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The uneven changes in potential evapotranspiration (PET) in response to temperature rise are called the 'evapotranspiration paradox' phenomenon, which is expected to intensify further under a warming climate. In this paper, we explored the spatial–temporal changes in the future 'evapotranspiration paradox' phenomenon over China and its 10 major river sub‐regions under different climate change scenarios. Thus, this paper uses four global climate model outputs under seven shared socioeconomic pathway‐based scenarios (SSP1‐1.9, SSP1‐2.6, SSP2‐4.5, SSP3‐7.0, SSP4‐3.4, SSP4‐6.0 and SSP5‐8.5) from the sixth phase of the Coupled Model Intercomparison Project (CMIP6). Considering the latest IPCC's 6th Assessment Report (AR6), this research emphasizes the 2021–2040 (near‐term), 2041–2060 (mid‐term) and 2081–2100 (long‐term) periods to anticipate the 'evapotranspiration paradox' phenomenon. In this study, PET is estimated based on the modified Penman–Monteith (P‐M) method (considering CO2). Furthermore, the paradox phenomenon in this study is defined considering two pivotal conditions: the surface temperature increases but the evaporation decreases (Type I), and the temperature decreases but the evaporation still tends to increase (Type II). The results show that there were only Type I 'evapotranspiration paradoxes' that existed in the historical period, which were dominant especially before the 1990s. Nearly 50% of the areas experienced the Type I 'evapotranspiration paradox' phenomenon that occurred during 1975–1994 and 1995–2014. Spatially, it covered 100% of the area of the Southeast River (SER) and the Liaohe River (LR) during 1975–1994 and the area of the SER, the HAR, the HHR and the LR during 1995–2014. In the future, the interdecadal growth rate of PET in China is projected to be the highest under the SSP5‐8.5 and the lowest under the SSP3‐7.0 with spatial variation. Importantly, the largest areas of approximately 36% and 45% with the Type I phenomenon are inclined to occur under the SSP1‐1.9 and SSP4‐6.0, respectively, over the long‐term period (2081–2100). The area with the Type I phenomenon will be less than 20% in the near‐term, and it is less than 12% in the mid‐term period. For the Type II evapotranspiration paradox, the uppermost 45% of the area is expected to experience the Type II phenomenon under SSP1‐1.9 during the mid‐term period, while it is 30% under SSP1‐2.6 during the long‐term period. However, this study's findings provide the scientific basis for formulating adaptation and mitigation strategies to combat 'evapotranspiration paradox'‐related extremes at regional scales. [ABSTRACT FROM AUTHOR]

A strong cooling event refers to a sharp change in the average temperature over a short period. The rapid change of temperature has important effect on human health and is highly concerned recent years. Based on the observed temperature data set from stations in Southwest China (SWC) from 1979 to 2017, this paper analyses the characteristics of the strong cooling event (SCE). The result shows that SCE occurs with the highest frequency during the time from February to May. Among them, the frequency of SCE in February exhibits an abrupt change before and after 2005 with a significant increase. Further study reveals that the change of SCE frequency in February is associated with the large‐scale background circulation patterns. After 2005, there is a cyclonic circulation anomaly in Northeast Asia and an anticyclonic circulation anomaly in the Tibet Plateau (TP). This pattern provides a favourable condition for the southward movement of cold air mass, thereby increasing the frequency of SCE in SWC. Furthermore, it is revealed that there is a strong correlation between the variation of SCE frequency in February and sea surface temperatures (SST) in the Northwest Pacific in January before 2005. The cold SST anomaly could favour the occurrence of extreme TD events in SWC through vertical circulation. After 2005, the correlation between SCE and Northwest Pacific SST is not significant. The sea ice in the northern Barents Sea and Kara Sea becomes the dominant impact factor. The abnormally low sea ice concentration is conducive to strengthen the meridional circulation over East Asia, leading to an increasing frequency of SCE in SWC. [ABSTRACT FROM AUTHOR]

Moisture sources and transport processes play a critical part in hydrological cycle and determine regional precipitation. This paper utilizes the Water Accounting Model‐2layers (WAM‐2layers) and the ERA5 reanalysis data to track the sources of precipitation over the Pearl River Basin (PRB). The contribution of external moisture and the role of local recycling are investigated. The results show that during the period from 1980 to 2020, oceanic sources including the western North Pacific and Indian Oceans serve as the primary moisture sources of precipitation over the PRB. The contributions to total seasonal precipitation are respectively 62.57% in MAM, 54.79% in JJA, 43.70% in SON and 60.88% in DJF. By contrast, the contribution of local recycling is generally below 5.50%. In the dry years of 1994, 1997 and 2001, the contribution of terrestrial sources is about 19.22%; in the wet years of 1989, 2009 and 2011, the contribution is about 16.31%. The summer precipitation anomalies are mainly attributable to moisture anomalies from the Equatorial Indian Ocean in the wet years and from Southeast Asia in the dry years. Furthermore, vertically integrated moisture flux anomalies over the boundaries of the PRB are generally the result of anomalous wind rather than anomalous moisture. In the wet years, low‐pressure systems induce strong cyclonic moisture transports, increasing the PRB precipitation. In the dry years, high‐pressure anomalies over the PRB block the moisture transports from the Indian Ocean and western North Pacific. [ABSTRACT FROM AUTHOR]

Drought seriously endangers the development of agro‐pastoral ecotone in arid and semi‐arid regions. However, drought evolution characteristics of semi‐arid sandy grassland and its drivers are not well understood in the complex climate change context. Thus, in this paper, the revised standardized precipitation evaporation indices on one‐month (SPEI‐1) and growing‐season (SPEI‐6) scale, flash drought and dry spells (DS) were calculated as drought indicators, and the temporal variabilities and meteorological drivers of drought in Horqin Sandy Land during the growing period (April–September) from 2007 to 2021 were studied. The results showed that SPEI‐1 and SPEI‐6 exhibited negative trends and periodic change. This drought aggravation was manifested in increased grades and numbers of drought months. Flash droughts can occur every month during the growing season. And its occurrence was not only positively correlated with all drought events in frequency but also synchronized in time. The increased number of DS showed an asymmetrical shift towards 7‐day‐and‐longer DS. SPEI sensitivity to precipitation (P) was noticeably higher than to atmospheric evapotranspiration demand (AED) at both monthly and growing season scales. SPEI sensitivity to AED was modulated by P amounts, which was higher during low P period. Apart from the amounts of P and AED, their temporal variability also strongly determined how they affect the drought severity. P was also the main driver for flash drought and long DS, but AED with larger amount and higher variability is the reason for their aggravation. Our results demonstrate the complexity of drought intensification in semi‐arid sandy grasslands and highlight the important role of AED anomalies in it. [ABSTRACT FROM AUTHOR]

This paper analyses the intraseasonal evolution of the winter haze pollution over the Beijing‐Tianjin‐Hebei (BTH) region in China between 1979 and 2013, and the influences of the atmospheric intraseasonal oscillations (ISOs) in mid–high latitudes. Two significant ISO signals of 10–20‐day and 20–40‐day are identified from the winter haze pollution over the BTH region, and their superposition notably contributes to the occurrence of haze pollution. On the 10–20‐day timescale, the haze pollution is intimately associated with a mid–high‐level southeastward propagating wave train that originates from the North Atlantic. With the wave evolution, an anomalous anticyclone reaches the Korean Peninsula–Japan, leading to strong descents and anomalous southerly winds over the BTH region, favourable for haze pollution. On the 20–40‐day timescale, the atmospheric wave train originates from the eastern North America, propagates eastward to the northwestern Lake Baikal, and then turns southward to the northeastern China–Japan. The peak stage of the haze pollution is related to the resultant zonal dipole, with the anomalous cyclone over the northwestern Lake Baikal and the anomalous anticyclone over the northeastern China–Japan. The dominance of the mid–upper tropospheric anticyclone over the BTH region suppresses the development of convection, thus hindering the vertical diffusion and wet deposition of pollutants. Moreover, the anomalous westerly winds between the dipole weaken the incursion of cold mass from higher latitudes, thus further contributing to the peak of haze pollution. [ABSTRACT FROM AUTHOR]

This paper describes the construction of a 0.25° × 0.25° daily soil temperature (TS) data set at six soil depths (i.e., 0, 5, 10, 15, 20, and 40 cm) based on a homogenized TS at more than 2,000 meteorological stations across mainland of China for 1960–2017. First, at each station, the observed TS is split into a daily climatology of 1981–2010 and a daily anomaly for 1960–2017. Then, they are respectively interpolated to 0.25° × 0.25° horizontal resolution by using the thin‐plain spline and the angular distance weight interpolation methods. Finally, a gridded multilayer TS data set is constructed from the sum of the above two gridded products. Latitude, longitude, and high‐resolution digital elevation models are explicitly incorporated into the interpolation processes. Selectivity tests indicate that the optimal interpolation distance for the TS anomaly field is 500 km, where the gridded data set may have maximum coverage of the entire Chinese mainland. The results show that the gridded TS climatology is slightly lower than the station observations. The differences between gridded and the station‐based TS varies ±3°C, with relatively large in SW and TIBET. For the gridded anomaly fields, the cross‐validation shows that the mean absolute errors between gridded and station‐based TS are generally less than 0.6°C in the YZ, SW, and SC, but they are above 1.0°C in the NW and TIBET due to the sparse station distribution and large topographic relief. From 1961 to 2016, the seasonal variability of the gridded TS is generally consistent with that of the surface air temperature. The gridded TS over the majority of land displays significantly positive trends in both summer and winter (p > 95%), indicating an overall warming land surface in China. The long‐term gridded TS data not only preserves the spatial features represented in the station observations, but also provides a spatio‐temporal continuous long‐term product of mainland China. Thus, it may be used in future studies, for example, evaluation of land surface model simulations, validation of satellite retrievals, land‐atmosphere interactions, and climate change. [ABSTRACT FROM AUTHOR]

