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Numerous circulation indices have been applied in practical climate services focused on regional precipitation. It is beneficial to identify the most influential or decisive indices, but this is difficult with conventional correlation analyses because of the underlying nonlinear mechanisms for precipitation. This paper demonstrates a set of the most influential indices for July–August precipitation in North China, based on the recursive random forest (RRF) method. These decisive circulation indices include the Polar–Eurasia teleconnection, North African subtropical high ridge position, India–Burma trough, Antarctic Oscillation, Northern Hemisphere polar vortex central latitude, North Atlantic Oscillation, and western Pacific subtropical high northern boundary position. Some of these factors have been recognized as directly influential to the regional precipitation, for example, those of the northwestern Pacific subtropical high; however, some are not easily understood. Decision tree (DT) models using these indices were developed to facilitate composite analyses to explain the RRF results. Taking one of the most interesting DT rules as an example, when the North African subtropical high ridge position is sufficiently far south, an anomalous anticyclone occurs in the upstream and an anomalous cyclone in the downstream of North China. This is unfavorable for northward moisture transport in eastern China and hence causes less precipitation in North China than climatology. The present results are not only helpful for improving diagnostic models of regional precipitation, but also enlightening for exploring how global climate change could impact a region by modulating large-scale circulation patterns. [ABSTRACT FROM AUTHOR]

ERA-Interim has been widely considered as a valid proxy for observations at global and regional scales. However, the verifications of ERA-Interim precipitation and temperature in mainland China have been rarely conducted, especially in the spatial and long-term performances. Therefore, in this study, we employed the interpolated ground station (STA) data to evaluate the spatial and temporal patterns and trends of ERAInterim precipitation and temperature during 1980-2012. The results showed that relatively weaker performances were observed in ERA-Interim precipitation, with the skill score (S index) ranging from 0.41 to 0.50. Interannual ERA-Interim precipitation presented comparable trends with STA precipitation at the annual and seasonal scales. Spatial patterns of empirical orthogonal function (EOF) modes and corresponding principal components were evidently different between annual ERA-Interim and STA precipitation. For temperature, annual and seasonal patterns of ERA-Interim data were in good consistency with those of STA over China with the S index ranging from 0.59 to 0.70. Yet interannual STA temperature recorded stronger warming trends (from 0.37 K decade-1 of wintertime to 0.53 K decade-1 of springtime) at the annual and seasonal scales compared to corresponding periods for ERA-Interim temperature (from 0.03 K decade-1 of wintertime to 0.25 K decade-1 of summertime). Overall, ERA-Interim precipitation and temperature had good agreement with STA data in east China with lower elevation (<1000m above sea level), but good agreements were not observed in west China with higher elevation. The findings suggest that caution should be paid when using ERA-Interim precipitation and temperature in areas with complex orography. [ABSTRACT FROM AUTHOR]

In this study, a microwave-based multisatellite merged product released from the European Space Agency's Climate Change Initiative (ESA CCI) and two model-based simulations from the Community Land Model 4.5 (CLM4.5) and Global Land Data Assimilation System (GLDAS) were used to investigate interannual variations and trends of soil moisture in China between 1979 and 2010. They were also evaluated using in situ observations from the nationwide agrometeorological network. These three datasets show consistent drying trends for surface soil moisture in northeastern and central China, as well the eastern portion of Inner Mongolia, and wetting trends in the Tibetan Plateau, which are also identified by in situ observations. Trends in the root-zone soil moisture are in line with those of surface soil moisture seen in the CLM4.5 and GLDAS simulations obtained from most areas in China (78%-88%), except for northwestern China and southwest of the Tibetan Plateau. Moreover, the drying trend intensifies with increasing soil depth. Taking the in situ measurements as reference, it is found that ESA CCI has better accuracy in identifying the significant drying trends while CLM4.5 and GLDAS capture wetting trends better. Compared to temperature, precipitation is the primary factor responsible for these trends, which controls the direction of soil moisture changes, while increasing temperatures can also enhance soil drying during periods of decreased precipitation. [ABSTRACT FROM AUTHOR]

