A comprehensive global investigation on the impact of reduction (changes) in aerosol emissions due to Coronavirus disease-2019 (COVID-19) lockdowns on aerosol single scattering albedo (SSA) utilizing satellite observations and model simulations is conducted for the first time. The absolute change in Ozone Monitoring Instrument (OMI) retrieved, and two highly-spatially resolved models (Modern-Era Retrospective Analysis for Research and Applications-2 (MERRA-2) and Copernicus Atmosphere Monitoring Service (CAMS)) simulated SSA is <4% (<0.04-0.05) globally during COVID (2020) compared to normal (2015-2019) period. Change in SSA during COVID is not significantly different from long-term and year-to-year variability in SSA. A small change in SSA indicates that significant reduction in anthropogenic aerosol emissions during COVID-19 induced lockdowns has a negligible effect in changing the net contribution of aerosol scattering and/or absorption to total aerosol extinction. The changes in species-wise aerosol optical depth (AOD) are examined in detail to explain the observed changes in SSA. Model simulations show that total AOD decreased during COVID-19 lockdowns, consistent with satellite observations. The respective contributions of sulfate and black carbon (BC) to total AOD increased, which resulted in a negligible change in SSA during the spring and summer seasons of COVID over South Asia. Europe and North America experience a small increase in SSA (<2%) during the summer season of COVID due to a decrease in BC contribution. The change in SSA (2%) is the same for a small change in BC AOD contribution (3%), and for a significant change in sulfate AOD contribution (20%) to total AOD. Since, BC SSA is 5-times lower (higher absorption) than that of sulfate SSA, the change in SSA remains the same. For a significant change in SSA to occur, the BC AOD contribution needs to be changed significantly (4-5 times) compared to other aerosol species. A sensitivity analysis reveals that change in aerosol radiative forcing during COVID is primarily dependent on change in AOD rather than SSA. These quantitative findings can be useful to devise more suitable future global and regional mitigation strategies aimed at regulating aerosol emissions to reduce environmental impacts, air pollution, and public health risks.

The volume of Earth system observations has grown massively in recent decades. However, multivariate or multisource analyses at the interface of atmosphere and land are still hampered by the sparsity of ground measurements and the abundance of missing values in satellite observations. This can hinder robust multivariate analysis and introduce biases in trends. Nevertheless, gap-filling is often done univariately, which can obscure physical dependencies. Here, we apply the new multivariate gap-filling framework CLIMate data gapFILL (CLIMFILL). CLIMFILL combines state-of-the-art spatial interpolation with an iterative approach accounting for dependencies across multiple incomplete variables. CLIMFILL is applied to a set of remotely sensed and in situ observations over land that are central to observing land-atmosphere interactions and extreme events. The resulting gridded monthly time series covers 1995-2020 globally with gap-free maps of nine variables: surface layer soil moisture from European Space Agency (ESA)-Climate Change Initiative (CCI), land surface temperature and diurnal temperature range from Moderate-resolution Imaging Spectroradiometer, precipitation from GPM, terrestrial water storage from GRACE, ESA-CCI burned area, and snow cover fraction as well as 2-m temperature and precipitation from CRU. Time series of anomalies are reconstructed better compared to state-of-the-art interpolation. The gap-filled data set shows high correlations with ERA5-Land, and soil moisture estimates compare favorably to in situ observations from the International Soil Moisture Network. Soil moisture drying trends in ESA-CCI only agree with the reanalysis product ERA5-Land trends after gap-filling. We furthermore showcase that key features of droughts and heatwaves in major fire seasons are well represented. The data set can serve as a step toward the fusion of multivariate multisource observations.

