Black carbon (BC) is one of the major aerosol components with relatively high implications on climatic patterns through its radiative forcing (RF). South Asia has recently experienced an increased concentration of pollution; however, relatively fewer studies have been carried out on long-term assessment of BC and its implications. The present study analyzed the long-term concentration of BC in selected urban locations over South Asia using the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2). The study employed statistical analysis, including linear regression techniques, to assess the long-term concentration of BC. The results show that a rapid increase of BC is observed over most urban locations of South Asia with the predominance in winter and hence requires strict regional control measures to reduce the excess concentration of BC in the atmosphere. High concentration of BC in winter is attributed to anthropogenic activities and changes in meteorological conditions that enhance the accumulation of pollutants in the atmosphere. The relationship of BC with cloud top temperature and cloud effective radius demonstrates the direct and indirect effect of BC on cloud properties in this region. The RF results reveal that aerosol optical depth has positive aerosol RF in the atmosphere and negative RF at the top of the atmosphere (TOA) as well as at the bottom of the atmosphere (BOA). Negative RF at the TOA indicates less forcing efficiency due to fewer BC aerosols. On the other hand, averaging aerosol RF within the atmosphere reveals positive forcing, which suggests the efficiency force exerted by BC aerosols after absorbing solar radiation.

Water temperature extremes can pose serious threats to the aquatic ecosystems of mountain rivers. These rivers are influenced by snow and glaciermelt, which change with climate. As a result, the frequency and severity of water temperature extremes may change. While previous studies have documented changes in non-extreme water temperature, it is yet unclear how extreme water temperatures change in a warming climate and how their hydro-meteorological drivers differ from those of non-extremes. This study aims to assess temporal changes and spatial variability in water temperature extremes and enhance our understanding of the driving processes across European mountain rivers in the current climate, at both a regional and continental scale. First, we describe the characteristics of extreme events and explore their relationships with catchment characteristics. Second, we assess trends in water temperature extremes and compare them with trends in mean water temperature. Third, we use random forest models to identify the main driving processes of water temperature extremes. Last, we conduct a co-occurrence analysis to examine the relationship between water temperature extremes and hydro-climatic extremes. Our results show that mean water temperature has increased by +0.38 +/- 0.14 ${+}0.38\pm 0.14$degrees C per decade, leading to more extreme events at high elevations in spring and summer. While non-extreme water temperatures are mainly driven by air temperature, water temperature extremes are also importantly influenced by soil moisture, baseflow, and meltwater. Our study highlights the complexity of water temperature dynamics in mountain rivers at the regional and continental scale, especially during water temperature extremes.

The seasonal mountain snowpack of the Western US (WUS) is a key water resource to millions of people and an important component of the regional climate system. Impurities at the snow surface can affect snowmelt timing and rate through snow radiative forcing (RF), resulting in earlier streamflow, snow disappearance, and less water availability in dry months. Predicting the locations, timing, and intensity of impurities is challenging, and little is known concerning whether snow RF has changed over recent decades. Here we analyzed the relative magnitude and spatio-temporal variability of snow RF across the WUS at three spatial scales (pixel, watershed, regional) using remotely sensed RF from spatially and temporally complete (STC) MODIS data sets (STC-MODIS Snow Covered Area and Grain Size/MODIS Dust Radiative Forcing on Snow) from 2001 to 2022. To quantify snow RF impacts, we calculated a pixel-integrated metric over each snowmelt season (1st March-30th June) in all 22 years. We tested for long-term trend significance with the Mann-Kendall test and trend magnitude with Theil-Sen's slope. Mean snow RF was highest in the Upper Colorado region, but notable in less-studied regions, including the Great Basin and Pacific Northwest. Watersheds with high snow RF also tended to have high spatial and temporal variability in RF, and these tended to be near arid regions. Snow RF trends were largely absent; only a small percent of mountain ecoregions (0.03%-8%) had significant trends, and these were typically decreasing trends. All mountain ecoregions exhibited a net decline in snow RF. While the spatial extent of significant RF trends was minimal, we found declining trends most frequently in the Sierra Nevada, North Cascades, and Canadian Rockies, and increasing trends in the Idaho Batholith. This study establishes a two-decade chronology of snow impurities in the WUS, helping inform where and when RF impacts on snowmelt may need to be considered in hydrologic models and regional hydroclimate studies.

