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In aiming for better access to climate change information and for providing climate service, it is important to obtain reliable high-resolution temperature simulations. Systematic comparisons are still deficient between statistical and dynamic downscaling techniques because of their inherent unavoidable uncertainties. In this paper, 20 global climate models (GCMs) and one regional climate model [Providing Regional Climates to Impact Studies (PRECIS)] are employed to evaluate their capabilities in reproducing average trends of mean temperature (Tm), maximum temperature (Tmax), minimum temperature (Tmin), diurnal temperature range (DTR), and extreme events represented by frost days (FD) and heat-wave days (HD) across China. It is shown generally that bias of temperatures from GCMs relative to observations is over ±1°C across more than one-half of mainland China. PRECIS demonstrates better representation of temperatures (except for HD) relative to GCMs. There is relatively better performance in Huanghuai, Jianghuai, Jianghan, south Yangzi River, and South China, whereas estimation is not as good in Xinjiang, the eastern part of northwest China, and the Tibetan Plateau. Bias-correction spatial disaggregation is used to downscale GCMs outputs, and bias correction is applied for PRECIS outputs, which demonstrate better improvement to a bias within ±0.2°C for Tm, Tmax, Tmin, and DTR and ±2 days for FD and HD. Furthermore, such improvement is also verified by the evidence of increased spatial correlation coefficient and symmetrical uncertainty, decreased root-mean-square error, and lower standard deviation for reproductions. It is seen from comprehensive ranking metrics that different downscaled models show the most improvement across different climatic regions, implying that optional ensembles of models should be adopted to provide sufficient high-quality climate information. [ABSTRACT FROM AUTHOR]

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

Middle and eastern routes of the South-North Water Diversion Project (SNWDP) of China, which are approximately located within the area 28°-42°N and 110°-122°E, are being constructed. This paper investigates the past climatic variations on various time scales using instrumental and proxy data. It is found that annual mean surface air temperature has increased significantly during the past 50-100 years, and winter and spring temperatures in the northern part of the region have undergone the most significant changes. A much more significant increase occurs for annual mean minimum temperature and extreme low temperature than for annual mean maximum temperature and extreme high temperature. No significant trend in annual precipitation is found for the region as a whole for the last 50 and 100 years, although obvious decadal and spatial variation is detectable. A seesaw pattern of annual and summer precipitation variability between the north and the south of the region is evident. Over the last 100 years, the Haihe River basin has witnessed a significant negative trend of annual precipitation, but no similar trend is detected for the Yangtze and Huaihe River basins. Pan evaporation has significantly decreased since the mid-1960s in the region in spite of the fact that the trend appears to have ended in the early 1990s. The negative trend of pan evaporation is very significant in the plain area between the Yangtze and Yellow Rivers. There was a notable series of dry intervals lasting decades in the north of the region. The northern drought of the past 30 years is not the most severe in view of the past 500 years; however, the southern drought during the period from the 1960s to the 1980s may have been unprecedented. The dryness-wetness index (DWI) shows significant oscillations with periodicities of 9.5 and 20 years in the south and 10.5 and 25 years in the north. Longer periodicities in the DWI series include 160-170- and 70-80-yr oscillations in the north, and 100-150-yr oscillations in the south. The observed climate change could have implications for the construction and management of the SNWDP. The official approval and start of the hydro project was catalyzed by the severe multiyear drought of 1997-2003 in the north, and the operation and management of the project in the future will also be influenced by climate change-in particular by precipitation variability. This paper provides a preliminary discussion of the potential implications of observed climate change for the SNWDP. [ABSTRACT FROM AUTHOR]

This paper presents projected changes in temperature and precipitation extremes in China by the end of the twenty-first century based on the Coupled Model Intercomparison Project phase 5 (CMIP5) simulations. The temporal changes and their spatial patterns in the Expert Team on Climate Change Detection and Indices (ETCCDI) indices under the RCP4.5 and RCP8.5 emission scenarios are analyzed. Compared to the reference period 1986-2005, substantial changes are projected in temperature and precipitation extremes under both emission scenarios. These changes include a decrease in cold extremes, an increase in warm extremes, and an intensification of precipitation extremes. The intermodel spread in the projection increases with time, with wider spread under RCP8.5 than RCP4.5 for most indices, especially at the subregional scale. The difference in the projected changes under the two RCPs begins to emerge in the 2040s. Analyses based on the mixed-effects analysis of variance (ANOVA) model indicate that by the end of the twenty-first century, at the national scale, the dominant contributor to the projection uncertainty of most temperature-based indices, and some precipitation extremes [including maximum 1-day precipitation (RX1day) and maximum 5-day precipitation (RX5day), and total extremely wet day total amount (R95p)], is the difference in emission scenarios. By the end of the twenty-first century, model uncertainty is the dominant factor at the regional scale and for the other indices. Natural variability can also play very important role. [ABSTRACT FROM AUTHOR]

