Search

Relative soil moisture is of great significance to the growth and yield of sugarcane. In this study, we use the relative soil moisture from the China Meteorological Administration Land Data Assimilation System (CLDAS) to dynamically evaluate the water requirement of sugarcane and its growth adaptability at different growth stages. Based on the data of relative soil moisture, air temperature, precipitation, and soil temperature, a sugarcane yield model is established to analyze the projected change trends of sugarcane yield in China from 2020 to 2100 under three future scenarios. Analysis results show that sugarcane requires more water during the elongation stage but less water at the ripening stage. The relative soil moisture from the CLDAS can be used to calculate the proportion of the daily suitable area to the total planting area. The combining of relative soil moisture data and water requirement indicators can better characterize the water requirement during sugarcane growth. Suitable relative soil moisture during the tillering and elongation stages is the most critical factor that directly affects the sugarcane yield. From 2020 to 2100, sugarcane yield will increase first and then decrease sharply. The increase in emissions can lead to an apparent downward trend in sugarcane yield. Based on the CLDAS data and water requirement indicators, a new method for monitoring the sugarcane growth throughout the growth period is proposed in this study. In the SSP370 and SSP460 scenarios, the sugarcane yield showed a downward trend, and there were mutations in 2064 and 2052, respectively. After the mutation, the yield decline trend was more obvious. Under the SSP585 scenario model, the sugarcane production showed an upward trend from 2022 to 2033 and a downward trend after 2033, and a mutation occurred in 2051. After the mutation, the downward trend of sugarcane production was more obvious. [ABSTRACT FROM AUTHOR]

Meteorological disasters have increasingly become one of the important interferences limiting vegetation growth and productivity recent years, especially in ecologically fragile regions. However, it is unknown how much the impact of meteorological disaster on the vegetation in ecologically fragile area under the changing climate. This study aims to identify the spatial and temporal distribution of four meteorological disasters (drought, rainstorm, high temperature, and low temperature) as well as net primary productivity (NPP) reduction rate in Guangxi province, China, which has large ecologically fragile Karst areas. We also aim to quantify the relative impact of each disaster on NPP loss. During the last 20 years (2000–2019), there was a decreasing trend for drought indicator (drought days), but an increasing trend for rainstorm (cumulated rainfall for daily rainfall higher than 50 mm and less than 99.9 mm), high temperature (daily maximum air temperature higher than 35°C and less than 37°C days), and low temperature (cumulated thermal time for daily minimum temperature less than 0°C) indictors. In the northeast area of study region, all the intensity of rainstorm, high- and low-temperature disasters showed an increasing trend. Under the more intense and frequent meteorological disasters, 87% study sites (60 stations/69 stations in total) showed an increasing trend in terms of NPP reduction rate. Results on grey correlation between each meteorological disaster and NPP reduction rate showed that high-temperature disaster had the greatest impact (27%) on vegetation growth, followed by drought (25%) and rainstorm (25%) disaster, and then low-temperature (23%) disaster. Our results would be helpful for meteorological disasters warning, vegetation protecting as well as policies making for governments. [ABSTRACT FROM AUTHOR]

The variation of surface air temperature is one of the most direct manifestations of global warming. Current research on this variable mainly focuses on climatology and extreme temperatures; however, the daily to monthly variation of temperature across extratropical regions is significantly affected by the annual cycle. Climate models play a key role in simulating the historical climate and assessing climate variability. This study investigated the temperature annual cycle and its variation in China from 1961 to 2014, using the observations collected at meteorological stations and the outputs of CMIP6 models. Regional differences and model discrepancies were evaluated to reveal the capabilities of CMIP6 models. The phase-max, phase-min, and amplitude were used to represent the annual cycle, after Fourier transformation was applied to daily temperature to filter high-frequency noise. The climatology, interannual variability, and long-term trends of the three above-mentioned parameters simulated in CMIP6 models were compared with those obtained from observations over the whole study area and in selected regions. The results showed that the models could reasonably describe the climatological temperature annual cycle from 1961 to 2014, although the values were underestimated relative to meteorological observations. Station observation and CMIP6 models also showed a similar spatial distribution of the phase-max, phase-min, and amplitude values, with an obvious north–south gradient. Station observations exhibited a large interannual variability, an advance in phase-max and phase-min, and a decrease in amplitude, which were poorly revealed by the CMIP6 models. [ABSTRACT FROM AUTHOR]

Global warming and associated frequent extreme hydrological events with increasingly severe climate change threaten human life and economic development. Consequently, climate change has become a significant focus of the scientific community. The middle reaches of the Yangtze River Basin (MYRB) contain abundant water resources and is an area with intensive human activities; it is not only the center of social and economic development in China but also the region with the highest frequency of drought and flood disasters. This study analyzed the spatiotemporal characteristics of several climate change indicators, including temperature, precipitation, and the standardized precipitation evapotranspiration index (SPEI), in the MYRB during 1961–2017, using principal component analysis (PCA). The main results are as follows: (1) mean temperature, monthly air temperature sum, precipitation sum, maximum daily precipitation, and number of days with precipitation exceeding 30 mm were the primary variables that experienced variations in the MYRB; (2) the average temperature during spring and autumn and precipitation intensity in summer increased significantly in the MYRB, primarily in the east and the north. Increased aridity during spring, autumn, and winter was apparent in the MYRB; and (3) changes in the distribution of temperature and the intensification of drought were the principal variables that changed across the study period in the Hanjiang River Basin, while the dominant variables in Dongting Lake Basin and Yichang to Hukou Basin were precipitation regime and temperature-related indicators. The results of this study can improve our understanding of how climate change affects the MYRB, allowing the development of mitigation measures for meteorological disasters. [ABSTRACT FROM AUTHOR]

The Yangtze River Delta (YRD) region, located over East China, is an international urban agglomeration radiating Asia Pacific with convenient transportation, advanced manufacturing industry, and modern service industry. The intensive human activities have exerted substantial effects on the weather and climate over the YRD region during the past decades, thus bringing more challenges to accurate weather and climate forecasting. However, the weekly cycles of surface air temperature and precipitation linked closely to human activities and their corresponding physical processes remain insufficiently understood. Here, we investigate the weekly cycles of summertime surface air temperature and precipitation and the weekend effect over the YRD region for the period of 2008–2019 using high-resolution observational data and reanalysis data. The results demonstrate that lower surface air temperature and higher precipitation generally manifest during weekends compared to weekdays over the YRD region particularly over the areas with intensive human activities. Further analysis of the underlying physical processes points to the aerosol-cloud-radiation interaction which largely explains the weekend effect in summertime temperature and precipitation over the YRD region. [ABSTRACT FROM AUTHOR]

With the intensification of global warming, extreme precipitation events occur frequently all over the world. Extreme precipitation has brought huge challenges to the development of human society and economy, and it is urgent to strengthen the analysis of the causes of extreme precipitation. In this study, we first extracted precipitation events from the precipitation time series from 1960 to 2018 in the Huaihe River Basin (HRB) and then extracted extreme precipitation events based on precipitation amount and precipitation intensity. The results show that extreme precipitation in the HRB has an increasing trend after 2000, although the increasing trend is not obvious, and the uncertainty of the occurrence of extreme precipitation events had increased. Extreme precipitation mainly had a strong correlation with the surface air temperature in the North Pacific, Indian Ocean, and Qinghai–Tibet Plateau. The El Niño year and the year of abnormal circulation contribute to the production of extreme precipitation in the HRB. In the years when extremely heavy precipitation occurred in the HRB, the subtropical high was northerly. Although most of the water vapor is brought from the Pacific by the East Asian monsoon, the water vapor that causes extreme precipitation in the HRB mainly comes from the Indian Ocean. Through multivariate wavelet coherence (MWC) analysis, annual precipitation is greatly affected by multiple climate variables, while extreme precipitation is greatly affected by a single climate variable. This study provides an important reference for the analysis and prediction of extreme precipitation. [ABSTRACT FROM AUTHOR]

