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The achievement of net-zero greenhouse gas (GHG) emissions by 2100 is required to limit global temperature rise below 2 °C above preindustrial levels. Earlier accomplishments of net-zero GHG emissions in developed regions support this global target. Here, we develop a road map for California to achieve net-zero GHG emissions sustainably in 2050 by using detailed modelling of energy system transformation, cross-sectoral connectivity and technology penetration, as well as quantify the associated health co-benefits from reduced co-emitted air pollutants. We find that approximately 14,000 premature deaths can be avoided in California in 2050 and that these health co-benefits are disproportionately higher in disadvantaged communities (that is, 35% of avoided deaths will come from 25% of the state’s population). The annualized monetary benefits (US$215 billion) exceed the GHG abatement cost (US$106 billion) by US$109 billion. This road map requires the use of bioenergy with carbon capture and sequestration technology to offset some GHG emissions. However, this technology comes at a price as it would emit a considerable amount of air pollutants and reduce health co-benefits by US$4 billion. Nevertheless, our analysis shows that ambitious GHG reduction efforts can provide substantial health co-benefits, especially for residents of disadvantaged communities. Transforming the energy system to achieve net-zero carbon emissions by 2100 is vital to fight climate change. This target can be achieved in California, USA, by 2050—alongside air quality benefits especially in disadvantaged communities—by using bioenergy with carbon capture and sequestration.

We extend a stochastic aerosol‐snow albedo model to explicitly simulate dust internally/externally mixed with snow grains of different shapes and for the first time quantify the combined effects of dust‐snow internal mixing and snow nonsphericity on snow optical properties and albedo. Dust‐snow internal/external mixing significantly enhances snow single‐scattering coalbedo and absorption at wavelengths of

The impact of solar activity on climate system is spatiotemporally selective and usually more significant on the regional scale. Using statistical methods and solar radio flux (SRF) data, this paper investigates the impact of the solar 11-yr cycle on regional climate of Northeast Asia in recent decades. Significant differences in winter temperature, precipitation, and the atmospheric circulation over Northeast Asia are found between peak and valley solar activity years. In peak years, temperature is higher over vast areas of the Eurasian continent in middle and high latitudes, and prone to producing anomalous high pressure there. Northeast Asia is located to the south of the anomalous high pressure, where the easterlies prevail and transport moisture from the western Pacific Ocean to the inland of East Asia and intensify precipitation there. In valley years, temperature is lower over the Eurasian continent and northern Pacific Ocean in middle and high latitudes, and there maintain anomalous low pressure systems in the two regions. Over the Northeast Asian continent, north winds prevail, which transport cold and dry air mass from the high latitude to Northeast Asia and reduce precipitation there. The correlation coefficient of winter precipitation in Northeast China and SRF reaches 0.4, and is statistically significant at the 99% confidence level based on the Student’s t-test. The latent heat flux anomalies over the Pacific Ocean caused by solar cycle could explain the spatial pattern of abnormal winter precipitation of China, suggesting that the solar activity may change the climate of Northeast Asia through air–sea interaction.

The long-term effects of complex terrain on solar energy distributions and surface hydrology over the Tibetan Plateau (TP) are investigated using the 4th version of the global Community Climate System Model (CCSM4) coupled with a 3-D radiative transfer (RT) parameterization. We examine the differences between the results from CCSM4 with the 3-D RT parameterization and the results from CCSM4 with the plane-parallel RT scheme. In January (winter), the net surface solar flux (FSNS) displays negative deviations over valleys and the north slopes of mountains, especially in the northern margin of the TP, as a result of the 3-D shadow effect. Positive deviations in FSNS in January are found over the south slopes of mountains and over mountain tops, where more solar flux is intercepted. The deviations in total cloud fraction and snow water equivalent (SWE) exhibit patterns opposite to that of FSNS. The SWE decreases due to the 3-D mountain effect in spring and the magnitude of this effect depends on the terrain elevations. The SWE is reduced by 1–17 mm over the TP in April, with the largest decrease in SWE at an elevation of 3.5–4.5 km. Negative deviations in precipitation are found throughout the year, except in May and December, and they follow the seasonal variations in the deviations in total cloud fraction. The total liquid runoff at 3.5–4.5 km elevation increases in April due to earlier (March) snowmelt caused by increased downward solar radiation. The possible deviations in surface energy and SWE over the TP, caused by plane-parallel assumption in most climate models may result in biases in the liquid runoff and the river water resources over the TP and downstream.

