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In August 2017, a smoke plume from wildfires in British Columbia and the Northwest Territories recirculated and persisted over northern Canada for over two weeks. We compared a full‐factorial set of NASA Goddard Institute for Space Studies ModelE simulations of the plume to satellite retrievals of aerosol optical depth and carbon monoxide, finding that ModelE performance was dependent on the model configuration, and more so on the choice of injection height approach, aerosol scheme and biomass burning emissions estimates than to the choice of horizontal winds for nudging. In particular, ModelE simulations with free‐tropospheric smoke injection, a mass‐based aerosol scheme and comparatively high fire NOx emissions led to unrealistically high aerosol optical depth. Using paired simulations with and without fire emissions, we estimated that for 16 days over an 850,000 km2 region, the smoke decreased planetary boundary layer heights by between 253 and 547 m, decreased downward shortwave radiation by between 52 and 172 Wm−2, and decreased surface temperature by between 1.5°C and 4.9°C, the latter spanning an independent estimate from operational weather forecasts of a 3.7°C cooling. The strongest surface climate effects were for ModelE configurations with more detailed aerosol microphysics that led to a stronger first indirect effect. Plain Language Summary: Smoke from biomass burning is known to have effects on surface weather. We used the NASA GISS ModelE to estimate these effects for a large 2017 smoke plume over northern Canada that persisted for two weeks. We first found that the height of the smoke release at the source was the most important factor influencing agreement between ModelE and satellite retrievals of aerosols and carbon monoxide, and that specific, plausible configurations of the model led to unrealistically high aerosol amounts. By comparing simulations with and without fire, we estimated a 16‐day cooling over a 850,000 km2 region of between 1.5°C and 4.9°C, depending on the model configuration. Key Points: We captured the overall pattern and magnitude of a large 2017 smoke plume over Canada with the NASA GISS ModelEOf the sixteen plausible model configurations tested under a full‐factorial design, two with higher NOx emissions, free‐tropospheric smoke release and mass‐based aerosols led to unrealistically high aerosol optical depthOver an 850,000 km2 region, we estimated a 16‐day surface cooling of between 1.5°C and 4.9°C [ABSTRACT FROM AUTHOR]

The new TROPESS (TRopospheric Ozone and its Precursors from Earth System Sounding) profile retrievals of carbon monoxide (CO) from the Cross-track Infrared Sounder (CrIS) are evaluated against Measurement of Pollution in the Troposphere (MOPITT) CO version 9 data. Comparison results that were adjusted to common a priori constraints in the retrieval processes have improved agreement between the two data sets over direct comparisons. TROPESS-CrIS CO profiles are within 5 % of MOPITT but have higher concentrations in the lower troposphere and lower concentrations in the upper troposphere. For the intense western US wildfire events in September 2020, we compare CO fields simulated by the GISS climate model to the two satellite CO observations. We show intermediate steps of the comparison process to illustrate the evaluation of model simulations by deriving the "retrieved" model CO profiles as they would be observed by the satellite. This includes the application of satellite level-2 data along with their corresponding diagnostic operators provided in the TROPESS-CrIS and MOPITT products. The process allows a diagnosis of potential model improvements in modeling fire emissions and pollution transport. [ABSTRACT FROM AUTHOR]

Using 10 years of satellite‐borne radar and lidar observations coupled with a novel method for automated occlusion identification, composite transects of cloud and precipitation across occluded thermal ridges of extratropical cyclones are, for the first time, constructed. These composites confirm that occluded sectors are characterized by the most extensive cloud cover and heaviest precipitation in any of the frontal regions of the cyclone. Hydrometeor frequency in occluded sectors is sensitive to the cyclone's ascent strength but not to the mean precipitable water in the cyclone's environment. This result is in contrast to the strong relationships between hydrometeor frequency and both precipitable water and ascent strength as previously reported in warm frontal regions. In both hemispheres, cloud and precipitation increase with the maximum value of the equivalent potential temperature at 700 hPa within the occluded thermal ridge, until a threshold is reached. For very large values of maximum equivalent potential temperature, hydrometeors become less frequent while precipitation rates increase. It is suggested that this conjunction is a by‐product of an increase in the frequency of convection in those instances. While in the Northern Hemisphere occluded sectors exhibit deeper and wider cloud structures than their Southern Hemisphere counterparts, their hydrometeor occurrence frequencies are less. The differences in maximum equivalent potential temperature of the thermal ridges in both hemispheres does not appear to explain the more frequent hydrometeors in the Southern Hemisphere. These relationships offer new perspectives on the interplay between cloud processes and cyclone evolution, as well as new observational constraints for process evaluation of Earth system models. [ABSTRACT FROM AUTHOR]

