Quantifying the attribution of model bias in simulating summer hot days in China with IAP AGCM 4.1

Using lAP AGCM simulation results for the period 1961-2005, summer hot days in China were calculated and then compared with observations. Generally, the spatial pattern of hot days is reasonably reproduced, with more hot days found in northern China, the Yangtze and Huaihe River basin, the Chuan-Yu region, and southern Xinjiang. However, the model tends to overestimate the number of hot days in the above-mentioned regions, particularly in the Yangtze and Huaihe River basin where the simulated summer-mean hot days is 13 days more than observed when averaged over the whole region, and the maximum overestimation of hot days can reach 23 days in the region. Analysis of the probability distribution of daily maximum temperature （Trnax） suggests that the warm bias in the model-simulated Tmax contributes largely to the overestimation of hot days in the model. Furthermore, the discrepancy in the simulated variance of the Tmax distribution also plays a non- negligible role in the overestimation of hot days. Indeed, the latter can even account for 22% of the total bias of simulated hot days in August in the Yangtze and Huaihe River basin. The quantification of model bias from the mean value and variability can provide more information for further model improvement.

Inhomogeneous trends in the onset date of extreme hot days in China over the last five decades

Using a homogenized daily maximum temperature(T_(max))dataset across China,this study characterized the spatiotemporal variation of the onset date of extreme hot days in a year(i.e.,FirstEHD)during 1960-2018.Inhomogeneous trends of FirstEHD over China during 1960-2018 can be found,with the advanced trend of FirstEHD over most parts in China,while a number of stations in North-Central China(NC)show the delayed trend of FirstEHD.Moreover,there exist interdecadal changes of FirstEHD trend,with a remarkable difference in the trend magnitude before and after the 1990s over South China(SC),and the sign of trend can even reverse from negative to positive after the 1990s in Xinjiang(XJ)and Yangtze River Basin(YR),and from positive to negative in NC.The overall trends of FirstEHD over NC,YR,and XJ during 1960-2018 are dominated by the trends before the 1990s,while they are dominated by the sharp advance after the 1990s over SC.It is further found that the trend of FirstEHD can generally be explained by the long-term trend in T_(max) over most parts of China,but the contribution from T_(max) variabilities is also non-negligible and can even account for more than 75% of the overall trend over NC.The possible factors responsible for the decadal changes in FirstEHD trends are also discussed.

Interannual Variation and Statistical Prediction of Summer Dry and Hot Days in South China from 1970 to 2018

The frequent occurrence of dry and hot(DH)days in South China in summer has a negative impact on social development and human health.This study explored the variation characteristics of DH days and the possible reasons for this knotty problem.The findings revealed a notable increase in the number of DH days across most stations,indicating a significant upward trend.Additionally,DH events were observed to occur frequently.The number of DH days increased during 1970-1990,decreased from 1991 to 1997,and stayed stable after 1997.The key climate factors affecting the interannual variability of the number of DH days were the Indian Ocean Basin warming(IOBW)in spring and the East Asian Summer Monsoon(EASM).Compared with the negative phase of IOBW,in the positive phase of IOBW,500 hPa and 850 hPa geopotential height enhanced,the West Pacific subtropical high strengthened and extended abnormally to the west,more solar radiation reached the surface,surface outgoing longwave radiation increased,and there was an anomalous anticyclone in eastern South China.The atmospheric circulation characteristics of the positive and negative phases of ESAM were opposite to those of IOBW,and the abnormal circulation of the positive(negative)phases of ESAM was unfavorable(favorable)for the increase in the number of DH days.A long-term prediction model for the number of summer DH days was established using multiple linear regression,incorporating the key climate factors.The correlation coefficient between the observed and predicted number of DH days was 0.65,and the root-mean-square error was 2.8.In addition,independent forecasts for 2019 showed a deviation of just 1 day.The results of the independent recovery test confirmed the stability of the model,providing evidence that climatic factors did have an impact on DH days in South China.

