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We compare the radiative feedbacks resulting from a uniform warming and cooling of sea surface temperatures by 4 K in an ensemble of global climate models. The global-mean net feedback is less stabilising in response to warming in all nine models. This is primarily due to a stronger tropical water vapour feedback, with a smaller contribution from the shortwave cloud feedback. The zonal-mean feedbacks are similarly robust across the ensemble. In the extra-tropics, more positive shortwave cloud feedback under warming is associated with further poleward migration of the mean Southern Hemisphere jet latitude in some models. However, additional experiments with an aquaplanet version of the HadGEM3 model suggest that the asymmetry of the jet shift is not driving that in the cloud feedbacks at these latitudes. In the tropics, stronger water vapour feedback under warming is offset by a weaker shortwave cloud feedback. The result is that the ensemble spread in the differences between the global feedbacks under warming and cooling is mainly determined by their differences in the tropics. The spatial distribution of the feedbacks largely reflects the zonal mean behaviour, although there is considerable intermodel variation in the regional cloud feedbacks, particularly in the tropical shortwave cloud feedback. Comparison with CO2- and solar-forced coupled experiments suggests that the global-mean longwave cloud feedback is nearly invariant to warming and cooling, regardless of the nature of the forcing. The shortwave cloud feedback is generally more positive under warming in the coupled models, consistent with the uniform SST perturbation experiments.

The extratropical shortwave (SW) cloud feedback is primarily due to increases in extratropical liquid cloud extent and optical depth. Here, we examine the response of extratropical (35°–75°) marine cloud liquid water path (LWP) to a uniform 4-K increase in sea surface temperature (SST) in global climate models (GCMs) from phase 5 of the Coupled Model Intercomparison Project (CMIP5) and variants of the HadGEM3-GC3.1 GCM. Compositing is used to partition data into periods inside and out of cyclones. The response of extratropical LWP to a uniform SST increase and associated atmospheric response varies substantially among GCMs, but the sensitivity of LWP to cloud controlling factors (CCFs) is qualitatively similar. When all other predictors are held constant, increasing moisture flux drives an increase in LWP. Increasing SST, holding all other predictors fixed, leads to a decrease in LWP. The combinations of these changes lead to LWP, and by extension reflected SW, increasing with warming in both hemispheres. Observations predict an increase in reflected SW over oceans of 0.8–1.6 W m−2per kelvin SST increase (35°–75°N) and 1.2–1.9 W m−2per kelvin SST increase (35°–75°S). This increase in reflected SW is mainly due to increased moisture convergence into cyclones because of increasing available moisture. The efficiency at which converging moisture is converted into precipitation determines the amount of liquid cloud. Thus, cyclone precipitation processes are critical to constraining extratropical cloud feedbacks.

International audience; We investigate the dependence of radiative feedback on the pattern of sea-surface temperature (SST) change in 14 Atmospheric General Circulation Models (AGCMs) forced with observed variations in SST and sea-ice over the historical record from 1871 to near-present. We find that over 1871-1980, the Earth warmed with feedbacks largely consistent and strongly correlated with long-term climate sensitivity feedbacks (diagnosed from corresponding atmosphere-ocean GCM abrupt-4xCO2 simulations). Post 1980, however, the Earth warmed with unusual trends in tropical Pacific SSTs (enhanced warming in the west, cooling in the east) and cooling in the Southern Ocean that drove climate feedback to be uncorrelated with—and indicating much lower climate sensitivity than—that expected for long-term CO2 increase. We show that these conclusions are not strongly dependent on the Atmospheric Model Intercomparison Project (AMIP) II SST data set used to force the AGCMs, though the magnitude of feedback post 1980 is generally smaller in nine AGCMs forced with alternative HadISST1 SST boundary conditions. We quantify a "pattern effect" (defined as the difference between historical and long-term CO2 feedback) equal to 0.48 ± 0.47 [5%-95%] W m-2 K-1 for the time-period 1871-2010 when the AGCMs are forced with HadISST1 SSTs, or 0.70 ± 0.47 [5%-95%] W m-2 K-1 when forced with AMIP II SSTs. Assessed changes in the Earth's historical energy budget agree with the AGCM feedback estimates. Furthermore satellite observations of changes in top-of-atmosphere radiative fluxes since 1985 suggest that the pattern effect was particularly strong over recent decades but may be waning post 2014.

We analyze the atmospheric processes that explain the large changes in radiative feedbacks between the two latest climate configurations of the Hadley Centre Global Environmental model. We use a large set of atmosphere‐only climate change simulations (amip and amip‐p4K) to separate the contributions to the differences in feedback parameter from all the atmospheric model developments between the two latest model configurations. We show that the differences are mostly driven by changes in the shortwave cloud radiative feedback in the midlatitudes, mainly over the Southern Ocean. Two new schemes explain most of the differences: the introduction of a new aerosol scheme and the development of a new mixed‐phase cloud scheme. Both schemes reduce the strength of the preexisting shortwave negative cloud feedback in the midlatitudes. The new aerosol scheme dampens a strong aerosol‐cloud interaction, and it also suppresses a negative clear‐sky shortwave feedback. The mixed‐phase scheme increases the amount of cloud liquid water path (LWP) in the present day and reduces the increase in LWP with warming. Both changes contribute to reducing the negative radiative feedback of the increase of LWP in the warmer climate. The mixed‐phase scheme also enhances a strong, preexisting, positive cloud fraction feedback. We assess the realism of the changes by comparing present‐day simulations against observations and discuss avenues that could help constrain the relevant processes., Key Points Large changes in shortwave cloud feedbacks exist between two recent configurations of Met Office modelChanges in midlatitude feedbacks explain most of the global‐mean differencesThe new aerosol and mixed‐phase schemes explain most of the feedback differences

