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This paper investigates the sensitivity of projected future climate changes over China to the horizontal resolution of a regional climate model RegCM4.4 (RegCM), using RCP8.5 as an example. Model validation shows that RegCM performs better in reproducing the spatial distribution and magnitude of present-day temperature, precipitation and climate extremes than the driving global climate model HadGEM2-ES (HadGEM, at 1.875° × 1.25° degree resolution), but little difference is found between the simulations at 50 and 25 km resolutions. Comparison with observational data at different resolutions confirmed the added value of the RCM and finer model resolutions in better capturing the probability distribution of precipitation. However, HadGEM and RegCM at both resolutions project a similar pattern of significant future warming during both winter and summer, and a similar pattern of winter precipitation changes including dominant increase in most areas of northern China and little change or decrease in the southern part. Projected precipitation changes in summer diverge among the three models, especially over eastern China, with a general increase in HadGEM, little change in RegCM at 50 km, and a mix of increase and decrease in RegCM at 25 km resolution. Changes of temperature-related extremes (annual total number of daily maximum temperature > 25 °C, the maximum value of daily maximum temperature, the minimum value of daily minimum temperature in the three simulations especially in the two RegCM simulations are very similar to each other; so are the precipitation-related extremes (maximum consecutive dry days, maximum consecutive 5-day precipitation and extremely wet days’ total amount). Overall, results from this study indicate a very low sensitivity of projected changes in this region to model resolution. While fine resolution is critical for capturing the spatial variability of the control climate, it may not be as important for capturing the climate response to homogeneous forcing (in this case greenhouse gas concentration changes). [ABSTRACT FROM AUTHOR]

In this paper, the intensity, area and duration of future droughts in China are analyzed using the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI). The SPI and SPEI are used to evaluate the simulation ability of drought characteristics with the regional climate model COSMO-CLM (CCLM). The projected intensity and duration of future drought events are analyzed for the period 2016-2050 under three different respective concentration pathways (RCPs). The simulated and projected drought events are analyzed by applying the intensity-area-duration method. The results show that CCLM has a robust capability to simulate the average drought characteristics, while some regional disparities are not well captured, mainly the simulation of more drought events of shorter duration in Northwest China. For the future period 2016-2050, more intense dryness conditions are projected for China. An increase in evapotranspiration is found all over China, while a reduction in precipitation is apparent in the southern river basins. The increase in evapotranspiration plays an important role in the changes of future droughts over the northern river basins and southern river basins. Under RCP2.6, drought events of longer duration and with higher frequency are projected for the southwest and southeast of China. Under RCP4.5 and RCP8.5, a continuing tendency to more dry conditions is projected along a dryness band stretching from the southwest to the northeast of China. More frequent drought events of longer duration are projected in the southwestern river basins. For all future droughts, larger extents are projected, especially for events with long-term duration. The projected long-term drought events will occur more often and more severe than during the baseline period, and their central locations will likely shift towards Southeast China. The results of this study can be used to initiate and strengthen drought adaptation measures at regional and local scale, especially in the south of China. [ABSTRACT FROM AUTHOR]

China faces an increasing challenge in water resources in the coming decades; thus high-confidence climate projection is of particular importance for the country's future. In this paper, we evaluate the performance of a long high-resolution continuous simulation over China based on multiple observations and the corresponding historical simulation. The simulation is completed using the Weather Research and Forecasting (WRF) model driven by the Model for Interdisciplinary Research on Climate version 5 (MIROC5) in the context of the Coupled Model Intercomparison Project Phase 5. The results show that both MIROC5 and WRF can capture the distribution and variability of temperature over China, whereas WRF shows improvements, particularly for simulation of regional features. Compared with MIROC5, WRF can reproduce the spatial distribution, annual cycle, probability distribution, and seasonal evolution of the precipitation over mainland China and the sub-regions with better performance. The trend is of fundamental importance in the future projection estimations, and WRF shows better skill in simulating the annual mean precipitation trend. However, there is overestimation of precipitation in Southeast China while negative one in the middle latitude of China in WRF simulation, which can be traced back to model bias in atmospheric circulation and water vapor transportation in these regions. Several extreme climate indices are selected to further assess the model's performance in simulating climate extremes, WRF can well reproduce the main features with better model skill compared with MIROC5. The better performance of WRF indicates the necessity of the dynamical downscaling technique and the robustness of regional climate simulation in future regional climate projection over China. [ABSTRACT FROM AUTHOR]

Extreme heat events happen frequently in East Asia, and may cause great damage to the ecosystem and society. The synergistic effect of the summer positive North Atlantic Oscillation (pNAO) and positive northwest Pacific (pNWP) sea surface temperature anomaly (SSTA) on the interannual variability of the extreme heat events in the central–eastern China (CEC) is investigated in this study. The two factors act synergistically in strengthening the extreme heat events in the CEC via a series of atmospheric bridges, and the CEC is likely to experience a hotter summer when both the summer pNAO and pNWP SSTA occur. The pNWP SSTA increases the strength of pNAO via the eastward propagating Rossby wave from the western Pacific. The enhanced pNAO induces a stronger eastward Rossby wave propagation across the Eurasian continent, and leads to a strong anomalous anticyclone over the CEC. The significantly increased atmosphere thickness increases the air temperature of the layer, and favors the extreme heat events in the CEC. Besides, the pNWP SSTA also has adjacent effect on the atmospheric circulation over the CEC, which could lead to a positive geopotential height anomaly. Therefore, the summer pNAO and pNWP SSTA act synergistically in influencing the atmospheric circulation over the CEC, and thereby significantly increase the extreme heat events in the CEC. [ABSTRACT FROM AUTHOR]

