Articles | Volume 22, issue 18
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Evaluation of tropical water vapour from CMIP6 global climate models using the ESA CCI Water Vapour climate data records
LATMOS/IPSL, UVSQ Université Paris-Saclay, CNRS, Guyancourt, France
LATMOS/IPSL, UVSQ Université Paris-Saclay, CNRS, Guyancourt, France
LMD/IPSL, Sorbonne-Université, CNRS, Paris, France
No articles found.
Chloé Radice, Hélène Brogniez, Pierre-Emmanuel Kirstetter, and Philippe Chambon
Atmos. Chem. Phys., 22, 3811–3825,Short summary
A novel probabilistic approach is proposed to evaluate relative humidity (RH) profiles simulated by an atmospheric model with respect to satellite-based RH defined from probability distributions. It improves upon deterministic comparisons by enhancing the information content to enable a finer assessment of each model–observation discrepancy, highlighting significant departures within a deterministic confidence range. Geographical and vertical distributions of the model biases are discussed.
Giulia Carella, Mathieu Vrac, Hélène Brogniez, Pascal Yiou, and Hélène Chepfer
Earth Syst. Sci. Data, 12, 1–20,Short summary
Observations of relative humidity for ice clouds over the tropical oceans from a passive microwave sounder are downscaled by incorporating the high-resolution variability derived from simultaneous co-located cloud profiles from a lidar. By providing a method to generate pseudo-observations of relative humidity at high spatial resolution, this work will help revisit some of the current key barriers in atmospheric science.
Hélène Brogniez, Stephen English, Jean-François Mahfouf, Andreas Behrendt, Wesley Berg, Sid Boukabara, Stefan Alexander Buehler, Philippe Chambon, Antonia Gambacorta, Alan Geer, William Ingram, E. Robert Kursinski, Marco Matricardi, Tatyana A. Odintsova, Vivienne H. Payne, Peter W. Thorne, Mikhail Yu. Tretyakov, and Junhong Wang
Atmos. Meas. Tech., 9, 2207–2221,Short summary
Because a systematic difference between measurements of water vapor performed by space-borne observing instruments in the microwave spectral domain and their numerical modeling was recently highlighted, this work discusses and gives an overview of the various errors and uncertainties associated with each element in the comparison process. Indeed, the knowledge of absolute errors in any observation of the climate system is key, more specifically because we need to detect small changes.
R. G. Sivira, H. Brogniez, C. Mallet, and Y. Oussar
Atmos. Meas. Tech., 8, 1055–1071,
M. Schröder, R. Roca, L. Picon, A. Kniffka, and H. Brogniez
Atmos. Chem. Phys., 14, 11129–11148,
Related subject area
Subject: Clouds and Precipitation | Research Activity: Atmospheric Modelling | Altitude Range: Troposphere | Science Focus: Physics (physical properties and processes)Impact of formulations of the homogeneous nucleation rate on ice nucleation events in cirrusTemperature and cloud condensation nuclei (CCN) sensitivity of orographic precipitation enhanced by a mixed-phase seeder–feeder mechanism: a case study for the 2015 Cumbria floodAerosol–precipitation elevation dependence over the central Himalayas using cloud-resolving WRF-Chem numerical modelingMachine learning of cloud types in satellite observations and climate modelsA modeling study of an extreme rainfall event along the northern coast of Taiwan on 2 June 2017Long-term upper-troposphere climatology of potential contrail occurrence over the Paris area derived from radiosonde observationsEquilibrium climate sensitivity increases with aerosol concentration due to changes in precipitation efficiencySouthern Ocean cloud and shortwave radiation biases in a nudged climate model simulation: does the model ever get it right?Aerosol characteristics and polarimetric signatures for a deep convective storm over the northwestern part of Europe – modeling and observationsEvaluation of Aerosol-Cloud Interactions in E3SM using a Lagrangian FrameworkAerosol–stratocumulus interactions: towards a better process understanding using closures between observations and large eddy simulationsThe impacts of secondary ice production on microphysics and dynamics in tropical convectionCloud adjustments from large-scale smoke–circulation interactions strongly modulate the southeastern Atlantic stratocumulus-to-cumulus transitionThe influence of multiple groups of biological ice nucleating particles on microphysical properties of mixed-phase clouds observed during MC3EQuantifying vertical wind shear effects in shallow cumulus clouds over AmazoniaCirrus cloud thinning using a more physically based ice microphysics scheme in the ECHAM-HAM general circulation modelImpacts of combined microphysical and land-surface uncertainties on convective clouds and precipitation in different weather regimesWeakening of tropical sea breeze convective systems through interactions of aerosol, radiation, and soil moistureSensitivity analysis of an aerosol-aware microphysics scheme in Weather Research and Forecasting (WRF) during case studies of fog in NamibiaDo Arctic mixed-phase clouds sometimes dissipate due to insufficient aerosol? Evidence from comparisons between observations and idealized simulationsContrail formation within cirrus: ICON-LEM simulations of the impact of cirrus cloud properties on contrail formationImpact of Holuhraun volcano aerosols on clouds in cloud-system-resolving simulationsWarm and moist air intrusions into the winter Arctic: a Lagrangian view on the near-surface energy budgetsConvective updrafts near sea-breeze frontsEvaluation of modelled summertime convective storms using polarimetric radar observationsEvaluating seasonal and regional distribution of snowfall in regional climate model simulations in the ArcticModeling impacts of ice-nucleating particles from marine aerosols on mixed-phase orographic clouds during 2015 ACAPEX field campaignInfluences of an entrainment–mixing parameterization on numerical simulations of cumulus and stratocumulus cloudsInvestigation of ice cloud modeling capabilities for the irregularly shaped Voronoi ice scattering models in climate simulationsAssessing the potential for simplification in global climate model cloud microphysicsTechnical note: Parameterising cloud base updraft velocity of marine stratocumuliRadiative and microphysical responses of clouds to an anomalous increase in fire particles over the Maritime Continent in 2015Intricate relations among particle collision, relative motion and clustering in turbulent clouds: computational observation and theoryThe effect of marine ice-nucleating particles on mixed-phase cloudsA strong statistical link between aerosol indirect effects and the self-similarity of rainfall distributionsQuantifying albedo susceptibility biases in shallow cloudsPrimary and secondary ice production: interactions and their relative importanceMicrophysical processes producing high ice water contents (HIWCs) in tropical convective clouds during the HAIC-HIWC field campaign: dominant role of secondary ice productionImportance of aerosols and shape of the cloud droplet size distribution for convective clouds and precipitationSecondary ice production processes in wintertime alpine mixed-phase cloudsMulti-thermals and high concentrations of secondary ice: a modelling study of convective clouds during the Ice in Clouds Experiment – Dust (ICE-D) campaignSubgrid-scale horizontal and vertical variation of cloud water in stratocumulus clouds: a case study based on LES and comparisons with in situ observationsA vertical transport window of water vapor in the troposphere over the Tibetan Plateau with implications for global climate changeBox model trajectory studies of contrail formation using a particle-based cloud microphysics schemeUpdraft dynamics and microphysics: on the added value of the cumulus thermal reference frame in simulations of aerosol–deep convection interactionsDemistify: a large-eddy simulation (LES) and single-column model (SCM) intercomparison of radiation fogCase study of a moisture intrusion over the Arctic with the ICOsahedral Non-hydrostatic (ICON) model: resolution dependence of its representationNew investigations on homogeneous ice nucleation: the effects of water activity and water saturation formulationsCloud droplet formation at the base of tropical convective clouds: closure between modeling and measurement results of ACRIDICON–CHUVAImpacts of long-range-transported mineral dust on summertime convective cloud and precipitation: a case study over the Taiwan region
Peter Spichtinger, Patrik Marschalik, and Manuel Baumgartner
Atmos. Chem. Phys., 23, 2035–2060,Short summary
We investigate the impact of the homogeneous nucleation rate on nucleation events in cirrus. As long as the slope of the rate is represented sufficiently well, the resulting ice crystal number concentrations are not crucially affected. Even a change in the prefactor over orders of magnitude does not change the results. However, the maximum supersaturation during nucleation events shows strong changes. This quantity should be used for diagnostics instead of the popular nucleation threshold.
