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The increased growth of vegetation has the potential to slow global climate warming. Therefore, analyzing and predicting the response assessment of Chinese vegetation to climate change is of great significance to studies of global warming. In this paper, we examine the spatiotemporal dynamics of vegetation leaf area index (LAI) values in China from 1981 to 2017 and their correlations with meteorological (hydrothermal) factors based on trend analysis and correlation analysis. We further construct an LAI prediction model based on hydrothermal conditions. The climate data obtained under different scenarios in the CMIP5 and CMIP6 climate models were used to predict the dynamic change trend of vegetation LAI from 2021 to 2100. The results show that most areas of China (72.82%) showed an improving trend in vegetation LAI from 1981 to 2017, during which the annual average LAI value increased at a rate of 0.0029 year−1. Vegetation LAI in China was significantly correlated with climatic factors (temperature, precipitation, and evapotranspiration), and the LAI prediction model constructed based on hydrothermal conditions had a high accuracy (Pearson's Cor value is 0.9729). From 2021 to 2100, approximately 2/3 of China's vegetation LAI area showed an improvement trend, and the impact of climate change on vegetation LAI predictions under the high emission scenario was greater than that under the low emission scenario. This research can provide a basis for studies on the climatic drivers of vegetation change and the global vegetation dynamic model. [ABSTRACT FROM AUTHOR]

Global climate change is expected to have a major impact on the hydrological cycle. Understanding potential changes in future extreme precipitation is important to the planning of industrial and agricultural water use, flood control, and ecological environment protection. In this paper, we study the statistical distribution of extreme precipitation based on historical observation and various global climate models (GCMs), and predict the expected change and the associated uncertainty. The empirical frequency, generalized extreme value (GEV) distribution, and L-moment estimator algorithms are used to establish the statistical distribution relationships and the multi-model ensemble predictions are established by the Bayesian model averaging (BMA) method. This ensemble forecast takes advantage of multi-model synthesis, which is an effective measure to reduce the uncertainty of model selection in extreme precipitation forecasting. We have analyzed the relationships among extreme precipitation, return period, and precipitation durations for 6 representative cities in China. More significantly, the approach allows for establishing the uncertainty of extreme precipitation predictions. The empirical frequency from the historical data is all within the 90% confidence interval of the BMA ensemble. For the future predictions, the extreme precipitation intensities of various durations tend to become larger compared to the historic results. The extreme precipitation under the RCP8.5 scenario is greater than that under the RCP2.6 scenario. The developed approach not only effectively gives the extreme precipitation predictions, but also can be used to any other extreme hydrological events in future climate. [ABSTRACT FROM AUTHOR]

The wet bulb temperature (Tw) has gained considerable attention as a crucial indicator of heat-related health risks. Here we report south-to-north spatially heterogeneous trends of Tw in China over 1979-2018. We find that actual water vapor pressure (Ea) changes play a dominant role in determining the different trend of Tw in southern and northern China, which is attributed to the faster warming of high-latitude regions of East Asia as a response to climate change. This warming effect regulates large-scale atmospheric features and leads to extended impacts of the South Asia high (SAH) and the western Pacific subtropical high (WPSH) over southern China and to suppressed moisture transport. Attribution analysis using climate model simulations confirms these findings. We further find that the entire eastern China, that accommodates 94% of the country's population, is likely to experience widespread and uniform elevated thermal stress the end of this century. Our findings highlight the necessity for development of adaptation measures in eastern China to avoid adverse impacts of heat stress, suggesting similar implications for other regions as well. Attributing spatially heterogeneous heat stress trends to water vapor pressure changes driven by climate change-induced rapid warming in high-latitudes of East Asia, the authors predict widespread and uniform future heat stress in eastern China. [ABSTRACT FROM AUTHOR]

Copyright of Advances in Atmospheric Sciences is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

We evaluated the potential impact of future climate change on spring maize and single-crop rice in northeastern China (NEC) by employing climate and crop models. Based on historical data, diurnal temperature change exhibited a distinct negative relationship with maize yield, whereas minimum temperature correlated positively to rice yield. Corresponding to the evaluated climate change derived from coupled climate models included in the Coupled Model Intercomparison Project Phase 5 (CMIP5) under the Representative Concentration Pathway 4.5 scenario (RCP4.5), the projected maize yield changes for three future periods [2010-39 (period 1), 2040-69 (period 2), and 2070-99 (period 3)] relative to the mean yield in the baseline period (1976-2005) were 2.92%, 3.11% and 2.63%, respectively. By contrast, the evaluated rice yields showed slightly larger increases of 7.19%, 12.39%, and 14.83%, respectively. The uncertainties in the crop response are discussed by considering the uncertainties obtained from both the climate and the crop models. The range of impact of the uncertainty became markedly wider when integrating these two sources of uncertainty. The probabilistic assessments of the evaluated change showed maize yield to be relatively stable from period 1 to period 3, while the rice yield showed an increasing trend over time. The results presented in this paper suggest a tendency of the yields of maize and rice in NEC to increase (but with great uncertainty) against the background of global warming, which may offer some valuable guidance to government policymakers. [ABSTRACT FROM AUTHOR]