The latest configuration of the Hadley Centre Global Environmental Model version 3 (HadGEM3) contains significant changes in the formulation of warm rain processes and aerosols. We evaluate the impacts of these changes in the simulation of warm rain formation processes using A-Train observations. We introduce a new model evaluation tool, quartile-based Contoured Frequency by Optical Depth Diagrams (CFODDs), in order to fill in some blind spots that conventional CFODDs have. Results indicate that HadGEM3 has weak linkage between the size of particle radius and warm rain formation processes, and switching to the new warm rain microphysics scheme causes more difference in warm rain formation processes than switching to the new aerosol scheme through reducing overly produced drizzle mode in HadGEM3. Finally, we run an experiment in which we perturb the second aerosol indirect effect (AIE) to study the rainfall-aerosol interaction in HadGEM3. Since the large changes in the cloud droplet number concentration (CDNC) appear in the AIE experiment, a large impact in warm rain diagnostics is expected. However, regions with large fractional changes in CDNC show a muted change in precipitation, arguably because large-scale constraints act to reduce the impact of such a big change in CDNC. The adjustment in cloud liquid water path to the AIE perturbation produces a large negative shortwave forcing in the midlatitudes.

In this work, we use the Clouds and the Earth’s Radiant Energy System (CERES) FluxByCloudTyp data product, which calculates TOA shortwave and longwave fluxes for cloud categories defined by cloud optical depth (τ) and cloud top pressure (p(c)), to evaluate the HadGEM2-A model with a simulator. The CERES Flux-by-cloud type simulator is comprised of a cloud generator that produces subcolumns with profiles of binary cloud fraction, a cloud property simulator that determines the (τ, p(c)) cloud type for each subcolumn, and a radiative transfer model that calculates TOA fluxes. The identification of duplicate atmospheric profiles reduces the number of radiative transfer calculations required by approximately 97.6%. In the Southern Great Plains region in JFD (January, February, and December) 2008, the simulator shows that simulated cloud tops are higher in altitude than observed, but also have higher values of OLR than observed, leading to a compensating error that results in an average value of OLR that is close to observed. When the simulator is applied to the Southeast Pacific stratocumulus region in JJA 2008, the simulated cloud tops are primarily low in altitude; however, the clouds tend to be less numerous, and have higher optical depths than are observed. In addition to the increase in albedo that comes from having too many clouds with higher optical depth, the HadGEM2-A albedo is higher than observed for those cloud types that occur most frequently. The simulator is also applied to the entire 60° N – 60° S region, and it is found that there are fewer clouds than observed for most cloud types, but there are also higher albedos for most cloud types, which represents a compensating error in terms of the shortwave radiative budget.

The importance of heat transport in the ocean to maintain energy balance between different regions is well known, with heat typically being transported from the Equator to high latitudes. Ocean heat transport (OHT) can be separated into two different components; a divergent component which contributes directly to the Earths’ energy budget as it is the energy that converges in an ocean basin to balance the release of heat into the atmosphere, and a rotational component which does not affect the energy budget. Climate models show significant uncertainty in projections of ocean heat uptake, both in terms of the magnitude and geographical pattern. Since the oceans’ response under climate changes depends on the patterns of surface energy fluxes, it is important to assess the simulation of surface fluxes as a potential constraint of transient and long-term responses of the Earths’ climate. Assuming that the ocean absorbs all of the excess energy within the Earth system, it is possible to directly relate the net surface flux (NSF) over the ocean to divergent OHT, potentially providing a metric to quantify how well climate models are able to reproduce observed patterns of NSF and OHT. In this work, we present a detailed comparison of different methods used to calculate divergent OHT from the NSF over the ocean using data from various CMIP6 models. The methods investigated include a least-squares solution to a matrix equation in which energy convergence is related to NSF via the Earths’ energy imbalance, and solving a Poisson equation over the ocean surface (see Forget and Ferreira 2020). Comparison to observational estimates of OHT requires that the observational data set includes only sources of divergent heat transport, which is often not the case. Therefore, we intend to produce a data set of radiative energy fluxes that are consistent with both energy and water constraints (see Rodell et al. 2015, L’Ecuyer et al. 2015, Thomas et al. 2020) which can be subject to the same methods of determining OHT, and see how these estimates compare to the results from climate models.

The configuration of the Met Office Unified Model being submitted to CMIP6 has a high climate sensitivity. Previous studies have suggested that the impact of model changes on initial tendencies in numerical weather prediction (NWP) should be used to guide their suitability for inclusion in climate models. In this study we assess, using NWP experiments, the atmospheric model changes which lead to the increased climate sensitivity in the CMIP6 configuration, namely, the replacement of the aerosol scheme with GLOMAP‐mode and the introduction of a scheme for representing the turbulent production of liquid water within mixed‐phase cloud. Overall, the changes included in this latest configuration were found to improve the initial tendencies of the model state variables over the first 6 hr of the forecast, this timescale being before significant dynamical feedbacks are likely to occur. The reduced model drift through the forecast appears to be the result of increased cloud liquid water, leading to enhanced radiative cooling from cloud top and contributing to a stronger shortwave cloud radiative effect. These changes improve the 5‐day forecast in traditional metrics used for numerical weather prediction. This study was conducted after the model was frozen and the climate sensitivity of the model determined; hence, it provides an independent test of the model changes contributing to the higher climate sensitivity. The results, along with the large body process‐orientated evaluation conducted during the model development process, provide reassurance that these changes are improving the physical processes simulated by the model.