Shifts in Southern Ocean (SO, 40–85°S) shortwave cloud feedback (SWFB) toward more positive values are the dominant contributor to higher effective climate sensitivity (ECS) in Coupled Model Intercomparison Project Phase 6 (CMIP6) models. To provide an observational constraint on the SO SWFB, we use a simplified physical model to connect SO SWFB with the response of column‐integrated liquid water mass (LWP) to warming and the susceptibility of albedo to LWP in 50 CMIP5 and CMIP6 GCMs. In turn, we predict the responses of SO LWP using a cloud‐controlling factor (CCF) model. The combination of the CCF model and radiative susceptibility explains about 50% of the variance in the GCM‐simulated SWFB in the SO. Observations of SW radiation fluxes, LWP, and CCFs from reanalysis are used to constrain the SO SWFB. Observations suggest a SO LWP increase in response to warming and albedo susceptibility to LWP that is on the lower end relative to GCMs. The overall constraint on the contribution of SO to global mean SWFB is −0.168 to +0.051 W m−2 K−1, relative to −0.277 to +0.270 Wm−2 K−1. In summary, observations suggest SO SWFB is less likely to be as extremely positive as predicted by some CMIP6 GCMs, but more likely to range from moderately negative to weakly positive. Plain Language Summary: Previous studies suggest that SO clouds reflect more sunlight in response to global warming and more strongly cool the planet ‐ a negative shortwave cloud feedback (SWFB). The SO SWFB in the latest generation of global climate models (GCMs) participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6) has shifted toward more positive values, leading to the larger predicted temperature responses to greenhouse gas increases in these GCMs. In this study, we examine if this more positive SWFB is consistent with observations. We connect the effect of SO clouds on reflected sunlight with the predicted response of cloud liquid content to global warming. The linkage between cloud liquid water content and large‐scale meteorology is applied to predict this cloud liquid response. Satellite observations of reflected sunlight, cloud liquid, and observations of large‐scale meteorology are applied to constrain the SO SWFB for 50 CMIP5 and CMIP6 GCMs. The results suggest that SO cloud liquid will increase with warming around the average of predictions of 50 GCMs. Satellite records suggest that SO SWFB is moderately negative to weakly positive, instead of extremely positive or negative as suggested by some GCMs. Key Points: Southern Ocean liquid water path increased over the past two decades due to enhanced moisture convergenceEnhanced moisture convergence contributes to a negative cloud feedback in the Southern OceanAcross global climate models, the sensitivity of upwelling shortwave to cloud opposes the sensitivity of cloud to moisture convergence [ABSTRACT FROM AUTHOR]