Tree-ring width chronologies are a critically important material to reconstruct past precipitation variability on the northeastern Tibetan Plateau (NTP). However, temperature signals are often encoded in these chronologies, which complicate the precipitation reconstructions and should be carefully assessed. Here, a dataset of 487 Qilian juniper (Juniperus przewalskii Kom.) tree-ring width series from 16 sites on the NTP were collected to investigate the influence of different temperature signals on the precipitation reconstructions. Correlation analysis showed that all tree-ring series recorded similar precipitation information, but had positive (p 0.05, Group1), weak (p 0.05, Group2), and negative (p < 0.05, Group3) correlations with temperature, respectively. In view of this, all tree-ring series were divided into three groups to develop chronologies to reconstruct local precipitation. During the calibration period of 1957?2011 CE, the Group1 reconstruction had the fastest uptrend, which almost overlapped the observed precipitation; the Group2 reconstruction showed a slower uptrend, whereas the Group3 reconstruction lacked an uptrend. As a result, we get different results when the reconstructions were used to assess the current precipitation status over the past millennium. The Group1 (Group2) reconstructions showed that the recent 20 (10) years were the highest precipitation period over the past millennium, whereas the Group3 reconstruction did not capture this phenomenon. Therefore, we caution that the temperature effects should be evaluated carefully before tree-ring width chronologies being employed to study past precipitation variability.

Aerosol-cloud interactions, also known as aerosol indirect effect (AIE), substantially impact rainfall frequency and intensity. Here, we analyze NEX-GDDP, a multimodel ensemble of high-resolution (0.25 degrees) historical simulations and future projections statistically downscaled from 21 CMIP5 models, to quantify the importance of AIE on extreme climate indices, specifically consecutive dry days (CDD), consecutive wet days (CWD), and simple daily intensity index (SDII). The 21 NEX-GDDP CMIP5 models are classified into models with reliable (REM) and unreliable (UREM) monsoon climate simulated over India based on their simulations of the climate indices. The REM group is further decomposed based on whether the models represent only the direct (REMADE) or the direct and indirect (REMALL) aerosol effects. Compared to REMADE, including all aerosol effects significantly improves the model skills in simulating the observed historical trends of all three climate indices over India. Specifically, AIE enhances dry days and reduces wet days in India in the historical period, consistent with the observed changes. However, by the middle and end of the 21st century, there is a relative decrease in dry days and an increase in wet days and precipitation intensity. Moreover, the REMALL simulated future CWD and CDD changes are mostly opposite to those in REMADE, indicating the substantial role of AIE in the future projection of dry and wet climates. These findings underscore the crucial role of AIE in future projections of the Indian hydroclimate and motivate efforts to accurately represent AIE in climate models. We investigate the impacts of aerosol on India's wet and dry climate. High-resolution downscaled CMIP5 models were used to calculate extreme indices like CDD (consecutive dry days), CWD (consecutive wet days), SDII (precipitation intensity). From the group of 22 models, 12 reliable models were chosen based on their fidelity to the observations. Amongst the reliable models, certain models incorporate only aerosol-radiation interaction (REMADE), while others have both aerosol-radiation and aerosol-cloud interaction (REMALL). We found that the simulated trends in the REMAll were similar to the observed trends. In the current period (1975-2005), the aerosol-cloud interactions led to the reduction in rainfall (both frequency and intensity wise) and enhanced the dry days, however in the future projections, the reduction in aerosol emissions leads to a wetter climate (increase in wet days and rainfall intensity) over India.

Arctic hydrology is experiencing rapid changes including earlier snow melt, permafrost degradation, increasing active layer depth, and reduced river ice, all of which are expected to lead to changes in stream flow regimes. Recently, long-term (>60 years) climate reanalysis and river discharge observation data have become available. We utilized these data to assess long-term changes in discharge and their hydroclimatic drivers. River discharge during the cold season (October-April) increased by 10% per decade. The most widespread discharge increase occurred in April (15% per decade), the month of ice break-up for the majority of basins. In October, when river ice formation generally begins, average monthly discharge increased by 7% per decade. Long-term air temperature increases in October and April increased the number of days above freezing (+1.1 d per decade) resulting in increased snow ablation (20% per decade) and decreased snow water equivalent (-12% per decade). Compared to the historical period (1960-1989), mean April and October air temperature in the recent period (1990-2019) have greater correlation with monthly discharge from 0.33 to 0.68 and 0.0-0.48, respectively. This indicates that the recent increases in air temperature are directly related to these discharge changes. Ubiquitous increases in cold and shoulder-season discharge demonstrate the scale at which hydrologic and biogeochemical fluxes are being altered in the Arctic.