Vegetation around the Daihai Lake, northern China, is very sensitive to climate changes. In this paper, pollen-based quantitative climate reconstructions using three methods [weighted averaging partial least squares method (WAPLS), modern analog technique (MAT), and pollen response surface method (PRS)] were conducted to obtain robust reconstructions of Holocene climate changes in the Daihai Lake area. The result obtained by the three methods all consistently show the annual precipitation to have been 50–100 mm lower in the early Holocene, 100–200 mm higher in the Mid-Holocene, and 50–100 mm lower again in the late Holocene than at present. The WAPLS and the MAT methods also show quasi-synchronous oscillations of the mean annual temperature (Ta); 1°–2°C lower in the Early Holocene and 1°–3°C higher in the Mid-Holocene than today. The time period from 6200 to 5100 cal yr BP was the wettest and the warmest interval, with an annual precipitation (Pa) greater than 550 mm and mean annual temperature Ta higher than 6.5°C. Several cold and dry events can be identified to occur about 8200, 6000, and 4400 cal yr BP, with an annual precipitation less than 400 mm and a mean annual temperature colder than 4.5°C, respectively. The mean temperature of the warmest month (Tw) as reconstructed using both WAPLS and MAT methods was relatively stable during the Holocene, fluctuating about ±2°C relative to the present level, but the PRS method suggests more varied Tw values in both amplitude and frequency. After 1500 cal yr BP, no consistent pattern can be observed from these three different analyses, probably because of the impact of intensified human disturbances on the natural vegetation. The fluctuations of annual precipitation (Pa) correspond to that observed in Dongge Cave in southern China. The differences might be linked to Indian monsoon and East Asia monsoon climates or caused by the different degree of dating precision, different temporal resolution, and different sensitive response of climate proxies to the climate variations. [ABSTRACT FROM AUTHOR]

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

On the basis of a newly developed observational dataset and a suite of climate model simulations, we evaluate changes in summer mean wet bulb globe temperature (WBGT) in China from 1961 through 2080. We show that summer mean WBGT has increased almost everywhere across China since 1961 as a result of human-induced climate change. Consequently, hot summers as measured by summer mean WBGT are becoming more frequent and more conducive to heat stress. Hot summers like the hottest on record during 1961–2015 in western or eastern China are now expected occur once every 3–4 years. These hot WBGT summers have become more than 140 times as likely in eastern China in the present decade (2010s) as in the 1961–90 baseline period and more than 1000 times as likely in western China. The substantially larger influence in western China is associated with its stronger warming signal, which is likely due to the high Bowen ratio of sensible to latent heat fluxes of dry soils and increases in absorbed solar radiation from the decline in mountain snow cover extent. Observation-constrained projections of future summer mean WBGT under the RCP8.5 emissions scenario indicate that, by the 2040s, almost every summer in China will be at least as hot as the hottest summer in the historical record, and by the 2060s it will be common (on average, every other year) for summers to be as much as 3.0°C hotter than the historical record, pointing to potentially large increases in the likelihood of human heat stress and to a massive adaption challenge. [ABSTRACT FROM AUTHOR]

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

The Sichuan basin is one of the most densely populated regions of China, making the area particularly vulnerable to the adverse impacts associated with future climate change. As such, climate models are important for understanding regional and local impacts of climate change and variability, like heat stress and drought. In this study, climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) are validated over the Sichuan basin by evaluating how well each model can capture the phase, amplitude, and variability of the regionally observed mean, maximum, and minimum temperature between 1979 and 2005. The results reveal that the majority of the models do not capture the basic spatial pattern and observed means, trends, and probability distribution functions. In particular, mean and minimum temperatures are underestimated, especially during the winter, resulting in biases exceeding −3°C. Models that reasonably represent the complex basin topography are found to generally have lower biases overall. The five most skillful climate models with respect to the regional climate of the Sichuan basin are selected to explore twenty-first-century temperature projections for the region. Under the CMIP5 high-emission future climate change scenario, representative concentration pathway 8.5 (RCP8.5), the temperatures are projected to increase by approximately 4°C (with an average warming rate of +0.72°C decade−1), with the greatest warming located over the central plains of the Sichuan basin, by 2100. Moreover, the frequency of extreme months (where mean temperature exceeds 28°C) is shown to increase in the twenty-first century at a faster rate compared to the twentieth century. [ABSTRACT FROM AUTHOR]

