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Variability in soil moisture has implications for regional terrestrial environments under a warming climate. This paper focuses on the spatiotemporal variability in the intra-annual persistence of soil moisture in China using the fifthgeneration reanalysis dataset by the European Centre for Medium-Range Weather Forecasts for the period 1979-2018. The results show that in China, the mean intra-annual persistence in the humid to arid zones increased from 60 to 115 days in the lower layer but decreased from 19 to 13 days and from 25 to 14 days in the upper and root layers, respectively. However, these changes were strongly attenuated in extremely dry and wet regions due to the scarcity of soil moisture anomalies. Large changes in persistence occurred in the lower soil layer in dryland areas, with a mean difference of up to 40 days between the 2010s and the 1980s. Overall increasing trends dominated the large-scale spatial features, despite regional decreases in the eastern arid zone and the North and Northeast China plains. In the root layer, the two plains experienced an expanded decrease while on the Tibetan Plateau it was dominated by decadal variability. These contrasting changes between the lower and root layers along the periphery of the transition zone was a reflection of the enhanced soil hydrological cycle in the root layer. The enhanced persistence in drylands lower layer is an indication of the intensified impacts of soil moisture anomalies (e.g., droughts) on terrestrial water cycle. These findings may help the understanding of climate change impacts on terrestrial environments. [ABSTRACT FROM AUTHOR]

The systematic bias of the estimated average temperature using daily Tmax and Tmin records relative to the standard average temperature of four time-equidistant observations and its effect on the estimated trend of long-term temperature change have not been well understood. This paper attempts to evaluate the systematic bias across mainland China using the daily data of national observational stations. The results revealed that the positive bias of annual mean temperature was large, reaching 0.58°C nationally on average; regional average bias was lowest in the northwest arid region and highest in the Qinghai–Tibetan Plateau; the bias was low in spring and summer and high in autumn and winter, reaching its lowest point in mid- and late May and highest point in early November. Furthermore, the bias showed a significant upward trend in the past 50 years, with a rising rate of 0.021°C (10 yr)−1, accounting for about 12% of the overall warming as estimated from the data of the observational network; the largest positive trend bias was found in the northwest arid region, while the east monsoon region experienced the smallest change; the most remarkable increase of the bias occurred after early 1990s. These results indicate that the customarily applied method to calculate daily and monthly mean temperature using Tmax and Tmin significantly overestimates the climatological mean and the long-term trend of surface air temperature in mainland China. [ABSTRACT FROM AUTHOR]

This paper describes the study of the relationship between the thermal configuration of the Bay of Bengal (BOB)-Tibetan Plateau (TP) region and the precipitation anomaly in Yunnan, a province in China, in May using ERA-Interim data and precipitation data for May from 125 meteorological stations across Yunnan for 1979-2014. Results from the analysis indicate that the interannual variability of May precipitation in Yunnan is significantly modulated by the BOB-TP thermal configuration. Model runs with a linear baroclinic model suggest physical consistency. The thermal conditions over the BOB mainly impact the May precipitation anomaly in Yunnan via changes in water vapor transport from the eastern BOB northeastward to southwestern Yunnan. The second factor influencing precipitation anomalies relates to the characteristics and variability of cold air transport from the TP to northeastern Yunnan. When the BOB (the TP) is occupied by positive (negative) diabatic heating, a thermal gradient with a warmer (colder) center over the BOB and a colder (warmer) center over the TP is established, and more-than-normal (less than normal) precipitation in Yunnan will occur in May. This relationship can persist from April to the following May to some extent; therefore, the BOB-TP thermal configuration in April could be used to forecast May precipitation in Yunnan. [ABSTRACT FROM AUTHOR]

Northeast China (NEC) is one of the major agricultural production areas in China, producing about 30% of China's total maize output. In the past five decades, maize yields in NEC increased rapidly. However, farmer yields still have potential to be increased. Therefore, it is important to quantify the impacts of agronomic factors, including soil physical properties, cultivar selections, and management practices on yield gaps of maize under the changing climate in NEC in order to provide reliable recommendations to narrow down the yield gaps. In this study, the Agricultural Production Systems Simulator (APSIM)-Maize model was used to separate the contributions of soil physical properties, cultivar selections, and management practices to maize yield gaps. The results indicate that approximately 5%, 12%, and 18% of potential yield loss of maize is attributable to soil physical properties, cultivar selection, and management practices. Simulation analyses showed that potential ascensions of yield of maize by improving soil physical properties PAY s, changing to cultivar with longer maturity PAY c, and improving management practices PAY m for the entire region were 0.6, 1.5, and 2.2 ton ha−1 or 9%, 23%, and 34% increases, respectively, in NEC. In addition, PAY c and PAY m varied considerably from location to location (0.4 to 2.2 and 0.9 to 4.5 ton ha−1 respectively), which may be associated with the spatial variation of growing season temperature and precipitation among climate zones in NEC. Therefore, changing to cultivars with longer growing season requirement and improving management practices are the top strategies for improving yield of maize in NEC, especially for the north and west areas. [ABSTRACT FROM AUTHOR]