Vegetation is one of the most important parts of the Earth's land surface system. To investigate the impact and uncertainty of multi-source vegetation data on climate simulations in East Asia, we have compared two Fractional Vegetation Cover (FVC) and five Leaf Area Index (LAI) products and then performed seven experiments from 1999 to 2018 with the WRF model. The results suggest that the sensitivity of vegetation climatology is large especially in south East Asia, with a maximum difference of 4 m2/m2 in LAI and 16% in FVC. For the mean temperature, the responses in East Asia are between ± 0.4 K, and the uncertainty over the Chinese Mainland gradually enhances with the rapid vegetation growth. The feedback of precipitation is highly heterogeneous with sensitivities ranging between ± 1 mm. For interannual variability, vegetation has a greater impact in summer and autumn. The uncertainty of temperature and precipitation in summer over the Chinese Mainland is 118 and 1754 times that in winter. In addition, the linear trend results also indicate that the maximum trend difference in temperature is around 0.04 K/a in eastern China, while the precipitation has a larger range of 0.04–0.10 mm/a in southern East Asia. Besides, the biophysical mechanism analysis suggests that vegetation impact on surface energy budget is mainly a competition between albedo feedback and moisture feedback, and the large differences in multi-source FVC and LAI are sufficient to simulate different or even opposite feedbacks. [ABSTRACT FROM AUTHOR]

Air turbulence, especially the clear-air turbulence (CAT), always affects flight safety. Based on six CAT diagnostics and ERA5 reanalysis data, the spatiotemporal characteristics of CAT potential in the middle and upper troposphere in China during 1979–2020 and the possible mechanisms are analyzed in this study. The results show that CAT occurs the most frequently in winter and spring at 250–300 and 200–225 hPa, respectively. In general, CAT occurs relatively less in summer and autumn. Moreover, the CAT potential decreases with altitude in each season, and the high-magnitude centers gradually move northward and eastward accompanied with a rising motion from winter to summer. During 1979–2020, the CAT potential shows clear increasing trends in most of China in winter, while decreasing trends in most regions in summer. In the "high CAT frequency region (HCFR, 75–135° E, 25–45° N)", the CAT potential has been significantly increasing in winter and decreasing in summer. Mechanism analysis indicates that the spatiotemporal distribution of East Asian subtropical westerly jet is well correlated with the CAT potential in the HCFR, with the spatial (temporal) correlation coefficients greater than 0.75 (0.54). In addition, the geopotential height pattern in various regions, the zonal circulation in the Eurasia and Atlantic, the Polar Vortex, the Subtropical High, and the sea surface temperature all have significant impact on the CAT in the HCFR. [ABSTRACT FROM AUTHOR]

In recent decades, China has experienced intense land use and cover change (LUCC). In this study, we modeled and explored the possible effects and mechanisms of realistic LUCCs on surface temperatures in China during 1984–2013 using the Regional Climate Model (RegCM) based on the annual dynamic LUCCs derived from Global Land Surface Satellite (GLASS-GLC) data. We compared two sets of ensemble experiments, one with a fixed LUCC scenario (fixed at 1984) and the other with a dynamic LUCC scenario (annual conversions from 1984 to 2013). The results showed that LUCCs in recent decades have been characterized by reforestation (accompanied by a reduction in cropland) in southern China, grassland-to-cropland conversions in North and Northeast China and bare land-to-grassland conversions in northwestern China. Such LUCCs led primarily to significant cooling of the daily maximum surface temperature (Tsmax) by approximately − 0.3 to − 0.6 °C in summer and autumn over the reforestation areas of southern China, followed by moderate cooling (~ − 0.2 °C) of the daily mean surface temperature (Ts), while the effect on the daily minimum surface temperature (Tsmin) was weak (within ± 0.1 °C) and nonsignificant. During winter and spring, the impacts of LUCC on all temperatures were less pronounced. Further investigation revealed that the cooling of Tsmax was dominated by the direct effects of LUCC (over 90%), particularly the reduction in aerodynamic resistance associated with the cropland-to-forest conversions in southern China. Additionally, seasonal differences and uncertainties in the LUCC-induced cooling of Tsmax were likely due to a combination of the relatively stable direct effect of LUCC and the uncertain model internal variability. Overall, our study highlights the effects of realistic and transient LUCC scenarios, which could provide insightful scientific clues to better assess and understand climate change. [ABSTRACT FROM AUTHOR]

Extreme precipitation often causes enormous economic losses and severe disasters. Changes in extreme precipitation potentially have large impacts on the human society. In this study, we investigated the changes in four precipitation extreme indices over China during 1961 ~ 2014. The indices include total wet-day precipitation (PRCPTOT), precipitation on extremely wet days (R95pTOT), number of extremely wet days (R95d) and precipitation intensity on extremely wet days (R95int) during the extended summer (May-August). Observation analyses showed that these four indices have significantly increased over southeast China (SEC) and northwest China (NWC) whilst decreased over northeast China (NEC) and southwest China (SWC). Based on HadGEM3-GC3.1 historical, greenhouse gas only (GHG) and anthropogenic aerosol only (AA) simulations, we assessed the relative roles of different forcings in the observed trends. Model reproduced the main features of increasing trends over SEC and NWC in historical simulations, suggesting a dominant role of forced changes in the trends of four indices over the two regions. Individual forcing simulations indicated that GHG and AA forcings influence the increases in summer extreme precipitation over SEC and NWC, respectively, through different processes. Over SEC, extreme precipitation increase is mainly due to GHG forcing that results in moisture flux convergence increase through thermodynamic and dynamic effects. In comparison to GHG forcing, AA forcing has a weak contribution because AA forced moisture flux convergence increase is offset by AA forced evaporation reduction. Over NWC, extreme precipitation increase is primarily attributed to AA forcing and secondarily to GHG forcing. AA forcing can result in moisture flux convergence increase through dynamic effect, and GHG forcing can result in evaporation increase. [ABSTRACT FROM AUTHOR]

