Articles | Volume 20, issue 23
https://doi.org/10.5194/acp-20-15461-2020
© Author(s) 2020. 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-20-15461-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| Highlight paper
| 
11 Dec 2020
Research article | Highlight paper |
| 11 Dec 2020
| 11 Dec 2020
Tropical Pacific climate variability under solar geoengineering: impacts on ENSO extremes
Grantham Institute – Climate Change and the Environment, Imperial
College London,
London, United Kingdom
Oeschger Centre for Climate Change Research and Institute of
Geography, University of
Bern, Bern, Switzerland
King Abdullah University of Science and Technology, Thuwal
23955-6900, Kingdom of Saudi Arabia
Peer J. Nowack
Grantham Institute – Climate Change and the Environment, Imperial
College London,
London, United Kingdom
Blackett Laboratory, Department of Physics, Imperial College London, London,
United Kingdom
Data Science Institute, Imperial College London, London, United Kingdom
School of Environmental Sciences, University of East Anglia, Norwich,
United Kingdom
Joanna D. Haigh
Grantham Institute – Climate Change and the Environment, Imperial
College London,
London, United Kingdom
Blackett Laboratory, Department of Physics, Imperial College London, London,
United Kingdom
Long Cao
School of Earth Sciences, Zhejiang University, Hangzhou, China
Luqman Atique
School of Earth Sciences, Zhejiang University, Hangzhou, China
Yves Plancherel
Grantham Institute – Climate Change and the Environment, Imperial
College London,
London, United Kingdom
Related authors
Mikhaël Schwander, Marco Rohrer, Stefan Brönnimann, and Abdul Malik
Clim. Past, 13, 1199–1212, https://doi.org/10.5194/cp-13-1199-2017, https://doi.org/10.5194/cp-13-1199-2017, 2017
Short summary
Short summary
We used a new classification of daily weather patterns to analyse the influence of solar variability (11-year cycle) on European climate from 1763 to 2009. The analysis of the weather patterns occurrences shows a reduction in the number of days with a westerly flow over Europe under low solar activity during late winter. In parallel, the number of days with an easterly flow increases. Based on these results we expect colder winter over Europe under low solar activity.
Stefan Brönnimann, Abdul Malik, Alexander Stickler, Martin Wegmann, Christoph C. Raible, Stefan Muthers, Julien Anet, Eugene Rozanov, and Werner Schmutz
Atmos. Chem. Phys., 16, 15529–15543, https://doi.org/10.5194/acp-16-15529-2016, https://doi.org/10.5194/acp-16-15529-2016, 2016
Short summary
Short summary
The Quasi-Biennial Oscillation is a wind oscillation in the equatorial stratosphere. Effects on climate have been found, which is relevant for seasonal forecasts. However, up to now only relatively short records were available, and even within these the climate imprints were intermittent. Here we analyze a 108-year long reconstruction as well as four 405-year long simulations. We confirm most of the claimed QBO effects on climate, but they are small, which explains apparently variable effects.
Xiao Lu, Yiming Liu, Jiayin Su, Xiang Weng, Tabish Ansari, Yuqiang Zhang, Guowen He, Yuqi Zhu, Haolin Wang, Ganquan Zeng, Jingyu Li, Cheng He, Shuai Li, Teerachai Amnuaylojaroen, Tim Butler, Qi Fan, Shaojia Fan, Grant L. Forster, Meng Gao, Jianlin Hu, Yugo Kanaya, Mohd Talib Latif, Keding Lu, Philippe Nédélec, Peer Nowack, Bastien Sauvage, Xiaobin Xu, Lin Zhang, Ke Li, Ja-Ho Koo, and Tatsuya Nagashima
EGUsphere, https://doi.org/10.5194/egusphere-2024-3702, https://doi.org/10.5194/egusphere-2024-3702, 2024
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
This study analyzes summertime ozone trends in East and Southeast Asia derived from a comprehensive observational database spanning from 1995 to 2019, incorporating aircraft observations, ozonesonde data, and measurements from 2500 surface sites. Multiple models are applied to attribute to changes in anthropogenic emissions and climate. The results highlight increases in anthropogenic emission are the primary driver of ozone increases both in the free troposphere and at the surface.
Kevin Debeire, Lisa Bock, Peer Nowack, Jakob Runge, and Veronika Eyring
EGUsphere, https://doi.org/10.5194/egusphere-2024-2656, https://doi.org/10.5194/egusphere-2024-2656, 2024
Short summary
Short summary
This study introduces a new method to reduce uncertainty in climate model projections of future precipitation patterns over land. By using advanced causal discovery techniques, our approach improves the reliability of precipitation projections under different global warming scenarios, supporting the development of more effective strategies to address the impacts of climate change.
Sarah Wilson Kemsley, Paulo Ceppi, Hendrik Andersen, Jan Cermak, Philip Stier, and Peer Nowack
Atmos. Chem. Phys., 24, 8295–8316, https://doi.org/10.5194/acp-24-8295-2024, https://doi.org/10.5194/acp-24-8295-2024, 2024
Short summary
Short summary
Aiming to inform parameter selection for future observational constraint analyses, we incorporate five candidate meteorological drivers specifically targeting high clouds into a cloud controlling factor framework within a range of spatial domain sizes. We find a discrepancy between optimal domain size for predicting locally and globally aggregated cloud radiative anomalies and identify upper-tropospheric static stability as an important high-cloud controlling factor.
Peer Nowack and Duncan Watson-Parris
EGUsphere, https://doi.org/10.5194/egusphere-2024-1636, https://doi.org/10.5194/egusphere-2024-1636, 2024
Short summary
Short summary
In our Opinion article, we review uncertainties in global climate change projections and current methods using Earth observations to constrain them, which is crucial for climate risk assessments and for informing society. We then discuss how machine learning can advance the field, discussing recent work that provides potentially stronger and more robust links between observed data and future climate projections. We further discuss challenges of applying machine learning to climate science.
Shuaib Rasheed, Simon C. Warder, Yves Plancherel, and Matthew D. Piggott
Nat. Hazards Earth Syst. Sci., 24, 737–755, https://doi.org/10.5194/nhess-24-737-2024, https://doi.org/10.5194/nhess-24-737-2024, 2024
Short summary
Short summary
Here we use a high-resolution bathymetry dataset of the Maldives archipelago, as well as corresponding high numerical model resolution, to carry out a scenario-based tsunami hazard assessment for the entire Maldives archipelago to investigate the potential impact of plausible far-field tsunamis across the Indian Ocean at the island scale. The results indicate that several factors contribute to mitigating and amplifying tsunami waves at the island scale.
Hendrik Andersen, Jan Cermak, Alyson Douglas, Timothy A. Myers, Peer Nowack, Philip Stier, Casey J. Wall, and Sarah Wilson Kemsley
Atmos. Chem. Phys., 23, 10775–10794, https://doi.org/10.5194/acp-23-10775-2023, https://doi.org/10.5194/acp-23-10775-2023, 2023
Short summary
Short summary
This study uses an observation-based cloud-controlling factor framework to study near-global sensitivities of cloud radiative effects to a large number of meteorological and aerosol controls. We present near-global sensitivity patterns to selected thermodynamic, dynamic, and aerosol factors and discuss the physical mechanisms underlying the derived sensitivities. Our study hopes to guide future analyses aimed at constraining cloud feedbacks and aerosol–cloud interactions.