We investigate the air quality impact of record‐breaking wildfires in Southern California during 5–18 December 2017 using the Weather Research and Forecasting model with Chemistry in combination with satellite and surface observations. This wildfire event was driven by dry and strong offshore Santa Ana winds, which played a critical role in fire formation and air pollutant transport. By utilizing fire emissions derived from the high‐resolution (375 × 375 m²) Visible Infrared Imaging Radiometer Suite active fire detections, the simulated magnitude and temporal evolution of fine particulate matter (PM_(2.5)) concentrations agree reasonably well with surface observations (normalized mean bias = 4.0%). Meanwhile, the model could generally capture the spatial pattern of aerosol optical depth from satellite observations. Sensitivity tests reveal that using a high spatial resolution for fire emissions and a reasonable treatment of plume rise (a fair split between emissions injected at surface and those lifted to upper levels) is important for achieving decent PM_(2.5) simulation results. Biases in PM_(2.5) simulation are relatively large (about 50%) during the period with the strongest Santa Ana wind, due to a possible underestimation of burning area and uncertainty in wind field variation. The 2017 December fire event increases the 14‐day averaged PM_(2.5) concentrations by up to 231.2 μg/m³ over the downwind regions, which substantially exceeds the U.S. air quality standards, potentially leading to adverse health impacts. The human exposure to fire‐induced PM_(2.5) accounts for 14–42% of the annual total PM_(2.5) exposure in areas impacted by the fire plumes.

We summarize the size parameter range of the applicability of four lightscattering computational methods for nonspheric dielectric particles. These methods include two exact methods - the extended boundary condition method (EBCM) and the invariant imbedding T-matrix method (II-TM) and two approximate approaches - the physical-geometric optics method (PGOM) and the improved geometric optics method (IGOM). For spheroids, the single-scattering properties computed by EBCM and II-TM agree for size parameters up to 150, and the comparison gives us confidence in using IITM as a benchmark for size parameters up to 150 for other geometries (e.g., hexagonal columns) because the applicability of II-TM with respect to particle shape is generic, as demonstrated in our previous studies involving a complex aggregate. This study demonstrates the convergence of the exact II-TM and approximate PGOM solutions for the complete set of single-scattering properties of a nonspherical shape other than spheroids and circular cylinders with particle sizes of ~48λ, specifically a hexagonal column with a size parameter of length as kL=300, where k=2π/λ and L is the column length. IGOM is also quite accurate except near the exact 180o backscattering direction. This study demonstrates that a synergetic combination of the numerically-exact II-TM and the approximate PGOM can seamlessly cover the entire size parameter range of practical interest. To demonstrate the applicability of the approach, we compute the optical properties of dust particles with a downstream application to the retrieval of dust aerosol optical thickness and effective particle size from polarimetric observations.

