scholarly journals Aerosol midlatitude cyclone indirect effects in observations and high-resolution simulations

2018 ◽  
Vol 18 (8) ◽  
pp. 5821-5846 ◽  
Author(s):  
Daniel T. McCoy ◽  
Paul R. Field ◽  
Anja Schmidt ◽  
Daniel P. Grosvenor ◽  
Frida A.-M. Bender ◽  
...  
Keyword(s):  
High Resolution ◽  
Rain Rate ◽  
Cloud Droplet ◽  
Moisture Flux ◽  
Conveyor Belt ◽  
Liquid Water Path ◽  
Aerosol Cloud ◽  
Cloud Properties ◽  
The Difference ◽  
Aerosol Cloud Interactions

Abstract. Aerosol–cloud interactions are a major source of uncertainty in inferring the climate sensitivity from the observational record of temperature. The adjustment of clouds to aerosol is a poorly constrained aspect of these aerosol–cloud interactions. Here, we examine the response of midlatitude cyclone cloud properties to a change in cloud droplet number concentration (CDNC). Idealized experiments in high-resolution, convection-permitting global aquaplanet simulations with constant CDNC are compared to 13 years of remote-sensing observations. Observations and idealized aquaplanet simulations agree that increased warm conveyor belt (WCB) moisture flux into cyclones is consistent with higher cyclone liquid water path (CLWP). When CDNC is increased a larger LWP is needed to give the same rain rate. The LWP adjusts to allow the rain rate to be equal to the moisture flux into the cyclone along the WCB. This results in an increased CLWP for higher CDNC at a fixed WCB moisture flux in both observations and simulations. If observed cyclones in the top and bottom tercile of CDNC are contrasted it is found that they have not only higher CLWP but also cloud cover and albedo. The difference in cyclone albedo between the cyclones in the top and bottom third of CDNC is observed by CERES to be between 0.018 and 0.032, which is consistent with a 4.6–8.3 Wm−2 in-cyclone enhancement in upwelling shortwave when scaled by annual-mean insolation. Based on a regression model to observed cyclone properties, roughly 60 % of the observed variability in CLWP can be explained by CDNC and WCB moisture flux.

scholarly journals The source of discrepancies in aerosol–cloud–precipitation interactions between GCM and A-Train retrievals

2016 ◽  
Vol 16 (23) ◽  
pp. 15413-15424 ◽  
Author(s):  
Takuro Michibata ◽  
Kentaroh Suzuki ◽  
Yousuke Sato ◽  
Toshihiko Takemura
Keyword(s):  
General Circulation ◽  
Climate Models ◽  
Circulation Model ◽  
Cloud Droplet ◽  
Systematic Difference ◽  
Liquid Water Path ◽  
Light Rain ◽  
Aerosol Cloud ◽  
Nonlinear Complexity ◽  
Aerosol Cloud Interactions

Abstract. Aerosol–cloud interactions are one of the most uncertain processes in climate models due to their nonlinear complexity. A key complexity arises from the possibility that clouds can respond to perturbed aerosols in two opposite ways, as characterized by the traditional “cloud lifetime” hypothesis and more recent “buffered system” hypothesis. Their importance in climate simulations remains poorly understood. Here we investigate the response of the liquid water path (LWP) to aerosol perturbations for warm clouds from the perspective of general circulation model (GCM) and A-Train remote sensing, through process-oriented model evaluations. A systematic difference is found in the LWP response between the model results and observations. The model results indicate a near-global uniform increase of LWP with increasing aerosol loading, while the sign of the response of the LWP from the A-Train varies from region to region. The satellite-observed response of the LWP is closely related to meteorological and/or macrophysical factors, in addition to the microphysics. The model does not reproduce this variability of cloud susceptibility (i.e., sensitivity of LWP to perturbed aerosols) because the parameterization of the autoconversion process assumes only suppression of rain formation in response to increased cloud droplet number, and does not consider macrophysical aspects that serve as a mechanism for the negative responses of the LWP via enhancements of evaporation and precipitation. Model biases are also found in the precipitation microphysics, which suggests that the model generates rainwater readily even when little cloud water is present. This essentially causes projections of unrealistically frequent and light rain, with high cloud susceptibilities to aerosol perturbations.

