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The out‐of‐phase mode of winter surface air temperature anomalies (SATAs) over northern Central Asia (NCA; 45°–65°N, 40°–100°E) between January and February is investigated in this study. This mode corresponds to warm (cold) SATAs in January (February) over NCA and is mainly modulated by the enhanced tropical convection anomalies over the Maritime Continent in previous late December, associated with MJO phase 4. These tropical convection anomalies can induce anomalous tropospheric Rossby‐wave sources over the North Pacific in late December. The eastward‐propagating Rossby‐wave train, triggered by these anomalous Rossby‐wave sources, can cause negative and positive tropospheric geopotential height anomalies over the Greenland–Scandinavia region and NCA in the following early–mid‐January, subsequently leading to warm SATAs over NCA in January. The negative geopotential height anomalies over the Greenland–Scandinavia region in early–mid‐January can trigger upward‐propagating wave activity fluxes (WAFs) into the stratosphere, resulting in negative stratospheric geopotential height anomalies in late January–early February. These stratospheric anomalies, by triggering downward‐propagating WAFs, can in turn lead to positive tropospheric geopotential height anomalies over the Greenland–Scandinavia region in early February. These anomalies over the Greenland–Scandinavia region can maintain themselves in the following mid‐ and late February by feedback of anomalous storm tracks, and cause negative geopotential height anomalies and subsequently cold SATAs over NCA in February by triggered southeastward‐propagating Rossby‐wave train. [ABSTRACT FROM AUTHOR]

The slowly varying soil temperature can exert local and nonlocal influences on regional climate system, and may thus provide a critical source of subseasonal-to-seasonal climate prediction. In this study, we identify that soil temperature in May over the key region of Central Asia (42 °N–50 °N, 62 °E–80°E, KRCA) from Noah, Mosaic, CLM and ERA-interim datasets is closely linked to variations of the surface air temperature, daily maximum temperature and hot days over Northeastern China in summer (June–July–August), with correlation coefficients of regional average detrended time series ranging from 0.42 to 0.54, and all significant at the 99% confidence level for the period of 1979–2018. The possible physical mechanism behind the substantial downstream impacts of soil temperature over Central Asia are explored via diagnostical analysis combined with regional climate model experiments. Warmer soil temperature in May over the KRCA can keep to the summer and cause positive anomalies of geopotential height in summer over Northeastern China through the Rossby wave propagation, and associated stronger subsidence warming, less cloud cover, more solar radiation reaching the surface, higher planetary boundary layer, and stronger thermal advection at 850 hPa, which provide favorable conditions for warmer surface air temperature particularly in the daytime as well as more hot days. This study further reveals that soil temperature over Central Asia in May makes important contribution to prediction of summer surface air temperature, daily maximum temperature and hot days over Northeastern China in terms of regional average time series and spatial patterns. Our findings highlight the previously-unknown substantial role of antecedent soil temperature condition over Central Asia for summer surface air temperature variation and prediction over Northeastern China. [ABSTRACT FROM AUTHOR]

Central Asia (CA) has experienced a faster temperature rise than the global land over the past decades. However, the role of regional/global drivers and their associated underlying biophysical mechanisms is poorly explored. Here, we combined observations and model simulations to show that the rapid warming in CA was overwhelmingly contributed by rapid spring warming (i.e., 49.23%). The decrease of cloud cover (CLD) was the main driver of spring warming in CA, leading to the surface receiving more solar radiation, consequently heating the surface air temperature, and contributing almost 40.79% to the spring warming. Besides, the strengthening of sea level pressure states results in continuous subsidence of vertical motion over CA, which was unfavorable for cloud formation. Our study will deepen our understanding of the climate evolution in the arid CA. Plain Language Summary: Central Asia (CA) has experienced a faster temperature rise than the global land over the past decades, which has brought unprecedented challenges to the survival and flourishing of life. The role of drivers and their associated underlying biophysical mechanisms is explored here. We conclude that the temperature increase in CA is overwhelmingly contributed by rapid warming in spring (i.e., 49.23%), and the rapidly increasing trend will continue till the end of this century. The decrease of cloud cover (CLD) was the main driver of spring warming in CA, leading to the surface receiving more solar radiation, and consequently heating the surface air temperature, contributing almost 40.79% to the spring warming. Besides, the strengthening of sea level pressure states results in subsidence of vertical motion over CA, which was unfavorable for cloud formation. Key Points: The rapid spring warming contributed most to the annual temperature increase in Central Asia (CA) among other seasonsThe rapid spring average temperature rise in arid CA was mainly driven by the decreased cloud coverThe increase in sea level pressure led to the subsidence of vertical motion over CA and consequently the decreased cloud cover [ABSTRACT FROM AUTHOR]

The Great Lakes Depression region basin is among the most sensitive regions to vegetation change due to climate change. This study estimated spatial-temporal changes and relationships in hydro-climate and vegetation dynamics in the basin. Studying the spatial-temporal variation between vegetation dynamics and hydro-climate in this basin is essential for assessing climate change and sustainability. This research involved an examination of the mean yearly air temperature, overall annual rainfall, fluctuations in river discharge, vegetation cover, and alterations in vegetation types within the selected basin stations. This was accomplished through the utilization of hydro-meteorological analysis, satellite assessment, land cover determination, and statistical analysis. Over the course of the study, it was observed that the average annual air temperature increased at all stations (with a positive change of Z = +1.16). The amount of precipitation decreased (Z = −0.79), especially from 2000 to 2014, and its statistical significance decreased. During the study period, average river discharge significantly decreased (Z = −3.51). Due to these combined factors, the lake's water level also decreased (Z = −2.03). Vegetation cover change varied in high mountains, near river and lake water surfaces, and in arid regions. Changes in air temperature and precipitation in the current year determine vegetation cover. Because of the large amount of precipitation in the summer months from 2000 to 2010 and 2020, the growth of vegetation cover during that period was relatively good. This study was conducted in arid and semi-arid regions of Central Asia and demonstrates the impact of climate change on changes in vegetation cover. [ABSTRACT FROM AUTHOR]

The acceleration of climate warming has led to a faster solid–liquid water cycle and a decrease in solid water storage in cold regions of the Earth. Although snowfall is the most critical input for the cryosphere, the phenology of snowfall, or potential snowfall phenology (PSP), has not been thoroughly studied, and there is a lack of indicators for PSP. For this reason, we have proposed three innovative indicators, namely, the start of potential snowfall season (SPSS), the end of potential snowfall season (EPSS), and the length of potential snowfall season (LPSS), to characterize the PSP. We then explored the spatial–temporal variation in all three PSP indicators in the past, present, and future across the Chinese Tianshan mountainous region (CTMR) based on the observed daily air temperature from 26 meteorological stations during 1961–2017/2020 combined with data from 14 models from CMIP6 (Phase 6 of the Coupled Model Intercomparison Project) under four different scenarios (SSP126, SSP245, SSP370, and SSP585, where SSP represents Shared Socioeconomic Pathway) during 2021–2100. The study showed that the SPSS, EPSS, and LPSS indicators could accurately describe the PSP characteristics across the study area. In the past and present, the potential snowfall season started on 2 November, ended on 18 March, and lasted for about 4.5 months across the CTMR on average. During 1961–2017/2020, the rate of advancing the EPSS (-1.6 d per decade) was faster than that of postponing the SPSS (1.2 d per decade). It was also found that there was a significant delay in the starting time (2–13 d) and advancement in the ending time (1–13 d), respectively, resulting in a reduction of 3–26 d for the LPSS. The potential snowfall season started earlier, ended later, and lasted longer in the north and center compared with the south. Similarly, the SPSS, EPSS, and LPSS indicators are also expected to vary under the four emission scenarios during 2021–2100. Under the highest emission scenario, SSP585, the starting time is expected to be postponed by up to 41 d, while the ending time is expected to be advanced by up to 23 d across the study area. This change is expected to reduce the length of the potential snowfall season by up to 61 d (about 2 months), and the length of the potential snowfall season will only last 2.5 months in the 2100s under the SSP585 scenario. The length of the potential snowfall season in the west and southwest of the CTMR will be compressed by more days due to a more delayed starting time and an advanced ending time under all four scenarios. This suggests that, with constant snowfall intensity, annual total snowfall may decrease, including the amount and frequency, leading to a reduction in snow cover or mass, which will ultimately contribute to more rapid warming through the lower reflectivity to solar radiation. This research provides new insights into capturing the potential snowfall phenology in the alpine region and can be easily extended to other snow-dominated areas worldwide. It can also help inform snowfall monitoring and early warning for solid water resources. [ABSTRACT FROM AUTHOR]