Measurements of air temperature and precipitation at 35 stations in Hubei Province, China, during 1962-2011 are used to investigate the regional climate change. There is an increasing trend for observed air temperature (0.23°C decade−1), which is slightly higher than that from multiple model simulations/predictions [phase 5 of CMIP (CMIP5) datasets] (0.16°C decade−1). The observed precipitation increases at the rate of 11.4 mm decade−1, while the CMIP5 results indicate a much lower decreasing trend (0.8 mm decade−1) in this region. To examine the ecological responses to the climate changes in Hubei Province, annual gross primary productivity (GPP) and net primary productivity (NPP) products during 2000-10 and leaf area index (LAI) products during 1981-2011 are also analyzed. It is discovered that GPP, NPP, and LAI increase at the rate of 1.8 TgC yr−1 yr−1, 1.1 TgC yr−1 yr−1, and 0.14 m2 m−2 decade−1, respectively. A linear model is further used to conduct the correlation analyses between climatic parameters (i.e., air temperature and precipitation) and ecological indicators (i.e., GPP, NPP, and LAI). The results indicate that the air temperature has a significant positive correlation with LAI ( R2 = 0.311) and GPP ( R2 = 0.189); precipitation is positively correlated with NPP ( R2 = 0.209). Thus, it is concluded that the air temperature exerts a stronger effect on the ecosystem than precipitation in Hubei Province over the past decades. [ABSTRACT FROM AUTHOR]

One of the potential impacts of global warming is likely to be experienced through changes in flood frequency and magnitude, which poses a potential threat to the downstream reservoir flood control system. In this paper, the downscaling results of the multimodel dataset from phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5, respectively) were coupled with the Variable Infiltration Capacity (VIC) model to evaluate the impact of climate change on the Feilaixia reservoir flood control in the Beijiang River basin for the first time. Four emissions scenarios [A1B and representative concentration pathway (RCP) scenarios RCP2.6, RCP4.5, and RCP8.5] were chosen. Results indicate that annual distribution and interannual variability of temperature and precipitation are well simulated by the downscaling results of the CMIP3 and CMIP5 multimodel dataset. The VIC model, which performs reasonably well in simulating runoff processes with high model efficiency and low relative error, is suitable for the study area. Overall, annual maximum 1-day precipitation in 2020-50 would increase under all the scenarios (relative to the baseline period 1970-2000). However, the spatial distribution patterns of changes in projected extreme precipitation are uneven under different scenarios. Extreme precipitation is most closely associated with extreme floods in the study area. There is a gradual increase in extreme floods in 2020-50 under any of the different emission scenarios. The increases in 500-yr return period daily discharge of the Feilaixia reservoir have been found to be from 4.35% to 9.18% in 2020-50. The reservoir would be likely to undergo more flooding in 2020-50. [ABSTRACT FROM AUTHOR]

Because of the limitations of coarse-resolution general circulation models (GCMs), delta change (DC) methods are generally used to derive scenarios of future climate as inputs into impact models. In this paper, the impact of future climate change on irrigation was investigated over China using the Community Land Model, version 4 (CLM4), which was calibrated against observed irrigation water demand (IWD) at the provincial level. The results show large differences in projected changes of IWD variability, extremes, timing, and regional responses between the DC and bias-corrected (BC) methods. For example, 95th-percentile IWD increased by 62% in the BC method compared to only a 28% increase in the DC method. In addition, a shift of seasonal IWD peaks (averaged over the country) to one month later in the year was projected when using the BC method, whereas no evident changes were predicted when using the DC method. Furthermore, low-percentile runoff has larger impacts in the BC method compared with proportional changes in the DC method, indicating that hydrological droughts seem to be exacerbated by increased climate variability. The discrepancies between the two methods were potentially due to the inability of the DC method to capture the changes in precipitation variability. Therefore, the authors highlight the potential effects of climate variability and the sensitivity to the choice of particular strategy-adjusting climate projection in assessing climate change impacts on irrigation. Some caveats, however, should be placed around interpretation of simulated percentage changes for all of China since a large model bias was found in southern China. [ABSTRACT FROM AUTHOR]