The impact of aerosols, especially the absorbing aerosols, in the Himalayan region is important for climate. We closely examine ground-based high-quality observations of aerosol characteristics including radiative forcing from several locations in the Indo-Gangetic Plain (IGP), the Himalayan foothills and the Tibetan Plateau, relatively poorly studied regions with several sensitive ecosystems of global importance, as well as highly vulnerable large populations. This paper presents a state-of-the-art treatment of the warming that arises from these particles, using a combination of new measurements and modeling techniques. This is a first-time analysis of its kind, including ground-based observations, satellite data, and model simulations, which reveals that the aerosol radiative forcing efficiency (ARFE) in the atmosphere is clearly high over the IGP and the Himalayan foothills (80-135 Wm(-2) per unit aerosol optical depth (AOD)), with values being greater at higher elevations. AOD is >0.30 and single scattering albedo (SSA) is similar to 0.90 throughout the year over this region. The mean ARFE is 2-4 times higher here than over other polluted sites in South and East Asia, owing to higher AOD and aerosol absorption (i.e., lower SSA). Further, the observed annual mean aerosol induced atmospheric heating rates (0.5-0.8 Kelvin/day), which are significantly higher than previously reported values for the region, imply that the aerosols alone could account for >50 % of the total warming (aerosols + greenhouse gases) of the lower atmosphere and surface over this region. We demonstrate that the current state-of-the-art models used in climate assessments significantly underestimate aerosol-induced heating, efficiency and warming over the Hindu Kush - Himalaya - Tibetan Plateau (HKHTP) region, indicating a need for a more realistic representation of aerosol properties, especially of black carbon and other aerosols. The significant, regionally coherent aerosol induced warming that we observe in the high altitudes of the region, is a significant factor contributing to increasingair temperature, observed accelerated retreat of the glaciers, and changes in the hydrological cycle and precipitation patterns over this region. Thus, aerosols are heating up the Himalayan climate, and will remain a key factor driving climate change over the region.

Limited by the scarcity of in situ vertical observation data, the influences of biomass burning in Southeast Asia on major atmospheric carbonaceous compositions in downwind regions have not been thoroughly studied. In this study, aircraft observations were performed to obtain high time-resolved in situ vertical distributions of black carbon (BC) as well as carbon monoxide (CO) and carbon dioxide (CO2). Four types of profiles were revealed: Mode I (from 2000 to 3000 m, the BC, CO and CO2 concentrations were enhanced), Mode II (with increasing altitude, the BC, CO and CO2 concentrations almost decreased), Mode III (inhomogeneous vertical BC, CO and CO2 profiles with BC peaks were observed from 2500 to 3000 m) and Mode IV (the BC, CO and CO2 concentrations increased above 1500 m). Furthermore, simulations were conducted to calculate radiative forcing (RF) caused by BC and study the heating rate (HR) of BC in combination with the vertical BC profiles. A larger BC distribution in the atmosphere re-sulted in a sharp RF change from negative to positive values, imposing a nonnegligible influence on the atmospheric temperature profile, with maximum HR values ranging from 0.4 to 5.8 K/day. The values of the absorption Angstrom exponent (AAE) were 1.46 +/- 0.11 and 1.48 +/- 0.17 at altitudes from 1000 to 2000 and 2000-3000 m, respectively. The average BC light absorption coefficient at the 370 nm wavelength (alpha BC (370)) accounted for 50.3 %-76.8 % of the alpha (370), while the brown carbon (BrC) light absorption coefficient at the 370 nm wavelength (alpha BrC (370)) contrib-uted 23.2 %-49.7 % to the alpha (370) at altitudes of 1000-2000 m. At altitudes of 2000-3000 m, alpha BC (370) and alpha BrC (370) contributed 43.8 %-88.2 % and 11.8 %-56.2 % to the alpha (370), respectively. These findings show that calculations that consider the surface BC concentration but ignore the vertical BC distribution could result in massive uncertainties in estimating the RF and HR caused by BC. This study helped achieve a deeper understanding of the influences of biomass burning over the region of Southeast Asia on the profiles of atmospheric carbonaceous compositions and atmospheric BC absorption and its warming effect.