The present study investigated seasonal and spatial characteristics of the trends in surface air temperature (SAT) over Central Asia during 1979–2018 and the relative contributions of dynamic and thermodynamic effects using a dynamical adjustment methodology. Regional averaged total SAT shows the largest rising rate in spring and its trend is not obvious in winter. The thermodynamically effect induces a widespread warming trend in most of Central Asia in all the four seasons. The dynamically induced SAT trends exhibit obvious seasonal and regional differences. Both dynamic and thermodynamic effects play a crucial role in the total SAT increasing trend in spring, the thermodynamic effect is predominantly responsible for SAT warming and the dynamic effect has a secondary contribution in summer, the rising temperature in autumn is attributed to the thermodynamic effect and the dynamic effect has a negative but insignificant contribution, and the total SAT trend in winter is small due to opposite contributions of thermodynamic and dynamic effects. Further analysis revealed that the changes in the Scandinavia pattern (SCAND) during 1979–2018 are likely the cause of dynamically induced temperature trends in spring, autumn and winter. The dynamical component of summer SAT trends over eastern Central Asia is contributed by the interdecadal transition of the Atlantic multidecadal oscillation (AMO) and Pacific decadal oscillation (PDO). Those climate modes contribute to SAT variations via their effects on wind-induced temperature advection and surface heat fluxes. [ABSTRACT FROM AUTHOR]

Transboundary rivers are often the cause of water-related international disputes. One example is the Amu Darya River, with a catchment area of 470 000 km2, which passes through five countries and provides water resources for 89 million people. Intensified human activities and climate change in this region have altered hydrological processes and led to water-related conflicts and ecosystem degradation. Understanding streamflow composition and quantifying the change impacts on streamflow in the Amu Darya basin (ADB) are imperative to water resources management. Here, a degree-day glacier-melt scheme coupled offline with the Variable Infiltration Capacity hydrological model (VIC-glacier), forced by daily precipitation, maximum and minimum air temperature, and wind speed, is used to examine streamflow composition and changes during 1953–2019. Results show large differences in streamflow composition among the tributaries. There is a decrease in the snowmelt component (−260.8 m3 s−1) and rainfall component (−30.1 m3 s−1) at Kerki but an increase in the glacier melt component (160.0 m3 s−1) during drought years. In contrast, there is an increase in the snowmelt component (378.6 m3 s−1) and rainfall component (12.0 m3 s−1) but a decrease in the glacier melt component (−201.8 m3 s−1) during wet years. Using the VIC-glacier and climate elasticity approach, impacts of human activities and climate change on streamflow at Kerki and Kiziljar during 1956–2015 are quantified. Both methods agree and show a dominant role played by human activities in streamflow reduction, with contributions ranging 103.2%–122.1%; however, the contribution of climate change ranges from −22.1% to −3.2%. [ABSTRACT FROM AUTHOR]

Many studies have examined the influence of global climate change and regional human activities on the climate of arid Central Asia, but their separate contributions have rarely been reported due to lack of a comprehensive description of regional human activities, especially the irrigation process, in the model. In this study, we conducted two sets of 40‐year continuous simulations with and without human activities to distinguish the effects of regional human activities and global climate change on the surface air temperature (T2), humidity (Q2) and precipitation of a typical mountain‐oasis‐desert system in northern Tianshan by using a modified WRF‐Noah model with irrigation processes. The results indicated that the annual average T2, Q2 and convective precipitation during the past 40 years increased by 0.393°C, 0.063 g/kg and 0.014 mm/d, respectively, and the annual average large‐scale precipitation and total annual average precipitation decreased by approximately −0.017 and −0.003 mm/d, respectively. Regional human activities contributed 52.63% and 50.38% of the change in large‐scale precipitation and total precipitation, respectively, while global climate change accounted for more than 80% of the change in temperature and humidity. Among the human activities, irrigation had the largest impact on T2/Q2 over the local irrigation region and on precipitation in the upstream Tianshan mountainous area. However, for the whole region, the increase in the green vegetation fraction was the core factor that impacted the regional climate. Our results can deepen the understanding of the attribution and mechanism of climate change and provide water and heat change references for other mountain‐oasis‐desert systems in arid endorheic regions. Plain Language Summary: We counted the separate contributions of global climate change and regional human activities on the surface air temperature (T2), humidity (Q2) and precipitation of arid Central Asia by difference of two sets of 40‐year continuous simulations with and without human activities. The results indicated that regional human activities contributed 52.63% and 50.38% of the change in large‐scale precipitation and total precipitation, respectively, while global climate change accounted for more than 80% of the change in temperature and humidity. Among the human activities, irrigation had the largest impact on T2/Q2 over the local irrigation region and on precipitation in the upstream Tianshan mountainous area. But the vegetation greening was main reason for the changes of regional climate for the whole region. Our results can deepen the understanding of the attribution and mechanism of climate change and provide water and heat change references for other mountain‐oasis‐desert systems in arid endorheic regions. Key Points: The attribution and mechanism of regional climate change in a typical mountain‐oasis‐desert system of arid Central Asia were exploredGlobal climate change dominated regional temperature change while regional human activities dominated regional precipitation changeThe increase in the green vegetation fraction was the core factor that impacted regional climate [ABSTRACT FROM AUTHOR]

The current work examines the impact of the snow cover extent (SCE) of the Tibetan Plateau (TP) on the interannual variation in the summer (June-July-August) surface air temperature (SAT) over Central Asia (CA) (SAT_CA) during the 1979–2019 period. The leading mode of the summer SAT_CA features a same-sign temperature anomalies in CA and explains 62% of the total variance in SAT_CA. The atmospheric circulation associated with a warming SAT_CA is characterized by a pronounced high-pressure system dominating CA. The high-pressure system is accompanied by warm advection as well as descending motion over CA, favoring the warming of the SAT_CA. Analysis shows that the interannual variation in the summer SAT_CA is significantly positively correlated with the April SCE over the central-eastern TP. In April, higher than normal SCE over the central-eastern TP has a pronounced cooling effect on the column of the atmosphere above the TP and can persist until the following early summer. Negative and positive height anomalies appear above and to the west of the TP. In the following months, the perturbation forcing generated by the TP SCE anomalies lies near the western center of the Asian subtropical westerly jet (SWJ), which promotes atmospheric waves in the zonal direction guided by the Asian SWJ. Associated with this atmospheric wave, in the following summer, a significant high-pressure system dominates CA, which is a favorable condition for a warm summer SAT_CA. [ABSTRACT FROM AUTHOR]

The land surface scheme (LSS) plays a very important role in the forecast of surface meteorological elements in the Central Asia arid region. Therefore, two LSSs viz. Noah and Noah-MP were evaluated over the Central Asia arid region in January and July 2017 using the Weather Research and Forecasting (WRF) model at a 3-km horizontal grid resolution. The objective was to assess the performance of WRF LSSs by calculated the mean error (ME) and the root mean squared error (RMSE) of simulated hourly meteorological elements, such as 2-m air temperature, 10-m wind speed, soil temperature, soil moisture at 5 and 25 cm thickness, and surface soil heat flux at 5 cm thickness. The results showed that, compared to Noah, Noah-MP modeled less surface sensible heat flux in the northern Xinjiang (15~20 W∙m−2) and surface latent heat flux in most areas of Xinjiang (<10 W∙m−2) in January, and mainly generated less sensible heat flux in most areas of north Xinjiang and the mountainous regions of southern Xinjiang (≤20 W·m−2) which on the contrary, generated more surface latent heat flux in most parts of Xinjiang (15~20 W·m−2) in July. Meanwhile, the surface soil heat flux generated from Noah-MP was closer to the observations at Hongliuhe and Kelameili stations in January, the ME increased by 17.5% and reduced by 80.7%, respectively, the RMSE decreased by 44.4% and 61.7%, respectively, and closer to the observations at Xiaotang station in July, the ME and RMSE reduced by 19.1% and 20.5%, respectively. Compared to Noah, Noah-MP improved the overall simulation of soil temperature and soil moisture over the northern and eastern Xinjiang (at 10 cm thickness), the ME and RMSE of simulated soil temperature reduced by 85.0% and 13.4% in January, decreased by 78.6% and increased by 6.2% in July, respectively, and the ME and RMSE of simulated soil moisture reduced by 67.2% and 14.9% in January, reduced by 33.3% and 2.8% in July, respectively. Compared to Noah, Noah-MP's results were lowered for the simulated 10-m wind speed and 2-m air temperature, especially the simulated 2-m air temperature over the cold climate regions of northern Xinjiang, was improved significantly, the ME and RMSE of simulated 10-m wind speed reduced by 0.8% and 4.9% in January, decreased by 6.7% and 2.8% in July, respectively, the ME and RMSE of simulated 2-m air temperature reduced by 2.8% and 1.0% in July, respectively. This study demonstrated the advantage of coupled Noah-MP over the Central Asia arid region, providing the basis for WRF/Noah-MP in future operational applications in the Central Asia arid region. [ABSTRACT FROM AUTHOR]