It is argued that the occurrence of cold events decreases under the background of global warming. However, from the mid-1990s to the early 2010s, northern China experienced a period of increasing occurrence of low temperature extremes (LTE). Factors responsible for this increase of LTE are investigated in this analysis. The results show that the interdecadal variation of the winter mean temperature over mid- and high-latitude Eurasia acts as an important thermal background. It is characterized by two dominant modes, the "consistent cooling" pattern and the "warm high-latitude Eurasia and cold midlatitude Eurasia" pattern, from the mid-1990s to the early 2010s. The two patterns jointly provide a cooling background for the increase of LTE in northern China. Meanwhile, though the interdecadal variation of the Arctic Oscillation (AO), Ural blocking (UB), and Siberian high (SH) are all highly correlated with the occurrence of LTE in northern China, the AO is found to play a dominant role. On one hand, the AO directly affects the occurrence of LTE because of its dynamic structure; on the other hand, it takes an indirect effect by affecting the intensity of UB and SH. Further analyses show that the winter temperature in mid- and high-latitude Eurasia and the AO are independent factors that influence the increase of LTE in northern China from the mid-1990s to the early 2010s. [ABSTRACT FROM AUTHOR]

In this study, the interdecadal variability of the relationship between ENSO and winter synoptic temperature variability (STV) over the Asian–Pacific–American region is investigated based on observational data from 1951 to 2018. An interdecadal shift in the ENSO–STV relationship occurred in the 1980s over Eastern China, changing from significant in period 1 (P1; 1951–87) to insignificant in period 2 (P2; 1988–2018). But the ENSO–STV relationship is significantly stable over North America for the whole period. In addition, a possible reason for this interdecadal shift in the ENSO–STV relationship over Eastern China is also investigated. During P1, the ENSO pattern is significantly correlated to the temperature gradient over Northeast Asia, which is the key region influencing the intensification of extratropical eddies. The intensification of extratropical eddies over Northeast Asia is directly associated with the magnitude of STV over Eastern China. But in P2, the ENSO pattern is not related to the temperature over Northeast Asia. Therefore, the change in the ENSO pattern from P1 to P2 contributes to the interdecadal shift in the ENSO–STV relationship in the 1980s over Eastern China by influencing the temperature gradient over Northeast Asia, while ENSO can influence the temperature gradient over North America for the whole period. Furthermore, the possible role of the ENSO patterns in P1 and P2 is also examined by using an atmospheric general circulation model, highlighting that the pattern of SST variation is a determining factor in regulating STV in different regions. [ABSTRACT FROM AUTHOR]

Persistent drought events that cause serious damage to the economy and environment are usually intensified by the feedback between the land surface and atmosphere. Therefore, reasonably modeling land–atmosphere coupling is critical for skillful prediction of persistent droughts. However, most high-resolution regional climate modeling has focused on the amplification effect of land–atmosphere coupling on local anticyclonic circulation anomalies, while less attention has been paid to the nonlocal influence through altering large-scale atmospheric circulation. Here we investigate how the antecedent land–atmosphere coupling over the area south of Lake Baikal (ASLB) influences the drought events occurring over its downstream region [i.e., Northeast China (NEC)] by using the Weather Research and Forecasting (WRF) Model and a linear baroclinic model (LBM). When the ASLB region is artificially forced to be wet in the WRF simulations during March–May, the surface sensible heating is weakened and results in a cooling anomaly in low level atmosphere during May–July. Consequently, the anticyclonic circulation anomalies over ASLB and NEC are weakened, and the severity of NEC drought during May–July cannot be captured due to the upstream wetting in March–May. In the LBM experiments, idealized atmospheric heating anomaly that mimics the diabatic heating associated with surface wetness is imposed over ASLB, and the quasi-steady response pattern of 500-hPa geopotential height to the upstream wetting is highly consistent with that in the WRF simulation. In addition, the lower-level heating instead of the upper-level cooling makes a major contribution to the high pressure anomaly over NEC. This study implies the critical role of modeling upstream land–atmosphere coupling in capturing downstream persistent droughts. [ABSTRACT FROM AUTHOR]