In this paper, the spatial and temporal characteristics of convective precipitation (CP) and large-scale precipitation (LSP) in southern China during 1980–2020 are analyzed using monthly mean precipitation data from MERRA-2. In addition, the possible effects of relative humidity on CP and LSP are explored. The results indicate the following. (1) The LSP dominates the proportion of total precipitation (TP). Both LSP and CP are more prevalent in the south and less prevalent in the north, but there is a difference in the regions of their maximum centers. (2) Significant interannual and seasonal variations are observed in precipitation. TP and LSP tended to be higher than average after the 1990s, while for the CP, a significant negative trend has dominated the past ten years. There are significant increasing trends for TP and LSP, with area-averaged linear trends of 78.1 mm/decade and 85.9 mm/decade, respectively, while that of CP is − 17.1 mm/decade. The increasing trends of LSP are mainly contributed by the precipitation of summer and autumn. (3) The variations of LSP are affected by relative humidity in the troposphere, while CP is only influenced by the changes in relative humidity due to air temperature or specific humidity. The trend of relative humidity is − 0.33%/decade, mainly due to rising temperature in the troposphere. (4) Changes in relative humidity caused by temperature or specific humidity alone act on large-scale precipitation through both interannual and interdecadal processes, causing large-scale precipitation to increase, and the convective precipitation is mainly affected by the interdecadal processes. [ABSTRACT FROM AUTHOR]

The deep blue sky is an indicator of a lower concentration of aerosols and a cloudless sky. With increasing human emissions, a trend towards days with fewer deep blue skies might indicate a decline in a good living environment for humans. This study investigates the long-term changes of the deep blue sky in China from 1980 to 2018. Due to a lack of direct measurements, we use atmospheric visibility and low cloud cover to classify blue sky days into three grades: light blue day, medium blue day, and deep blue day. Climatologically, annual deep blue days increase from southeast China to northwest China, with the maximum number in Xinjiang and eastern Inner Mongolia and the minimum number in western Qinghai and southern Hebei. From 1980 to 2018, annual deep blue days show a prominent decreasing trend in most of China, with area-mean annual deep blue days decreasing by −0.48 days per year (d/y) in China, and the variation becomes more obvious after 2013. The maximum decreasing trend is observed in eastern China. The most prominent decreases of deep blue days are seen in winter. Both air pollution and the change in meteorological conditions contribute to the decrease of wintertime deep blue days in China. Specifically, the decrease in surface wind speed hinders the cleaning of air by winds, the increase in surface air temperature, and decrease in relative humidity is favorable for low cloud increase, and the increasing emission of pollution reduces atmospheric visibility. [ABSTRACT FROM AUTHOR]

As an intrinsic feature of daily surface air temperature (SAT) variability found in station measurements, temporal asymmetry (TA) can be taken as an evaluation metric to access the quality of SAT re-analysis product. In this study, TA calculated from four SAT variables, i.e., daily mean SAT (Tmean), daily maximum SAT (Tmax), daily minimum SAT (Tmin) and diurnal temperature range (TDTR = Tmax − Tmin), is applied to evaluate synoptic-scale performance of four reanalysis products (NCEP-2, JRA-55, ERA-I, and ERA-5) over China. The results show that four re-analyses overall overestimate the TA of daily Tmax and Tmin variability over China, but with a comparatively consistent estimated TA for Tmean. Moreover, the TA of Tmean variability for these four re-analyses shares high spatial consistency with those from the observation. However, four re-analyses own the similar region-dependent spatial patterns of overestimated TA for Tmax and Tmin variability, especially for Tmax. Since high TA is an indicator for strong nonlinear feature, only Tmean reanalysis is the most suitable to explore synoptic-scale extreme events, such as heat waves and cold waves, which are highly related to the strong nonlinear processes. [ABSTRACT FROM AUTHOR]

Here we investigate the key features of early and late South China Sea summer monsoon (SCSSM) onset. To carry out the investigation, we select five extreme early and nine extreme late onset years (14 days or more, before and after the normal onset date are considered "late" and "early" onset years, respectively). Since the mean SCSSM onset occurs in May, we analyze the changes in composite mean meteorological fields during May. Next, we examine the differences in daily evolution (from 10 to 2 days before the onset) of various vital variables between the early and late SCSSM onset years. We demonstrate that during the early SCSSM onset years, surface air temperature (SAT) is warmer over the North Pacific Ocean, South China Sea (SCS), and Northern China, which gradually extend towards East Asia. These SAT anomalies over Northern China, East Asia, and SCS are due to the advection of warm anomalies from the North Pacific Ocean. Consequently, a dipole-like sea level pressure (SLP) pattern had developed, with lower SLP over East Asia, Northern China, SCS, and North Pacific Ocean, and higher SLP over the Indian Ocean. It subsequently brought moisture-laden wind from the Indian Ocean towards SCS and East Asian landmass and is responsible for early SCSSM onset. [ABSTRACT FROM AUTHOR]

The uncertainty in trend estimates caused by temporal scale effect has rarely been studied. In response to this challenge, this study aims to explore temporal scale effects on trend detection based on in situ measurements throughout China given that they provide full temporal details of surface elements. Three common temporal scales (daily, monthly, and yearly) were used to present findings. Two different trend detection methods (i.e., simple linear regression and breaks for additive seasonal and trend) were employed to check the dependence of temporal scale effects on methods. It was found that temporal scale effects were dependent on the type of elements, the time span of datasets, and trend detection methods. They are more significant for elements with fast changes (e.g., snow depth) compared to those with gradual changes (e.g., albedo, air temperature). And temporal scale effects from daily to monthly scale are generally larger than those from monthly to yearly scale. The former is almost independent of trend detection methods, while the latter shows a clear dependence (i.e., dealing with seasonality or not). Trend estimates of surface albedo and longwave net radiation are mainly affected by temporal scale effects, while those of snow depth, shortwave net radiation, and air temperature are affected by both temporal scale effects and the choice of trend detection methods. The feedbacks between these elements show a clear dependence on temporal scale, which are generally stronger on monthly scale but weaker on yearly scale. [ABSTRACT FROM AUTHOR]

The variability of air temperature extremes exerts a great influence on agricultural production and the global hydrologic cycle. It has been the focus of attention for the past several decades. Using observed surface air temperature from 192 meteorological stations in South China maintained by the China Meteorological Administration, this study computed and analyzed 10 extreme temperature indices and the mean temperature at multiple spatiotemporal scales for the period from 1961 to 2018. These indices were analyzed with particular reference to the growing season of rice. Results showed that the variation trends of all annual indices exhibited different north–south patterns across decades, and the most recent 20-year period experienced greater warming than previous periods. The regional averaged rates of the annual mean maximum temperature, the annual mean minimum temperature, summer days, and tropical nights were 0.163 °C decade−1, 0.197 °C decade−1, 1.2 days decade−1, and 5.4 days decade−1, respectively. Except for the month of April, the southern region mostly experienced stronger warming than the northern region, especially in summer and autumn. Nighttime warming was usually greater than daytime warming, especially in June and October. Most temperature indices showed very weak correlations with large-scale atmospheric oscillations. [ABSTRACT FROM AUTHOR]

The Arctic polar vortex (APV) system plays an important role in controlling winter and spring atmospheric circulation pattern in China. Here, we evaluate the anomalous APV-induced spring vegetation variability and lagged productivity responses in China. We found that both strong and weak APV conditions have almost equally negative impacts on spring vegetation growth in China, e.g., negative NDVI anomalies occurred in 48.6 and 53.2% of China's vegetated areas under strong and weak APV conditions, respectively. However, large seasonal compensation effects were associated with weak APV conditions, and beneficial lagged vegetation productivity responses occurred in 67.2% of China's vegetated areas, whereas adverse responses occurred in only 32.8% of vegetated areas. Under a strong APV, adverse lagged vegetation productivity responses occurred in 54.5% of China's vegetated areas, whereas beneficial responses occurred in only 45.5% of vegetated areas. The temperature, precipitation, and solar radiation changes caused by anomalous APV-induced changes in circulation patterns are the main reasons for spring vegetation variability. The lagged vegetation productivity responses were attributed to anomalous APV-related precipitation and air temperature anomalies in the following summer and autumn. This improved understanding of the strong links between APV anomalies and vegetation dynamics in China should facilitate early warning of vegetation productivity reductions under anomalous APV conditions. [ABSTRACT FROM AUTHOR]

In this study, a stepwise-clustered statistical downscaling model is established to simulate future apparent temperatures based on NCEP reanalysis data and four global climate models (GCMs). AP is a metric used to quantify thermal comfort or discomfort. The model can express nonlinear relationships between variables at large scale and local scale. The model is employed for projecting future apparent temperature changes over the Pearl River Delta (PRD), on the south coast of China, under three representative concentration pathways (RCP) scenarios. The cluster tree generated for the daily apparent temperature is calibrated for the period 1971–1990 and validated for the period 1991–2000. The R2 values obtained for the validation period at eight selected cities for four GCMs (i.e., CanESM2, CNRM-CM5, CSIRO-Mk3-6-0, and IPSL-CM5A-LR) are 0.88, 0.87, 0.86, and 0.87, respectively. The results reflected that apparent temperature is projected to have a constant increment over the PRD in the future period (2035–2095). Moreover, the monthly apparent temperature in April has the largest expected increment in the future period, while the smallest increment is found in January. The results also indicated that the apparent temperature increases faster than the air temperature under the RCP4.5 and the RCP8.5 scenarios in the PRD. The findings illuminate that the expected increase in apparent temperature over the PRD can be mainly explained by increasing air temperatures and decreasing wind speeds. The results can provide decision makers with useful information for urban health risk assessments. [ABSTRACT FROM AUTHOR]