This paper provides a review of paleoclimate modeling activities in China. Rather than attempt to cover all topics, we have chosen a few climatic intervals and events judged to be particularly informative to the international community. In historical climate simulations, changes in solar radiation and volcanic activity explain most parts of reconstructions over the last millennium prior to the industrial era, while atmospheric greenhouse gas concentrations play the most important role in the 20th century warming over China. There is a considerable model-data mismatch in the annual and boreal winter temperature change over China during the mid-Holocene [6000 years before present (ka BP)], while coupled models with an interactive ocean generally perform better than atmospheric models. For the Last Glacial Maximum (21 ka BP), climate models successfully reproduce the surface cooling trend over China but fail to reproduce its magnitude, with a better performance for coupled models. At that time, reconstructed vegetation and western Pacific sea surface temperatures could have significantly affected the East Asian climate, and environmental conditions on the Qinghai-Tibetan Plateau were most likely very different to the present day. During the late Marine Isotope Stage 3 (30-40 ka BP), orbital forcing and Northern Hemisphere glaciation, as well as vegetation change in China, were likely responsible for East Asian climate change. On the tectonic scale, the Qinghai-Tibetan Plateau uplift, the Tethys Sea retreat, and the South China Sea expansion played important roles in the formation of the East Asian monsoon-dominant environment pattern during the late Cenozoic. [ABSTRACT FROM AUTHOR]

The source region of the Yangtze River (SRYR) is located in the hinterland of the Tibetan Plateau (TP). Due to the harsh climate environment, there are few meteorological stations in its territory, and the measured meteorological data are also less. To overcome the impact of lack of measured meteorological data, the China Meteorological Forcing Dataset (CMFD) was used to couple with the meteorological data, to make the meteorological data more representative of the average climate state of the SRYR. Furthermore, we used the Soil and Water Assessment Tool (SWAT) to verify interpolation effect of meteorological data. Then the six global climate models (GCMs) were integrated through deep learning (DL) algorithm to make it closer to the changes in weather data after correction. The future water resource changes of SRYR were obtained by coupling the SWAT model with the integrated meteorological data. The results show that the CMFD dataset has a high precision in the SRYR, and that the average relative error (RE), coefficient of determination (R2), Nash–Sutcliffe efficiency (Ens) with the measured temperature and precipitation are 10.66%, 0.99, and 0.93, respectively. The CMFD dataset can be used for meteorological data integration. After the meteorological data integration, the Ens between simulated runoff and observed runoff increased from 0.64 to 0.70, and the RE reduced from 13.4 to 10.3%. Under the future climate scenario, the runoff in the SRYR shows a decreasing trend, the average annual runoff decreased by 11.89%, and the distribution of runoff during the year changes is even more dramatic. This shows that the SRYR faces the risk of water resources reduction, which will bring challenges to water resources management in the SRYR. This study provides a new idea for meteorological data correction. [ABSTRACT FROM AUTHOR]

Global warming has altered the thermodynamic and dynamic environments of the climate system, thus affecting the energy budget and water cycle process of the land-atmosphere system. Under changes in key hydrological elements such as precipitation, runoff, and terrestrial water storage, future drought variation remains a complex question. Existing studies have utilized terrestrial water storage anomaly (TWSA) in drought monitoring and assessment, but they usually focused on either drought duration or intensity, overlooking the multi-faced attributes of droughts as well as their socioeconomic impacts under a non-stationary condition. In this study, we first identify dry/wet conditions over China using GRACE/GRACE-FO satellite observations, and then evaluate the feedback effects of humidity and energy factors (e.g., sensible heat flux, latent heat flux, atmospheric relative humidity, and convective available potential energy) to drought events. Future changes in TWSA and dry/wet conditions are projected by eight Coupled Model Inter-comparison Project Phase 6 (CMIP6) global climate models (GCMs) under three shared socioeconomic pathways (SSPs), with their biases corrected by a trend-preserving quantile mapping method. The time-varying Copula function of drought duration and intensity is constructed by a moving windows method, and future bivariate drought risks are quantified with the most likely realization method. The population and GDP affected by increasing drought risks are finally quantified based on the SSPs data. It is found that the land-atmosphere coupling effects closely interact with drought evolution, and the uneven distribution of water resources is projected to be further aggravated, with most areas of China will be threatened by continuous drying tendency. By the end of the century, the duration of moderate, severe and exceptional droughts in some regions of China will double, and the drought intensity will increase by over 80%. For the 50-year bivariate droughts during the historical period, their occurrence may increase by 5–10 times in several regions, and might affect about 35–55% of China's population and GDP at the end of 21st century. [ABSTRACT FROM AUTHOR]

Normandy is the world's leading producer of flax fiber (Linum usitatissimu L.), which is mainly exported to China for textile manufacturing. Flax is a plant that is cultivated in spring and that grows in an oceanic climate with regular watering and limited thermal excesses. This article aims at projecting the impact of climate change on the phenology of this plant when subjected to climatic hazards that may occur during its development. These projections use two regional climate models (ALADIN-Climate and WRF) based on the two scenarios generated by the latest IPPC report—intergovernmental panel on climate change—(RCP 4.5 and RCP 8.5). The rise in temperatures would result in a time-cycle reduction. Consequently, flax would not be exposed to the early summer water shortage. However, thermal conditions could be unfavorable, especially due to the increased frequency of heat days. Flax is also exposed to the risk of lodging during heavy rainfall episodes; however, the results are somehow contrasted between the two climate models used. This research demonstrates the interest of multidisciplinary impact studies so as to anticipate the consequences of climate change on agricultural crops. [ABSTRACT FROM AUTHOR]