This study revisits the long-term variabilities of the East Asian summer monsoon (EASM) in 1958–2017 through examination of diurnal cycles. We group monsoon days into four dynamic quadrants (Q1 to Q4), with emphasis on the strong daily southerlies coupled with a large (Q1) or small (Q4) diurnal amplitude over Southeast China. The occurrence day of Q1 increases in June–July with the seasonal progress of the EASM. It is most pronounced in the 1960s to the 1970s and declines to the lowest in the 1980s to the 1990s, whereas the Q4 occurrence increases notably from the 1970s to the 1990s; both groups return to normal in recent years. The interdecadal decrease (increase) of Q1 (Q4) occurrence corresponds well to the known weakening of EASM in the twentieth century, and it also coincides with the rainfall anomalies over China shifting from a “north flooding and south drought” to a “north drought and south flooding” mode. The rainfall under Q1 (Q4) can account for ~60% of the interannual variance of summer rainfall in northern (southern) China. The contrasting effects of Q1 and Q4 on rainfall are due to their remarkably different regulation on water vapor transport and convergence. The interannual/interdecadal variations of Q1 (Q4) occurrence determine the anomalous water vapor transports to northern (southern) China, in association with the various expansion of the western Pacific subtropical high. In particular, Q1 conditions can greatly intensify nighttime moisture convergence, which is responsible for the long-term variations of rainfall in northern China. The results highlight that the diurnal cycles in monsoon flow act as a key regional process working with large-scale circulation to regulate the spatial distributions and long-term variabilities of EASM rainfall. [ABSTRACT FROM AUTHOR]

Hourly blackbody temperature data from the warm seasons (May–September) of 2009–18 were used to detect mesoscale convective systems (MCSs) generated in the southwest mountain area (elevation ≥ 500 m) of China. A total of 3059 MCSs were grouped into four categories (C1, C2, C3, and C4) according to their generation positions using K-means clustering. Major characteristics of the four types of MCSs and their synoptic environmental conditions were investigated. The MCSs had a peak in July and a minimum in May, and usually lasted from 3 to 21 h. The C1 MCSs generated in the northeast of the Tibetan Plateau developed faster, were largest, and had a longer lifespan. The C2 and C4 MCSs had greater intensity and were initiated in the southeast of the Tibetan Plateau and the west of the Yungui Plateau, and near the Wuling and Xuefeng Mountains, respectively. The C3 MCSs initiated in the Qinling, Ta-pa, and Wushan Mountains were smallest. The C1 and C2 MCSs contributed more than 30% to total precipitation, which was more than the C3 and C4 MCSs (<25%), and the contribution rate of MCSs to short-duration heavy rainfall affected by local MCSs was over 60%. Composite synoptic circulations of the four types of MCSs showed several factors, including the locations and intensities of cyclones in the Bay of Bengal and high pressure in the Indochina Peninsula in the low-to-middle troposphere, and vortexes or southwesterly winds in the low-level troposphere, regulate the location and intensity of convection. [ABSTRACT FROM AUTHOR]

Because spring precipitation in East Asia is critical for recharging water resources after dry winters, its spatiotemporal variations and related mechanisms need in-depth research. This study analyzed a leading spatiotemporal variability of precipitation over East Asia for boreal spring (March-May) during 1979 to 2017. We found that a dipole mode dominates the anomalous spring precipitation between southern China and Southeast Asia with significant interannual and decadal variations. The interannual dipole mode is attributable to the eastern Pacific (EP)-type El Niño-Southern Oscillation (ENSO) while the decadal dipole mode is related to the decadal variation of the central Pacific (CP)-type ENSO. In the El Niño phases of both time scales, the anticyclonic anomaly over the South China Sea and Philippines causes moisture convergence (divergence) over southern China (Southeast Asia), resulting in positive (negative) precipitation anomalies therein; the opposite occurs in the La Niña phases. The ensemble experiments using the Community Atmosphere Model version 5.1 confirmed that the tropical sea surface temperature (SST) in the EP- and CP-type ENSO can be the major drivers of the interannual and decadal dipole modes, respectively. About half of 15 climate models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5) showed that the El Niño phase of dipole mode will become dominant in the future. The individual models' future projections however considerably vary, implying that there is still large uncertainty. [ABSTRACT FROM AUTHOR]

