Soil moisture variations and its relevant feedbacks (e.g., soil moisture–temperature and soil moisture–precipitation) have a crucial impact on the climate system. This study uses reanalysis and Coupled Model Intercomparison Project phase 6 simulations datasets to detect, attribute, and project soil moisture variations. The effect of anthropogenic forcings [greenhouse gases (GHG), anthropogenic aerosols (AA), and land use (LU) change] on soil moisture is much larger than that of the natural forcing. Soil moisture shows a drying trend at a global scale, which is mainly attributed to GHG forcing. The effects of external forcings vary with the regions significantly. Over eastern South America, GHG, AA, and natural forcings make soil dry, while LU forcing makes the soil wet. Over severely drying Europe, all the external forcings including GHG, AA, LU, and natural forcing exhibit drying effect. The optimal fingerprint method detection results show that some of GHG, AA, LU, and natural signals can be detected in soil moisture variations in some regions such as Europe. The soil will keep drying in all scenarios over most parts of the globe except Sahel and parts of mid-latitudes of Asia. With the increase of anthropogenic emissions, the variation of global soil moisture will be more extreme, especially in hotspots where the land–atmosphere coupling is intensive. The drying trend of soil moisture will be much larger on the surface than in middle and deep layers in the future, and this phenomenon will be more severe under the high-emission scenario. It may be affected by increased evaporation and the effect of carbon dioxide fertilization caused by global warming.
Abstract The NCEP Climate Forecast System (CFS) is an important source of information for seasonal climate prediction in many Asian countries affected by monsoon climate. The authors provide a comprehensive analysis of the prediction of the Asian summer monsoon (ASM) by the new CFS version 2 (CFSv2) using the hindcast for 1983–2010, focusing on seasonal-to-interannual time scales. Many ASM features are well predicted by the CFSv2, including heavy monsoon rainfall centers, large-scale monsoon circulation patterns, and monsoon onset and retreat features. Several commonly used dynamical monsoon indices and their associated precipitation and circulation patterns can be predicted several months in advance. The CFSv2 has better skill in predicting the Southeast Asian monsoon than predicting the South Asian monsoon. Compared to CFS version 1 (CFSv1), the CFSv2 has increased skill in predicting large-scale monsoon circulation and precipitation features but decreased skill for the South Asian monsoon, although some biases in the CFSv1 still exist in the CFSv2, especially the weaker-than-observed western Pacific subtropical high and the exaggerated strong link of the ASM to ENSO. Comparison of CFSv2 hindcast with output from Atmospheric Model Intercomparison Project (AMIP) and Coupled Model Intercomparison Project (CMIP) simulations indicates that exclusion of ocean–atmosphere coupling leads to a weaker ASM. Compared to AMIP, both hindcast and CMIP show a more realistic annual cycle of precipitation, and the interannual variability of the ASM is better in hindcast. However, CMIP does not show any advantage in depicting the processes associated with the interannual variability of major dynamical monsoon indices compared to AMIP.
Abstract Despite the prevalence of artificial separation of daytime and nighttime hot extremes, they may actually co-occur or occur sequentially. Considering their potential lead-lag configuration, this study identified an entire heatwave period as consecutive days with either daytime or nighttime hot extremes and investigated the changes of the prevalence and sequence of daytime and nighttime hot extremes during heatwaves over China from 1961 to 2017. It was found that the majority (82%) of heatwaves were compound heatwaves that had both daytime and nighttime hot extremes exceeding the 90th percentile-based thresholds, while only 7% (11%) were purely daytime (nighttime) heatwaves that contained only daytime (nighttime) hot extremes. During the entire periods of compound heatwaves, daytime hot extremes usually occurred one day or a few days before nighttime hot extremes, which was in accordance with the daily variations in radiation and meteorological conditions, such as the increasing surface humidity and cloud cover, and decreasing solar radiation during the entire heatwave periods. From 1961 to 2017, compound heatwave numbers exhibited the sharpest increase with a statistically significant trend of 0.44 times decade −1 , in contrast to an insignificant trend of 0.00 times decade −1 for purely daytime heatwaves and a significant trend of 0.09 times decade −1 for purely nighttime heatwaves. Within the compound heatwave periods, hot nights were starting earlier and ending later, and numbers of concurrent daytime-nighttime hot extremes increased significantly at 0.20 days decade −1 . In particular, urban area were not only subject to increasingly more frequent and longer compound heatwaves, but also to more occurrences of concurrent daytime-nighttime hot extremes with more serious impact. This study provides instructions for researchers to customize and select appropriate heatwave indices.