Drought has become a global concern, and timely and accurate drought monitoring has an important guiding significance for the regional ecological security, economic development, and agricultural production of countries along the "New Silk Road Economic Belt" in the context of global warming. Since natural disasters have occurred frequently around the world in recent years, the drought has also posed a great threat to the global ecological environment, particularly to the long-term social and economic development of Central Asia and the surrounding countries. In this study, a Temperature Vegetation Dryness Index (TVDI) model was established using the MODIS Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI) in Central Asia from 2001 to 2020. Based on trend analysis, MK test, and geographic detectors, the spatial and temporal variations, of drought and drought changing patterns in Central Asia in the last 20 years, the drought evolution pattern and the influence of different factors (temperature, mean annual precipitation, land use type, population density, DEM, slope, aspect) on TVDI were also investigated. The results show that: 1) There was an obvious regional pattern in the spatial distribution of TVDI in the study area, which were mainly characterized by regional and local droughts. The frequency and degree of droughts in the southwestern part of Central Asia are than those in the northeastern part, with a decreasing trend from the southwest to the northeast. For all the study area, 66% of the area showed a significantly increasing trend of drought (P<0.05), whereas, 34% of the area showed a significant decreasing trend of drought (P<0.05), indicating a pattern of "dry in the north and wet in the south". Overall, Central Asia shows an increasing trend of aridity, with the most severest drought in the northwestern part of Kazakhstan. 2) The degree annual of drought slightly increased over the past 20 years, with the severest drought occurred in 2012. There was a significantly different spatial distribution of TVDI, which with a clear seasonal change. The drought degree was ranked as follows: summer>spring>autumn. 3) The single-factor detection results showed that the contribution of the influencing factors to drought was ranked as follows: temperature > DEM > slope > precipitation > land use type, with the controlling factors of temperature and DEM for the drought (all q values were greater than 0.45). The multi-factor analysis showed the two-factor enhancement and non-linear enhancement, with t major contribution from the four combinations, e.g., — temperature and DEM, temperature and slope, temperature and land use, and temperature and precipitation. Under the background of global climate warming and increasing human activities (vegetation deterioration, urbanization and construction, cultivation, overgrazing, industrial pollution, etc.), the air temperature gradually increased and the precipitation decreased in Central Asia over the past 20 years. These changes led to vegetation degradation, which in turn resulted in ecological degradation and increased drought degrees. This finding can provide a scientific reference for the decision-making on the drought prevention and control, particularly for the ecological risks and geo-security impacts. [ABSTRACT FROM AUTHOR]

Determining what caused the global Last Glaciation and last glacial termination, despite opposing orbital summer insolation signatures between the polar hemispheres, remains a puzzle of paleoclimatology. This problem can be addressed by comparing chronologies of glaciation from different latitudes and different climatic regimes in both hemispheres. Here, we present a 10Be surface‐exposure chronology of glacial landforms constructed during and since the local Last Glaciation in the continental environment of Central Asia in the high Mongolian Altai (49°N, 88°E). Four belts of lateral moraines document maximal phases of the former Khoton glacier at 35,440 ± 980 years ago, 23,430 ± 850 years ago, 20,780 ± 610 years ago, and 19,520 ± 550 years ago. Our chronology indicates that deglaciation from these maximal positions began as early as 18,810 ± 510 years ago, was well underway by 17,680 ± 510 years ago, and was nearly completed by 16,040 ± 490 years ago. Overall, our chronology shows that glaciation in western Mongolia overlapped with the global Last Glacial Maximum and that extensive recession from glacial‐to‐interglacial limits took place early in the last glacial termination during Heinrich Stadial 1. Khoton Nuur deglaciation led the demise of large Northern Hemisphere ice sheets and increases in radiative forcing agents by several millennia. We suggest that this rapid switch in the mode of glaciation implies the involvement of an additional climatic factor that could have produced locally rapid warming and deglaciation ∼18,800–16,000 years ago. Plain Language Summary: Leading hypotheses for the causes of ice ages and their terminations involve important roles for ice‐sheet feedbacks and greenhouse gases in driving global glacial cycles. Mountain glacier length records afford valuable insights into past climate conditions because mountain glaciers are highly sensitive to the effects of atmospheric temperature changes. Here, we use glacial geology and surface‐exposure dating to chart the ice‐age history of a mountain glacier system located in the Mongolian Altai of Central Asia. Results from the Altai show that the ancient glacier achieved ice‐age maxima at the same time as glaciers in midlatitude Southern Alps of New Zealand on the opposite side of the world. Likewise, rapid and extensive glacier recession took place in both locations between ∼18,000 and 16,000 years ago—signaling an early and rapid termination of ice age conditions in these two bipolar midlatitude locations. The rapid climate warming that drove glacier retreat in western Mongolia led to the demise of the huge Northern Hemisphere ice sheets by several millennia and even outpaced the rise of atmospheric CO2. Any solution to the ice‐age climate puzzle must account for synchrony of glacial maxima as well as coeval rapid deglaciation in Central Asia and the Southern Hemisphere. Key Points: 10Be dating of moraines indicates at least four glacier maxima in the Mongolian Altai during the Last GlaciationThe timing of Mongolian glacier maxima overlapped with the global Last Glacial MaximumDeglaciation began as early as ∼18.8 kyrs ago and interglacial conditions were achieved by ∼16.0 kyrs ago [ABSTRACT FROM AUTHOR]

Given the various altitudes of the Vakhsh River Basin (VRB) in Central Asia, global warming has significant implications for water resources and environmental changes as most snow surfaces and glaciers are situated above 3000 m above sea level in the catchment. The aim of this study is to use observational climate data to evaluate the response of low- and high-altitude areas in the VRB to climate warming through assessment of annual mean air temperature and annual mean precipitation trends and magnitudinal variability. The long-term hydro-climatic variables are evaluated employing the original Mann-Kendall test, modified Mann-Kendall (MMK) test, and Sen's slope estimator. The general pattern of the annual mean air temperature reveals continuous warming in the catchment over the 1934–1995 and 1960–2015 time periods. The MMK test result shows a statistically significant increase in the annual mean air temperature trend in the low elevation stations during the 1960 to 2015 time period. Similarly, at the alpine N.P. Gorbunov (Fedchenko Glacier) climate station at 4162 m, the annul mean temperature exhibits a statistically significant increasing trend during the 1934–1995 time period with a Kendall statistic (Z) of 7.266 and a slope value of 0.010. The results of the MMK test reveal a statistically significant decrease in the annual mean precipitation trend solely in one station with a Z of –2.385 and a slope value and p-value of –1.273 and 0.017, respectively. However, the results of the MMK test exhibit a statistically significant increasing trend in annual mean precipitation in the high-elevation stations such as Lyakhsh and N.P. Gorbunov with Z values of 6.367 and 6.818, slope values of 1.530 and 8.824, and p-values of 0.000 and 0.000, respectively. These findings show pronounced climatic change in the VRB. The long-term data analysis indicates changes in air temperature and precipitation conditions; thereby, the results provide guidance for planning new national mitigation and adaptation activities. [ABSTRACT FROM AUTHOR]

The recent summer surface air temperature (SAT) changes over densely populated Eurasia exhibit a non‐uniform pattern with amplified warming over Europe and East Asia (EA) but weak warming over Central Asia (CA), forming a wave train‐like structure. However, the key factors that determine this non‐uniform warming pattern remain unclear. By analyzing observations and model simulations, here, we show that more than half of the SAT multidecadal variations from 1950 to 2014 over Europe‐west Asia and EA may have resulted from external forcing, rather than from internal variability in the Atlantic as previously thought. In contrast, the recent SAT over CA is influenced mainly by internal variations in the Atlantic and Pacific oceans. Large ensemble model simulations suggest that the forced SAT multidecadal variations over Eurasia are mainly caused by changes in greenhouse gases and aerosols. Our findings provide strong evidence for major impacts of external forcing on multidecadal climate variations over Eurasia. Plain Language Summary: Previous studies have documented non‐uniform decadal warming rates in summer since the mid‐1990s over densely populated Eurasia, with amplified warming over Europe and East Asia (EA) but weak warming over Central Asia. This unique tripole warming pattern and its cause have attracted considerable attention. It may arise from internal variability (IV; e.g., Atlantic Multidecadal Oscillation [AMO]) and/or external forcing. Furthermore, it was found that the recent AMO resulted from both IV and decadal changes in aerosols. Thus, the relative contributions of IV and external forcing to the recent Eurasian warming pattern remain unclear. Here we show that the surface air temperature multidecadal variations since 1950 over Eurasia are caused by both IV and external forcing, with more than half of the variations over Europe‐west Asia and EA resulted from external forcing (i.e., greenhouse gases [GHGs] and aerosols), in contrast to the previous notion that the non‐uniform warming is mainly originated from the Atlantic Ocean. Looking ahead into the upcoming decades, aerosols will continue to decrease, whereas the AMO will likely be in its positive phase. These changes, together with continued increases in GHGs, will accelerate warming trends over Eurasia and further exacerbate summer heat waves. Key Points: More than half of the multidecadal surface air temperature (SAT) variations from 1950 to 2014 over Europe‐west Asia and East Asia resulted from external forcingThe forced SAT multidecadal variations over Eurasia are mainly caused by changes in greenhouse gases and aerosolsOur study helps reconcile human and natural drivers of the tripole pattern of multidecadal summer temperature variations over Eurasia [ABSTRACT FROM AUTHOR]