A comprehensive investigation of physical, optical, and chemical characteristics of columnar aerosols over two locations with distinct environmental settings in the Indo-Gangetic Plain (IGP) region, namely, Kanpur (urban and industrial area) and Gandhi College (rural area), is conducted using high-quality aerosol datasets obtained from ground-based Aerosol Robotic Network (AERONET) observations during the recent five year period (2015-2019). This study utilizes all the crucial columnar aerosol parameters necessary for accurately estimating aerosol radiative forcing. Quantification of contribution by different aerosol species originating from natural and anthropogenic sources to the total aerosol optical depth (AOD) and single scattering albedo (SSA) is important to understand the specific mechanisms that influence the aerosol composition, thereby reducing the uncertainty in aerosol radiative forcing. For the first time, two highly spatially resolved models' (Modern-Era Retrospective Analysis for Research and Applications-2 (MERRA-2) and Copernicus Atmosphere Monitoring Service (CAMS)) simulated absorbingspecies-wise (black carbon (BC), dust, and brown carbon (BrC)) AOD, and absorption AOD (AAOD) are compared and contrasted against the AERONET observations over the IGP region in a systematic manner. MERRA-2 AODs are mostly lower, whereas CAMS AODs are consistently higher than the AERONET AODs. A comparison of collocated time and space observations with models clearly suggests that improvements in emission inventories on a seasonal scale are essential. MERRA-2 SSA is noted lower than the AERONET SSA during the winter season due to overestimation in BC AOD. During winter in >70% of MERRA-2 simulated SSA the difference is higher than +/- 0.03 (the uncertainty range of AERONET SSA) whereas during pre-monsoon and monsoon seasons >60% of MERRA-2 SSA lies within the uncertainty range of AERONET SSA. Both models show a gradient in AODDust decreasing from west to east in the IGP. However, observations do not often exhibit the gradient in dust, which is validated by air mass back trajectory analyses as air masses travel through different pathways to IGP and reverse the west to east gradient in AODDust. This quantitative and comparative collocated analysis of observed aerosol characteristics with models on a seasonal scale will enable a better estimation of aerosol radiative forcing, and can help improve aerosol processes and parameterizations in models.

Upper Brahmaputra (UB) is the largest (similar to 240,000 km(2)) river basin of the Tibetan Plateau, where hydrological processes are highly sensitive to climate change. However, constrained by difficult access and sparse in situ observations, the variations in precipitation, glaciers, frozen ground, and vegetation across the UB basin remain largely unknown, and consequently the impacts of climate change on streamflow cannot be accurately assessed. To fill this gap, this project aims to establish a basinwide, large-scale observational network (that includes hydrometeorology, glacier, frozen ground, and vegetation observations), which helps quantify the UB runoff processes under climate-cryosphere-vegetation changes. At present, a multisphere observational network has been established throughout the catchment: 1) 12 stations with custom-built weighing automatic rain/snow meters and temperature probes to obtain elevation-dependent gradients; 2) 9 stations with soil moisture/temperature observations at four layers (10, 40, 80, 120 cm) covering Alpine meadow, grasslands, shrub, and forest to measure vegetation (biomass and vegetation types) and soil (physical properties) simultaneously; 3) 34 sets of probes to monitor frozen ground temperatures from 4,500 to 5,200 m elevation (100-m intervals), and two observation systems to monitor water and heat transfer processes in frozen ground at Xuegela (5,278 m) and Mayoumula (5,256 m) Mountains, for improved mapping of permafrost and active layer characteristics; 4) 5 sets of altimetry discharge observations along ungauged cross sections to supplement existing operational gauges; 5) high-precision glacier boundary and ice-surface elevation observations at Namunani Mountain with differential GPS, to supplement existing glacier observations for validating satellite imagery. This network provides an excellent opportunity to monitor UB catchment processes in great detail.

Monitoring changes in river runoff at the Third Pole (TP) is important because rivers in this region support millions of inhabitants in Asia and are very sensitive to climate change. Under the influence of climate change and intensified cryospheric melt, river runoff has changed markedly at the TP, with significant effects on the spatial and temporal water resource distribution that threaten water supply and food security for people living downstream. Despite some in situ observations and discharge estimates from state-of-the-art remote sensing technology, the total river runoff (TRR) for the TP has never been reliably quantified, and its response to climate change remains unclear. As part of the Chinese Academy of Sciences' Pan-Third Pole Environment Study for a Green Silk Road, the TP-River project aims to construct a comprehensive runoff observation network at mountain outlets (where rivers leave the mountains and enter the plains) for 13 major rivers in the TP region, thereby enabling TRR to be accurately quantified. The project also integrates discharge estimates from remote sensing and cryosphere-hydrology modeling to investigate long-term changes in TRR and the relationship between the TRR variations and westerly/monsoon. Based on recent efforts, the project provides the first estimate (656 +/- 23 billion m(3)) of annual TRR for the 13 TP rivers in 2018. The annual river runoff at the mountain outlets varies widely between the different TP rivers, ranging from 2 to 176 billion m(3), with higher values mainly corresponding to rivers in the Indian monsoon domain, rather than in the westerly domain.