Abstract The effect of Eurasian spring snowmelt on surface air temperature (SAT) in late spring (April–May) and early summer (June–July) and the relevant physical mechanisms during 1981–2016 are investigated. Results show that the first mode of the inter-annual Eurasian spring snowmelt represents an east–west dipole anomaly pattern, with an intense center over Siberia and another moderate center around eastern Europe. The European spring snowmelt shows an insignificant relation to the local SAT, whereas the Siberian spring snowmelt has a significant impact on the SAT in late spring and early summer. More Siberian spring snowmelt contributes to higher SAT in late spring and lower SAT in early summer via different mechanisms. In late spring, increased Siberian spring snowmelt corresponds to less local surface albedo and cloud cover, leading to the surface absorbing more shortwave radiation and thereby higher SAT. The sub-surface and deep soil moisture anomalies generated from Siberian spring snowmelt can persist into early summer. Excessive Siberian spring snowmelt corresponds to positive soil moisture anomalies, contributing to decreased sensible heat and increased cloud cover in early summer. Increased cloud cover leads to the surface receiving less shortwave radiation. Thus, lower SAT appears over Siberia in early summer due to reduced sensible heat and shortwave radiation. However, the simulation of Eurasian spring snowmelt variability and its influences on SAT via the snow hydrological effect is still a challenge for the climate models that participated in the Coupled Model Intercomparison Project phase 6.
Abstract Under global warming, the summer surface air temperature (SAT) change signal in the northern mid‐latitudes is generally the most significant, while the SAT change in North China (NC) shows distinct local characteristics. Using simulations from the Coupled Model Intercomparison Project Phase 6 and observation from Berkeley Earth Surface Temperature, this study reveals an unusually weak signal of summer SAT change in NC since the 1960s. This uniquely weak signal can be attributed to the small net contribution of external forcings, mainly from anthropogenic greenhouse gases (GHG) and aerosols (AA). Compared to other land regions in the same latitudinal band, the GHG‐induced warming was weaker and AA‐induced cooling was stronger in NC, resulting in the weakest SAT change signal and thus the lowest signal‐to‐noise ratio. This weaker GHG‐induced warming plays a more important role in the SAT change difference between NC and other land regions in the same latitudinal zone. Under different emission scenarios in the future, the signal‐to‐noise ratio in NC will become as large as those in the other land regions in the same latitudinal band and the northern hemisphere, which is partly due to the smaller relative differences in the SAT change signal between NC and the other two regions. The projections of SAT change indicate that climate change in NC will probably become more violent and vulnerable.
Abstract Glacio-meteorological data obtained during the Greenland Ice Margin Experiment (GIMEX) investigations in West Greenland (the Søndre Strømfjord transect) have been used to test and calibrate energy-balance/mass-balance models for the ice/snow surface. The region is characterised by the development of a wide zone of low surface albedo in the course of the melting season. This zone was simulated in one of the energy-balance models by including the effect of surficial meltwater on albedo. Observed mass-balance and albedo data were used to constrain the models. Although all the models are capable of predicting the transect balance reasonably well, only the model with the meltwater albedo coupling, is able to reproduce the observed albedo pattern and mass-balance profile along the transect. By including the feedback between surficial meltwater and albedo in the model, the sensitivity of the specific balance to changes in air temperature is found to be greatest just below the equilibrium line (in contrast to what is generally found for valley glaciers). A 1 K warming of the air temperature would increase the mean ablation along the transect by 0.5 m w.e.year −1 .
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