scholarly journals Untangling causality in midlatitude aerosol-cloud adjustments

2019 ◽  
Author(s):  
Daniel T. McCoy ◽  
Paul Field ◽  
Hamish Gordon ◽  
Gregory S. Elsaesser ◽  
Daniel P. Grosvenor
Keyword(s):  
Radiative Forcing ◽  
Sensible Heat Flux ◽  
Cloud Droplet ◽  
Causal Link ◽  
Cloud Microphysics ◽  
Liquid Water Path ◽  
Aerosol Cloud ◽  
Causal Pathways ◽  
Model Adjustment ◽  
Aerosol Cloud Interactions

Abstract. Aerosol-cloud interactions represent the leading uncertainty in our ability to infer climate sensitivity from the observational record. The forcing from changes in cloud albedo driven by increases in cloud droplet number (Nd) (the first indirect effect) is confidently negative and has narrowed its probable range in the last decade, but the sign and strength of forcing associated with changes in cloud macrophysics in response to aerosol (aerosol-cloud adjustments) remain uncertain. This uncertainty reflects our inability to accurately quantify variability not associated with a causal link flowing from the cloud microphysical state to cloud macrophysical state. Once variability associated with meteorology has been removed, covariance between the liquid water path averaged across cloudy and clear regions (LWP, here, characterizing the macrophysical state) and Nd (characterizing the microphysical) is the sum of two causal pathways linking Nd to LWP: Nd altering LWP (adjustments) and precipitation scavenging aerosol and thus depleting Nd. Only the former term is relevant to constraining adjustments, but disentangling these terms in observations is challenging. We hypothesize that the diversity of constraints on aerosol-cloud adjustments in the literature may be partly due to not explicitly characterizing covariance flowing from cloud to aerosol, and aerosol to cloud. Here, we restrict our analysis to the regime of extratropical clouds outside of low-pressure centers associated with cyclonic activity. Observations from MAC-LWP, and MODIS are compared to simulations in the MetOffice Unified Model (UM) GA7.1 (the atmosphere model of HadGEM3-GC3.1 and UKESM1). The meteorological predictors of LWP are found to be similar between the model and observations. There is also agreement with previous literature on cloud-controlling factors finding that increasing stability, moisture, and sensible heat flux enhance LWP, while increasing subsidence, and sea surface temperature decrease it. A simulation where cloud microphysics are insensitive to changes in Nd is used to characterize covariance between Nd and LWP that is induced by factors other than aerosol-cloud adjustments. By removing variability associated with meteorology and scavenging we infer the sensitivity of LWP to changes in Nd. Application of this technique to UM GA7.1 simulations reproduces the true model adjustment strength. Observational constraints developed using simulated covariability not induced by adjustments and observed covariability between Nd and LWP predict a 25–30 % overestimate by the UM GA7.1 in LWP change and a 30–35% overestimate in associated radiative forcing.

scholarly journals Satellite-based estimate of the variability of warm cloud properties associated with aerosol and meteorological conditions

2018 ◽  
Vol 18 (24) ◽  
pp. 18187-18202 ◽  
Author(s):  
Yuqin Liu ◽  
Jiahua Zhang ◽  
Putian Zhou ◽  
Tao Lin ◽  
Juan Hong ◽  
...  
Keyword(s):  
Cloud Cover ◽  
Cloud Droplet ◽  
Cloud Fraction ◽  
Meteorological Conditions ◽  
Liquid Water Path ◽  
Time Step ◽  
Aerosol Cloud ◽  
Cloud Properties ◽  
Almost All ◽  
Step Over