Copyright of Advances in Atmospheric Sciences is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

To connect a wide range of research communities including climate change mitigation and adaptation activities, the Intergovernmental Panel on Climate Change (IPCC) 6th assessment report (AR6) employs the Shared Socioeconomic Pathway (SSP) scenarios. The CORDEX East Asia calls for a dynamical downscaling of climate change projections under the new SSP scenarios. In this study, the state-of-the-art regional climate model RegCM4 with a horizontal resolution of 25 km was used to dynamically downscale future climate changes, which were derived from the global climate model FGOALS-g3, under multiple SSP scenarios over the CORDEX East Asia Phase II domain. Compared to the driving global model FGOALS-g3, the downscaling exhibited added value in the simulation of present-day mean and extreme rainfall over China in terms of both spatial pattern correlation and biases. The largest improvements were found over the Pearl River Basin and the Yangtze River Basin. For the period of 2081–2100 under the SSP2-4.5 scenario, the areas in China with increases in the projected mean and extreme rainfall generally overlapped with the areas with substantial climatological mean and extreme rainfall in both RegCM4 and FGOALS-g3, which highlights the importance of simulated climatology in projecting future rainfall changes. The moisture budget analyses indicated that the projected increases in summer mean rainfall were mainly attributed to thermodynamic processes associated with the increased moisture. The mean and extreme rainfall was most sensitive to the increased emission scenarios in the Northwest Interior River Basin and least sensitive in southern China. From SSP1-2.6 to SSP5-8.5, larger fractions of land area and population would be affected by greater increased and more intense rainfall. If the emissions were reduced from SSP5-8.5 to SSP1-2.6, over 80% of the impacts would be avoided over most regions in China. [ABSTRACT FROM AUTHOR]

Both climate and land-use changes can influence drought in different ways. Thus, to predict future drought conditions, hydrological simulations, as an ideal means, can be used to account for both projected climate change and projected land-use change. In this study, projected climate and land-use changes were integrated with the Soil and Water Assessment Tool (SWAT) model to estimate the combined impact of climate and land-use projections on hydrological droughts in the Lutheran River basin. We showed that the measured runoff and the remote sensing inversion of soil water content were simultaneously used to validate the model to ensure the reliability of the model parameters. Following calibration and validation, the SWAT model was forced with downscaled precipitation and temperature outputs from a suite of nine global climate models (GCMs) based on CMIP5, corresponding to three different representative concentration pathways (RCP2.6, RCP4.5 and RCP8.5) for three distinct time periods: 2011–2040, 2041–2070 and 2071–2100, referred to as early century, mid-century and late-century, respectively, and the land use predicted by the CA–Markov model in the same future periods. Hydrological droughts were quantified using the standardized runoff index (SRI). Compared to the baseline scenario (1961–1990), mild drought occurred more frequently during the next three periods (except for the 2080s under the RCP2.6 emissions scenario). Under the RCP8.5 emissions scenario, the probability of severe drought or above occurring in the 2080s increased, the duration was prolonged, and the severity increased. Under the RCP2.6 scenario, the upper central region of the Luanhe River in the 2020s and upper reaches of the Luanhe River in the 2080s were more likely to experience extreme drought events. Under the RCP8.5 scenario, the middle and lower Luanhe River in the 2080s was more likely to experience these conditions. [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]

To better understand the variation in mountainous discharge (MD) in the future, a basin case study was conducted in the upstream Taolai River Basin (UTRB) in arid northwestern China. The Blaney-Criddle (B-C) equation, Budyko framework, and water balance method were coupled for MD calculations. The outputs of 10 global climate models (GCMs) are synthesized to confirm the future changes in air temperature and precipitation under 3 selected Representative Concentration Pathway (RCP) scenarios. The climate elasticity (CE) method was used to determine the variation in MD, and the influence of climate factors on that was quantitatively analyzed. The results reveal that the coupling framework of the three methods is suitable for MD determination in the UTRB. The weight-based synthesis of the 10 GCM outputs shows overall increases in temperature (T) and precipitation (P) under the 3 scenarios during most of the time until 2099. The above climate change leads to an increase in MD. According to CE analysis, the positive effectiveness of precipitation is greater than the negative effectiveness of temperature on MD variation, and the increase in precipitation would induce more MD in the UTRB. Uncertainty analysis reveals that GCM outputs dominate in predicting precipitation, while the RCP scenarios influence temperature more. Overall, under the background of climate change, the risk of extreme floods during wet years might increase, and a water deficit will still occur during normal and dry years. The study provides a case example for better understanding MD responses to climate change in the upper reaches of inland river basins. Findings are helpful for reasonable water resource development and utilization in the middle and lower reaches of these basins in the future. As in the Taolai River Basin, considering the future water demand across the whole basin, the development of water-saving technologies and reasonable industrial structures is crucial for a sustainable future. [ABSTRACT FROM AUTHOR]

