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Abstract: Aerosol‐cloud interactions (ACI) in warm clouds are the primary source of uncertainty in effective radiative forcing (ERF) during the historical period and, by extension, inferred climate sensitivity. The ERF due to ACI (ERFaci) is composed of the radiative forcing due to changes in cloud microphysics and cloud adjustments to microphysics. Here, we examine the processes that drive ERFaci using a perturbed parameter ensemble (PPE) hosted in CAM6. Observational constraints on the PPE result in substantial constraints in the response of cloud microphysics and macrophysics to anthropogenic aerosol, but only minimal constraint on ERFaci. Examination of cloud and radiation processes in the PPE reveal buffering of ERFaci by the interaction of precipitation efficiency and radiative susceptibility.

A large spread in model estimates of the equilibrium climate sensitivity (ECS), defined as the global mean near-surface air-temperature increase following a doubling of atmospheric CO2 concentration, leaves us greatly disadvantaged in guiding policy-making for climate change adaptation and mitigation. In this study, we show that the projected ECS in the latest generation of climate models is highly related to seasonal variations of extratropical low-cloud fraction (LCF) in historical simulations. Marked reduction of extratropical LCF from winter to summer is found in models with ECS > 4.75 K, in accordance with the significant reduction of extratropical LCF under a warming climate in these models. In contrast, a pronounced seasonal cycle of extratropical LCF, as supported by satellite observations, is largely absent in models with ECS

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]

We utilize ocean 10‐m wind speed (U10m) from the microwave Multi‐sensor Advanced Climatology data set to examine the coupling between convective cloud and precipitation processes, synoptic state, and U10m and to evaluate the representation of U10m in global climate models (GCMs). We find that midlatitude U10m is underestimated by GCMs relative to observations. We examine two potential mechanisms to explain this model behavior: cold pool formation in cold air outbreaks (CAOs) associated with downdrafts that enhance U10m and sea surface temperature (SST) gradients affecting U10m through thermally forced surface winds at regional scales. When the effects of the CAO index (M) and SST gradients on U10m are accounted for, a relationship between GCM horizontal resolution and U10m appears. The strongest correlation between resolution and U10m is over the western boundary currents characterized by frequent CAOs atop strong SST gradients which drives the strongest surface fluxes on Earth. Plain Language Summary: Surface wind drives the exchange of momentum and energy between the atmosphere and ocean, forcing movement of ocean surface water that impacts the circulation responsible for transporting heat and carbon. It is thus important to study how well global climate models (GCMs) simulate near surface winds. Here, we show an underestimation of ocean surface wind in the latest‐generation of GCMs and examine how an underestimation of ocean surface winds covaries with biases in surface temperature and fine‐scale precipitation‐driven circulations. We show the effect of model horizontal grid resolution on the wind speed bias and analyze surface wind speed bias occurrence in western boundary currents. Key Points: Coupled model intercomparison project (CMIP6) models underestimate midlatitude ocean surface wind speed compared to spaceborne microwave radiometersSimulated ocean surface wind speed bias scales with model resolution at a magnitude strongly influenced by meteorologyOcean surface wind speed bias is most correlated with resolution in western boundary currents [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]

This paper documents the methodology and preliminary results from a Perturbed Parameter Ensemble (PPE) technique, where multiple parameters are varied simultaneously and the parameter values are determined with Latin hypercube sampling. This is done with the Community Atmosphere Model version 6 (CAM6), the atmospheric component of the Community Earth System Model version 2 (CESM2). We apply the PPE method to CESM2-CAM6 to understand climate sensitivity to atmospheric physics parameters. The initial simulations vary 45 parameters in the microphysics, convection, turbulence and aerosol schemes with 263 ensemble members. These atmospheric parameters are typically the most uncertain in many climate models. Control simulations are analyzed and targeted simulations to understand climate forcing due to aerosols and fast climate feedbacks. The use of various emulators is explored in the multi- dimensional space mapping input parameters to output metrics. Parameter impacts on various model outputs, such as radiation, cloud and aerosol properties are evaluated. Machine learning is also used to probe optimal parameter values against observations. Our findings show that using PPE is a valuable tool for climate uncertainty analysis. Furthermore, by varying many parameters simultaneously, we find that many different combinations of parameter values can produce results consistent with observations, and thus careful analysis of tuning is important. The CESM2-CAM6 PPE is publicly available, and extensible to other configurations to address questions of other model processes in the atmosphere and other model components (e.g. coupling to the land surface). [ABSTRACT FROM AUTHOR]