Abstract. Aerosol–cloud interaction (ACI) is examined using 10 years of data from the MODIS/Terra (morning orbit) and MODIS/Aqua (afternoon orbit) satellites. Aerosol optical depth (AOD) and cloud properties retrieved from both sensors are used to explore in a statistical sense the morning-to-afternoon variation of cloud properties in conditions with low and high AOD, over both land and ocean. The results show that the interaction between aerosol particles and clouds is more complex and of greater uncertainty over land than over ocean. The variation in d(Cloud_X), defined as the mean change in cloud property Cloud_X between the morning and afternoon overpasses in high-AOD conditions minus that in low-AOD conditions, is different over land and ocean. This applies to cloud droplet effective radius (CDR), cloud fraction (CF) and cloud top pressure (CTP), but not to cloud optical thickness (COT) and cloud liquid water path (CWP). Both COT and CWP increase over land and ocean after the time step, irrespective of the AOD. However, the initial AOD conditions can affect the amplitude of variation of COT and CWP. The effects of initial cloud fraction and meteorological conditions on the change in CF under low- and high-AOD conditions after the 3 h time step over land are also explored. Two cases are considered: (1) when the cloud cover increases and (2) when the cloud cover decreases. For both cases, we find that almost all values of d(CF) are positive, indicating that the variations of CF are larger in high AOD than that in low AOD after the 3 h time step. The results also show that a large increase in cloud fraction occurs when scenes experience large AOD and stronger upward motion of air parcels. Furthermore, the increase rate of cloud cover is larger for high AOD with increasing relative humidity (RH) when RH is larger than 20 %. We also find that a smaller increase in cloud fraction occurs when scenes experience larger AOD and larger initial cloud cover. Overall, the analysis of the diurnal variation of cloud properties provides a better understanding of aerosol–cloud interaction over land and ocean.

Aerosol-cloud interactions from combined observations with geostationary and polar-orbiting sensors

2020 ◽  
Author(s):  
Matthias Tesche ◽  
Torsten Seelig ◽  
Fani Alexandri ◽  
Peter Bräuer ◽  
Goutam Choudhury ◽  
...  
Keyword(s):  
Rain Rate ◽  
Cloud Condensation Nuclei ◽  
Cloud Formation ◽  
Development Phase ◽  
Time Resolved ◽  
Aerosol Cloud ◽  
Cloud Properties ◽  
The Pacific ◽  
Aerosol Cloud Interactions ◽  
Ice Water

<p>Atmospheric aerosol particles are of great importance for cloud formation in the atmosphere because they are needed to act as cloud condensation nuclei (CCN) in liquid-water clouds and as ice nucleating particles (INP) in ice-containing clouds. Changes in aerosol concentration affect the albedo, development, phase, lifetime and rain rate of clouds. These aerosol-cloud interactions (ACI) and the resulting climate effects still cause the largest uncertainty in assessing climate change as they are understood only with medium confidence.</p><p>The PACIFIC project, which is embedded in the French-German Make Our Planet Great Again (MOPGA) initiative, aims to improve our understanding of ACI by enhancing the representation of those aerosols that are relevant for cloud processes and by quantifying temporal changes in cloud properties throughout the cloud life cycle. PACIFIC uses a three-fold approach for studying ACI based on spaceborne observations by (i) using spaceborne lidar data to obtain unprecedented insight in CCN and INP concentrations at cloud level opposed to using column-integrated parameters, (ii) characterizing the development of clouds by tracking them in time-resolved geostationary observations opposed to resorting to the snap-shot view of polar-orbiting sensors, and (iii) combining the detailed observations from polar-orbiting sensors with the time-resolved observations of geostationary sensors – for clouds observed by both – to study the effects of CCN and INP on the albedo, liquid and ice water content, droplet and crystal size, development, phase and rain rate of clouds within different regimes carefully accounting for the meteorological background.</p><p>This contribution will present the scope of the MOPGA-GRI project PACIFIC and illustrate the first findings.</p>

scholarly journals The scale problem in quantifying aerosol indirect effects

2012 ◽  
Vol 12 (2) ◽  
pp. 1031-1049 ◽  
Author(s):  
A. McComiskey ◽  
G. Feingold
Keyword(s):  
Radiative Forcing ◽  
Process Model ◽  
Full Range ◽  
Liquid Water Path ◽  
Aerosol Cloud ◽  
Cloud Properties ◽  
Wide Range ◽  
Albedo Effect ◽  
Aerosol Cloud Interactions ◽  
The Impact

Abstract. A wide range of estimates exists for the radiative forcing of the aerosol effect on cloud albedo. We argue that a component of this uncertainty derives from the use of a wide range of observational scales and platforms. Aerosol influences cloud properties at the microphysical scale, or the "process scale", but observations are most often made of bulk properties over a wide range of resolutions, or "analysis scales". We show that differences between process and analysis scales incur biases in quantification of the albedo effect through the impact that data aggregation and computational approach have on statistical properties of the aerosol or cloud variable, and their covariance. Measures made within this range of scales are erroneously treated as equivalent, leading to a large uncertainty in associated radiative forcing estimates. Issues associated with the coarsening of observational resolution particular to quantifying the albedo effect are discussed. Specifically, the omission of the constraint on cloud liquid water path and the separation in space of cloud and aerosol properties from passive, space-based remote sensors dampen the measured strength of the albedo effect. We argue that, because of this lack of constraints, many of these values are in fact more representative of the full range of aerosol-cloud interactions and their associated feedbacks. Based on our understanding of these biases we propose a new observationally-based and process-model-constrained, method for estimating aerosol-cloud interactions that can be used for radiative forcing estimates as well as a better characterization of the uncertainties associated with those estimates.