This study finds a significantly decreasing (increasing) trend (1979–2018) of sea level pressure (SLP) over coastal East Asia (far North Pacific) during May and June, which resembles the negative (positive) Pacific Decadal Oscillation (PDO) (North Pacific Oscillation, NPO)‐like pattern. Thus, we examine May composite differences between early and late Indian summer monsoon (ISM) onset years. Sea surface temperature (SST) differences show that early (late) ISM onset is accompanied by a negative (positive) PDO‐like state. Whereas, in SLP, an intense low pressure over northwestern India, the Arabian Sea to Southeast Asia (far North Pacific, East Asia) is associated with the early (late) onset. During the early onset, warm surface air temperature (SAT) anomalies over southeast Russia propagate towards Central Asia to the Middle East and the northwest Indian subcontinent, strengthening the land‐sea thermal contrast, which subsequently strengthens the monsoon low. We thus show how the positive NPO, negative PDO, and high spring Bering Sea ice link with the SAT anomalies. In the early onset, more wave packets generated in response to these North Pacific anomalies propagate towards the Atlantic and European region, reaching and converging over the northwest Indian subcontinent. The warm surface anomalies possibly draw eastward‐propagating waves towards northwest India, thus intensifying the monsoon low there. Meanwhile, in the CAM5 PDO simulation, we observe a similar pattern of atmospheric responses, where warm SAT anomalies associated with stationary Rossby wave trains propagate from the North Pacific towards the North Atlantic to Central Asia and the northwest Indian subcontinent, strengthening the monsoon low. Terefore, our study highlights the crucial role of the North Pacific anomalies in modulating the ISM onset processes via atmospheric pathways. [ABSTRACT FROM AUTHOR]

In this study, we investigate the dominant modes of surface air temperature variations of the cold season (from November through to the next March) and the warm season (from May to September) over Central Asia, and their associations with large-scale climate patterns for the period of 1979–2016. The first two modes of the cold season surface air temperature (CSAT) over Central Asia, obtained by empirical orthogonal function (EOF) analysis, feature the monopole structure and the north-south dipole pattern, respectively. For the warm season surface air temperature (WSAT), the leading two EOF modes are characterized by the homogenous structure and the northwest-southeast seesaw pattern, respectively. Further analysis indicates that the large-scale atmospheric circulation anomalies play key roles in the CSAT and WSAT variations over Central Asia. The CSAT variation over Central Asia is closely related to the Scandinavia pattern (SCAND) and the Arctic Oscillation (AO), while the WSAT variation is tightly tied to the East Atlantic/Western Russia pattern (EAWR) and the North Atlantic Oscillation (NAO). These large-scale climate patterns tend to cause the CSAT and WSAT anomalies over Central Asia via their effects on regional geopotential heights, warming advections, and other processes. Positive geopotential height anomalies and increased downward solar radiations generally favor positive SAT anomalies over Central Asia. Moreover, the warm advections are also conducive to the formation of positive SAT anomalies over Central Asia. Our findings are expected to facilitate the improvement of understanding and predicting the CSAT and WSAT variations over Central Asia. [ABSTRACT FROM AUTHOR]

The green alga Pediastrum is an ecologically significant component of freshwater ecosystems, but its potential as an independent proxy for quantitative paleoenvironmental reconstruction is relatively unexplored. Here we use multivariate statistical analysis to explore the relationship between the Pediastrum composition of lake surface sediments and environmental variables. The findings highlight the mean growing season air temperature between March and October (T Mar-Oct) as the most important factor determining the Pediastrum composition. We then establish the first transfer function between the Pediastrum taxa and T Mar-Oct , which enables us to provide a quantitative temperature reconstruction for the past ∼8.2 kyr based on sedimentary subfossil Pediastrum records from Bosten Lake in Xinjiang, China. Our findings reveal an exceptionally warm climate during ∼4.8–3.6 kyr, with temperatures ∼4 °C higher compared to those during ∼8.2–4.8 kyr. This unusually warm climate is verified by the carbonate clumped isotopes record of the same core and other paleoclimate records. These findings contribute to our understanding of past temperature changes in Central Asia and provide a basis for future research on long-term lake ecosystem dynamics under past climatic warming. • We developed the first Pediastrum -temperature transfer function. • Paleotemperature was reconstructed based on the subfossil Pediastrum record from Bosten Lake (China). • An unusually warm climate occurred in Central Asia during 4.8–3.6 kyr. [ABSTRACT FROM AUTHOR]

Lakes in Central Asia, characterized largely by a semiarid climate and delicate ecosystems, are quite sensitive and vulnerable to climate change but remain less exploited, due mostly to a lack of in-situ measurements. Lake ice phenology is an essential climate variable identified by the Global Climate Observation System. To overcome the overestimation of clouds by the MODIS cloud mask, we developed and distributed a two-step Random Forest algorithm based on MODIS data on the Google Earth Engine. This algorithm first distinguishes cloudy pixels from non-cloudy pixels, and then ice pixels are discriminated from non-cloudy pixels using additional thermal infrared information. We validated the algorithm by implementing it over several boreal lakes with in-situ records in North America and compared our results with existing lake ice phenology datasets. We subsequently retrieved lake ice phenology for 20 large lakes (> 100 km2) in Central Asia from 2001 to 2021 and examined trends in lake ice phenology over this period. On average, lakes in Central Asia underwent later freezing at 0.13 d/yr, earlier thawing at 0.32 d/yr, and shorter ice duration at 0.45 d/yr, with over half of the lakes witnessing significant trends in at least one ice phenology indicator. To evaluate the impact of meteorological factors on lake ice phenology, we built a linear mixed model that predicts ice phenology using meteorological variables from ERA5. Daily mean air temperature dominates ice phenology, with mean air temperature during October to June in the following year explaining approximately 35% of the variance of the duration between freezing and thawing for each lake. Our study offers a comprehensive analysis of lake ice phenology in Central Asia under climate change. • A two-step ice classification approach addresses overestimation of MODIS cloud mask. • A complete and consistent 21-year ice phenology dataset for 20 Central Asia lakes. • Over half of the lakes have significant trends in at least one phenology indicator. • Mean air temperature explains approximately 35% of the variance of ice duration. [ABSTRACT FROM AUTHOR]

The precipitation variability is subject to impacts of both ocean and land surface condition changes. The present study investigates the role of land surface condition in the interannual variation of the early rainy season (May–June) precipitation over the Indochina Peninsula. A precursory signal is identified in surface air temperature (SAT) during March–April over central Asia after the late 1970s. The air temperature anomalies extend to middle troposphere and persist to early summer (May–June) and modulate the land‐sea thermal contrast and lower‐level and upper‐level winds over the North Indian Ocean and thus affect the early rainy season precipitation over the Indochina Peninsula. The maintenance of SAT anomalies over central Asia is related to that of surface heat flux anomalies that in turn is attributed to the persisting atmospheric wind anomalies. The precursory signal is weak before the late 1970s due to the lack of persisting atmospheric wind anomalies. The interdecadal change in the persistence of central Asian SAT anomalies is associated with a difference in the distribution of the North Atlantic sea surface temperature (SST) anomalies. After the late 1970s, the North Atlantic SST anomalies with a southwest‐northeast distribution excite a wave train that extends from the North Atlantic to central Asia during May–June. Before the late 1970s, the wave train associated the North Atlantic SST anomalies with a south–north distribution is confined to the North Atlantic region. [ABSTRACT FROM AUTHOR]

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The Irtysh River is the main water resource of Eastern Kazakhstan and its upper basin is severely affected by spring floods each year, primarily as a result of snowmelt. Knowledge of the large‐scale processes that influence the timing of these snow‐induced floods is currently lacking, but critical for the management of water resources in the area. In this study, we evaluated the variability in winter–spring snow cover in five major sub‐basins of the Upper Irtysh basin between 2000 and 2017 as a possible explanatory factor of spring flood events, assessing the time of peak snow cover depletion rate and snow cover disappearance from the moderate‐resolution imaging spectroradiometer (MODIS) MOD10A2 data set. We found that on average, peak snow cover retreat occurs between 22 March and 14 April depending on the basin, with large interannual variations but no clear trend over the MODIS period, while our comparative analysis of longer‐term snow cover extent from the National Oceanic and Atmospheric Administration Climate Data Record data set suggests a shift to earlier snow cover disappearance since the 1970s. In contrast, the annual peak snow cover depletion rate displays a weak increasing trend over the study period and exceeded 5,900 km2/day in 2017. The timing of snow disappearance in spring shows significant correlations of up to 0.82 for the largest basin with winter indices of the Arctic Oscillation (AO) over the region. The primary driver is the impact of the large‐scale pressure anomalies upon the mean spring (MAM) air temperatures and resultant timing of snow cover disappearance, particularly at elevations 500–2,000 m above sea level. This suggests a lagged effect of this atmospheric circulation pattern in spring snow cover retreat. The winter AO index could therefore be incorporated into long‐term runoff forecasts for the Irtysh. Our approach is easily transferable to other similar catchments and could support flood management strategies in Kazakhstan and other countries. [ABSTRACT FROM AUTHOR]