It is widely accepted that global warming is affecting forests near the tree line by increasing tree growth in these cold-limited environments. However, since about 1970, a reduction in tree growth near the tree line has been observed in response to warming and increased drought stress. This reduction in tree growth has been mainly reported in forests of the northern hemisphere but less studied in southern forests. In this study, we investigated tree populations of Nothofagus pumilio located near the arboreal altitudinal limit in the central Patagonian Andes (45-47 degrees S, Aysen region, Chile). In this region, warming has been accompanied by increased drought conditions since the 2000s. We explored whether this climatic variability has promoted or reduced tree growth at the regional scale in tree lines of these broadleaved temperate forests of central Patagonia. We constructed tree-ring chronologies and determined common growth patterns and trends, and then analyzed the influence of recent climate. We detected a significant change in the slope of regional growth trends between the periods 1955-1985 and 1985-2015. We found that positive growth trends in the period 1955-1985 were associated with warmer and drier springs. However, after 1985, we found a stabilization in N. pumilio growth associated with a steady increase in temperature in autumn. Our results support the idea that more frequent warm autumns, with very thin or no snow cover, have stabilized tree growth due to water deficit at the end of the growing season of N. pumilio. The predicted climate change scenario of increasing temperatures and drought in central Patagonia may increase competition among trees for water, particularly at the end of the growing season. Consequently, we could expect a decreasing forest growth trend in central Patagonia, potentially impacting forest dynamics of these southern forests.

Recent satellite observations of atmospheric aerosol loading over Asia indicate a dipole pattern in the aerosol optical depth (AOD) with a substantial decrease in AOD over East Asia and persistent increase in AOD over South Asia, the two global hotspots of aerosol emissions. Aerosol emissions over Asia are also changing rapidly. However, the evolution of physical, optical and chemical columnar aerosol characteristics, and their radiative effects over time, and the resultant impacts of such evolving trends on climate and other associated risks are not yet properly quantified, and used in climate impact assessments. In order to do so, we closely examine, in addition to satellite observations, for the first time, high-quality, ca. two-decade long ground-based observations since 2001 of aerosols and their radiative effects from several locations in the Indo-Gangetic Plain (IGP) in South Asia and the North China Plain (NCP) in East Asia. A clear divergence in the trends in AODs is evident between the IGP and the NCP. The single scattering albedo (SSA) is increasing, and the absorption AOD due to carbonaceous aerosols (AAOD(CA)) is decreasing over both regions, confirming that aerosols are becoming more scattering in nature. The trends in observed aerosol content (AOD) and composition (SSA) are statistically significant over Kanpur in the IGP and Beijing in the NCP, two locations with longest ground-based records. The aerosol radiative forcing of atmosphere (ARF(ATM)) and resultant atmospheric heating rate (HR) are decreasing over both regions. However, current regionally coherent and high annual HR of 0.5-1.0 K day(-1) has severe implications to climate, hydrological cycle, and cryosphere over Asia and beyond. These results based on high-quality observations over a large spatial domain are of great significance and are crucial for modelling and quantifying aerosol-climate interactions. (C) 2021 The Author(s). Published by Elsevier B.V. on behalf of International Association for Gondwana Research.

Freezing and thawing indices (FI and TI) are commonly used as indicators for climate change assessment and permafrost extent estimation in cold regions. In this study, based on the meteorological daily data (1978-2017) among 34 meteorological stations in Tibet, the temperature in space has been interpolated and FI and TI have been calculated. Finally, spatiotemporal variations have been analyzed and the permafrost area has been estimated. The results showed the mean annual of FI and TI in Tibet are 1241.36 and 1290.22 degrees C.day, respectively. A significant downward trend in freezing index (FI) and an upward trend in thawing index (TI) have been reported in the time series, in against, analyzing the spatial distribution showed there is an increasing trend from southeast to northwest for FI while TI was decreased gradually in the same region in Tibet. This research indicates that altitude has a significant influence on the change of FI and TI. With the increase of altitude, FI decreased and TI increased more significantly. The permafrost area was estimated at about 0.59 x 10(6) km(2) in Tibet.

The active layer thickness (ALT) in permafrost regions, which affects water and energy exchange, is a key variable for assessing hydrological processes, cold-region engineering, and climate change. In this study, the authors analyzed the variation trends and relative changes of simulated ALTs using the Chinese Academy of Sciences Land Surface Model (CAS-LSM) and the Chinese Academy of Sciences Flexible Global Ocean-Atmosphere-Land System Model, gridpoint version 3 (CAS-FGOALS-g3). Firstly, the simulated ALTs produced by CAS-LSM were shown to be reasonable by comparing them with Circumpolar Active Layer Monitoring observations. Then, the authors simulated the ALTs from 1979 to 2014, and their relative changes across the entire Northern Hemisphere from 2015 to 2100. It is shown that the ALTs have an increasing trend. From 1979 to 2014, the average ALTs and their variation trends over all permafrost regions were 1.08 m and 0.33 cm yr(-1), respectively. The relative changes of the ALTs ranged from 1% to 58%, and the average relative change was 10.9%. The variation trends of the ALTs were basically consistent with the variation trends of the 2-m air temperature. By 2100, the relative changes of ALTs are predicted to be 10.3%, 14.6%, 30.1%, and 51%, respectively, under the four considered hypothetical climate scenarios (SSP-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). This study indicates that climate change has a substantial impact on ALTs, and our results can help in understanding the responses of the ALTs of permafrost due to climate change.