The Yalong River basin (YRB), originating from the Tibetan Plateau, is critical for China's western development and electricity transmission. Climate change would affect the streamflow and potentially impact the hydropower in the YRB. In this study, the Automated Statistical Downscaling technique and the hydrological model SWAT were used to reproduce the observed precipitation, temperature and streamflow and predict them in the future. More importantly, the Bayesian Model Averaging (BMA) method was used to appraise the performance of four different Global Climate Models (GCMs) in simulating historical streamflow (1984–1997), and to quantify the uncertainties in future projections (2021–2100) under three Representative Concentration Pathways (RCPs) in the YRB. It was found that (i) the SWAT hydrological model has good applicability in the YRB; (ii) the BMA method can capture the historical streamflow reasonably better than individual GCM projections, providing a scientific reference for the future water resources planning and utilization in the YRB. [ABSTRACT FROM AUTHOR]

Flood wave superposition (FWS) of upstream and tributary rivers, as a typical compound hydrological event, may lead to considerable downstream flood hazards. In spite of this, the quantitative identification of FWS classification so far remains elusive. In this study, we quantitatively examined the typical matching patterns of FWS based on flood peak magnitude and timing between the upstream and tributary discharge, to evaluate the flood severity for both present-day conditions and future climate projections. The future FWS projection was realized using hydrological modeling coupled with multiple outputs of global climate models (GCMs) under the Representative Concentration Pathway (RCP) 2.6 and 8.5 emission scenarios. A triple point of discharge stations, including upstream, downstream and tributary stations, located at a river confluence of the Poyang Lake Basin, China, was selected as the study area. The results revealed that the frequency of perfect temporal matching (0-day time lag) of projected peaks between upstream and tributary floods increased from 61% in the reference period to >68% and > 66% in the future under RCPs 2.6 and 8.5, respectively. Furthermore, both the future numbers and frequencies of the projected peaks between upstream and tributary floods with both perfect temporal and magnitude matching (the classification associated with the most damage in FWS) would substantially increase across all GCMs under RCPs 2.6 and 8.5. These findings indicate that future FWS is expected to experience increasing severity due to the changing climate under no matter RCP 2.6 or 8.5 emission scenarios. Overall, it is suggested that effective adaptation strategies be developed in order to stagger the timing of upstream and tributary floods in the future. [ABSTRACT FROM AUTHOR]

Despite the importance of the Yellow River to China, climate change for the middle reaches of the Yellow River Basin (YRB) has been investigated far less than for other regions. This work focuses on future changes in mean and extreme climate of the YRB for the near-term (2021–2040), mid-term (2041–2060), and far-term (2081–2100) future, and assesses these with respect to the reference period (1986–2005) using the latest REgional MOdel (REMO) simulations, driven by three global climate models (GCMs) and assuming historical and future [Representative Concentration Pathway (RCP) 2.6 and 8.5] forcing scenarios, over the CORDEX East Asia domain at 0.22° horizontal resolution. The results show that REMO reproduces the historical mean climate state and selected extreme climate indices reasonably well, although some cold and wet biases exist. Increases in mean temperature are strongest for the far-term in winter, with an average increase of 5.6 °C under RCP 8.5. As expected, the future temperatures of the warmest day (TXx) and coldest night (TNn) increase and the number of frost days (FD) declines considerably. Changes to mean temperature and FD depend on elevation, which could be explained by the snow-albedo feedback. A substantial increase in precipitation (34%) occurs in winter under RCP 8.5 for the far-term. Interannual variability in precipitation is projected to increase, indicating a future climate with more extreme events compared to that of today. Future daily precipitation intensity and maximum 5-day precipitation would increase and the number of consecutive dry days would decline under RCP 8.5. The results highlight that pronounced warming at high altitudes and more intense rainfall could cause increased future flood risk in the YRB, if a high GHG emission pathway is realized. [ABSTRACT FROM AUTHOR]

Copyright of Advances in Atmospheric Sciences is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Recent studies have reported a variety of health consequences of climate change. However, the vulnerability of individuals and cities to climate change remains to be evaluated. We project the excess cause-, age-, region-, and education-specific mortality attributable to future high temperatures in 161 Chinese districts/counties using 28 global climate models (GCMs) under two representative concentration pathways (RCPs). To assess the influence of population ageing on the projection of future heat-related mortality, we further project the age-specific effect estimates under five shared socioeconomic pathways (SSPs). Heat-related excess mortality is projected to increase from 1.9% (95% eCI: 0.2–3.3%) in the 2010s to 2.4% (0.4–4.1%) in the 2030 s and 5.5% (0.5–9.9%) in the 2090 s under RCP8.5, with corresponding relative changes of 0.5% (0.0–1.2%) and 3.6% (−0.5–7.5%). The projected slopes are steeper in southern, eastern, central and northern China. People with cardiorespiratory diseases, females, the elderly and those with low educational attainment could be more affected. Population ageing amplifies future heat-related excess deaths 2.3- to 5.8-fold under different SSPs, particularly for the northeast region. Our findings can help guide public health responses to ameliorate the risk of climate change. Global warming is expected to increase mortality due to heat stress in many regions. Here, the authors asses how mortality due to high temperatures changes in China changes for different demographic groups and show that heat-related excess mortality is increasing under climate change, a process that is strongly amplified by population ageing. [ABSTRACT FROM AUTHOR]