This paper utilizes reanalysis data and statistical methods to elucidate the physical mechanisms of intraseasonal variations of precipitation over southern China during the boreal winter, as well as the two primary factors influencing these variations. Anomalous southerly (northerly) wind over southern China will result in the strong moisture convergence (divergence) in enhanced (suppressed) scenarios, and the stronger positive (negative) horizontal advection of absolute vorticity at upper troposphere induces the anomalous ascending (descending) motion in enhanced (suppressed) scenarios. The Madden–Julian oscillation (MJO) in the tropics and a wave train over the North Atlantic and Eurasia with four activity centres in the mid–high latitudes (referred as NAE‐wave train) are the two primary factors that modulate the intraseasoanl precipitation over southern China. The intraseasonal circulation induced by MJO and NAE‐wave train exhibits distinct features, resulting in different physical mechanisms of their influences. The moisture flux divergence anomalies over southern China associated with MJO mainly stem from the meridional moisture convergence, whereas the meridional moisture advection is the first contributor in the influence of NAE‐wave train. The anomalous vorticity advection at upper troposphere associated with MJO is primarily influenced by the meridional advection, but that associated with NAE‐wave train is dominated by the zonal advection. Anomalous precipitation induced by MJO is concentrated mainly over South China, while that caused by NAE‐wave train is primarily located in the mid–lower Yangtze River basin. Therefore, different phases locking of MJO and NAE‐wave train could lead to various precipitation anomalies over southern China. [ABSTRACT FROM AUTHOR]

Increasing variability of precipitation induced by climate change raises uncertainties for ecosystem services and agricultural production in the Poyang Lake Basin (PLB), China. Reanalysis precipitation datasets (RPDs) are attractive alternatives for monitoring the hydro‐climate cycles. However, their applicability in China has mainly been evaluated at the national scale, while less attention has been paid to the PLB or southeastern China. Here, we apply various metrics to evaluate the magnitude and spatial similarity of annual, monthly, different intensities and the spatial structure of precipitation from four reanalysis—the fifth global atmospheric analysis dataset of the European Center for Medium‐Range Weather Forecasts (ECMWF) (ERA5), Interim ECMWF Reanalysis (ERA‐Interim), Japanese 55‐year Reanalysis project (JRA55) and Modern‐Era Retrospective analysis for Research and Applications, Version 2 (MERRA‐2), against the rain‐gauges over the PLB during 1980–2018. The results showed that the detection capacity of ERA5 and MERRA2 shifted around 2002, whereas that of ERA‐Interim and JRA55 did not substantially change. Before 2002, ERA‐Interim had the lowest biases for the magnitude of annual, monthly and different intensities of precipitation (except for heavy rain), while ERA5 and MERRA2 had strengths in capturing spatial correlation. Notably, ERA5 and MERRA2 had region‐wide wet and dry biases, respectively, before 2002, which can be attributed mainly to the estimation of flood season precipitation (from April to June) and heavy rain. In contrast, the fractional contribution of light–moderate rain was underestimated and overestimated by ERA5 and MERRA2, respectively. However, after 2002, because of the improved reproducibility of flood season precipitation and heavy rain magnitude, the systematic biases of ERA5 and MERRA2 significantly decreased, especially for ERA5, which outperformed other RPDs on all aspects of precipitation. The conclusions of this paper suggest that the variation of applicability over time should be seriously tested before the utilization of RPDs in hydro‐climate analyses. [ABSTRACT FROM AUTHOR]

The cold surge (CS) is an extreme climate event that frequently affects China. By using a 0.25° × 0.25° gridded observation dataset provided by the China Meteorological Administration (CN05.1), this paper investigates the spatial–temporal characteristics of various CSs in China during 1962–2018. According to the duration and coverage area (CA), CSs are classified into the short‐lived cold surges (SLCSs), the persistent cold surges (PCSs) and the extensive and persistent cold surges (EPCSs). They are also divided into the weak cold surges (WCSs), the strong cold surges (SCSs) and the super strong cold surges (SSCSs) based on the temperature drop (ΔT). The extreme cold surges (ECSs) are also defined and occur 38 times over 57 years. The total CSs and various CSs all display patterns of higher frequencies in the northeast and lower frequencies in the southwest. Northeast China and Inner Mongolia are frequently hit by various CSs, but the frequencies show overall downward trends in the regions during 1962–2018. The ΔT of the total CSs and ECSs both show significant decreasing trends in the whole of China from 1962 to 2018. From 1962 to 2018, the annual frequency and the ΔT of the total CSs both show decreasing trends. SLCSs and WCSs frequencies show overall increasing trends, but other kinds of CSs show overall decreasing trends. The annual frequencies of the total CSs and various CSs all have trend abrupt changes around 2000. The ΔT of ECSs shows a sharply increasing trend during 1962–2018. The total CSs and all kinds of CSs frequencies have a significant periodic oscillation. ECSs occur most in February. The total CSs and other kinds of CSs occur most in January. There are obvious differences between the multiyear average ECSs frequencies before 2000 and after 2000. [ABSTRACT FROM AUTHOR]

Moisture transport, associated with moisture sources and synoptic‐scale weather conditions, is a key dynamic process of precipitation events. Using the K‐means clustering method and the FLEXPART Lagrangian particle dispersion model, this paper investigates moisture contributions from different source regions to extreme precipitation in the first rainy season (hereafter FRS) over South China. In average, land regions contribute more to the FRS extreme precipitation over South China than the ocean regions. The main source regions are Southeast Asia (22.7%), South China (17.2%), the South China Sea (14.3%), and the Bay of Bengal (8.3%). Extreme precipitation events are classified into three types by the K‐means clustering based on 850 hPa geopotential height, which are all characterized by an anomalous low‐pressure system over South China with varying intensity and locations. The distribution of geopotential height anomaly for Type I (30.3%) is characterized the low trough extending from Japan to South China, while Type II (42.5%) and Type III (27.2%) are characterized by "west negative–east positive" and "north positive–south negative" patterns over East Asia with anomalous cyclone over South China, respectively. The much larger contribution of land sources than ocean regions are mainly concentrated in Type I and Type III, of which the contribution from each source region is similar. Ocean sources play a more important role in Type II and are mainly from the Indian Ocean (16.2%) associated with the onset of South China Sea summer monsoon. [ABSTRACT FROM AUTHOR]

The amount of winter precipitation over southeast China (SCWP) is significantly affected by the El Niño–Southern Oscillation (ENSO), with generally an enhanced SCWP response to El Niño events. In this paper, we find that this relationship shows remarkable nonstationarities on the multidecadal timescale. Running ENSO–SCWP correlation maintains statistically significant before the mid‐1960s and after the mid‐1990s but not during the interim period, which exhibits an approximate synchronized temporal evolution with the Atlantic Multidecadal Oscillation (AMO). A statistical method for interpreting nonstationary relationships is then applied to quantitatively verify and measure this possible AMO modulation. It is demonstrated that the nonstationary ENSO–SCWP correlation can be expressed to a large extent by the influence of the AMO–ENSO nonlinear effect (AMO*Niño3.4) on the SCWP. This influence intensifies the ENSO–SCWP relationship during the positive AMO phase but weakens it during the negative AMO phase. Therefore, the nonstationarity in the ENSO–SCWP relationship comes predominantly from an AMO modulation via this key nonlinear effect. We further suggest that a positive AMO favours a westward shift of ENSO sea surface temperature (SST) anomaly pattern in the tropical Pacific. Correspondingly, the anomalous western North Pacific (WNP) anticyclone also migrates westward, which gives rise to pronounced moisture transports and vertical motions over the adjacent southeast China, thereby resulting in a significant ENSO–SCWP relationship. In contrast, during the negative AMO phase, the eastward‐shifted ENSO SST and WNP anticyclonic anomalies produce significant atmospheric anomalies primarily to the east of the Chinese mainland, thus having less effect on the SCWP. [ABSTRACT FROM AUTHOR]

General circulation models (GCMs) are developed to simulate the past climate and generate future climate predictions. In the context of global warming, their important roles in identifying possible solutions to water resources planning/management are recognized by the world. However, in actual and regional implementation, due to many factors like initial and boundary conditions, parameters and model structures and so forth, there are great variabilities and uncertainties across the future climate projections of GCMs outputs, which has attracted criticism from water resources planners. Thus, the GCMs usually must be evaluated for assessing their performances in simulating the historical observations. Currently, there are many different conclusions and opinions as to whether the optimal individual model is more advantageous or whether the combined consideration of MME works better. The purpose of this paper is to compare the advantages and disadvantages between the selection of the optimal single GCM and multi‐model ensemble (MME) based on one of the more objective selection methods called TOPSIS. The results show that the performances of GCMs in simulating precipitation and temperature in different climate subregions over China are not identical. For CMIP6 GCMs simulations, the optimal precipitation GCM is CMCC‐CM2‐SR5 for EC, MIROC6 for SC, SWC and NWC, CESM2‐WACCM for NC and NEC, and FGOALS‐g3 for QTP. As for temperature, only NESM3 and BCC‐ESM1 are the optimal GCM for QTP and NWC, respectively; in other subregions, MME is better than single GCM. In general, a simple arithmetic averaging approach employed to generate the MME model is not superior to the optimal GCM, although the error metric with the observed data is reduced, at the cost of a severe compression of the interannual variability. [ABSTRACT FROM AUTHOR]

