Winter baseflow (WB) can stabilize freshwater inputs and has important impacts on nutrient migration and the water cycle of a specific region and the oceans. This study systematically analyzed the WB variations in fourteen major Eurasian rivers and found they all had commonly increasing trends (except the Yellow River), with the mean increase ratio of 53.0% (+/- 34.8%, confidence interval 95%) over the past 100 years (the longest time series is 1879-2015). Relative to Northern Eurasia (60 degrees N-70 degrees N) and Southern Eurasia (30 degrees N-40 degrees N), the river WB in middle Eurasia (40 degrees N-60 degrees N) had the largest increase rate (0.60%/year). The increases of the WB in Northern Eurasia and Southern Eurasia have speeded up since the 1990s; on the contrary, they have slowed down or even turned to a decreasing trend after the 1990s in the middle Eurasian rivers. Using multiple linear regression analysis, the quantitative relationship between WB and winter surface air temperature (max, mean and min), snowfall, soil temperature, antecedent precipitation, as well as the river-ice dynamic were determined. We found that the winter air temperature, especially the minimum air temperature was one major factor accounting for WB variation in Eurasia over the past century. When the winter air temperature rises, this leads a reduction in the thickness and volume of river ice, and thus decreases water storage in river ice and leads to an increase in the WB. About 19.6% (6.7%-41.5%) of the winter WB increase in rivers of Siberia was caused by the decreased river ice during the past 100 years. Although groundwater recharge was the dominant reason for WB change, the role of river ice should not be ignored in hydrological study of cold regions.

Empirical orthogonal function (EOF) and correlation analyses were employed to investigate the winter and spring snow depth in Eurasia and its relationship with Eastern China precipitation based on the observed and reanalyzed data from 1980 to 2016. The results show that the winter and spring snow cover in Eurasia not only highlights a decreasing trend due to global warming (the first EOF mode, its variance accounted for 24.4% and 22.6% of the total variance) but also exhibits notable interdecadal variation (the second EOF mode, its variance accounted for 10.2% and 11.5% of the total variance). The second EOF mode of winter snow depth in Eurasia is characterized by a west-east dipole pattern. It was observed that the spatial correlation pattern between the EOF2 of Eurasian snow depth and summer precipitation in China closely resembles the meridional quadrupole structure of the third EOF mode of summer precipitation in China. This pattern is characterized by excessive rainfall in Northeast China and the lower-middle reaches of the Yangtze River, and less rainfall over the Yellow River basin and southern China. The EOF mode of spring snow depth not only reflects the declining trend but also regulates precipitation in Eastern China. The possible mechanisms by which snow depth causes changes in soil moisture and subsequently affects atmospheric circulation are then explored from the perspective of the hydrological effects of snow cover. Decreased (Increased) snow depth in Eurasia during the winter and spring directly leads to diminished (increased) soil moisture while increasing (decreasing) net radiation and sensible heat flux at the surface. The meridional distribution of surface temperature also exhibits a dipole pattern, leading to enhanced subtropical westerly jet in the upper troposphere. The Eurasian snow cover anomalies pattern triggered an anomalous mid-latitude Eurasian wave train, which strengthened significantly in the Western Siberian Plain. It then splits into two branches, one continuing to propagate eastward at high latitudes and the other shifting towards East Asia, thereby impacting precipitation in Eastern China. This work indicates that the second EOF mode of Eurasian snow cover can impact the precipitation variability in Eastern China during the same period and in summer on an interdecadal scale.

Europe has experienced many extreme heat waves over the past few decades. In this study, the physical processes underlying these long-lasting and wide-ranging heat wave events are investigated based on a case study in Europe in June 2021. Heat waves are associated with barotropic anticyclonic anomalies accompanied by positive geopotential height anomalies locally. These anomalies persist under the conditions of increased meridional air temperature gradients of the mid-upper troposphere in the high latitudes of Eurasia and the formation of the Arctic front jet. The shrinking high-latitude snow cover in April-May favors higher surface temperatures and larger meridional temperature gradients in June in the mid-upper troposphere due to the soil moisture-evaporation-temperature positive feedback process. The summer Arctic front jet is then strengthened, and the mid-latitude westerly winds are weakened. This atmospheric circulation background favors waveguide formation and wave resonance that produces high-amplitude atmospheric waves and the stagnation of ridges in the midlatitudes. Numerical experiments using the Community Atmosphere Model version 5 verify the proposed physical mechanisms, with the climatic responses in sensitivity experiments to anomalous snowfall rates closely resembling the observational results. Therefore, in June 2021, under the identified atmospheric circulation background and the perturbation of the upstream positive phase of the North Atlantic Oscillation, the large-scale barotropic high pressure and barotropic anticyclonic circulation in the study region tended to be stable and persistent, which is favorable for the production of long-lasting and wide-ranging heat wave events.

Recent research has shown that snow cover induces extreme wintertime cooling and has detrimental impacts. Although the dramatic loss of Arctic sea ice certainly has contributed to a more extreme climate, the mechanism connecting sea-ice loss to extensive snow cover is still up for debate. In this study, a significant relationship between sea ice concentration (SIC) in the Barents-Kara (B-K) seas in November and snow cover extent over Eurasia in winter (November-January) has been found based in observational datasets and through numerical experiments. The reduction in B-K sea ice gives rise to a negative phase of Arctic Oscillation (AO), a deepened East Asia trough, and a shallow trough over Europe. These circulation anomalies lead to colder-than-normal Eurasian mid-latitude temperatures, providing favorable conditions for snowfall. In addition, two prominent cyclonic anomalies near Europe and Lake Baikal affect moisture transport and its divergence, which results in increased precipitation due to moisture advection and wind convergence. Furthermore, anomalous E-P flux shows that amplified upward propagating waves associated with the low SIC could contribute to the weakening of the polar vortex and southward breakouts of cold air. This work may be helpful for further understanding and predicting the snowfall conditions in the middle latitudes.