Julia Thomas, Andrew Barrett, and Corinna Hoose
Atmos. Chem. Phys., 23, 1987–2002,Short summary
We study the sensitivity of rain formation processes during a heavy-rainfall event over mountains to changes in temperature and pollution. Total rainfall increases by 2 % K−1, and a 6 % K−1 increase is found at the highest altitudes, caused by a mixed-phase seeder–feeder mechanism (frozen cloud particles melt and grow further as they fall through a liquid cloud layer). In a cleaner atmosphere this process is enhanced. Thus the risk of severe rainfall in mountains may increase in the future.
Pramod Adhikari and John F. Mejia
Atmos. Chem. Phys., 23, 1019–1042,Short summary
We used an atmospheric model to assess the impact of aerosols through radiation and cloud interaction on elevation-dependent precipitation and surface temperature over the central Himalayan region. Results showed contrasting altitudinal precipitation responses to the increased aerosol concentration, which can significantly impact the hydroclimate of the central Himalayas, increasing the risk for extreme events and influencing the regional supply of water resources.
Peter Kuma, Frida A.-M. Bender, Alex Schuddeboom, Adrian J. McDonald, and Øyvind Seland
Atmos. Chem. Phys., 23, 523–549,Short summary
We present a machine learning method for determining cloud types in climate model output and satellite observations based on ground observations of cloud genera. We analyse cloud type biases and changes with temperature in climate models and show that the bias is anticorrelated with climate sensitivity. Models simulating decreasing stratiform and increasing cumuliform clouds with increased CO2 concentration tend to have higher climate sensitivity than models simulating the opposite tendencies.
Chung-Chieh Wang, Ting-Yu Yeh, Chih-Sheng Chang, Ming-Siang Li, Kazuhisa Tsuboki, and Ching-Hwang Liu
Atmos. Chem. Phys., 23, 501–521,Short summary
The extreme rainfall event (645 mm in 24 h) at the northern coast of Taiwan on 2 June 2017 is studied using a cloud model. Two 1 km experiments with peak amounts of 541 and 400 mm are compared to isolate the reasons for such a difference. It is found that the frontal rainband remains fixed in location for a longer period in the former run due to a low disturbance that acts to focus the near-surface convergence. Therefore, the rainfall is more concentrated and there is a higher total amount.
Kevin Wolf, Nicolas Bellouin, and Olivier Boucher
Atmos. Chem. Phys., 23, 287–309,Short summary
Recent studies estimate the radiative impact of contrails to be similar to or larger than that of emitted CO2; thus, contrail mitigation might be an opportunity to reduce the climate effects of aviation. A radiosonde data set is analyzed in terms of the vertical distribution of potential contrails, contrail mitigation by flight altitude changes, and linkages with the tropopause and jet stream. The effect of prospective jet engine developments and alternative fuels are estimated.
Atmos. Chem. Phys., 22, 15767–15775,Short summary
Using idealized simulations we demonstrate that the equilibrium climate sensitivity (ECS), i.e. the increase in surface temperature under equilibrium conditions due to doubling of the CO2 concentration, increases with the aerosol concentration. The ECS increase is explained by a faster increase in precipitation efficiency with warming under high aerosol concentrations, which more efficiently depletes the water from the cloud and thus is manifested as an increase in the cloud feedback parameter.
Sonya L. Fiddes, Alain Protat, Marc D. Mallet, Simon P. Alexander, and Matthew T. Woodhouse
Atmos. Chem. Phys., 22, 14603–14630,Short summary
Climate models have difficulty simulating Southern Ocean clouds, impacting how much sunlight reaches the surface. We use machine learning to group different cloud types observed from satellites and simulated in a climate model. We find the model does a poor job of simulating the same cloud type as what the satellite shows and, even when it does, the cloud properties and amount of reflected sunlight are incorrect. We have a lot of work to do to model clouds correctly over the Southern Ocean.
Prabhakar Shrestha, Jana Mendrok, and Dominik Brunner
Atmos. Chem. Phys., 22, 14095–14117,Short summary
The study extends the Terrestrial Systems Modeling Platform with gas-phase chemistry aerosol dynamics and a radar forward operator to enable detailed studies of aerosol–cloud–precipitation interactions. This is demonstrated using a case study of a deep convective storm, which showed that the strong updraft in the convective core of the storm produced aerosol-tower-like features, which affected the size of the hydrometeors and the simulated polarimetric features (e.g., ZDR and KDP columns).
Matthew W. Christensen, Po-Lun Ma, Peng Wu, Adam C. Varble, Johannes Mülmenstädt, and Jerome Fast
Atmos. Chem. Phys. Discuss.,
Revised manuscript accepted for ACPShort summary
An increase in aerosol concentration (tiny airborne particles) is shown to suppress rainfall and increase the abundance of droplets in clouds passing over Graciosa Island in the Azores. Cloud drops remain affected by aerosol for several days across thousands of kilometers in satellite data. Simulations from an earth system model show good agreement but differences in the amount of cloud water and extent remain despite modification to model parameters which control the warm rain process.
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,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.
Zhipeng Qu, Alexei Korolev, Jason A. Milbrandt, Ivan Heckman, Yongjie Huang, Greg M. McFarquhar, Hugh Morrison, Mengistu Wolde, and Cuong Nguyen
Atmos. Chem. Phys., 22, 12287–12310,Short summary
Secondary ice production (SIP) is an important physical phenomenon that results in an increase in the cloud ice particle concentration and can have a significant impact on the evolution of clouds. Here, idealized simulations of a tropical convective system were conducted. Agreement between the simulations and observations highlights the impacts of SIP on the maintenance of tropical convection in nature and the importance of including the modelling of SIP in numerical weather prediction models.