Extreme climate events have exerted strong effects on permafrost environments over the past few decades. The occurrence of extreme warming events during the cold season can alter the hydrothermal dynamics of the active layer. Here, we used meteorological and observational soil hydrothermal data to investigate variations in extreme warming events and their impacts on the hydrothermal regimes of the active layer in three permafrost regions in China. The results indicated that the eight analyzed extreme warming indices showed statistically significant increasing trends with differing rates from 1962 to 2019. Prominent differences existed in the mean values and linear trend magnitudes not only among the three permafrost regions but also among the eight indices. Most recorded high-intensity extreme warming events occurred primarily in the past 15 years (2005–2019). The occurrence times of extreme events and the active layer freeze–thaw process codetermined the influential extents of the extreme events on the active layer hydrothermal conditions at the Tanggula permafrost Monitoring Site. Events that occurred from March to April could cause soil temperature to increase with a greater magnitude than that induced by events occurring from October to November. Different event types could also lead to distinct differences in their corresponding influential extents. [ABSTRACT FROM AUTHOR]

Understanding future drought risks plays a crucial role in developing climate change adaptation strategies and in enhancing disaster resilience. However, previous studies may lead to biased conclusions due to the neglect of two factors, including the relative performance of climate simulations and the uncertainty in drought characterization. In this study, Bayesian model averaging is used to merge five regional climate model simulations and to project future changes in hydroclimatic regimes over China under two representative emission scenarios (RCP4.5 and RCP8.5). Drought characteristics, including drought severity and duration, are extracted using the Standardized Precipitation Evapotranspiration Index (SPEI). A Bayesian copula approach is used to uncover underlying interactions of drought characteristics and associated uncertainties across 10 climate divisions of China. The regional return periods of drought characteristics are used to assess future changes in multidimensional drought risks and the probability of extreme droughts. Our findings reveal that the variations in drought characteristics are generally underestimated by the ensemble mean (AEM) simulation. The Bayesian framework improves the reliability and accuracy of hydroclimate simulations and better reproduces the drought regimes compared to the AEM simulation. The drought duration and severity are projected to substantially increase for most areas of China based on the Bayesian framework, but the AEM simulation may lead to multiple opposite behaviors, especially under RCP4.5. The estimated joint risk from drought duration and drought severity is expected to increase under both emission scenarios. The likelihood of extreme droughts is also projected to increase as the radiative forcing increases. [ABSTRACT FROM AUTHOR]

Two different bias correction methods, the quantile mapping (QM) and quantile delta mapping (QDM), are applied to simulated daily temperature and precipitation over China from a set of 21st century regional climate model (the ICTP RegCM4) projections. The RegCM4 is driven by five different general circulation models (GCMs) under the representative concentration pathway RCP4.5 at a grid spacing of 25 km using the CORDEX East Asia domain. The focus is on mean temperature and precipitation in December–January–February (DJF) and June–July–August (JJA). The impacts of the two methods on the present day biases and future change signals are investigated. Results show that both the QM and QDM methods are effective in removing the systematic model biases during the validation period. For the future changes, the QDM preserves the temperature change signals well, in both magnitude and spatial distribution, while the QM artificially modifies the change signal by decreasing the warming and modifying the patterns of change. For precipitation, both methods preserve the change signals well but they produce greater magnitude of the projected increase, especially the QDM. We also show that the effects of bias correction are variable- and season-dependent. Our results show that different bias correction methods can affect in different way the simulated change signals, and therefore care has to be taken in carrying out the bias correction process. [ABSTRACT FROM AUTHOR]

A new bias-corrected, statistically downscaled product, the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset, has been developed and released to help in understanding climate change at local to regional scales. Here, we evaluate the performance of the NEX-GDDP data in simulating daily maximum temperature (TX) and daily minimum temperature (TN) in the historical period 1961–2005 over China at national and regional scales. Projected future changes in TX and TN are assessed under the Representative Concentration Pathways (RCPs) 4.5 and 8.5 emissions scenarios. Results show that the NEX-GDDP data can capture the basic spatial patterns of TX and TN, but these results underestimate the warming trends of TX and TN from 1961 to 2005 over China. The largest biases are found in western China due to its complex terrain conditions; these biases are 2.33 and 2.21 times larger than those found in eastern China for TX and TN, respectively. The climate projections show that the difference in uncertainties is small between the east and the west, and higher warming changes correspond to greater uncertainties. The increasing trends under the RCP8.5 are 2.22 and 2.31 times the size found under the RCP4.5 by the end of the twenty-first century for TX and TN, respectively. The Tibetan plateau has the fastest warming trend under the two scenarios. [ABSTRACT FROM AUTHOR]

