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Lakes under natural conditions are potential indicators of climate change, but limited evidence has been proposed to explicitly explain the mechanisms of large-scale lake changes associated with climate. In this paper, satellite imageries from the 1970s to 2010 were compared to track the dynamic change patterns of plateau lakes. It aims to identify the forcing of climate change on the lakes in plateau regions of China. Results revealed that: (1) widespread expanding trends in the area and abundance of lakes on wetter plateau regions, by increasing precipitation and snow presented a positive effect on lake levels, as well as warming resulted glacier melting and permafrost degrading contributed to expansion of lakes in the regions covered by glaciers on the Tibetan Plateau by 58-62 % and of 13-20 % on the western Inner Mongolia and Xinjiang Plateau; (2) shrinkage lakes in the main portion of the arid regions were mainly caused by the decreasing wind speed resulted water balance change, irrigation and other human utilization of water resources. Although precipitation decreased, wind speed also has the most dominant impact on decreasing evaporation, followed by solar radiation, both of which offset the effect of increasing temperature, especially in eastern Inner Mongolia and Xinjiang Plateau; (3) thawing permafrost led to shrinkage of lakes in an area of seasonal permafrost, the shrinking and splitting of lakes in a discontinuous permafrost zone, and the rising of lake levels in an area of continuous permafrost; (4) the future of the plateau lakes under climate change must be in question, because the glacier and snow melting water is not sustainable for wetter regions, and the increasing water consumption caused by the farmland expansion for arid regions. [ABSTRACT FROM AUTHOR]

Regional precipitation patterns may change in a warmer climate, thereby increasing flood and drought risks. In this paper, annual, annual maximum, intense, heavy, moderate, light, and trace precipitation are employed as indicators to assess changes in precipitation patterns under two scenarios in which the global mean temperature increases by 1.5 °C and 2.0 °C relative to pre-industrial levels using the regional climate model COSMO-CLM (CCLM). The results show that annual precipitation in China will be approximately 2.5% higher under 1.5 °C warming relative to the present-day baseline (1980–2009), although it will decrease by approximately 4.0% under an additional 0.5 °C increase in global mean temperature. This trend is spatially consistent for regions with annual precipitation of 400–800 mm, which has experienced a drying trend during the past half century; thus, limiting global warming to 1.5 °C may mitigate these drying conditions. The annual maximum precipitation continues to increase from present day levels to the 2.0 °C warming scenario. Relative to the baseline period, the frequency of trace and light precipitation days exhibits a negative trend, while that of moderate, heavy, and intense precipitation days has a positive trend under the 1.5 °C warming scenario. For the 2.0 °C warming world, the frequency of days is projected to decrease for all precipitation categories, although the intensity of intense precipitation increases. Spatially, a decrease in the number of precipitation days is expected to continue in central and northern China, where a drying trend has persisted over the past half century. Southeastern China, which already suffers greatly from flooding, is expected to face more heavy and intense precipitation with an additional 0.5 °C increase in global mean temperature. Meanwhile, the intensity of intense precipitation is expected to increase in northern China, and the contribution of light and moderate precipitation to the annual precipitation is expected to decrease in southeastern China. Therefore, flood risk in northern China and drought risk in southern China should draw more attention for a global air temperature increase from 1.5 °C to 2.0 °C. [ABSTRACT FROM AUTHOR]

Climate change shifts the distributions of a set of climatic variables, including temperature, precipitation, humidity, wind speed, sunshine duration, and evaporation. This paper explores the importance of those additional climatic variables other than temperature and precipitation. Using the county-level agricultural data from 1980 to 2010 in China, we find that those additional climatic variables, especially humidity and wind speed, are critical for crop growth. Therefore, omitting those variables is likely to bias the predicted impacts of climate change on crop yields. In particular, omitting humidity tends to overpredict the cost of climate change on crop yields, while ignoring wind speed is likely to underpredict the effect. Our preferred specification indicates that climate change is likely to decrease the yields of rice, wheat, and corn in China by 36.25%, 18.26%, and 45.10%, respectively, by the end of this century. [ABSTRACT FROM AUTHOR]

This paper tries to answer the question that whether farmers can adjust better to climate change in the short-term than in long-term by using panel data models and long difference models respectively. We find that short term weather shocks are less detrimental to maize yield than the long-term climate changes, which can be seen as the evidences of adaptations. For adaptation options, we find farmers choose to decrease maize planting area or enlarge the irrigation inputs to cope with the increase of extreme heat days; when there are more precipitations, farmers will increase the input of fertilizer or labor. [ABSTRACT FROM AUTHOR]