To improve cloud feedback understanding and simulation, observations have been used to quantify the rate of change of cloud radiative properties as a function of specific environmental metrics (or cloud controlling factors; CCFs). The study focuses on low‐level cloud dominated regions during 2006–2010. For each ocean gridpoint, Spearman's rank correlation coefficients of daily mean observed cloud fraction versus (a) 10‐m wind, (b) sensible heat flux (SHF), (c) sea surface temperature, (d) estimated inversion strength (EIS), (e) 850 hPa vertical velocity, and (f) the M parameter (∆θskin800hPa ${\increment}{\theta }_{\text{skin}}^{800\text{hPa}}$) are sorted to identify the dominant CCFs in both extratropics (30°–60°N/S) and subtropics (30°S–30°N). A novel map for visualizing dominant CCFs for low‐level cloud fraction reveals that: ∆θskin800hPa ${\increment}{\theta }_{\text{skin}}^{800\text{hPa}}$ dominates in the subtropical stratocumulus regions while 10‐m winds dominate in shallow cumulus regions but in the extratropics, a different inversion structure diagnostic (EIS) dominates, while SHF dominates in western boundary current areas. Plain Language Summary: Clouds in the lower levels of the atmosphere cover up to 80% of the oceans in some specific areas within the ±30° latitude band (i.e., the subtropics regions) but also cover a large portion of the mid‐latitude oceans (i.e., the extratropics). In the subtropics, cloud cover has been found to depend principally on sea surface temperature and the stability or thermal structure of the lower levels of the troposphere. Using satellite observations and reanalysis data, we test whether these relationships are found everywhere, and importantly, we find that these dependencies are not uniform across the global oceans. Where cloud cover is large, stability is the strongest driver of cloud cover, but the atmospheric vertical structure of this stability most strongly correlated with the clouds differs between the subtropics and extratropics. Where cloud cover is relatively small, near surface wind speed has the strongest relationship with cloud cover in the subtropics, while at higher latitudes and more specifically in the western boundary current regions, air‐sea energy exchanges (i.e., sensible heat flux) dominate. These regionally varying relationships are depicted with a novel map of dominant cloud controlling factors. This map can help with evaluation and development of climate models. Key Points: A novel map of dominant controlling factors for low‐level oceanic cloud fraction reveals regionally varying patternsSubtropical and extratropical low clouds depend on stability, but the dominant stability metric varies by region, challenging modelsSurface wind speed dominates in cumulus‐dominated regions, sensible heat fluxes dominate in western boundary current regions in winter [ABSTRACT FROM AUTHOR]

The new TROPESS (TRopospheric Ozone and its Precursors from Earth System Sounding) profile retrievals of Carbon Monoxide (CO) from the Cross-track Infrared Sounder (CrIS) are evaluated against Measurement of Pollution in the Troposphere (MOPITT) CO Version 9 data. Comparison results that were adjusted to common a priori constraints in the retrieval processes have improved agreement between the two data sets over direct comparisons. CrIS CO profiles are within 5 % of MOPITT but have higher concentrations in the lower troposphere and lower concentrations in the upper troposphere. For the intense W. US wildfire events in September 2020, we compare GISS climate model simulated CO fields to the two satellite CO observations. We show intermediate steps of the comparison process to illustrate the evaluation of model simulations by deriving the "retrieved" model CO profiles as they would be observed by the satellite. This includes the application of satellite Level 2 data along with their corresponding diagnostic operators provided in the TROPESS and MOPITT products. The process allows a diagnosis of potential model improvements in modelling fire emissions and pollution transport. [ABSTRACT FROM AUTHOR]

Deep convective system maximum areal extent is driven by the stratiform anvil area since convective area fractions are much less than unity when systems reach peak size. It is important to understand the processes that drive system size given the impact large systems have on rainfall and that of anvils on high cloud feedbacks. Using satellite diabatic heating and convective‐stratiform information mapped to convective systems, composite analyses suggest that system maximum sizes occur at the temporal mid‐point of system lifecycles with both maximum size and duration correlating with peak heating above the melting level. However, variations in system growth rates exist, with the overall smooth composites emerging as the average of highly variable system trajectories. Thus, this study focuses on understanding convective system growth rates on short (30‐min) timescales via development of a simple analytical source—sink model that predicts system area changes. Growth occurs when detrained convective mass (inferred from the vertical gradient of diabatic heating and temperature lapse rates) and/or generation of convective area exceeds a sink term whose magnitude is proportional to the current cloud shield size. The model works well for systems over land and ocean, and for systems characterized by varying degrees of convective organization and duration (1.5–35 hr, with correlations often >0.8 across lifetime bins). The model may serve as a useful foundation for improved understanding of processes driving changes in tropics‐wide convective system cloud shields, and further supports conceptual development and evaluation of prognostic climate model stratiform anvil area parameterizations. Plain Language Summary: Thunderstorms are prolific producers of ice higher up in the atmosphere, and those that produce more ice also produce more heating since ice formation releases heat (known as "latent heating"). That heating varies with altitude, and in this study, we develop a simple model that connects the variations in heating with altitude to the rate at which thunderstorms produce lightly to moderately raining areas that many people experience for minutes‐hours after the most intense part of the thunderstorm passes. Key Points: A simple analytical model for cloud area growth and decay rates is developed, with a source term driven by convective cell diabatic heatingThe model works equally well for convective systems of varying duration and degrees of convective organization over both land and oceanThe model suggests that a system convective area fraction of approximately 0.15 is needed for stratiform cloud area maintenance [ABSTRACT FROM AUTHOR]