Michael S. Diamond, Pablo E. Saide, Paquita Zuidema, Andrew S. Ackerman, Sarah J. Doherty, Ann M. Fridlind, Hamish Gordon, Calvin Howes, Jan Kazil, Takanobu Yamaguchi, Jianhao Zhang, Graham Feingold, and Robert Wood
Atmos. Chem. Phys., 22, 12113–12151,Short summary
Smoke from southern Africa blankets the southeast Atlantic from June-October, overlying a major transition region between overcast and scattered clouds. The smoke affects Earth's radiation budget by absorbing sunlight and changing cloud properties. We investigate these effects in regional climate and large eddy simulation models based on international field campaigns. We find that large-scale circulation changes more strongly affect cloud transitions than smoke microphysical effects in our case.
Sachin Patade, Deepak Waman, Akash Deshmukh, Ashok Kumar Gupta, Arti Jadav, Vaughan T. J. Phillips, Aaron Bansemer, Jacob Carlin, and Alexander Ryzhkov
Atmos. Chem. Phys., 22, 12055–12075,Short summary
This modeling study focuses on the role of multiple groups of primary biological aerosol particles as ice nuclei on cloud properties and precipitation. This was done by implementing a more realistic scheme for biological ice nucleating particles in the aerosol–cloud model. Results show that biological ice nucleating particles have a limited role in altering the ice phase and precipitation in deep convective clouds.
Micael Amore Cecchini, Marco de Bruine, Jordi Vilà-Guerau de Arellano, and Paulo Artaxo
Atmos. Chem. Phys., 22, 11867–11888,Short summary
Shallow clouds (vertical extent up to 3 km height) are ubiquitous throughout the Amazon and are responsible for redistributing the solar heat and moisture vertically and horizontally. They are a key component of the water cycle because they can grow past the shallow phase to contribute significantly to the precipitation formation. However, they need favourable environmental conditions to grow. In this study, we analyse how changing wind patterns affect the development of such shallow clouds.
Colin Tully, David Neubauer, Nadja Omanovic, and Ulrike Lohmann
Atmos. Chem. Phys., 22, 11455–11484,Short summary
The proposed geoengineering method, cirrus cloud thinning, was evaluated using a more physically based microphysics scheme coupled to a more realistic approach for calculating ice cloud fractions in the ECHAM-HAM GCM. Sensitivity tests reveal that using the new ice cloud fraction approach and increasing the critical ice saturation ratio for ice nucleation on seeding particles reduces warming from overseeding. However, this geoengineering method is unlikely to be feasible on a global scale.
Christian Barthlott, Amirmahdi Zarboo, Takumi Matsunobu, and Christian Keil
Atmos. Chem. Phys., 22, 10841–10860,Short summary
The relevance of microphysical and land-surface uncertainties for convective-scale predictability is evaluated with a combined-perturbation strategy in realistic convection-resolving simulations. We find a large ensemble spread which demonstrates that the uncertainties investigated here and, in particular, their collective effect are highly relevant for quantitative precipitation forecasting of summertime convection in central Europe.
J. Minnie Park and Susan C. van den Heever
Atmos. Chem. Phys., 22, 10527–10549,Short summary
This study explores how increased aerosol particles impact tropical sea breeze cloud systems under different environments and how a range of environments modulate these cloud responses. Overall, sea breeze flows and clouds that develop therein become weaker due to interactions between aerosols, sunlight, and land surface. In addition, surface rainfall also decreases with more aerosol particles. Weakening of cloud and rain with more aerosols is found irrespective of 130 different environments.
Michael John Weston, Stuart John Piketh, Frédéric Burnet, Stephen Broccardo, Cyrielle Denjean, Thierry Bourrianne, and Paola Formenti
Atmos. Chem. Phys., 22, 10221–10245,Short summary
An aerosol-aware microphysics scheme is evaluated for fog cases in Namibia. AEROCLO-sA campaign observations are used to access and parameterise the model. The model cloud condensation nuclei activation is lower than the observations. The scheme is designed for clouds with updrafts, while fog typically forms in stable conditions. A pseudo updraft speed assigned to the lowest model levels helps achieve more realistic cloud droplet number concentration and size distribution in the model.
Lucas J. Sterzinger, Joseph Sedlar, Heather Guy, Ryan R. Neely III, and Adele L. Igel
Atmos. Chem. Phys., 22, 8973–8988,Short summary
Aerosol particles are required for cloud droplets to form, and the Arctic atmosphere often has much fewer aerosols than at lower latitudes. In this study, we investigate whether aerosol concentrations can drop so low as to no longer support a cloud. We use observations to initialize idealized model simulations to investigate a worst-case scenario where all aerosol is removed from the environment instantaneously. We find that this mechanism is possible in two cases and is unlikely in the third.
Pooja Verma and Ulrike Burkhardt
Atmos. Chem. Phys., 22, 8819–8842,Short summary
This paper investigates contrail ice formation within cirrus and the impact of natural cirrus on the contrail ice formation in the high-resolution ICON-LEM simulations over Germany. Contrail formation often leads to increases in cirrus ice crystal number concentration by a few orders of magnitude. Contrail formation is affected by pre-existing cirrus, leading to changes in contrail formation conditions and ice nucleation rates that can be significant in optically thick cirrus.
Mahnoosh Haghighatnasab, Jan Kretzschmar, Karoline Block, and Johannes Quaas
Atmos. Chem. Phys., 22, 8457–8472,Short summary
The impact of aerosols emitted by the Holuhraun volcanic eruption on liquid clouds was assessed from a pair of cloud-system-resolving simulations along with satellite retrievals. Inside and outside the plume were compared in terms of their statistical distributions. Analyses indicated enhancement for cloud droplet number concentration inside the volcano plume in model simulations and satellite retrievals, while there was on average a small effect on both liquid water path and cloud fraction.
Cheng You, Michael Tjernström, and Abhay Devasthale
Atmos. Chem. Phys., 22, 8037–8057,Short summary
In winter when solar radiation is absent in the Arctic, the poleward transport of heat and moisture into the high Arctic becomes the main contribution of Arctic warming. Over completely frozen ocean sectors, total surface energy budget is dominated by net long-wave heat, while over the Barents Sea, with an open ocean to the south, total net surface energy budget is dominated by the surface turbulent heat.
Shizuo Fu, Richard Rotunno, and Huiwen Xue
Atmos. Chem. Phys., 22, 7727–7738,Short summary
The convective updrafts near the sea-breeze fronts (SBFs) play important roles in initiating deep convection, but their characteristics are not well understood. By performing large-eddy simulations, we explain why the updrafts near the SBF are larger than but have similar strength to the updrafts ahead of the SBF. The results should also apply to other boundary-layer convergence zones similar to the SBF.