Suzanne Robinson, Ruza F. Ivanovic, Lauren J. Gregoire, Julia Tindall, Tina van de Flierdt, Yves Plancherel, Frerk Pöppelmeier, Kazuyo Tachikawa, and Paul J. Valdes
Geosci. Model Dev., 16, 1231–1264, https://doi.org/10.5194/gmd-16-1231-2023, https://doi.org/10.5194/gmd-16-1231-2023, 2023
Short summary
Short summary
We present the implementation of neodymium (Nd) isotopes into the ocean model of FAMOUS (Nd v1.0). Nd fluxes from seafloor sediment and incorporation of Nd onto sinking particles represent the major global sources and sinks, respectively. However, model–data mismatch in the North Pacific and northern North Atlantic suggest that certain reactive components of the sediment interact the most with seawater. Our results are important for interpreting Nd isotopes in terms of ocean circulation.
Suzanne Robinson, Ruza Ivanovic, Lauren Gregoire, Lachlan Astfalck, Tina van de Flierdt, Yves Plancherel, Frerk Pöppelmeier, and Kazuyo Tachikawa
EGUsphere, https://doi.org/10.5194/egusphere-2022-937, https://doi.org/10.5194/egusphere-2022-937, 2022
Preprint archived
Short summary
Short summary
The neodymium (Nd) isotope (εNd) scheme in the ocean model of FAMOUS is used to explore a benthic Nd flux to seawater. Our results demonstrate that sluggish modern Pacific waters are sensitive to benthic flux alterations, whereas the well-ventilated North Atlantic displays a much weaker response. In closing, there are distinct regional differences in how seawater acquires its εNd signal, in part relating to the complex interactions of Nd addition and water advection.
Xiang Weng, Grant L. Forster, and Peer Nowack
Atmos. Chem. Phys., 22, 8385–8402, https://doi.org/10.5194/acp-22-8385-2022, https://doi.org/10.5194/acp-22-8385-2022, 2022
Short summary
Short summary
We use machine learning to quantify the meteorological drivers behind surface ozone variations in China between 2015 and 2019. Our novel approaches show improved performance when compared to previous analysis methods. We highlight that nonlinearity in driver relationships and the impacts of large-scale meteorological phenomena are key to understanding ozone pollution. Moreover, we find that almost half of the observed ozone trend between 2015 and 2019 might have been driven by meteorology.
Peer Nowack, Lev Konstantinovskiy, Hannah Gardiner, and John Cant
Atmos. Meas. Tech., 14, 5637–5655, https://doi.org/10.5194/amt-14-5637-2021, https://doi.org/10.5194/amt-14-5637-2021, 2021
Short summary
Short summary
Machine learning (ML) calibration techniques could be an effective way to improve the performance of low-cost air pollution sensors. Here we provide novel insights from case studies within the urban area of London, UK, where we compared the performance of three ML techniques to calibrate low-cost measurements of NO2 and PM10. In particular, we highlight the key issue of the method-dependent robustness in maintaining calibration skill after transferring sensors to different measurement sites.
Carl Thomas, Apostolos Voulgarakis, Gerald Lim, Joanna Haigh, and Peer Nowack
Weather Clim. Dynam., 2, 581–608, https://doi.org/10.5194/wcd-2-581-2021, https://doi.org/10.5194/wcd-2-581-2021, 2021
Short summary
Short summary
Atmospheric blocking events are complex large-scale weather patterns which block the path of the jet stream. They are associated with heat waves in summer and cold snaps in winter. Blocking is poorly understood, and the effect of climate change is not clear. Here, we present a new method to study blocking using unsupervised machine learning. We show that this method performs better than previous methods used. These results show the potential for unsupervised learning in atmospheric science.
Alexander Kuhn-Régnier, Apostolos Voulgarakis, Peer Nowack, Matthias Forkel, I. Colin Prentice, and Sandy P. Harrison
Biogeosciences, 18, 3861–3879, https://doi.org/10.5194/bg-18-3861-2021, https://doi.org/10.5194/bg-18-3861-2021, 2021
Short summary
Short summary
Along with current climate, vegetation, and human influences, long-term accumulation of biomass affects fires. Here, we find that including the influence of antecedent vegetation and moisture improves our ability to predict global burnt area. Additionally, the length of the preceding period which needs to be considered for accurate predictions varies across regions.
James Keeble, Birgit Hassler, Antara Banerjee, Ramiro Checa-Garcia, Gabriel Chiodo, Sean Davis, Veronika Eyring, Paul T. Griffiths, Olaf Morgenstern, Peer Nowack, Guang Zeng, Jiankai Zhang, Greg Bodeker, Susannah Burrows, Philip Cameron-Smith, David Cugnet, Christopher Danek, Makoto Deushi, Larry W. Horowitz, Anne Kubin, Lijuan Li, Gerrit Lohmann, Martine Michou, Michael J. Mills, Pierre Nabat, Dirk Olivié, Sungsu Park, Øyvind Seland, Jens Stoll, Karl-Hermann Wieners, and Tongwen Wu
Atmos. Chem. Phys., 21, 5015–5061, https://doi.org/10.5194/acp-21-5015-2021, https://doi.org/10.5194/acp-21-5015-2021, 2021
Short summary
Short summary
Stratospheric ozone and water vapour are key components of the Earth system; changes to both have important impacts on global and regional climate. We evaluate changes to these species from 1850 to 2100 in the new generation of CMIP6 models. There is good agreement between the multi-model mean and observations, although there is substantial variation between the individual models. The future evolution of both ozone and water vapour is strongly dependent on the assumed future emissions scenario.
Shuaib Rasheed, Simon C. Warder, Yves Plancherel, and Matthew D. Piggott
Ocean Sci., 17, 319–334, https://doi.org/10.5194/os-17-319-2021, https://doi.org/10.5194/os-17-319-2021, 2021
Short summary
Short summary
Environmental issues arising due to coastal modification and future sea level scenarios are a major environmental hazard facing the Maldives today. Here, we carry out high-resolution tidal modelling of a Maldivian atoll for the first time and show that coastal modification in the island scale is capable of driving large-scale change in the wider atoll basin in a short time, comparable to that of long-term sea level rise scenarios and on par with observations.
Yifei Dai, Long Cao, and Bin Wang
Geosci. Model Dev., 13, 3119–3144, https://doi.org/10.5194/gmd-13-3119-2020, https://doi.org/10.5194/gmd-13-3119-2020, 2020
Short summary
Short summary
NESM v3 is one of the CMIP6 registered Earth system models. We evaluate its ocean carbon cycle component and present its present-day and future oceanic CO2 uptake based on the CMIP6 historical and SSP5–8.5 scenarios. We hope that this paper can serve as a documentation of the marine biogeochemical cycle in NESM v3. Also, the model defects found and their underlying causes analyzed in this paper could help users and further model development.