Precipitation is expected to increase under global warming. However, large discrepancies in precipitation sensitivities to global warming among observations and models have been reported, partly owing to the large natural variability of precipitation, which accounts for over 90% of its total variance in China. Here, the authors first elucidated precipitation sensitivities to the long-term warming trend and interannual-decadal variations of surface air temperature T a over China based on daily data from approximately 2000 stations from 1961 to 2014. The results show that the number of dry, trace, and light precipitation days has stronger sensitivities to the warming trend than to the T a interannual-decadal variation, with 14.1%, −35.7%, and −14.6% K−1 versus 2.7%, −7.9%, and −3.1% K−1, respectively. Total precipitation frequency has significant sensitivities to the warming trend (−18.5% K−1) and the T a interannual-decadal variation (−3.6% K−1) over China. However, very heavy precipitation frequencies exhibit larger sensitivities to the T a interannual-decadal variation than to the long-term trend over Northwest and Northeast China and the Tibetan Plateau. A warming trend boosts precipitation intensity, especially for light precipitation (9.8% K−1). Total precipitation intensity increases significantly by 13.1% K−1 in response to the warming trend and by 3.3% K−1 in response to the T a interannual-decadal variation. Very heavy precipitation intensity also shows significant sensitivity to the interannual-decadal variation of T a (3.7% K−1), particularly in the cold season (8.0% K−1). Combining precipitation frequency and intensity, total precipitation amount has a negligible sensitivity to the warming trend, and the consequent trend in China is limited. Moderate and heavy precipitation amounts are dominated by their frequencies. [ABSTRACT FROM AUTHOR]

The potential predictability of seasonal extreme precipitation accumulation (SEPA) across mainland China is evaluated, based on daily precipitation observations during 1960-2013 at 675 stations. The potential predictability value (PPV) of SEPA is calculated for each station by decomposing the observed SEPA variance into a part associated with stochastic daily rainfall variability and another part associated with longer-time-scale climate processes. A Markov chain model is constructed for each station and a Monte Carlo simulation is applied to estimate the stochastic part of the variance. The results suggest that there are more potentially predictable regions for summer than for the other seasons, especially over southern China, the Yangtze River valley, the north China plain, and northwestern China. There are also regions of large PPVs in southern China for autumn and winter and in northwestern China for spring. The SEPA series for the regions of large PPVs are deemed not entirely stochastic, either with long-term trends (e.g., increasing trends in inland northwestern China) or significant correlation with well-known large-scale climate processes (e.g., East Asian winter monsoon for southern China in winter and El Niño for the Yangtze River valley in summer). This fact not only verifies the claim that the regions have potential predictability but also facilitates predictive studies of the regional extreme precipitation associated with large-scale climate processes. [ABSTRACT FROM AUTHOR]

After the end of the 1970s, there has been a tendency for enhanced summer precipitation over south China and the Yangtze River valley and drought over north China and northeastern China. Coincidentally, Arctic ice concentration has decreased since the late 1970s, with a larger reduction in summer than spring. However, the Arctic warming is more significant in spring than summer, suggesting that spring Arctic conditions could be more important in their remote impacts. This study investigates the potential impacts of the Arctic on summer precipitation in China. The leading spatial patterns and time coefficients of the unfiltered, interannual, and interdecadal precipitation (1960-2008) modes were analyzed and compared using empirical orthogonal function (EOF) analysis, which shows that the first three EOFs can capture the principal precipitation patterns (northern, central, and southern patterns) over eastern China. Regression of the Arctic spring and summer temperature onto the time coefficients of the leading interannual and interdecadal precipitation modes shows that interdecadal summer precipitation in China is related to the Arctic spring warming but that the relationship with Arctic summer temperature is weak. Moreover, no notable relationships were found between the first three modes of interannual precipitation and Arctic spring or summer temperatures. Finally, correlations between summer precipitation and the Arctic Oscillation (AO) index from January to August were investigated, which indicate that summer precipitation in China correlates with AO only to some extent. Overall, this study suggests important relationships between the Arctic spring temperature and summer precipitation over China at the interdecadal time scale. [ABSTRACT FROM AUTHOR]