Based on the latest series of homogenized ground surface temperature (GST) and surface air temperature (SAT) data for China, this study performed a detailed analysis of the trend of the differences between the two homogenized series in 1961–2016. The differences, referred to as surface–air temperature differences (SATDs) in this study, were separately averaged by month, season, and year. The long-term and spatial changes in the trends of SATDs were investigated. Moreover, interdecadal trend breakpoints were identified to understand the characteristics of trends in fluctuation. The possible influences of precipitation, Pacific Decadal Oscillation (PDO), and global warming on SATDs were also analyzed. The results showed that during the 12 months of a year, only three months, March, April, and May, exhibited increasing trends of station-averaged, monthly mean SATDs while the other nine months exhibited decreasing trends. In addition, the station-averaged annual and seasonal mean SATDs of summer, autumn, and winter all showed significant decreasing trends, while the spring mean SATDs showed a significant increasing trend. The spatial distribution pattern of the linear trends of monthly, seasonal, and annual SATDs in meteorological stations indicated that SATDs had more obviously increasing trends in the northern regions than the southern regions of China. The trends of station-averaged monthly mean SATDs (except for April) and station-averaged seasonal and annual mean SATDs experienced interdecadal breakpoints, fully indicative of obvious interdecadal fluctuations with temporal complexity among China's SATD trends. By the regression analysis of monthly STADs against simultaneous precipitation, as well as the comparative analysis of their linear trends, we found that both amount of precipitation and the change of precipitation type have important influences on SATDs. The results of convergent cross mapping analysis also revealed the causal effect of precipitation on SATDs. [ABSTRACT FROM AUTHOR]

In this paper, by using forecasts of the highest and lowest daily surface air temperatures from the Coupled Forecast System version 2 (CFSv2) over a period of 9 months, NCEP/DOE reanalysis data from the National Centers for Environmental Prediction (NCEP), and data from the U.S. NOAA Climate Prediction Center (CPC), three cold waves are identified during 2015–2016 in China, and the CFSv2 forecasts of these cold waves are evaluated. The results show that the high-resolution CPC data and the low-resolution NCEP/DOE data both very clearly show the temperature drops and temperature anomalies of these cold waves. The earlier the forecast lead time is, the greater the errors in the beginning and ending dates of the cold waves between the CFSv2 forecasts and the observations; there are errors of 1–2 days in the durations of the cold waves between the CFSv2 forecasts and the observations. CFSv2 exhibits certain abilities to forecast the overall temperature drops and temperature anomalies of cold waves at forecast lead times of 0, 5, 10, and 15 days, but the CFSv2 prediction ability is poor at forecast lead times exceeding 20 days. CFSv2 can predict the spatial distribution of temperature drops better than it can predict that of temperature anomalies, but the absolute errors in the observed temperature drops are greater than those in the observed temperature anomalies. The temperature drops from the CFSv2 forecasts are obviously underestimated in North China, South China, and their nearby areas but overestimated in Mongolia and Northeast China. The temperature anomalies from the CFSv2 forecasts are obviously underestimated in the inland areas of China but overestimated in the surrounding oceans and adjacent coastal areas. The difference fields at forecast lead times of 0 and 30 days are basically the same, but the absolute values of the differences increase with increases in the forecast lead time (with a few exceptions). [ABSTRACT FROM AUTHOR]

Against the background of global warming, the climatic suitability for growing usual crops has been changing in certain regions. In this study, we focused on the Ningxia Plain in China, an important wine grape (Vitis vinifera L.) growing region. Based on the daily average air temperature data from 1981 to 2017, we investigated changes in the planting boundaries of different climate zones for wine grape before and after 1997 (when an abrupt change in regional air temperature occurred). The goal of this study is to provide scientific evidence for local agricultural authorities to make long-term climate change adaptation plans. We used the effective accumulated temperature as an indicator to evaluate the inter-decadal changes in the climate zones for wine grape. We concluded as follows: (1) since the abrupt change in regional air temperature in 1997, the subtotal area of climate zone I for wine grape was reduced by 31%, while the subtotal area of climate zone II (moved southward) and III (part of climate zone II in the northern part of the region turned into climate zone III) for wine grape was expanded by 7% and 24%, respectively; (2) during the 1990s, climate zone III for wine grape emerged in the study region; during the 2000s, the planting boundaries of climate zone II and III moved southward; during the period of 2011–2017, climate zone I (suitable) for wine grape mostly vanished in the Ningxia Plain; and (3) since the abrupt change in regional air temperature in 1997, most of the area in the Eastern Foothills of the Helan Mountains turned from climate zone II to climate zone III for wine grape, with the exceptions of Hongsipu district and the relatively high altitude area. During the 37 study years, most of the area in the study region remained as climate zone II for wine grape with a probability of 80%. Overall, the climate zones for wine grape in Ningxia, China have changed against the background of global warming. In particular, the wine grape varieties and wine types are expected to be changed in the Helan Mountains area in order to adapt to the ongoing climate change. [ABSTRACT FROM AUTHOR]

Soil water content (SWC) and soil temperature (ST) are important properties in water-energy balance processes. Our objective was to analyze the SWC and ST variations at different soil depths (0–10, 10–40, 40–100, and 100–200 cm) and different timescales (daily, monthly, and annual) affected by precipitation and air temperature at seven sub-regions and entire mainland China. The sine function was used to fit the variations of daily and monthly ST. The results showed that the monthly and annual SWC and ST values were relatively low in northwest China and the alpine region of Qinghai-Tibetan plateau; however, higher values were shown in east China. SWC and ST fluctuated both randomly and periodically, especially at the 0–10 cm depth. The daily and monthly ST had regular time-lags and typical periodical changes, which could be fitted by a sine function for both the grids and sub-regions in China with a coefficient of determination (R2) of 0.855. Further, the correlations between SWC and precipitation were good in southern and northeastern China, but poor in northwestern China and Qinghai-Tibet Plateau at the depths < 40 cm. The correlations between ST and AT within the depths < 100 cm were generally good (R2 > 0.76). In conclusion, the spatiotemporal distribution of SWC and ST was greatly affected by precipitation and air temperature. The fitted sine functions for daily and monthly ST are very useful for elementary determination of the long-term mean ST values for a location. [ABSTRACT FROM AUTHOR]

Fully and accurately studying temperature variations in montane areas are conducive to a better understanding of climate modeling and climate-growth relationships on regional scales. To explore the spatio-temporal changes in air and soil temperatures and their relationship in montane areas, on-site monitoring over 2 years (2015 and 2016) was conducted at nine different elevations from 2040 to 2740 m a.s.l. on Luya Mountain in the semiarid region of China. The results showed that the annual mean of air temperature lapse rate (ATLR) was 0.67 °C/100 m. ATLR varied obviously in different months within a range of 0.57~0.79 °C/100 m. The annual mean of the soil temperature lapse rate (STLR) was 0.48 °C/100 m. Seasonally, monthly mean soil temperature did not show a consistent pattern with regard to elevation. The relationships between air and soil temperatures showed piecewise changes. Soil was decoupled from the air temperature in cold winter and early spring. The parameters of the growing season based on the two temperature types had no corresponding relations, and seasonal mean of soil temperature showed the smallest value at mid-elevation rather than in the treeline ecotone. Based on these changes, our results emphasized that altitudinal and seasonal variability caused by local factors (such as snow cover and soil moisture) should be taken into full consideration in microclimate extrapolation and treeline prediction in montane areas, especially in relation to soil temperature. [ABSTRACT FROM AUTHOR]