scholarly journals Aerosol-cloud interactions in the NASA GMI: model development and indirect forcing assessments

2007 ◽  
Vol 7 (5) ◽  
pp. 14295-14330 ◽  
Author(s):  
N. Meskhidze ◽  
R. E. P. Sotiropoulou ◽  
A. Nenes ◽  
J. Kouatchou ◽  
B. Das ◽  
...  
Keyword(s):  
Transport Model ◽  
Model Development ◽  
Cloud Droplet ◽  
Chemical Transport Model ◽  
Remotely Sensed Data ◽  
Liquid Water Path ◽  
Model Framework ◽  
Aerosol Cloud ◽  
Aerosol Cloud Interactions ◽  
Indirect Forcing

Abstract. This study uses the NASA Global Modeling Initiative (GMI) 3-D chemical transport model (CTM) for assessments of indirect forcing and its sensitivity to the treatment of aerosol, aerosol-cloud interactions and meteorological fields. Three different meteorological datasets from NASA Data Assimilation Office (DAO), NASA finite volume GCM (FVGCM) and the Goddard Institute for Space Studies version II' (GISS II') GCM were used. GMI is ideal for this study as different model components (such as meteorological fields and chemical mechanisms) can easily be interchanged under the same model framework to capture the first aerosol indirect effect (AIE), and its sensitivity to parameterizations and meteorological fields. Cloud droplet number concentration was calculated by implementing both diagnostic and physically based droplet parameterizations. Derived cloud properties, such as cloud optical thickness and effective radius were compared with the remotely sensed data from Moderate Resolution Imaging Spectroradiometer (MODIS). GMI was able to capture the spatial variability and the land-ocean contrast observed in the satellite record. Depending on the meteorological field and droplet parameterization used, the annual mean first AIE ranged from −0.99 to −1.48 W m−2. It is found that, roughly 80% of the variation is attributed to changes in the meteorology (primarily from variations in liquid water path), while the remaining 20% is attributed to different cloud droplet parameterizations.

scholarly journals Unveiling aerosol–cloud interactions – Part 2: Minimising the effects of aerosol swelling and wet scavenging in ECHAM6-HAM2 for comparison to satellite data

2017 ◽  
Vol 17 (21) ◽  
pp. 13165-13185 ◽  
Author(s):  
David Neubauer ◽  
Matthew W. Christensen ◽  
Caroline A. Poulsen ◽  
Ulrike Lohmann
Keyword(s):  
Liquid Water ◽  
Cloud Droplet ◽  
Liquid Water Path ◽  
Large Variability ◽  
Water Path ◽  
Cloud Albedo ◽  
Aerosol Cloud ◽  
Aerosol Processing ◽  
Wet Scavenging ◽  
Aerosol Cloud Interactions