Krishna-Pillai Sukumara-Pillai Krishnamohan, Govindasamy Bala, Long Cao, Lei Duan, and Ken Caldeira
Earth Syst. Dynam., 10, 885–900, https://doi.org/10.5194/esd-10-885-2019, https://doi.org/10.5194/esd-10-885-2019, 2019
Short summary
Short summary
We find that sulfate aerosols are more effective in cooling the climate system when they reside higher in the stratosphere. We explain this sensitivity in terms of radiative forcing at the top of the atmosphere. Sulfate aerosols heat the stratospheric layers, causing an increase in stratospheric water vapor content and a reduction in high clouds. These changes are larger when aerosols are prescribed near the tropopause, offsetting part of the aerosol-induced negative radiative forcing/cooling.
Yifei Dai, Long Cao, and Bin Wang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2018-68, https://doi.org/10.5194/gmd-2018-68, 2018
Revised manuscript not accepted
Short summary
Short summary
NESM-2.0.1 is one of the few models from China that present the ocean carbon cycle simulations. Our results demonstrate that NESM-2.0.1 does a reasonable job in simulating current-day marine ecosystems and oceanic CO2 uptake. The model also can be used as a useful tool in the investigation of feedback interactions between the ocean carbon cycle, atmospheric CO2, and climate change.
William T. Ball, Justin Alsing, Daniel J. Mortlock, Johannes Staehelin, Joanna D. Haigh, Thomas Peter, Fiona Tummon, Rene Stübi, Andrea Stenke, John Anderson, Adam Bourassa, Sean M. Davis, Doug Degenstein, Stacey Frith, Lucien Froidevaux, Chris Roth, Viktoria Sofieva, Ray Wang, Jeannette Wild, Pengfei Yu, Jerald R. Ziemke, and Eugene V. Rozanov
Atmos. Chem. Phys., 18, 1379–1394, https://doi.org/10.5194/acp-18-1379-2018, https://doi.org/10.5194/acp-18-1379-2018, 2018
Short summary
Short summary
Using a robust analysis, with artefact-corrected ozone data, we confirm upper stratospheric ozone is recovering following the Montreal Protocol, but that lower stratospheric ozone (50° S–50° N) has continued to decrease since 1998, and the ozone layer as a whole (60° S–60° N) may be lower today than in 1998. No change in total column ozone may be due to increasing tropospheric ozone. State-of-the-art models do not reproduce lower stratospheric ozone decreases.
William T. Ball, Justin Alsing, Daniel J. Mortlock, Eugene V. Rozanov, Fiona Tummon, and Joanna D. Haigh
Atmos. Chem. Phys., 17, 12269–12302, https://doi.org/10.5194/acp-17-12269-2017, https://doi.org/10.5194/acp-17-12269-2017, 2017
Short summary
Short summary
Several ozone composites show different decadal trends, even in composites built with the same data. We remove artefacts affecting trend analysis with a new method (BASIC) and construct an ozone composite, with uncertainties. We find a significant ozone recovery since 1998 in the midlatitude upper stratosphere, with no hemispheric difference. We recommend using a similar approach to construct a composite based on the original instrument data to improve stratospheric ozone trend estimates.
Lili Xia, Peer J. Nowack, Simone Tilmes, and Alan Robock
Atmos. Chem. Phys., 17, 11913–11928, https://doi.org/10.5194/acp-17-11913-2017, https://doi.org/10.5194/acp-17-11913-2017, 2017
Short summary
Short summary
Ozone is a key air pollutant. We model two geoengineering schemes, stratospheric sulfur injection and solar irradiance reduction, to compare their impacts on atmospheric ozone concentrations. With the nearly identical global mean surface temperature reduction, solar dimming increases global average surface ozone concentration, while sulfate injection decreases it. This difference is due to different stratosphere–troposphere exchange of ozone and tropospheric ozone chemistry in the two scenarios.
Mikhaël Schwander, Marco Rohrer, Stefan Brönnimann, and Abdul Malik
Clim. Past, 13, 1199–1212, https://doi.org/10.5194/cp-13-1199-2017, https://doi.org/10.5194/cp-13-1199-2017, 2017
Short summary
Short summary
We used a new classification of daily weather patterns to analyse the influence of solar variability (11-year cycle) on European climate from 1763 to 2009. The analysis of the weather patterns occurrences shows a reduction in the number of days with a westerly flow over Europe under low solar activity during late winter. In parallel, the number of days with an easterly flow increases. Based on these results we expect colder winter over Europe under low solar activity.
Stefan Brönnimann, Abdul Malik, Alexander Stickler, Martin Wegmann, Christoph C. Raible, Stefan Muthers, Julien Anet, Eugene Rozanov, and Werner Schmutz
Atmos. Chem. Phys., 16, 15529–15543, https://doi.org/10.5194/acp-16-15529-2016, https://doi.org/10.5194/acp-16-15529-2016, 2016
Short summary
Short summary
The Quasi-Biennial Oscillation is a wind oscillation in the equatorial stratosphere. Effects on climate have been found, which is relevant for seasonal forecasts. However, up to now only relatively short records were available, and even within these the climate imprints were intermittent. Here we analyze a 108-year long reconstruction as well as four 405-year long simulations. We confirm most of the claimed QBO effects on climate, but they are small, which explains apparently variable effects.
Peer Johannes Nowack, Nathan Luke Abraham, Peter Braesicke, and John Adrian Pyle
Atmos. Chem. Phys., 16, 4191–4203, https://doi.org/10.5194/acp-16-4191-2016, https://doi.org/10.5194/acp-16-4191-2016, 2016
Short summary
Short summary
Various forms of solar radiation management (SRM) have been proposed to counteract man-made climate change. However, all these countermeasures could have unintended side-effects. We add a novel perspective to this discussion by showing how atmospheric ozone changes under solar geoengineering could affect UV exposure and air pollution. This would have implications for human health and ecology. Atmospheric composition changes are therefore important to consider in the evaluation of any SRM scheme.
S. S. Dhomse, M. P. Chipperfield, W. Feng, W. T. Ball, Y. C. Unruh, J. D. Haigh, N. A. Krivova, S. K. Solanki, and A. K. Smith
Atmos. Chem. Phys., 13, 10113–10123, https://doi.org/10.5194/acp-13-10113-2013, https://doi.org/10.5194/acp-13-10113-2013, 2013
Related subject area
Subject: Hydrosphere Interactions | Research Activity: Atmospheric Modelling and Data Analysis | Altitude Range: Troposphere | Science Focus: Physics (physical properties and processes)
Towards kilometer-scale ocean–atmosphere–wave coupled forecast: a case study on a Mediterranean heavy precipitation event
The impact of sea waves on turbulent heat fluxes in the Barents Sea according to numerical modeling
Simulation of the radiative effect of haze on the urban hydrological cycle using reanalysis data in Beijing
A new roughness length parameterization accounting for wind–wave (mis)alignment
Tracing changes in atmospheric moisture supply to the drying Southwest China
The incorporation of an organic soil layer in the Noah-MP land surface model and its evaluation over a boreal aspen forest
The impacts of moisture transport on drifting snow sublimation in the saltation layer
On the importance of cascading moisture recycling in South America
Sensitivity of high-temperature weather to initial soil moisture: a case study using the WRF model
On the "well-mixed" assumption and numerical 2-D tracing of atmospheric moisture
How relevant is the deposition of mercury onto snowpacks? – Part 1: A statistical study on the impact of environmental factors
How relevant is the deposition of mercury onto snowpacks? – Part 2: A modeling study
César Sauvage, Cindy Lebeaupin Brossier, and Marie-Noëlle Bouin
Atmos. Chem. Phys., 21, 11857–11887, https://doi.org/10.5194/acp-21-11857-2021, https://doi.org/10.5194/acp-21-11857-2021, 2021
Short summary
Short summary
Air–sea processes are key elements during Mediterranean heavy precipitation events. We aim to progress in their representation in high-resolution weather forecast. Using coupled ocean–air–wave simulations, we investigated air–sea mechanisms modulated by ocean and waves during a case that occurred in southern France. Results showed significant impact of the forecast on low-level dynamics and air–sea fluxes and illustrated potential benefits of coupled numerical weather prediction systems.
