulations of Radiatively Driven Convection: Sensitivities to the Representation of Small Scales, J. Atmos. Sci., 56, 3963–3984, https://doi.org/10.1175/1520-0469(1999)056<3963:LESORD>2.0.CO;2, 1999. a
Stevens, B., Moeng, C.-H., Ackerman, A. S., Bretherton, C. S., Chlond, A., de Roode, S.and Edwards, J., Golaz, J.-C., Jiang, H., Khairoutdinov, M., Kirkpatrick, M. P., Lewellen, D. C. Lock, A., Müller, F. M., E. Stevens, D., Whelan, E., and Zhu, P.: Evaluation of large-eddy simulations via observations of nocturnal marine stratocumulus, J. Atmos. Sci., 133, 1443–1462, https://doi.org/10.1256/qj.02.202, 2005. a
Stevens, B., Giorgetta, M., Esch, M., Mauritsen, T., Crueger, T., Rast, S., Salzmann, M., Schmidt, H., Bader, J., Block, K., Brokopf, R., Fast, I., Kinne, S., Kornblueh, L., Lohmann, U., Pincus, R., Reichler, T., and Roeckner, E.: Atmospheric component of the MPI-M Earth System Model: ECHAM6, J. Adv. Model. Earth Sy., 5, 146–172, https://doi.org/10.1002/jame.20015, 2013. a, b, c, d
Struthers, H., Ekman, A., Glantz, P., Iversen, T., Kirkevåg, A., Seland, Ø., Mårtensson, E., Noone, K., and Nilsson, E.: Climate-induced changes in sea salt aerosol number emissions: 1870 to 2100, J. Geophys. Res.-Atmos, 118, 670–682, https://doi.org/10.1002/jgrd.50129, 2013. a
Stubenrauch, C. J., Rossow, W. B., Kinne, S., Ackerman, S., Cesana, G., Chepfer, H., Di Girolamo, L., Getzewich, B., Guignard, A., Heidinger, A., Maddux, B., Menzel, P., Minnis, P., Pearl, C., Platnick, S., Poulsen, C., Riedi, J., Sun-Mack, S., Walther, A., Winker, D., Zeng, S., and Zhao, G.: Assessment of global cloud datasets from satellites: Project and database initiated by the GEWEX radiation panel, B. Am. Meteor. Soc., 94, 1031–1049, https://doi.org/10.1175/BAMS-D-12-00117.1, 2013. a
Sullivan, S. C., Lee, D., Oreopoulos, L., and Nenes, A.: Role of updraft velocity in temporal variability of global cloud hydrometeor number, P. Natl Acad. Sci. USA, 113, 5791–5796, https://doi.org/10.1073/pnas.1514039113, 2016. a, b
Sundqvist, H., Berge, E., Kristjánsson, J. E.: Condensation and cloud parameterization studies with a mesoscale numerical weather prediction model, Mon. Weather Rev., 117, 1641–1657, https://doi.org/10.1175/1520-0493(1989)117<1641:CACPSW>2.0.CO;2, 1989. a, b
Suselj, K., Teixeira, J., Kurowski, M. J., and Molod, A.: Improving the representation of subtropical boundary layer clouds in the NASA GEOS model with the eddy-diffusivity/mass-flux parameterization, Mon. Weather Rev., 149, 793–809, https://doi.org/10.1175/MWR-D-20-0183.1, 2021. a
Suzuki, K., Stephens, G., Bodas-Salcedo, A., Wang, M., Golaz, J.-C., Yokohata, T., and Koshiro, T.: Evaluation of the Warm Rain Formation Process in Global Models with Satellite Observations, J. Atmos. Sci., 72, 3996–4014, https://doi.org/10.1175/JAS-D-14-0265.1, 2015. a, b
Tao, W.-K., Anderson, D., Chern, J., Entin, J., Hou, A., Houser, P., Kakar, R., Lang, S., Lau, W., Peters-Lidard, C., Li, X., Matsui, T., Rienecker, M., Schoeberl, M. R., Shen, B.-W., Shi, J. J., and Zeng, X.: The Goddard multi-scale modeling system with unified physics, Ann. Geophys., 27, 3055–3064, https://doi.org/10.5194/angeo-27-3055-2009, 2009. a