Shortwave (SW) cloud feedback (SWFB) is the primary driver of uncertainty in the effective climate sensitivity (ECS) predicted by global climate models (GCMs). ECS for several GCMs participating in the sixth assessment report exceed 5K, above the fifth assessment report "likely" maximum (4.5K) due to extratropical SWFB's that are more positive than those simulated in the previous generation of GCMs. Here we show that across 57 GCMs Southern Ocean SWFB can be predicted from the sensitivity of column‐integrated liquid water mass (LWP) to moisture convergence and to surface temperature. The response of LWP to moisture convergence and the response of albedo to LWP anti‐correlate across GCMs. This is because GCMs that simulate a larger response of LWP to moisture convergence tend to have higher mean‐state LWPs, which reduces the impact of additional LWP on albedo. Observational constraints suggest a modestly negative Southern Ocean SWFB— inconsistent with extreme ECS. Plain Language Summary: As the climate warms, moisture convergence into the extratropics strengthens, increasing cloudiness, reflected sunlight, and precipitation. Increased cloudiness in response to moisture convergence is affected by how efficiently clouds condense from water vapor relative to how efficiently precipitation depletes them. Simulations where clouds form efficiently cannot reflect much more sunlight in the extratropics because they are already very cloudy and bright. Observations constrain both the sensitivity of reflected sunlight to cloud and of cloud to moisture. Combining these constraints with constraints on other cloud regimes rules out extremely small and large future warming. Key Points: Enhanced moisture convergence with warming creates a negative extratropical cloud feedbackCloud source and sink efficiency set the extratropical cloud responseConstraint by observations suggests a weakly negative feedback‐ and a moderate effective climate sensitivity [ABSTRACT FROM AUTHOR]

The next‐generation global climate model from the NASA Goddard Institute for Space Studies, GISS‐E3, contains many improvements to resolution and physics that allow for improved representation of tropical cyclones (TCs) in the model. This study examines the properties of TCs in two different versions of E3 at different points in its development cycle, run for 20 years at 0.5° resolution, and compares these TCs with observations, the previous generation GISS model, E2, and other climate models. E3 shares many TC biases common to global climate models, such as having too few tropical cyclones, but is much improved from E2. E3 produces strong enough TCs that observation‐based wind speed thresholds can now be used to detect and track them, and some storms now reach hurricane intensity; neither of these was true of E2. Model development between the first and second versions of E3 further increased the number and intensity of TCs and reduced TC count biases globally and in most regions. One‐year sensitivity tests to changes in various microphysical and dynamical tuning parameters are also examined. Increasing the entrainment rate for the more strongly entraining plume in the convection scheme increases the number of TCs (though also affecting other climate variables, and in some cases increasing biases). Variations in divergence damping did not have a strong effect on simulated TC properties, contrary to expectations based on previous studies. Overall, the improvements in E3 make it more credible for studies of TC activity and its relationship to climate. Plain Language Summary: Tropical cyclones, storms known as hurricanes, typhoons, or cyclones in different parts of the world, are one of the most dangerous natural hazards, and it is an important question whether they will get more powerful or common in our changing climate. Global climate models, used by scientists to study climate change, can simulate tropical cyclones, but in the models these storms tend to be weaker and less numerous than in the real world, and this is especially true for the previous generation climate model developed by NASA, known as GISS‐E2. We analyzed tropical cyclones in the newest version of this model, GISS‐E3, running at its highest resolution, in which the world is divided into grid boxes about 50 km wide. We found that the new version has more and stronger cyclones than the old version. While the storms are still weaker and less numerous than in the real world, GISS‐E3 now simulates storms strong enough that they would be called hurricanes instead of tropical storms, and it is comparable to its peer climate models in its representation of tropical cyclones. Key Points: The new NASA GISS‐E3 global climate model at 0.5° resolution simulates more realistic tropical cyclone activity versus the E2 versionHurricane intensity storms are now simulated, and the average storms are comparable to other 0.5° climate modelsTropical cyclone counts in E3 are very sensitive to convective plume entrainment rates but not to divergence damping coefficients [ABSTRACT FROM AUTHOR]