Topography exerts significant influences on the incoming solar radiation at the land surface. A few stand-alone regional and global atmospheric models have included parameterizations for sub-grid topographic effects on solar radiation. However, nearly all Earth system models (ESMs) that participated in the Coupled Model Intercomparison Project (CMIP6) use a plane-parallel (PP) radiative transfer scheme that assumes that the terrain is flat. In this study, we incorporated a well-validated sub-grid topographic (TOP) parameterization in the Energy Exascale Earth System Model (E3SM) Land Model (ELM) version 1.0 to quantify the effects of sub-grid topography on solar radiation flux, including the shadow effects and multi-scattering between adjacent terrain. We studied the role of sub-grid topography by performing ELM simulations with the PP and TOP schemes over the Tibetan Plateau (TP). Additional ELM simulations were performed at multiple spatial resolutions to investigate the role of spatial scale on sub-grid topographic effects on solar radiation. The Moderate Resolution Imaging Spectroradiometer (MODIS) data was used to compare with the ELM simulations. The results show that topography has non-negligible effects on surface energy budget, snow cover, snow depth, and surface temperature over the TP. The absolute differences in surface energy fluxes for net solar radiation, latent heat flux, and sensible heat flux between TOP and PP exceed 20, 10, and 5 W m−2, respectively. The differences in land surface albedo, snow cover fraction, snow depth, and surface temperature between TOP and PP exceed 0.1, 0.1, 10 cm, and 1 K, respectively. The magnitude of the sub-grid topographic effects is dependent on seasons and elevations and is also sensitive to the spatial scales. Although the sub-grid topographic effects on solar radiation are larger with more spatial details at finer spatial scales, they cannot be simply neglected at coarse spatial scales. When compared to MODIS data, incorporating the sub-grid topographic effects overall reduces the biases of ELM in simulating surface energy balance, snow cover, and surface temperature, especially in the high-elevation and snow-covered regions over the TP. The inclusion of sub-grid topographic effects on solar radiation parameterization in ELM will contribute to advancing our understanding of the role of the surface topography on terrestrial processes over complex terrain.

Surface brightening has been observed in China since 2005. However, it remains unclear whether the brightening has accelerated recently in response to the strictest ever air pollution control policies since 2013. By combining intensive surface and satellite observations, we find an unprecedented rapid increasing trend in surface solar radiation (SSR) of 0.70‐1.16 Wm‐2yr‐1 over the eastern and central China for 2014‐2019. Using a novel method to identify the relative contributions of aerosol and cloud radiative effects to the SSR trends, we find that the strongly declining aerosol radiative effect due to the strict air pollution controls is the main cause of the upward SSR trends; cloud variations should not be the main reason. Distinction exists in seasonal trends of SSR, with decreasing trends in winter and increasing trends in other seasons. Air pollution controls play an important role in regulating SSR, which has valuable implications for photovoltaic power generation.This article is protected by copyright. All rights reserved.

In response to the Coronavirus Disease 2019 (COVID-19), California issued statewide stay-at-home orders, bringing about abrupt and dramatic reductions in air pollutant emissions. This crisis offers us an unprecedented opportunity to evaluate the effectiveness of emission reductions on air quality. Here we use the Weather Research and Forecasting model with Chemistry (WRF-Chem) in combination with surface observations to study the impact of the COVID-19 lockdown measures on air quality in southern California. Based on activity level statistics and satellite observations, we estimate the sectoral emission changes during the lockdown. Due to the reduced emissions, the population-weighted concentrations of fine particulate matter (PM2.5) decrease by 15 % in southern California. The emission reductions contribute 68 % of the PM2.5 concentration decrease before and after the lockdown, while meteorology variations contribute the remaining 32 %. Among all chemical compositions, the PM2.5 concentration decrease due to emission reductions is dominated by nitrate and primary components. For O3 concentrations, the emission reductions cause a decrease in rural areas but an increase in urban areas; the increase can be offset by a 70 % emission reduction in anthropogenic volatile organic compounds (VOC). These findings suggest that a strengthened control on primary PM2.5 emissions and a well-balanced control on nitrogen oxides and VOC emissions are needed to effectively and sustainably alleviate PM2.5 and O3 pollution in southern California.