Global climate models (GCMs) differ greatly in their shortwave cloud feedback. One feature that is consistent across GCMs is a positive shortwave cloud feedback in the subtropics, and a negative shortwave cloud feedback across the midlatitudes. Confidence has grown in the mechanisms that lead to, and the strength of, the subtropical shortwave cloud feedback, but the midlatitude negative shortwave cloud feedback is not well-constrained or well-understood. It is critical to reduce uncertainty in midlatitude shortwave cloud feedback. A more positive midlatitude shortwave cloud feedback in the sixth coupled model intercomparison project (CMIP6) has been found to be one of the primary causes of the increased climate sensitivity of CMIP6 models relative to CMIP5. We show that changes in midlatitude cyclones in future climates are the primary cause of the negative shortwave cloud feedback and are thus key to understanding the high climate sensitivity in the most recent GCMs. Warming-induced changes in cloud liquid water path in midlatitude cyclones can almost entirely be explained by Clausius-Clapeyron increasing moisture convergence into cyclones. One concern with simulating midlatitude cyclones is the lack of predictive skill at low resolution. A more realistic relationship between moisture flux and cyclone liquid content is found at high horizontal resolution (∆x Predicted midlatitude cloud feedbacks based on convection-permitting model output (model output is shown in a). The moisture flux along the warm conveyor belt (WCB) of a cyclone plays a central role in determining cyclone cloud liquid water path (LWP) (b). Because WCB scales with water vapor path (WVP) and surface wind speed, WCB moisture flux increases following Clausius-Clapeyron and predicts a negative midlatitude cloud feedback.

The contribution of cloud to the radiation budget of southern West Africa (SWA) is poorly understood and yet it is important for understanding regional monsoon evolution and for evaluating and improving climate models, which have large biases in this region. Radiative transfer calculations applied to atmospheric profiles obtained from the CERES– CloudSat–CALIPSO–MODIS (CCCM) dataset are used to investigate the effects of 12 different cloud types (defined by their vertical structure) on the regional energy budget of SWA (5°–10°N, 8°W–8°E) during June–September. We show that the large regional mean cloud radiative effect in SWA is due to nonnegligible contributions from many different cloud types; eight cloud types have a cloud fraction larger than 5% and contribute at least 5% of the regional mean shortwave cloud radiative effect at the top of the atmosphere. Low clouds, which are poorly observed by passive satellite measurements, were found to cause net radiative cooling of the atmosphere, which reduces the heating from other cloud types by approximately 10%. The sensitivity of the radiation budget to underestimating low-cloud cover is also investigated. The radiative effect of missing low cloud is found to be up to approximately −25 W m−2 for upwelling shortwave irradiance at the top of the atmosphere and 35 W m−2 for downwelling shortwave irradiance at the surface.

Climate models show a robust negative feedback in the midlatitudes, coincident with an increase in cloud liquid in the mixed-phase region of the control climate. This 'mixed-phase feedback' is normally attributed to a feedback caused by a phase-change feedback (ice to liquid). Here we use an aquaplanet configuration to investigate this in more detail. We use high-frequency instantaneous diagnostics and composite them in ascending and descending regimes. We find that a large fraction of the increase in cloud liquid water in the mixed-phase region does not significantly contribute to the radiative feedback due to a masking effect of the ice cloud above. Using some simple arguments and approximate calculations, we estimate that about one-third of the total shortwave negative radiative feedback is driven by a phase-change feedback, whereas the rest of the feedback is driven by changes in ice and warm liquid clouds.

The Global Coupled 3 (GC3) configuration of the Met Office Unified Model is presented. Amongst other applications, GC3 is the basis of the United Kingdom's submission to the Coupled Model Intercomparison Project 6 (CMIP6). This paper documents the model components that make up the configuration (although the scientific description of these components are in companion papers), and details the coupling between them. The performance of GC3 is assessed in terms of mean biases and variability in long climate simulations using present-day forcing. The suitability of the configuration for predictabiity on shorter timescales (weather and seasonal forecasting) is also briefly discussed. The performance of GC3 is compared against GC2, the previous Met Office coupled model configuration, and against an older configuration (HadGEM2-AO) which was the submission to CMIP5. In many respects, the performance of GC3 is comparable with GC2, however there is a notable improvement in the Southern Ocean warm sea surface temperature bias which has been reduced by 75%, and there are improvements in cloud amount and some aspects of tropical variability. Relative to HadGEM2-AO, many aspects of the present-day climate are improved in GC3 including tropospheric and stratospheric temperature structure, most aspects of tropical and extra-tropical variability and top-of-atmosphere & surface fluxes. A number of outstanding errors are identified including a residual asymmetric sea surface temperature bias (cool northern hemisphere, warm Southern Ocean), an overly strong global hydrological cycle and insufficient European blocking.

The Cloud Feedback Model Intercomparison Project Observational Simulator Package (COSP) gathers together a collection of observation proxies or “satellite simulators” that translate model-simulated cloud properties to synthetic observations as would be obtained by a range of satellite observing systems. This paper introduces COSP2, an evolution focusing on more explicit and consistent separation between host model, coupling infrastructure, and individual observing proxies. Revisions also enhance flexibility by allowing for model-specific representation of sub-grid-scale cloudiness, provide greater clarity by clearly separating tasks, support greater use of shared code and data including shared inputs across simulators, and follow more uniform software standards to simplify implementation across a wide range of platforms. The complete package including a testing suite is freely available.

Since 2016, the South African Weather Service (SAWS) has been running convective-scale simulations to assist with forecast operations across southern Africa. These simulations are run with a tropical configuration of the Met Office Unified Model (UM), nested in the Met Office global model, but without data assimilation. For November 2016, convection-permitting simulations at 4.4- and 1.5-km grid lengths are compared against a simulation at 10-km grid length with convection parameterization (the current UM global atmosphere configuration) to identify the benefits of increasing model resolution for forecasting convection across southern Africa. The simulations are evaluated against satellite rainfall estimates, CloudSat vertical cloud profiles, and SAWS radar data. In line with previous studies using the UM, on a monthly time scale, the diurnal cycle of convection and the distribution of rainfall rates compare better against observations when convection-permitting model configurations are used. The SAWS radar network provides a three-dimensional composite of radar reflectivity for northeast South Africa at 6-min intervals, allowing the evaluation of the vertical development of precipitating clouds and of the timing of the onset of deep convection. Analysis of four case study days indicates that the 4.4-km simulations have a later onset of convection than the 1.5-km simulations, but there is no consistent bias of the simulations against the radar observations across the case studies.

