冰川径流是西北干旱区径流的主要组成部分，研究未来气候变化对冰川径流的影响对西北干旱区径流至关重要。以博尔塔拉河上游源流区为研究区，构建嵌入冰川模块的SWAT模型，模拟温泉水文站1972—2018年月径流过程，并在此基础上研究了气候变化情景下（RCP4.5和RCP8.5）未来（2020—2050年）气候变化对冰川径流的影响。结果表明：SWAT模型能够很好地模拟源流区径流变化过程，在整个模拟期间，径流数据的纳什系数（NSE）为0.82，偏差百分比（PBIAS）为-3.22%，均方根误差与实测值标准差的比值（RSR）为0.42，决定性系数（R2）为0.84，模型性能评定为优。根据CMIP5气候模式2种情景的模拟结果，2种情景模拟未来总径流都呈现出增加趋势，分别将以0.31×10～8m3·（10a）-1和0.40×10～8m3·（10a）-1的速度继续增加，冰川径流占比较历史时期的27.61%分别提升了4.84%和9.38%。冰川径流增加是径流量增加的主要原因。通过相关性分析发现，随着...

冰川径流是西北干旱区径流的主要组成部分，研究未来气候变化对冰川径流的影响对西北干旱区径流至关重要。以博尔塔拉河上游源流区为研究区，构建嵌入冰川模块的SWAT模型，模拟温泉水文站1972—2018年月径流过程，并在此基础上研究了气候变化情景下（RCP4.5和RCP8.5）未来（2020—2050年）气候变化对冰川径流的影响。结果表明：SWAT模型能够很好地模拟源流区径流变化过程，在整个模拟期间，径流数据的纳什系数（NSE）为0.82，偏差百分比（PBIAS）为-3.22%，均方根误差与实测值标准差的比值（RSR）为0.42，决定性系数（R2）为0.84，模型性能评定为优。根据CMIP5气候模式2种情景的模拟结果，2种情景模拟未来总径流都呈现出增加趋势，分别将以0.31×10～8m3·（10a）-1和0.40×10～8m3·（10a）-1的速度继续增加，冰川径流占比较历史时期的27.61%分别提升了4.84%和9.38%。冰川径流增加是径流量增加的主要原因。通过相关性分析发现，随着...

This study investigates the impacts of climate change on the hydrology and soil thermal regime of 10 sub-arctic watersheds (northern Manitoba, Canada) using the Variable Infiltration Capacity (VIC) model. We utilize statistically downscaled and biascorrected forcing datasets based on 17 general circulation model (GCM) - representative concentration pathways (RCPs) scenarios from phase 5 of the Coupled Model Intercomparison Project (CMIP5) to run the VIC model for three 30-year periods: a historical baseline (1981-2010: 1990s), and future projections (2021-2050: 2030s and 2041-2070: 2050s), under RCPs 4.5 and 8.5. Future warming increases the average soil column temperature by similar to 2.2 C in the 2050s and further analyses of soil temperature trends at three different depths show the most pronounced warming in the top soil layer (1.6 degrees C 30-year(-1) in the 2050s). Trend estimates of mean annual frozen soil moisture fraction in the soil column show considerable changes from 0.02 30-year(-1) (1990s) to 0.11 30-year(-1) (2050s) across the study area. Soil column water residence time decreases significantly (by 5 years) during the 2050s when compared with the 1990s as soil thawing intensifies the infiltration process thereby contributing to faster conversion to baseflow. Future warming results in 40%-50% more baseflow by the 2050s, where it increases substantially by 19.7% and 46.3% during the 2030s and 2050s, respectively. These results provide crucial information on the potential future impacts of warming soil temperatures on the hydrology of sub-arctic watersheds in north-central Canada and similar hydro-climatic regimes.

人类活动引起的当代气候变暖已导致全球海平面显著上升,在21世纪全球气候继续变暖的背景下,东南沿海海平面的升高将对区域环境及社会可持续发展带来巨大挑战,但目前对未来区域海平面变化的预估尚存在较大的不确定性。本文基于筛选的国际耦合模式比较计划第5阶段(CMIP5)的10个模拟性能较好的气候模式输出结果,通过多模式集合预估了未来温室气体三种排放情景下21世纪东海和南海区域海平面高度的趋势变化,并分析了不同影响因子的贡献。通过计算海水热比容、盐比容和动力因子对海平面高度的影响,并在考虑冰川冰盖消融等因子的订正后,发现:21世纪东海和南海海平面高度都呈现连续上升趋势,东海和南海地区上升幅度略小于全球平均,南海上升幅度略大于东海。在温室气体低(RCP2.6)、中(RCP4.5)和高(RCP8.5)排放情景下,21世纪后期(2081-2100年)较前期(2006-2025年)东海/南海平均海平面分别上升0.26 [0.01-0.55] m/0.29 [0.05-0.55] m、0.38[0.10-0.66] m/0.40[0.14-0.67]m和0.52[0.15-0.89]m/0.52[0.23-...