This study examines the modifications of air‐sea coupling processes by dust‐radiation‐cloud interactions over the North Atlantic Ocean using a high‐resolution coupled atmosphere‐wave‐ocean‐dust (AWOD) regional model. The dust‐induced mechanisms that are responsible for changes of sea surface temperature (SST) and latent and sensible heat fluxes (LHF/SHF) are also examined. Two 3‐month numerical experiments are conducted, and they differ only in the activation and deactivation of dust‐radiation‐cloud interactions. Model results show that the dust significantly reduces surface downward radiation fluxes (SDRF) over the ocean with the maximum change of 20–30 W m−2. Over the dust plume region, the dust effect creates a low‐pressure anomaly and a cyclonic circulation anomaly, which drives a positive wind stress curl anomaly, thereby reducing sea surface height and mixed layer depth. However, the SST change by dust, ranging from −0.5 to 0.5 K, has a great spatial variation which differs from the dust plume shape. Dust cools SST around the West African coast, except under the maximum dust plume ridge, and extends westward asymmetrically along the northern and southern edges of the dust plume. Dust unexpectedly warms SST over a large area of the western tropical North Atlantic and north of the dust plume. These SST changes are controlled by different mechanisms. Unlike the SST change pattern, the LHF and SHF changes are mostly reduced underneath the dust plume region, though they are different in detail due to different dominant factors, and increased south of the dust plume over the tropic., Key Points Dust‐radiation‐cloud interactions mainly cool SST offshore the North Africa and warm SST over the southwestern dust plume regionDust reduces upward LHF and SHF underneath the dust plume region and increases the values south of the dust plumeChanges of SST/LHF/SHF by dust are not only attributed to the dust‐induced SDRF reduction but also changes of WSC and upper‐ocean dynamic

Tropical anvil clouds have a profound impact on Earth's weather and climate. Their role in Earth's energy balance and hydrologic cycle is heavily modulated by the vertical structure of the microphysical properties for various hydrometeors in these clouds and their dependence on the ambient environmental conditions. Accurate representations of the variability and covariability of such vertical structures are key to both the satellite remote sensing of cloud and precipitation and numerical modeling of weather and climate, which remain a challenge. This study presents a new method to combine vertically resolved observations from CloudSat radar reflectivity and Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation cloud masks with probability distributions of cloud microphysical properties and the ambient atmospheric conditions from detailed in situ measurements on tropical anvils sampled during the National Aeronautics and Space Administration TC4 (Tropical Composition, Cloud and Climate Coupling) mission. We focus on the microphysical properties of the vertical distribution of ice water content, particle size distributions, and effective sizes for different hydrometeors, including ice particles and supercooled liquid droplets. Results from this method are compared with those from in situ data alone and various CloudSat/Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation cloud retrievals. The sampling limitation of the field experiment and algorithm limitations in the current retrievals is highlighted, especially for the liquid cloud particles, while a generally good agreement with ice cloud microphysical properties is seen from different methods. While the method presented in this study is applied to tropical anvil clouds observed during TC4, it can be readily employed to study a broad range of ice clouds sampled by various field campaigns., Key Points The vertical structure of ice cloud microphysics is studied by combining field campaign in situ measurements with satellite observationsA generally good agreement with ice cloud microphysical properties below 12 km is seen from in situ observations and satellite retrievalsResults indicate the sampling limitation of the field experiment and algorithm limitations in the satellite retrievals

This study presents a comprehensive evaluation of eight aerosol optical depth (AOD) products from the latest MODIS C6.1 DT, DB and DTB, MISR V23, and VIIRS V1 DB dataset against the Aerosol Robotic Network (AERONET) measurements on global scale during 2012 to 2019. The latest MODIS DB products are found to be superior over DT in most cases. MODIS DTB products generally have a better performance than either DT or DB. VIIRS shows the best overall performance on global and regional scale while MISR has a systematic underestimation in moderate and high AOD conditions. Median AOD bias shows distinct regional dependence with the biggest divergence between satellite AOD products appearing in Asia. All these AOD products tend to have better performance in high latitude region and poorer performance in the tropics likely due to the complex aerosol condition and common high cloud cover in the tropics. Time series stability evaluation shows a distinct temporal pattern of statistics, in which the observation number and median AOD bias tend to be high in summer while low in winter and correlation R has a reversing trend. Among these products, VIIRS V1 DB has the highest time series stability of bias. Influence of aerosol loading, particle size, land use, elevation, and precipitable water and temperature on AOD retrievals is broadly consistent between products. High aerosol loading, small particle size, bright surface, high altitude, and high precipitable water and temperature tend to decrease the retrieval accuracy, e.g. lower expected error (EE) within ratio and larger median bias. The latest AOD products need to be furthermore improved under extreme conditions like very fine aerosols, elevated terrain and high precipitable water and temperature.