In this study, the climate changes over Arid Central Asia (ACA) during the mid‐Holocene (approximately 6,000 calendar years ago, MH) and the Last Glacial Maximum (approximately 21,000 calendar years ago, LGM) were investigated using multimodel simulations derived from the Paleoclimate Modelling Intercomparison Project Phase 3 (PMIP3). During the MH, the multimodel median (MMM) shows that in the core region of ACA, the regionally averaged annual surface air temperature (SAT) decreases by 0.13°C and annual precipitation decreases by 3.45%, compared with the preindustrial (PI) climate. The MMM of the SAT increases by 1.67/0.13°C in summer/autumn, whereas it decreases by 1.23/1.11°C in spring/winter. The amplitude of the seasonal cycles of the SAT increases over ACA due to different MH orbital parameters. For precipitation, the regionally averaged MMM decreases by 5.77%/5.69%/0.39%/5.24% in spring/summer/autumn/winter, respectively. Based on the analysis of the aridity index (AI), compared with the PI, a drier climate appears in southern Central Asia and western Xinjiang due to decreasing precipitation. During the LGM, the MMM shows that the regionally averaged SAT decreases by 5.04/4.36/4.70/5.12/5.88°C and precipitation decreases by 27.78%/28.16%/31.56%/27.74%/23.29% annually and in the spring, summer, autumn, and winter, respectively. Robust drying occurs throughout almost the whole core area. Decreasing precipitation plays a dominant role in shaping the drier conditions, whereas strong cooling plays a secondary but opposite role. In response to the LGM external forcings, over Central Asia and Xinjiang, the seasonal cycle of precipitation has a smaller amplitude compared with that under the PI climate. In the model‐data comparison, the simulated MH moisture changes over ACA are to some extent consistent with the reconstructions, further confirming that drier conditions occurred during that period than during the PI. [ABSTRACT FROM AUTHOR]

Located in the intermediate zone between the taiga forests in Siberian Plain and the deserts in Central Asia, the Altai Mountains are of scientific concern about Holocene climate change in the past decades. However, researches about modern climate changes are relatively scarce in the Altai Mountains. In this study, temporal- spatial changes of air temperature and precipitation were investigated systematically in the Altai Mountains based on fifteen meteorological records over the period of 1970–2015. The Altai Mountains experienced a rapid warming trend with a rate of 0.41°C/decade and an insignificantly wetting trend at a rate of 4.82 mm/decade during 1970–2015. The magnitude of temperature trend was negatively correlated with elevation in cold season (spring and winter), whereas that was positively correlated with elevation in warm season (summer and autumn). The cyclonic anomalies to the northwest and an anticyclonic anomalies to the southeast blocked the southward cold air and then provided the favorable condition for an increasing precipitation via the southwesternly wind in the Altai Mountains. [ABSTRACT FROM AUTHOR]

The vertical distribution of vegetation types along an elevational gradient in mountain areas largely depends on the elevational changes in air temperature and humidity. In this study, we presented the seasonal and diurnal variations in the elevational gradients of air temperature and humidity on the southern and northern slopes in the middle Tianshan Mountain Range using data collected throughout the year via HOBO data loggers. The measurements were conducted at 12 different elevations from 1548 to 3277 m from September 2004 to August 2005. The results showed that the annual mean air temperature decreased along the elevational gradients with temperature lapse rates of (0.71±0.20)°C/100 m and (0.59±0.05)°C/100 m on the northern and southern slopes, respectively. The annual mean absolute humidity significantly decreased with increasing elevation on the northern slope but showed no significant trend on the southern slope. The annual mean relative humidity did not show a significant trend on the northern slope but increased with increasing elevation on the southern slope. The mean air temperature lapse rate exhibited significant seasonal variation, which is steeper in summer and shallower in winter, and this value varied between 0.37°C/100 m and 0.75°C/100 m on the southern slope and between 0.30°C/100 m and 1.02°C/100 m on the northern slope. The mean absolute and relative humidity also exhibited significant seasonal variations on both slopes, with the maximum occurring in summer and the minimum occurring in winter or spring. The monthly diurnal range of air temperature on both slopes was higher in spring than in winter. The annual range of air temperature on the southern slope was higher than that on the northern slope. Our results suggest that significant spatiotemporal variations in humidity and temperature lapse rate are useful when analyzing the relationships between species range sizes and climate in mountain areas. [ABSTRACT FROM AUTHOR]

The Selenge basin contributes approximately 50% of the total inflow into Lake Baikal and is thus of high significance for the regional hydrological regime. Our study was conducted in the upper reaches of the basin, where the Selenge river and its tributaries flow through the Mongolian forest-steppe. Monthly and maximum runoff, precipitation, and air temperature data from 12 gauging stations collected between 1978 and 2015 were analyzed to characterize the hydrological regime response to climate change. Concomitant with rising temperatures and increased potential evaporation, river runoff in the Mongolian part of the Selenge basin has decreased from the first interval (1978–1995) of our study period compared with the consecutive interval from 1996 to 2015. The decrease in runoff throughout the study area was most likely caused by an increase in potential evapotranspiration (and not reduced precipitation or land use changes) for both summer rainfall- and snowmelt-dominated rivers. Annual maximum runoff has also strongly decreased suggesting that reduced flooding is a contemporary threat for Mongolia's riverine ecosystems, probably causing the replacement of wetland and mesic habitats. [ABSTRACT FROM AUTHOR]

The patterns of snow accumulation and ablation were largely influenced by climate change. Current studies on the snow cover characteristics were mainly based on remote sensing retrievals in the Tianshan Mountains, however, they suffered from short record observations. This study quantified the climatology and variations in snowpack patterns related to snow depth from 1961 to 2015 at 48 meteorological stations across the Tianshan Mountains, spanning the elevations from 312 to 3543 m asl. Moreover, this study analyzed the contribution of the air temperature and precipitation during snow accumulation season to snow onset day, as well as the contribution of effective daily >0 °C accumulative temperature and snow depth maximum during snowmelt season to snow end day, respectively. The results showed that the snow depth maximum and snow cover days exhibited similar distribution, i.e., decreasing pattern in a northwest-to-southeast direction. Significant trend toward a shortened snow cover days was identified by 2.7 days decade−1 at the high altitude of the north slope, although it exhibited a non-significant increasing trend in low-middle altitude regions. A higher snow depth maximum was observed mainly in the north slope by 2.08 cm decade−1 without any significant elevation-dependency. There existed a positive sensitivity of snow onset day to air temperature with 0.64 days °C−1 during snow accumulation season, but an opposite sensitivity of snow end day to effective accumulative temperature with 0.82 days °C−1 during snow melt season. In addition, a positive sensitivity of snow end day to snow depth maximum was revealed with 1.84 days cm−1 during snowmelt season. • Significant trend toward a shortened snow cover days was identified by 2.7 days decade−1 at the high altitude of the north slope during 1961–2015 period. • A higher snow depth maximum was observed mainly in the north slope by 2.08 cm decade−1 during 1961–2015 period. • Opposite sensitivities were found between snowpack and temperature during different snow seasons. [ABSTRACT FROM AUTHOR]

Central Asia witnessed progressive aridification during the Miocene, commonly related to mountain uplift, the Paratethys retreat and global climate cooling. However, the formation of Miocene lakes in Central Asia seems to oppose drier conditions, suggesting that the precise timing, extent and forcing of the aridification is still not well constrained. This study presents a facies model for the alluvial–lacustrine part of the Middle to Late Miocene of the Ili Basin, obtained from two successions. The model enables the semi‐quantitative assessment of regional water level and salinity, and characterizes the control of water level on evaporite formation and diagenesis. Both the proximal Kendyrlisai and the distal Aktau successions show an overall increase in water availability from dry mudflat deposits to lacustrine sedimentation with a transitional playa phase. Increasing evaporation rates outpaced the water supply and caused groundwater salinization. Subsequent lake expansion coincided with a basin‐wide desalinization and required a shift to a positive water budget. A climatic control of the hydrological evolution is inferred due to abrupt salinization and a minor tectonic influence. The long‐term water accumulation is probably related to the hydrological closure of the basin in the early Middle Miocene (15·3 Ma). Starting at 14·3 Ma, the step‐wise salinization occurred simultaneously with the global cooling of the Miocene Climate Transition. The Miocene Climate Transition led to extreme aridity in the Ili Basin, highlighted by the early diagenetic formation of displacive anhydrite in the basin centre. The expansion of the freshwater lake (12·7 to 11·5 Ma) was possibly promoted by lower evaporation rates due to decreasing air temperatures in the Ili Basin after the Miocene Climate Transition. The extreme aridity in the Ili Basin is interpreted as a continental counterpart to the Badenian Salinity Crisis in the Central Paratethys. This emphasizes the role of atmospheric forcing on evaporite sedimentation across Eurasia during the Middle Miocene. [ABSTRACT FROM AUTHOR]

In the spring of 2022, a stratospheric final warming (SFW) event occurred on March 19 at 10 hPa in the Northern Hemisphere, ranking the third earliest SFW event during 1979–2022. Meanwhile, Central Asia recorded the highest surface air temperature (SAT) in the ensuing April in recent 44 years. Based on the fifth generation reanalysis data from European Centre for Medium-Range Weather Forecasts, this study reports an intimate linkage between the SFW onset and the extremely high SAT in Central Asia in April 2022. Specifically, after the SFW onset, positive geopotential height anomalies in the stratospheric polar region persist for more than a month, which propagate downward to the troposphere in about one week, resulting in a negative phase of the Northern Annular Mode (NAM) in the upper troposphere during the period from late March to mid-April. Such a negative NAM tends to excite an anomalous Rossby wave train propagating southeastward from the North Atlantic to Central Asia, causing an anomalous high over Central Asia in the middle and upper troposphere. As a result, the associated anomalies in descending motion and adiabatic heating would lead to the in situ unprecedented high SAT in April. • Unprecedented heat waves hit Central Asia in April 2022. • Such extreme heat waves are related to the preceding stratospheric final warming. • The 200-hPa Northern Annular Mode is crucial in linking SFW and the heat waves. [ABSTRACT FROM AUTHOR]