Soil temperature is an important variable of earth's surface system, and studying it is of great benefit to understanding the energy and hydrological cycles and climate change. Based on soil temperature data at a depth of 3.2 m from 113 stations in China from 1980 to 2017, the spatial distribution and temporal variation of the soil temperatures in China were analyzed by using a fuzzy C-means algorithm (FCM), linear fitting and the Mann–Kendall method. The results show that the average annual soil temperature at 3.2 m in China gradually increased from north to south, with the lowest temperatures in the northeast and Qinghai–Tibetan Plateau ( T 3.2 m ≤ 5 ∘ C ) and the highest in South China ( T 3.2 m ≥ 25 ∘ C ). The country is divided into 10 regions using the FCM method. The soil temperature anomalies show a continuous increase over time, but there are significant regional differences in the warming speeds. The northeast and northwest regions exhibit the largest temperature increases, approximately 0.57 ° C / 10 a , North China has the second highest increases, with approximately 0.36 ° C / 10 a , and the values in other areas are less than 0.3 ° C / 10 a . Over the 38-year period, the soil temperature increased by approximately 1.4 ° C , and the temperature increase mainly occurred during the last 20 years. The positive center of the annual soil temperature anomaly at 3.2 m in the Qinghai–Tibetan Plateau during the last 2 decades of the twentieth century became cooling to a negative soil temperature anomaly at 3.2 m during the first 2 decades of the twenty-first century. The negative centers for the annual soil temperature anomaly at 3.2 m in the south of Shaanxi and the middle reaches of the Yangtze River during the last 2 decades of the twentieth century became warming to positive soil temperature anomalies at 3.2 m in the first 2 decades of the twenty-first century. In the other regions, different turning points of the positive–negative temperature anomaly are exhibited at 3.2 m. [ABSTRACT FROM AUTHOR]

Simulation of surface air temperature over China from a set of regional climate model (RCM) climate change experiments are analyzed with the focus on bias and change signal of the RCM and driving general circulation models (GCMs). The set consists of 4 simulations by the RCM of RegCM4 driven by 4 different GCMs for the period of 1979–2099 under the mid-range RCP4.5 (representative concentration pathway) scenario. Results show that for present day conditions, the RCM provides with more spatial details of the distribution and in general reduces the biases of GCM, in particular in DJF (December–January–February) and over areas with complex topography. Bias patterns show some correlation between the RCM and driving GCM in DJF but not in JJA (June–July–August). In JJA, the biases in RCM simulations show similar pattern and low sensitivity to the driving GCM, which can be attributed to the large effect of internal model physics in the season. For change signals, dominant forcings from the driving GCM are evident in the RCM simulations as shown by the magnitude, large scale spatial distribution, as well as interannual variation of the changes. The added value of RCM projection is characterized by the finer spatial detail in sub-regional (river basins) and local scale. In DJF, profound warming over the Tibetan Plateau is simulated by RCM but not GCMs. In general no clear relationships are found between the model bias and change signal, either for the driving GCMs or nested RCM. [ABSTRACT FROM AUTHOR]

Four statistical downscaling methods, that is, three quantile mapping based techniques including bias-correction and spatial downscaling (BCSD), bias-correction and climate imprint (BCCI), and bias correction constructed analogues with quantile mapping reordering (BCCAQ), and the cumulative distribution function transform (CDF-t) method, are evaluated with daily observed precipitation and surface temperature for 1961–2005 over China. The four downscaling methods improve the accuracy over the driving general climate models (GCMs) significantly in terms of spatial variability, bias, seasonal cycle, and probability density functions of daily series and extreme events. Overall, BCSD outperforms other methods in frequency distributions of daily temperature, precipitation, and extreme precipitation indices such as wet and dry spell lengths. But it comparably has larger biases in temperature-related extremes. When downscaling the seasonal and extreme precipitation, the three quantile mapping based techniques exhibit better capacity than CDF-t in terms of the spatial correlation and bias over all subregions. Whereas CDF-t methods overestimate consecutive wet days and extreme wet indices significantly, as it displays limited improvement over the driving GCMs by producing too many drizzle days using either absolute or relative threshold. All methods are equally skillful in downscaling monthly and seasonal temperature, and the temperature extremes are better reproduced by BCCI, BCCAQ and CDF-t. However, the statistical downscaling methods show limited capacity in improving the interannual variability of temperature and precipitation extremes. [ABSTRACT FROM AUTHOR]

The changes in three aspects of frequency, intensity and duration of the compound, daytime and nighttime heat waves (HWs) over China during extended summer (May–September) in a future period of the mid-21st century (FP; 2045–2055) under RCP4.5 scenario relative to present day (PD; 1994–2011) are investigated by two models, MetUM-GOML1 and MetUM-GOML2, which comprise the atmospheric components of two state-of-the-art climate models coupled to a multi-level mixed-layer ocean model. The results show that in the mid-21st century all three types of HWs in China will occur more frequently with strengthened intensity and elongated duration relative to the PD. The compound HWs will change most dramatically, with the frequency in the FP being 4–5 times that in the PD, and the intensity and duration doubling those in the PD. The changes in daytime and nighttime HWs are also remarkable, with the changes of nighttime HWs larger than those of daytime HWs. The future changes of the three types of HWs in China in two models are similar in terms of spatial patterns and area-averaged quantities, indicating these projected changes of HWs over the China under RCP4.5 scenario are robust. Further analyses suggest that projected future changes in HWs over China are determined mainly by the increase in seasonal mean surface air temperatures with change in temperature variability playing a minor role. The seasonal mean temperature increase is due to the increase in surface downward longwave radiation and surface shortwave radiation. The increase in downward longwave radiation results from the enhanced greenhouse effect and increased water vapour in the atmosphere. The increase in surface shortwave radiation is the result of the decreased aerosol emissions, via direct aerosol–radiation interaction and indirect aerosol–cloud interaction over southeastern and northeastern China, and the reduced cloud cover related to a decrease in relative humidity. [ABSTRACT FROM AUTHOR]