The relatively short lifetimes of aerosols in the atmosphere result in climatic and health effects that are strongly dependent on intra-annual variations in particle concentrations. While many studies have examined the seasonal and diurnal variations of regional aerosol optical depth (AOD), understanding the temporal variations in aerosol vertical distribution and particle types is also important for accurate computation of aerosol radiative effects. In this paper, we combine the observations from four satellite-borne sensors and ground-based AOD and fine particle (PM2.5) measurements to investigate the seasonal and diurnal variations of aerosol column loading, vertical distribution, and particle types over three populous regions: the Eastern United States (EUS), Western Europe (WEU), and Eastern and Central China (ECC). In all three regions, column AOD, as well as AOD higher than 800 m above ground level, peaks in summer/spring probably due to accelerated formation of secondary aerosols and hygroscopic growth. However, AOD at height below 800 m mostly peaks in winter except that a second maximum in summer occurs over the EUS region, which is consistent with observed temporal trends in surface PM2.5 concentrations. AOD due to fine particles ( 1.4 μm diameter) generally shows less variability, except for the ECC region where a peak occurs in spring, consistent with the prevalence of airborne dust during this season. When aerosols are classified according to sources, the dominant type is associated with anthropogenic air pollution, which has a similar seasonal pattern as total AOD. Dust and sea-spray aerosols in the WEU region peak in summer and winter, respectively, but do not show an obvious seasonal pattern in the EUS region. Smoke aerosols, as well as absorbing aerosols, present an obvious unimodal distribution with a maximum occurring in summer over the EUS and WEU regions, whereas they follow a bimodal distribution with peaks in August and March (due to crop residue burning) over the ECC region. In general, the nighttime-daytime AOD difference is more positive in summer than in winter, likely attributable to a larger diurnal temperature range in summer. Smoke AOD is much higher in the nighttime than in the daytime. The results of this study can help to improve the current estimates of the climatic and health impacts of aerosols.

This paper presents a $K_{u}$ -band (14–16 GHz) CMOS frequency-modulated continuous-wave (FMCW) radar transceiver developed to measure dry-snow depth for water management purposes and to aid in retrieval of snow water equivalent. An on-chip direct digital frequency synthesizer and digital-to-analog converter digitally generates a chirping waveform which then drives a ring oscillator-based $K_{u}$ -Band phase-locked loop to provide the final $K_{u}$ -band FMCW signal. Employing a ring oscillator as opposed to a tuned inductor-based oscillator (LC-VCO) allows the radar to achieve wide chirp bandwidth resulting in a higher axial resolution (7.5 cm), which is needed to accurately quantify the snowpack profile. The demonstrated radar chip is fabricated in a 65-nm CMOS process. The chip consumes 252.4 mW of power under 1.1-V supply, making its payload requirements suitable for observations from a small unmanned aerial vehicle.

A version of the WRF-Chem model with fully coupled aerosol–meteorology–snowpack is employed to investigate the impacts of various aerosol sources on precipitation and snowpack in California. In particular, the impacts of locally emitted anthropogenic and dust aerosols, and aerosols transported from outside California are studied. We differentiate three pathways of aerosol effects: aerosol–radiation interaction (ARI), aerosol–snow interaction (ASI), and aerosol–cloud interaction (ACI). The convection-permitting model simulations show that precipitation, snow water equivalent (SWE), and surface air temperature averaged over the whole domain (34–42∘ N, 117–124∘ W, not including ocean points) are reduced when aerosols are included, therefore reducing large biases in these variables due to the absence of aerosol effects in the model. Aerosols affect California water resources through the warming of mountaintops and the reduction of precipitation; however, different aerosol sources play different roles in changing surface temperature, precipitation, and snowpack in California by means of various weights of the three pathways. ARI by all aerosols mainly cools the surface, leading to slightly increased SWE over the mountains. Locally emitted dust aerosols warm the surface of mountaintops through ASI, in which the reduced snow albedo associated with dusty snow leads to more surface absorption of solar radiation and reduced SWE. Transported aerosols and local anthropogenic aerosols play a dominant role in increasing nonprecipitating clouds but reducing precipitation through ACI, leading to reduced SWE and runoff on the Sierra Nevada, as well as the warming of mountaintops associated with decreased SWE and hence lower surface albedo. The average changes in surface temperature from October 2012 to June 2013 are about −0.19 and 0.22 K for the whole domain and over mountaintops, respectively. Overall, the averaged reduction during October to June is about 7 % for precipitation, 3 % for SWE, and 7 % for surface runoff for the whole domain, while the corresponding numbers are 12, 10, and 10 % for the mountaintops. The reduction in SWE is more significant in a dry year, with 9 % for the whole domain and 16 % for the mountaintops. The maximum reduction of ∼ 20 % in precipitation occurs in May and is associated with the maximum aerosol loading, leading to the largest decrease in SWE and surface runoff over that period. It is also found that dust aerosols can cause early snowmelt on the mountaintops and reduced surface runoff after April.