The variability of the lower tropospheric temperature inversion (TI) across China remains poorly understood. Using seven years' worth of high-resolution radiosonde measurements at 120 sites, we compile the climatology of lower tropospheric TI in terms of frequency, intensity, and depth during the period from 2011 to 2017. The TI generally exhibits strong seasonal and geographic dependencies. Particularly, the TI frequency is found to be high in winter and low in summer, likely due to the strong aerosol radiative effect in winter. The frequency of the surface-based inversion (SBI) exhibits a ''west low, east high'' pattern at 0800 Beijing time (BJT), which then switches to ''west high, east low'' at 2000 BJT. Both the summertime SBI and elevated inversion (EI) reach a peak at 0800 BJT and a trough at 1400 BJT. Interestingly, the maximum wintertime EI frequency occurs over Southeast China (SEC) rather than over the North China Plain (NCP), likely attributable to the combination of the heating effect of black carbon (BC) originating from the NCP, along with the strong subsidence and trade inversion in SEC. Correlation analyses between local meteorology and TI indicate that larger lower tropospheric stability (LTS) favors more frequent and stronger TIs, whereas the stronger EI under smaller LTS conditions (unstable atmosphere) is more associated with subsidence rather than BC. Overall, the spatial pattern of the lower tropospheric TI and its variability in China are mainly controlled by three factors: local meteorology, large-scale subsidence, and BC-induced heating. These findings help shed some light on the magnitude, spatial distribution, and underlying mechanisms of the lower tropospheric TI variation in China. [ABSTRACT FROM AUTHOR]

Recent studies demonstrated the existence of a conspicuous atmospheric combination mode (C-mode) originating from nonlinear interactions between El Niño–Southern Oscillation (ENSO) and the Pacific warm pool annual cycle (AC). Here we find that the C-mode exhibits prominent decadal amplitude variations during the ENSO decaying boreal spring season. It is revealed that the Atlantic multidecadal oscillation (AMO) can largely explain this waxing and waning in amplitude. A robust positive correlation between ENSO and the C-mode is detected during a negative AMO phase but not during a positive phase. Similar results can also be found in the relationship of ENSO with 1) the western North Pacific (WNP) anticyclone and 2) spring precipitation over southern China, both of which are closely associated with the C-mode. We suggest that ENSO property changes due to an AMO modulation play a crucial role in determining these decadal shifts. During a positive AMO phase, ENSO events are distinctly weaker than those in an AMO negative phase. In addition, El Niño events concurrent with a positive AMO phase tend to exhibit a westward-shifted sea surface temperature (SST) anomaly pattern. These SST characteristics during the positive AMO phase are both not conducive to the development of the meridionally asymmetric C-mode atmospheric circulation pattern and thus reduce the ENSO/C-mode correlation on decadal time scales. These observations can be realistically reproduced by a coupled general circulation model (CGCM) experiment in which North Atlantic SSTs are nudged to reproduce a 50-yr sinusoidally varying AMO evolution. Our conclusion carries important implications for understanding seasonally modulated ENSO dynamics and multiscale climate impacts over East Asia. [ABSTRACT FROM AUTHOR]

The present study investigates the interdecadal changes in the relationship between El Niño–Southern Oscillation (ENSO) and midlatitude North Atlantic (MNA) sea surface temperature (SST) with northwest China (NWC) winter precipitation (WP) variability and the plausible causes. Results show that ENSO and MNA SST have weak correlations with NWC WP before the mid-1990s, whereas the connections are enhanced sharply afterward, with above (below) normal precipitation occuring when there are positive (negative) ENSO SST and negative (positive) MNA SST anomalies (SSTA). Remarkable differences are found in the atmospheric circulations. After the mid-1990s, there is a pronounced Pacific–North American–Eurasian (PNA-EU)-like pattern in the Northern Hemisphere, whereas an Arctic Oscillation–like pattern is found before the mid-1990s. The change in the relationships between NWC WP and SSTs is likely attributable to the enhanced connection between ENSO and MNA SST after the mid-1990s. It is found that ENSO and MNA SSTA can cause NWC WP variation independently through atmospheric teleconnections. In addition, significant precipitation anomalies also occur when concurrent but oppositely signed SSTs anomalies in the two regions are observed. The reinforced negative correlations between ENSO and MNA SST after the mid-1990s act in concert on NWC WP by exciting a PNA-EU-like pattern. This information would help us to better understand the physical processes of the teleconnections between NWC WP variability and the ENSO/MNA SST, in which the strength of the correlation between ENSO and MNA SST should be taken into account. [ABSTRACT FROM AUTHOR]

