The adjustment of cloud amount to aerosol effects occurs to a large extent in response to the aerosol effect on precipitation. Here the marine boundary layer clouds were studied by analyzing the dependence of rain intensity measured by Global Precipitation Measurement on cloud properties. We showed that detectable rain initiates when the drop effective radius at the cloud top (r e ) exceeds 14 μm, and precipitation is strongly suppressed with increasing cloud drop concentration (N d ), which contributes to the strong dependence of cloud amount on aerosols. The rain rate increases sharply with cloud thickness (CGT) and r e when r e > 14 μm. The dependence of rain rate on r e and CGT presents a simple framework for precipitation susceptibility to aerosols, which explains other previously observed relationships. We showed that sorting data by CGT and using alternative cloud condensation nuclei proxy rather than aerosol optical depth are critical for studying aerosol-cloud-precipitation interactions.Plain Language Summary Aerosol-cloud interaction remains the greatest uncertainty in future climate projection. Precipitation is a key process that mediates how the cloud amount responds to aerosol perturbations. Here we combined precipitation measured by the radar onboard the satellite of Global Precipitation Measurement (GPM) and cloud properties retrieved from Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Aqua satellite for studying the dependence of rain intensity on cloud properties for marine boundary layer water clouds over the Southern Hemisphere Ocean. Our results showed that rain is sharply intensified when droplets at the cloud top grow larger than 14 μm, and precipitation decreases with increasing cloud drop number concentration (N d ). A simple framework to explain the relationship between precipitation and aerosols is proposed here by showing the dependence of precipitation on N d and cloud geometric thickness. We also discussed why using aerosol optical depth (AOD) as CCN proxy in previous studies could lead to great uncertainties and why sorting cloud geometrical thickness is necessary. Key Points:• Precipitation is strongly suppressed with increasing cloud drop concentration • Sorting data by cloud thickness and using alternative CCN proxy rather than AOD are critical for studying aerosol-cloud interactions • Detectable rain initiates when the drop effective radius at the cloud top exceeds 14 μm Supporting Information:• Supporting Information S1

Increased deployment of solar farms in the last decade is coincident with continued monitoring of surface spectral reflectances by the moderate resolution imaging spectroradiometers (MODIS) aboard NASA Aqua satellite. By analyzing the surface spectral reflectances retrieved at seven MODIS shortwave bands, this study quantifies the changes of surface spectral reflectances caused by solar farms commissioned in the southwestern US. Our case study using one solar farm indicates a 20%–25% reduction of surface reflectance over the seven MODIS bands due to the solar panel installation. Radiative transfer calculation shows that such a reduction in surface spectral reflectance leads to a ∼23% decrease in the upward shortwave broadband flux at the surface and a ∼14%–18% decrease in the clear-sky reflected shortwave flux at the top of atmosphere (TOA). Though the MODIS surface reflectance retrievals can be affected by other factors such as aerosol or thin-cirrus contaminations, five out of six solar farm sites analyzed here show unambiguously detectable changes of surface reflectances due to solar panel installations. The brighter the surface is at a given MODIS band before the solar-farm construction, the larger the spectral reflectance reduction tends to be. If all the bright deserts, which occupies about 4% of the global surface, were covered with the solar panels similar to what has been studied here, the estimated instantaneous TOA shortwave radiative forcing would be no more than 1.1 W m−2.

Atmospheric Infrared Sounder (AIRS) aboard the National Aeronautics and Space Administration (NASA) Aqua satellite has been operating since September 2002. Its information content, superb instrument performance, and dense sampling pattern make the AIRS radiances an invaluable data set for climate studies. The trends of global‐mean, nadir‐view, clear‐sky AIRS radiances from 2003 to 2020 are studied here, together with the counterparts of synthetic radiances based on two reanalyzes, European Centre for Medium‐Range Weather Forecasts Reanalysis V5 (ECMWF ERA5) and NASA Goddard Earth Observing System V5.4.1 (GEOS‐5.4.1; a reanalysis product without assimilation of hyperspectral radiances such as AIRS). The AIRS observation shows statistically significant negative trends in most of its CO2 channels, positive but non‐significant trends in the channels over the window regions, and statistically significant positive trends in some of its H2O channels. The best agreements between observed and simulated radiance trends are seen over the CO2 tropospheric channels, while the observed and simulated trends over the CO2 stratospheric channels are opposite. ERA5 results largely agree with the AIRS observation over the H2O channels. The comparison in the H2O channels helps reveal a data continuity issue in the GEOS‐5.4.1. Contributions from individual variables to the radiance trends are also assessed by performing separate simulations. This study provides the first synopsis of the global‐mean trend of AIRS radiances over all its thermal‐IR channels.

<p>Climate models often ignore cloud scattering and surface emissivity in the longwave (LW) for computational efficiency. Such approximations can cause biases in radiative fluxes and affect simulated climate, especially in the Arctic because of its large sensitivity to perturbations. We implemented treatments to both physics into the Energy Exascale Earth System Model (E3SM) version 2 by DoE and assessed their impacts on the simulated mean-state global climate as well as climate feedback and sensitivity.</p> <p>By turning on and off the switches in the modified E3SMv2 model, we studied the changes in mean-state climate due to cloud LW scattering and surface emissivity effects by comparing four 35-year fully-coupled simulations. Cloud LW scattering warms the entire global troposphere by ~0.4 K on average; the warming is stronger in the Arctic (~0.8 K) than in the tropics, which is a manifestation of the polar amplification phenomenon. When realistic emissivity is incorporated into the model, the surface skin temperature increases by 0.36 K instantaneously on a global average, especially in the Sahara Desert (~0.7 K) where the surface emissivity is low. Surface skin temperature, as well as surface air temperature and tropospheric temperature, further increases by 0.19 K due to the inclusion of surface spectral emissivity. The mean-state climate changes due to both effects are linearly additive. The latitudinal and seasonal pattern of surface air temperature warming resulting from both effects is very similar to the response due to CO<sub>2</sub> increase in the standard E3SMv2 model.</p> <p>We also carried out four 35-year simulations under the abrupt 4xCO<sub>2</sub> scenario, with cloud LW scattering and/or surface emissivity effects on and off. Based on standard radiative kernel analysis, we found that total global-mean climate feedback does not change significantly after including either or both physics. Nevertheless, lapse rate feedback, water vapor feedback, and cloud feedbacks in the tropics have changes by up to 10%. They are primarily associated with high cloud fraction response in the upper troposphere. Our study suggests that both the cloud LW scattering effect and the surface spectral emissivity effect should be included in climate models for a faithful representation of the radiative process in the atmosphere, especially at regional scales.</p> <p><img src="" alt="" /></p>