Climate change has substantial impacts on regional hydrology in the major river basins. To figure out such latent hydrological impacts of changing climate, more reliable hydrological simulations are imperative. In this study, we evaluated the impacts of climate change on hydrological regime in the Upper Yangtze River Basin based on four downscaled and bias-corrected Global Climate Model outputs from Coupled Model Intercomparison Project Phase 5 under four Representative Concentration Pathways (RCP2.6, RCP4.5, RCP6.0, and RCP8.5) driving three hydrological models. Two model evaluation approaches were applied: simple and comprehensive. The comprehensive approach was used to evaluate models in the historical period, optimizing objective function at four gauges, and hydrological models were weighted for impact assessment based on their performance. In such a way, projected streamflow time series are obtained under different emission scenarios. Results show that the annual average discharge is projected to increase by 4.1–10.5% under the RCP scenarios at the end of twenty-first century relative to the reference period (1970–1999). Moreover, the high flow is projected to increase and the low flow to decrease indicating a higher probability of flood and drought occurrence in the basin. The severity of floods and droughts may increase. In comparison with the simple one-site model evaluation approach, the comprehensive method reveals that the anticipated extreme flow events would be less severe, and annual mean discharge slightly lower. The projected results imply that application of the comprehensive model evaluation approach could narrow the simulated spreads of projections significantly, and might provide more credible results. [ABSTRACT FROM AUTHOR]

The impacts of climate change on future drought properties in various regions across China are accessed using multiple statistical approaches, based on 20 downscaled global climate models provided by NASA (NEX-GDDP) under Representative Concentration Pathways (RCP) 4.5 and RCP8.5 emission scenarios. Results show that temperature plays a crucial role on the variability of drought conditions in China by comparing the discrepancies between Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI). Unobvious variability of drought extent is projected for SPI, while the drought extent for SPEI is remarkable. Based on SPEI, a considerable aggravation in spatial extent and severity of future drought events are found in the majority of regions, particularly in northwest and northeast China, except for winter over northeast region. The drought extent increases more significantly after late 2070s under RCP8.5 scenario, and the differences of drought extent are not significant between RCP4.5 and RCP8.5 scenarios in the early and mid-twenty-first century. More than 85% of the regions show a decreasing trend for SPEI in spring, summer, and autumn, suggesting drought tendency in most of China, and drought frequency also increases significantly in north and northwest China except for winter. The dramatic aggravation of drought attribution is mainly projected to the increases in potential evapotranspiration (PET) in northwestern and northern regions of China, whereas in northwestern region, the exacerbating drought conditions are expected to the attribution of deficiencies of rainfall. At national scale, PET plays a more dominant role to the future severe and widespread droughts across China in the context of climate change. [ABSTRACT FROM AUTHOR]

Based on the outputs of 27 global climate models (GCMs) from the Coupled Model Inter-comparison Project Phase 5 (CMIP5), projected changes of extreme temperature events have been analyzed over nine river basins in China by the end of the twenty-first century relative to the reference period 1961-1990. The temporal and spatial changes and their projection uncertainty are studied using the extreme temperature indices defined by the Expert Team of Climate Change Detection and Indices (ETCCDI) under two Representative Concentration Pathways (RCPs). The model simulations predict a general increasing (decreasing) trend in warm (cold) extremes over China in the twenty-first century, with more pronounced warming trend under a higher emission scenario. The projected changes in cold and warm extremes exhibit a large difference in spatial patterns. The high-latitude and high-elevation regions of China (e.g., Continental and Southwest basins) are projected to respond more strongly to changes in cold extremes, while eastern and southern China (e.g., Yangtze River and Pearl River basins) tend to be more sensitive to the increases in warm extremes. In general, projected changes in cold indices based on minimum temperature tend to be more pronounced than in warm indices based on maximum temperature. Uncertainty analysis shows a large difference among the 27 GCMs under 2 RCP scenarios, and the uncertainty ranges tend to be larger under a higher emission scenario. Overall, the uncertainties in the emission scenarios are smaller than those from the climate models in the near future period. However, for the long-term climate projections (e.g., by the end of the twenty-first century), the projected difference under various emission scenarios tends to be larger than those by different climate models and hence can be the dominant contributor to the projection uncertainty of temperature indices. [ABSTRACT FROM AUTHOR]