The hydrological projections provided by the outputs of Global Climate Models (GCMs) combining hydrological models include multi‐source uncertainties, which may challenge the formulation of relevant adaption and mitigation policies. In this paper, the overall uncertainty and the relative contribution of each uncertainty component were investigated for hydrological projections over 408 watersheds in China by using 3 shared socioeconomic pathway emission scenarios (SSP1‐2.6, SSP2‐4.5, and SSP5‐8.5), 21 GCMs, 8 bias correction methods, 4 hydrological models, and 2 sets of optimized hydrological model parameters. The results show that the total uncertainty (T) is mainly contributed by uncertainty related to global climate models (G), with the mean percentage ranging from 60.4 to 64.1%, followed by the interaction uncertainties among all components, with the mean percentage ranging from 22.0 to 26.4%. The uncertainty contribution of hydrological models (H) (6.1–9.4%) ranks third, followed by emission scenarios (S) (2.9–5.9%) and bias correction methods (B) (0.2–1.1%). The uncertainty contribution of the optimized hydrological model parameters (P) (0.2–0.3%) is almost negligible. In terms of spatial variability, the relative contribution of uncertainty related to global climate models (G) is the highest in the near future for northern China (67.5–70.6%) and in the far future for southern China (66.1–66.7%). However, it was found to be lower for the Tibetan Plateau and northwestern China (45.3–57.9%) in the near and far future. The relative contribution of hydrological model uncertainty is higher for southwestern and northwestern China and the Tibetan Plateau (7.2–19.5%) and lower for northern, eastern, and southern China (2.5–6.6%). This study highlights the importance of including multiple GCMs and hydrological models in hydrological impact studies to consider their overall uncertainty. The development of global climate models and hydrological models is still the best way to reduce the uncertainty of climate change impact studies. [ABSTRACT FROM AUTHOR]

In this paper, the connection between the November northeast Asian snow cover and the following winter precipitation over southern China is studied for the period of 1979–2014. The results indicate that, when there is more November snow cover over northeast Asia, the precipitation in southern China is depressed during the following January, and vice versa. Mechanism analysis suggests that the troposphere‐stratosphere interaction may play an important role in the delayed connection between the two. The more November snow cover over northeast Asia could enhance the vertical propagation of the wave activity, and it could also weaken the westerly winds over northern Asia in the troposphere by decreasing the meridional temperature gradient over the region. The persistent weakening of the tropospheric westerly winds is in favour of the upward propagation of the wave activity into the stratosphere in November and December, and the associated convergence anomalies of the E‐P flux in the stratosphere induce the weakened stratospheric polar vortex. Thereafter, the abnormal polar vortex propagates downward to the lower troposphere and produces a low pressure anomaly to the east of Lake Baikal during January. Such a low pressure anomaly tends to strengthen the southward invasion of the cold air to southern China, which is unfavourable for the precipitation there. This leading signal of the November snow cover over northeast Asia provides a potential source for the prediction of the January precipitation over southern China. [ABSTRACT FROM AUTHOR]

Along with the rapid urbanization and economic development, the Yangtze River Middle‐Reach urban agglomeration (YRMR) has suffered from increasingly serious environmental problems. Characterizing the long‐term dynamics of aerosol optical depth (AOD) in YRMR is of important significance for scientific control of aerosol pollutants over this region. Previously, numerous researches have analysed the temporal and spatial characteristics of AOD in different regions through statistical values of AOD time series or using trend analysis methods based on linear regression models. It is challenging to approximate nonlinear trends and identify change points of AOD time series. This paper proposed a new methodology for investigating the dynamics of AOD over the YRMR region on a monthly basis by using the Terra MODIS Collection 6.1 Level 2 aerosol products (MOD04_L2) during 2001–2017. A three‐dimensional spatio‐temporal interpolation method was used to generate gap‐filled monthly AOD maps, and then a generic Bayesian time series decomposition algorithm was applied to analyse the trends and change points of monthly AOD time series. The results showed that the areas with high AOD values were mainly located in the core cities and the connecting belts. Strong positive AOD anomalies had been observed during 2006–2011, whereas the positive anomalies were typically intermingled with negative anomalies and it indicated that the evolution patterns of AOD for different regions were different and influenced by fluctuations. Trend analysis of the monthly mean AOD values indicated that AOD in YRMR increased first, then fluctuated, and finally decreased. Although it was difficult to separate the increasing and fluctuating periods from each other due to the fluctuation, the decreasing trend after 2011 was significant, and a significant drop of AOD had been observed since 2014. Long‐term AOD variations were closely related to national policies, and the results could provide useful references for regional environmental assessment and decision‐making. [ABSTRACT FROM AUTHOR]

This paper analyses the different relationships between the two types of South Asian highs (SAH)—the southern mode of the SAH (SSAH) and the traditional SAH in its entirety (ESAH)—with respect to the variations in summer rainfall over East Asia. The ESAH is closely related to summer rainfall over northeastern China, whereas the SSAH is closely linked to summer rainfall over the Yangtze River valley, northern China, and Japan. Above‐normal rainfall tends to occur over northeastern China in strong ESAH years, whereas strong SSAH years tend to yield above‐normal rainfall over the Yangtze River valley and Japan together with below‐normal rainfall over northern China. The westerly jet and the western Pacific subtropical high (WPSH) shifts northward associated with a strengthened ESAH. The related anomalous southwesterly winds to the northwestern side of the WPSH transports abundant water vapour to northeastern China and leads to above‐normal rainfall there. In contrast, the westerly jet shifts southward and WPSH shifts southwestward to the South China Sea associated with a strengthened and southeastward‐shifted SSAH. Accordingly, a cyclonic anomaly appears over Northeast Asia and mid‐latitude western northern Pacific and an anticyclonic anomaly occurs over subtropical western North Pacific. The associated southwesterly wind anomalies over the Yangtze River valley and Japan contributes to above‐normal rainfall over these regions via transporting sufficient amount of water vapour. In addition, the anomalous northerly winds to the western flank of the cyclonic anomaly results in below‐normal rainfall over northern China via carrying drier air southward. Furthermore, the preceding winter ENSO events may play a more important role in the SSAH variation via modulating India Ocean SST. [ABSTRACT FROM AUTHOR]

Two skilful 2‐month‐leading hybrid downscaling prediction schemes in October for winter surface air temperature (SAT) over China are proposed in this paper. The schemes are based on the year‐to‐year increment approach and the coupled climate patterns between the winter SAT over China and its predictors. Observed North Pacific sea surface temperature (SST) from the preceding July to September, Arctic sea ice concentration (SIC) in the preceding August and winter sea level pressure (SLP) over pan Eurasia from version 2 of the Climate Forecast System (CFSv2) are selected as the predictors based on the fundamental physics. Individual‐predictor schemes (IP‐schemes), that is, SLP‐scheme, SST‐scheme, SIC‐scheme, indicate that these predictors exhibit prediction skills in different regions. Multi‐predictor scheme I (MP‐schemeI) is developed by combining three predictors. However, MP‐schemeI shows limited skill in predicting SAT over Northeast China (NECTA), due to the limited skill of CFSv2 over the extratropics. Thus, MP‐schemeII is established, in which a hybrid downscaling model for NECTA is constructed. These two MP‐schemes have comparable prediction skill over China, but MP‐schemeII outperforms MP‐schemeI over NEC. The temporal (spatial) anomaly correlation coefficient (ACC) increases from 0.23 (0.15) in MP‐schemeI to 0.36 (0.21) in MP‐schemeII, and the ratio of the same sign of anomalous years (Anomalous‐RSS) improves from 39.1% to 56.5% over NEC. For the winter SAT over China, the MP‐schemes greatly enhance the prediction compared with CFSv2 outputs and the IP‐schemes. The temporal (spatial) ACC increases from 0.29 (0.05) in CFSv2 to 0.52 (0.29) in the MP‐schemes, and the station‐average root‐mean‐square error decreases by about 48.0% compared with CFSv2. Moreover, the RSS (Anomalous‐RSS) of the winter SAT over China is 55.9% (47.4%) in CFSv2 and 64.7% (63.2%) in the MP‐schemes. This indicates that the MP‐schemes perform better in predicting anomalous winters. [ABSTRACT FROM AUTHOR]