Despite the importance of seasonal distribution and interannual variability of rainfall to the ecosystem and society, there is a lack of regional-level studies on rainfall seasonality, and teleconnections between global climate events and rainfall seasonality are not well understood. To address these issues, this study analyzed the spatial and temporal characteristics of rainfall seasonality across China from 1961 to 2012. A novel application of information theory-based rainfall seasonality indicators was conducted at the regional scale, and observed monthly precipitation data was used. The rainfall seasonality anomalies during negative and positive phases of the El Niño–Southern Oscillation, Indian Ocean Dipole, North Atlantic Oscillation, and Pacific Decadal Oscillation, and the possible physical mechanisms behind were also investigated. The results showed that rainfall seasonality increased, especially in Southeast China, which can be attributed to changes in magnitude (annual rainfall), timing, or duration of the wet season. Global climate events significantly affected rainfall seasonality indicators in Southeast China during negative and positive phases. The sea surface temperature (SST) or sea level pressure (SLP), and wind anomalies during the negative and positive phases might explain the spatial differences in the influences of global climate events on rainfall seasonality across China. These results may prove valuable for sustainable water resource management and agricultural production in China. [ABSTRACT FROM AUTHOR]

Atmospheric water vapor has not only been reported to increase in the real world, but is also expected to increase in climate models. Correctly simulating water vapor and its relationship with temperature is thus vital for climate models. In this study, atmospheric precipitable water (PW) from phase 5 of the Coupled Model Intercomparison Project (CMIP5) is evaluated over China during 1970–2005, and then the future changes of PW and their correlation with near-surface air temperature (Ts) are further investigated. The results show that the PW biases in the model simulations are within ~ 20% for most of eastern China, but have larger root-mean-square error over southeastern China. Most models are able to simulate the observed PW upward trends since 1970, but with large inter-model spread. CanESM2, GFDL-CM3, HadGEM2-ES and MIROC5 are relatively better at reproducing the observed long-term variations and trends for the whole of China and its subregions. An empirical orthogonal function (EOF) analysis shows that the model simulations reproduce the first observed leading modes well, but barely capture the temporal variation revealed by the second observed EOF. The model simulations project ubiquitous increases in PW in the twenty-first century, resulting from an increase in the mean and a flattening of the probability distribution functions of the PW anomalies. In particular, the increases in PW under the most severe future emissions scenario (RCP8.5) are nearly twice as much as those under the low–mid emissions scenario (RCP4.5) for most of China by the late twenty-first century. The model simulations suggest that the changes in PW are largely consistent with the changes in Ts during 1970–2005, with a dPW/dTs slope of ~ 4.6–6.0% K−1, which roughly agrees with the observed results but is slightly lower than the 7% K−1 implied by the Clausius–Clapeyron equation with a constant relative humidity. In the twenty-first century, the dPW/dTs is projected to be about 5.5–7.0% K−1 under the RCP4.5 scenario, but may reach ~ 7.4% K−1 or higher under the RCP8.5 scenario. [ABSTRACT FROM AUTHOR]

In this study, we use four statistical downscaling methods to statistically downscale seven Coupled Model Intercomparison Project (CMIP5) Global Climate Models (GCMs) and project the changes in precipitation and temperature over China under RCP4.5 and RCP8.5 emission scenarios. The four statistical downscaling methods are bias-correction and spatial downscaling (BCSD), bias-correction and climate imprint (BCCI), bias correction constructed analogues with quantile mapping reordering (BCCAQ), and cumulative distribution function transform (CDF-t). Though large inter-model variability exists in the distribution and magnitude of changes in projected precipitation, particularly for wet spell length (CWD), all downscaling methods generally project a consistent enhancement of precipitation in both summer and winter over most parts of China. For the arid and semiarid Northwest China, the shortened dry spell length (CDD) is accompanied by the pronouncedly intensified very wet days (R95p), as well as the increase in maximum 5-day precipitation amount (Rx5day). In contrast, southeastern regions may experience more consecutive dry days and more severe wet precipitation extremes. The projected changes from different downscaling techniques are fairly similar for temperature, apart from the diurnal temperature range for BCSD. Warming is projected across the whole domain with larger magnitude over the north and in winter under RCP8.5. More summer days and fewer frost days would appear in the future. The bias correction components of downscaling methods cause a higher degree of agreement among models, and the downscaled results generally retain the main climate change signal of the driving models. [ABSTRACT FROM AUTHOR]

The near-surface air temperature over China is simulated from 1950 to 2099 using the PRECIS model from the Met Office Hadley Centre at a 25-km resolution. In order to reflect the different parametric and structural uncertainties in future temperature projections, the PRECIS model is driven by five lateral boundary conditions, which include a four-member HadCM3-based perturbed-physics ensemble (i.e., HadCM3Q0, Q1, Q7 and Q13) and an ECHAM5 model. For the present climate, PRECIS reasonably reproduces the spatial patterns of near-surface air temperatures over most regions in China, except for some underestimation in the west. The annual cycles of mean temperature are well captured but its magnitude is slightly underestimated throughout the year. Future temperature projections are further analyzed for three successive 30-year periods throughout the twenty-first century. Despite more uncertainties with time, the ensemble results demonstrate that the temperature over China is likely to continue to increase throughout the twenty-first century, with different spatial-time variation. There is an apparent increasing pattern along with the latitude for seasonal temperature. Through comparison with the driving GCMs, PRECIS ensemble shows smaller biases in most regions of China, except for in the west plateau. The cause is that RCMs could inherit some errors from the driving GCMs in addition to their own errors. These errors could be magnified unintentionally in downscaling over high elevations and have been propagated into future climate projections. However, there is no apparent relationship between projected changes and model biases (i.e., larger bias does not necessarily lead to bigger changes in temperature). These results could be directly used to analyze the impacts caused by climate warming on agriculture, energy and other related sectors in China. [ABSTRACT FROM AUTHOR]