Partitioning deep convective cloud condensates into components that sediment and detrain, known to be a challenge for global climate models, is important for cloud vertical distribution and anvil cloud formation. In this study, we address this issue by improving the convective microphysics scheme in the National Center for Atmospheric Research Community Atmosphere Model version 5.3 (CAM5.3). The improvements include: (1) considering sedimentation for cloud ice crystals that do not fall in the original scheme, (2) applying a new terminal velocity parameterization that depends on the environmental conditions for convective snow, (3) adding a new hydrometeor category, "rimed ice," to the original four‐class (cloud liquid, cloud ice, rain, and snow) scheme, and (4) allowing convective clouds to detrain snow particles into stratiform clouds. Results from the default and modified CAM5.3 models were evaluated against observations from the U.S. Department of Energy Tropical Warm Pool‐International Cloud Experiment (TWP‐ICE) field campaign. The default model overestimates ice amount, which is largely attributed to the underestimation of convective ice particle sedimentation. By considering cloud ice sedimentation and rimed ice particles and applying a new convective snow terminal velocity parameterization, the vertical distribution of ice amount is much improved in the midtroposphere and upper troposphere when compared to observations. The vertical distribution of ice condensate also agrees well with observational best estimates upon considering snow detrainment. Comparison with observed convective updrafts reveals that current bulk model fails to reproduce the observed updraft magnitude and occurrence frequency, suggesting spectral distributions be required to simulate the subgrid updraft heterogeneity. Key Points: Graupel is added to a convective microphysics scheme for global climate modelsNew convective ice particle terminal velocity schemes are implemented and convective snow is allowed to detrainVertical distribution of ice mass in the midtroposphere and upper troposphere is improved [ABSTRACT FROM AUTHOR]

Simulations of the CMIP6 historical period 1850–2014, characterized by the emergence of anthropogenic climate drivers like greenhouse gases, are presented for different configurations of the NASA Goddard Institute for Space Studies (GISS) Earth System ModelE2.1. The GISS‐E2.1 ensembles are more sensitive to greenhouse gas forcing than their CMIP5 predecessors (GISS‐E2) but warm less during recent decades due to a forcing reduction that is attributed to greater longwave opacity in the GISS‐E2.1 pre‐industrial simulations. This results in an atmosphere less sensitive to increases in opacity from rising greenhouse gas concentrations, demonstrating the importance of the base climatology to forcing and forced climate trends. Most model versions match observed temperature trends since 1979 from the ocean to the stratosphere. The choice of ocean model is important to the transient climate response, as found previously in CMIP5 GISS‐E2: the model that more efficiently exports heat to the deep ocean shows a smaller rise in tropospheric temperature. Model sea level rise over the historical period is traced to excessive drawdown of aquifers to meet irrigation demand with a smaller contribution from thermal expansion. This shows how fully coupled models can provide indirect observational constraints upon forcing, in this case, constraining irrigation rates with observed sea level changes. The overall agreement of GISS‐E2.1 with observed trends is familiar from evaluation of its predecessors, as is the conclusion that these trends are almost entirely anthropogenic in origin. Plain Language Summary: Measurements show clear evidence of warming over the twentieth century and up to the present day. Our anticipation of future change comes from computer models of climate. These are based upon well‐established physical principles like Newton's laws of motion and radiative transfer theory; the models are closely related to those used for weather forecasting. We can never predict the weather on a particular day, 50 years in the future, but we can calculate whether that future decade will be warmer than our present climate. Part of our confidence in such a forecast comes from testing a climate model's ability to reproduce warming and other changes measured over the past century. We use observations of atmospheric composition and the sunlight received by our planet to calculate how the model responds to their changes. The climate model of the NASA Goddard Institute for Space Studies, GISS‐E2.1, closely follows changes measured in the ocean and atmosphere as the concentrations of greenhouse gases and other pollutants rise. This agreement suggests that future warming by greenhouse gases will be reliably predicted by GISS‐E2.1. This suggests that the warming we already experience is due to our consumption of fossil fuels that has led to the increase of carbon dioxide and other greenhouse gases in the atmosphere over the past two centuries. Key Points: Tropospheric warming and ocean heat uptake by 2014 are smaller in GISS‐E2.1 and closer to observed trends than in its CMIP5 predecessorGISS‐E2.1 climate sensitivity is higher than in CMIP5 GISS‐E2, but forcing by greenhouse gases is smallerAtmospheric trends vary among model configurations with the storage of heat beneath the thermocline [ABSTRACT FROM AUTHOR]