人类活动引起的当代气候变暖已导致全球海平面显著上升,在21世纪全球气候继续变暖的背景下,东南沿海海平面的升高将对区域环境及社会可持续发展带来巨大挑战,但目前对未来区域海平面变化的预估尚存在较大的不确定性。本文基于筛选的国际耦合模式比较计划第5阶段(CMIP5)的10个模拟性能较好的气候模式输出结果,通过多模式集合预估了未来温室气体三种排放情景下21世纪东海和南海区域海平面高度的趋势变化,并分析了不同影响因子的贡献。通过计算海水热比容、盐比容和动力因子对海平面高度的影响,并在考虑冰川冰盖消融等因子的订正后,发现:21世纪东海和南海海平面高度都呈现连续上升趋势,东海和南海地区上升幅度略小于全球平均,南海上升幅度略大于东海。在温室气体低(RCP2.6)、中(RCP4.5)和高(RCP8.5)排放情景下,21世纪后期(2081-2100年)较前期(2006-2025年)东海/南海平均海平面分别上升0.26 [0.01-0.55] m/0.29 [0.05-0.55] m、0.38[0.10-0.66] m/0.40[0.14-0.67]m和0.52[0.15-0.89]m/0.52[0.23-...

Despite the fundamental importance of soil temperature for Earth's carbon and energy budgets, ecosystem functioning, and agricultural production, studies of climate change impacts on soil processes have mainly relied on air temperatures, assuming they are accurate proxies for soil temperatures. We evaluated changes in soil temperature, moisture, and air temperature predicted over the 21st century from 14 Earth system models. The model ensemble predicted a global mean soil warming of 2.3 0.7 and 4.5 1.1 degrees C at 100-cm depth by the end of the 21st century for RCPs 4.5 and 8.5, respectively. Soils at 100 cm warmed at almost exactly the same rate as near-surface (similar to 1 cm) soils. Globally, soil warming was slightly slower than air warming above it, and this difference increased over the 21st century. Regionally, soil warming kept pace with air warming in tropical and arid regions but lagged air warming in colder regions. Thus, air warming is not necessarily a good proxy for soil warming in cold regions where snow and ice impede the direct transfer of sensible heat from the atmosphere to soil. Despite this effect, high-latitude soils were still projected to warm faster than elsewhere, albeit at slower rates than surface air above them. When compared with observations, the models were able to capture soil thermal dynamics in most biomes, but some failed to recreate thermal properties in permafrost regions. Particularly in cold regions, using soil warming rather than air warming projections may improve predictions of temperature-sensitive soil processes.

Permafrost degradation caused by contemporary climate change significantly affects arctic regions. Active layer thickening combined with the thaw subsidence of ice-rich sediments leads to irreversible transformation of permafrost conditions and activation of exogenous processes, such as active layer detachment, thermokarst and thermal erosion. Climatic and permafrost models combined with a field monitoring dataset enable the provision of predicted estimations of the active layer and permafrost characteristics. In this paper, we present the projections of active layer thickness and thaw subsidence values for two Circumpolar Active Layer Monitoring (CALM) sites of Eastern Chukotka coastal plains. The calculated parameters were used for estimation of permafrost degradation rates in this region for the 21st century under various IPCC climate change scenarios. According to the studies, by the end of the century, the active layer will be 6-13% thicker than current values under the RCP (Representative Concentration Pathway) 2.6 climate scenario and 43-87% under RCP 8.5. This process will be accompanied by thaw subsidence with the rates of 0.4-3.7 cm.a(-1). Summarized surface level lowering will have reached up to 5 times more than current active layer thickness. Total permafrost table lowering by the end of the century will be from 150 to 310 cm; however, it will not lead to non-merging permafrost formation.