Observational analysis indicates significant changes in some temperature extremes over China across the mid-1990s. The decadal changes in hot extremes are characterized as a rise in annual hottest day and night temperature (TXx and TNx) and an increase in frequencies of summer days (SU) and tropical night (TR). The decadal changes in cold extremes are distinguished by a rise in annual coldest day and night temperature (TXn and TNn) and a decrease in frequencies of ice days (ID) and frost days (FD). These decadal changes manifest not only over China as a whole, but also over individual climate sub-regions. An atmosphere-ocean-mixed-layer coupled model forced by changes in greenhouse gases (GHG) concentrations and anthropogenic aerosol (AA) emissions realistically reproduces the general spatial patterns and magnitudes of observed changes in both hot and cold extremes across the mid-1990s, suggesting a pronounced role of anthropogenic changes in these observed decadal changes. Separately, changes in GHG forcing lead to rise in TXx, TNx, TXn and TNn, increase in frequencies of SU and TR and decrease in frequencies of ID and FD over China through increased Greenhouse Effect with positive clear sky longwave radiation and play a dominant role in simulated changes of both hot and cold extremes over China. The AA forcing changes tend to cool Southern China and warm Northern China during summer via aerosol-radiation interaction and AA-induced atmosphere-cloud feedback and therefore lead to some weak decrease in hot extremes over Southeastern China and increase over Northern China. Meanwhile, AA changes lead to warming over China during winter through cloud feedbacks related to aerosol induced cooling over tropical Indian Ocean and western tropical Pacific, and also induce changes in cold extremes the same sign as those induced by GHG, but with weak magnitude. [ABSTRACT FROM AUTHOR]

This study investigates observed and modeled contributions of global sea surface temperature (SST) to China winter climate trends in 1960-2014, including increased precipitation, warming through about 1997, and cooling since then. Observations and Atmospheric Model Intercomparison Project (AMIP) simulations with prescribed historical SST and sea ice show that tropical Indian Ocean (TIO) warming and increasing rainfall causes diabatic heating that generates a tropospheric wave train with anticyclonic 500-hPa height anomaly centers in the TIO or equatorial western Pacific (TIWP) and northeastern Eurasia (EA) and a cyclonic anomaly over China, referred to as the TIWP-EA wave train. The cyclonic anomaly causes Indochina moisture convergence and southwesterly moist flow that enhances South China precipitation, while the northern anticyclone enhances cold surges, sometimes causing severe ice storms. AMIP simulations show a 1960-1997 China cooling trend by simulating increasing instead of decreasing Arctic 500-hPa heights that move the northern anticyclone into Siberia, but enlarge the cyclonic anomaly so it still simulates realistic China precipitation trend patterns. A separate idealized TIO SST warming simulation simulates the TIWP-EA feature more realistically with correct precipitation patterns and supports the TIWP-EA teleconnection as the primary mechanism for long-term increasing precipitation in South China since 1960. Coupled Model Intercomparison Project (CMIP) experiments simulate a reduced TIO SST warming trend and weak precipitation trends, so the TIWP-EA feature is absent and strong drying is simulated in South China for 1960-1997. These simulations highlight the need for accurately modeled SST to correctly attribute regional climate trends. [ABSTRACT FROM AUTHOR]

The impact of global warming on the characteristics of mean and extreme precipitations over China is investigated by using the Providing REgional Climate Impacts for Studies (PRECIS) model. The PRECIS model was driven by the Hadley Centre Global Environment Model version 2 with Earth System components and coupling (HadGEM2-ES). The results of both models are analyzed in terms of mean precipitation and indices of precipitation extremes (R95p, R99p, SDII, WDF, and CWD) over China at the resolution of 25 km under the Representative Concentration Pathways 4.5 and 8.5 (RCP4.5 and RCP8.5) scenarios for the baseline period (1976-2005) and two future periods (2036-2065 and 2070-2099). With improved resolution, the PRECIS model is able to better represent the fine-scale physical process than HadGEM2-ES. It can provide reliable spatial patterns of precipitation and its related extremes with high correlations to observations. Moreover, there is a notable improvement in temporal patterns simulation through the PRECIS model. The PRECIS model better reproduces the regional annual cycle and frequencies of daily precipitation intensity than its driving GCM. Under RCP4.5 and RCP8.5, both the HadGEM2-ES and the precis project increasing annual precipitation over the entire country for two future periods. Precipitation increase in winter is greater than the increase in summer. The results suggest that increased radiative forcing from RCP4.5 to RCP8.5 would further intensify the magnitude of projected precipitation changes by both PRECIS and HadGEM2-ES. For example, some parts of south China with decreased precipitation under RCP4.5 would expect even less precipitation under RCP8.5; regions (northwest, northcentral and northeast China) with increased precipitation under RCP4.5 would expect more precipitation under RCP8.5. Apart from the projected increase in annual total precipitation, the results also suggest that there will be an increase in the days with precipitation higher than 15 mm and a decrease in the days with precipitation less than 5 mm. Under both RCPs, there would be an increasing trend in the magnitude of changes in precipitation extremes indices (R95p, R99p, and SDII) over China, while an opposite trend is projected for CWD and no apparent trend is projected for WDF from 2036-2065 to 2070-2099. Increased extreme precipitation amounts accompanied with decreased frequencies of extreme precipitation suggest that the future daily extreme precipitation intensity is likely to become large in northeast China and south China. [ABSTRACT FROM AUTHOR]