Prabhakar Shrestha, Silke Trömel, Raquel Evaristo, and Clemens Simmer
Atmos. Chem. Phys., 22, 7593–7618,Short summary
The study makes use of ensemble numerical simulations with forward operator to evaluate the simulated cloud and precipitation processes with radar observations. While comparing model data with radar has its own challenges due to errors in the forward operator and processed radar measurements, the model was generally found to underestimate the high reflectivity, width/magnitude (value) of ZDR columns and high precipitation.
Annakaisa von Lerber, Mario Mech, Annette Rinke, Damao Zhang, Melanie Lauer, Ana Radovan, Irina Gorodetskaya, and Susanne Crewell
Atmos. Chem. Phys., 22, 7287–7317,Short summary
Snowfall is an important climate indicator. However, microphysical snowfall processes are challenging for atmospheric models. In this study, the performance of a regional climate model is evaluated in modeling the spatial and temporal distribution of Arctic snowfall when compared to CloudSat satellite observations. Excellent agreement in averaged annual snowfall rates is found, and the shown methodology offers a promising diagnostic tool to investigate the shown differences further.
Yun Lin, Jiwen Fan, Pengfei Li, Lai-yung Ruby Leung, Paul J. DeMott, Lexie Goldberger, Jennifer Comstock, Ying Liu, Jong-Hoon Jeong, and Jason Tomlinson
Atmos. Chem. Phys., 22, 6749–6771,Short summary
How sea spray aerosols may affect cloud and precipitation over the region by acting as ice-nucleating particles (INPs) is unknown. We explored the effects of INPs from marine aerosols on orographic cloud and precipitation for an atmospheric river event observed during the 2015 ACAPEX field campaign. The marine INPs enhance the formation of ice and snow, leading to less shallow warm clouds but more mixed-phase and deep clouds. This work suggests models need to consider the impacts of marine INPs.
Xiaoqi Xu, Chunsong Lu, Yangang Liu, Shi Luo, Xin Zhou, Satoshi Endo, Lei Zhu, and Yuan Wang
Atmos. Chem. Phys., 22, 5459–5475,Short summary
A new entrainment–mixing parameterization which can be directly implemented in microphysics schemes without requiring the relative humidity of the entrained air is proposed based on the explicit mixing parcel model. The parameterization is implemented in the two-moment microphysics scheme and exhibits different effects on different types of clouds and even on different stages of stratocumulus clouds, which are affected by turbulent dissipation rate and aerosol concentration.
Ming Li, Husi Letu, Yiran Peng, Hiroshi Ishimoto, Yanluan Lin, Takashi Y. Nakajima, Anthony J. Baran, Zengyuan Guo, Yonghui Lei, and Jiancheng Shi
Atmos. Chem. Phys., 22, 4809–4825,Short summary
To build on the previous investigations of the Voronoi model in the remote sensing retrievals of ice cloud products, this paper developed an ice cloud parameterization scheme based on the single-scattering properties of the Voronoi model and evaluate it through simulations with the Community Integrated Earth System Model (CIESM). Compared with four representative ice cloud schemes, results show that the Voronoi model has good capabilities of ice cloud modeling in the climate model.
Ulrike Proske, Sylvaine Ferrachat, David Neubauer, Martin Staab, and Ulrike Lohmann
Atmos. Chem. Phys., 22, 4737–4762,Short summary
Cloud microphysical processes shape cloud properties and are therefore important to represent in climate models. Their parameterization has grown more complex, making the model results more difficult to interpret. Using sensitivity analysis we test how the global aerosol–climate model ECHAM-HAM reacts to changes to these parameterizations. The model is sensitive to the parameterization of ice crystal autoconversion but not to, e.g., self-collection, suggesting that it may be simplified.
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,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.
Azusa Takeishi and Chien Wang
Atmos. Chem. Phys., 22, 4129–4147,Short summary
Nanometer- to micrometer-sized particles in the atmosphere, namely aerosols, play a crucial role in cloud formation as cloud droplets form on aerosols. This study uses a weather forecasting model to examine the impacts of a large emission of aerosol particles from biomass burning activities over Southeast Asia. We find that additional cloud droplets brought by fire-emitted particles can lead to taller and more reflective convective clouds with increased rainfall.
Ewe-Wei Saw and Xiaohui Meng
Atmos. Chem. Phys., 22, 3779–3788,Short summary
Collision–coagulation of small droplets in turbulent clouds leads to the production of rain. Turbulence causes droplet clustering and higher relative droplet velocities, and these should enhance the collision–coagulation rate. We find, surprisingly, that collision–coagulation starkly diminishes clustering and strongly alters relative velocities. We provide a theory that explains this result. Our results call for a new perspective on how we understand particle/droplet collision in clouds.
Tomi Raatikainen, Marje Prank, Jaakko Ahola, Harri Kokkola, Juha Tonttila, and Sami Romakkaniemi
Atmos. Chem. Phys., 22, 3763–3778,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.
Kalli Furtado and Paul Field
Atmos. Chem. Phys., 22, 3391–3407,Short summary
The complex processes involved mean that no simple answer to this question has so far been discovered: do aerosols increase or decrease precipitation? Using high-resolution weather simulations, we find a self-similar property of rainfall that is not affected by aerosols. Using this invariant, we can collapse all our simulations to a single curve. So, although aerosol effects on rain are many, there may be a universal constraint on the number of degrees of freedom needed to represent them.
Graham Feingold, Tom Goren, and Takanobu Yamaguchi
Atmos. Chem. Phys., 22, 3303–3319,Short summary
The evaluation of radiative forcing associated with aerosol–cloud interactions remains a significant source of uncertainty in future climate projections. Using high-resolution numerical model output, we mimic typical satellite retrieval methodologies to show that data aggregation can introduce significant error (hundreds of percent) in the cloud albedo susceptibility metric. Spatial aggregation errors tend to be countered by temporal aggregation errors.
Xi Zhao and Xiaohong Liu
Atmos. Chem. Phys., 22, 2585–2600,Short summary
The goal of this study is to investigate the relative importance and interactions of primary and secondary ice production in the Arctic mixed-phase clouds. Our results show that the SIP is not only a result of ice crystals produced from ice nucleation, but also competes with the ice production; conversely, strong ice nucleation also suppresses SIP.
Yongjie Huang, Wei Wu, Greg M. McFarquhar, Ming Xue, Hugh Morrison, Jason Milbrandt, Alexei V. Korolev, Yachao Hu, Zhipeng Qu, Mengistu Wolde, Cuong Nguyen, Alfons Schwarzenboeck, and Ivan Heckman
Atmos. Chem. Phys., 22, 2365–2384,Short summary
Numerous small ice crystals in tropical convective storms are difficult to detect and could be potentially hazardous for commercial aircraft. Previous numerical simulations failed to reproduce this phenomenon and hypothesized that key microphysical processes are still lacking in current models to realistically simulate the phenomenon. This study uses numerical experiments to confirm the dominant role of secondary ice production in the formation of these large numbers of small ice crystals.