The effect of spring Arctic Stratospheric Ozone (ASO) changes on spring precipitation in China is analyzed using observations, reanalysis data, and the Whole Atmosphere Community Climate Model version 4 (WACCM4). We find that February-March mean ASO changes have a significant impact on April-May mean precipitation over Loess Plateau and middle-lower reaches of the Yangtze River—two important grain-producing regions with large populations. Changes in the polar vortex link the ASO to precipitation in China. Stratospheric circulation anomalies caused by ASO changes can propagate to the North Pacific. An increase in ASO leads to enhanced westerlies in the high and low latitudes of the North Pacific but weakened westerly in the mid-latitudes of the North Pacific. The circulation anomalies over the North Pacific, forced by the increase of ASO, can extend westwards to East Asia, leading to an abnormal anticyclone in the East Asian upper and middle troposphere, and an abnormal cyclone in the lower troposphere. This enhances the warm and humid airstream from Western Pacific to Chinese mainland and strengthens upwelling over Loess Plateau and middle-lower reaches of the Yangtze River. These conditions enhance precipitation in central China during positive ASO anomaly events and reduce precipitation during negative events. The WACCM4 simulations support the results from statistical analysis of observations and reanalysis data. Our results suggest that ASO variation can serve as a predictor of spring precipitation variation over Loess Plateau and middle-lower reaches of the Yangtze River. [ABSTRACT FROM AUTHOR]

Extreme heat (EH) over North China (NC) is affected by both large scale circulations and local topography, and could be categorized into foehn favorable and no-foehn types. In this study, the performance of a regional coupled model in simulating EH over NC was examined. The effects of regional air-sea coupling were also investigated by comparing the results with the corresponding atmosphere-alone regional model. On foehn favorable (no-foehn) EH days, a barotropic cyclonic (anticyclonic) anomaly is located to the northeast (northwest) of NC, while anomalous northwesterlies (southeasterlies) prevail over NC in the lower troposphere. In the uncoupled simulation, barotropic anticyclonic bias occurs over China on both foehn favorable and no-foehn EH days, and the northwesterlies in the lower troposphere on foehn favorable EH days are not obvious. These biases are significantly reduced in the regional coupled simulation, especially on foehn favorable EH days with wind anomalies skill scores improving from 0.38 to 0.47, 0.47 to 0.61 and 0.38 to 0.56 for horizontal winds at 250, 500 and 850 hPa, respectively. Compared with the uncoupled simulation, the reproduction of the longitudinal position of Northwest Pacific subtropical high (NPSH) and the spatial pattern of the low-level monsoon flow over East Asia are improved in the coupled simulation. Therefore, the anticyclonic bias over China is obviously reduced, and the proportion of EH days characterized by anticyclonic anomaly is more appropriate. The improvements in the regional coupled model indicate that it is a promising choice for the future projection of EH over NC. [ABSTRACT FROM AUTHOR]

The daily temperatures from observational data, NCEP-2 and CFSR reanalysis data all exhibit long-range correlation (LRC) characteristics, which provides a test bed for assessing the reliability of reanalysis data. In this study, the quality of the NCEP-2 and CFSR data in China are evaluated on the basis of the LRC characteristics of daily temperatures, including daily average temperature (DAT), daily maximum temperature (DMAT), daily minimum temperature (DMIT), and diurnal temperature range (DTR). Compared with the observations, the quality of NCEP-2 daily temperature is relatively good in central and eastern Northwest China, and most of central and eastern China, especially for NCEP-2 DMAT. However, the NCEP-2 reanalysis data as well as CFSR has a significant difference with the LRC of the observations in most of Sichuan, Qinghai-Tibet Plateau and some areas of southwestern Xinjiang at a significance level of Alpha = 0.05. In general, the LRC characteristics of NCEP-2 daily temperature perform better than that of CFSR data. As far as DAT is concerned, CFSR perform worse in central and eastern Northwest China, and better than NCEP-2 only in South China and eastern Jiangnan. The quality of the CFSR DMAT is worse than that of NCEP-2 in central and eastern Northwest China, western Inner Mongolia, and eastern China. The quality of NCEP-2 DMIT is better than CFSR in central and eastern Northwest China, most of Inner Mongolia, and is worse than it in most of South China and eastern Jiangnan. The reliability of the CFSR DTR is very low in most of China. [ABSTRACT FROM AUTHOR]

Given the severe impacts of hot summers on human and natural systems, we attempt to quantify future changes in extreme hot summer frequency in China using the Coupled Model Intercomparison Project Phase 5 (CMIP5) projections. Unlike previous studies focusing on fixed future time slices, we investigate the changes as a function of global mean temperature (GMT) rise. Analyses show that extreme hot summers (June-July-August mean temperature higher than 90 % quantile of 1971-2000 climatology) are projected to occur at least 80 % of the time across China with a GMT rise of 2 °C. The fraction of land area with extreme hot summers becoming the norm (median of future summer temperatures exceed the extreme) will increase from ~15 % with 0.5 °C of GMT rise to ~97 % with 2.5 °C GMT rise, which is much greater than for the global land surface as a whole. A distinct spatial pattern of the GMT rise threshold over which the local extreme hot summer first becomes the norm is revealed. When averaged over the country, the GMT rise threshold is 0.96 °C. Earth system models exhibit comparable results to climate system models, but with a relatively larger spread. Further analysis shows that the concurrence of hot and dry summers will increase significantly with the spatial structure of responses depending on the definition of drying. The increase of concurrent hot and dry conditions will induce potential droughts which would be more severe than those induced by only precipitation deficits. [ABSTRACT FROM AUTHOR]