In this study, likely changes in extreme temperatures (including 16 indices) over China in response to global warming throughout the twenty-first century are investigated through the PRECIS regional climate modeling system. The PRECIS experiment is conducted at a spatial resolution of 25 km and is driven by a perturbed-physics ensemble to reflect spatial variations and model uncertainties. Simulations of present climate (1961–1990) are compared with observations to validate the model performance in reproducing historical climate over China. Results indicate that the PRECIS demonstrates reasonable skills in reproducing the spatial patterns of observed extreme temperatures over the most regions of China, especially in the east. Nevertheless, the PRECIS shows a relatively poor performance in simulating the spatial patterns of extreme temperatures in the western mountainous regions, where its driving GCM exhibits more uncertainties due to lack of insufficient observations and results in more errors in climate downscaling. Future spatio-temporal changes of extreme temperature indices are then analyzed for three successive periods (i.e., 2020s, 2050s and 2080s). The projected changes in extreme temperatures by PRECIS are well consistent with the results of the major global climate models in both spatial and temporal patterns. Furthermore, the PRECIS demonstrates a distinct superiority in providing more detailed spatial information of extreme indices. In general, all extreme indices show similar changes in spatial pattern: large changes are projected in the north while small changes are projected in the south. In contrast, the temporal patterns for all indices vary differently over future periods: the warm indices, such as SU, TR, WSDI, TX90p, TN90p and GSL are likely to increase, while the cold indices, such as ID, FD, CSDI, TX10p and TN10p, are likely to decrease with time in response to global warming. Nevertheless, the magnitudes of changes in all indices tend to decrease gradually with time, indicating the projected warming will begin to slow down in the late of this century. In addition, the projected range of changes for all indices would become larger with time, suggesting more uncertainties would be involved in long-term climate projections. [ABSTRACT FROM AUTHOR]

Heat waves (HWs) can have disastrous impacts on human activities and natural systems, and are one of the current foci of scientific research, particularly in the context of global warming. However, there is no standard definition of a HW, which makes assessment of temporal trends a challenge. In this study, based on daily mean, maximum and minimum temperature, and relative humidity datasets from China Meteorological Administration, the patterns, trends and variations of HW in China during 1961-2014 are investigated. Sixteen previously published HW indices (HIs) are calculated, which are divided into two types using relative and absolute threshold temperatures, respectively. During 1961-2014, both relative and absolute threshold HIs show the highest number of HW in Jianghua and South China, geographically consistent with the climate characteristics of China. The majority of HIs shows negative/positive trends of HW days before/after 1990 over the whole of China, but especially in Jianghua and South China, which reflects rapid warming since 1990. There are significant correlations among different HIs in the same type (both absolute and relative), but correlations are weak between relative and absolute threshold HIs. Because relative and absolute HIs show contrasting trends, the choice of HI is therefore critical for future analysis [ABSTRACT FROM AUTHOR]

In this study, the intensity, area, and duration of droughts in China are analyzed using the Standardized Precipitation Index (SPI). The SPI was calculated on monthly data for 530 meteorological stations in China for the period 1960-2013. The time series were analyzed for ten major hydrological regions of China, respectively. The relationships between the intensity and the area of droughts for a specific duration were analyzed by the intensity-area-duration method. The results show that areas with a significant trend in dryness can be found in a band reaching from the southwest to the northeast of China, while areas with significant trends in wetness are especially detected in the northern river basins in recent decades. In addition, for recent years (2000-2013), most of the ten major hydrological regions show opposite trends in the SPI when compared to the whole study period (1960-2013) except for the central and southwestern parts of China. This dryness/wetness trends are related to the intensity and duration of drought events, which have been stronger and lasted longer in the detected dryness band except for some northern river basins. A regional shift of drought centers is found from the northwest to the southeast within Central China. Moreover, a decreasing trend in drought area is observed, which might be related to the regional changes in precipitation pattern associated with the atmosphere-ocean interaction. Changes in the SST of the Tropical Pacific and the Tropical Indian Ocean may have resulted in frequent severe drought events of small areal extent in the central and southwestern parts of China. For the study period, the most severe droughts that covered large areas mainly occurred in the north and west of China during the mid-to-late twentieth century. However, in the early twenty-first century, the most severe droughts were located in the southwest of China covering areas less than 0.7 million km. Conclusively, drought areas show a decreasing tendency, while more intense droughts of longer duration have been experienced, especially in the south of China, in the last decades. [ABSTRACT FROM AUTHOR]

Urbanization plays an important role in human-induced climate change at the regional scale through altered land-atmosphere interactions over urban areas. In this study, the impacts of future urbanization in China on climate are investigated. The Weather Research and Forecasting model is used to downscale future projections using Representative Concentration Pathways (RCP) 4.5 simulations from the Community Earth System Model. Results for 2050 show decreased latent and increased sensible heat fluxes over the urban area, therefore leading to higher surface temperatures and less humidity. Future climate projections reveal that urbanization produces strong warming effects, up to 1.9 °C at regional and local/urban scales, which is comparable to the magnitude of greenhouse gas forcing under the RCP 4.5 scenario. Greater urban warming effects are projected during night and summer, which can be attributed to the high heat capacity of built-up areas. The impacts of urbanization on precipitation show varying effects primarily in summer-both increases and decreases depending on spatial scale-related to both local moisture deficits and large-scale circulation changes. Urbanization could strengthen the East Asian summer monsoon in southern China in summer, and slightly weaken it in eastern China in winter. Due to these significant impacts, we suggest that urbanization should be included in model projections to provide a more realistic and complete depiction of future climate. [ABSTRACT FROM AUTHOR]