A persistent concern about the social consequences of climate change is that large, vulnerable populations will be involuntarily displaced. Existing evidence suggests that changes in precipitation and temperature can increase migration in particular contexts, but the potential for this relationship to evolve over time alongside processes of adaptation and development has not been widely explored. To address this issue, we link longitudinal data from 20 thousand Chinese adults from 1989 to 2011 to external data on climate anomalies and use this linked dataset to explore how climatic effects on internal migration have changed over time while controlling for potential spatial and temporal confounders. We find that temperature anomalies initially displaced permanent migrants at the beginning of our study period, but that this effect had reversed by the end of the study period. A parallel analysis of income shares suggests that the explanation might lie in climate vulnerability shifting from agricultural to non-agricultural livelihood activities. Taken together with evidence from previous case studies, our results open the door to a potential future in which development and in situ adaptation allow climate-induced migration to decline over time, even as climate change unfolds. [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]

Climate change and urbanization collectively influence precipitation changes. However, their separate potential contributions to precipitation changes are not well understood due to their complex interactions. Hence, a "trajectory"‐based method was used to separate their potential contributions across national, regional and local scales in China. Precipitation changes in non‐urban regions can be regarded as representing the influence of climate change and can serve as a reference for isolating precipitation changes due to urbanization in urban areas. Our results revealed that climate change was the dominant factor for precipitation trends, while urbanization exhibited a relatively weak influence, especially for extreme precipitation at the national scale. At the regional scale, the impacts of urbanization on precipitation became more significant. About 20.2 and −30.6% of positive and negative trends in total precipitation originated from urbanization. At the local scale, the potential contribution of urbanization was strongly correlated with local environmental characteristics. Although there were differences in the potential contributions of climate change and urbanization at national, regional and local scales, climate change was the dominant factor for precipitation trends and urbanization acted as a regulator to drying or wetting due to precipitation under climate change. In general, urbanization causes a greater impact on total precipitation than on precipitation extremes. Due to this, attribution approach is static and broad‐based and does not render the level of confidence that is needed for scale‐aware attribution, future studies are needed to understand the physical mechanisms of impacts of local environment changes on precipitation trends at different geographical locations over China. [ABSTRACT FROM AUTHOR]

The numerous temperature and precipitation reconstructions in China based on tree-ring-width data have played significant roles in furthering the understanding of past climate changes. However, the geographical variability in the responses of trees to climate variations in China remains largely undetermined. Here, we describe an important spatial boundary in the response of trees to climate variations, namely the 600-mm annual precipitation isoline. We found that, to the north of this line, tree-ring widths are usually positively correlated with precipitation and negatively correlated with growing-season temperature. To the south of this line, the tree-ring widths respond positively to temperature, and winter half-year temperatures are the main reconstructed parameters, especially on the third topographical step of China. We also found that precipitation reconstructions based on tree-ring data and the Palmer Drought Severity Index almost exclusively fall in the region of the 200- to 600-mm annual precipitation isolines, not other regions. Our findings indicate that, when using multiple tree-ring-width chronologies for large-scale past climate reconstructions, the climatic signal of each tree-ring-width series should be carefully considered. [ABSTRACT FROM AUTHOR]

Understanding the changes in aridity is crucial because of the substantial impacts it can have on human society. However, realistic aridity changes and their underlying climatic mechanisms demonstrate large uncertainties in China. Here we adopted the aridity index (AI) to assess the aridity changes in China, and we quantified the relative contributions of various climatic drivers (the precipitation, net radiation, wind speed, relative humidity, and air temperature) to AI changes based on the station data during 1961–2016. Our results showed that the arid/semi‐arid northwest China and Tibet Plateau experienced wetting trends, while western sub‐humid north and northeast China and western humid south China exhibited drying trends during 1961–2016. The dominant climatic drivers involved in the changing AI trends changed from arid to humid regions. In arid northwest China, increasing precipitation and decreasing wind speeds contributed the most to the wetting trends (0.024 and 0.017 in 56 years, respectively). In the semi‐arid Tibet Plateau, increasing precipitation dominated the wetting trends (0.045 in 56 years). However, in sub‐humid/humid north and northeast China and south China, decreasing wind speed and net radiation dominated the annual AI changes (0.061 and 0.092 in 56 years, respectively). In addition, AI of northwest China and the Tibet Plateau exhibited a significant abrupt change in 1987 and exhibited wetter states afterwards, which could be caused by the abrupt increase in precipitation in 1987. This study could improve current understanding of the aridity changes in China and help adapt its potential impacts. This study investigated the aridity changes and their underlying climatic mechanisms in China using station data during 1961–2016. Results showed that the "arid regions getting drier; humid regions getting wetter" is not applicable to China. The dominant climatic driver for aridity changes varies from arid to humid regions. Precipitation dominates the wetting trends in arid/semi‐arid northwest China and the Tibet Plateau, whereas wind speed and net radiation dominate aridity changes in sub‐humid/humid north and northeast China and south China. [ABSTRACT FROM AUTHOR]