Abstract. Aerosol–cloud interactions (ACIs) are uncertain and the estimates of the ACI effective radiative forcing (ERFaci) magnitude show a large variability. Within the Aerosol_cci project the susceptibility of cloud properties to changes in aerosol properties is derived from the high-resolution AATSR (Advanced Along-Track Scanning Radiometer) data set using the Cloud–Aerosol Pairing Algorithm (CAPA) (as described in our companion paper) and compared to susceptibilities from the global aerosol climate model ECHAM6-HAM2 and MODIS–CERES (Moderate Resolution Imaging Spectroradiometer – Clouds and the Earth's Radiant Energy System) data. For ECHAM6-HAM2 the dry aerosol is analysed to mimic the effect of CAPA. Furthermore the analysis is done for different environmental regimes. The aerosol–liquid water path relationship in ECHAM6-HAM2 is systematically stronger than in AATSR–CAPA data and cannot be explained by an overestimation of autoconversion when using diagnostic precipitation but rather by aerosol swelling in regions where humidity is high and clouds are present. When aerosol water is removed from the analysis in ECHAM6-HAM2 the strength of the susceptibilities of liquid water path, cloud droplet number concentration and cloud albedo as well as ERFaci agree much better with those of AATSR–CAPA or MODIS–CERES. When comparing satellite-derived to model-derived susceptibilities, this study finds it more appropriate to use dry aerosol in the computation of model susceptibilities. We further find that the statistical relationships inferred from different satellite sensors (AATSR–CAPA vs. MODIS–CERES) as well as from ECHAM6-HAM2 are not always of the same sign for the tested environmental conditions. In particular the susceptibility of the liquid water path is negative in non-raining scenes for MODIS–CERES but positive for AATSR–CAPA and ECHAM6-HAM2. Feedback processes like cloud-top entrainment that are missing or not well represented in the model are therefore not well constrained by satellite observations. In addition to aerosol swelling, wet scavenging and aerosol processing have an impact on liquid water path, cloud albedo and cloud droplet number susceptibilities. Aerosol processing leads to negative liquid water path susceptibilities to changes in aerosol index (AI) in ECHAM6-HAM2, likely due to aerosol-size changes by aerosol processing. Our results indicate that for statistical analysis of aerosol–cloud interactions the unwanted effects of aerosol swelling, wet scavenging and aerosol processing need to be minimised when computing susceptibilities of cloud variables to changes in aerosol.

scholarly journals Deconvolution of boundary layer depth and aerosol constraints on cloud water path in subtropical stratocumulus decks

2020 ◽  
Vol 20 (6) ◽  
pp. 3609-3621
Author(s):  
Anna Possner ◽  
Ryan Eastman ◽  
Frida Bender ◽  
Franziska Glassmeier
Keyword(s):  
Boundary Layer ◽  
Radiative Forcing ◽  
Cloud Droplet ◽  
Process Modelling ◽  
Liquid Water Path ◽  
Marine Stratocumulus ◽  
Water Path ◽  
Aerosol Cloud ◽  
Aerosol Cloud Interactions ◽  
Relative Change

Abstract. The liquid water path (LWP) adjustment due to aerosol–cloud interactions in marine stratocumulus remains a considerable source of uncertainty for climate sensitivity estimates. An unequivocal attribution of LWP adjustments to changes in aerosol concentration from climatology remains difficult due to the considerable covariance between meteorological conditions alongside changes in aerosol concentrations. We utilise the susceptibility framework to quantify the potential change in LWP adjustment with boundary layer (BL) depth in subtropical marine stratocumulus. We show that the LWP susceptibility, i.e. the relative change in LWP scaled by the relative change in cloud droplet number concentration, in marine BLs triples in magnitude from −0.1 to −0.31 as the BL deepens from 300 to 1200 m and deeper. We further find deep BLs to be underrepresented in pollution tracks, process modelling, and in situ studies of aerosol–cloud interactions in marine stratocumulus. Susceptibility estimates based on these approaches are skewed towards shallow BLs of moderate LWP susceptibility. Therefore, extrapolating LWP susceptibility estimates from shallow BLs to the entire cloud climatology may underestimate the true LWP adjustment within subtropical stratocumulus and thus overestimate the effective aerosol radiative forcing in this region. Meanwhile, LWP susceptibility estimates in deep BLs remain poorly constrained. While susceptibility estimates in shallow BLs are found to be consistent with process modelling studies, they overestimate pollution track estimates.

scholarly journals Evaluation of aerosol and cloud properties in three climate models using MODIS observations and its corresponding COSP simulator, and their application in aerosol-cloud interaction

2019 ◽  
Author(s):  
Giulia Saponaro ◽  
Moa K. Sporre ◽  
David Neubauer ◽  
Harri Kokkola ◽  
Pekka Kolmonen ◽  
...  
Keyword(s):  
Optical Depth ◽  
Climate Models ◽  
Cloud Droplet ◽  
Global Scale ◽  
Cloud Optical Depth ◽  
Aerosol Cloud ◽  
Cloud Properties ◽  
Direct Model ◽  
Land Surfaces ◽  
Aerosol Cloud Interactions