The standardized precipitation evapotranspiration index (SPEI) is computed and compared in China using reference evapotranspiration calculated using the Thornthwaite (TH) approach and the Penman-Monteith (PM) equation. The analysis reveals that SPEI_PM outperforms the SPEI_TH with regard to drought monitoring during the period 1961-2012 over China, especially in arid regions of China. Furthermore, the SPEI_PM also performs better with regard to observed variations in soil moisture and streamflow in China. Thus, changes in drought characteristics over China are detected on the basis of variations in the SPEI_PM. The results indicate that droughts over China exhibit pronounced decadal variations over the past 50 yr, with more frequent and severe droughts occurring before the 1980s and in the 2000s compared with the 1980s and 1990s. Since the late 1990s, droughts have become more frequent and severe across China, especially in some regions of northern China. Concurrently, consecutive drought events have also increased across China. This suggests that dry conditions in China have been enhanced in recent years. Further analyses illustrate that the temperature and precipitation anomalies exhibit different roles in detecting droughts across China, which is primarily due to the magnitude of their variations and different climate variability. Considering temperature and precipitation perturbations, droughts exhibit relatively larger responses to temperature fluctuations in northern China and relatively larger responses to precipitation anomalies in southern China. [ABSTRACT FROM AUTHOR]

Historical temperature variability over China during the twentieth century and projected changes under three emission scenarios for the twenty-first century are evaluated on the basis of a multimodel ensemble of 20 GCMs from phase 5 of the Coupled Model Intercomparison Project (CMIP5) and two observational datasets. Changes relative to phase 3 of the Coupled Model Intercomparison Project (CMIP3) are assessed, and the performance of individual GCMs is also quantified. Compared with observations, GCMs have substantial cold biases over the Tibetan Plateau, especially in the cold season. The timing and location of these biases also correspond to the greatest disagreement among the individual models, indicating GCMs' limitations in reproducing climatic features in this complex terrain. The CMIP5 multimodel ensemble shows better agreement with observations than CMIP3 in terms of the temperature biases. Both CMIP3 and CMIP5 capture the climatic warming over the twentieth century. However, the magnitude of the annual mean temperature trends is underestimated. There is also limited agreement in the spatial and seasonal patterns of temperature trends over China. Based on six statistical measures, four individual models-the Max Planck Institute Earth System Model, low resolution (MPI-ESM-LR), Second Generation Canadian Earth System Model (CanESM2), Model for Interdisciplinary Research on Climate, Earth System Model (MIROC-ESM), and Community Climate System Model, version 4 (CCSM4)-best represent surface air temperature variability over China. The future temperature projections indicate that the representative concentration pathway (RCP) 8.5 and RCP 4.5 scenarios exhibit a gradual increase in annual temperature during the twenty-first century at a rate of 0.60° and 0.27°C (10 yr)−1, respectively. As the lowest-emission mitigation scenario, RCP 2.6 projects the lowest rate of temperature increase [0.10°C (10 yr)−1]. By the end of the twenty-first century, temperature is projected to increase by 1.7°-5.7°C, with larger warming over northern China and the Tibetan Plateau. [ABSTRACT FROM AUTHOR]

In the global lands, the bias of urbanization effects still exits in the surface air temperature series of many city weather stations to a certain extent. Reliable reference climate stations need to be selected for the detection and correction of the local manmade warming bias. The underlying image data of remote sensing retrieval is adopted in this study to obtain the spatial distribution of surface brightness temperature, and the surface air temperature reference stations are determined based on the locations of the weather stations in the remote sensing surface thermal fields. Among the 672 national reference climate stations and national basic weather stations of mainland China, for instance, 113 surface air temperature reference stations are selected for applying this method. Compared with the average surface air temperature series of the reference stations obtained by a more sophisticated method developed in China, this method is proven to be robust and applicable, and can be adopted for the evaluation and adjustment study on the urbanization bias of the currently used air temperature records of surface climate stations in the global lands. [ABSTRACT FROM AUTHOR]

A study is presented of the geographical distribution and spatial and temporal variabilities of the western China snow cover in the past 47 yr between 1951 and 1997. The data used consist of Scanning Multichannel Microwave Radiometer (SMMR) 6-day snow-depth charts, NOAA weekly snow extent charts, and the daily snow depth and number of snow cover days from 106 selected meteorological stations across western China. Empirical orthogonal function was performed on the SMMR dataset to better understand the spatial pattern and variability of the Qinghai–Xizang (Tibet) snow cover. A multiple linear regression analysis was conducted to show the association of interannual variations between snow cover and snow season temperature as well as precipitation. Further, the autoregressive moving average model was fitted to the snow and climate time series to test for their long-term trends. Results show that western China did not experience a continual decrease in snow cover during the great warming period of the 1980s and 1990s. It is of interest to note that no correlation was identified between temperature and precipitation in the snow cover season. However, year-to-year fluctuation of snow cover responds to both snowfall and snow season temperature. About one-half to two-thirds of the total variance in snow cover is explained by the linear variations of snowfall and snow season temperature. The long-term variability of western China snow cover is characterized by a large interannual variation superimposed on a small increase trend. The positive trend of the western China snow cover is consistent with increasing snowfall, but is in contradiction to regional warming. In addition, many constraints of the Qinghai–Xizang (Tibet) snow cover force the author’s challenge of Blanford’s hypothesis. [ABSTRACT FROM AUTHOR]