Christian Barthlott, Amirmahdi Zarboo, Takumi Matsunobu, and Christian Keil
Atmos. Chem. Phys., 22, 2153–2172,Short summary
The relative impact of cloud condensation nuclei (CCN) concentrations and the shape parameter of the cloud droplet size distribution is evaluated in realistic convection-resolving simulations. We find that an increase in the shape parameter can produce almost as large a variation in precipitation as a CCN increase from maritime to polluted conditions. The choice of the shape parameter may be more important than previously thought for determining cloud radiative characteristics.
Paraskevi Georgakaki, Georgia Sotiropoulou, Étienne Vignon, Anne-Claire Billault-Roux, Alexis Berne, and Athanasios Nenes
Atmos. Chem. Phys., 22, 1965–1988,Short summary
The modelling study focuses on the importance of ice multiplication processes in orographic mixed-phase clouds, which is one of the least understood cloud types in the climate system. We show that the consideration of ice seeding and secondary ice production through ice–ice collisional breakup is essential for correct predictions of precipitation in mountainous terrain, with important implications for radiation processes.
Zhiqiang Cui, Alan Blyth, Yahui Huang, Gary Lloyd, Thomas Choularton, Keith Bower, Paul Field, Rachel Hawker, and Lindsay Bennett
Atmos. Chem. Phys., 22, 1649–1667,Short summary
High concentrations of ice particles were observed at temperatures greater than about –8 C. The default scheme of the secondary ice production cannot explain the high concentrations. Relaxing the conditions for secondary ice production or considering dust aerosol alone is insufficient to produce the observed amount of ice particles. It is likely that multi-thermals play an important role in producing very high concentrations of secondary ice particles in some tropical clouds.
Justin A. Covert, David B. Mechem, and Zhibo Zhang
Atmos. Chem. Phys., 22, 1159–1174,Short summary
Stratocumulus play an important role in Earth's radiative balance. The simulation of these cloud systems in climate models is difficult due to the scale at which cloud microphysical processes occur compared with model grid sizes. In this study, we use large-eddy simulation to analyze subgrid-scale variability of cloud water and its implications on a cloud water to drizzle model enhancement factor E. We find current values of E may be too large and that E should be vertically dependent in models.
Xiangde Xu, Chan Sun, Deliang Chen, Tianliang Zhao, Jianjun Xu, Shengjun Zhang, Juan Li, Bin Chen, Yang Zhao, Hongxiong Xu, Lili Dong, Xiaoyun Sun, and Yan Zhu
Atmos. Chem. Phys., 22, 1149–1157,Short summary
A vertical transport window of tropospheric vapor exists on the Tibetan Plateau (TP). The TP's thermal forcing drives the vertical transport
windowof vapor in the troposphere. The effects of the TP's vertical transport window of vapor are of importance in global climate change.
Andreas Bier, Simon Unterstrasser, and Xavier Vancassel
Atmos. Chem. Phys., 22, 823–845,Short summary
We investigate contrail formation in an aircraft plume with a particle-based multi-trajectory 0D model. Due to the high plume heterogeneity, contrail ice crystals form first near the plume edge and then in the plume centre. The number of ice crystals varies strongly with ambient conditions and soot properties near the contrail formation threshold. Our results imply that the multi-trajectory approach does not necessarily lead to improved scientific results compared to a single mean trajectory.
Daniel Hernandez-Deckers, Toshihisa Matsui, and Ann M. Fridlind
Atmos. Chem. Phys., 22, 711–724,Short summary
We investigate how the concentration of aerosols (small particles that serve as seeds for cloud droplets) affect the dynamics of simulated clouds using two different frameworks, i.e., the traditional selection of cloudy rising grid points and tracking small-scale coherent rising features (cumulus thermals). By doing so, we find that these cumulus thermals reveal useful information about the coupling between internal cloud circulations and cloud droplet and raindrop formation.
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,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.
Hélène Bresson, Annette Rinke, Mario Mech, Daniel Reinert, Vera Schemann, Kerstin Ebell, Marion Maturilli, Carolina Viceto, Irina Gorodetskaya, and Susanne Crewell
Atmos. Chem. Phys., 22, 173–196,Short summary
Arctic warming is pronounced, and one factor in this is the poleward atmospheric transport of heat and moisture. This study assesses the 4D structure of an Arctic moisture intrusion event which occurred in June 2017. For the first time, high-resolution pan-Arctic ICON simulations are performed and compared with global models, reanalysis, and observations. Results show the added value of high resolution in the event representation and the impact of the intrusion on the surface energy fluxes.
Manuel Baumgartner, Christian Rolf, Jens-Uwe Grooß, Julia Schneider, Tobias Schorr, Ottmar Möhler, Peter Spichtinger, and Martina Krämer
Atmos. Chem. Phys., 22, 65–91,Short summary
An important mechanism for the appearance of ice particles in the upper troposphere at low temperatures is homogeneous nucleation. This process is commonly described by the
Koop line, predicting the humidity at freezing. However, laboratory measurements suggest that the freezing humidities are above the Koop line, motivating the present study to investigate the influence of different physical parameterizations on the homogeneous freezing with the help of a detailed numerical model.
Ramon Campos Braga, Barbara Ervens, Daniel Rosenfeld, Meinrat O. Andreae, Jan-David Förster, Daniel Fütterer, Lianet Hernández Pardo, Bruna A. Holanda, Tina Jurkat-Witschas, Ovid O. Krüger, Oliver Lauer, Luiz A. T. Machado, Christopher Pöhlker, Daniel Sauer, Christiane Voigt, Adrian Walser, Manfred Wendisch, Ulrich Pöschl, and Mira L. Pöhlker
Atmos. Chem. Phys., 21, 17513–17528,Short summary
Interactions of aerosol particles with clouds represent a large uncertainty in estimates of climate change. Properties of aerosol particles control their ability to act as cloud condensation nuclei. Using aerosol measurements in the Amazon, we performed model studies to compare predicted and measured cloud droplet number concentrations at cloud bases. Our results confirm previous estimates of particle hygroscopicity in this region.
Yanda Zhang, Fangqun Yu, Gan Luo, Jiwen Fan, and Shuai Liu
Atmos. Chem. Phys., 21, 17433–17451,Short summary
This paper explores the impacts of dust on summertime convective cloud and precipitation through a numerical experiment. The result indicates that the long-range-transported dust can notably affect the properties of convective cloud and precipitation by enhancing immersion freezing and invigorating convection. We also analyze the different dust effects predicted by the Morrison and SBM schemes, which are partially attributed to the saturation adjustment approach utilized in the bulk schemes.