A good understanding of spatiotemporal characteristics of historical droughts is important for managing and tackling drought hazards. This paper aims to investigate spatiotemporal variations of drought in mainland China over 1961–2016 based on the standardized precipitation evapotranspiration index (SPEI) at the 1‐ and 12‐month timescales. The trend significance and magnitude of 12‐month SPEI were analysed using the modified Mann–Kendall (MMK) method and Sen's slope values. The empirical orthogonal function (EOF) and ensemble empirical mode decomposition (EEMD) were applied to analyse the spatial patterns and periods in 1‐month SPEI series. The results showed that the temporal fluctuations of SPEI were weaker as the timescale increased. The droughts in 1960s were the severest than in other decades. The sites with SPEI < −5 (denoting the extreme droughts) mainly located in the northwestern and southwestern China. An overall wetter trend was detected in most regions of China, except the belt from northeastern to middle and southwestern China. The 1‐month SPEI had shorter than 1.20‐year of mean periods for the seven sub‐regions and China, while had 0.22–2.95 years of mean periods at different sites. Residuals (decomposed from 1‐month SPEI) showed increasing trends in most of the sub‐regions except sub‐region 3. In northern and northwestern China, longer periods of SPEI were detected. The highest values of EOF1 and EOF2 illustrated the eastern and northeastern China were drought‐sensitive areas. From the correlations between 1‐month SPEI and the atmospheric circulations, the AO was the main physical factor that influenced drought occurrence in mainland China. The identified spatiotemporal characteristics of SPEI could offer references for drought prevention and management in China. [ABSTRACT FROM AUTHOR]

From the perspectives of remote sensing and climatic factors like surface meteorological parameters, large‐scale atmospheric circulations, and external forcing factors (EFFs), the authors synthesize and review spatiotemporal variations of PM2.5 over North China and how climate anomalies affect autumn and winter haze variability in North China according to recent studies. This review focuses on both interannual and interdecadal timescales. It is shown that circulations play an important role in influencing haze variability. Atmospheric circulations, which would be modulated by EFFs like sea surface temperature, sea ice, and snowpack, can affect the climate variability in haze over North China via modulation of surface‐layer parameters that are closely connected with the haze phenomenon. Therefore, EFFs are deemed significant factors impacting the climate variability of haze over North China, serving as paramount precursory signals for haze prediction. Furthermore, this paper suggests potential future research directions for haze variability studies in North China on the basis of summarizing and concluding the associated processes/mechanisms on how climatic factors affect haze variability, which could provide reference for treating and forecasting in situ hazy conditions. [ABSTRACT FROM AUTHOR]

The roles of moisture sources and transport in intraseasonal precipitation variabilities during the preflood season over South China are complex and different. In this paper, ERA‐Interim reanalysis data that were collected four times daily from 1979 to 2017 are used to analyse the variation and influence of moisture transport in intraseasonal precipitation during the preflood season over South China. Using the Hybrid Single‐Particle Lagrangian Integrated Trajectory model, fixed atmospheric moisture sources are defined: land area source (LD source), Indian Ocean source (IO source), Pacific Ocean source (PO source), South China Sea source (SCS source), and South China source (SC source). Sea source moisture transport accounts for more than 75% of the total precipitation during the preflood season, which is the most important moisture source in South China. For April, southeasterly moisture transport, which includes PO source and SCS source moisture transports, is the major moisture transport over South China. Then, the IO source and SCS source precipitation increased significantly during May. During June, the IO source precipitation accounted for 43.75% of the total precipitation, thus dominating precipitation over South China. In addition, there is a significant difference in the interdecadal variation in the preflood season precipitation before and after the Indian summer monsoon onset. Before the Indian summer monsoon onset, the land‐sea thermal contrast decreased, which led to a significant interdecadal reduction in the IO source, PO source, and SCS source moisture transports. After the Indian summer monsoon onset, the increase in IO source moisture transport is the primary cause of the interdecadal increase in precipitation over South China. [ABSTRACT FROM AUTHOR]

Seasonal prediction of extreme precipitation has long been a challenge especially for the East Asian Summer Monsoon region, where extreme rains are often disastrous for the human society and economy. This paper introduces a decision‐tree (DT) method for predicting extreme precipitation in the rainy season over South China in April–June (SC‐AMJ) and the North China Plain in July–August (NCP‐JA). A number of preceding climate indices are adopted as predictors. In both cases, the DT models involving ENSO and NAO indices exhibit the best performance with significant skills among those with other combinations of predictors and are superior to their linear counterpart, the binary logistic regression model. The physical mechanisms for the DT results are demonstrated by composite analyses of the same DT path samples. For SC‐AMJ, an extreme season can be determined mainly via two paths: the first follows a persistent negative NAO phase in February–March; the second goes with decaying El Niño. For NCP‐JA, an extreme season can also be traced via two paths: the first is featured by "non El Niño" and an extremely negative NAO phase in the preceding winter; the second follows a shift from El Niño in the preceding winter to La Niña in the early summer. Most of the mechanisms underlying the decision rules have been documented in previous studies, while some need further studies. The present results suggest that the decision‐tree approach takes advantage of discovering and incorporating various nonlinear relationships in the climate system, hence is of great potential for improving the prediction of seasonal extreme precipitation for given regions with increasing sample observations. [ABSTRACT FROM AUTHOR]

Drought occurs more frequently in the context of climate change and threatens water security worldwide. An appropriate fitting distribution is crucial for accurately identifying drought using drought indices. Here, seven two‐parameter distributions (Gamma, Gumbel, Logistic, Log–Logistic, Log‐normal, Normal, and Weibull) and four distributions (general logistic, generalized extreme value, Normal, and Pearson Type III) are applied to calculate the standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI), respectively, to choose the most appropriate fit for the 541 stations in China. The results show that, in most cases, Gamma and general logistic were the best distributions for SPI and SPEI, respectively. Nevertheless, we noted that Pearson Type III and generalized extreme value also fit the SPEI series well, indicating the importance of distribution fitting assessment for various regions. The annual and seasonal drought evolutions across China were clarified, with drought decreasing significantly in western Northwest China (annually and each season), northern North China (spring and winter), the Tibetan Plateau (spring), and the lower reaches of the Yangtze River (winter) and increasing mainly in South China (spring) and western South China (summer and autumn). The intensity, duration and severity of light, moderate, and severe drought were also detected; the results suggest that drought in China is mainly concentrated around the changes in light and moderate drought. Additionally, we assessed the sensitivity of drought evolution to various meteorological variables. The most sensitive variable in South China, North China and the Tibetan Plateau is precipitation, followed by wind speed, temperature, relative humidity, and sunshine duration; in Northwest China, the order is wind speed, precipitation, temperature, relative humidity, and sunshine duration. Furthermore, the correlation results also indicate that the drought evolution is affected by the multivariate ENSO index, while the influencing characteristics are different in various seasons and regions. The results in this paper contribute to drought mitigation and the effective utilization of water resources in China. [ABSTRACT FROM AUTHOR]

In this paper, we evaluate a 48‐member multiphysics ensemble using the Weather Research and Forecasting (WRF) model for the JJA extreme precipitation and temperature in 2003 over the CORDEX‐EA‐II domain. The simulated precipitation and temperature are reasonable in the subregions controlled by a large‐scale circulation, yet the biases for both precipitation and temperature are evident over the subregions where the effects of mesoscale processes are important. The performance of various combinations of WRF physical schemes for simulating the JJA precipitation is dependent on the region. Meanwhile, the cumulus and microphysical schemes have substantial influences on the simulation of precipitation, and the land surface models and cumulus schemes play crucial roles in the surface temperature. Our analysis shows that the combination of Noah for the land surface process, Lin for the microphysics, G3D for the cumulus parameterization, and CAM for the radiation scheme can provide the most reliable reproduction of both precipitation and temperature extremes over China. Ensemble analysis shows that the simulated climate extremes are usually accompanied by a large ensemble spread, implying sensitivities to the model physical processes in some subregions. The simulated wind fields at low‐to‐middle atmospheric levels display responses to the options of the land surface models and cumulus schemes. The essential impact of the land–atmospheric interaction on simulating the extremes can be largely attributed to the active convective processes. WRF has difficulties in reproducing the observed temporal evolution of the rainfall process, which consists of continuous large rainfall episodes in the observation data set during the simulation period. [ABSTRACT FROM AUTHOR]

ABSTRACT This paper presents an evaluation study of the Regional Climate Model version 4.3 ( RegCM4.3) over the Loess Plateau in northern China, which is a semi-arid region characterized by complex topography. During recent years, a series of reforestation programmes have been implemented across the region that might influence the local climate in complex ways. To better understand the local climate, the RegCM4.3 was applied to simulate the present-day conditions over the Loess Plateau. The simulation was carried out from 1990 to 2009 at the 50-km horizontal resolution, with lateral boundary conditions taken from the ECMWF-Interim reanalysis. A series of climate variables and processes were evaluated during the winter and summer seasons, such as 2-m air temperature, precipitation, wind circulation, surface energy balance, full moisture budget, and cloud radiative forcing (CRF). The possible origins of the simulation bias and the physical linkages with other model processes were examined. In general, RegCM4.3 is able to reproduce both the spatial and temporal features of the regional climate over the Loess Plateau. However, there are still biases in some meteorological variables including precipitation and 2-m air temperature. In particular, the model tends to produce cold biases during winter and underestimate precipitation during summer. Further analyses indicates that the cold biases in winter may have resulted from the deficiency of the downward longwave radiation fluxes, excessive ground heat fluxes, and negative temperature advection by the seasonal mean circulation. These processes are primarily triggered by deficiencies in CRF and excessive northwesterlies over the plateau. The underestimated precipitation during summer is associated with a weak southerly monsoon in the model. A full moisture budget analysis reveals that the dry bias in this region can be mainly attributed to model deficiency in moisture advection and convergence, and to a lesser extent to that in surface evaporation. [ABSTRACT FROM AUTHOR]