Stanislav Myslenkov, Anna Shestakova, and Dmitry Chechin
Atmos. Chem. Phys., 21, 5575–5595, https://doi.org/10.5194/acp-21-5575-2021, https://doi.org/10.5194/acp-21-5575-2021, 2021
Tom V. Kokkonen, Sue Grimmond, Sonja Murto, Huizhi Liu, Anu-Maija Sundström, and Leena Järvi
Atmos. Chem. Phys., 19, 7001–7017, https://doi.org/10.5194/acp-19-7001-2019, https://doi.org/10.5194/acp-19-7001-2019, 2019
Short summary
Short summary
This is the first study to evaluate and correct the WATCH WFDEI reanalysis product in a highly polluted urban environment. It gives an important understanding of the uncertainties in reanalysis products in local-scale urban modelling in polluted environments and identifies and corrects the most important variables in hydrological modelling. This is also the first study to examine the effects of haze on the local-scale urban hydrological cycle.
Sara Porchetta, Orkun Temel, Domingo Muñoz-Esparza, Joachim Reuder, Jaak Monbaliu, Jeroen van Beeck, and Nicole van Lipzig
Atmos. Chem. Phys., 19, 6681–6700, https://doi.org/10.5194/acp-19-6681-2019, https://doi.org/10.5194/acp-19-6681-2019, 2019
Short summary
Short summary
Two-way feedback occurs between offshore wind and waves. Using an extensive data set of offshore measurements, we show that the wave roughness affecting the wind is dependent on the alignment between the wind and wave directions. Moreover, we propose a new roughness parameterization that takes into account the dependence on alignment. Using this in numerical models will facilitate a better representation of offshore wind, which is relevant to wind energy and and climate modeling.
Chi Zhang, Qiuhong Tang, Deliang Chen, Laifang Li, Xingcai Liu, and Huijuan Cui
Atmos. Chem. Phys., 17, 10383–10393, https://doi.org/10.5194/acp-17-10383-2017, https://doi.org/10.5194/acp-17-10383-2017, 2017
Short summary
Short summary
Precipitation over Southwest China (SWC) has decreased significantly in recent years. By tracking precipitation moisture, we found that the reduced precipitation results from the reduced moisture supply from the extended west, which is influenced by the South Asian summer monsoon and the westerlies. Further study revealed the dynamic variations in circulation dominate the interannual variations in SWC precipitation. Changes in circulation systems may be related to the recent changes in SSTs.
Liang Chen, Yanping Li, Fei Chen, Alan Barr, Michael Barlage, and Bingcheng Wan
Atmos. Chem. Phys., 16, 8375–8387, https://doi.org/10.5194/acp-16-8375-2016, https://doi.org/10.5194/acp-16-8375-2016, 2016
Short summary
Short summary
This work is the first time that Noah-MP is used to investigate the impact of parameterizing organic soil at a boreal forest site. Including an organic soil parameterization significantly improved performance of the model in surface energy and hydrology simulations due to the lower thermal conductivity and greater porosity of the organic soil. It substantially modified the partition between direct soil evaporation and vegetation transpiration in the simulation.
Ning Huang, Xiaoqing Dai, and Jie Zhang
Atmos. Chem. Phys., 16, 7523–7529, https://doi.org/10.5194/acp-16-7523-2016, https://doi.org/10.5194/acp-16-7523-2016, 2016
Short summary
Short summary
Drifting snow sublimation (DSS) is of glaciological and hydrological importance. This work is related to the simulation of DSS, which is obviously related to the scientific topics, such as multi-field coupling of wind, snow particles, humidity, etc. Previous studies argued that sublimation will soon vanish in saltation layer. This work shows the sublimation rate of saltating snow can be several orders of magnitude greater than that of the suspended snow due to the impact of moisture advection.
D. C. Zemp, C.-F. Schleussner, H. M. J. Barbosa, R. J. van der Ent, J. F. Donges, J. Heinke, G. Sampaio, and A. Rammig
Atmos. Chem. Phys., 14, 13337–13359, https://doi.org/10.5194/acp-14-13337-2014, https://doi.org/10.5194/acp-14-13337-2014, 2014
X.-M. Zeng, B. Wang, Y. Zhang, S. Song, X. Huang, Y. Zheng, C. Chen, and G. Wang
Atmos. Chem. Phys., 14, 9623–9639, https://doi.org/10.5194/acp-14-9623-2014, https://doi.org/10.5194/acp-14-9623-2014, 2014
H. F. Goessling and C. H. Reick
Atmos. Chem. Phys., 13, 5567–5585, https://doi.org/10.5194/acp-13-5567-2013, https://doi.org/10.5194/acp-13-5567-2013, 2013
D. A. Durnford, A. P. Dastoor, A. O. Steen, T. Berg, A. Ryzhkov, D. Figueras-Nieto, L. R. Hole, K. A. Pfaffhuber, and H. Hung
Atmos. Chem. Phys., 12, 9221–9249, https://doi.org/10.5194/acp-12-9221-2012, https://doi.org/10.5194/acp-12-9221-2012, 2012
D. Durnford, A. Dastoor, A. Ryzhkov, L. Poissant, M. Pilote, and D. Figueras-Nieto
Atmos. Chem. Phys., 12, 9251–9274, https://doi.org/10.5194/acp-12-9251-2012, https://doi.org/10.5194/acp-12-9251-2012, 2012
Cited articles
Adler, R. F., Huffman, G. J., Chang, A., Ferraro, R., Xie, P-P., Janowiak,
J., Rudolf, B., Schneider, U., Curtis, S., Bolvin, D., Gruber, A., Susskind,
J., Arkin, P., and Nelkin, E.: The version-2 Global Precipitation
Climatology Project (GPCP) monthly precipitation analysis (1979–Present),
J. Hydrometeorol., 4, 1147–1167, 2003.
An II., S. and Jin, F.-F.: Nonlinearity and Asymmetry of ENSO, J. Climate,
17, 2399–2412, 2004.
Bala, G., Duffy, P. B., and Taylor, K. E.: Impact of geoengineering schemes
on the global hydrological cycle, P. Natl. Acad. Sci. USA, 105, 7664–7669, https://doi.org/10.1073/pnas.0711648105, 2008.