Evapotranspiration (ETa) and gross primary productivity (GPP) are two of the key flux indices in a basin system. This study investigated the evolutions of ETa and GPP and the contributions of climate variables and vegetation index over multiple land cover types, simulated by the VIP model (Vegetation Interfaces Processes, RS version) with Terra-Modis 250 m Normalized Difference Vegetation Index (NDVI) dataset in the Ziya-Daqing basins (ZDB), China, during 2001–2015. The nonparametric Mann-Kendall test was used to analyze the changes in ETa and GPP. Contributions to the variations of ETa and GPP were explored using a differential equation method. The analyses revealed that ETa and GPP were high in the eastern plain, and spatial distributions were mainly associated with distributions of the major land-cover types. ETa and GPP showed positive trends in the western Taihang Mountains and negative trends in the eastern plain region. The annual ETa and GPP increased from 2001 to 2015 in most land-use types except cropland and urban. The decreases in ETa and GPP were primarily attributed to solar dimming in cropland and urban. The increases in ETa and GPP mainly occurred in the natural land-cover types (e.g., mixed forest and grassland) as a tradeoff between the positive effect of greening and the negative effect of declined radiation. In ZDB, the contributions of net radiation, air temperature, wind speed, and leaf area index to the change in ETa were − 0.681%, − 0.379%, − 0.032%, and 1.442%, respectively. The contributions of net short-wave radiation, air temperature, relative humidity, and fraction of photosynthetically active radiation to the change in GPP were − 2.411%, 0.085%, − 0.020%, and 10.224%, respectively. Thus, the "greening" was the major reason for ETa and GPP increases in natural vegetations, whereas solar dimming was the major reason for ETa and GPP decreases in cropland. [ABSTRACT FROM AUTHOR]

When meteorological stations are quite unevenly distributed, a simple regional arithmetic mean of observation data may assign an excessive weight to one region with dense stations, which affects the representativeness of the regional mean. In this study, we used the homogenized monthly maximum (Tmax), mean (Tm), and minimum (Tmin) temperature dataset at more than 2400 national surface meteorological stations in China. Based on a thin plate spline (TPS) interpolation method, we selected a three-dimensional (longitude, latitude, and elevation above sea level) interpolation model that is suitable for the temperature curve surface fitting in China, and constructed a gridded temperature dataset with a horizontal resolution of 0.5° during 1961 to 2015. Cross-validation indicates that the annual average of generalized cross-validation (GCV) is relatively small, and the ratio of GCV to the observed temperature is relatively low. Both the root of GCV and the root-mean-square error of temperature are smaller than those of the previous temperature gridded products. A comparison between our dataset and the Climate Research Unit (CRU) TS4.02 dataset indicates that the CRU's data overestimate the warming trend in China during 1961–1984, whereas underestimate the warming trend during 1985–2015. [ABSTRACT FROM AUTHOR]

Over the hinterland of the Taklimakan Desert (TD), the diurnal and seasonal cycles of the air temperature (AT) and horizontal sand-dust flux (HSDF) were investigated, based on in situ data including sand saltation counts and meteorological parameters in the period 2008–2010. In particular, the relationship between AT and HSDF was determined. It was found that 74.7% of HSDF was observed between 10:00 and 20:00, and HSDF in spring and summer accounted for 92.3% of the annual flux. Further, the diurnal and annual cycles of HSDF and AT presented an exponential distribution, with correlation coefficients (R) of 0.97 and 0.93, respectively. Additionally, when AT was 0 °C or lower, the frequency of sand saltation was only 4.3%. The maximum sand saltation frequency was 70.1%, which occurred at 33–34 °C, while 67.6% of the total HSDF occurred at 24–34 °C. Finally, a Gauss equation was established over the TD: Q = 250.2 + 1368.5e−2 × [(T−30.8)/7.3]^2, with R = 0.90. Results revealed a strong correlation between HSDF and AT, indicating that AT should be noticeable in HSDF parameterization schemes. [ABSTRACT FROM AUTHOR]

Spatiotemporal changes of temperature and precipitation extremes from 1956 to 2015 were analyzed at 200 representative weather stations evenly distributed in the temperate continental zone (TCZ), temperate monsoon zone (TMZ), mountain plateau zone (MPZ), and (sub) tropical monsoon zone (SMZ) of China, using 16 extreme temperature and 11 extreme precipitation indexes. The results showed that warm days (TX90p) and warm nights (TN90p) increased significantly, while cool days (TX10p) and cool nights (TN10p) decreased significantly in the whole China. Overall increasing trends were found for maximum and minimum daily maximum temperature (TXx and TXn) and maximum and minimum daily minimum temperature (TNx and TNn). Warm indexes, including summer days (SU25), tropical nights (TR20), warm spell duration indicator (WSDI), and growing season length (GSL), showed increasing trends, whereas cold indexes such as frost days (FD0), ice days (ID0), cold spell duration indicator (CSDI), and diurnal temperature range (DTR) showed decreasing trends. These extreme temperature indexes exhibited high correlations with mean air temperature. MPZ exhibited the most remarkable change magnitudes among the four zones, while the smallest changes occurred in SMZ. An accelerating warming trend was particularly observed since 1986. Nationally, only daily rainfall intensity (SDII) showed significantly increasing trends, while the increasing trends of other precipitation indexes were not significant. Apart from consecutive wet days (CWD), changes of precipitation extremes presented increasing trends. PRCPTOT and R10mm exhibited the highest correlation coefficient across contrasting climatic zones. Regionally averaged precipitation totals were decreasing in TMZ during 1956–1985, but increasing trends were identified after 1985. The upward tendency of precipitation totals in MPZ and the west part of TCZ may alleviate the pressure of water shortage in arid and semi-arid regions of China, but the upward trend in SMZ, especially in the coastal areas of southeastern China, may aggravate the risk of flood-induced disasters in these regions. [ABSTRACT FROM AUTHOR]

Soil moisture (SM) feedback on climate variables especially temperature is an important aspect in land-atmosphere coupling. Based on the Global Land Data Assimilation System (GLDAS) V2.0 SM data and the gridded observational temperature data, we statistically analyze the thermal feedback of SM over North China (NC). The results show that SM exerts a decreasing trend under the background of evident warming over NC, inducing a decadal enhancement of SM feedbacks on the local temperature and extreme hot events. The SM feedback contributes 6% of the total air temperature variation during 1961–2012, while it reaches 36% after the regional warming during 1994–2012. Such SM affecting temperature is mainly reflected in its feedback on daily maximum temperature, which is also intensified during the warm period. The decadal intensification is also found in the feedback of SM on hot extremes. Further analyses show that the abnormal changes of the latent and sensible heat fluxes caused by the SM anomaly are the main reasons that affect the thermal conditions. Besides, the rising Bowen ratio indicates that upward thermal transfer on the land surface is enhanced in recent years, which suggests that the atmosphere is more sensible to the abnormal heating on the ground. This consequently translates into the decadal intensification of the local thermal feedback of SM in summer over NC. [ABSTRACT FROM AUTHOR]

Air temperature and vapor pressure are both considered important factors affecting thermal comfort during summer. However, their variability contributes differently to the comfort level. Based on daily observations over a 56-year period (1961–2016), this study used the Mann–Kendall (MK) test and Theil–Sen's estimator to examine the trends in summer air temperature and vapor pressure for 648 stations across China. Geographic information system (GIS) grouping analysis was applied to understand the spatial pattern of their changes. Further, based on the assumption of constant wind speed and mean radiant temperature equal to air temperature, the responses of summer daily mean Universal Thermal Comfort Index (UTCI) and the number of summer days with "no thermal stress" to changes in summer air temperature and vapor pressure were investigated. Sensitivity analysis was carried out to identify the areas where UTCI is more sensitive to air temperature and vapor pressure changes. Comparison of the contributions of air temperature and vapor pressure was made to understand the different roles they have played in the changes of UTCI. The results show that approximately 70% of the stations show significant increases in summer air temperature and 33% of the stations show upward trends in summer vapor pressure. As a consequence of the increasing UTCI throughout most of the country, the number of "no thermal stress" days dropped sharply in many areas with an exception of the Tibetan Plateau where this number rose by an average of 0.05 days per year during the study period. Sensitivity analysis shows that summer UTCI is much more sensitive to a unit change of air temperature than that of vapor pressure. However, due to its substantial changes in some regions, including Northwest and Northeast China, the middle and lower reaches of Yangtze River, vapor pressure also played an important role in either intensifying or mitigating the thermal stress in summer. [ABSTRACT FROM AUTHOR]