The interactions between aerosols and ice clouds represent one of the largest uncertainties in global radiative forcing from pre-industrial time to the present. In particular, the impact of aerosols on ice crystal effective radius (Rei), which is a key parameter determining ice clouds' net radiative effect, is highly uncertain due to limited and conflicting observational evidence. Here we investigate the effects of aerosols on Rei under different meteorological conditions using 9-year satellite observations. We find that the responses of Rei to aerosol loadings are modulated by water vapor amount in conjunction with several other meteorological parameters. While there is a significant negative correlation between Rei and aerosol loading in moist conditions, consistent with the "Twomey effect" for liquid clouds, a strong positive correlation between the two occurs in dry conditions. Simulations based on a cloud parcel model suggest that water vapor modulates the relative importance of different ice nucleation modes, leading to the opposite aerosol impacts between moist and dry conditions. When ice clouds are decomposed into those generated from deep convection and formed in situ, the water vapor modulation remains in effect for both ice cloud types, although the sensitivities of Rei to aerosols differ noticeably between them due to distinct formation mechanisms. The water vapor modulation can largely explain the difference in the responses of Rei to aerosol loadings in various seasons. A proper representation of the water vapor modulation is essential for an accurate estimate of aerosol–cloud radiative forcing produced by ice clouds.

A set of parameterizations is developed for spectral single-scattering properties of clean and black carbon (BC)-contaminated snow based on geometric-optics surface wave (GOS) computations, which explicitly resolves BC–snow internal mixing and various snow grain shapes. GOS calculations show that, compared with nonspherical grains, volume-equivalent snow spheres show up to 20% larger asymmetry factors and hence stronger forward scattering, particularly at wavelengths 99%. Based on GOS calculations, BC–snow internal mixing enhances the snow single-scattering coalbedo at wavelengths 99%. Overall, in addition to snow grain size, both BC–snow internal mixing and snow grain shape play critical roles in quantifying BC effects on snow optical properties. The present parameterizations can be conveniently applied to snow, land surface, and climate models including snowpack radiative transfer processes.

Aerosol-cloud interactions (aerosol indirect effects) play an important role in regional meteorological variations, which could further induce feedback on regional air quality. While the impact of aerosol-cloud interactions on meteorology and climate has been extensively studied, their feedback on air quality remains unclear. Using a fully coupled meteorology-chemistry model, we find that increased aerosol loading due to anthropogenic activities in China substantially increases column cloud droplet number concentration and liquid water path (LWP), which further leads to a reduction in the downward shortwave radiation at surface, surface air temperature and planetary boundary layer (PBL) height. The shallower PBL and accelerated cloud chemistry due to larger LWP in turn enhance the concentrations of particulate matter with diameter less than 2.5 μm (PM2.5) by up to 33.2 μg m−3 (25.1%) and 11.0 μg m−3 (12.5%) in January and July, respectively. Such a positive feedback amplifies the changes in PM2.5 concentrations, indicating an additional air quality benefit under effective pollution control policies but a penalty for a region with a deterioration in PM2.5 pollution. Additionally, we show that the cloud processing of aerosols, including wet scavenging and cloud chemistry, could also have substantial effects on PM2.5 concentrations.