A negative extratropical shortwave cloud feedback driven by changes in cloud optical depth is a feature of global climate models (GCMs). A robust positive trend in observed liquid water path (LWP) over the last two decades across the warming Southern Ocean supports the negative shortwave cloud feedback predicted by GCMs. This feature has been proposed to be due to transitions from ice to liquid with warming. To gain insight into the shortwave cloud feedback we examine extratropical cyclone variability and the response of extratropical cyclones to transient warming in GCM simulations. Multi-Sensor Advanced Climatology Liquid Water Path (MAC-LWP) microwave observations of cyclone properties from the period 1992–2015 are contrasted with GCM simulations, with horizontal resolutions ranging from 7 km to hundreds of kilometers. We find that inter-cyclone variability in LWP in both observations and models is strongly driven by the moisture flux along the cyclone's warm conveyor belt (WCB). Stronger WCB moisture flux enhances the LWP within cyclones. This relationship is replicated in GCMs, although its strength varies substantially across models. It is found that more than 80 % of the enhancement in Southern Hemisphere (SH) extratropical cyclone LWP in GCMs in response to a transient 4 K warming can be predicted based on the relationship between the WCB moisture flux and cyclone LWP in the historical climate and their change in moisture flux between the historical and warmed climates. Further, it is found that that the robust trend in cyclone LWP over the Southern Ocean in observations and GCMs is consistent with changes in the moisture flux. We propose two cloud feedbacks acting within extratropical cyclones: a negative feedback driven by Clausius–Clapeyron increasing water vapor path (WVP), which enhances the amount of water vapor available to be fluxed into the cyclone, and a feedback moderated by changes in the life cycle and vorticity of cyclones under warming, which changes the rate at which existing moisture is imported into the cyclone. Both terms contribute to increasing LWP within the cyclone. While changes in moisture flux predict cyclone LWP trends in the current climate and the majority of changes in LWP in transient warming simulations, a portion of the LWP increase in response to climate change that is unexplained by increasing moisture fluxes may be due to phase transitions. The variability in LWP within cyclone composites is examined to understand what cyclonic regimes the mixed-phase cloud feedback is relevant to. At a fixed WCB moisture flux cyclone LWP increases with increasing sea surface temperature (SST) in the half of the composite poleward of the low and decreases in the half equatorward of the low in both GCMs and observations. Cloud-top phase partitioning observed by the Atmospheric Infrared Sounder (AIRS) indicates that phase transitions may be driving increases in LWP in the poleward half of cyclones.

The primary objective of CFMIP is to inform future assessments of cloud feedbacks through improved understanding of cloud–climate feedback mechanisms and better evaluation of cloud processes and cloud feedbacks in climate models. However, the CFMIP approach is also increasingly being used to understand other aspects of climate change, and so a second objective has now been introduced, to improve understanding of circulation, regional-scale precipitation, and non-linear changes. CFMIP is supporting ongoing model inter-comparison activities by coordinating a hierarchy of targeted experiments for CMIP6, along with a set of cloud-related output diagnostics. CFMIP contributes primarily to addressing the CMIP6 questions How does the Earth system respond to forcing? and What are the origins and consequences of systematic model biases? and supports the activities of the WCRP Grand Challenge on Clouds, Circulation and Climate Sensitivity.A compact set of Tier 1 experiments is proposed for CMIP6 to address this question: (1) what are the physical mechanisms underlying the range of cloud feedbacks and cloud adjustments predicted by climate models, and which models have the most credible cloud feedbacks? Additional Tier 2 experiments are proposed to address the following questions. (2) Are cloud feedbacks consistent for climate cooling and warming, and if not, why? (3) How do cloud-radiative effects impact the structure, the strength and the variability of the general atmospheric circulation in present and future climates? (4) How do responses in the climate system due to changes in solar forcing differ from changes due to CO2, and is the response sensitive to the sign of the forcing? (5) To what extent is regional climate change per CO2 doubling state-dependent (non-linear), and why? (6) Are climate feedbacks during the 20th century different to those acting on long-term climate change and climate sensitivity? (7) How do regional climate responses (e.g. in precipitation) and their uncertainties in coupled models arise from the combination of different aspects of CO2 forcing and sea surface warming?CFMIP also proposes a number of additional model outputs in the CMIP DECK, CMIP6 Historical and CMIP6 CFMIP experiments, including COSP simulator outputs and process diagnostics to address the following questions. How well do clouds and other relevant variables simulated by models agree with observations?What physical processes and mechanisms are important for a credible simulation of clouds, cloud feedbacks and cloud adjustments in climate models?Which models have the most credible representations of processes relevant to the simulation of clouds?How do clouds and their changes interact with other elements of the climate system?

The Southern Ocean is a pivotal component of the global climate system yet it is poorly represented in climate models, with significant biases in upper-ocean temperatures, clouds and winds. Combining Atmospheric and Coupled Model Inter-comparison Project (AMIP5/CMIP5) simulations, with observations and equilibrium heat budget theory, we show that across the CMIP5 ensemble variations in sea surface temperature biases in the 40–60°S Southern Ocean are primarily caused by AMIP5 atmospheric model net surface flux bias variations, linked to cloud-related short-wave errors. Equilibration of the biases involves local coupled sea surface temperature bias feedbacks onto the surface heat flux components. In combination with wind feedbacks, these biases adversely modify upper-ocean thermal structure. Most AMIP5 atmospheric models that exhibit small net heat flux biases appear to achieve this through compensating errors. We demonstrate that targeted developments to cloud-related parameterisations provide a route to better represent the Southern Ocean in climate models and projections., The Southern Ocean is critically important for global climate yet poorly represented by climate models. Here the authors trace sea surface temperature biases in this region to cloud-related errors in atmospheric-model simulated surface heat fluxes and provide a pathway to improve the models.