Using multiple independent satellite and reanalysis datasets, we compare relationships between mesoscale convective system (MCS) precipitation intensity Pmax, environmental moisture, large-scale vertical velocity, and system radius among tropical continental and oceanic regions. A sharp, nonlinear relationship between column water vapor and Pmax emerges, consistent with nonlinear increases in estimated plume buoyancy. MCS Pmax increases sharply with increasing boundary layer and lower free tropospheric (LFT) moisture, with the highest Pmax values originating from MCSs in environments exhibiting a peak in LFT moisture near 750 hPa. MCS Pmax exhibits strikingly similar behavior as a function of water vapor among tropical land and ocean regions. Yet, while the moisture–Pmax relationship depends strongly on mean tropospheric temperature, it does not depend on sea surface temperature over ocean or surface air temperature over land. Other Pmax-dependent factors include system radius, the number of convective cores, and the large-scale vertical velocity. Larger systems typically contain wider convective cores and higher Pmax, consistent with increased protection from dilution due to dry air entrainment and reduced reevaporation of precipitation. In addition, stronger large-scale ascent generally supports greater precipitation production. Last, temporal lead–lag analysis suggests that anomalous moisture in the lower–middle troposphere favors convective organization over most regions. Overall, these statistics provide a physical basis for understanding environmental factors controlling heavy precipitation events in the tropics, providing metrics for model diagnosis and guiding physical intuition regarding expected changes to precipitation extremes with anthropogenic warming. [ABSTRACT FROM AUTHOR]

This paper describes the GISS‐E2.1 contribution to the Coupled Model Intercomparison Project, Phase 6 (CMIP6). This model version differs from the predecessor model (GISS‐E2) chiefly due to parameterization improvements to the atmospheric and ocean model components, while keeping atmospheric resolution the same. Model skill when compared to modern era climatologies is significantly higher than in previous versions. Additionally, updates in forcings have a material impact on the results. In particular, there have been specific improvements in representations of modes of variability (such as the Madden‐Julian Oscillation and other modes in the Pacific) and significant improvements in the simulation of the climate of the Southern Oceans, including sea ice. The effective climate sensitivity to 2 × CO2 is slightly higher than previously at 2.7–3.1°C (depending on version) and is a result of lower CO2 radiative forcing and stronger positive feedbacks. Plain Language Summary: This paper describes the latest iteration of the National Aeronautics and Space Administration (NASA) Goddard Institute for Space Studies (GISS) climate model, which will be used for understanding historical climate change and to make projections for the future. We compare the model output to a wide range of observations over the recent era (1979–2014) and show that there has been a significant increase in how well the model performs compared to the previous version from 2014, particularly in the Southern Ocean, though some persistent biases remain. The model has a temperature response to the increase of carbon dioxide that is slightly higher than previous versions but is well within the range expected from observational and past climate constraints. Key Points: GISS‐E2.1 is an updated climate model version for use within the CMIP6 projectAtmospheric composition is calculated consistently in all model versionsResults demonstrate a significant improvement in skill in a climate model without changes to atmospheric resolution [ABSTRACT FROM AUTHOR]

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 the cloud macrophysical state. Once variability associated with meteorology has been removed, covariance between the liquid water path (LWP) averaged across cloudy and clear regions (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 (Multisensor Advanced Climatology of Liquid Water Path) and MODIS are compared to simulations in the Met Office 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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Extratropical cyclones provide a unique set of challenges and opportunities in understanding variability in cloudiness over the extratropics (poleward of 30°). We can gain insight into the shortwave cloud feedback from examining cyclone variability. Here we contrast global climate models (GCMs) with horizontal resolutions from 7 km up to hundreds of kilometers with Multi-Sensor Advanced Climatology Liquid Water Path (MAC-LWP) microwave observations of cyclone properties from the period 1992-2015. We find that inter-cyclone variability in both observations and models is strongly driven by moisture flux along the cyclone's warm conveyor belt (WCB). Stronger WCB moisture flux enhances liquid water path (LWP) within cyclones. This relationship is replicated in GCMs, although its strength varies substantially across models. In the southern hemisphere (SH) oceans 28-42% of the observed interannual variability in cyclone LWP may be explained by WCB moisture flux variability. This relationship is used to 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. We show that changes in moisture flux drive can explain the observed trend in Southern Ocean cyclone LWP over the last two decades. Transient warming simulations show that the majority of the change in cyclone LWP can be explained by changes in WCB moisture flux, as opposed to changes in cloud phase. The variability 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 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. [ABSTRACT FROM AUTHOR]