ABSTRACT: Central Asia, a typical arid and semi‐arid area, is very sensitive to climate change and is projected to undergo vigorous warming trend in future. However, it is still unclear how extreme temperatures have changed. Therefore, using the daily maximum and minimum temperatures collected from 108 stations in the study area from 1981 to 2015, the spatial–temporal variations in extreme temperature in Central Asia were analysed on both annual and seasonal scales based on 11 indices from The Expert Team on Climate Change Detection and Indices. Results show that: (1) from 1981 to 2015, all extreme temperature values exhibited increasing trends on an annual scale, but maximum temperature (TMAX) increased faster than the minimum temperature (TMIN), leading to an overall increase in the diurnal temperature range (DTR). Most of the stations in Central Asia, except for those in Xinjiang (China), exhibited an increasing trend in DTR, while most of the stations in Xinjiang (China) exhibited reversely significant decreasing trends. (2) TMAX, TMIN and DTR increased significantly, mainly during spring and summer. The trends of most warm extreme indices (warm days, warm nights and warmest days) indicate that the warming mainly occurred in spring, while most cold extreme indices (cool days, cool nights and coldest nights) exhibited significant warming trends in autumn. Dominant warming during spring and autumn can lead to longer summers, which may further accelerate the frequencies and magnitudes of temperature extremes. (3) Additionally, TMAX, TMIN and the percentile‐based warm indices all exhibited significant increasing trends from southwestern Central Asia (Turkmenistan) to eastern Central Asia (Xinjiang (China)) via the Tianshan Mountains. Although the percentile‐based cold indices showed decreasing trends in this region, they were too minor to offset the overall warming trend. With longer summers, stronger and more prolonged melting seasons were detected in the mountains of Central Asia. [ABSTRACT FROM AUTHOR]

This work investigated projected future changes in seasonal mean air temperature (°C) and precipitation (mm/day) climatology for the three periods of 2011–2040, 2041–2070, and 2071–2100, with respect to the control period of 1971–2000 for the Central Asia domain via regional climate model simulations. In order to investigate the projected changes in near future climate conditions, the Regional Climate Model, RegCM4.3.5 of the International Centre for Theoretical Physics (ICTP) was driven by two different CMIP5 global climate models. The HadGEM2-ES global climate model of the Met Office Hadley Centre and the MPI-ESM-MR global climate model of the Max Planck Institute for Meteorology were downscaled to 50 km for the Coordinated Regional Climate Downscaling Experiment (CORDEX) Region 8. We investigated the seasonal time-scale performance of RegCM4.3.5 in reproducing observed climatology over the domain of the Central Asia by using two different global climate model outputs. For the future climatology of the domain, the regional model projects relatively high warming in the warm season with a decrease in precipitation in almost all parts of the domain. A warming trend is notable, especially for the northern part of the domain during the cold season. The results of our study show that surface air temperatures in the region will increase between 3 °C and about 7 °C on average, according to the emission scenarios for the period of 2071–2100 with respect to past period of 1971–2000. Therefore, the projected warming and decrease in precipitation might adversely affect the ecological and socio-economic systems of this region, which is already a mostly arid and semi-arid environment. [ABSTRACT FROM AUTHOR]

Glacier hydrology has profound implications for socio-economic development and nature conservation in arid Central Asia. Process-based hydrological models, which are the traditional tools used to simulate glacier melting, have made considerable contributions to advance our understanding of glacio-hydrology. Simultaneously, deep learning (DL) models have achieved excellent performance in many complex tasks and provide high accuracy. However, it is uncertain whether glacio-hydrological studies can benefit from the application of DL models. In this study, to help us assess water resource change for glacier-influenced regions, we used DL models to simulate glacio-hydrological processes in the Urumqi Glacier No. 1 in northwest China. First, we proposed a newly DL model called Exogenous Regularization Network (ERNet), which focuses on the relationship between exogenous (temperature and precipitation) and endogenous (runoff) variables, balancing the roles of different variables in the simulation process. Second, we compared ERNet with a stacked long short-term memory (LSTM) model and a process-based glacio-hydrology model, FLEX G. Experiments showed that compared with the other two models, ERNet not only performed well in runoff and peak flow simulations but also displayed superior transferability. Third, given that the DL model is data-driven, we experimentally compared the importance of air temperature and precipitation to glacial runoff processes. The results show that air temperature plays a dominant role in glacier runoff generation. We believe that the proposed model provides a useful predictive tool and that the results shed light on the future implication in cold region hydrology. • We proposed a new DL model called the Exogenous Regularization Network (ERNet). • ERNet performed well in runoff and peak flow simulation, and transferability test. • We analysed the importance of meteorological inputs for runoff simulation. • We provided some practical advices for the usage of DL models in glacio-hydrology. [ABSTRACT FROM AUTHOR]

Climate change scenarios predict that Central Asia may experience an increase in the frequency and magnitude of temperature and precipitation extremes by the end of the 21st century, but the response regularity of different types of vegetation to climate extremes is uncertain. Based on remote-sensed vegetation index and in-situ meteorological data for the period of 2000–2012, we examined the diverse responses of vegetation to climate mean/extremes and differentiated climatic and anthropogenic influence on the vegetation in Central Asia. Our results showed that extensive vegetation degradation was related to summer water deficit as a result of the combined effect of decreased precipitation and increased potential evapotranspiration. Water was a primary climatic driver for vegetation changes regionally, and human-induced changes in vegetation confined mainly to local areas. Responses of vegetation to water stress varied in different vegetation types. Grasslands were most responsive to water deficit followed by forests and desert vegetation. Climate extremes caused significant vegetation changes, and different vegetation types had diverse responses to climate extremes. Grasslands represented a symmetric response to wet and dry periods. Desert vegetation was more responsive during wet years than in dry years. Forests responded more strongly to dry than to wet years due to a severe drought occurred in 2008. This study has important implications for predicting how vegetation ecosystems in drylands respond to climate mean/extremes under future scenarios of climate change. [ABSTRACT FROM AUTHOR]

The study of parameterization schemes is important for land surface models (LSMs) due to the uncertainties existed in simulating snow. However, previous studies have mainly assessed the qualitative sensitivity of parameterization combinations on snow simulations in LSMs. To better understand the parameterization schemes and reduce the model uncertainties in simulating snow depth, 24 ensemble experiments were conducted in this study using the Weather Research and Forecasting (WRF) model coupled with the Noah land surface model with multiparameterization options (WRF/Noah-MP) model based on four physical subprocesses: snow surface albedo (ALB); precipitation partitioning between rain and snowfall (SNF); snow/soil temperature time (STC); surface layer turbulence (SFC) schemes. Additionally, the sensitivities of the four parameterizations in simulating the snow depth were quantitatively assessed. The results showed that the WRF/Noah-MP model underestimated snow depth, with underestimation in the snow accumulation season and overestimation in the early snow accumulation and snow ablation seasons. The Sobol sensitivity revealed the dominant role of the ALB and STC subprocesses in the simulation of the snow depth. The sensitivities of the four physical subprocesses varied in the different snow seasons and at different altitudes. Additionally, all the subprocesses exhibited interactions when simulating the snow depth in the Tianshan Mountains in this study, except for the ALB in the snow ablation season and the STC at >1000 m. Distinct differences existed in the snow depth simulations using the different selected schemes with the ALB, STC, and SFC subprocess parameterization. Comparison of the parameterization schemes of the four subprocesses revealed that the ALB, STC, and SFC subprocess parameterizations mainly affected the snow depth simulation through the heat fluxes, while the SNF affected it through the air temperature. • Parameterizations sensitivity was quantitatively assessed by Sobol analysis using WRF/Noah-MP model over the Tianshan Mountains. • The dominant roles of the ALB and STC subprocesses in the simulation of the snow depth were identified compared with the SNF and SFC subprocesses. • The sensitivities of STC and ALB varied with different altitudes and snow season. • Interactions were found among all of the subprocesses in simulating snow depth in the Tianshan Mountains. [ABSTRACT FROM AUTHOR]

Abstract: Understanding the impact of climate change on water resources is essential to sustainable development. Urumqi River, a medium-size headwater catchment in the Tianshan mountains, was chosen to evaluate the impact of climate change on its discharges, where impacts of human activities on water are negligible and the influence of glacier melt is minor as far as the mountainous outlet is concerned. Analysis of the time series of temperature, precipitation and river discharge of the hydrological station at the mountainous outlet from 1959 to 2006 was carried out using different statistical methods, including linear regression, Mann–Kendall test and wavelet analysis. Although both temperature and precipitation show a significant upward trend with a gradient of 0.02 °C/y and 2.08 mm/y, respectively, there is no significant rising trend in the stream discharge. The reasons are attributed to the hysteresis and buffering effects of groundwater in conveying the change from precipitation to stream discharge. Common short periods of less than 8 years exist in the three time series, which is a common trend in NW China. Precipitation has stronger influence on stream discharge than air temperature throughout the 48 years of instrumental records in the Urumqi River catchment. [Copyright &y& Elsevier]