The concept of feedback is key in assessing whether a perturbation to a system is amplified or damped by mechanisms internal to the system. In polar regions, climate dynamics are controlled by both radiative and non-radiative interactions between the atmosphere, ocean, sea ice, ice sheets and land surfaces. Precisely quantifying polar feedbacks is required for a process-oriented evaluation of climate models, a clear understanding of the processes responsible for polar climate changes, and a reduction in uncertainty associated with model projections. This quantification can be performed using a simple and consistent approach that is valid for a wide range of feedbacks, offering the opportunity for more systematic feedback analyses and a better understanding of polar climate changes., Estimating the magnitude of radiative and non-radiative feedbacks is key for understanding the climate dynamics of polar regions. Here the authors propose an inclusive methodology to quantify the influence of all those feedbacks, stimulating more systematic analyses in observational and model ensembles.

A new framework is presented for analysing the causes of model sea ice biases, demonstrated with the CMIP5 model HadGEM2-ES. Arctic sea ice extent has decreased over recent decades and has reached historic minima in late summer in recent years. Climate models project an ice-free Arctic in late summer during the 21st century, with wide-ranging implications for global climate and geopolitics. However, substantial spread remains in climate model projections of the rate of sea ice decline, with drivers poorly understood. In the framework described, the sea ice volume is treated as a consequence of the integrated surface energy balance. A system of simple models allows specific portions of the surface flux anomaly to be attributed to individual processes by calculating for each process an induced surface flux anomaly. The method allows detailed quantification of the role played by the surface albedo and ice thickness-growth feedbacks in causing anomalous sea ice melt and growth. It shows biases in the HadGEM2-ES sea ice volume simulation to be due to a bias in spring surface melt onset date, partly countered by a counteracting bias in winter downwelling longwave radiation. The framework is applicable in principle to any model and has the potential to greatly improve understanding of the reasons for ensemble spread in modelled sea ice state.

The Earth's hemispheric reflectances are equivalent to within ± 0.2 Wm-2, even though the Northern Hemisphere contains a greater proportion of higher reflectance land areas, because of greater cloud cover in the Southern Hemisphere. This equivalence is unlikely to be by chance, but the reasons are open to debate. Here we show that equilibrating hemispheric albedos in the Hadley Centre Global Environment Model version 2-Earth System coupled climate model significantly improves what have been considered longstanding and apparently intractable model biases. Monsoon precipitation biases over all continental land areas, the penetration of monsoon rainfall across the Sahel, the West African monsoon 'jump', and indicators of hurricane frequency are all significantly improved. Mechanistically, equilibrating hemispheric albedos improves the atmospheric cross-equatorial energy transport and increases the supply of tropical atmospheric moisture to the Hadley cell. We conclude that an accurate representation of the cross-equatorial energy transport appears to be critical if tropical performance is to be improved.

This study examines the warm rain formation process over the global ocean in global climate models. Methodologies developed to analyze CloudSat and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite observations are employed to investigate the cloud-to-precipitation process of warm clouds and are applied to the model results to examine how the models represent the process for warm stratiform clouds. Despite a limitation of the present study that compares the statistics for stratiform clouds in climate models with those from satellite observations, including both stratiform and (shallow) convective clouds, the statistics constructed with the methodologies are compared between the models and satellite observations to expose their similarities and differences. A problem common to some models is that they tend to produce rain at a faster rate than is observed. These model characteristics are further examined in the context of cloud microphysics parameterizations using a simplified one-dimensional model of warm rain formation that isolates key microphysical processes from full interactions with other processes in global climate models. The one-dimensional model equivalent statistics reproduce key characteristics of the global model statistics when corresponding autoconversion schemes are assumed in the one-dimensional model. The global model characteristics depicted by the statistics are then interpreted as reflecting behaviors of the autoconversion parameterizations adopted in the models. Comparisons of the one-dimensional model with satellite observations hint at improvements to the formulation of the parameterization scheme, thus offering a novel way of constraining key parameters in autoconversion schemes of global models.

Future responses of cloud regimes are analyzed for five CMIP5 models forced with observed SSTs and subject to a patterned SST perturbation. Correlations between cloud properties in the control climate and changes in the warmer climate are investigated for each of a set of cloud regimes defined using a clustering methodology. The only significant (negative) correlation found is in the in-regime net cloud radiative effect for the stratocumulus regime. All models overestimate the in-regime albedo of the stratocumulus regime. Reasons for this bias and its relevance to the future response are investigated. A detailed evaluation of the models’ daily-mean contributions to the albedo from stratocumulus clouds with different cloud cover fractions reveals that all models systematically underestimate the relative occurrence of overcast cases but overestimate those of broken clouds. In the warmer climate the relative occurrence of overcast cases tends to decrease while that of broken clouds increases. This suggests a decrease in the climatological in-regime albedo with increasing temperature (a positive feedback); this is opposite to the feedback suggested by the analysis of the bulk in-regime albedo. Furthermore we find that the inter-model difference in the sign of the in-cloud albedo feedback is consistent with the difference in sign of the in-cloud liquid water path response, and there is a strong positive correlation between the in-regime liquid water path in the control climate and its response to warming. We therefore conclude that further breakdown of the in-regime properties into cloud cover and in-cloud properties is necessary to better understand the behavior of the stratocumulus regime. Since cloud water is a physical property and is independent of a model’s radiative assumptions, it could potentially provide a useful emergent constraint on cloud feedback.

The Cloud Feedback Model Intercomparison Project Observational Simulator Package (COSP) gathers together a collection of observation proxies or satellite simulators that translate model-simulated cloud properties to synthetic observations as would be obtained by a range of satellite observing systems. This paper introduces COSP 2, an evolution focusing on more explicit and consistent separation between host model, coupling infrastructure, and individual observing proxies. Revisions also enhance flexibility by allowing for model-specific representation of sub-grid scale cloudiness, provide greater clarity by clearly separating tasks, support greater use of shared code and data including shared inputs across simulators, and follow more uniform software standards to simplify implementation across a wide range of platforms. The complete package including a testing suite is freely available.