The European Center for Medium-Range Weather Forecasts (ECMWF) released its latest reanalysis dataset named ERA5 in 2017. To assess the performance of ERA5 in Antarctica, we compare the near-surface temperature data from ERA5 and ERA-Interim with the measured data from 41 weather stations. ERA5 has a strong linear relationship with monthly observations, and the statistical significant correlation coefficients (p < 0.05) are higher than 0.95 at all stations selected. The performance of ERA5 shows regional differences, and the correlations are high in West Antarctica and low in East Antarctica. Compared with ERA5, ERA-Interim has a slightly higher linear relationship with observations in the Antarctic Peninsula. ERA5 agrees well with the temperature observations in austral spring, with significant correlation coefficients higher than 0.90 and bias lower than 0.70 degrees C. The temperature trend from ERA5 is consistent with that from observations, in which a cooling trend dominates East Antarctica and West Antarctica, while a warming trend exists in the Antarctic Peninsula except during austral summer. Generally, ERA5 can effectively represent the temperature changes in Antarctica and its three subregions. Although ERA5 has bias, ERA5 can play an important role as a powerful tool to explore the climate change in Antarctica with sparse in situ observations.

Long-term and high-resolution gridded products of precipitation and temperature data are highly important to study the changes in climate and environment under global warming. Considering the uncertainties of these products in mountainous areas, it is necessary to evaluate the data reliability. This study evaluates the performances of the CMFD (China Meteorological Forcing Dataset) and ERA5-Land in simulating precipitation and temperature in the Qilian Mountains over the period of 1980-2018. We use the observation data of 28 basic meteorological stations in the Qilian Mountains to compare with the reanalysis products. Error metrics (the correlation coefficient (CC), the root mean square error (RMSE), the mean absolute error (MAE), and the relative bias (BIAS)) are used to quantify the monthly differences in existence between the observed data and reanalysis data. Our findings indicate that both CMFD and ERA5-Land could well reproduce the spatial distribution of mean monthly precipitation and temperature in the region. A good correlation is found between CMFD and OBS under different amounts of monthly precipitation conditions. The monthly average temperatures of CMFD and ERA5-Land reveal a high correlation with the observed results. Moreover, the CC values of CMFD and ERA5-Land precipitation products are the highest in autumn and the lowest in winter, and the CC values of both CMFD and ERA5-Land temperature products are higher in spring and autumn. However, we find that both reanalysis products underestimate the temperature to varying degrees, and the amount of precipitation is overestimated by ERA5-Land. The results of the evaluation show that the errors in precipitation yielded by CMFD as a whole are distinctly fewer than those yielded by ERA5-Land, while the errors in air temperature yielded by both ERA5-Land and CMFD are nearly identical to each other. Overall, ERA5-Land is more suitable than CMFD for studying the trends of temperature changes in the Qilian Mountains. As for simulation of precipitation, CMFD performs better in the central and eastern parts of the Qilian Mountains, whereas ERA5-Land performs better in the western part of the Qilian Mountains.

East Asia is the strongest global source region for anthropogenic black carbon (BC), the most important light-absorbing aerosol contributing to direct radiative climate forcing. To provide extended observational constraints on regional BC distributions and impacts, in situ measurements of BC were obtained with a single particle soot photometer during the May/June 2016 Korean-United States Air Quality aircraft campaign (KORUS-AQ) in South Korea. Unique chemical tracer relationships were associated with BC sourced from different regions. The extent and variability in vertical BC mass burden for 48 profiles over a single site near Seoul were investigated using back trajectory and chemical tracer analysis. Meteorologically driven changes in transport influenced the relative importance of different source regions, impacting observed BC loadings at all altitudes. Internal mixing and size distributions of BC further demonstrated dependence on source region: BC attributed to China had a larger mass median diameter (18013nm) than BC attributed to South Korea (15225nm), and BC associated with long-range transport was less thickly coated (604nm) than that sourced from South Korea (7516nm). The column BC direct radiative effect at the top of the atmosphere was estimated to be 1.0-0.5+0.9W/m(2), with average values for different meteorological periods varying by a factor of 2 due to changes in the BC vertical profile. During the campaign, BC sourced from South Korea ( 31%), China (22%), and Russia (14%) were the most significant single-region contributors to the column direct radiative effect.