This study provides observational evidence for feedbacks that amplify the short-term hydrological response associated with the warm phase of the El Niño-Southern Oscillation. Our analyses make use of a comprehensive set of independent satellite observations collected over decades to show that much larger local changes to cloud (~50%/K) and precipitation (~60%/K) occur than would be expected from the guidance of Clausius-Clapeyron theory (~7%/K). This amplification comes from atmospheric feedbacks involving shifts in the patterns of latent and radiative heating that mutually act on the dynamics enhancing changes to the hydrological cycle. We also confirm the existence of an opposing negative flux feedback at the ocean surface, driven largely by solar radiation changes, that opposes the surface warming. Estimates of the strength of this and other feedback factors associated with warming in the Niño3 region are provided from observations. These observations are also used to examine comparative processes and feedbacks in model experiments from the Coupled Model Intercomparison Project Phase 5 Atmospheric Model Intercomparison Project. [ABSTRACT FROM AUTHOR]

Model calibration (or "tuning") is a necessary part of developing and testing coupled ocean-atmosphere climate models regardless of their main scientific purpose. There is an increasing recognition that this process needs to become more transparent for both users of climate model output and other developers. Knowing how and why climate models are tuned and which targets are used is essential to avoiding possible misattributions of skillful predictions to data accommodation and vice versa. This paper describes the approach and practice of model tuning for the six major US climate modeling centers. While details differ among groups in terms of scientific missions, tuning targets, and tunable parameters, there is a core commonality of approaches. However, practices differ significantly on some key aspects, in particular, in the use of initialized forecast analyses as a tool, the explicit use of the historical transient record, and the use of the present-day radiative imbalance vs. the implied balance in the preindustrial era as a target. [ABSTRACT FROM AUTHOR]

Despite continuous improvements in microwave sensors and retrieval algorithms, our understanding of precipitation uncertainty is quite limited, due primarily to inconsistent findings in studies that compare satellite estimates toin situobservations over different parts of the world. This study seeks to characterize the temporal and spatial properties of uncertainty in the Tropical Rainfall Measuring Mission Microwave Imager surface rainfall product over tropical ocean basins. Two uncertainty analysis frameworks are introduced to qualitatively evaluate the properties of uncertainty under a hierarchy of spatiotemporal data resolutions. The first framework (i.e. ‘climate method’) demonstrates that, apart from random errors and regionally dependent biases, a large component of the overall precipitation uncertainty is manifested in cyclical patterns that are closely related to large-scale atmospheric modes of variability. By estimating the magnitudes of major uncertainty sources independently, the climate method is able to explain 45–88% of the monthly uncertainty variability. The percentage is largely resolution dependent (with the lowest percentage explained associated with a 1° × 1° spatial/1 month temporal resolution, and highest associated with a 3° × 3° spatial/3 month temporal resolution). The second framework (i.e. ‘weather method’) explains regional mean precipitation uncertainty as a summation of uncertainties associated with individual precipitation systems. By further assuming that self-similar recurring precipitation systems yield qualitatively comparable precipitation uncertainties, the weather method can consistently resolve about 50% of the daily uncertainty variability, with only limited dependence on the regions of interest. [ABSTRACT FROM PUBLISHER]