Bayr, T., Dommenget, D., Martin, T., and Power, S. B.: The eastward shift of
the Walker circulation in response to global warming and its relationship to
ENSO variability, Clim. Dynam., 43, 2747–2763,
https://doi.org/10.1007/s00382-014-2091-y, 2014.
Bellenger, H., Guilyardi, E., Leloup, J., Lengaigne, M., and Vialard, J.:
ENSO representation in climate models: from CMIP3 to CMIP5, Clim. Dynam., 42,
1999–2018, https://doi.org/10.1007/s00382-013-1783-z, 2014.
Boer, G. J., Yu, B., Kim, S., and Flato, G. M.: Is there observational
support for an El Niño-like pattern of future global warming?, Geophys.
Res. Lett., 31, 1–4, https://doi.org/10.1029/2003GL018722, 2004.
Bove, M. C., Elsner, J. B., Landsea, C. W., Niu, X., and O Brien, J. J.:
Effect of El Niño on U.S. landfalling hurricanes, revisited, B. Am.
Meteorol. Soc., 79, 2477–2482, 1998.
Cai, W., Borlace, S., Lengaigne, M., van Rensch, P., Collins, M., Vecchi,
G., Timmermann, A., Santoso, A., McPhaden, M. J., Wu, L., England, M. H.,
Wang, G., Guilyardi, E., and Jin, F-F.: Increasing frequency of extreme El
Niño events due to greenhouse warming, Nat. Clim. Change, 4,
111–116, https://doi.org/10.1038/nclimate2100, 2014.
Cai, W., Santoso, A., Wang, G., Yeh, S. W., An, S. Il, Cobb, K. M., Collins,
M., Guilyardi, E., Jin, F-F., Kug, J-S., Lengaigne, M., McPhaden, M. J.,
Takahashi, K., Timmermann, A., Vecchi, G., Watanabe, M., and Wu, L.: ENSO
and greenhouse warming, Nat. Clim. Change., 5, 849–859,
https://doi.org/10.1038/nclimate2743, 2015a.
Cai, W., Wang, G., Santoso, A., Mcphaden, M. J., Wu, L., Jin, F-F.,
Timmermann, A., Collins, M., Vecchi, G., Lengaigne, M., England, M. H.,
Dommenget, D., Takahashi, K., and Guilyardi, E.: Increased frequency of
extreme La Niña events under greenhouse warming, Nat. Clim. Change,
5, 132–137, https://doi.org/10.1038/nclimate2492, 2015b.
Cai, W., Wang, G., Dewitte, B., Wu, L., Santoso, A., Takahashi, K., Yang,
Y., Carréric, A., and McPhaden, M. J.: Increased variability of eastern
Pacific El Niño greenhouse warming, Nature, 564, 201–206,
https://doi.org/10.1038/s41586-018-0776-9, 2018.
Cai, W., Wang, G., Santoso, A., Lin, X., and Wu, L.: Definition of Extreme
El Niño and Its Impact on Projected Increase in Extreme El Niño
Frequency, Geophys. Res. Lett., 44, 11184–11190,
https://doi.org/10.1002/2017GL075635, 2017.
Cao, L., Duan, L., Bala, G., and Caldeira, K.: Simulated long-term climate
response to idealised solar geoengineering, Geophys. Res. Lett., 43,
2209–2217, https://doi.org/10.1002/2016GL068079, 2016.
Capotondi, A., Wittenberg, A., and Masina, S.: Spatial and temporal
structure of Tropical Pacific interannual variability in 20th century
coupled simulations, Ocean. Model., 15, 274–298,
https://doi.org/10.1016/j.ocemod.2006.02.004, 2006.
Chen, L., Li, T., Yu, Y., and Behera, S. K.: A possible explanation for the
divergent projection of ENSO amplitude change under global warming, Clim.
Dynam., 49, 3799–3811, https://doi.org/10.1007/s00382-017-3544-x,
2017.
Chung, C. T. Y., Power, S. B., Arblaster, J. M., Rashid, H. A., and Roff, G.
L.: Non-linear precipitation response to El Niño and global warming in
the Indo-Pacific, Clim. Dynam., 42, 1837–1856,
https://doi.org/10.1007/s00382-013-1892-8, 2014.
Coats, S. and Karnauskas, K. B.: Are Simulated and Observed
Twentieth-Century Tropical Pacific Sea Surface Temperature Trends
Significant Relative to Internal Variability?, Geophys. Res. Lett., 44,
9928–9937, https://doi.org/10.1002/2017GL074622, 2017.
Collins, M., An, S.-I., Cai, W., Ganachaud, A., Guilyardi, E., Jin, F.-F.,
Jochum, M., Lengaigne, M., Power, S., Timmermann, A., Vecchi, G., and
Wittenberg, A.: The impact of global warming on the tropical Pacific Ocean
and El Niño, Nat. Geosci., 3, 391–397,
https://doi.org/10.1038/ngeo868, 2010.
Cox, P. M., Betts, R. A., Jones, C. D., Spall, S. A., and Totterdell, I. J.:
Acceleration of global warming due to carbon-cycle feedbacks in a coupled
climate model, Nature, 408, 184–187, https://doi.org/10.1038/35041539, 2000.
Crutzen, P. J.: Albedo enhancement by stratospheric sulfur injections: A
contribution to resolve a policy dilemma?, Climatic Change, 77,
211–219, https://doi.org/10.1007/s10584-006-9101-y, 2006.
Curry, C. L., Sillmann, J., Bronaugh, D., Alterskjaer, K., Cole, J. N. S.,
Ji, D., Kravitz, B., Kristjánsson, J. E., Moore, J. C., Muri, H.,
Niemeier, U., Robock, A., Tilmes, S., and Yang, S.: A multimodel examination
of climate extremes in an idealised geoengineering experiment, J. Geophys.
Res.-Atmos., 119, 3900–3923, https://doi.org/10.1002/2013JD020648, 2014.
Dewitte, B., Yeh, S-W., and Thual, S.: Reinterpreting the thermocline
feedback in the western-central equatorial Pacific and its relationship with
the ENSO modulation, Clim. Dynam., 41, 819–830,
https://doi.org/10.1007/s00382-012-1504-z, 2013.
Essery, R. and Clark, D. B.: Developments in the MOSES 2 land-surface model
for PILPS 2e, Glob. Planet. Change, 38, 161–164,
https://doi.org/10.1016/S0921-8181(03)00026-2, 2003.
Ferret, S. and Collins, M.: ENSO feedbacks and their relationships with the
mean state
in a flux adjusted ensemble, Clim. Dynam., 52, 7189–7208,
https://doi.org/10.1007/s00382-016-3270-9, 2019.
Gabbie, G., Eisenman, I., Wittenberg, A., and Tziperman, E.: Modulation of
Westerly Wind Bursts by Sea Surface Temperature: A Semistochastic Feedback
for ENSO, J. Atmos. Sci., 64, 3281–3295,
https://doi.org/10.1175/JAS4029.1, 2007.
Gabriel, C. J. and Robock, A.: Stratospheric geoengineering impacts on El
Niño/Southern Oscillation, Atmos. Chem. Phys., 15, 11949–11966,
https://doi.org/10.5194/acp-15-11949-2015, 2015.