Drought and vegetation conditions within the Damqu River Basin, part of the Yangtze River Source Region (YRSR), are assessed here using the standardized precipitation index (SPI), the standardized precipitation evapotranspiration index (SPEI), the normalized difference vegetation index (NDVI), and the leaf area index (LAI). We utilized Sen’s method, least squares regression method, linear regression and Pearson’s correlation analysis to study variations in drought and vegetation indices and the drought effect on vegetation between 1988 and 2015. Results reveal that droughts occurred at a 25% frequency over this period; SPI and SPEI analyses show that 1994, 1999, 2005, and 2010 were change points and that the basin was characterized by varying drought and humidity trends. Subsequent to 2010, both SPI and SPEI decreased within the basin, while 1995, 2000, 2004, and 2010 were change points for NDVI and LAI while the watershed exhibited variable trends in vegetation reduction and increase. The NDVI-annual values of 63.36% regions and the LAI-summer values of 68.39% areas within the basin were decreased during 1988–2015 and 2000–2015, respectively. Subsequent to 2010, both NDVI and LAI decreased within the basin and significant positive correlations at inter-annual and inter-summer time scales were seen in both drought and vegetation indices; drought has exerted a lag effect on vegetation as shown by significant positive correlations between annual SPI/SPEI values and following year NDVI/LAI values. [ABSTRACT FROM AUTHOR]

The spatial and temporal variations of daily maximum temperature (Tmax), daily minimum temperature (Tmin), daily maximum precipitation (Pmax) and daily maximum wind speed (WSmax) were examined in China using Mann-Kendall test and linear regression method. The results indicated that for China as a whole, Tmax, Tmin and Pmax had significant increasing trends at rates of 0.15 °C per decade, 0.45 °C per decade and 0.58 mm per decade, respectively, while WSmax had decreased significantly at 1.18 m·s-1 per decade during 1959-2014. In all regions of China, Tmin increased and WSmax decreased significantly. Spatially, Tmax increased significantly at most of the stations in South China (SC), northwestern North China (NC), northeastern Northeast China (NEC), eastern Northwest China (NWC) and eastern Southwest China (SWC), and the increasing trends were significant in NC, SC, NWC and SWC on the regional average. Tmin increased significantly at most of the stations in China, with notable increase in NEC, northern and southeastern NC and northwestern and eastern NWC. Pmax showed no significant trend at most of the stations in China, and on the regional average it decreased significantly in NC but increased in SC, NWC and the mid-lower Yangtze River valley (YR). WSmax decreased significantly at the vast majority of stations in China, with remarkable decrease in northern NC, northern and central YR, central and southern SC and in parts of central NEC and western NWC. With global climate change and rapidly economic development, China has become more vulnerable to climatic extremes and meteorological disasters, so more strategies of mitigation and/or adaptation of climatic extremes, such as environmentally-friendly and low-cost energy production systems and the enhancement of engineering defense measures are necessary for government and social publics. [ABSTRACT FROM AUTHOR]

The relation between climate change and historical rhythms has long been discussed; however, this type of study still faces the lack of high-resolution data of long-term socio-economic processes. In this study, we collected 1101 items of direct and proffered evidence from 24 Chinese fiscal and economic history books written by leading contemporary scholars. By analysing the semantics of words, we reconstructed a 2130-year-long fiscal sequence with decadal resolution to express the phase transition of fiscal soundness for approximately 21 dynasties in China. Our reconstruction shows four relatively sufficient stages and three relatively deficient stages, with several secondary stages lasting 60 or 160 years on average within each large stage, from 220 bc to ad 1910. Then, the fiscal association with climate change was analysed. The results show that the fiscal crisis was more likely to occur in cold-dry climatic scenarios. Both temperature and precipitation displayed more significant effects on the fiscal fluctuation within the long term, particularly for temperature. In short, fiscal decline had a 10-year lag in response to decreasing precipitation, whereas influence of decreasing temperature on the fiscal balance might be through amplifying already deteriorating fiscal conditions. Regional differences existed in the influence of precipitation on the fiscal balance. The precipitation in the Northern China Plain and in the Jiang-Huai area had more significant effects on the fluctuation of the dynastic fiscal balance than on that in the Jiang-Nan area. In particular, the dynastic finance was more sensitive to the change in the precipitation in the Northern China Plain because of its special geographical, economic and social backgrounds. [ABSTRACT FROM AUTHOR]

Long-term precipitation trend is a good indicator of climate and hydrological change. The data from 635 ground stations are used to quantify the temporal trends of precipitation with different intensity in China from 1961 to 2016. These sites are roughly uniformly distributed in the east or west regions of China, while fewer sites exist in the western region. The result shows that precipitation with a rate of <10 mm/day dominates in China, with a fraction of >70%. With a 95% confidence level, there is no significant temporal change of annually averaged precipitation in the whole of China. Seasonally, there are no significant temporal changes except for a robust decreasing trend in autumn. Spatially, significant differences in the temporal trends of precipitation are found among various regions. The increasing trend is the largest in Northwest China, and the decreasing trend is the largest in North China. The annually averaged number of precipitation days shows a decreasing trend in all regions except for Northwest China. Regarding precipitation type, the number of light precipitation days shows a robust decreasing trend for almost all regions, while other types show no significant change. Considering the high frequency, the temporal trends of light precipitation could highly explain the temporal variation of the total precipitation amount in China. [ABSTRACT FROM AUTHOR]