The Qinghai Lake is the largest saltwater lake in the Tibetan Plateau and in mainland China. Effects of the lake on surface climate of the coastal areas, however, are not well understood. This article utilizes hourly observation data of warm season from 17 automatic weather stations to analyze the diurnal and seasonal variations in air temperature in different coastal zones of the Qinghai Lake. The EOS/MODIS data was also used to analyze the surface temperature differences between the lake and its surrounding areas. The results show a few unique characteristics of the plateau lake: (1) based on the satellite data, lake surface temperature is lower than its surrounding areas (4.9~25.1 °C and 12.2~35.6 °C respectively) in the daytime, while it is obviously higher than that in the surrounding areas (1.9~10.5 °C and − 13.1~6.3 °C respectively) at the nighttime. Daily mean water surface temperature is higher than that in the surrounding areas, which is 7.8~17.9 °C and − 2.6~17.9 °C respectively; (2) based on data of meteorological stations, coastal zones closer to the shoreline have a higher air temperature during the warm season largely due to the much warmer nighttime near the shoreline than those in deep inland zones. For the on-shore, near-shore, and far-shore zones, mean daytime air temperature is 8.7~9.6 °C, 9.5~11.1 °C, and 10.0~10.7 °C, respectively, and the mean nighttime air temperature is 2.9~4.1 °C, 1.3~12.3 °C, and − 0.2~0.4 °C respectively. The hourly mean diurnal temperature range (DTR) increases with distance to the shoreline, which is 8.6 °C, 10.9 °C, and 12.3 °C in the on-shore, near-shore, and far-shore zones respectively; (3) differences between maximum and minimum 5-day mean daily maximum (minimum) air temperature during the warm season are 20.3 °C (23.3 °C), 21.7 °C (25.6 °C), and 22.6 °C (26.7 °C) for the on-shore, near-shore, and far-shore zones, respectively, indicating an asymmetrical effect on daytime and nighttime air temperature in the on-shore zone; (4) daily maximum air temperature of the on-shore zone is lower before early October, but it is slightly higher afterward and occurs later; (5) daily minimum air temperature of the on-shore zone is on average higher than that of the far-shore zone, especially after the mid-September, and it also appears later in autumn than in summer. [ABSTRACT FROM AUTHOR]

In this study, we investigate spatial differences in thermal comfort conditions using the net effective temperature (NET) considering the synthetic effects of air temperature, relative humidity, and wind speed. Using a daily-scale dataset of maximum air temperature (Tmax), relative humidity, and wind speed from 518 stations during 1960–2016 across China, we analyze the influence of different climate conditions on NET or Tmax at three different levels of hot conditions (35 °C < Tmax < 37 °C, NETTmax35 for HT35 cases; 37 °C < Tmax < 40 °C, NETTmax37 for HT37 cases; NET = 27 °C, NET27 cases). In HT35 (HT37) cases, NETTmax35 (NETTmax37) can reach up to 32 °C (34 °C) in southern China and also can be less than 29 °C (31 °C) in western Northwest China. In NET27 cases as the threshold for the thermal sensation of very hot, Tmax should be over 33 °C in western Northwest China and was less than 30.5 °C in southern China, by contrast. With global warming, there is an increasing trend in the number of extreme hot days in most part of China, but a decreasing trend is detected in the part of Jianghuai region, partly due to the decreasing trend in Tmax. [ABSTRACT FROM AUTHOR]

Gridded climatic datasets with fine spatial resolution can potentially be used to depict the climatic characteristics across the complex topography of China. In this study, we collected records of monthly temperature at 1153 stations and precipitation at 1202 stations in China and neighboring countries to construct a monthly climate dataset in China with a 0.025° resolution (~ 2.5 km). The dataset, named LZU0025, was designed by Lanzhou University and used a partial thin plate smoothing method embedded in the ANUSPLIN software. The accuracy of LZU0025 was evaluated based on three aspects: (1) Diagnostic statistics from the surface fitting model during 1951–2011. The results indicate a low mean square root of generalized cross validation (RTGCV) for the monthly air temperature surface (1.06 °C) and monthly precipitation surface (1.97 mm1/2). The method used variable square root transformation for the spline surface fitting to reduce positive skewness in the measured precipitation values and no variable transformation in air temperature case. This indicates that the surface fitting models are accurate. (2) Error statistics of comparisons between interpolated monthly LZU0025 with the withholding of climatic data from 265 stations during 1951–2011. The results show that the predicted values closely tracked the real true values with values of mean absolute error (MAE) of 0.59 °C and 70.5 mm and standard deviation of the mean error (STD) of 1.27 °C and 122.6 mm. In addition, the monthly STDs exhibited a consistent pattern of variation with RTGCV. (3) Comparison with other datasets. This was done in two ways. The first was via comparison of standard deviation, mean, and time trend derived from all datasets to a reference dataset released by the China Meteorological Administration (CMA), using Taylor diagrams. The second was to compare LZU0025 with the station dataset in the Tibetan Plateau. Taylor diagrams show that the standard deviation derived from LZU had a higher correlation with that produced by the CMA (R = 0.76 for air temperature, and R = 0.96 for precipitation) compared to those from other datasets. The standard deviation for the index derived from LZU was more close to that induced from CMA, and the centered normalized root-mean-square difference for this index derived from LZU and CMA was lower. A similar superior performance of LZU was found in the comparison of mean and time trend derived from LZU and those from other datasets. LZU0025 had high correlation with the Coordinated Energy and Water Cycle Observation Project (CEOP)—Asian Monsoon Project (CAMP) Tibet surface meteorology station dataset for air temperature, despite a non-significant correlation for precipitation at a few stations. Based on this comprehensive analysis, we conclude that LZU0025 is a reliable dataset. LZU0025, which has a fine resolution, can be used to identify a greater number of climate types, such as tundra and subpolar continental, along the Himalayan Mountain. We anticipate that LZU0025 can be used for the monitoring of regional climate change and precision agriculture modulation under global climate change. [ABSTRACT FROM AUTHOR]

Previous studies indicate that vegetation and lakes in arid and semi-arid regions are closely related to climate change. However, the responses of vegetation and lakes to climate-related variables have rarely been contrastively studied. The Hulun Lake (HLL) and its surrounding grasslands in Northeast Inner Mongolia of China comprise a semi-arid region that has experienced intense climate change over the last several decades. This study aims to understand the key factors that control the variations in the lake area and vegetation cover over the last five decades in the HLL region, as well as contrastively investigate the different responses of the lake area and vegetation cover to climate-related variables. Analysis results indicate that the variations with increasing change rates in the HLL area were mainly controlled by precipitation fluctuation. Moreover, an increase or decrease in the air temperature and relative humidity could affect the response time of the HLL area to the change in precipitation. The Normalized Difference Vegetation Index (NDVI) variations from 1990 to 1999 around the HLL region were mainly controlled by the intense local grazing rather than climatic restrictions. The fluctuation in NDVI after 1999 reflects the response of the vegetation cover to climatic change. The correlation analysis shows that the variations in the HLL area were closely related to the multi-year tendency of precipitation amount and to the Standardized Precipitation Evapotranspiration Index (SPEI) with a long timescale. However, NDVI is sensitive to changes in short-term precipitation amount, such as seasonal precipitation, and in SPEI with a monthly timescale. The soil moisture at shallow depths (< 0.1 m) was the key root–zone soil moisture that could influence NDVI, whereas soil moisture at depths of 0.4 to 1.0 m and the HLL area were closely related and had similar responses to climatic change. [ABSTRACT FROM AUTHOR]

Long-term climate memory is ubiquitous in climate systems, but its contribution to climate prediction has not been assessed systematically. We used an integral fractional statistical model (FISM) to quantify climate memories in different variables over China. Their contributions to climate prediction were estimated using explained variances. We found different climate memory effects for different variables in different regions. The contribution of climate memory to climate variability is stronger in temperature than in precipitation records. For temperatures (including both air temperature and land temperature), the average variance explained by climate memory is around 3∼4%. For precipitation, the average explained variance was 0.6%. The low values for explained variances indicate that, on average, the contributions of climate memory to temperature and precipitation predictions are small. But in specific regions, higher climate memory effects may occur. For precipitation, climate memory can contribute 3% of the variance in southeast China. For temperature, climate memory can explain ≥ 10% of the variance in northeast and southwest China, which is not low and should be considered in prediction. Therefore, for more accurate climate prediction, we suggest first determining the contribution of climate memory. For variables or regions with strong climate memory effects, a scheme considering climate memory effects may help improve future climate predictions. [ABSTRACT FROM AUTHOR]