Tegen, I., Harrison, S. P., Kohfeld, K., Prentice, I. C., Coe, M., and Heimann, M.: Impact of vegetation and preferential source areas on global dust aerosol: Results from a model study, J. Geophys. Res.-Atmos, 107, 4576, https://doi.org/10.1029/2001JD000963, 2002. a
Tegen, I., Neubauer, D., Ferrachat, S., Siegenthaler-Le Drian, C., Bey, I., Schutgens, N., Stier, P., Watson-Parris, D., Stanelle, T., Schmidt, H., Rast, S., Kokkola, H., Schultz, M., Schroeder, S., Daskalakis, N., Barthel, S., Heinold, B., and Lohmann, U.: The global aerosol–climate model ECHAM6.3–HAM2.3 – Part 1: Aerosol evaluation, Geosci. Model Dev., 12, 1643–1677, https://doi.org/10.5194/gmd-12-1643-2019, 2019. a, b
Teixeira, J., Cardoso, S., Bonazzola, M., Cole, J., DelGenio, A., DeMott, C., Franklin, C., Hannay, C., Jakob, C., Jiao, Y., Karlsson, J., Kitagawa, H., Köhler, M., Kuwano-Yoshida, A., LeDrian, C., Li, J., Lock, A., Miller, M. J., Marquet, P., Martins, J., Mechoso, C. R., van Meijgaard, E., Meinke, I., Miranda, P. M. A., Mironov, D., Neggers, R., Pan., H. L., Randall, D. A., Rasch, P. J., Rockel, B., Rossow, W. B., Ritter, B., Siebesma, A. P., Soares, P. M. M., Turk, F. J., Vaillancourt, P. A., Von Engeln, A., and Zhao, M.: Tropical and subtropical cloud transitions in weather and climate prediction models: The GCSS/WGNE Pacific Cross-Section Intercomparison (GPCI), J. Climate, 24, 5223–5256, https://doi.org/10.1175/2011JCLI3672.1, 2011. a
Teixeira, J., and Hogan, T. F.: Boundary layer clouds in a global atmospheric model: Simple cloud cover parameterizations, J. Climate, 15, 1261–1276, https://doi.org/10.1175/1520-0442(2002)015<1261:BLCIAG>2.0.CO;2, 2002. a
Tiedtke, M.: Representation of clouds in large-scale models. Mon. Weather Rev., 121, 3040–3061, https://doi.org/10.1175/1520-0493(1993)121<3040:ROCILS>2.0.CO;2, 1993 a
Tonttila, J., Maalick, Z., Raatikainen, T., Kokkola, H., Kühn, T., and Romakkaniemi, S.: UCLALES–SALSA v1.0: a large-eddy model with interactive sectional microphysics for aerosol, clouds and precipitation, Geosci. Model Dev., 10, 169–188, https://doi.org/10.5194/gmd-10-169-2017, 2017. a
Tonttila, J., Raatikainen, T., Ahola, J., Kokkola, H., Ruuskanen, A., and Romakkaniemi, S.: UCLALESSALSA/UCLALES-SALSA: Ahola et al., 2021, Zenodo [code], https://doi.org/10.5281/zenodo.5289397, 2021. a
Tselioudis, G., Rossow, W. B., Jakob, C., Remillard, J., Tropf, D., and Zhang, Y.: Evaluation of clouds, radiation, and precipitation in CMIP6 models using global weather states derived from ISCCP-H cloud property data, J. Climate, 34, 7311–7324, https://doi.org/10.1175/JCLI-D-21-0076.1, 2021. a
Van Vuuren, D. P., Edmonds, J., Kainuma, M., Riahi, K., Thomson, A., Hibbard, K., Hurtt, G. C., Kram, T., Krey, V., Lamarque, J.-F., Matsui, T., M., Meinshausen, M., Nakicenovic, N., Smith, S. J., and Rose, S. K.: The representative concentration pathways: an overview, Climatic Change, 109, 5–31, https://doi.org/10.1007/s10584-011-0148-z, 2011. a