The high-resolution regional climate model (RCM) REMO has been implemented over the region of Central Asia, including western China. A model run forced by reanalysis data (1/2° resolution), and two runs forced by a GCM (one run with 1/2° and one run with 1/6° resolution) have been realized. The model has been evaluated regarding its ability to simulate the mean climate of the period 1971–2000. It has been found that the spatial pattern of mean temperature and precipitation is simulated well by REMO. The REMO simulations are often closer to observational data than reanalysis data are, and show considerably higher spatial detail. The GCM-forced simulations extend to the year 2100 under the A1B scenario. The climate change signal of temperature is largest in winter in the northern part of the study area and over mountainous terrain. A warming up to 7°C is projected until the end of the 21st century. In summer, warming is strongest over the southern part of Central Asia. Changes in precipitation are spatially more heterogeneous. [ABSTRACT FROM AUTHOR]

Lakes play an important role in regulating the regional climate, especially the large one in the arid region. The Aral Sea located in Central Asia, was once the fourth largest lake in the world, but gradually shrunk and lost more than 80% of its surface. As the Ara Sea dries up in last 60 years, the role of Aral Sea in regulating the regional climate dampens. However, how the Aral Sea regulates the regional climate and its mechanisms remains less understand. The climatic effect of the Aral Sea on regional climate is quantified by comparing two ideal simulations, with the Aral Sea included or excluded, using ALARO-SURFEX regional climate model under 4-km horizontal resolution. The model's performance in reproducing the 2-m temperature, precipitation and surface energy fluxes was evaluated firstly. The Aral Sea decreases (increases) the 2-m temperature in spring-summer (autumn-winter) over the Aral Sea and ambient land, which causes higher (lower) sea level pressure in spring-summer (autumn-winter) corresponding to enhanced the divergence (convergence) in spring-summer (autumn-winter). The lake-effect penetrates to the atmosphere, cools (warms) the daytime air temperature by 2.03 °C (0.07 °C) below (above) the height of 1.4-km during May to September but warming the nighttime air temperature by 0.42 °C below 0.6-km, leads to enhancing descent (ascent) motion in daytime (nighttime), which suppress (trigger) development of local convection in daytime (nighttime). The presence of Aral Sea increases specific humidity below 0.8-km in both daytime and nighttime. As a result, the annual precipitation, especially convective precipitation is increased by 7.08 mm and mainly occurs in nighttime-morning and open water period, but reduced precipitation occurs in 13:00–17:00 and ice frozen period. The presence of Aral Sea substantially reduces the sensible heat, enhances the latent heat, increases ground heat fluxes, but these effects depend season and diurnal variation. The temperature change induced by the Aral Sea is most contributed by the change of latent heat (ground heat) in open water period (ice frozen period), in diurnal timescale, the ground heat contributes most in both daytime and nighttime temperature change. • The regional climate model, ALARO-SURFEX, shows a reliable performance in the Aral Sea region. • Due to the lake-land thermal contrast,climate effect of the Aral Sea remains seasonal and diurnal variation. • Climate effect of the Aral Sea depends on background atmospheric circulation, vegetation condition and topography. [ABSTRACT FROM AUTHOR]

Lake level is a sensitive integral indicator of climate change on regional scales, especially in enclosed endorheic basins. Eurasia contains the largest endorheic zone with several large terminal lakes, whose water levels recently underwent remarkable variations. To address the patterns of these variations and their links to the climate change, we investigated the variability of levels in 15 lakes of three neighboring endorheic regions—Central Asia, Tibetan Plateau, and Mongolian Plateau. Satellite altimetry revealed a heterogeneous pattern among the regions during 1992–2018: lake levels increased significantly in Central Asia and the Tibetan Plateau but decreased on the Mongolian Plateau. The shifts to the increasing trend were detected since 1997 in Central Asia, since 1998 in the southern part of the Tibetan Plateau, and since 2005 in its northern part. The shift in air temperatures around 1997 and the precipitation shifts around 1998 and 2004 contributed to the trend's turning points, with precipitation being the major contributor to the heterogeneous pattern of lake levels. Our findings reveal the linkage of the heterogeneous pattern of lake levels to climatic factors in the endorheic basins, providing a further understanding of the hydrological regime in the Eurasian endorheic zone and its sensitivity to climate change. [ABSTRACT FROM AUTHOR]

The seasonal and inter-annual variations of stable isotopes in alpine precipitation in arid Central Asia is of great help to understand the modern hydrological processes and climate proxy in the westerly-dominant region. In this study, we measured the 3-year precipitation isotope values at a site located on the southern Tianshan Mountains in Central Asia. The δ 18O values of precipitation show a statistically significant relationship with air temperature (R 2 = 0.58). The trajectory diagnostics indicate the strong influence of westerly moisture, although the local trajectories do exist. According to the 3-year isotope records in the sampling site, the δ 18O values of precipitation correlated with the meridional circulation index, while the correlation with the zonal circulation index is generally weak. An isotope-enabled GCM is used to analyze the correlation between the δ 18O values in summer precipitation and the meridional and zonal wind speeds on a longer time scale; there is a strong correlation between the δ 18O values and the meridional wind speed for the upwind direction. The findings indicate the meridional movement of mid-latitude westerly can be sensitively recorded in the modern precipitation in arid Central Asia, and the inter-annual variability of precipitation isotopes in Central Asia can not only be attributed to temperature effect. • A multiple year measurement of precipitation isotope in a mountainous site of arid Central Asia is presented. • The δ 18O value of precipitation is significantly correlated with the meridional wind in the upwind direction. • The inter-annual isotopic variation of precipitation are attributed to the moisture path, instead of only temperature effect. [ABSTRACT FROM AUTHOR]

Spatiotemporal variability in the land surface energy flux is largely and comprehensively affected by many factors, including land surface temperature (LST), land coverage, soil characteristics, terrain conditions, etc. In contrast with other climatic zones, arid and semiarid lands have fragile ecological environments that are more sensitive to land surface energy flux changes. In this study, we used MODerate Resolution Imaging Spectroradiometer (MODIS) LST products (2001–2015) for air temperature comparisons. Then, we investigated the spatiotemporal variation in LSTs in the Syr Darya Basin (SDB) during 2001–2015. More specifically, a new statistical model known as GeoDetector was adopted to analyze the driving factors controlling the spatiotemporal variation in LSTs. The result shows that the MODIS LST can provide a good estimation of air temperature, especially at night. The LST change rate can be considered as an important indicator of climate change (rapid warming at high altitudes) and human activities (increased water consumption of crop). Based on the GeoDetector model, we determined that the elevation explained more of the LST distribution (84–90%) and spatiotemporal variation (22–26%) than any other land surface parameters. The combination of albedo and the other explanatory variables can significantly increase the explanatory power of each single factor, especially with elevation. Image 1 • A significant surface warming trend was founded in the upper reaches of SDB. • MODIS derived LST has a high consistency with the air temperature, especially at night. • The spatial trend of LST can be considered as an important indicator of climate change and human activities. • Elevation plays the most dominant role in the spatiotemporal variation of LST in SDB. • GeoDetector model was firstly adopted to analyze the driving factors controlling the spatiotemporal variation of LST. [ABSTRACT FROM AUTHOR]

Using historical data compiled by the Climate Research Unit, spatial and temporal analysis, trend analysis, empirical orthogonal function (EOF) analysis, and Taylor diagram analysis were applied to test the ability of 24 Coupled Model Intercomparison Project Phase 5 (CMIP5) climate models to accurately simulate the annual mean surface air temperature in central Asia from the perspective of the average climate state and climate variability. Results show that each model can reasonably capture the spatial distribution characteristics of the surface air temperature in central Asia but cannot accurately describe the regional details of climate change impacts. Some of the studied models, including CNRM-CM5, GFDL-CM3, and GISS-E2-H, could better simulate the high- and low-value centers and the contour distribution of the surface air temperature. Taylor diagram analysis showed that the root mean square errors of all models were less than 3, the standard deviations were between 8.36 and 13.45, and the spatial correlation coefficients were greater than 0.96. EOF analysis showed that the multi-model ensemble can accurately reproduce the surface air temperature characteristics in central Asia from 1901 to 2005, including the rising periods and the fluctuations of the north and south inversion phases. Overall, this study provides a valuable reference for future climate prediction studies in central Asia. [ABSTRACT FROM AUTHOR]