The timing and duration of snow cover critically affect surface albedo, surface energy budgets, and hydrological processes. Previous studies using in-situ or satellite remote sensing data have mostly been site-specific (Siberia and the Tibetan Plateau), and remote sensing and/or modeling data include large uncertainties. Here, we used 1103 stations with long-term (1966-2012) ground-based snow measurements to investigate spatial and temporal variability in snow cover timing and duration and factors impacting those changes across the Eurasian continent. We found the earliest annual onset and latest disappearance of snow cover occurred along the Arctic coast, where the long-term (1971-2000) mean annual snow cover duration (SCD) was more than nine months which was the longest in this study. The shortest SCD, <= 10 days, was found in southern China. The first and last dates of snow cover (FD and LD, respectively), SCD, and the ratio of SCD to snow season length (RDL) were generally latitude dependent over the Eurasian Continent, while were elevation dependent on the Tibetan Plateau. During the period from 1966 through 2012, FD delayed and LD advanced by similar to 1 day/decade, and RDL increased by about 0.01/decade. The LD, SCD, and RDL anomalies (relative to the period 1971-2000) were also significantly correlated with latitude. Advances in LD and positive RDL were more significant in low-latitude regions, decreases in SCD were more significant in high-latitude regions. Changes in SCD were related to air temperature and snowfall in autumn and warming in spring. SCD specifically increased in the northern Xinjiang and northeastern China to increased snowfall. The significant reduction in SCD in southwestern Russia, the Tibetan Plateau and along the Yangtze River was mainly affected by climate warming. (C) 2020 Elsevier B.V. All rights reserved.

During the past several decades, the Earth system has changed significantly, especially across Northern Eurasia. Changes in the socio-economic conditions of the larger countries in the region have also resulted in a variety of regional environmental changes that can have global consequences. The Northern Eurasia Future Initiative (NEFI) has been designed as an essential continuation of the Northern Eurasia Earth Science Partnership Initiative (NEESPI), which was launched in 2004. NEESPI sought to elucidate all aspects of ongoing environmental change, to inform societies and, thus, to better prepare societies for future developments. A key principle of NEFI is that these developments must now be secured through science-based strategies co-designed with regional decision-makers to lead their societies to prosperity in the face of environmental and institutional challenges. NEESPI scientific research, data, and models have created a solid knowledge base to support the NEFI program. This paper presents the NEFI research vision consensus based on that knowledge. It provides the reader with samples of recent accomplishments in regional studies and formulates new NEFI science questions. To address these questions, nine research foci are identified and their selections are briefly justified. These foci include warming of the Arctic; changing frequency, pattern, and intensity of extreme and inclement environmental conditions; retreat of the cryosphere; changes in terrestrial water cycles; changes in the biosphere; pressures on land use; changes in infrastructure; societal actions in response to environmental change; and quantification of Northern Eurasia's role in the global Earth system. Powerful feedbacks between the Earth and human systems in Northern Eurasia (e.g., mega-fires, droughts, depletion of the cryosphere essential for water supply, retreat of sea ice) result from past and current human activities (e.g., large-scale water withdrawals, land use, and governance change) and potentially restrict or provide new opportunities for future human activities. Therefore, we propose that integrated assessment models are needed as the final stage of global change assessment. The overarching goal of this NEFI modeling effort will enable evaluation of economic decisions in response to changing environmental conditions and justification of mitigation and adaptation efforts.

Significant climatic changes over Northern Eurasia during the 20th century have been reflected in numerous variables of economic, social, and ecological interest, including the natural frequency of forest fires. For the former USSR, we are now using the Global Daily Climatology Network and a new Global Synoptic Data Network archive, GSDN, created jointly by U.S. National Climatic Data Center and Russian Research Institute for Hydrometeorological Information. Data from these archives (approximately 1500 of them having sufficiently long meteorological time series suitable for participation in our analyses) are employed to estimate systematic changes in indices used in the United States and Russia to assess potential forest fire danger. We use four indices: (1) Keetch-Byram Drought Index, (KBDI; this index was developed and widely used in the United States); (2) Nesterov, (3) Modified Nesterov, and (4) Zhdanko Indices (these indices were developed and widely used in Russia). Analyses show that after calibration, time series of the days with increased potential forest fire danger constructed using each of these three indices (a) are well correlated and (b) deliver similar conclusions about systematic changes in the weather conditions conducive to forest fires. Specifically, over the Eastern half of Northern Eurasia (Siberia and the Russian Far East) statistically significant increases in indices that characterize the weather conditions conducive to forest fires were found. These areas coincide with the areas of most significant warming during the past several decades south of the Arctic Circle. West of the Ural Mountains, the same indices show a steady decrease in the frequency of dry weather summer days during the past 60 yr. This study is corroborated with available statistics of forest fires and with observed changes in drought statistics in agricultural regions of Northern Eurasia. (C) 2006 Elsevier B.V. All rights reserved.