Marine cold-air outbreaks (CAOs) occur in the postfrontal sector of midlatitude storms, usually accompanied by dry intrusions (DIs) shaping the free-tropospheric (FT) air aloft. Substantial rain initiates overcast to broken regime transitions in marine boundary layer (MBL) cloud decks that form where cold air first meets relatively high sea surface temperatures. An exemplary CAO in the northwest Atlantic shows earlier transitions (corresponding to reduced extents of overcast clouds) closer to the low pressure center. We hypothesize that gradients in the meteorological pattern imposed by the prevailing DI induced a variability in substantial rain onset and thereby transition. We compile satellite observations, reanalysis fields, and Lagrangian large-eddy simulations (LES) translating along MBL trajectories to show that postfrontal trajectories closer to the low pressure center are more favorable to rain formation (and thereby cloud transitions) because of 1) weaker FT subsidence rates, 2) greater FT humidity, 3) stronger MBL winds, and 4) a colder MBL with reduced lower-tropospheric stability. LES confirms the observed variability in transitions, with substantial rain appearing earlier where there is swifter reduction of cloud condensation nucleus (CCN) concentration and increase of liquid water path (LWP). Prior to substantial rain, CCN budgets indicate dominant loss terms from FT entrainment and hydrometeor collisions. LWP-enhancing cloud thickness increases more rapidly for weaker large-scale subsidence that enables faster MBL deepening. Mere MBL warming and moistening cannot explain cloud thickness increases. The generality of such a DI-imposed cloud transition pattern merits further investigation with more cases that may additionally be convoluted by onshore aerosol gradients. Significance Statement: Cold-air outbreaks (CAOs) lead to marine boundary layer (MBL) clouds that commonly undergo rain-initiated overcast to broken cloud regime transitions that can drastically impact reflected solar radiation. We aim to better understand what mechanisms control these transitions. For a CAO event in the northwest Atlantic that shows earlier transitions closer to the low pressure center, we find the transition timing to be largely governed by the coinciding dry intrusion that imposes an inhomogeneous large-scale meteorological pattern onto the overlying free troposphere and thereby affects MBL rain formation. Our findings update conceptual understanding of extratropical cyclones and motivate analyzing observations and conducting simulations for more postfrontal cases through a Lagrangian perspective as done here for one case, to assess the generality of our findings. [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]

In light of the upcoming launch of the Global Precipitation Measurement (GPM) mission, a parametric retrieval algorithm of the nonraining parameters over the global oceans is developed with the ability to accommodate all currently existing and planned spaceborne microwave window channel sensors and imagers. The physical retrieval is developed using all available sensor channels in a full optimal estimation inversion. This framework requires that retrieved parameters be physically consistent with all observed satellite radiances regardless of the sensor being used. The retrieval algorithm has been successfully applied to the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E), the Special Sensor Microwave Imager (SSM/I), and the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) with geophysical parameter retrieval results comparable to independent studies using sensor-optimized algorithms. The optimal estimation diagnostics characterize the retrieval further, providing errors associated with each of the retrieved parameters, indicating whether the retrieved state is physically consistent with observed radiances, and yielding information on how well simulated radiances agree with observed radiances. This allows for the quantitative assessment of potential calibration issues in either the model or sensor. In addition, there is an expected, consistent response of these diagnostics based on the scene being observed, such as in the case of a raining scene, allowing for the emergence of a rainfall detection scheme providing a new capability in rainfall identification for use in passive microwave rainfall and cloud property retrievals.