We examine the links between the thermal condition of the troposphere over the Tibetan Plateau with the atmospheric circulation and climate over the Eurasian continent. The temperature of the troposphere over the Tibetan Plateau is higher than the temperature in other regions at the same latitude and is consistent with the temperature of the Eurasian troposphere on an interannual timescale. The higher temperature of the troposphere over the Tibetan Plateau leads to anomalous south–north temperature gradients from mid-latitudes over the Eurasian continent to its two flanks, accompanied by anomalous easterly and westerly winds in the upper troposphere in the subtropics and at higher latitudes. Anomalous anticyclonic circulations and subsidence motions appear between the anomalous easterly and westerly winds and contribute to the high surface air temperature over West Asia, Central Asia and East Asia via anomalous vertical temperature advection in the troposphere and change in the amount of solar radiation incident on the surface. The enhanced East Asian summer monsoon associated with the high temperature of the troposphere over the Tibetan Plateau also partly contributes to the high surface air temperature over East Asia via horizontal temperature advection. The westerly wind anomalies in the north of the mid-latitudes over the Eurasian continent indicate the enhancement and northward shift of the mid-latitude westerly jet. This is related to anomalous upward motion and higher precipitation in Northeast China and North China. Sensitivity experiments based on an atmospheric model verify the impact of anomalous tropospheric heating over the Tibetan Plateau in summer on the atmospheric circulation over the Eurasian continent. • The Tibetan tropospheric temperature is coincident with the Eurasian tropospheric temperature at interannual time scales. • The Tibetan tropospheric temperature anomaly can change the intensity and position of the mid-latitude westerly jet. • The thermal condition of the Tibetan Plateau is related to SAT anomalies over West Asia, Central Asia, and East Asia. [ABSTRACT FROM AUTHOR]

The evolution of Holocene moisture in semiarid and arid regions of Central Asia is key to understanding changes in current and future water resources, and has been a hotly debated topic in the past few decades. Central Asian loess deposits have shown potential as records of past moisture changes, particularly during the Holocene. Here, the variations in effective moisture during the Holocene in the semiarid regions of the Yili Basin, Central Asia, are obtained from three loess sections. Reliable chronologies were constructed using 26 quartz optically stimulated luminescence (OSL) ages. The strengthening pedogenesis, steady increases in magnetic susceptibility, and continuous decreases in mean grain size in the three loess sections all suggest that effective moisture continuously increased throughout the Holocene, indicating a dry early Holocene, a moderately humid middle Holocene, and a wet late Holocene. Rainfall carried by the Asian summer monsoon and the Westerlies contributes to the moisture changes in Central Asia. However, considering the dominance of evaporation over rainfall in controlling aridity-humidity shifts in this region, the continuous weakening of evaporation caused by a decrease in Northern Hemisphere summer insolation and associated atmospheric temperatures is primarily responsible for the wetting trend throughout the Holocene in the semiarid regions of the Yili Basin. • OSL chronologies of three loess sections in the Yili Basin are presented. • Pedostratigraphy, MS, and MGS are used to represent effective moisture. • Effective moisture shows an increasing trend during the Holocene. • Evaporation is dominant in controlling changes in effective moisture. [ABSTRACT FROM AUTHOR]

Precipitation is a key process in the hydrologic cycle. However, accurate precipitation data are scarce in high mountainous areas, mainly restricted by complex topography, solid precipitation and sparse recording stations. In order to evaluate the quality of precipitation measurement, this study conducted a comparison campaign of precipitation measurements with the PWS100 laser sensor and the Geonor T-200B rain gauge for an entire year from 30 April 2018 to 1 May 2019 at an elevation of 3835 m in a nival glacial zone in eastern Tianshan, Central Asia. The results show that the daily precipitation values recorded by Geonor T-200B and PWS100 are well correlated and the annual precipitation amounts recorded by the two instruments differ by 7%, indicating good capabilities of both instruments in solid precipitation measurement. However, the amount of precipitation measured by Geonor T-200B was 36 mm lower in June to August and 120 mm higher in the remaining months compared with the values measured by PWS100. Our study indicated that Geonor T-200B is more efficient than PWS100 in terms of catching solid precipitation measurements. According to the PWS100 data, the experiment site was dominated by solid precipitation particles, accounting for 60% of total precipitation particles. Based on the precipitation particle and in-situ air temperature measurements, a set of temperature thresholds were established to discriminate rain, sleet and snow. The threshold temperature of rainfall and snowfall is −1.5 and 8 °C, respectively. When air temperature ranges from −1.5 to 8 °C, sleet occurs, meanwhile the ratio of rain to snow depends on air temperature. [ABSTRACT FROM AUTHOR]

Hydro–climatic variables play an essential role in assessing the long-term changes in streamflow in the snow-fed and glacier-fed rivers that are extremely vulnerable to climatic variations in the alpine mountainous regions. The trend and magnitudinal changes of hydro–climatic variables, such as temperature, precipitation, and streamflow, were determined by applying the non-parametric Mann–Kendall, modified Mann–Kendall, and Sen's slope tests in the Kofarnihon River Basin in Central Asia. We also used Pettitt's test to analyze the changes during the 1951–2012 and 1979–2012 time periods. This study revealed that the variations of climate variables have their significant spatial patterns and are strongly regulated by the altitude. From mountainous regions down to plain regions, the decadal temperature trends varied from −0.18 to 0.36 °C/decade and the variation of precipitation from −4.76 to −14.63 mm yr−1 per decade. Considering the temporal variation, the temperature trends decreased in winter and significantly increased in spring, and the precipitation trends significantly decreased in spring but significantly increased in winter in the high-altitude areas. As consequence, total streamflow in headwater regions shows the obvious increase and clear seasonal variations. The mean monthly streamflow decreased in fall and winter and significantly increased in the spring and summer seasons which can be attributed to the influence of global warming on the rapid melting of snow and ice. Although the abrupt change points in air temperature and precipitation occurred around the 1970s and 1990s in the low-altitude areas and 2000s in the high-altitude areas during the 1951–2012 and 1979–2012 periods, the general trends of hydro–climatic variables keep consistent. This study benefits water resource management, socio–economic development, and sustainable agricultural planning in Tajikistan and its downstream countries. [ABSTRACT FROM AUTHOR]

There is growing scientific interest in the impact of atmospheric circulation on regional air quality; however, it is poorly studied in Central Asia. This study is the first assessment of the evidence-based relations between air pollution episodes and the elementary circulation mechanisms (ECMs, by the classification from Dzerdzeevskii et al.) with atmospheric blocking process effects on an urban atmosphere over the geographical center of the Eurasian continent. The capital city of Kazakhstan, Nur-Sultan, is selected as the study location since it is located in the north of the Kazakh Uplands in a dry steppe zone. First, an episode identification procedure using multiple stations and multiple-pollutant time series data is proposed. After the identification of the aggregated pollutant episodes during the heating and non-heating periods in 2017, their relations with blocking anticyclones and cyclones are further investigated by checking the reversal of meridional gradients in the 500 hPa and 850 hPa geopotential height (GPH) maps. In total, 12 and 9 pollution episodes lasting an average of 5 days were identified in heating and non-heating periods, respectively. Following the calendar of continuous ECM changes, the type of ECM is determined for each episode, and then, the types of ECMs with atmospheric circulation and trajectory characteristics corresponding to the episodes were analyzed in detail. The findings suggest that i) regional and local air pollution levels on the Eurasian Steppes are actively controlled by regional meteorological variations, ii) the northern streams of cold Arctic air spread to the region and Siberian anticyclone reaches in winter, leading to extreme negative air temperature anomalies that contribute to the further cooling of the Arctic air and formation of extensive stationary anticyclones with blocking effects over the region, iii) a cold season circulation type, ECM 13w, was one of the most dominant ECMs with approximately 23% annual prevalence causing 30% of all the episodes, iv) ECMs 11a, 5a, and 5b were also associated with much higher pollution levels (up to 4-fold increases over the annual average), but they had lower prevalences (up to 5%). As a result, it was demonstrated that the regional climate conditions with particular ECMs regulate the ventilation characteristics of the atmosphere over the study area, and local air pollution concentrations increase to extreme levels and remain there longer, particularly during stationary anticyclone periods. • The atmospheric circulation patterns on regional air quality over Central Asia studied as a first time. • The Elementary Circulation Mechanisms (ECMs) classification (by Dzerdzeevskii et al.) was employed to analyze the relations between air pollution episodes and atmospheric blocking systems in the region. • Several episodic periods attributed to blocking anticyclone were identified. • Air pollution levels are strongly controlled by global meteorological variations. [ABSTRACT FROM AUTHOR]

Central Asia is a region that has a large land mass, yet meteorological stations in this area are relatively scarce. To address this data issues, in this study, we selected two reanalysis datasets (the ERA40 and NCEP/NCAR) and downscaled them to 40 × 40 km using RegCM. Then three gridded datasets (the CRU, APHRO, and WM) that were extrapolated from the observations of Central Asian meteorological stations to evaluate the performance of RegCM and analyze the spatiotemporal distribution of precipitation and air temperature. We found that since the 1960s, the air temperature in Xinjiang shows an increasing trend and the distribution of precipitation in the Tianshan area is quite complex. The precipitation is increasing in the south of the Tianshan Mountains (Southern Xinjiang, SX) and decreasing in the mountainous areas. The CRU and WM data indicate that precipitation in the north of the Tianshan Mountains (Northern Xinjiang, NX) is increasing, while the APHRO data show an opposite trend. The downscaled results from RegCM are generally consistent with the extrapolated gridded datasets in terms of the spatiotemporal patterns. We believe that our results can provide useful information in developing a regional climate model in Central Asia where meteorological stations are scarce. [ABSTRACT FROM AUTHOR]