ABSTRACT The biases in the Global Circulation Models ( GCMs) are crucial for understanding future climate changes. Currently, most bias correction methodologies suffer from the assumption that model bias is stationary. This paper provides a non-stationary bias correction model, termed residual-based bagging tree ( RBT) model, to reduce simulation biases and to quantify the contributions of single models. Specifically, the proposed model estimates the residuals between individual models and observations, and takes the differences between observations and the ensemble mean into consideration during the model training process. A case study is conducted for 10 major river basins in Mainland China during different seasons. Results show that the proposed model is capable of providing accurate and stable predictions while including the non-stationarities into the modelling framework. Significant reductions in both bias and root mean squared error are achieved with the proposed RBT model, especially for the central and western parts of China. The proposed RBT model has consistently better performance in reducing biases when compared with the raw ensemble mean, the ensemble mean with simple additive bias correction, and the single best model for different seasons. Furthermore, the contribution of each single GCM in reducing the overall bias is quantified. The single model importance varies between 3.1% and 7.2%. For different future scenarios ( RCP 2.6, RCP 4.5, and RCP 8.5), the results from RBT model suggest temperature increases of 1.44, 2.59, and 4.71 °C by the end of the century, respectively, when compared with the average temperature during 1970-1999. [ABSTRACT FROM AUTHOR]

More than half the world's population lives in cities. In tropical and subtropical regions, the growth of mega and compact cities are on the rise. The urban climatic issues of heat, humidity, lack of daylight, solar access, and urban ventilation is of topical concern to urban planners and governments. This paper puts forward a notion that a well established view of the low impact of urban climate on planning may be due to the lack of planning on the part of urban climatologists. Overly detailed and precise meteorological information, and excessively sophisticated climatic explanations and knowledge presentation do not help planners; information overload makes planners feel discouraged and ill equipped. In this paper, the understanding of Hong Kong based on the scale of planned decision making is elaborated with examples. Urban climatic information must be presented sequentially to fit the hierarchal process of planning and land use decision making. For better transfer of knowledge and communication, 'prevailing' and 'criticality' should be observed; information overload must be avoided, and spatial information must be presented graphically whenever possible. Scholars have argued that instead of the need for precision and accuracy, most of the time planners need to make balanced and reasonable decisions. Simplicity is the key. Furthermore, the advent of rapid urbanisation in the age of climate change further endows urban climatologists the burden to develop appropriate and easy-to-understand urban climate knowledge for planners. Resolving something complicated into something simple for planners is the only way forward. Copyright © 2011 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

Hong Kong is a high-density sub-tropical city with 7 million people living in an urban area of just over 260 km2. Tall and closely packed buildings are the common urban morphology. How the urban geometry influences the microclimate in summer daytime is a primary planning concern. The sky view factor (SVF) has been commonly used to indicate the impact of urban geometry on air temperature differences in cities. However, only limited discussions in this aspect have been addressed for daytime course in high-rise and high-density urban environment such as Hong Kong. This paper firstly provides a comprehensive review of SVF analysis in urban climatology studies and then presents a simulation approach to investigate the role of SVF in determining summer daytime intra-urban air temperature differences in urban Hong Kong. An ArcGIS-embedded computer program is developed for calculating continuous SVF values for an entire urban environment and an SVF map is generated. The result is evaluated against meteorological data observed in field measurements. The regression analysis shows that the spatial average of SVF values has a close negative relationship with daytime intra-urban temperature differences. The study indicates that SVF is a significant factor for understanding the microthermal climate in Hong Kong's street canyons. The paper further raises discussions on the application of SVF analysis to urban planning. The study demonstrates that the SVF analysis is a useful and effective tool for planners and urban climatologists conducting studies on high-rise and high-density sub-tropical cities. The understanding can provide support for the development of planning standards and good practice. Copyright © 2010 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

ABSTRACT This study investigates the influence of the South Indian Ocean subtropical dipole (IOSD) on spring (March-April-May; MAM) rainfall over central-eastern China (CEC) and its dynamic processes by using station observations of China, Met Office Hadley Centre SST data for the period 1951-2012 and European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis data for the period 1958-2012. It is found that the IOSD event which peaks in the boreal winter can persist to the following spring, with strength slightly weakening. Boreal spring rainfall over CEC, i.e. the middle-lower reaches of Yangtze River, the Yellow River valley as well as regions between them, has a significant correlation with the IOSD event. When the positive (negative) IOSD event occurs in the previous winter, the CEC is dry (wet) in the spring. One of possible mechanisms that the IOSD affects the China spring rainfall is the modulation of the meridional circulation, especially the Hadley cell in the tropic along 100-120°E. In the positive IOSD years, associated with the cold sea surface temperature anomalies (SSTA) and warm SSTA in the southeastern Indian Ocean (SEIO) and southwestern Indian Ocean, there is anomalous ascent over the equatorial Indian Ocean, whereas downward flows over the SEIO and CEC. The Hadley cell over this region intensifies. Anomalous northerly wind at 850 hPa prevails, preventing wet and warm air flow from the low latitudes, which in turn transports less moisture into CEC and favours decreased rainfall. Meanwhile, the CEC is located at the sinking region of the Hadley cell. The atmosphere is fed by low moisture content over this area, also unfavourable for the occurrence of precipitation. This paper suggests that the SSTA in the southern Indian Ocean can be a good predictor for the China spring precipitation and proposes a possible mechanism for the connection of the mid-latitude climate variations of both hemispheres induced by air-sea interaction. [ABSTRACT FROM AUTHOR]

In this paper, ring-width chronologies of pine trees ( Pinus sylvestris var. mongolica) from one sampling site in the northern Greater Higgnan Mountains, China, were constructed. The results of growth-climate responses show that mean temperature is the limiting factor affecting radial growth of pine trees in the study area. Consequently, mean temperature from May to October from 1717 to 2008 has been reconstructed using the standard chronology. For the calibrated period (1957-2008), the explained variance of the reconstruction is 57%. The characteristics of the reconstruction expose that mean temperature has increased since the 1970s, and the decade 2000s and 1990s are also ranked as the warm decades on record. However, this period from 1970s to now is not exceptional within the past 300 years. By applying an 11-year moving average to the reconstruction, three warm periods and three cold periods are evident. The warm and cold periods of the reconstructed mean temperature correspond well with other reconstructions. Power spectral and wavelet analysis demonstrated the existence of significant ∼70- and ∼100-year cycles of variability. Furthermore, the reconstruction and North Atlantic Oscillation Index showed a significant positive correlation ( r = 0.34, n = 136, p < 0.0001). Copyright © 2012 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

One of the great model biases in simulating the East Asian summer monsoon are the warming bias of the summer surface air temperature (SAT) in mid-eastern China in the late 1970s. Previous studies have found that the summer equatorward displacement of the Asian Jet Stream (AJS) could result in SAT cooling in mid-eastern China in the past half century. This paper focuses on the relationship of the meridional displacement bias of the Asian Jet Stream (AJS) with the SAT bias in mid-eastern China in 22 IPCC AR4 models. On the basis of 20C3M simulation outputs, the bias analyses show that the summer SAT bias in mid-eastern China are closely linked to the bias of the subtropical upper-level zonal wind around the AJS core. Climatologically, the summer AJS cores in more than half of IPCC models are north of the observed one, and most of models underestimate the intensity of the AJS. Ten models (bccr_bcm2_0, cccma_cgcm3_1_t63, cnrm_cm3, gfdl_cm_2_0, gfdl_cm2_1, ipsl_cm4, miroc3_2_hires, mpi_echam5, ncar_ccsm3_0, and ukmo_hadgem1) are able to capture the AJS meridional displacement-the distinct feature of the summer AJS-for the influences of climate in eastern China. Among these ten models, bccr_bcm2_0, cccma_cgcm3_1_t63, miroc3_2_hires, mpi_echam5 and ncar_ccsm3_0 fail to simulate the multi-decadal variations of the AJS and cccma_cgcm3_1_t63, cnrm_cm3, ipsl_cm4, mpi_echam5, and ukmo_hadgem1 underestimate large-scale circulations associated with the AJS over eastern China. Thus, merely two models, gfdl_cm_2_0 and gfdl_cm2_1, have the ability in successfully simulating the SAT cooling in mid-eastern China during the late 1970s. These results imply that a good simulation of the AJS is important for weather and climate forecasts and assessments in eastern China. Copyright © 2011 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