International audience; We examine the diurnal cycle of marine cloud feedback using high frequency outputs in CFMIP-2 idealised uniform +4 K SST perturbation experiments from seven CMIP5 models. Most of the inter-model spread in the diurnal mean marine shortwave cloud feedback can be explained by low cloud responses, although these do not explain the model responses at the neutral/weakly negative end of the feedback range, where changes in mid and high level cloud properties are more important. All of the models show reductions in marine low cloud fraction in the warmer climate, and these are in almost all cases largest in the mornings when more cloud is present in the control simulations. This results in shortwave cloud feedbacks being slightly stronger and having the largest inter-model spread at this time of day. The diurnal amplitudes of the responses of marine cloud properties to the warming climate are however small compared to the inter-model differences in their diurnally meaned responses. This indicates that the diurnal cycle of cloud feedback is not strongly relevant to understanding inter-model spread in overall cloud feedback and climate sensitivity. A number of unusual behaviours in individual models are highlighted for future investigation. © 2014 Crown Copyright.

[1] This study uses a regime sorting technique to explore the relationships that ACCESS1.3 clouds have with the large-scale environment. Satellite simulator output is used to demonstrate that the modeled clouds have similar sensitivity to the large-scale dynamic and thermodynamic conditions as shown by CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO). The high cloud cover and longwave cloud radiative effect is represented very well in the model across all regimes. The cloud types that the model simulates the most poorly are stratocumulus over cool sea surface temperatures (SSTs) and the deep convective regimes associated with strong upward midtropospheric vertical velocity and weak lower tropospheric stabilities. The reflectance of the deep convective regimes shows a stronger sensitivity to SST and less dependence on the large-scale dynamics than the observations. Many of the model errors identified occur across all regimes, such as the underestimate of clouds with large scattering ratios (SR) and the too frequent occurrence of drizzle and rain. A sensitivity test in which a different warm rain scheme was used shows that the modelled frequency of occurrence of nonprecipitating low cloud is quite sensitive to the autoconversion parameterization. The new scheme produced more cloud with large SR and higher cloud tops in better agreement with the observations. The thermodynamic regime analysis shows that the transition of shallow to deeper convection in the model requires a warmer SST and weaker LTS than the observations. The significant underestimate of cumulus congestus is likely to contribute to this delay due to the role these clouds have in preconditioning the midtroposphere for the onset of deep convection.

The Transpose-Atmospheric Model Intercomparison Project (AMIP) is an international model intercomparison project in which climate models are run in “weather forecast mode.” The Transpose-AMIP II experiment is run alongside phase 5 of the Coupled Model Intercomparison Project (CMIP5) and allows processes operating in climate models to be evaluated, and the origin of climatological biases to be explored, by examining the evolution of the model from a state in which the large-scale dynamics, temperature, and humidity structures are constrained through use of common analyses. The Transpose-AMIP II experimental design is presented. The project requests participants to submit a comprehensive set of diagnostics to enable detailed investigation of the models to be performed. An example of the type of analysis that may be undertaken using these diagnostics is illustrated through a study of the development of cloud biases over the Southern Ocean, a region that is problematic for many models. Several models share a climatological bias for too little reflected shortwave radiation from cloud across the region. This is found to mainly occur behind cold fronts and/or on the leading side of transient ridges and to be associated with more stable lower-tropospheric profiles. Investigation of a case study that is typical of the bias and associated meteorological conditions reveals the models to typically simulate cloud that is too optically and physically thin with an inversion that is too low. The evolution of the models within the first few hours suggests that these conditions are particularly sensitive and a positive feedback can develop between the thinning of the cloud layer and boundary layer structure.

Most studies evaluating cloud in general circulation models present new diagnostic techniques or observational datasets, or apply a limited set of existing diagnostics to a number of models. In this study, we use a range of diagnostic techniques and observational datasets to provide a thorough evaluation of cloud, such as might be carried out during a model development process. The methodology is illustrated by analysing two configurations of the Met Office Unified Model – the currently operational configuration at the time of undertaking the study (Global Atmosphere 6, GA6), and the configuration which will underpin the United Kingdom's Earth System Model for CMIP6 (Coupled Model Intercomparison Project 6) (GA7). By undertaking a more comprehensive analysis which includes compositing techniques, comparing against a set of quite different observational instruments and evaluating the model across a range of timescales, the risks of drawing the wrong conclusions due to compensating model errors are minimised and a more accurate overall picture of model performance can be drawn. Overall the two configurations analysed perform well, especially in terms of cloud amount. GA6 has excessive thin cirrus which is removed in GA7. The primary remaining errors in both configurations are the in-cloud albedos which are too high in most northern hemisphere cloud types and sub-tropical stratocumulus, whilst the stratocumulus on the cold air side of southern hemisphere cyclones has in-cloud albedo's which are too low.

[1] Cloud properties from the Australian Community Climate and Earth System Simulator (ACCESS1.3) are evaluated using the Cloud Feedback Model Intercomparison Project (CFMIP) Observational Simulator Package (COSP). CloudSat, CALIPSO, and International Satellite Cloud Climatology Project (ISCCP) observations are used to evaluate the modeled cloud cover, condensate properties, and cloud optical depths for two seasons. The global distribution of cloud in the model is generally well represented with maximum high cloud in the tropics and low cloud over the eastern edges of the ocean basins. The model captures the observed position of the midlatitude storm track clouds and the modeled cloud top heights compare well with the observations in the upper troposphere. However, there is a lack of modeled midlevel cloud in the tropics and midlatitudes. The average high cloud cover in the Tropical Warm Pool region shows good agreement with CALIPSO. However, the modeled radar reflectivities and lidar scattering ratios are biased toward lower values, suggesting that the ice water contents and particles sizes of these clouds in the model are too small. Over the Southern Ocean the modeled cloud cover is underestimated due to a lack of mid- and low-level cloud. The low clouds over the Southern Ocean and the California stratocumulus clouds in the model have too little condensate and optical thickness and too much rain and drizzle. A sensitivity experiment showed that reducing the ice fall speeds improves aspects of the modeled cloud properties by increasing the frequency of occurrence of high clouds with large scattering ratios and optically thick low clouds. ACCESS1.3 has a reasonable representation of cloud. However, the underestimate of ice water content and particles sizes in high clouds and the too frequent occurrence of drizzle may impact the modeled cloud feedbacks and regional precipitation associated with current and perturbed climates.