Gandhi, S. M. and Sarkar B. C.: Conventional and Statistical Resource/Reserve Estimation, in: Essentials of Mineral Exploration and Evaluation, 1st Edn., editted by: Gandhi, S. M. and Sarkar B. C., Elsevier, Amsterdam, the Netherlands, 271–288,
https://doi.org/10.1016/C2015-0-04648-2, 2016.
Gibbons, J. D. and Chakraborti, S.: Nonparametric Statistical Inference,
5th Ed., Statistics: Textbooks and Monographs, Chapman and Hall/CRC Press,
Taylor and Francis Group, 195–219, 2011.
Govindasamy, B. and Caldeira, K.: Geoengineering Earth's radiation balance
to mitigate CO2-induced climate change, Geophys. Res. Lett., 27,
2141–2144, https://doi.org/10.1029/1999GL006086, 2000.
Guilyardi, E.: El Niño–mean state–seasonal cycle interactions in a
multimodel ensemble, Clim. Dynam., 26, 329–348,
https://doi.org/10.1007/s00382-005-0084-6, 2006.
Guo, A., Moore, J. C., and Ji, D.: Tropical atmospheric circulation response
to the G1 sunshade geoengineering radiative forcing experiment, Atmos. Chem.
Phys., 18, 8689–8706, https://doi.org/10.5194/acp-18-8689-2018, 2018.
Ham, Y.: A reduction in the asymmetry of ENSO amplitude due to global
warming: The role of atmospheric feedback, Geophys. Res. Lett., 44,
8576–8584, https://doi.org/10.1002/2017GL074842, 2017.
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 monthly averaged data on single levels from 1979 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS), https://doi.org/10.24381/cds.f17050d7 (24 January 2020), 2019.
Hollander, M., Wolfe, D. A., and Chicken, E.: Nonparametric Statistical Methods, 3rd Ed., John Wiley and Sons, Inc., Hoboken, New Jersey, USA, 115-149, 2014.
Hong, Y., Moore J. C., Jevrejeva, S., Ji, D., Phipps, S. J., Lenton, A.,
Tilmes, S., Watanabe, S., and Zhao, L.: Impact of the GeoMIP G1 sunshade
geoengineering experiment on the Atlantic meridional overturning
circulation, Environ. Res. Lett., 12, 034009,
https://doi.org/10.1088/1748-9326/aa5fb8, 2017.
Hu, S. and Fedorov, A. V.: Exceptionally strong easterly wind burst
stalling El Niño of 2014, P. Natl. Acad. Sci. USA, 113, 2005–2010,
https://doi.org/10.1073/pnas.1514182113, 2016.
Huang, P. and Ying, J.: A multimodel ensemble pattern regression method to
correct the tropical pacific SST change patterns under global warming, J.
Climate, 28, 4706–4723, https://doi.org/10.1175/JCLI-D-14-00833.1,
2015.
Kao, H.-Y. and Yu, J.-Y.: Contrasting Eastern-Pacific and Central-Pacific
Types of ENSO, J. Climate, 22, 615–632,
https://doi.org/10.1175/2008JCLI2309.1, 2009.
Kim, S. T. and Jin, F.-F.: An ENSO stability analysis, Part I: results from
a hybrid
coupled model, Clim Dynam., 36, 1593–1607, https://doi.10.1007/s00382-010-0796-0, 2011a.
Kim, S. T. and Jin, F.-F.: An ENSO stability analysis, Part II: results from
the twentieth
and twenty-first century simulations of the CMIP3 models, Clim. Dynam., 36,
1609–1627, https://doi.10.1007/s00382-010-0872-5, 2011b.
Kim, S. T., Cai, W., Jin, F.-F., Santoso, A., Wu, L., Guilyardi, E., and An,
S.-I.: Response of El Niño sea surface temperature variability to
greenhouse warming, Nat. Clim. Change, 4, 786–790,
https://doi.org/10.1038/nclimate2326, 2014.
Knutson, T. R. and Manabe, S.: Impact of increased CO2 on simulated
ENSO-like phenomena, Geophys. Res. Lett., 21, 2295–2298,
https://doi.org/10.1029/94GL02152, 1994.
Kohyama, T., Hartmann, D. L., and Battisti, D. S.: La Niña-like
mean-state response to global warming and potential oceanic roles, J.
Climate, 30, 4207–4225, https://doi.org/10.1175/JCLI-D-16-0441.1,
2017.
Kravitz, B., Robock, A., Boucher, O., Schmidt, H., Taylor, K. E.,
Stenchikov, G., and Schulz, M.: The Geoengineering Model Intercomparison
Project (GeoMIP), Atmos. Sci. Lett., 12, 162–167,
https://doi.org/10.1002/asl.316, 2011.
Kravitz, B., Forster, P. M., Jones, A., Robock, A., Alterskjær, K.,
Boucher, O., Jenkins, A. K. L., Korhonen, H., Kristjánsson, J. E., Muri
H., Niemeier, U., Partanen, A.-I., Rasch, P. J., Wang, H., and Watanabe, S.:
Sea spray geoengineering experiments in the geoengineering model
intercomparison project (GeoMIP): Experimental design and preliminary
results, J. Geophys. Res.-Atmos., 118, 11175–11186,
https://doi.org/10.1002/jgrd.50856, 2013a.
Kravitz, B., Caldeira, K., Boucher, O., Robock, A., Rasch, P. J.,
Alterskjær, K., Karam, D. B., Cole, J. N. S., Curry, C. L., Haywood, J.
M., Irvine, P. J., Ji, D., Jones, A., Kristjánsson, J. E., Lunt D. J.,
Moore, J. C., Niemeier, U., Schmidt, H., Schulz, M., Singh, B., Tilmes, S.,
Watanabe, S., Yang, S., and Yoon, J.-H.: Climate model response from the
Geoengineering Model Intercomparison Project (GeoMIP), J. Geophys.
Res.-Atmos., 118, 8320–8332, https://doi.org/10.1002/jgrd.50646, 2013b.
Kravitz, B., Robock, A., Tilmes, S., Boucher, O., English, J. M., Irvine, P.
J., Jones, A., Lawrence, M. G., MacCracken, M., Muri, H., Moore, J. C.,
Niemeier, U., Phipps, S. J., Sillmann, J., Storelvmo, T., Wang, H., and
Watanabe, S.: The Geoengineering Model Intercomparison Project Phase 6
(GeoMIP6): simulation design and preliminary results, Geosci. Model Dev., 8,
3379–3392, https://doi.org/10.5194/gmd-8-3379-2015, 2015.
Latif, M. and Keenlyside, N. S.: El Niño/Southern Oscillation response
to global warming, P. Natl. Acad. Sci. USA, 106, 20578–20583,
https://doi.org/10.1073/pnas.0710860105, 2009.
Liu, Z., Vavrus, S., He, F., Wen, N., and Zhong, Y.: Rethinking tropical
ocean response to global warming: The enhanced equatorial warming, J.
Climate, 18, 4684–4700, https://doi.org/10.1175/JCLI3579.1, 2005.