The precipitation in China manifests a remarkable quasi-biennial signal. For interannual variability, about 70% stations over China indicate the dominance of a quasi-2-year period. The maximum precipitation variability associated with the quasi-biennial oscillation is located over the Yangtze River valley (YRV) and Huaihe River valley (HRV) as well as South China. This paper attempts to reveal the spatial-temporal evolution of the precipitation in China and related large-scale atmospheric circulation associated with the tropospheric biennial oscillation (TBO) in East Asia by using a season-dependent empirical orthogonal function (S-EOF) analysis approach. The leading two modes of the TBO of summer precipitation in China and associated large-scale circulations are examined by the S-EOF analysis and regression analyses based on the S-EOF time coefficients. The first TBO mode is characterized by an elongated band of positive precipitation anomalies along the YRV and negative precipitation anomalies over both North and South China. The second TBO mode is characterized by an elongated band of positive precipitation anomalies along the HRV and negative precipitation anomalies to the north of the Yellow River and to the south of the Yangtze River, respectively. Meanwhile, the leading modes of the TBO in East Asia may be determined by the meridional teleconnection Rossby wave pattern extending from the WNP to the midlatitudes of East Asia that is forced by the heating source fluctuation over the WNP during boreal summer. And the cold air activity, which is associated with the East Asian winter monsoon, may further influence the leading modes of the TBO through a modulation of the large-scale atmosphere circulation over East Asia during the following boreal summer. Also found is that the TBO in East Aisa depends on both the large-scale air-sea coupling over the tropical Indo-Pacific Ocean regions and the tropical-midlatitude interaction in the western North Pacific (WNP)-East Asia region. A fundamental element for the TBO in East Asia is the WNP monsoon. It is not only an important component of the TBO cycle in the tropics but also serves as a major source of the TBO signal for the subtropical East Asia. The meridional teleconnection Rossby wave train over the WNP-East Asia region acts as a conveyer belt that transports the tropical TBO signal to the midlatitudes of East Asia, and produces the TBO footprints in the large-scale circulation and precipitation in East Asia. Furthermore, the cold air activity over the East Asia during boreal summer also services as an important link in the chain events of the tropical-midlatitude interaction, with enhancing the role of the TBO modes in East Asia. Copyright © 2011 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

This paper discusses projections of heavy rainfall events in China during the 21st century based on daily precipitation data from the Fourth Assessment Report's (AR4) Coupled General Circulation Models (CGCM). Results show that all three experimental scenarios (scenarios A2, A1B, and B1) project consistent changes in frequency and intensity of heavy rainfall at the end of 21st century. In the regions of Northeast China and North China, there are no significant changes in frequency but there are remarkable increases in intensity of heavy rainfall, indicating that enhanced intensity is the main contributor to increased ratios of heavy rainfall to total annual precipitation in these regions. In regions of the lower reaches of Yangtze River and South China, increases in the amount of heavy rainfall are closely associated with increased frequency and increased intensity. Projected frequencies of heavy rainfall at the end of 21st century increase by 30.9 ∼ 56.6% in the Yangtze River and 35.9 ∼ 50.2% in South China compared to the period of 1980-1999, and projected intensities increase by 1.0 ∼ 5.7% and 2.8 ∼ 6.3%, respectively. Additionally, the ratios of heavy rainfall to total annual precipitation increase by 2.3 ∼ 5.4% in the Yangtze River and 1.8 ∼ 3.8% in South China. The significant increases of heavy rainfall ratios indicate that as the climate warms, heavy rainfall events are expected to increase at rates that are much faster than increases in total precipitation amounts, indicating that China will experience increased amounts of flooding. These results are substantially consistent among the three IPCC (Intergovernmental Panel on Climate Change) scenarios. The increased probability of heavy rainfall events in China is closely connected with increased transportation of water vapour from the Arabian Sea and the South China Sea. Additionally, atmosphere stratification has become increasingly unstable, which has provided a favorable background for the initiation of heavy rainfall at the end of the 21st century. Copyright © 2010 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

Solar radiation (Rs), a critical variable in agricultural and eco-environmental processes, is not measured at many meteorological stations. Prediction of Rs has drawn increasing attention in the recent years. However, due to the dynamic nature of atmosphere, accurate estimation of Rs from routinely measured meteorological variables is a challenging task. Studies have demonstrated that machine-learning approaches outperformed traditional statistical methods. This paper presents an application of Support Vector Machines (SVMs) for monthly mean daily Rs estimates using measured maximum, minimum, and mean air temperatures (Tmax, Tmin, and Tmean, respectively). Twenty-four stations covering different climatic regions-cold (C), severe cold (SC), mild (M), hot summer and cold winter within the Yangtze River Plain (HSCW-A), and hot summer and cold winter within the Sichuan Basin (HSCW-B)-across China were gathered and analysed. Five SVM models with different input attributes were created. These models were also compared with two empirical temperature-based methods. Root mean squared error (RMSE), Nash-Sutcliffe coefficient (NSE), and coefficient of residual mass (CRM) were employed to compare the performances of different methods. The newly developed model, SVM using Tmax-Tmin, and Tmean, outperformed other models with an averaged RMSE of 1.637 MJ m−2 and NSE of 0.813. On a regional scale, when Rs was estimated using the parameters developed at other sites, estimation of Rs within HSCW-B and SC regions were more reliable than in other zones. Especially in HSCW-B region, estimates of Rs using the parameters developed at Zunyi gave better performance (RMSE = 1.117 MJ m−2, NSE = 0.922) than that using the parameters obtained from their own data (RMSE = 1.309 MJ m−2, NSE = 0.894). The results showed that the SVM methodology may be a promising alternative to the traditional approach for predicting solar radiation at any locations where the records of air temperatures are available. Copyright © 2010 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

This paper studied the spatial and temporal variability of the statistical structures of precipitation across Xinjiang, China, by analysing the time series of daily precipitation from 50 weather stations during the period from 1961 to 2008. Three indices precipitation concentration index (CI), precipitation concentration degree (PCD) and precipitation concentration period (PCP) were used to detect precipitation concentrations and the associated spatial patterns. The results show that higher precipitation CI values were mainly observed in Southern Xinjiang, whereas lower precipitation CI values were mostly detected in Northern Xinjiang. The precipitation CI values are noticeably larger in places where both annual total precipitation and number of rainy days are lower. The Mann-Kendall trend test demonstrates that the most parts of Xinjiang are characterized by no significant trends of precipitation CI at the 0.05 significance level. The periodicity characteristic of precipitation CI time series in Xinjiang could be detected by wavelet power spectrum analysis, and significant periods of that in most of Xinjiang were concentrated on 2-5 years band. The results of PCP reveal that rainfall in Xinjiang mostly occurs in summer, and the rainy season arrives earlier in Eastern Xinjiang than Western Xinjiang, whereas the results of PCD indicate that the rainfall in Northern Xinjiang was more dispersed within a year than that in Southern Xinjiang. Copyright © 2010 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

In a previous study by the authors, a regional climate model (hereafter the RCM) developed to study the summer monsoon over South China (SC) and the South China Sea (SCS) has been tested and found to be able to simulate to a large extent the precipitation over this region for the months of May and June. To examine the interannual variability of the summer monsoon here, it is necessary to establish a model climatology to serve as a comparison and to reduce or even remove any systematic model biases. This paper presents the analyses of such a 10-year climatology (1991-2000). The model was initialized on 1 April and integrated up to the end of June for the ten years. The initial atmospheric conditions and lateral boundary data used in this study are from the European Centre for Medium-range Weather Forecasts '40-year' reanalyses. The RCM can reproduce well the main features of the monsoon circulation and vertical structure of the atmosphere. The RCM can simulate the intensification and northwestward displacement of the south Asian upper anticyclones from May to June, as well as the low-level moisture transport from the Bay of Bengal to SC. In the simulation, the average SCS summer monsoon onset occurs in the fourth pentad of May, which is consistent with the results from previous observational research. In addition, the RCM can reproduce the main characteristics of the onset such as the change of the low-level zonal flow from easterly to westerly as well as the rapid increase in daily precipitation. The SC and SCS precipitation anomalies have the correct sign in almost all the years. The shortcomings of the model simulation include an under-prediction of the strength of the subtropical high over the Northwest Pacific and the moisture transport from the Bay of Bengal to the Indochina Peninsula (IC) and SCS. A cold bias in surface air temperature is also observed, with the 10-year mean biases of the simulated surface air temperature over SC, SCS and IC in May and June being about −2.1 °C, −2.4 °C and −1.4 °C respectively. The 10-year mean biases of the simulated daily precipitation rate over SC, SCS and IC are about 2.0, −3.8 and 3.5 mm d−1 respectively. Copyright © 2005 Royal Meteorological Society. [ABSTRACT FROM AUTHOR]

This paper describes the general moisture conditions and the annual and seasonal trends of temperature, precipitation, potential evapotranspiration and aridity/humidity index from 1971 to 2000 in China. Observed climatic data from 616 meteorological stations over China's land surface were used. Potential evapotranspiration was calculated by the Penman-Monteith model with a modified net radiation part to accommodate China's unique climatic conditions. According to the aridity/humidity index, a ratio of potential evapotranspiration to precipitation, four moisture regional types were delineated gradually from the southeast to the northwest, i.e. humid, subhumid, semiarid and arid throughout China. Linear regression was performed on the 30-year time series of the four climate factors in order to detect possible trends. The results confirm the obvious spatial and temporal difference of climate trends. Surface air temperature has increasing trends almost all over China especially in winter. Most stations are statistically significant. Annual precipitation shows increasing trends at more than half of the stations, and the increasing trends mainly occur in summer and winter while the decreasing trends occur in spring and autumn. However, most stations are not statistically significant. Potential evapotranspiration has decreasing trends in most stations and nearly half of the stations are statistically significant. Annual aridity/humidity index shows primarily decreasing trends with a distribution nearly the same as the increasing trends of precipitation. The index has the decreasing trends in spring and summer and the increasing trends in autumn and winter. The results suggest that it is necessary to consider precipitation and potential evapotranspiration simultaneously to describe the moisture conditions exactly. Copyright © 2005 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