Column water vapor (CWV) is studied using data from the Dynamics of the Madden-Julian Oscillation (DYNAMO) field experiment. A distinctive moist mode in tropical CWV probability distributions motivates the work. The Lagrangian CWV tendency (LCT) leaves together the compensating tendencies from phase change and vertical advection, quantities that cannot be measured accurately by themselves, to emphasize their small residual, which governs evolution. The slope of LCT versus CWV suggests that the combined effects of phase changes and vertical advection act as a robust positive feedback on CWV variations, while evaporation adds a broadscale positive tendency. Analyzed diabatic heating profiles become deeper and stronger as CWV increases. Stratiform heating is found to accompany Lagrangian drying at high CWV, but its association with deep convection makes the mean LCT positive at high CWV. Lower-tropospheric wind convergence is found in high-CWV air masses, acting to shrink their area in time. When ECMWF heating profile indices and S-Pol and TRMM radar data are binned jointly by CWV and LCT, bottom-heavy heating associated with shallow and congestus convection is found in columns transitioning through Lagrangian moistening into the humid, high-rain-rate mode of the CWV distribution near 50-55 mm, while nonraining columns and columns with widespread stratiform precipitation are preferentially associated with Lagrangian drying. Interpolated sounding-array data produce substantial errors in LCT budgets, because horizontal advection is inaccurate without satellite input to constrain horizontal gradients. [ABSTRACT FROM AUTHOR]

Utilizing data from the Quick Scatterometer (QuikSCAT), a new observational parameter related to mesoscale cold pool activity [termed cold pool kinetic energy (CPKE)] is developed and investigated. CPKE and the Climate Prediction Center (CPC) morphing technique (CMORPH) rainfall product (both scaled to 2.25°) are geolocated to 25 tropical island radiosonde sites. CPKE and radiosonde-derived nondilute CAPE, entraining CAPE (ECAPE), saturation fraction, and a new measure of convective inhibition (that takes into account stable layers above the LFC) are investigated with respect to rainfall time tendencies. Over the life cycle of rainfall, the composite temporal evolutions of CPKE and convective inhibition are quantitatively similar, but slightly out of phase. The maximum in CPKE precedes the maximum in convective inhibition by 3-6 h, thus allowing for an oscillation in the ratio of convective inhibition to CPKE relative to maximum rainfall. This ratio falls below unity at the time rainfall begins increasing and averages to near unity over the entire life cycle. These results imply a lagged, coupled relationship between CPKE and convective inhibition during rainfall. The rapid increase in rainfall occurs when saturation fraction and ECAPE exceed approximately 70% and 280 J kg-1, respectively, consistent with previously noted thresholds for deep convection transition. However, since similar thermodynamic conditions are found before the increase in rainfall, observations support a hypothesis that the onset time for transition from light to heavy rainfall occurs when triggering energy (as captured in CPKE) approaches and exceeds convective inhibition. The observed onset and time scale for CAPE depletion by convection is nearly equivalent to the initial temporal appearance and time duration (6-12 h) that CPKE exceeds convective inhibition. [ABSTRACT FROM AUTHOR]

The Multi-Sensor Advanced Climatology of Liquid Water Path (MAC-LWP), an updated and enhanced version of the University of Wisconsin (UWisc) cloud liquid water path (CLWP) climatology, currently provides 29 years (1988 - 2016) of monthly gridded (1°) oceanic CLWP information constructed using Remote Sensing Systems (RSS) inter-calibrated 0.25°-resolution retrievals. Satellite sources include SSM/I, TMI, AMSR-E, WindSat, SSMIS, AMSR-2 and GMI. To mitigate spurious CLWP trends, the climatology is corrected for drifting satellite overpass times by simultaneously solving for the monthly average CLWP and monthly-mean diurnal cycle. In addition to a longer record and six additional satellite products, major enhancements relative to the UWisc climatology include updating the input to version 7 RSS retrievals, a correction for a CLWP bias (based on matchups to clear-sky MODIS scenes), and the construction of a total (cloud+rain) liquid water path (TLWP) record for use in analyses of columnar liquid water in raining clouds. Because the microwave emission signal from cloud water is similar to that of precipitation-sized hydrometeors, greater uncertainty in the CLWP record is expected in regions of substantial precipitation. Therefore, the TLWP field can also be used as a quality-control screen, where uncertainty increases as the ratio of CLWP to TLWP decreases. For regions where confidence in CLWP is highest (i.e. CLWP:TLWP > 0.8), systematic differences in MAC CLWP relative to UWisc CLWP range from -15% (e.g. global oceanic stratocumulus decks) to +5-10% (e.g. portions of the higher-latitudes, storm tracks, and shallower convection regions straddling the ITCZ). The dataset is currently hosted at the Goddard Earth Science Data and Information Services Center (http://disc.sci.gsfc.nasa.gov).