Stationarity is an assumption that permeates training and practice in water-resource engineering. However, with global change, the validity of stationarity as well as uncertainty of nonstationarity in water-resource planning are being questioned; thus, it is critical to evaluate the stationarity of climate variables, especially precipitation. Based on the continuous observation data of precipitation from 1427 stations across China, 593 efficient grid cells (1° × 1°) are constructed, and the annual precipitation stationarities from 1959 to 2018 are analyzed. The evaluated autocorrelation stationarity indicates that 92.24%–96.12% of the grid cells for an autocorrelation coefficient of lag 1–8 years of precipitation are indistinguishable from 0 [90% confidence level (CL)]. The mean stationarity indicates that 97.47% of the grid cells have a stable mean for 30 years (90% CL); beyond the confidence limits, they are mainly located in the northwest of China, where annual precipitation is less, and the average exceeding range is ±3.78 mm. The long-term observation of annual precipitation in Beijing (1819–2018) and Shanghai (1879–2018) also yields autocorrelation and mean stationarities. There is no significant difference in the annual precipitations between the past 20 years (1999–2018) and the past 60 years (1959–2018) over China. Therefore, the annual precipitation in China exhibits a weak stationary behavior that is indistinguishable from the stationary stochastic process. The average variation in precipitation is ±9.55% between 30 successive years and 16.53% between 10 successive years. Therefore, it is valuable and feasible to utilize the historical data of annual precipitation as the basis of water-resources application. [ABSTRACT FROM AUTHOR]

Temperature seasonality, the difference between summer and winter temperatures in mid–high latitudes, is an important component of the climate. Whether humans have had detectable influences on changing surface temperature seasonality at scales smaller than the subcontinental scale, where humans are directly impacted, is not clear. In this study, the first detection and attribution analysis of changes in temperature seasonality in China has been carried out. Detection and attribution of both summer and winter temperatures were also conducted, with careful consideration of observational uncertainty and the inconsistency between observation and model simulations induced by the long coastline and country border in China. The results show that the response to external forcings is robustly detectable in the spatiotemporal pattern of weakening seasonality and in that of warming winter temperature, although models may have underestimated the observed changes. The response to external forcings is detectable and consistent with the observed change in summer temperature averaged over China. Human influences are detectable in changes in seasonality and summer and winter temperatures, most robustly in winter, and these influences can be separated from those of natural forcing when averaged over China. The recent increase in summer temperature was found to be due to external forcings, and the warming hiatus in winter temperature from 1998 to 2013 was due to a statistically significant cooling trend induced by internal variability. These results will give insights into the understanding of the warming hiatus in China, as well as the hot summers and cold winters in recent years. [ABSTRACT FROM AUTHOR]

This study introduces a multivariable covariance index (MVCI) to illustrate the synoptic features of mei-yu in the Yangtze River valley (YRV) region, which contains information of three indicators of mei-yu including precipitation, surface relative humidity, and tropospheric vertical motion. The interdecadal variation in the synoptic features of mei-yu during 1961–2016 is investigated using the MVCI. The date of mei-yu peak and the intensity of mei-yu underwent noticeable interdecadal variations over past decades, which are characterized by a delayed (relatively early) mei-yu peak and a relatively large (small) mei-yu intensity during 1985–97 (1961–80 and 2006–16). The mechanisms of these interdecadal variations are further discussed. The interdecadal variation in the date of mei-yu peak is mainly modulated by the meridional water vapor transport over eastern China during June, which may be partially attributed to an influence of the Pacific decadal oscillation (PDO) on the clockwise gyre over the North Pacific during boreal summer. The interdecadal variation in mei-yu intensity is associated with the interdecadal variation of tropospheric vertical motion over the YRV region during boreal summer, which may be partially attributed to an interaction between the PDO and the large-scale tropical east–west circulation during boreal summer. In addition, the interdecadal variation in the water vapor flux budget and relative humidity over the YRV region also exerted an impact on the interdecadal variation of mei-yu intensity in the YRV region. [ABSTRACT FROM AUTHOR]

Evaluation of Chinese precipitation extremes is conducted based on large ensemble projections of the present climate and 4-K-warmer climates derived from a high-resolution atmospheric general circulation model. The model reproduced the overall trend and magnitude of total precipitation and extreme precipitation events for China reasonably well, revealing that this dataset can represent localized precipitation extremes. Precipitation extremes are more frequent and more severe in future projections under 4-K-warmer climates than in the representative concentration pathway 8.5 (RCP8.5) scenario of phase 5 of the Coupled Model Intercomparison Project (CMIP5). Our results show that using a large-ensemble simulation can improve the ability to estimate with high precision both the precipitation mean and the precipitation extremes compared with small numbers of simulations, and the averaged maximum yearly precipitation will be likely to increase by approximately 18% under a +4-K future in southern China compared with the past. Finally, uncertainty evaluation in future precipitation projections indicates that the component caused by the difference in six ΔSST patterns is more important in southern China compared with the component due to the atmospheric internal variability. All these results could provide valuable insights in simulating and predicting precipitation extremes in China. [ABSTRACT FROM AUTHOR]