Climate change as a result of the increased greenhouse gas emissions may influence the availability of water resources in many regions on the globe. In the past decades, China has been facing severe shortage of water resources. This study focuses on the assessment of the impact of climate change on both blue and green water resources in ten large river basins in China. The blue and green water resources for these river basins were derived from the terrestrial hydrological fluxes in period 1960-2100, which were simulated with the Max Planck Institute Hydrological Model-MPI-HM. The forcing data for the hydrological model, the precipitation and temperature were obtained from three coupled Atmosphere-Ocean General Circulation Models (GCMs)-ECHAM5, IPSL and CNRM, under A2 and B1 greenhouse gas emission scenarios. The statistical bias correction method was applied on the output from the three GCMs. By using this climate model-hydrology model modeling chain, the impact of climate change on the blue and green water resources was analyzed over the ten Chinese river basins. Here, the projected changes in 2071-2100 are considered relative to 1971-2000. The projected change of monthly mean and annual mean of green water resources show the general increase for all ten river basins; among them, Inland river, Zhemin river and Zhujiang river have larger change signal than other basins. For blue water resources, increases of the annual mean are projected from November to March for Heilongjiang river, Liaohe river and Yellow river, Inland river in Northern China; and decreases are projected for Huaihe river, Zhemin river, Haihe river, Yangzi river, Southwest river, and Zhujiang river basins in Southern China. It is found that climate change has impact on both blue and green water resources over large river basins in China. The sustainable blue water resources management should take into account the different changes in both Northern and Southern China. The results show that a better management of green water resources is of importance for food and ecological securities in the context of global change. [ABSTRACT FROM AUTHOR]

Summer rainfall over China has shown decadal variability in the past half century, which has resulted in major north-south shifts in rainfall with important implications for flooding and water resource management. This study has demonstrated how multi-century climate model simulations can be used to explore interdecadal natural variability in the climate system in order to address important questions around recent changes in Chinese summer rainfall, and whether or not anthropogenic climate change is playing a role. Using a 1,000-year simulation of HadCM3 with constant pre-industrial external forcing, the dominant modes of total and interdecadal natural variability in Chinese summer rainfall have been analysed. It has been shown that these modes are comparable in magnitude and in temporal and spatial characteristics to those observed in the latter part of the twentieth century. However, despite 1,000 years of model simulation it has not been possible to demonstrate that these modes are related to similar variations in the global circulation and surface temperature forcing occurring during the latter half of the twentieth century. This may be in part due to model biases. Consequently, recent changes in the spatial distribution of Chinese summer rainfall cannot be attributed solely to natural variability, nor has it been possible to eliminate the likelihood that anthropogenic climate change has been the driving factor. It is more likely that both play a role. [ABSTRACT FROM AUTHOR]

National Centers for Environmental Prediction recently upgraded its operational seasonal forecast system to the fully coupled climate modeling system referred to as CFSv2. CFSv2 has been used to make seasonal climate forecast retrospectively between 1982 and 2009 before it became operational. In this study, we evaluate the model's ability to predict the summer temperature and precipitation over China using the 120 9-month reforecast runs initialized between January 1 and May 26 during each year of the reforecast period. These 120 reforecast runs are evaluated as an ensemble forecast using both deterministic and probabilistic metrics. The overall forecast skill for summer temperature is high while that for summer precipitation is much lower. The ensemble mean reforecasts have reduced spatial variability of the climatology. For temperature, the reforecast bias is lead time-dependent, i.e., reforecast JJA temperature become warmer when lead time is shorter. The lead time dependent bias suggests that the initial condition of temperature is somehow biased towards a warmer condition. CFSv2 is able to predict the summer temperature anomaly in China, although there is an obvious upward trend in both the observation and the reforecast. Forecasts of summer precipitation with dynamical models like CFSv2 at the seasonal time scale and a catchment scale still remain challenge, so it is necessary to improve the model physics and parameterizations for better prediction of Asian monsoon rainfall. The probabilistic skills of temperature and precipitation are quite limited. Only the spatially averaged quantities such as averaged summer temperature over the Northeast China of CFSv2 show higher forecast skill, of which is able to discriminate between event and non-event for three categorical forecasts. The potential forecast skill shows that the above and below normal events can be better forecasted than normal events. Although the shorter the forecast lead time is, the higher deterministic prediction skill appears, the probabilistic prediction skill does not increase with decreased lead time. The ensemble size does not play a significant role in affecting the overall probabilistic forecast skill although adding more members improves the probabilistic forecast skill slightly. [ABSTRACT FROM AUTHOR]

Climate change will affect the energy system in a number of ways, one of which is through changes in demands for heating and cooling in buildings. Understanding the potential effect of climate change on heating and cooling demands requires taking into account not only the manner in which the building sector might evolve over time, but also important uncertainty about the nature of climate change itself. In this study, we explore the uncertainty in climate change impacts on heating and cooling requirement by constructing estimates of heating and cooling degree days (HDD/CDDs) for both reference (no-policy) and 550 ppmv CO concentration pathways built from three different Global Climate Models (GCMs) output and three scenarios of gridded population distribution. The implications that changing climate and population distribution might have for building energy consumption in the U.S. and China are then explored by using the results of HDD/CDDs as inputs to a detailed, building energy model, nested in the long-term global integrated assessment framework, Global Change Assessment Model (GCAM). The results across the modeled changes in climate and population distributions indicate that unabated climate change would cause building sector's final energy consumption to decrease modestly (6 % decrease or less depending on climate models) in both the U.S. and China by the end of the century as decreased heating consumption more than offsets increased cooling using primarily electricity. However, global climate change virtually has negligible effect on total CO emissions in the buildings sector in both countries. The results also indicate more substantial implications for the fuel mix with increases in electricity and decreases in other fuels, which may be consistent with climate mitigation goals. The variation in results across all scenarios due to variation of population distribution is smaller than variation due to the use of different climate models. [ABSTRACT FROM AUTHOR]