The frequency and magnitude of global warming events varies greatly across different regions and countries. The climatic diversity for China and future warming features are projected across 12 climatic zones based on the ensemble of the five well‐performing high‐resolution downscaled climate models for each zone. There are warming patterns for the mean near‐surface air temperature (Tm), maximum near‐surface air temperature (Tmax), minimum near‐surface air temperature (Tmin) as well as heatwave and frost events. Under RCP4.5 and RCP8.5 scenarios, the three indices (i.e., Tm, Tmax and Tmin) countrywide are likely to increase at respective rates of 0.30–0.31 and 0.64–0.67°C·decade−1. The extent of frost event (FE) are projected to decrease at a rate of −1912 and −4442 day·km−2·decade−1 while the extent of heatwave event (HE) increase at a rate of 1116 and 3557 day·km−2·decade−1 under RCP4.5 and RCP8.5 scenarios, respectively. A higher increment in temperatures, a decreasing trend in diurnal temperature range (DTR), frost days and FE are highlighted in the western and northern zones, while these trends are opposite in southern zones. The warming is likely to get faster in the current colder zones (western and northern zones) while heatwave is more intense and severe in Jianghuai, Jianghan, the south Yangzi River, South China and Xinjiang. These potential changes indicate that adaption and mitigation strategies are necessary in response to future warming. [ABSTRACT FROM AUTHOR]

West China experienced an extremely wet autumn in 2017, and the amount of September–October precipitation is the greatest during 1961–2018. This study explored the physical processes responsible for two primary intraseasonal precipitation events which contribute greatly to such an extremely wet season. The first event peaking in early September is induced by the southward movement of a frontal system from the northern China, which is attributed to the southward displacement of an intraseasonal anticyclonic anomaly. The northerly anomaly associated with the anticyclone advects cold air into West China and thus triggers frontal precipitation. The second event peaking in early October is related to the northward shift and intensification of an intraseasonal anticyclonic anomaly centred over the northwestern Pacific Ocean. The southerly anomaly along the western flank of the anticyclone transports moisture to West China and thus triggers precipitation. The different initiation processes for the two precipitation events may be due to the distinct dynamical and thermal‐dynamical conditions in September and October. West China has sufficient moisture but less dynamical disturbances in September, while it has adequate dynamical disturbances but less moisture in October. [ABSTRACT FROM AUTHOR]

To understand the impact of the boreal summer intraseasonal oscillation (BSISO) propagation on summer precipitation in North China, this study analysed the quantitative relationship between the BSISO and summer precipitation in North China and its influence mechanism using summer precipitation data from 1981 to 2020, the NCEP/NCAR reanalysis data and the NOAA outgoing longwave radiation (OLR). The results show that there is a strong correlation between summer precipitation in North China and the BSISO. Over the past 40 years, the variance in summer precipitation anomalies in North China caused by BSISO1 accounted for 16.8%, whereas the impact of BSISO2 accounted for 13.1%. Their combined impact accounted for 30% of the variance in summer precipitation in North China. The BSISO influences summer precipitation process in North China primarily through upper tropospheric circulation and lower‐level water vapour transport. At 500 and 200 hPa, the BSISO excited some disturbance centres of a deep barotropic structure propagating from west to east along the upper‐tropospheric westerly jet. North China is controlled by the blocking circulation pattern of "high in the east and low in the west" while there is a negative (positive) anomaly near Lake Baikal and a positive (negative) anomaly near the Korean Peninsula. At 850 hPa, the BSISO stimulates an anticyclonic circulation anomaly on the north side of its convective area, and the southerly winds on the west side of the anticyclone enhance water vapour transport to North China. This high‐ and low‐level circulation configuration is favourable for precipitation processes in North China. The results suggest that the influence of both low‐frequency signals in the middle and high latitudes and the BSISO signal in the tropics should be considered to make extended‐range forecasts of precipitation processes in North China. [ABSTRACT FROM AUTHOR]

Wind speed changes impact society and have important implications for climate change studies. Thus, high‐resolution and high‐quality wind speed datasets are necessary for environmental monitoring and ecosystem research. However, there is no complete set of high spatial and temporal resolution wind speed datasets for China. Additionally, it is extremely challenging to produce wind speed data at high spatial and temporal resolution for large‐scale regions with diverse climate types and complex topographies, such as China. In this study, we used multisource remote sensing images, obtained data on various environmental factors through the Google Earth Engine and Evapotranspiration (ET) Watch Cloud platforms, and combined machine learning algorithms to downscale the ERA5 reanalysis wind speed data, and finally obtained the daily wind speed datasets with 1 km spatial resolution for China in 2015. To verify the accuracy of the model and data products, we selected several metrics to evaluate in conjunction with the actual site observed data. The results show that the multifactor combination model of artificial neural network combining land surface temperature, sunshine durations and roughness factors outperforms a single‐factor combination model, and the results were in good agreement with the original data (R2 of 0.95 and RMSE of 0.40 m·s−1). The final wind speed data products were also in good agreement with the observed meteorological data (R2 range of 0.86–0.95 and RMSE range of 0.33–0.44 m·s−1); moreover, the accuracy and precision were greatly improved over the original data. This study provided a dataset that has potential applications in future climate change and ecosystem studies. [ABSTRACT FROM AUTHOR]

A comprehensive understanding of the patterns of drought and flood alternation in adjacent months is essential for enabling climate adaptation and mitigation strategies. However, there is a paucity of knowledge regarding short‐cycle drought–flood abrupt alteration (s‐DFAA) and its responses to multiple environmental factors at various timescales. This is because of the inadequate formula construction of the existing short‐cycle drought–flood abrupt alteration index (SDFAI), such as the inability to introduce drought standards. To accurately capture the s‐DFAA's characteristics in the Qinling‐Daba Mountains (Qinba Mountains), we proposed a revised SDFAI (R‐SDFAI), which incorporates the standardized precipitation index (SPI) and allows for the customization of drought standards. Next, we used wavelet transform coherence and multiple wavelet coherence to investigate the timescale relationships between s‐DFAA events and their influence factors such as relative humidity, sunshine duration, temperature, evaporation, Arctic Oscillation (AO), Niño3.4 SSTA Index (Niño3.4), Total Sunspot Number Index (TSNI) and Pacific Decadal Oscillation Index (PDO). Our results showed that the R‐SDFAI outperformed traditional SDFAI in capturing s‐DFAA events and characterizing their severity. Furthermore, s‐DFAA events identified by R‐SDFAI at different levels (i.e., mild, moderate, severe, extreme and total) displayed insignificant downward trends. Spatially, there were more s‐DFAA events in the east than the west. Wavelet analysis indicated that meteorological factors and teleconnections significantly impact s‐DFAA events at large timescales, though their driving mechanisms differed substantially. Among meteorological factors, single relative humidity and its related combinations exhibited relatively high percent area of significant coherence (PASC, ranging from 17.47 to 29.46). Each teleconnection and its combinations are irreplaceable, with PASC values always increasing with the number of variables. The PASC ranges from 8.3 to 10.29 for one factor, 12.38 to 18.65 for two factors, 24.02 to 30.58 for three factors and 40.88 for four factors, respectively. [ABSTRACT FROM AUTHOR]

Many studies have shown that the climate system has the long‐range correlation (LRC) characteristics, which provide a good test bed for evaluating the performance of climate models. In this study, the LRC characteristics of the observed surface daily temperature data in China is first analysed by detrended fluctuation analysis. It is found that the daily temperature records, including daily mean temperature (Tmean), daily maximum temperature (Tmax), and daily minimum temperature (Tmin), all exhibit LRC characteristics with scaling exponents more than 0.6 in most of China. Then, the performances of two different versions for the Beijing Climate Center Climate System Model (BCC‐CSM), namely, BCC‐CSM1.1m in CMIP5 and BCC‐CMS2‐MR in CMIP6, are quantitatively evaluated by comparing the differences of the LRC characteristics between the observations and the simulations. The results indicate that BCC‐CSM2‐MR performs better than BCC‐CSM1.1(m) in western Northwest China, most of south of the middle and lower reaches of Yangtze River, North China, central Inner Mongolia for the daily Tmean and Tmax. As far as the daily Tmin is concerned, BCC‐CSM1.1(m) performs better than BCC‐CSM2‐MR in western South China and southern Xinjiang, and the performance of BCC‐CSM2‐MR in CMIP6 has not been significant improved. Compared with BCC‐CSM1.1(m), BCC‐CSM2‐MR cannot significantly improve the simulations for the LRC characteristics of the three daily temperature variables in central and eastern Qinghai‐Tibet plateau, and the areas of between lower reaches of Yellow River and Yangtze River. [ABSTRACT FROM AUTHOR]

In 2021/2022 winter, an intraseasonal surface air temperature (SAT) reversal occurred in China, shifting from regional warm to cold phase in late January 2022. The intraseasonal variations of winter SAT in China are tightly connected with 500 hPa potential height. In particular, the Arctic Oscillation (AO) positive phase is diagnosed to be contributing to the SAT reversal. Under its influence, the intraseasonal build‐up and collapse of blockings over Urals Mountain led to the cold surges in February 2022. Seasonal prediction systems (SPSs) such as NCEP_CFSv2, EC_SYSTEM5 and BCC_CSM1.1 are assessed to have poor predictability in this SAT reversal and similar historical events, owing to not only the poor skills in winter SAT predictions but also the integral inertia in SPSs. Prediction skill only increases as the forecasting time approaches, owing to initial values. Besides, the SPSs can simulate the physical process of the influence on SAT from circulation. The poor predictability is attributed to the poor prediction skills in mid–high latitude circulation pattern and potential height over China. [ABSTRACT FROM AUTHOR]