Permafrost has significant impacts on climate change through its strong interaction with the climate system. In order to better understand the permafrost variation and the role it plays in climate change, model outputs from Phase 5 of the Coupled Model Intercomparison Project (CMIP5) are used in the present study to diagnose the near-surface permafrost on the Tibetan Plateau (TP), assess the abilities of the models to simulate present-day (1986-2005) permafrost and project future permafrost change on the TP under four different representative concentration pathways (RCPs). The results indicate that estimations of present-day permafrost using the surface frost index (SFI) and the Kudryavtsev method (KUD) show a spatial distribution similar to that of the frozen soil map on the TP. However, the permafrost area calculated via the KUD is larger than that calculated via the SFI. The SFI produces a present-day permafrost area of 127.2 x 10(4) km(2). The results also indicate that the permafrost on the TP will undergo regional degradation, mainly at the eastern, southern and northeastern edges, during the 21st century. Furthermore, most of the sustainable permafrost will probably exist only in the northwestern TP by 2099. The SFI also indicates that the permafrost area will shrink by 13.3 x 10(4) km(2) (9.7%) and 14.6 x 10(4) km(2) (10.5%) under the RCP4.5 and RCP8.5 scenarios, respectively, in the next 20 years and by 36.7 x 10(4) km(2) (26.6%) and 45.7 x 10(4) km(2) (32.7%), respectively, in the next 50 years. The results are helpful for us to better understand the permafrost response to climate change over the TP, further investigate the physical mechanism of the freeze-thaw process and improve the model parameterization scheme.

Global warming of 2 degrees C above preindustrial levels has been considered to be the threshold that should not be exceeded by the global mean temperature to avoid dangerous interference with the climate system. However, this global mean target has different implications for different regions owing to the globally nonuniform climate change characteristics. Permafrost is sensitive to climate change; moreover, it is widely distributed in high-latitude and high-altitude regions where the greatest warming is predicted. Permafrost is expected to be severely affected by even the 2 degrees C global warming, which, in turn, affects other systems such as water resources, ecosystems, and infrastructures. Using air and soil temperature data from ten coupled model intercomparison project phase five models combined with observations of frozen ground, we investigated the permafrost thaw and associated ground settlement under 2 degrees C global warming. Results show that the climate models produced an ensemble mean permafrost area of 14.01 x 10(6) km(2), which compares reasonably with the area of 13.89 x 10(6) km(2) (north of 45A degrees N) in the observations. The models predict that the soil temperature at 6 m depth will increase by 2.34-2.67 degrees C on area average relative to 1990-2000, and the increase intensifies with increasing latitude. The active layer thickness will also increase by 0.42-0.45 m, but dissimilar to soil temperature, the increase weakens with increasing latitude due to the distinctly cooler permafrost at higher latitudes. The permafrost extent will obviously retreat north and decrease by 24-26% and the ground settlement owing to permafrost thaw is estimated at 3.8-15 cm on area average. Possible uncertainties in this study may be mostly attributed to the less accurate ground ice content data and coarse horizontal resolution of the models.

Soil properties such as soil organic carbon (SOC) stocks and active-layer thickness are used in earth system models (ESMs) to predict anthropogenic and climatic impacts on soil carbon dynamics, future changes in atmospheric greenhouse gas concentrations, and associated climate changes in the permafrost regions. Accurate representation of spatial and vertical distribution of these soil properties in ESMs is a prerequisite for reducing existing uncertainty in predicting carbon-climate feedbacks. We compared the spatial representation of SOC stocks and active-layer thicknesses predicted by the coupled Model Intercomparison Project Phase 5 (CMIP5) ESMs with those predicted from geospatial predictions, based on observation data for the state of Alaska, USA. For the geospatial modeling, we used soil profile observations (585 for SOC stocks and 153 for active-layer thickness) and environmental variables (climate, topography, land cover, and surficial geology types) and generated fine-resolution (50-m spatial resolution) predictions of SOC stocks (to 1-m depth) and active-layer thickness across Alaska. We found large inter-quartile range (2.5-5.5 m) in predicted active-layer thickness of CMIP5 modeled results and small inter-quartile range (11.5-22 kg m(-2)) in predicted SOC stocks. The spatial coefficient of variability of active-layer thickness and SOC stocks were lower in CMIP5 predictions compared to our geospatial estimates when gridded at similar spatial resolutions (24.7 compared to 30% and 29 compared to 38%, respectively). However, prediction errors, when calculated for independent validation sites, were several times larger in ESM predictions compared to geospatial predictions. Primary factors leading to observed differences were (1) lack of spatial heterogeneity in ESM predictions, (2) differences in assumptions concerning environmental controls, and (3) the absence of pedogenic processes in ESM model structures. Our results suggest that efforts to incorporate these factors in ESMs should reduce current uncertainties associated with ESM predictions of carbon-climate feedbacks. (C) 2016 The Authors. Published by Elsevier B.V.