Although the impact of the North Atlantic Oscillation (NAO), especially the antecedent NAO in winter and spring, on East Asian summer climate has been studied extensively, the possible connection from the summer NAO (SNAO) and then the Tibetan Plateau (TP) to East China summer rainfall remains unclear. This study reveals that on interannual time scales the SNAO is significantly correlated with the variations of East China summer rainfall and the thermal forcing of the TP provides an intermediate bridge effect in this Eurasian teleconnection. The SNAO primarily regulates the rainfall variability over the TP through large-scale wave trains and the TP rainfall anomalies in turn lead to a change in local diabatic heating, which excites Rossby waves to the downstream regions. To the northeast of the TP, an anomalous barotropic cyclone is formed in the nearly entire troposphere, generating low-level northerly flow anomalies over northern China. Meanwhile, the TP heating also induces low-level southerly flow anomalies over southern China. The anomalous northerly and southerly winds converge in the lower troposphere, enhancing the summer rainfall over central East China. Compared to the SNAO, the TP thermal forcing exerts a more direct impact on the variations of East China summer rainfall in the Eurasian teleconnection discussed. [ABSTRACT FROM AUTHOR]

Compared to traditional drought events, flash droughts evolve rapidly during short-termextreme atmospheric conditions,with a lasting period of one pentad to severalweeks. There are two main categories of flash droughts: the heatwave flash drought (HWFD), which is mainly caused by persistent high temperatures (heatwaves), and the precipitation deficit flash drought (PDFD), which is mainly triggered by precipitation deficits. The authors' previous research focused on the characteristics and causes of flash drought based on meteorological observations and Variable Infiltration Capacity (VIC) model simulations in a humid subtropical basin (Gan River basin, China). In this study, the authors evaluated the downscaled phase 5 of the CoupledModel Intercomparison Project (CMIP5)models' simulations, coupledwith theVICmodel (CMIP5-VIC) in reproducing flash droughts in a humid subtropical basin in China. Most downscaled CMIP5-VIC simulations can reproduce the spatial patterns of flash droughts with respect to the benchmarks. The coupled models fail to readily replicate interannual variation (interannual pentad change), but most models can reflect the interannual variability (temporal standard deviation) and long-term average pentads of flash droughts. It is difficult to simultaneously depict both the spatial and temporal features of flash droughts within only one coupled model. The climatological patterns of the best multimodel ensemble mean are close to those of the all-model ensemble mean, but the best multimodel ensemble mean has a minimal bias range and relatively low computational burden. [ABSTRACT FROM AUTHOR]

In this study, temporal trends and spatial patterns of extreme temperature change are investigated at 352 meteorological stations in China over the period 1956-2013. The temperature series are first examined for evidence of long-range dependence at daily and monthly time scales. At most stations there is evidence of significant long-range dependence. Noncrossing quantile regression has been used for trend analysis of temperature series. For low quantiles of daily mean temperature and monthly minimum value of daily minimum temperature (TNn) in January, there is an increasing trend at most stations. A decrease is also observed in a zone ranging from northeastern China to central China for higher quantiles of daily mean temperature and monthly maximum value of daily maximum temperature (TXx) in July. Changes of the large-scale atmospheric circulation partly explain the trends of temperature extremes. To reveal the spatial pattern of temperature changes, a density-based spatial clustering algorithm is used to cluster the quantile trends of daily temperature series for 19 quantile levels (0.05, 0.1, ..., 0.95). Spatial cluster analysis identifies a few large clusters showing different warming patterns in different parts of China. Finally, quantile regression reveals the connections between temperature extremes and two large-scale climate patterns: El Niño-Southern Oscillation (ENSO) and the Arctic Oscillation (AO). The influence of ENSO on cold extremes is significant at most stations, but its influence on warm extremes is only weakly significant. The AO not only affects the cold extremes in northern and eastern China, but also affects warm extremes in northeastern and southern China. [ABSTRACT FROM AUTHOR]