Abstract. The evaluation of modeling diagnostics with appropriate observations is an important task that establishes the capabilities and reliability of models. In this study we compare aerosol and cloud properties obtained from three different climate models ECHAM-HAM, ECHAM-HAM-SALSA, and NorESM with satellite observations using MOderate Resolution Imaging Spectrometer (MODIS) data. The simulator MODIS-COSP version 1.4 was implemented into the climate models to obtain MODIS-like cloud diagnostics, thus enabling model to model and model to satellite comparisons. Cloud droplet number concentrations (CDNC) are derived identically from MODIS-COSP simulated and MODIS-retrieved values of cloud optical depth and effective radius. For CDNC, the models capture the observed spatial distribution of higher values typically found near the coasts, downwind of the major continents, and lower values over the remote ocean and land areas. However, the COSP-simulated CDNC values are higher than those observed, whilst the direct model CDNC output is significantly lower than the MODIS-COSP diagnostics. NorESM produces large spatial biases for ice cloud properties and thick clouds over land. Despite having identical cloud modules, ECHAM-HAM and ECHAM-HAM-SALSA diverge in their representation of spatial and vertical distribution of clouds. From the spatial distributions of aerosol optical depth (AOD) and aerosol index (AI), we find that NorESM shows large biases for AOD over bright land surfaces, while discrepancies between ECHAM-HAM and ECHAM-HAM-SALSA can be observed mainly over oceans. Overall, the AIs from the different models are in good agreement globally, with higher negative biases on the Northern Hemisphere. We computed the aerosol-cloud interactions as the sensitivity of dln(CDNC)/dln(AI) on a global scale. However, one year of data may be considered not enough to assess the similarity or dissimilarities of the models due to large temporal variability in cloud properties. This study shows how simulators facilitate the evaluation of cloud properties and expose model deficiencies which are necessary steps to further improve the parametrization in climate models.

scholarly journals Evaluation of aerosol and cloud properties in three climate models using MODIS observations and its corresponding COSP simulator, as well as their application in aerosol–cloud interactions

2020 ◽  
Vol 20 (3) ◽  
pp. 1607-1626 ◽  
Author(s):  
Giulia Saponaro ◽  
Moa K. Sporre ◽  
David Neubauer ◽  
Harri Kokkola ◽  
Pekka Kolmonen ◽  
...  
Keyword(s):  
Optical Depth ◽  
Climate Models ◽  
Cloud Droplet ◽  
Global Scale ◽  
Cloud Optical Depth ◽  
Aerosol Cloud ◽  
Cloud Properties ◽  
Direct Model ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Aerosol Cloud Interactions

Abstract. The evaluation of modelling diagnostics with appropriate observations is an important task that establishes the capabilities and reliability of models. In this study we compare aerosol and cloud properties obtained from three different climate models (ECHAM-HAM, ECHAM-HAM-SALSA, and NorESM) with satellite observations using Moderate Resolution Imaging Spectroradiometer (MODIS) data. The simulator MODIS-COSP version 1.4 was implemented into the climate models to obtain MODIS-like cloud diagnostics, thus enabling model-to-model and model-to-satellite comparisons. Cloud droplet number concentrations (CDNCs) are derived identically from MODIS-COSP-simulated and MODIS-retrieved values of cloud optical depth and effective radius. For CDNC, the models capture the observed spatial distribution of higher values typically found near the coasts, downwind of the major continents, and lower values over the remote ocean and land areas. However, the COSP-simulated CDNC values are higher than those observed, whilst the direct model CDNC output is significantly lower than the MODIS-COSP diagnostics. NorESM produces large spatial biases for ice cloud properties and thick clouds over land. Despite having identical cloud modules, ECHAM-HAM and ECHAM-HAM-SALSA diverge in their representation of spatial and vertical distributions of clouds. From the spatial distributions of aerosol optical depth (AOD) and aerosol index (AI), we find that NorESM shows large biases for AOD over bright land surfaces, while discrepancies between ECHAM-HAM and ECHAM-HAM-SALSA can be observed mainly over oceans. Overall, the AIs from the different models are in good agreement globally, with higher negative biases in the Northern Hemisphere. We evaluate the aerosol–cloud interactions by computing the sensitivity parameter ACICDNC=dln⁡(CDNC)/dln⁡(AI) on a global scale. However, 1 year of data may be considered not enough to assess the similarity or dissimilarities of the models due to large temporal variability in cloud properties. This study shows how simulators facilitate the evaluation of cloud properties and expose model deficiencies, which are necessary steps to further improve the parameterisation in climate models.

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