It has been confirmed that the karst rocky desertification (KRD) has severely changed the interactions between atmosphere and terrestrial ecosystem which would cause a significant effect on regional climate system. In this study, the Weather and Research Forecasting model was applied to investigate the biogeophysical impact on temperature and precipitation change by land use/land cover change data with different KRD conditions in 1993, 2003, and 2013 in Southwest China. The results showed that an improving trend of KRD has been found in Southwest China, especially in east Sichuan, Chungking, southwest Yunnan, and south Guangxi. The 2-m air temperature decreased by 0~− 1 °C in general with this improving trend. The possible reason was the decreasing KRD accompanied by the decreasing albedo, causing the increasing net shortwave radiation and the increasing net radiation. Meanwhile, the increasing evaporation strengthened the latent heat flux and weakened the sensible heat flux so that decreased temperature was addressed in forest areas. The effect of KRD change transferred to the upper troposphere through atmosphere vertical convection, which made the subtropical high to be strengthened and westerly extended. Therefore, the upward moisture flux at the surface (QFX) was weakened in the central part of Guangxi, southern Guizhou, which led to the decrease of the precipitation. Moreover, the southwest monsoon was strengthened, which caused the increasing water vapor flux and led to the heavy rainfall in the west of Yunnan. [ABSTRACT FROM AUTHOR]

Using multiple datasets, including three grid datasets (ERA-Interim, WFDEI, and SURF) and one station dataset, we analyzed the climatological distributions and trends of daily maximum air temperature (DMAT) and number of heat days (NHD) over China from 1979 to 2012. In general, all the three grid datasets show the highest climatological DMAT and NHD values in Xinjiang and southeast China, and increasing trends of DMAT and NHD in most of China. Nevertheless, both the climatological condition and trend exhibit differences in detail among the three grid datasets. Using the observed grid dataset (SURF) as a reference, the results show that the WFDEI dataset is closer to SURF than ERA-Interim in characterizing climatological features of DMAT and NHD, and the values from ERA-Interim dataset are lower than the SURF in most part of China. Since the trends of NHD in WFDEI are smaller than those in the other two grid datasets, especially in the middle and lower beaches of the Yangtze River, ERA-Interim is better than WFDEI in representing the trends of NHD. In four regions: Chuanyu, Huanghuai, Xinjiang, and Southeast where the NHD occurs frequently and increases rapidly, the WFDEI is more reliable than ERA-Interim due to the fact that the changes of regional NHD in WFDEI are more consistent with those in observed datasets. Because there exist biases in the records of DMAT between the ERA-interim and WFDEI, it is better to adopt percentile index than absolute threshold to study the changes of China extreme air temperature when using reanalysis datasets. [ABSTRACT FROM AUTHOR]

Lapse rates of near-surface (2 m) air temperature are important parameters in hydrologic and climate simulations, especially for the mountainous areas without enough in-situ observations. In Xinjiang, northwestern China, the elevations range from higher than 7000 m to lower than sea level, but the existing long-term meteorological measurements are limited and distributed unevenly. To calculate lapse rates in Xinjiang, the daily data of near-surface air temperature (Tmin, Tave, and Tmax) were measured by automatic weather stations from 2012 to 2014. All the in situ observation stations were gridded into a network of 1.5° (latitude) by 1.5° (longitude), and the spatial distribution and the daily, monthly, seasonal variations of lapse rates for Tmin, Tave, and Tmax in Xinjiang are analyzed. The Urumqi River Basin has been considered as a case to study the influence of elevation, aspect, and the wet and dry air conditions to the Tmin, Tave, and Tmax lapse rates. Results show that (1) the lapse rates for Tmin, Tave, and Tmax vary spatially during the observation period. The spatial diversity of Tmin lapse rates is larger than that of Tave, and that of Tmax is the smallest. For each season, Tmax lapse rates have more negative values than Tave lapse rates which are steeper than Tmin lapse rates. The weakest spatial diversity usually appears in July throughout a year. (2) The comparison for the three subregions (North, Middle, and South region) exhibits that lapse rates have similar day-to-day and month-to-month characteristics which present shallower values in winter months and steeper values in summer months. The Tave lapse rates in North region are shallower than those in Middle and South region, and the steepest Tave lapse rates of the three regions all appear in April. Tmin lapse rates are shallower than Tmax lapse rates. The maximum medians of Tmin and Tmax lapse rates for each grid in the three regions all appear in January, whereas the minimum medians all concentrate in July. (3) The seasonality of Tmin, Tave, and Tmax in Xinjiang is also observed. An increasing trend from summer to winter and a decreasing trend from winter to next summer can be seen clearly. (4) The inversion phenomenon is obvious in the Urumqi River Basin and appears in March, November, December, January, and February. The great inversion phenomenon days (24 days) and persistent inversion phenomenon days (12 days) present in January. The influences of elevation and aspect are complex. Lapse rates for Tave, Tmin, and Tmax are steeper under humid air conditions, while dry air conditions lead to shallower lapse rates. [ABSTRACT FROM AUTHOR]

Precipitation diurnal cycle over Fujian in the pre-summer rainy season has been revealed based on the hourly rain gauge data during 2009-2013. The precipitation amount (PA) over northwestern Fujian and most southeast coasts shows relatively small diurnal variability. This is in contrast to large diurnal variations in the mountainous areas. Regional differences in precipitation diurnal cycles are obviously noted among the coastal, valley, hilly, and mountainous areas. The precipitation diurnal cycles are significantly affected by the terrain elevation and distance to coast, PA and precipitation frequency (PF) show much more pronounced double diurnal peaks with the terrain elevation and distance to coast increased. However, the precipitation intensity (PI) basically shows one distinct late afternoon diurnal peak for different elevations and distances to coast. Four typical patterns of precipitation diurnal cycle are further identified by cluster analysis. The four typical PF patterns show relatively apparent morning peaks over coasts, inland mountains, and hills in addition to distinct late afternoon maxima. Low PF with weak diurnal amplitude is mainly located over the coastal areas, while high PF with strong diurnal amplitude is found over the valley, hilly, and mountainous regions. The PA exhibits a weak early morning peak and a relatively strong late afternoon peak over coastal, hilly, or mountainous areas and windward slopes but only one distinct late afternoon peak over the valley regions and leeward slopes. The amplitude of PA diurnal cycle is the weakest over the coastal areas but the strongest over the valley regions or leeward slopes among the four PA patterns. The four PI diurnal cycle patterns consistently show distinct afternoon peaks. [ABSTRACT FROM AUTHOR]

Analyses of the variation characteristics for aridity index (AI) can further enhance the understanding of climate change and have effect on hydrology and agriculture. In this paper, based on the data of 283 standard meteorological stations, the temporal-spatial variations and the influences of climate factors on AI were investigated and the relationship between AI and two climate indices (the Arctic Oscillation (AO); El Nino-Southern Oscillation (ENSO)) were also assessed in northern China (NC) during the period from 1961 to 2012. The results revealed that the annual mean AI decreased at the rate of −0.031 per decade in the past 52 years and the trend was statistically significant at the 0.01 level. The Mann-Kendall (M-K) test presented that the percentages of stations with positive trends and negative trends for AI were 10 and 81.9 % (22.6 % statistically significant), respectively. Spatially, in the western part of 100° E, the extremely dry area declined and the climate tended to become wet obviously. In the eastern part of 100° E, dry area moved toward the east and the south, which resulted in the enhancement of semiarid area and the shrinkage of subhumid area. The contributions of sunshine duration and precipitation to the decline of AI are more than those of other meteorological variables in NC. Moreover, the average temperature has risen significantly and AI decreased in NC, which indicated the existence of 'paradox.' Relationship between climate indices (AO and ENSO) and AI demonstrated that the influence of ENSO on AI overweight the AO on AI in NC. [ABSTRACT FROM AUTHOR]

As a pivotal section of the Silk Road in northwest China, the Hexi Corridor is a popular tourist destination. In this study, the tourism climate conditions in this region were discussed using the Physiologically Equivalent Temperature (PET) and the Climate-Tourism/Transfer-information-Scheme (CTIS) from 1980 to 2012. Overall, cold or cool stress was prevalent in the area, and the optimal travel period was from May to September. With global warming, the annual numbers of cumulative days with relatively cold conditions decreased, and the annual numbers of cumulative days with comfortable and relatively hot conditions increased. Two typical stations, Wushaoling and Dunhuang, were compared and analysed for their tourism climate information according to the frequency of PET and CTIS conditions, respectively. In addition, regional variations in the tourism climate conditions based on geographic information systems (GIS) were investigated during the optimal travel period. [ABSTRACT FROM AUTHOR]