Multi-decadal high resolution simulations over the CORDEX East Asia domain were performed with the regional climate model RegCM3 nested within the Flexible Global Ocean-Atmosphere-Land System model, Grid-point Version 2 (FGOALS-g2). Two sets of simulations were conducted at the resolution of 50 km, one for present day (1980-2005) and another for near-future climate (2015-40) under the Representative Concentration Pathways 8.5 (RCP8.5) scenario. Results show that RegCM3 adds value with respect to FGOALS-g2 in simulating the spatial patterns of summer total and extreme precipitation over China for present day climate. The major deficiency is that RegCM3 underestimates both total and extreme precipitation over the Yangtze River valley. The potential changes in total and extreme precipitation over China in summer under the RCP8.5 scenario were analyzed. Both RegCM3 and FGOALS-g2 results show that total and extreme precipitation tend to increase over northeastern China and the Tibetan Plateau, but tend to decrease over southeastern China. In both RegCM3 and FGOALS-g2, the change in extreme precipitation is weaker than that for total precipitation. RegCM3 projects much stronger amplitude of total and extreme precipitation changes and provides more regional-scale features than FGOALS-g2. A large uncertainty is found over the Yangtze River valley, where RegCM3 and FGOALS-g2 project opposite signs in terms of precipitation changes. The projected change of vertically integrated water vapor flux convergence generally follows the changes in total and extreme precipitation in both RegCM3 and FGOALS-g2, while the amplitude of change is stronger in RegCM3. Results suggest that the spatial pattern of projected precipitation changes may be more affected by the changes in water vapor flux convergence, rather than moisture content itself. [ABSTRACT FROM AUTHOR]

Climate change in the 21st century over China is simulated using the Abdus Salam International Centre for Theoretical Physics (ICTP) Regional Climate Model version 3 (RegCM3). The model is one-way nested within the global model CCSR/NIES/FRCGC MIROC3.2_hires (Center for Climate System Research/National Institute for Environmental Studies/Frontier Research Center for Global Change/Model for Interdisciplinary Research on Climate). A 150-year (1951-2100) transient simulation is conducted at 25 km grid spacing, under the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (IPCC SRES) A1B scenario. Simulations of present climate conditions in China by RegCM3 are compared against observations to assess model performance. Results show that RegCM3 reproduces the observed spatial structure of surface air temperature and precipitation well. Changes in mean temperature and precipitation in December-January-February (DJF) and June-July-August (JJA) during the middle and end of the 21st century are analyzed. Significant future warming is simulated by RegCM3. This warming becomes greater with time, and increased warming is simulated at high latitude and high altitude (Tibetan Plateau) areas. In the middle of the 21st century in DJF, a general increase of precipitation is found in most areas, except over the Tibetan Plateau. Precipitation changes in JJA show an increase over northwest China and a decrease over the Tibetan Plateau. There is a mixture of positive and negative changes in eastern China. The change pattern at the end of the century is generally consistent with that in mid century, except in some small areas, and the magnitude of change is usually larger. In addition, the simulation is compared with a previous simulation of the RegCM3 driven by a different global model, to address uncertainties of the projected climate change in China. [ABSTRACT FROM AUTHOR]

An interactive system coupling the Beijing Climate Center atmospheric general circulation model (BCC_AGCM2.0.1) and the Canadian Aerosol Module (CAM) with updated aerosol emission sources was developed to investigate the global distributions of optical properties and direct radiative forcing (DRF) of typical aerosols and their impacts on East Asian climate. The simulated total aerosol optical depth (AOD), single scattering albedo, and asymmetry parameter were generally consistent with the ground-based measurements. Under all-sky conditions, the simulated global annual mean DRF at the top of the atmosphere was −2.03 W m for all aerosols including sulfate, organic carbon (OC), black carbon (BC), dust, and sea salt; the global annual mean DRF was −0.23 W m for sulfate, BC, and OC aerosols. The sulfate, BC, and OC aerosols led to decreases of 0.58° and 0.14 mm day in the JJA means of surface temperature and precipitation rate in East Asia. The differences of land-sea surface temperature and surface pressure were reduced in East Asian monsoon region due to these aerosols, thus leading to the weakening of East Asian summer monsoon. Atmospheric dynamic and thermodynamic were affected due to the three types of aerosol, and the southward motion between 15°N and 30°N in lower troposphere was increased, which slowed down the northward transport of moist air carried by the East Asian summer monsoon, and moreover decreased the summer monsoon precipitation in south and east China. [ABSTRACT FROM AUTHOR]