The stable oxygen isotope composition of precipitation (δ18Op) in southern China is considered as a valuable proxy of climatic conditions. However, their interpretations have been controversial. In this study, based on the observed and simulated data (isoGSM2) on oxygen isotope composition of precipitation, the linkage between summer precipitation (P) and δ18Op in the Dongting Lake basin and their possible influencing factors were investigated. The results indicate that the interannual variation of summer δ18Op is consistent with that of annual δ18Op. They both show a significantly negative correlation with the summer P, suggesting that the stable isotope composition in precipitation may be considered as a proxy of summer precipitation in the Dongting Lake basin. Statistically, the amount effect and circulation effect are significant in the isotope composition of precipitation in the basin. Based on either the observed data in Changsha or the simulated data for the basin, the local amount effect appears more important than large‐scale circulation for δ18Op during extreme summers. These results can potentially improve the reconstruction of paleoclimate in the East Asian monsoon region. Further study is needed to determine the contribution of local and large‐scale factors to the oxygen isotope composition of precipitation and to quantify the integral rainout along the moisture transporting paths. [ABSTRACT FROM AUTHOR]

Understanding future dry and wet changes under global climate change is of great regional significance in China. Based on six Global Climate Models (GCM) from the Coupled Model Intercomparison Project phase 6 (CMIP6), we project the changes of dry‐wet climate regions in China in the 21st century under the three SSP‐RCP (shared socioeconomic pathway‐representative concentration pathway) scenarios (SSP1‐2.6, SSP2‐4.5 and SSP5‐8.5), and further identify the key climatic factors that lead to the transition of dry‐wet climate regions. The results show the area of humid and subhumid regions in China will show an upward trend in the future, while the area of semiarid and arid regions will show a downward trend. Especially under the SSP5‐8.5 scenario, the area of the subhumid region has the largest increase trend (0.042% per year), and the area of the arid region has the largest decline trend (−0.048% per year). The three main transfer directions of dry‐wet climate regions are from arid to semiarid regions, from semiarid to subhumid regions, and from subhumid to humid regions in the future. Due to the future extensive wetting trend in the north, the future dry‐wet climate regions will shift to wetter types in Tibet, North China, the Qinling‐Huaihe regions and the northeast. In addition, the key climatic factors for the transition of dry‐wet climate regions are mainly precipitation, maximum temperature and solar radiation. The increase of precipitation plays a dominant role for areas projected to change to wetter types, and the increase of potential evapotranspiration (PET) plays a dominant role for areas projected to change to drier types. The PET changes in changed areas of dry‐wet climate regions are mainly dominated by maximum temperature and solar radiation. Our research has important implications for future water resource management and reconsideration of climate mitigation and adaptation policies. [ABSTRACT FROM AUTHOR]

Consecutive extreme wet days (CEWDs) typically affect the likelihood of flooding and landslides and have negative effects on both natural and artificial ecosystems; however, the spatiotemporal changes in their features are still unclear at the national scale. Investigating changes in the frequency and intensity of such events is essential for climate risk management. Here, this study thoroughly analysed CEWD features in China from 1980 to 2020 using the daily observation dataset. We also evaluated and compared the ability of two widely used precipitation products, the European Centre for Medium‐Range Weather Forecasts Reanalysis 5th Generation (ERA5) and the Multi‐Source Weighted‐Ensemble Precipitation version 2 (MSWEP), to detect CEWD features. According to the observation data, the frequency and intensity of CEWD events are related to local climate and present "high eastern and low western" spatial patterns across China. Since 1980, more than half of China's mainland has experienced increases in both the frequency and intensity of CEWDs. Some stations detected decreasing trends in CEWD frequency and amounts, which are primarily located in the eastern coastal regions and southwest of warm temperate humid/subhumid regions. The ERA5 precipitation product generally outperforms MSWEP data in detecting CEWD events, and the latter significantly underestimates the annual frequency and amounts of CEWDs. These findings provide basic and valuable information regarding CEWD features across China and where such studies can be conducted based on precipitation datasets. Furthermore, these findings will also aid policymakers in managing extreme precipitation‐related natural hazards. [ABSTRACT FROM AUTHOR]

Instantaneous precipitation can often cause devastating disasters on the Earth's surface. Continuous increases in extreme precipitation around the world have caused widespread concern, and it is necessary to study the extreme hourly precipitation over a large scale and long time series. Using specific numbers of unique hourly precipitation point data from 1980 to 2019, our research found that there are different spatial patterns regarding the frequency and intensity of extreme hourly precipitation in Mainland China, but the clear spatial pattern of being weak in the west and strong in the east of China. Most extreme hourly precipitation events occurred from June to August in the north of China and from April to October in the south of China. Afternoon and midnight are the peak periods of extreme precipitation events in southern China. The frequency of extreme hourly precipitation in the whole of China had increased by 0.7 hr/10a and increased significantly in the northwest and southeast of China. The average intensity of extreme hourly precipitation has decreased by 0.1 mm·hr−1/10a in the whole of China. While the maximum intensity has increased in local areas, the trend of changes is not significant in the whole of China. We have discovered that rapid urbanization is likely to be responsible for the frequency of extreme hourly precipitation in China. It is urgent to enact flood protection measures because this change is expected to worsen in the future with intensified urbanization in China. [ABSTRACT FROM AUTHOR]

Based on the daily precipitation data and the forecast data from subseasonal‐to‐seasonal (S2S) models, the prediction abilities of four S2S models for regional rainstorm processes are assessed. The results show that: Compared with the observations, the precipitation amounts that predicted by CMA, KMA, NCEP and UKMO models are lower. If the rainfall area is more concentrated and the precipitation amounts are greater, the biases are larger. When the lead times are greater than 15 days, the models cannot predict the occurrences of regional rainstorms. Among the four models, NCEP and UKMO models have better prediction abilities. NCEP model can make real‐time forecast four times a day and initial time forecast results at 0000, 0600, 1200 and 1800 UTC are different. Compared with an initial time forecast, average of four initial time forecast results is closer to the observed values. The less precipitation predicted by NCEP, CMA, KMA and UKMO models may result of the underestimate of cyclonic circulation convergence intensity and water vapour flux amounts. [ABSTRACT FROM AUTHOR]

Various climatic factors and their interactions affect China's snow depth alterations. However, a measure of the relative importance of climatic factors regarding the variance in snow depth is lacking. Here, we use a heretofore largest dataset, quality‐controlled daily observations from 1,665 meteorological stations, and statistical analyses to identify proxy drivers and their contributions regarding regional variability and trends in China's snow depth and snow depth‐climate relationships from 1951 to 2019. Results show that seasonal snow depth alterations are substantial in China and caused by various climatic drivers. In winter, observed positive trends in the northwest and northeast of China mainly respond to augmentation in solid precipitation and snow accumulation in fall. For the Tibetan Plateau, the negative snow depth anomaly seems to respond to the rising air temperature below the freezing point along with some secular changes in solid precipitation and shallower fall snowpacks. All these trends in winter snow depth over the northwest, northeast, and Tibetan Plateau of China account approximately for 30% of the total interannual variance in spring snow depth in these regions. In the milder central north and south of China, snow accumulation is not evident. Besides solid precipitation and rising air temperature below the freezing point, atmospheric humidity is also notable for its effect on the interannual variance in winter snow depth in these regions. In spring and fall, however, the negative effect of warming climate on snow depth becomes remarkably more important. It seems that about 13–33% (12–50%) of the total interannual variance in the widespread decrease (insignificant perturbation), except for some weak increases in the northeast region (decreases in the Tibetan Plateau), of China's spring (fall) snow depth are caused by the rising air temperature below the freezing point. [ABSTRACT FROM AUTHOR]

This study investigates the performance of the 23 CMIP6 models in simulating spring precipitation over China and preliminarily explores the reasons for the underestimation of spring precipitation over South China (SC). The results show that the CMIP6 models can generally capture spring precipitation over China but have distinct underestimations in SC. In addition to analysing the results of the multimodel ensemble mean (MME), based on the regional mean spring precipitation differences over SC, we also analyse five models with greater overestimated precipitation amounts composing the high‐value MME (H_MME) and five models with greater underestimated precipitation amounts composing the low‐value MME (L_MME) as comparisons. Moisture budget analysis reveals that the underestimated dynamic component of vertical moisture advection mainly causes the negative biases of spring precipitation over SC. Further analyses indicate that the underestimation of the intensity of the East Asian subtropical jet (EASJ) generally causes weakened secondary meridional circulation to the south of 30°N and moisture convergence over SC in CMIP6 models. Consequently, less moistened air would be lifted to high levels, providing an unfavourable background for the occurrence of spring precipitation and inducing underestimation compared with the observations. The modelling EASJ shows much stronger (weaker) H_MME (L_MME), which generally enhances (weakens) the dynamic component of the secondary circulation over SC, favourable for the increase (decrease) in spring precipitation. [ABSTRACT FROM AUTHOR]