Enhanced Cooling Efficiency of Urban Trees on Hotter Summer Days in 70 Cities of China

Increasing the urban tree cover percentage(TCP) is widely recognized as an efficient way to mitigate the urban heat island effect. The cooling efficiency of urban trees can be either enhanced or attenuated on hotter days, depending on the physiological response of urban trees to rising ambient temperature. However, the response of urban trees' cooling efficiency to rising urban temperature remains poorly quantified for China's cities. In this study, we quantify the response of urban trees' cooling efficiency to rising urban temperature at noontime [~1330 LT(local time), LT=UTC+8] in 17summers(June, July, and August) from 2003–19 in 70 economically developed cities of China based on satellite observations. The results show that urban trees have stronger cooling efficiency with increasing temperature, suggesting additional cooling benefits provided by urban trees on hotter days. The enhanced cooling efficiency values of urban trees range from 0.002 to 0.055℃ %-1 per 1℃ increase in temperature across the selected cities, with larger values for the lowTCP-level cities. The response is also regulated by background temperature and precipitation, as the additional cooling benefit tends to be larger in warmer and wetter cities at the same TCP level. The positive response of urban trees' cooling efficiency to rising urban temperature is explained mainly by the stronger evapotranspiration of urban trees on hotter days.These results have important implications for alleviating urban heat risk by utilizing urban trees, particularly considering that extreme hot days are becoming more frequent in cities under global warming.

An Abrupt Increase in the Summer High Temperature Extreme Days across China in the mid-1990s

Based on the daily maximum surface air temperature records from an updated homogenized temperature dataset for 549 Chinese stations during 1960-2008,we reveal that there is an abrupt increase in the number of days with high temperature extremes （HTEs,an HTE day is defined when the maximum temperature exceeds the 95th percentile of the daily maximum temperature distributions） across China in the mid-1990s.Before this regime shift,the average number of HTE days is about 2.9 d yr 1 during the period from the 1970s to the early 1990s,while it rocketed to about 7.2 d yr 1 after the mid-1990s.We show that the significant HTE day increase occurs uniformly across the whole of China after the regime shift.The observational evidence raises the possibility that this change in HTE days is associated with global-scale warming as well as circulation adjustment.Possible causes for the abrupt change in the HTE days are discussed,and the circulation adjustment is suggested to play a crucial role in the increase in HTE days in this region.

The Relationship between Spring Soil Moisture and Summer Hot Extremes over North China

The increase in the occurrence of hot extremes is known to have resulted in serious consequences for human society and ecosystems. However, our ability to seasonally predict hot extremes remains poor, largely due to our limited understanding of slowly evolving earth system components such as soil moisture, and their interactions with climate. In this study, we focus on North China, and investigate the relationship of the spring soil moisture condition to summer hot extremes using soil moisture data from the Global Land Data Assimilation System and observational temperature for the period 1981-2008. It is found that local soil moisture condition in spring is closely linked to summer hot days and heat waves over North China, accounting for 19%-34% of the total variances. Spring soil moisture anomalies can persist to the summer season, and subsequently alter latent and sensible heat fluxes, thus having significant effects on summer hot extremes. Our findings indicate that the spring soil moisture condition can be a useful predictor for summer hot days and heat waves over North China.

Climatology and Trends of High Temperature Extremes across China in Summer

Based on the daily maximum air temperature data from 300 stations in China from 1958 to 2008, the climatological distribution of the number of days with high temperature extremes （HTEs, maximum temperatures higher than 35℃） are studied with a focus on the long-term trends. Although the number of HTE days display well-defined sandwich spatial structures with significant decreasing trends in central China and increasing trends in northern China and southern China, the authors show that the decrease of HTE days in central China occurs mainly in the early period before the 1980s, and a significant increase of HTE days dominates most of the stations after the 1980s. The authors also reveal that there is a jump-like acceleration in the number of HTE days at most stations across China since the mid 1990s, especially in South China, East China, North China, and northwest China.

Dataset of high temperature extremes over the major land areas of the Belt and Road for 1979-2018

Hot temperature extremes exert strong negative socioeconomic and environmental impacts worldwide.In this paper,we focus on the major land areas of the Belt and Road(BR)and develop a dataset of high temperature extremes including hot days,hot nights and combined hot extremes using Climate Prediction Center(CPC)gridded daily temperature data at a resolution of 0.5°during 1979-2018.The constant thresholds of daily maximum surface air temperature(Tmax)include 28℃,30℃,32℃,35℃,38℃,and 40℃,while those of daily minimum surface air temperature(Tmin)consist of 20℃,25℃,and 30℃.Data of hot days,hot nights and combined hot extreme are produced based on different constant Tmax and Tmin thresholds and their combination.We also adopt the 90th and 95th percentile thresholds of Tmax and Tmin to generate high temperature extreme data.The validation with China Meteorological Administration(CMA)data over eastern China for the period of 1979-2011 indicates that our dataset can generally describe the spatial and temporal variations of high temperature extremes well.Potential applications of this dataset include analyses on the local-to-regional characteristics of high temperature extremes and their impacts on various sectors over the major BR land areas.The dataset is available at http://www.sciencedb.cn/dataSet/handle/904.