The global mean precipitation is largely constrained by atmospheric radiative cooling rates (Qr), which are sensitive to changes in high cloud fraction. We investigate variations of high cloud fraction with surface temperature (Ts) from July 2002 to June 2015 and compute their radiative effects on Qr using the Fu-Liou-Gu (FLG) plane-parallel radiation model. We find that the tropical-mean (30oS-30oN) high cloud fraction decreases with increasing Ts at a rate of about –1.0±0.34 % K–1 from 2002 to 2015, which leads to an enhanced atmospheric cooling around 0.86 W m–2 K–1. On the other hand, the northern mid-latitudes (30oN-60oN) high cloud fraction increases with surface warming at a rate of 1.85±0.65 % K–1 and the near-global mean (60oS-60oN) high cloud fraction shows a statistically insignificant decreasing trend with increasing Ts over the analysis period. Dividing high clouds into cirrus, cirrostratus and deep convective clouds, we find that cirrus cloud fraction increases with surface warming at a rate of 0.32±0.11 % K–1 (0.01±0.17 % K–1) for the near global-mean (tropical-mean), while cirrostratus and deep convective clouds decrease with surface warming at a rate of –0.02±0.18 % K–1 and –0.33±0.18 % K–1 for the near global-mean and –0.64±0.23 % K–1 and –0.37±0.13 % K–1 for the tropical-mean, respectively. High cloud fraction response to feedback to Ts accounts for approximately 1.9±0.7 % and 16.0±6.1 % of the increase in precipitation per unit surface warming over the period of 2002-2015 for the near global-mean and the tropical-mean, respectively.

The reflection and transmission of polarized light for a cirrus cloud consisting of randomly oriented hexagonal columns were calculated by two very different vector radiative transfer models. The forward peak of the phase function for the ensemble-averaged ice crystals has a value of order 6 × 10 3 so a truncation procedure was used to help produce numerically efficient yet accurate results. One of these models, the Vectorized Line-by-Line Equivalent model (VLBLE), is based on the doubling–adding principle, while the other is based on a vector discrete ordinates method (VDISORT). A comparison shows that the two models provide very close although not entirely identical results, which can be explained by differences in treatment of single scattering and the representation of the scattering phase matrix. The relative differences in the reflected I and Q Stokes parameters are within 0.5% for I and within 1.5% for Q for all viewing angles. In 1971 Hansen [1] showed that for scattering by spherical particles the 3×3 approximation is sufficient to produce accurate results for the reflected radiance I and the degree of polarization (DOP), and he conjectured that these results would hold also for non-spherical particles. Simulations were conducted to test Hansen׳s conjecture for the cirrus cloud particles considered in this study. It was found that the 3×3 approximation also gives accurate results for the transmitted light, and for Q and U in addition to I and DOP. For these non-spherical ice particles the 3×3 approximation leads to an absolute error 2 × 10 − 6 for the reflected and transmitted I , Q and U Stokes parameters. Hence, it appears to be an excellent approximation, which significantly reduces the computational complexity and burden required for multiple scattering calculations.

Previous modeling of snow albedo, a key climate feedback parameter, follows the independent scattering approximation (ISA) such that snow grains are considered as a number of separate units with distances longer than wavelengths. Here we develop a new snow albedo model for widely observed close-packed snow grains internally mixed with black carbon (BC) and demonstrate that albedo simulations match closer to observations. Close packing results in a stronger light absorption for clean and BC-contaminated snow. Compared with ISA, close packing reduces pure snow albedos by up to ~0.05, whereas it enhances BC-induced snow albedo reduction and associated surface radiative forcing by up to 15% (20%) for fresh (old) snow, with larger enhancements for stronger structure packing. Finally, our results suggest that BC-snow albedo forcing and snow albedo feedback (climate sensitivity) are underestimated in previous modeling studies, making snow close packing consideration a necessity in climate modeling and analysis.