The Southern Ocean is a critical region for global climate, yet large cloud and solar radiation biases over the Southern Ocean are a long-standing problem in climate models and are poorly understood, leading to biases in simulated sea surface temperatures. This study shows that supercooled liquid clouds are central to understanding and simulating the Southern Ocean environment. A combination of satellite observational data and detailed radiative transfer calculations is used to quantify the impact of cloud phase and cloud vertical structure on the reflected solar radiation in the Southern Hemisphere summer. It is found that clouds with supercooled liquid tops dominate the population of liquid clouds. The observations show that clouds with supercooled liquid tops contribute between 27% and 38% to the total reflected solar radiation between 40° and 70°S, and climate models are found to poorly simulate these clouds. The results quantify the importance of supercooled liquid clouds in the Southern Ocean environment and highlight the need to improve understanding of the physical processes that control these clouds in order to improve their simulation in numerical models. This is not only important for improving the simulation of present-day climate and climate variability, but also relevant for increasing confidence in climate feedback processes and future climate projections.

In this work, we use the Clouds and the Earth’s Radiant Energy System (CERES) FluxByCloudTyp data product, which calculates TOA shortwave and longwave fluxes for cloud categories defined by cloud optical depth (𝜏) and cloud top pressure (𝑝𝑐), to evaluate the HadGEM2-A model with a simulator. The CERES Flux-by-cloud type simulator is comprised of a cloud generator that produces subcolumns with profiles of binary cloud fraction, a cloud property simulator that determines the (𝜏,𝑝𝑐) cloud type for each subcolumn, and a radiative transfer model that calculates TOA fluxes. The identification of duplicate atmospheric profiles reduces the number of radiative transfer calculations required by approximately 97.6%. In the Southern Great Plains region in JFD (January, February, and December) 2008, the simulator shows that simulated cloud tops are higher in altitude than observed, but also have higher values of OLR than observed, leading to a compensating error that results in an average value of OLR that is close to observed. When the simulator is applied to the Southeast Pacific stratocumulus region in JJA 2008, the simulated cloud tops are primarily low in altitude; however, the clouds tend to be less numerous, and have higher optical depths than are observed. In addition to the increase in albedo that comes from having too many clouds with higher optical depth, the HadGEM2-A albedo is higher than observed for those cloud types that occur most frequently. The simulator is also applied to the entire 60o N – 60o S region, and it is found that there are fewer clouds than observed for most cloud types, but there are also higher albedos for most cloud types, which represents a compensating error in terms of the shortwave radiative budget.

Ice cloud representation in general circulation models remains a challenging task, due to the lack of accurate observations and the complexity of microphysical processes. In this article, we evaluate the ice water content (IWC) and ice cloud fraction statistical distributions from the numerical weather prediction models of the European Centre for Medium-Range Weather Forecasts (ECMWF) and the UK Met Office, exploiting the synergy between the CloudSat radar and CALIPSO lidar. Using the last three weeks of July 2006, we analyse the global ice cloud occurrence as a function of temperature and latitude and show that the models capture the main geographical and temperature-dependent distributions, but overestimate the ice cloud occurrence in the Tropics in the temperature range from −60 °C to −20 °C and in the Antarctic for temperatures higher than −20 °C, but underestimate ice cloud occurrence at very low temperatures. A global statistical comparison of the occurrence of grid-box mean IWC at different temperatures shows that both the mean and range of IWC increases with increasing temperature. Globally, the models capture most of the IWC variability in the temperature range between −60 °C and −5 °C, and also reproduce the observed latitudinal dependencies in the IWC distribution due to different meteorological regimes. Two versions of the ECMWF model are assessed. The recent operational version with a diagnostic representation of precipitating snow and mixed-phase ice cloud fails to represent the IWC distribution in the −20 °C to 0 °C range, but a new version with prognostic variables for liquid water, ice and snow is much closer to the observed distribution. The comparison of models and observations provides a much-needed analysis of the vertical distribution of IWC across the globe, highlighting the ability of the models to reproduce much of the observed variability as well as the deficiencies where further improvements are required.

In this paper an ensemble model of ice crystals previously used to simulate the shortwave scattering properties of cirrus is now applied to simulate its equivalent radar reflectivity (Ze) at 94 GHz. It is shown that the ensemble model conserves the mass of aggregating ice crystals when compared against in situ derived mass-dimensional (m-D) relationships. The ensemble model derived m-D relationship is applied to the Rayleigh –Gans approximation to obtain a new parametrized radar reflectivity forward model for general circulation models (GCMs). The derived forward model is parametrized as a function of ice mixing ratio and in-cloud temperature, and it is shown that the forward model error is generally well within ±2 dBZe using a linear fit; this new parametrization negates the need for an ‘effective diameter’. The Met Office Unified global Model (MetUM) predictions of ice water content (IWC) andZe are compared against profiledinsitu microphysical probe estimates of IWC andZe ,b ased oninsitu estimates. Theinsitu IWC profiles were obtained from a midlatitude cirrus case during an airborne campaign around the UK. The paper demonstrates that towards cloud-bottom and cloud-top the MetUM prediction of IWC is generally within and outside the experimental uncertainty, respectively. The MetUM forward simulation of Ze assumes two particle size distributions (PSDs) of differing shapes and it is shown that the broader PSD simulates Ze better when compared againstZe based oninsitu estimates for all altitudes. For the same case the PSD assumed in the CloudSat retrieval of IWC is also investigated and it is speculated that it could be too narrow towards cloud-bottom. The paper demonstrates the need for consistent PSDs when forward modelling Ze at 94 GHz, and the forward radar model error in the MetUM should be better characterized. Copyright c � 2011 British