This study reveals the impacts of climatic variable trends on drought severity in Xinjiang, China. Four drought indices, including the self-calibrating Palmer drought severity index (sc-PDSI), Erinç's index ( I ), Sahin's index ( I ), and UNEP aridity index (AI), were used to compare drought severity. The ensemble empirical mode decomposition and the modified Mann-Kendall trend test were applied to analyze the nonlinear components and trends of the climatic variable and drought indices. Four and six climatic scenarios were generated in sc-PDSI, I , I , and AI with different combinations of the observed and detrended climatic variables, respectively. In Xinjiang, generally increasing trends in minimal, average, and maximal air temperature ( T , T , T ) and precipitation ( P) were found, whereas a decreasing trend in wind speed at 2 m height ( U ) was observed. There were significantly increasing trends in all of the four studied drought indices. Drought relief was more obvious in northern Xinjiang than in southern Xinjiang. The strong influences of increased P on drought relief and the weak influences of increased T , T , and T on drought aggravation were shown by comparing four drought indices under different climate scenarios. Decreased U had a weak influence on drought, as shown by the AI in different climate scenarios. The weak influences of T and U were considered to be masked by the strong influences of P on droughts. Droughts were expected to be more severe if P did not increase, but were likely milder without an increase in air temperature and with a decrease in U . [ABSTRACT FROM AUTHOR]

Global increases in duration and prevalence of droughts require detailed drought characterization at various spatial and temporal scales. In this study, drought severity in Xinjiang, China was investigated between 1961 and 2012. Using meteorological data from 55 weather stations, the UNEP (1993) index ( I ), Erinç's aridity index ( I ), and Sahin's aridity index ( I ) were calculated at the monthly and annual timescales and compared to the Penman-Monteith based standard precipitation evapotranspiration index (SPEI). Drought spatiotemporal variability was analyzed for north (NX), south (SX), and entire Xinjiang (EX). I could not be calculated at 51 stations in winter as T was below 0. At the monthly timescale, I , I , and I correlated poorly to SPEI because of seasonality and temporal variability, but annual I , I , and I correlated well with SPEI. Annual I , I , and I showed strong spatial variability. The 15 extreme droughts denoted by monthly SPEI occurred in NX but out of phase in SX. Annual precipitation, maximum temperature, and relative and specific humidity increased, while air pressure and potential evapotranspiration decreased over 1961-2012. The resulting increases in the four drought indices indicated that drought severity in Xinjiang decreased, because the local climate became warmer and wetter. [ABSTRACT FROM AUTHOR]

This study examines the sampling error uncertainties in the monthly surface air temperature (SAT) change in China over recent decades, focusing on the uncertainties of gridded data, national averages, and linear trends. Results indicate that large sampling error variances appear at the station-sparse area of northern and western China with the maximum value exceeding 2.0 K while small sampling error variances are found at the station-dense area of southern and eastern China with most grid values being less than 0.05 K. In general, the negative temperature existed in each month prior to the 1980s, and a warming in temperature began thereafter, which accelerated in the early and mid-1990s. The increasing trend in the SAT series was observed for each month of the year with the largest temperature increase and highest uncertainty of 0.51 ± 0.29 K (10 year) occurring in February and the weakest trend and smallest uncertainty of 0.13 ± 0.07 K (10 year) in August. The sampling error uncertainties in the national average annual mean SAT series are not sufficiently large to alter the conclusion of the persistent warming in China. In addition, the sampling error uncertainties in the SAT series show a clear variation compared with other uncertainty estimation methods, which is a plausible reason for the inconsistent variations between our estimate and other studies during this period. [ABSTRACT FROM AUTHOR]

The parameterization of physical processes is one of the critical elements to properly simulate the regional climate over eastern China. It is essential to conduct detailed analyses on the effect of physical parameterization schemes on regional climate simulation, to provide more reliable regional climate change information. In this paper, we evaluate the 25-year (1983-2007) summer monsoon climate characteristics of precipitation and surface air temperature by using the regional spectral model (RSM) with different physical schemes. The ensemble results using the reliability ensemble averaging (REA) method are also assessed. The result shows that the RSM model has the capacity to reproduce the spatial patterns, the variations, and the temporal tendency of surface air temperature and precipitation over eastern China. And it tends to predict better climatology characteristics over the Yangtze River basin and the South China. The impact of different physical schemes on RSM simulations is also investigated. Generally, the CLD3 cloud water prediction scheme tends to produce larger precipitation because of its overestimation of the low-level moisture. The systematic biases derived from the KF2 cumulus scheme are larger than those from the RAS scheme. The scale-selective bias correction (SSBC) method improves the simulation of the temporal and spatial characteristics of surface air temperature and precipitation and advances the circulation simulation capacity. The REA ensemble results show significant improvement in simulating temperature and precipitation distribution, which have much higher correlation coefficient and lower root mean square error. The REA result of selected experiments is better than that of nonselected experiments, indicating the necessity of choosing better ensemble samples for ensemble. [ABSTRACT FROM AUTHOR]

By characterizing the patterns of temperature extremes over nine integrated agricultural regions (IARs) in China from 1961 to 2011, this study performed trend analyses on 16 extreme temperature indices using a high-resolution (0.5° × 0.5°) daily gridded dataset and the Mann-Kendall method. The results show that annually, at both daytime and nighttime, cold extremes significantly decreased but warm extremes significantly increased across all IARs. Overall, nighttimes tended to warm faster than daytimes. Diurnal temperature ranges (DTR) diminished, apart from the mid-northern Southwest China Region and the mid-Loess Plateau Region. Seasonally, DTR widely diminished across all IARs during the four seasons except for spring. Higher minimum daily minimum temperature (TNn) and maximum daily maximum temperature (TXx), in both summer and winter, were recorded for most IARs except for the Huang-Huai-Hai Region; in autumn, all IARs generally encountered higher TNn and TXx. In all seasons, warming was observed at daytime and nighttime but, again, nighttimes warmed faster than daytimes. The results also indicate a more rapid warming trend in Northern and Western China than in Southern and Eastern China, with accelerated warming at high elevations. The increases in TNn and TXx might cause a reduction in agriculture yield in spring over Northern China, while such negative impact might occur in Southern China during summer. In autumn and winter, however, the negative impact possibly occurred in most of the IARs. Moreover, increased TXx in the Pearl River Delta and Yangtze River Delta is possibly related to rapid local urbanization. Climatically, the general increase in temperature extremes across Chinese IARs may be induced by strengthened Northern Hemisphere Subtropical High or weakened Northern Hemisphere Polar Vortex. [ABSTRACT FROM AUTHOR]

How rising temperature and changing solar radiation affect evaporation of natural water bodies remains poor understood. In this study, evaporation from Lake Taihu, a large (area 2400 km) freshwater lake in the Yangtze River Delta, China, was simulated by the CLM4-LISSS offline lake model and estimated with pan evaporation data. Both methods were calibrated against lake evaporation measured directly with eddy covariance in 2012. Results show a significant increasing trend of annual lake evaporation from 1979 to 2013, at a rate of 29.6 mm decade according to the lake model and 25.4 mm decade according to the pan method. The mean annual evaporation during this period shows good agreement between these two methods (977 mm according to the model and 1007 mm according to the pan method). A stepwise linear regression reveals that downward shortwave radiation was the most significant contributor to the modeled evaporation trend, while air temperature was the most significant contributor to the pan evaporation trend. Wind speed had little impact on the modeled lake evaporation but had a negative contribution to the pan evaporation trend offsetting some of the temperature effect. Reference evaporation was not a good proxy for the lake evaporation because it was on average 20.6 % too high and its increasing trend was too large (56.5 mm decade). [ABSTRACT FROM AUTHOR]

The global climate has experienced unprecedented warming in the past century. The multiscale evolution of the warming is studied to better understand the spatial and temporal variation patterns of temperature. In this study, based on the yearly surface air temperature from the gridded CRU TS 3.22 dataset and the ensemble empirical mode decomposition method (EEMD), we investigated the multiscale evolution of temperature variability in the arid region of Northwest China (ARNC) from 1901 to 2013. Furthermore, the possible influences on the ARNC temperature change from the Atlantic Multidecadal Oscillation (AMO), Pacific Decadal Oscillation (PDO), and dipole mode index (DMI) were also discussed. The results indicated that in the past century, the overall temperature in the ARNC has showed a significant non-linear upward trend, and its changes have clearly exhibited an interannual scale (quasi-2-3 and quasi-6-7-year) and an interdecadal scale (quasi-14, quasi-24, and quasi-70-year). Compared with the reconstructed interannual variation, the reconstructed interdecadal variability plays a decisive role in the ARNC warming and reveals the climatic pattern transformation from the cold period to the warm period before and after 1987. Additionally, there were also regional differences in the spatial patterns of change trend in the ARNC temperature at a given time. We also found that the AMO and PDO had significant impacts on the ARNC temperature fluctuation at an interdecadal scale, whereas the DMI had a more important role in warming at the annual scale, which suggests that the importance of oceans cannot be ignored when considering climate change. Our findings deepen the understanding of the temperature changes all over the ARNC in the context of global warming. [ABSTRACT FROM AUTHOR]