Lloyd, J., Guilyardi, E., and Weller, H.: The role of atmosphere feedbacks
during ENSO in the CMIP3 models, Part II: using AMIP runs to understand the
heat flux feedback mechanisms, Clim. Dynam., 37, 1271–1292,
https://doi.org/10.1007/s00382-010-0895-y, 2011.
Lloyd, J. E., Guilyardi, E., Weller, H., and Slingo, J.: The role of
atmosphere feedbacks during ENSO in the CMIP3 models, Atmos. Sci. Lett., 10,
170–176, https://doi.org/10.1002/asl.227170-176, 2009.
Lunt, D. J., Ridgwell, A., Valdes, P. J., and Seale, A.: Sunshade World: A
fully coupled GCM evaluation of the climatic impacts of geoengineering,
Geophys. Res. Lett., 35, L12710, https://doi.org/10.1029/2008GL033674, 2008.
Luo, Y., Lu, J., Liu, F., and Liu, W.: Understanding the El Niño-like
oceanic response in the tropical Pacific to global warming, Clim. Dynam.,
45, 1945–1964, https://doi.org/10.1007/s00382-014-2448-2, 2015.
Malik, A., Brönnimann, S., Stickler, A., Raible, C. C., Muthers, S.,
Anet, J., Rozanov, E., and Schmutz, W.: Decadal to multi-decadal scale
variability of Indian summer monsoon rainfall in the coupled
ocean-atmosphere-chemistry climate model SOCOL-MPIOM, Clim. Dynam.,
49, 3551–3572, https://doi.org/10.1007/s00382-017-3529-9, 2017.
Meehl G. A. and Washington, W. M.: El Niño like climate change in a
model with increased atmospheric CO2 concentrations, Nature, 382, 56–60, 1996.
Moore, T. R., Matthews, H. D., Simmons, C., and Leduc, M.: Quantifying
changes in extreme weather events in response to warmer global temperature,
Atmos. Ocean., 53, 412–425,
https://doi.org/10.1080/07055900.2015.1077099, 2015.
Nowack, P. J., Abraham, N. L., Maycock, A. C., Braesicke, P., Gregory, J.
M., Joshi, M. M., Osprey, A., and Pyle, J. A.: A large ozone-circulation
feedback and its implications for global warming assessments, Nat. Clim.
Change, 5, 41–45, https://doi.org/10.1038/nclimate2451, 2015.
Nowack, P. J., Abraham, N. L., Braesicke, P., and Pyle, J. A.: Stratospheric
ozone changes under solar geoengineering: implications for UV exposure and
air quality, Atmos. Chem. Phys., 16, 4191–4203,
https://doi.org/10.5194/acpd-15-31973-2015, 2016.
Nowack, P. J., Braesicke, P., Abraham, N. L., and Pyle J. A.: On the role of
ozone feedback in the ENSO amplitude response under global warming, Geophys.
Res. Lett., 44, 3858–3866, https://doi.org/10.1002/2016GL072418, 2017.
Nowack, P. J., Abraham, N. L., Braesicke, P., and Pyle J. A.: The impact of
stratospheric ozone feedbacks on climate sensitivity estimates, J. Geophys.
Res.-Atmos., 123, 4630–4641, https://doi.org/10.1002/2017JD027943, 2018.
Ohba, M. and Ueda, H.: Role of non-linear atmospheric response to SST on the
asymmetric transition process of ENSO, J. Clim., 22, 177–192,
https://doi.org/10.1175/2008JCLI2334.1, 2009.
Pachauri, R. K., Allen, M. R., Barros, V. R., Broome, J., Cramer, W.,
Christ, R., Church, J. A., Clarke, L., Dahe, Q., Dasgupta, P., Dubash, N.
K., Edenhofer, O., Elgizouli, I., Field, C. B., Forster, P., Friedlingstein,
P., Fuglestvedt, J., Gomez-Echeverri, L., Hallegatte, S., Hegerl, G.,
Howden, M., Jiang, K., Jimenez Cisneroz, B., Kattsov, V., Lee, H., Mach, K.
J., Marotzke, J., Mastrandrea, M. D., Meyer, L., Minx, J., Mulugetta, Y.,
O'Brien, K., Oppenheimer, M., Pereira, J. J., Pichs-Madruga, R., Plattner,
G. K., Pörtner, H. O., Power, S. B., Preston, B., Ravindranath, N. H.,
Reisinger, A., Riahi, K., Rusticucci, M., Scholes, R., Seyboth, K., Sokona,
Y., Stavins, R., Stocker, T. F., Tschakert, P., van Vuuren, D., and van
Ypserle, J. P.: Climate change 2014: synthesis report, contribution of
Working Groups I, II and III to the Fifth Assessment Report of the
Intergovernmental Panel on Climate Change, edited by: Pachauri, R. and Meyer, L.,
Geneva, Switzerland, IPCC, p. 151, ISBN: 978-92-9169-143-2, 2014.
Park, W., Keenlyside, N., Latif, M., Ströh, A., Redler, R., Roeckner,
E., and Madec, G.: Tropical Pacific climate and its response to global
warming in the Kiel Climate Model, J. Climate, 22, 71–92,
https://doi.org/10.1175/2008JCLI2261.1, 2009.
Philip, S. Y. and van Oldenborgh, G. J.: Shifts in ENSO coupling processes
under global warming, Geophys. Res. Lett., 33, 1–5,
https://doi.org/10.1029/2006GL026196, 2006.
Power, S., Delage, F., Chung, C., Kociuba, G., and Keay, K.: Robust
twenty-first-century projections of El Niño and related precipitation
variability, Nature, 502, 541–545, https://doi.org/10.1038/nature12580,
2013.
Rayner, N. A., Parker, D. E., Horton, E. B., Folland, C. K., Alexander, L.
V, Rowell, D. P., and Kaplan, A.: Global analyses of sea surface
temperature, sea ice, and night marine air temperature since the late
nineteenth century, J. Geophys. Res.-Atmos., 108, 1063–1082,
https://doi.org/10.1029/2002JD002670, 2003.
Ropelewski, C. F. and Halpert, M. S.: Global and regional scale
precipitation patterns associated with the El Niño/Southern Oscillation,
Mon. Weather Rev., 115, 1606–1626, https://doi.org/10.1175/1520-0493(1987)115<1606:GARSPP>2.0.CO;2, 1987.
Santoso, A., Mcphaden, M. J., and Cai, W.: The defining characteristics of
ENSO extremes and the strong 2015/2016 El Niño, Rev. Geophys., 55,
1079–1129, https://doi.org/10.1002/2017RG000560, 2017.
Schmidt, H., Alterskjær, K., Alterskjær, K., Bou Karam, D., Boucher,
O., Jones, A., and Timmreck, C.: Solar irradiance reduction to counteract
radiative forcing from a quadrupling of CO2: climate responses simulated by
four earth system models, Earth. Syst. Dynam., 3, 63–78,
https://doi.org/10.5194/esd-3-63-2012, 2012.
Schopf, P. S. and Burgman, R. J.: A simple mechanism for ENSO residuals and
asymmetry, J. Climate, 19, 3167–3179, 2006.
Stevenson, S. and Fox-Kemper, B.: ENSO model validation using wavelet
probability analysis, J. Climate, 23, 5540–5547,
https://doi.org/10.1175/2010JCLI3609.1, 2010.