Midlatitude cyclones taken from 18 months of global operational Met Office Unified Model analysis archives were combined to form three-dimensional composite cyclones. Given an accurate dynamical and thermodynamical representation of the atmosphere from 4D-Var analysis, this study attributes differences between observations and the model cloud/precipitation to potential shortcomings in the physical parametrizations that control cloud/precipitation. Coincident ( ± 6 h) data from CloudSat radar, AMSR-E microwave, and ISCCP flux products were collected into composites for comparison. Only cyclones over the ocean were analysed here. Considering all of the observations in a single composite shows that horizontal slices through the composite display qualitative agreement between the mean reflectivity structures seen in the UM and CloudSat data. Splitting the composite cyclone into quadrants reveals that the UM underpredicts fractions of reflectivities greater than –20 dBZ and + 10 dBZ at heights above 2 km in the poleward quadrants. This lack of cloud is manifested in smaller short-wave top-of-atmosphere fluxes from the UM composite cyclone than from the observations. Comparison of UM precipitation rates with CloudSat shows agreement to within the assumed potential bias of the observations. Copyright © 2011 British Crown copyright, the Met Office. Published by John Wiley & Sons Ltd.

International audience; Errors in the simulation of clouds in general circulation models (GCMs) remain a long-standing issue in climate projections, as discussed in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report. This highlights the need for developing new analysis techniques to improve our knowledge of the physical processes at the root of these errors. The Cloud Feedback Model Intercomparison Project (CFMIP) pursues this objective, and under that framework the CFMIP Observation Simulator Package (COSP) has been developed. COSP is a flexible software tool that enables the simulation of several satellite-borne active and passive sensor observations from model variables. The flexibility of COSP and a common interface for all sensors facilitates its use in any type of numerical model, from high-resolution cloud-resolving models to the coarser-resolution GCMs assessed by the IPCC, and the scales in between used in weather forecast and regional models. The diversity of model parameterization techniques makes the comparison between model and observations difficult, as some parameterized variables (e.g., cloud fraction) do not have the same meaning in all models. The approach followed in COSP permits models to be evaluated against observations and compared against each other in a more consistent manner. This permits a more detailed diagnosis of the physical processes that govern the behavior of clouds and precipitation in numerical models. The World Climate Research Programme (WCRP) Working Group on Coupled Modelling has recommended the use of COSP in a subset of climate experiments that will be assessed by the next IPCC report. In this article we describe COSP, present some results from its application to numerical models, and discuss future work that will expand its capabilities.

The partitioning of the earth radiation budget (ERB) between its atmosphere and surface components is of crucial interest in climate studies as it has a significant role in the oceanic and atmospheric general circulation. An analysis of the present-day climate simulation of the surface radiation budget in the atmospheric component of the new Hadley Centre Global Environmental Model version 1 (HadGEM1) is presented, and the simulations are assessed by comparing the results with fluxes derived from satellite data from the International Satellite Cloud Climatology Project (ISCCP) and ground measurements from the Baseline Surface Radiation Network (BSRN). Comparisons against radiative fluxes from satellite and ground observations show that the model tends to overestimate the surface incoming solar radiation (Ss,d). The model simulates Ss,d very well over the polar regions. Consistency in the comparisons against BSRN and ISCCP-FD suggests that the ISCCP-FD database is a good test for the performance of the surface downwelling solar radiation in climate model simulations. Overall, the simulation of downward longwave radiation is closer to observations than its shortwave counterpart. The model underestimates the downward longwave radiation with respect to BSRN measurements by 6.0 W m−2. Comparisons of land surface albedo from the model and estimates from the Moderate Resolution Imaging Spectroradiometer (MODIS) show that HadGEM1 overestimates the land surface albedo over deserts and over midlatitude landmasses in the Northern Hemisphere in January. Analysis of the seasonal cycle of the land surface albedo in different regions shows that the amplitude and phase of the seasonal cycle are not well represented in the model, although a more extensive validation needs to be carried out. Two decades of coupled model simulations of the twentieth-century climate are used to look into the model’s simulation of global dimming/brightening. The model results are in line with the conclusions of the studies that suggest that global dimming is far from being a uniform phenomenon across the globe.

The launch of the CloudSat cloud radar has provided some of the first near-global views of the threedimensional structure of clouds from space. To evaluate clouds in numerical models and compare them to the observations made by CloudSat, it is useful to have a tool that converts modeled clouds to radar returns that might be viewed by a radar system on a satellite passing over the model domain. QuickBeam is a user-friendly radar simulation package that performs this function and is freely available to the meteorological community. The workings of the simulator are briefly described and several applications of the simulator to numerical models are demonstrated.

The latest coupled configuration of the Met Office Unified Model (Global Coupled configuration 2, GC2) is presented. This paper documents the model components which make up the configuration (although the scientific description of these components is detailed elsewhere) and provides a description of the coupling between the components. The performance of GC2 in terms of its systematic errors is assessed using a variety of diagnostic techniques. The configuration is intended to be used by the Met Office and collaborating institutes across a range of timescales, with the seasonal forecast system (GloSea5) and climate projection system (HadGEM) being the initial users. In this paper GC2 is compared against the model currently used operationally in those two systems. Overall GC2 is shown to be an improvement on the configurations used currently, particularly in terms of modes of variability (e.g. mid-latitude and tropical cyclone intensities, the Madden–Julian Oscillation and El Niño Southern Oscillation). A number of outstanding errors are identified with the most significant being a considerable warm bias over the Southern Ocean and a dry precipitation bias in the Indian and West African summer monsoons. Research to address these is ongoing.