Ackerley, D., Chadwick, R., Dommenget, D., and Petrelli, P.: An ensemble of AMIP simulations with prescribed land surface temperatures, Geosci. Model Dev., 11, 3865–3881, https://doi.org/10.5194/gmd-11-3865-2018, 2018. a
Allan, R. P., Liu, C., Zahn, M., Lavers, D. A., Koukouvagias, E., and Bodas-Salcedo, A.: Physically consistent responses of the global atmospheric hydrological cycle in models and observations, Surv. Geophys., 35, 533–552, 2014. a
Allan, R. P., Barlow, M., Byrne, M. P., Cherchi, A., Douville, H., Fowler, H. J., Gan, T. Y., Pendergrass, A. G., Rosenfeld, D., Swann, A. L., Wilcox, L. J., and Zolina, O.: Advances in understanding large-scale responses of the water cycle to climate change, Ann. NY Acad. Sci., 1472, 49–75, 2020. a
Andersson, A., Fennig, K., Klepp, C., Bakan, S., Graßl, H., and Schulz, J.: The Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data – HOAPS-3, Earth Syst. Sci. Data, 2, 215–234, https://doi.org/10.5194/essd-2-215-2010, 2010. a
Arias, P. A., Bellouin, N., Coppola, E., Jones, R. G., Krinner, G., Marotzke, J., Naik, V., Palmer, M. D., Plattner, G.-K., Rogelj, J., Rojas, M., Sillmann, J., Storelvmo, T., Thorne, P. W., Trewin, B., Achuta Rao, K., Adhikary, B., Allan, R. P., Armour, K., Bala, G., Barimalala, R., Berger, S., Canadell, J. G., Cassou, C., Cherchi, A., Collins, W., Collins, W. D., Connors, S. L., Corti, S., Cruz, F., Dentener, F. J., Dereczynski, C., Di Luca, A., Diongue Niang, A., Doblas-Reyes, F. J., Dosio, A., Douville, H., Engelbrecht, F., Eyring, V., Fischer, E., Forster, P., Fox-Kemper, B., Fuglestvedt, J. S., Fyfe, J. C., Gillett, N. P., Goldfarb, L., Gorodetskaya, I., Gutierrez, J. M., Hamdi, R., Hawkins, E., Hewitt, H. T., Hope, P., Islam, A. S., Jones, C., Kaufman, D. S., Kopp, R. E., Kosaka, Y., Kossin, J., Krakovska, S., Lee, J.-Y., Li, J., Mauritsen, T., Maycock, T. K., Meinshausen, M., Min, S.-K., Monteiro, P. M. S., Ngo-Duc, T., Otto, F., Pinto, I., Pirani, A., Raghavan, K., Ranasinghe, R., Ruane, A. C., Ruiz, L., Sallée, J.-B., Samset, B. H., Sathyendranath, S., Seneviratne, S. I., Sörensson, A. A., Szopa, S., Takayabu, I., Tréguier, A.-M., van den Hurk, B., Vautard, R., von Schuckmann, K., Zaehle, S., Zhang, X., and Zickfeld, K.: Technical Summary, in: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S. L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J. B. R., Maycock, T. K., Waterfield, T., Yelekçi, O., Yu, R., and Zhou, B., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 33−-144, 2021. a
Boucher, O., Servonnat, J., Albright, A. L., Aumont, O., Balkanski, Y., Bastrikov, V., Bekki, S., Bonnet, R., Bony, S., Bopp, L., Braconnot, P., Brockmann, P., Cadule, P., Caubel, A., Cheruy, F., Codron, F., Cozic, A., Cugnet, D., D'Andrea, F., Davini, P., Casimir de Lavergne, Denvil, S., Deshayes, J., Devilliers, M., Ducharne, A., Dufresne, J. L., Dupont, E., Éthé, C., Fairhead, L., Falletti, L., Flavoni, S., Foujols, M. A., Gardoll, S., Gastineau, G., Ghattas, J., Grandpeix, J. Y., Guenet, B., Guez, L. E., Guilyardi, E., Guimberteau, M., Hauglustaine, D., Hourdin, F., Idelkadi, A., Joussaume, S., Kageyama, M., Khodri, M., Krinner, G., Lebas, N., Levavasseur, G., Lévy, C., Li, L., Lott, F., Lurton, T., Luyssaert, S., Madec, G., Madeleine, J. B., Maignan, F., Marchand, M., Marti, O., Mellul, L., Meurdesoif, Y., Mignot, J., Musat, I., Ottlé, C., Peylin, P., Planton, Y., Polcher, J., Rio, C., Rochetin, N., Rousset, C., Sepulchre, P., Sima, A., Swingedouw, D., Thiéblemont, R., Traore, A. K., Vancoppenolle, M., Vial, J., Vialard, J., Viovy, N., and Vuichard, N.: Presentation and evaluation of the IPSL-CM6A-LR climate model, J. Adv. Model. Earth Sy., 12, e2019MS002010, https://doi.org/10.1029/2019MS002010, 2020. a, b
Brogniez, H. and Pierrehumbert, R. T.: Intercomparison of tropical tropospheric humidity in GCMs with AMSU-B water vapor data, Geophys. Res. Lett., 34, L17812, https://doi.org/10.1029/2006GL029118, 2007. a, b
Chung, E.-S., Soden, B. J., Sohn, B.-J., and Schmetz, J.: Model-simulated humidity bias in the upper troposphere and its relation to the large-scale circulation, J. Geophys. Res.-Atmos., 116, D10110, https://doi.org/10.1029/2011JD015609, 2011. a
Belward, A. and Dowell, M. (Eds.): The Global Observing System for Climate: Implementation Needs, World Meteorological Organization (WMO), https://library.wmo.int/index.php?lvl=notice_display&id=19838#.Yyvvd-wzY6E (last access: 19 September 2022), 2016. a
Danabasoglu, G., Lamarque, J.-F., Bacmeister, J., Bailey, D., DuVivier, A., Edwards, J., Emmons, L., Fasullo, J., Garcia, R., Gettelman, A., Hannay, C., Holland, M. M., Large, W. G., Lauritzen, P. H., Laurence, D. M., Lenaerts, J. T. M., Lindsay, K., Lipscomb, W. H., Mills, M. J., Neale, R., Oleson, K. W., Otto-Bliesner, B., Phillips, A. S., Sacks, W., Tilmes, S., van Kampenhout, L., Vertenstein, M., Bertini, A., Dennis, J., Deser, C., Fischer, C., Fox-Kemper, B., Kay, J. E., Kinnison, D., Kushner, P. J., Larson, V. E., Long, M. C., Mickelson, S., Moore, J. K., Nienhouse, E., Polvani, L., Rasch, P. J., and Strand, W. G.: The community earth system model version 2 (CESM2), J. Adv. Model. Earth Sy., 12, e2019MS001916, https://doi.org/10.1029/2019MS001916, 2020. a
Diedrich, H., Preusker, R., Lindstrot, R., and Fischer, J.: Retrieval of daytime total columnar water vapour from MODIS measurements over land surfaces, Atmos. Meas. Tech., 8, 823–836, https://doi.org/10.5194/amt-8-823-2015, 2015. a
Du, M., Huang, K., Zhang, S., Huang, C., Gong, Y., and Yi, F.: Water vapor anomaly over the tropical western Pacific in El Niño winters from radiosonde and satellite observations and ERA5 reanalysis data, Atmos. Chem. Phys., 21, 13553–13569, https://doi.org/10.5194/acp-21-13553-2021, 2021. a