The spatial and temporal pattern of sub-daily temperature change in mainland China was analysed for the period from 1973 to 2011 using a 3-hourly dataset based on 408 stations. The increase in surface air temperature was more significant by night between 1973 and 1992, with the fastest upward trend around local midnight being about 0.27 °C/decade, while it was more significant by day between 1992 and 2011, with the fastest upward trend being about 0.46 °C/decade in mid-late morning. The season with rapid temperature increase also shifted from winter in 1973-1992 (the largest increase happened near midnight in December, 0.75 °C/decade) to spring in 1992-2011 (the largest increase happened at in the early afternoon in March, 0.82 °C/decade). The change in the spatial distributions of the sub-daily temperature trends shows that Northeast China warmed more significantly in 1973-1992 than elsewhere, but it cooled in 1992-2011, when Southwest China was the new focus of temperature increase whereas it had previously been cooling. A preliminary analysis of the possible causes implies that changes in solar radiation, cloud cover, aerosols and the observational environments near the stations might have contributed to these observed temperature changes. [ABSTRACT FROM AUTHOR]

Climate changes over China from the present (1990-1999) to future (2046-2055) under the A1FI (fossil fuel intensive) and A1B (balanced) emission scenarios are projected using the Regional Climate Model version 3 (RegCM3) nests with the National Center for Atmospheric Research (NCAR) Community Climate System Model (CCSM). For the present climate, RegCM3 downscaling corrects several major deficiencies in the driving CCSM, especially the wet and cold biases over the Sichuan Basin. As compared with CCSM, RegCM3 produces systematic higher spatial pattern correlation coefficients with observations for precipitation and surface air temperature except during winter. The projected future precipitation changes differ largely between CCSM and RegCM3, with strong regional and seasonal dependence. The RegCM3 downscaling produces larger regional precipitation trends (both decreases and increases) than the driving CCSM. Contrast to substantial trend differences projected by CCSM, RegCM3 produces similar precipitation spatial patterns under different scenarios except autumn. Surface air temperature is projected to consistently increase by both CCSM and RegCM3, with greater warming under A1FI than A1B. The result demonstrates that different scenarios can induce large uncertainties even with the same RCM-GCM nesting system. Largest temperature increases are projected in the Tibetan Plateau during winter and high-latitude areas in the northern China during summer under both scenarios. This indicates that high elevation and northern regions are more vulnerable to climate change. Notable discrepancies for precipitation and surface air temperature simulated by RegCM3 with the driving conditions of CCSM versus the model for interdisciplinary research on climate under the same A1B scenario further complicated the uncertainty issue. The geographic distributions for precipitation difference among various simulations are very similar between the present and future climate with very high spatial pattern correlation coefficients. The result suggests that the model present climate biases are systematically propagate into the future climate projections. The impacts of the model present biases on projected future trends are, however, highly nonlinear and regional specific, and thus cannot be simply removed by a linear method. A model with more realistic present climate simulations is anticipated to yield future climate projections with higher credibility. [ABSTRACT FROM AUTHOR]

The effects of the northeastern Eurasian snow cover on the frequency of spring dust storms in northwestern China have been examined for the period 1979-2007. Averaged over all 43 stations in northwestern China, a statistically significant relationship has been found between dust-storm frequency (DSF) and Eurasian snow-water equivalent (SWE) during spring: mean DSF of 7.4 and 3.3 days for years of high- and low SWE, respectively. Further analyses reveal that positive SWE anomalies enhance the meridional gradients of the lower tropospheric temperatures and geopotential heights, thereby strengthening westerly jets and zonal wind shear over northwestern China and western Inner Mongolia of China, the regions of major dust sources. The anomalous atmospheric circulation corresponding to the Eurasian SWE anomalies either reinforces or weakens atmospheric baroclinicity and cyclogenesis, according to the sign of the anomaly, to affect the spring DSF. This study suggests that Eurasian SWE anomalies can be an influential factor of spring DSF in northwestern China and western Inner Mongolia of China. [ABSTRACT FROM AUTHOR]

Based on daily maximum and minimum surface air temperature and precipitation records at 303 meteorological stations in China, the spatial and temporal distributions of indices of climate extremes are analyzed during 1961-2003. Twelve indices of extreme temperature and six of extreme precipitation are studied. Temperature extremes have high correlations with the annual mean temperature, which shows a significant warming of 0.27°C/decade, indicating that changes in temperature extremes reflect the consistent warming. Stations in northeastern, northern, northwestern China have larger trend magnitudes, which are accordance with the more rapid mean warming in these regions. Countrywide, the mean trends for cold days and cold nights have decreased by −0.47 and −2.06 days/decade respectively, and warm days and warm nights have increased by 0.62 and 1.75 days/decade, respectively. Over the same period, the number of frost days shows a statistically significant decreasing trend of −3.37 days/decade. The length of the growing season and the number of summer days exhibit significant increasing trends at rates of 3.04 and 1.18 days/decade, respectively. The diurnal temperature range has decreased by −0.18°C/decade. Both the annual extreme lowest and highest temperatures exhibit significant warming trends, the former warming faster than the latter. For precipitation indices, regional annual total precipitation shows an increasing trend and most other precipitation indices are strongly correlated with annual total precipitation. Average wet day precipitation, maximum 1-day and 5-day precipitation, and heavy precipitation days show increasing trends, but only the last is statistically significant. A decreasing trend is found for consecutive dry days. For all precipitation indices, stations in the Yangtze River basin, southeastern and northwestern China have the largest positive trend magnitudes, while stations in the Yellow River basin and in northern China have the largest negative magnitudes. This is inconsistent with changes of water vapor flux calculated from NCEP/NCAR reanalysis. Large scale atmospheric circulation changes derived from NCEP/NCAR reanalysis grids show that a strengthening anticyclonic circulation, increasing geopotential height and rapid warming over the Eurasian continent have contributed to the changes in climate extremes in China. [ABSTRACT FROM AUTHOR]