Based on daily air temperature data from 772 stations in China, the present study uses absolute index and percentile index to investigate the spatial and temporal features of summer extreme temperature over China during the period 1960-2013. The analysis indicates that Xinjiang and southeastern China are two major domains where extreme heat events frequently occur and that the number of heat day (NHD) and the frequency of heat wave (FHW) both show an increasing trend throughout the country except for Shandong and Henan provinces where a decreasing trend is identified. Although the two leading empirical orthogonal function (EOF) modes of the NHD and the FHW based on the absolute index and percentile index have differences, the time series of the first principal components (PC1) are consistent; PC1 depicts opposite trends from 1960 to late 1990s and during the late 1990s to 2013. According to the climatology and EOF modes, four sub-regions are chosen: Chuanyu, Huanghuai, Southeast, and Xinjiang area. The inter-decadal variation over the four sub-regions differs, but the NHD and the FHW significantly increase after the mid-1990s. Based on Mann-Kendall method, it is found that the NHD and the FHW over Chuanyu exhibited abrupt shifts in 1978 and 2000; sudden shifts occurred in 1973 and 2000 over Huanghuai; an abrupt shift occurred over the Southeast area in 2003. [ABSTRACT FROM AUTHOR]

The Northeast China is one of typical regions experiencing intensive human activities within short time worldwide. Particularly, as the significant changes of agriculture land and forest, typical characteristics of pattern and process of agroforestry ecotone change formed in recent decades. The intensive land use change of agroforestry ecotone has made significant change for regional land cover, which had significant impact on the regional climate system elements and the interactions among them. This paper took agroforestry ecotone of Nenjiang River Basin in China as study region and simulated temperature change based on land cover change from 1950s to 1978 and from 1978 to 2010. The analysis of temperature difference sensitivity to land cover change based on Weather Research and Forecasting (WRF) model showed that the land cover change from 1950s to 1978 induced warming effect over all the study area, including the change of grassland to agriculture land, grassland to deciduous broad-leaved forest, and deciduous broad-leaved forest to shrub land. The land cover change from 1978 to 2010 induced cooling effect over all the study area, including the change of deciduous broad-leaved forest to agriculture land, grassland to agriculture land, shrub land to agriculture land, and deciduous broad-leaved forest to grassland. In addition, the warming and cooling effect of land cover change was more significant in the region scale than specific land cover change area. [ABSTRACT FROM AUTHOR]

To expand torrential rain, which is a meso- and microscale weather process, to a meso- and long-scale weather process, in this paper, we choose South China as a sample region and propose the conception of the 'Cumulative Effect' of torrential rain (CETR) by using daily precipitation observational data from 740 stations. Through a statistical analysis of the observations, three indexes-continuous time ( L ), control area ( A ), and precipitation contribution rate ( Q )-are used to define the CETR and indicate the torrential rain processes. The relationships between the CETR and simultaneous total precipitation over South China are analyzed in the pre-flooding and latter flooding seasons. This analysis shows that on both interannual and interdecadal scales, the three indexes are highly correlated with simultaneous total precipitation over South China in the pre-flooding season and latter flooding season. Moreover, an empirical orthogonal function (EOF) analysis is performed to classify the spatial distribution of the CETR. In both the pre-flooding season and the latter flooding season, the four major spatial models of torrential rain are similar to those of total precipitation over South China. With regard to the amount of precipitation caused by the CETR, the latter flooding season is affected more significantly than the pre-flooding season. Regarding the geographical distribution of precipitation, the opposite result occurs. In conclusion, in both the pre-flooding season and the latter flooding season, the CETR influences and even determines the amount and distribution of precipitation over South China. [ABSTRACT FROM AUTHOR]

The sensitivity of surface air temperature response to different grassland types and vegetation cover changes in the regions of temperate grassland of China was analyzed by observation minus reanalysis (OMR) method. The basis of the OMR approach is that reanalysis data are insensitive to local surface properties, so the temperature differences between surface observations and reanalysis can be attributed to land effects. Results showed that growing-season air temperature increased by 0.592 °C/decade in the regions of temperate grassland of China, with about 31 % of observed warming associated with the effects of grassland types and vegetation cover changes. For different grassland types, the growing-season OMR trend was the strongest for temperate desert steppe (0.259 °C/decade) and the weakest for temperate meadow (0.114 °C/decade). Our results suggest that the stronger intraseasonal changes of grassland vegetation are present, the more sensitive the OMR trend responds to the intraseasonal vegetation cover changes. In August and September, the OMR of temperate meadow showed a weak cooling trend. For temperate meadow, about 72.2 and 72.6 % of surface cooling were explained by both grassland type and increase of vegetation cover for August and September, respectively. For temperate steppe and temperate desert steppe, due to the limited soil moisture and little evaporative cooling feedback, the vegetation changes have no significant effect on the surface air temperature. These results indicate that the impact of grassland types and vegetation cover changes should be considered when projecting further climate change in the temperate grassland region of China. [ABSTRACT FROM AUTHOR]

Historical temperature and precipitation extremes and their potential future changes are quantified and evaluated throughout the landmass of China. A statistical model of climate extremes based on generalized extreme value (GEV) distribution is applied to both historical climate data and bias correction and spatial disaggregation (BCSD) downscaled Coupled Model Inter-comparison Project phase 5 (CMIP5) projections. The results indicate relatively moderate historical warm extreme conditions in China with regional means of maximum temperature 28.9, 29.4, and 29.8 °C for 10-, 20-, and 50-year return periods, respectively, whereas the corresponding regional means of minimum temperature are −20.1, −20.8, and −21.5 °C, manifesting a downward trend northwardly with relative larger regional variations in cold extremes. The historical precipitation extremes also decline gradually from south-southeast toward northwest with significant regional differences. As for the future, the warm extremes are expected to aggravate by roughly 1.66-4.92 °C projected by CMIP5, indicating larger increasing rate and spatial differences compared to cold extremes. The extreme precipitation is projected to increase 7.9-13.4 %, the dry regions would see a larger increasing rate compared to wet regions. The increasing radiative forcing concentration would trigger upward variations in both temperature and precipitation extreme magnitudes. Also, the warm extreme changes are more sensitive to the radiative forcing concentration than the cold extremes. The CMIP5 projections basically maintain a favorable inter-model consistency in temperature and rainfall extreme simulation for the future, but the inter-model difference of warm extremes is larger than cold extremes. [ABSTRACT FROM AUTHOR]

Reference evapotranspiration (ET) is the key factor for hydrologic water balance, irrigation scheduling, and water resources planning. Based on Food and Agriculture Organization (FAO) Penman-Monteith method and the climate variables of 57 meteorological stations from 1960 to 2010 in southwest China, the spatial and temporal distributions of ET were analyzed by using Mann-Kendall test and Sen's slope estimator. Sensitivity coefficient was used to analyze the sensitivities of ET to four climate variables, and the key climate variables attributed to ET change were determined. Result showed that there was a slight downward trend of ET from 1960 to 2010 and spatially increasing trend from northeast to southwest in annual time scale. Results also showed that ET had relatively higher sensitivity to wind speed and mean air temperature, and wind speed was the dominant variable for change of ET in southwest China. The inverse relationship between increasing air temperature and decreasing evaporation, 'evaporation paradox,' existed in southwest China, and the negative contribution of wind speed to the changes of ET offset the positive contribution of air temperature. [ABSTRACT FROM AUTHOR]

Daily records including the 0-cm average ground surface temperature (AGST) and average air temperature (AAT) from 557 meteorological stations over China from 1951 to 2010 are analyzed by employing the detrended fluctuation analysis (DFA) method. Different long-range correlation behaviors are found between AGST and AAT. The results show that the regional-averaged, minimum, and maximum values of the scaling exponents for AGST are shifted to the higher values than those for AAT over China. Furthermore, the number of stations where the differences of the scaling exponents between AGST and AAT is greater than zero accounts for about 87 % of the total. The probability distributions of the exponent differences are concentrated on the value of 0.04. Then, we make a numerical test to prove the significance of the difference in exponents by shuffling the data records which have removed the seasonal cycle. The results show that the difference of scaling exponents between AGST and AAT is significant. Through the comparison and analysis of AGST and AAT, we find that AGST seems to be more sensitive to detect temperature persistence changes. [ABSTRACT FROM AUTHOR]