ESA: CCI water vapour data, ESA [data set], https://climate.esa.int/en/projects/water-vapour/, last access: 19 September 2022. a
ESGF: CMIP6, ESGF [data set], https://esgf-node.ipsl.upmc.fr/projects/esgf-ipsl/, last access: 19 September 2022. a
Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., and Taylor, K. E.: Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization, Geosci. Model Dev., 9, 1937–1958, https://doi.org/10.5194/gmd-9-1937-2016, 2016. a, b
Fennig, K., Schröder, M., Andersson, A., and Hollmann, R.: A Fundamental Climate Data Record of SMMR, SSM/I, and SSMIS brightness temperatures, Earth Syst. Sci. Data, 12, 647–681, https://doi.org/10.5194/essd-12-647-2020, 2020. a
Fischer, J. and Bennartz, R.: Retrieval of total water vapour content from MERIS measurements, Algorithm Theoretical Basis Document PO-TN-MEL-GS, 5, Institute for Space Sciences, Freie Universität Berlin, https://earth.esa.int/eogateway/instruments/meris/atbd (last access: 19 September 2022), 1997. a
Gao, B.-C. and Kaufman, Y. J.: Water vapor retrievals using Moderate Resolution Imaging Spectroradiometer (MODIS) near-infrared channels, J. Geophys. Res.-Atmos., 108, 4389, https://doi.org/10.1029/2002JD003023, 2003. a
Gettelman, A., Mills, M., Kinnison, D., Garcia, R., Smith, A., Marsh, D., Tilmes, S., Vitt, F., Bardeen, C., McInerny, J., Liu, H. L., Solomon, S. C., Polvani, L. M., Emmons, L. K., Lamarque, J. F., Richter, J. H., Glanville, A. S., Bacmeister, J. T., Phillips, A. S., Neale, R. B., Simpson, I. R., DuVivier, A. K., Hodzic, A., and Randel, W. J.: The whole atmosphere community climate model version 6 (WACCM6), J. Geophys. Res.-Atmos., 124, 12380–12403, https://doi.org/10.1029/2019JD030943, 2019. a
Held, I. M. and Soden, B. J.: Water vapor feedback and global warming, Annu. Rev. Energ. Env., 25, 441–475, 2000. a
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R.J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., Patrica de Rosnay, Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J. N.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, 2020. a, b
Huang, X., Soden, B. J., and Jackson, D. L.: Interannual co-variability of tropical temperature and humidity: A comparison of model, reanalysis data and satellite observation, Geophys. Res. Lett., 32, L17808, https://doi.org/10.1029/2005GL023375, 2005. a
IPCC (Hartmann, D. L., Klein Tank, A. M. G., Rusticucci, M., Alexander, L. V., Brönnimann, S., Charabi, Y., Dentener, F. J., Dlugokencky, E. J., Easterling, D. R., Kaplan, A., Soden, B. J., Thorne, P. W., Wild, M., and Zhai, P. M.): Observations: Atmosphere and Surface, 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, edited by: 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., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, https://www.ipcc.ch/report/ar5/wg1/ (last access: 24 September 2022), 2013. a
Jiang, J. H., Su, H., Zhai, C., Perun, V. S., Del Genio, A., Nazarenko, L. S., Donner, L. J., Horowitz, L., Seman, C., Cole, J., Gettelman, A., Ringer, M. A., Rotstayn, L., Jeffrey, S., Wu, T. W., Brient, F., Dufresne, J. L., Kawai, H., Koshiro, T., Watanabe, M., Lécuyer, T. S., Volodin, E. M., Iversen, T., Drange, H., Mesquita, M. D. S., Read, W. G., Waters, J. W., Tian, B. J., Teixeira, J., and Stephens, G. L.: Evaluation of cloud and water vapor simulations in CMIP5 climate models using NASA “A-Train” satellite observations, J. Geophys. Res.-Atmos., 117, D14105, https://doi.org/10.1029/2011JD017237. 2012. a
Konsta, D., Chepfer, H., and Dufresne, J.-L.: A process oriented characterization of tropical oceanic clouds for climate model evaluation, based on a statistical analysis of daytime A-train observations, Clim. Dynam., 39, 2091–2108, 2012. a
Lindstrot, R., Preusker, R., Diedrich, H., Doppler, L., Bennartz, R., and Fischer, J.: 1D-Var retrieval of daytime total columnar water vapour from MERIS measurements, Atmos. Meas. Tech., 5, 631–646, https://doi.org/10.5194/amt-5-631-2012, 2012. a, b
Lindstrot, R., Stengel, M., Schröder, M., Fischer, J., Preusker, R., Schneider, N., Steenbergen, T., and Bojkov, B. R.: A global climatology of total columnar water vapour from SSM/I and MERIS, Earth Syst. Sci. Data, 6, 221–233, https://doi.org/10.5194/essd-6-221-2014, 2014. a
Lu, J., Vecchi, G. A., and Reichler, T.: Expansion of the Hadley cell under global warming, Geophys. Res. Lett., 34, L06805, https://doi.org/10.1029/2006GL028443, 2007. a
Lurton, T., Balkanski, Y., Bastrikov, V., Bekki, S., Bopp, L., Braconnot, P., Brockmann, P., Cadule, P., Contoux, C., Cozic, A., Cugnet, D., Dufresne, J. L., Éthé, C., Foujols, M. A., Ghattas, J., Hauglustaine, D., Hu, R. M., Kageyama, M., Khodri, M., Lebas, N., Levavasseur, G., Marchand, M., Ottlé, C., Peylin, P., Sima, A., Szopa, S., Thiéblemont, R., Vuichard, N., and Boucher, O.: Implementation of the CMIP6 Forcing Data in the IPSL-CM6A-LR Model, J. Adv. Model. Earth Sy., 12, e2019MS001940, https://doi.org/10.1029/2019MS001940, 2020. a
Ma, J., Chadwick, R., Seo, K.-H., Dong, C., Huang, G., Foltz, G. R., and Jiang, J. H.: Responses of the tropical atmospheric circulation to climate change and connection to the hydrological cycle, Annu. Rev. Earth Pl. Sc., 46, 549–580, 2018. a
Mbengue, C. and Schneider, T.: Storm-track shifts under climate change: Toward a mechanistic understanding using baroclinic mean available potential energy, J. Atmos. Sci., 74, 93–110, 2017. a