Wang, X., Han, Y., Xue, W., Yang, G., and Zhang, G. J.: Stable climate simulations using a realistic general circulation model with neural network parameterizations for atmospheric moist physics and radiation processes, Geosci. Model Dev., 15, 3923–3940, https://doi.org/10.5194/gmd-15-3923-2022, 2022. a
Watanabe, M., Emori, S., Satoh, M., and Miura, H.: A PDF-based hybrid prognostic cloud scheme for general circulation models, Clim. Dynam., 33, 795–816, https://doi.org/10.1007/s00382-008-0489-0, 2009. a
West, R. E. L., Stier, P., Jones, A., Johnson, C. E., Mann, G. W., Bellouin, N., Partridge, D. G., and Kipling, Z.: The importance of vertical velocity variability for estimates of the indirect aerosol effects, Atmos. Chem. Phys., 14, 6369–6393, https://doi.org/10.5194/acp-14-6369-2014, 2014. a, b
Wilson, D. R., Bushell, A. C., Kerr-Munslow, A. M., Price, J. D. and Morcrette, C. J.: PC2: A prognostic cloud fraction and condensation scheme. I: Scheme description. Q. J. Roy. Meteor. Soc., 134, 2093–2107. https://doi.org/10.1002/qj.333, 2008. a
Wood, R.: Stratocumulus Clouds, Mon. Weather Rev., 140, 2373–2423, https://doi.org/10.1175/MWR-D-11-00121.1, 2012. a, b
Yamaguchi, T., Feingold, G., and Larson, V. E.: Framework for improvement by vertical enhancement: A simple approach to improve representation of low and high-level clouds in large-scale models, J. Adv. Model. Earth Sy., 9, 627–646, https://doi.org/10.1002/2016MS000815, 2017. a
Yoshioka, M., Regayre, L. A., Pringle, K. J., Johnson, J. S., Mann, G. W., Partridge, D. G., Sexton, D. M. H., Lister, G. M. S., Schutgens, N., Stier, P., Kipling, Z., Bellouin, N., Browse, J., Booth, B. B. B., Johnson, C. E., Johnson, B., Mollard, J. D. P., Lee, L., and Carslaw, K. S.: Ensembles of Global Climate Model Variants Designed for the Quantification and Constraint of Uncertainty in Aerosols and Their Radiative Forcing, J. Adv. Model. Earth Sy., 11, 3728–3754, https://doi.org/10.1029/2019MS001628, 2019. a, b
Yuval, J. and O'Gorman, P. A.: Stable machine-learning parameterization of subgrid processes for climate modeling at a range of resolutions, Nat. Commun., 11, 3295, https://doi.org/10.1038/s41467-020-17142-3, 2020. a, b
Yuval, J., O'Gorman, P. A., and Hill, C. N.: Use of neural networks for stable, accurate and physically consistent parameterization of subgrid atmospheric processes with good performance at reduced precision, Geophys. Res. Lett., 48, e2020GL091363, https://doi.org/10.1029/2020GL091363, 2021. a
Zheng, Y., Rosenfeld, D., and Li, Z.: Quantifying cloud base updraft speeds of marine stratocumulus from cloud top radiative cooling, Geophys. Res. Lett., 43, 11,407–11,413, https://doi.org/10.1002/2016GL071185, 2016. a
Short summary
Our results show that the global model is stable and it provides meaningful results. This way we can include a physics-based presentation of sub-grid physics (physics which happens on a 100 m scale) in the global model, whose resolution is on a 100 km scale.
Our results show that the global model is stable and it provides meaningful results. This way we...
Altmetrics
Final-revised paper
Preprint