Stocker, T. F., Qin D., Plattner, G. K., Tignor M., Allen, S. K., Boschung,
J., Nauels, A., Xia, Y., Bex, V., and Midgley P. M.: Summary for
Policymakers, in: Climate Change 2013: The Physical Science Basis.
Contribution of Working Group I to the Fifth Assessment Report of the
Intergovernmental Panel on Climate Change, Cambridge University Press,
Cambridge, UK and New York, NY, USA,
https://doi.org/10.1017/CBO9781107415324.004, 2013.
Sun, N., Zhou, T., Chen, X., Endo, H., Kitoh, A., and Wu, B.: Amplified
tropical Pacific rainfall variability related to background SST warming,
Clim. Dynam., 54, 2387–2402, https://doi.org/10.1007/s00382-020-05119-3, 2020.
Takahashi, K., Montecinos, A., Goubanova, K., and Dewitte, B.: ENSO regimes:
Reinterpreting the canonical and Modoki El Niño, Geophys. Res. Lett.,
38, L10704, https://doi.org/10.1029/2011GL047364, 2011.
Tilmes, S., Richter, J. H., Kravitz, B., MacMartin, D. G., Mills, M. J.,
Simpson, I. R., Glanville, A. S., Fasullo, J. T., Phillips, A. S., Lamarque,
J., Tribbia, J., Edwards, J., Mickelson, S., and Gosh, S.: CESM1(WACCM)
Stratospheric Aerosol Geoengineering Large Ensemble (GLENS) Project, Bull.
Am. Meteorol. Soc., 99, 2361–2371,
https://doi.org/10.1175/BAMS-D-17-0267.1, 2018.
Valdes, P. J., Armstrong, E., Badger, M. P. S., Bradshaw, C. D., Bragg, F.,
Crucifix, M., Davies-Barnard, T., Day, J. J., Farnsworth, A., Gordon, C.,
Hopcroft, P. O., Kennedy, A. T., Lord, N. S., Lunt, D. J., Marzocchi, A.,
Parry, L. M., Pope, V., Roberts, W. H. G., Stone, E. J., Tourte, G. J. L.,
and Williams, J. H. T.: The BRIDGE HadCM3 family of climate models:
HadCM3@Bristol v1.0, Geosci. Model Dev., 10, 3715–3743,
https://doi.org/10.5194/gmd-10-3715-2017, 2017.
van Oldenborgh, G. J., Philip, S. Y., and Collins, M.: El Niño in a
changing climate: A multimodel study, Ocean. Sci., 1, 81–95,
https://doi.org/10.5194/os-1-81-2005, 2005.
Vecchi, G. A. and Soden, B. J.: Global warming and the weakening of
the tropical circulation, J. Climate, 20, 4316–4340,
https://doi.org/10.1175/JCLI4258.1, 2007.
Vecchi, G. A. and Wittenberg, A. T.: El Niño and our future climate:
where do we stand? Wiley Interdiscip, Rev. Clim. Change, 1, 260–270,
https://doi.org/10.1002/wcc.33, 2010.
Vecchi, G. A., Soden, B. J., Wittenberg, A. T., Held, I. M., Leetmaa, A.,
and Harrison, M. J: Weakening of tropical Pacific atmospheric circulation
due to anthropogenic forcing, Nature, 441, 73–76, 2006.
Vega-Westhoff, B. and Sriver, R. L: Analysis of ENSO's response to unforced
variability and anthropogenic forcing using CESM, Sci. Rep., 7,
1–10, https://doi.org/10.1038/s41598-017-18459-8, 2017.
Wang, G., Cai, W., Gan, B., Wu, L., Santoso, A., Lin, X., Chen, Z., and
McPhaden, M. J.: Continued increase of extreme El Ninõ frequency long
after 1.5 C warming stabilisation, Nat. Clim. Change, 7, 568–572,
https://doi.org/10.1038/NCLIMATE3351, 2017.
Wang, G., Cai, W., and Santoso, A.: Stronger Increase in the Frequency of
Extreme Convective than Extreme Warm El Niño Events under Greenhouse
Warming, J. Climate, 33, 675–690,
https://doi.org/10.1175/JCLI-D-19-0376.1, 2020.
Wang, Y., Luo, Y., Lu, J., and Liu, F.: Changes in ENSO amplitude under
climate warming and cooling, Clim. Dynam., 52, 1871–1882,
https://doi.org/10.1007/s00382-018-4224-1, 2018.
Watanabe, M., Kug, J.-S., Jin, F.-F., Collins, M., Ohba, M., and Wittenberg,
A. T.: Uncertainty in the ENSO amplitude change from the past to the future,
Geophys. Res. Lett., 39, L20703, https://doi.org/10.1029/2012GL053305, 2012.
Wigley, T. M. L.: A combined mitigation/geoengineering approach to climate
stabilisation, Science, 314, 452–454, https://doi.org/10.1126/science.1131728, 2006.
Xie, R. and Jin, F-F.: Two Leading ENSO Modes and El Niño Types in the
Zebiak–Cane Model, J. Climate, 31, 1943–1962,
https://doi.org/10.1175/JCLI-D-17-0469.1, 2018.
Yang, H. and Wang F.: Revisiting the thermocline depth in the equatorial
Pacific, J. Climate, 22, 3856–3863,
https://doi.org/10.1175/2009JCLI2836.1, 2009.
Yang, S., Li, Z., Yu, J.-Y., Hu, X., Dong, W., and He, S.: El
Niño–Southern oscillation and its impact in the changing climate, Natl.
Sci. Rev., 5, 840–857, https://doi.org/10.1093/nsr/nwy046, 2018.
Yeh, S. W., Kug, J. S., Dewitte, B., Kwon, M. H., Kirtman, B. P., and Jin,
F. F.: El Niño in a changing climate, Nature, 461, 511–514,
https://doi.org/10.1038/nature08316, 2009.
Yu, J.-Y. and Kim, S. T.: Identification of Central-Pacific and
Eastern-Pacific types of ENSO in CMIP3 models, Geophys. Res. Lett., 37, L15705,
https://doi.org/10.1029/2010GL044082, 2010.
Zelle, H., van Oldenborgh, G. J., Burgers, G., and Dijkstra, H.: El Niño
and greenhouse warming: results from ensemble simulations with the NCAR
CCSM, J. Climate, 18, 4669–4683, https://doi.org/10.1175/JCLI3574.1, 2005.
Zhou, Z. Q. and Xie, S. P.: Effects of climatological model biases on the
projection of tropical climate change, J. Climate, 28, 9909–9917,
https://doi.org/10.1175/JCLI-D-15-0243.1, 2015.
Short summary
Solar geoengineering has been introduced to mitigate human-caused global warming by reflecting sunlight back into space. This research investigates the impact of solar geoengineering on the tropical Pacific climate. We find that solar geoengineering can compensate some of the greenhouse-induced changes in the tropical Pacific but not all. In particular, solar geoengineering will result in significant changes in rainfall, sea surface temperatures, and increased frequency of extreme ENSO events.
Solar geoengineering has been introduced to mitigate human-caused global warming by reflecting...
Altmetrics
Final-revised paper
Preprint