Müller, W. A., Jungclaus, J. H., Mauritsen, T., Baehr, J., Bittner, M., Budich, R., Bunzel, F., Esch, M., Ghosh, R., Haak, H., Ilyina, T., Kleine, T., Kornblueh, L., Li, H., Modali, K., Notz, D., Pohlmann, H., Roeckner, E., Stemmler, I., Tian, F., and Marotzke, J.: A Higher-resolution Version of the Max Planck Institute Earth System Model (MPI-ESM1. 2-HR), J. Adv. Model. Earth Sy., 10, 1383–1413, https://doi.org/10.1029/2017MS001217, 2018. a
Pierrehumbert, R.: Lateral mixing as a source of subtropical water vapor, Geophys. Res. Lett., 25, 151–154, 1998. a
Pierrehumbert, R. T. and Roca, R.: Evidence for control of Atlantic subtropical humidity by large scale advection, Geophys. Res. Lett., 25, 4537–4540, 1998. a
Preusker, R., Carbajal Henken, C., and Fischer, J.: Retrieval of Daytime Total Column Water Vapour from OLCI Measurements over Land Surfaces, Remote Sensing, 13, 932, https://doi.org/10.3390/rs13050932, 2021. a
Raval, A. and Ramanathan, V.: Observational determination of the greenhouse effect, Nature, 342, 758–761, 1989. a
Schröder, M., Jonas, M., Lindau, R., Schulz, J., and Fennig, K.: The CM SAF SSM/I-based total column water vapour climate data record: methods and evaluation against re-analyses and satellite, Atmos. Meas. Tech., 6, 765–775, https://doi.org/10.5194/amt-6-765-2013, 2013. a
Schröder, M., Lockhoff, M., Shi, L., August, T., Bennartz, R., Brogniez, H., Calbet, X., Fell, F., Forsythe, J., Gambacorta, A., Ho, S. P., Kursinski, E. R., Reale, A., Trent, T., and Yang, Q.: The GEWEX water vapor assessment: Overview and introduction to results and recommendations, Remote Sensing, 11, 251, https://doi.org/10.3390/rs11030251, 2019. a
Séférian, R., Nabat, P., Michou, M., Saint-Martin, D., Voldoire, A., Colin, J., Decharme, B., Delire, C., Berthet, S., Chevallier, M., Sénési, S., Franchisteguy, L., Vial, J., Mallet, M., Joetzjer, E., Geoffroy, O., Guérémy, J. F., Moine, M. P., Msadek, R., Ribes, A., Rocher, M., Roehrig, R., Salas-y-Mélia, D., Sanchez, E., Terray, L., Valcke, S., Waldman, R., Aumont, O., Bopp, L., Deshayes, J., Éthé, C., and Madec, G.: Evaluation of CNRM Earth System Model, CNRM-ESM2-1: Role of Earth System Processes in Present-Day and Future Climate, J. Adv. Model. Earth Sy., 11, 4182–4227, https://doi.org/10.1029/2019MS001791, 2019. a
Sherwood, S., Roca, R., Weckwerth, T., and Andronova, N.: Tropospheric water vapor, convection, and climate, Rev. Geophys., 48, RG2001, https://doi.org/10.1029/2009RG000301, 2010. a
Sohn, B.-J. and Bennartz, R.: Contribution of water vapor to observational estimates of longwave cloud radiative forcing, J. Geophys. Res.-Atmos., 113, RG2001, https://doi.org/10.1029/2008JD010053, 2008. a
Sohn, B.-J., Schmetz, J., Stuhlmann, R., and Lee, J.-Y.: Dry bias in satellite-derived clear-sky water vapor and its contribution to longwave cloud radiative forcing, J. Climate, 19, 5570–5580, 2006. a
Stephens, G. L.: On the relationship between water vapor over the oceans and sea surface temperature, J. Climate, 3, 634–645, 1990. a
Swart, N. C., Cole, J. N. S., Kharin, V. V., Lazare, M., Scinocca, J. F., Gillett, N. P., Anstey, J., Arora, V., Christian, J. R., Hanna, S., Jiao, Y., Lee, W. G., Majaess, F., Saenko, O. A., Seiler, C., Seinen, C., Shao, A., Sigmond, M., Solheim, L., von Salzen, K., Yang, D., and Winter, B.: The Canadian Earth System Model version 5 (CanESM5.0.3), Geosci. Model Dev., 12, 4823–4873, https://doi.org/10.5194/gmd-12-4823-2019, 2019. a
Trenberth, K. E., Stepaniak, D. P., and Caron, J. M.: The global monsoon as seen through the divergent atmospheric circulation, J. Climate, 13, 3969–3993, 2000. a
Trenberth, K. E., Fasullo, J., and Smith, L.: Trends and variability in column-integrated atmospheric water vapor, Clim. Dynam., 24, 741–758, 2005. a
Vallis, G. K., Zurita-Gotor, P., Cairns, C., and Kidston, J.: Response of the large-scale structure of the atmosphere to global warming, Q. J. Roy. Meteor. Soc., 141, 1479–1501, 2015. a
Virgin, J. G., Fletcher, C. G., Cole, J. N. S., von Salzen, K., and Mitovski, T.: Cloud Feedbacks from CanESM2 to CanESM5.0 and their influence on climate sensitivity, Geosci. Model Dev., 14, 5355–5372, https://doi.org/10.5194/gmd-14-5355-2021, 2021. a, b
Voldoire, A., Saint-Martin, D., Sénési, S., Decharme, B., Alias, A., Chevallier, M., Colin, J., Guérémy, J.-F., Michou, M., Moine, M.-P., Nabat, P., Roehrig, R., Salas y Mélia, D., Séférian, R., Valcke, S., Beau, I., Belamari, S., Berthet, S., Cassou, C., Cattiaux, J., Deshayes, J., Douville, H., Ethé, C., Franchistéguy, L., Geoffroy, O., Lévy, C., Madec, G., Meurdesoif, Y., Msadek, R., Ribes, A., Sanchez-Gomez, E., Terray, L., and Waldman, R.: Evaluation of CMIP6 deck experiments with CNRM-CM6-1, J. Adv. Model. Earth Sy., 11, 2177–2213, https://doi.org/10.1029/2019MS001683, 2019. a
Wulfmeyer, V., Hardesty, R. M., Turner, D. D., Behrendt, A., Cadeddu, M. P., Di Girolamo, P., Schlüssel, P., Van Baelen, J., and Zus, F.: A review of the remote sensing of lower tropospheric thermodynamic profiles and its indispensable role for the understanding and the simulation of water and energy cycles, Rev. Geophys., 53, 819–895, 2015. a
- Full-text XML
A 2003–2017 satellite-based atmospheric water vapour climate data record is used to assess climate models and reanalyses. The focus is on the tropical belt, whose regional variations in the hydrological cycle are related to the tropospheric overturning circulation. While there are similarities in the interannual variability, the major discrepancies can be explained by the presence of clouds, the representation of moisture fluxes at the surface and cloud processes in the models.
A 2003–2017 satellite-based atmospheric water vapour climate data record is used to assess...