The relation of spring (March-May) to summer (July-August) precipitation in eastern China is examined using observed data. It is found that when spring precipitation from the lower and middle reaches of the Yangtze River valley to northern China (the YRNC region) is higher (lower), more (less) summer precipitation occurs in northeastern China and the lower and middle reaches of the Yangtze River valley, and less (more) in southeastern China. The analysis of physical mechanism showed that higher (lower) spring precipitation in the YRNC region is closely related to wet (dry) spring soil moisture, which decreases (increases) the surface temperature and sensible heat flux in late spring. Because the memory of spring soil moisture in the YRNC region reaches about 2.4 months, the surface thermal anomaly lasts into the subsequent summer, resulting in a weak (strong) East Asian summer monsoon. A weak East Asian summer monsoon corresponds to an anomalous anticyclone and a cyclone over southeastern and northeastern China, respectively, in the lower troposphere. The anomalous anticyclone depresses the summer precipitation in southeastern China, and the anomalous cyclone promotes precipitation over northeastern China. The abnormal northerly and southerly winds associated with the anomalous cyclone and anticyclone, respectively, converge in the lower and middle reaches of the Yangtze River valley, inducing more summer precipitation there. [ABSTRACT FROM AUTHOR]

Daytime (0800-2000 Beijing time) and nighttime (2000-0800 Beijing time) precipitation at approximately 2100 stations in China from 1979 to 2014 was used to evaluate eight current reanalyses. Daytime, nighttime, and nighttime-daytime contrast of precipitation were examined in aspects of climatology, seasonal cycle, interannual variability, and trends. The results show that the ECMWF interim reanalysis (ERA-Interim), ERA-Interim/Land, Japanese 55-year Reanalysis (JRA-55), and NCEP Climate Forecast System Reanalysis (CFSR) can reproduce the observed spatial pattern of nighttime-daytime contrast in precipitation amount, exhibiting a positive center over the eastern Tibetan Plateau and a negative center over southeastern China. All of the reanalyses roughly reproduce seasonal variations of nighttime and daytime precipitation, but not always nighttime-daytime contrast. The reanalyses overestimate drizzle and light precipitation frequencies by greater than 31.5% and underestimate heavy precipitation frequencies by less than −30.8%. The reanalyses successfully reproduce interannual synchronizations of daytime and nighttime precipitation frequencies and amounts with an averaged correlation coefficient r of 0.66 against the observed data but overestimate their year-to-year amplitudes by approximately 64%. The trends in nighttime, daytime, and nighttime-daytime contrast of the observed precipitation amounts are mainly dominated by their frequencies ( r = 0.85). Less than moderate precipitation frequency has exhibited a significant downward trend (−2.5% decade−1 during nighttime and −1.7% decade−1 during daytime) since 1979, which is roughly captured by the reanalyses. However, only JRA-55 captures the observed trend of nighttime precipitation intensity (2.4% decade−1), while the remaining reanalyses show negative trends. Overall, JRA-55 and CFSR provide the best reproductions of the observed nighttime-daytime contrast in precipitation intensity, although they have considerable room for improvement. [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]

The Tibetan Plateau (TP) has an average elevation of over 4000 m and with its surrounding mountains is regarded as Earth's 'third pole.' As a result of its size and height, climate change in the TP has its own unique characteristics that include a proposed positive correlation between the surface temperature and pressure. This study examines the trends and relationships between the surface pressure and temperature in the TP through the examination of monthly mean data from 71 stations during 1961-2013. On annual, seasonal, and monthly time scales, the TP exhibits a statistically significant warming trend that attains a rate of 0.30°C decade−1 for annual means over the period 1961-2013. The most pronounced warming occurs in winter, in agreement with previous studies, with evidence of acceleration in the rate after the mid-1980s and the global warming slowdown period. For the entire period of 1961-2013, the surface pressure in the TP has a positive trend of 0.08 hPa decade−1 on an annual basis, again with the largest trends occurring in winter. However, unlike what occurred with the surface temperature, the trend in surface pressure, in most cases, reversed sign after the mid-1980s. The trend in the geopotential height at 500 hPa from the National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP-NCAR) reanalysis is consistent with the observed surface pressure trends. Over the period 1961-2013, there is a seasonal shift in the nature of the relationship between the surface temperature and pressure with a negative correlation during summer and autumn, and a positive correlation during winter. This suggests that the nature of the relationship between these two climate elements reflects the changing nature of the seasonal snow cover (land surface property) and cloud in the region. [ABSTRACT FROM AUTHOR]