By comparing two sets of quality-controlled daily temperature observation data with and without the inhomogeneity test and adjustment from 654 stations in China during 1956-2004 and 1956-2010, impacts of inhomogeneity on changing trends of four percentile temperature extreme indices, including occurrences of cold days, cold nights, warm days, and warm nights with varying intensities, were discussed. It is found that the inhomogeneity affected the long-term trends averaged over extensive regions limitedly. In order to minimize the inhomogeneity impact, the 83 stations identified with obvious inhomogeneity impacts were removed, and an updated analysis of changing trends of the four temperature extreme indices with varying intensities during 1956-2010 was conducted. The results show that annual occurrences of both cold nights and cold days decreased greatly while those of warm nights and warm days increased significantly during the recent 20 years. The more extreme the event is, the greater the magnitude of changing trends for the temperature extreme index is. An obvious increasing trend was observed in annual occurrences of cold days and cold nights in the recent four years. The magnitude of changing trends of warm extreme indices was greater than that of cold extreme indices, and it was greater in northern China than in southern China. Trends for summer occurrence of cold days were not significant. Decreasing trends of occurrences of both cold nights and cold days were the greatest in December, January, and February (DJF) but the least in June, July, and August (JJA), while increasing trends of warm nights were the greatest in JJA. Cold nights significantly decreased from 1956 to 1990, and then the decreasing trend considerably weakened. The decreasing trend also showed an obvious slowdown in recent years for occurrence of cold days. However, increasing trends of warm nights and warm days both have been accelerated continuously since the recent decades. Further analysis presents that the evolution of the trends fo
The sea surface temperature (SST) of the tropical western Pacific Ocean (TWPO) showed a pronounced warming in the late 1990s. Using numerical experiments of a regional climate model (RegCM), we analyzed the impact of this warming on rainfall over the Yangtze-Huaihe River valley of China during the Meiyu period (June-July). The model results revealed that the observed decadal changes in Meiyu rainfall since the late 1990s can be reproduced by a control experiment forced by the observed SST. Additionally, the sensitivity experiments suggested that the warming trend in the TWPO played a substantial role in the northward shift of the Meiyu belt in the late 1990s.
In this paper,the characteristics of meteorological variables are statistically correlated with icing events(i.e.,glaze and rime) in China,using daily observations of air temperature,relative humidity,wind speed,and weather phenomena from 700 stations in China from 1954 to 2008.The weather conditions most favorable for icing events are investigated and two statistical models are developed to discriminate potential freezing days.Low air temperature,high relative humidity,and low wind speed are shown to be important conditions for occurrence of icing events;also,the favorable daily mean air temperature is shown to have a decreasing trend from north to south in China,while the favorable relative humidity and wind speed varies little across the country.The statistical model developed with the daily mean temperature combined with precipitation,fog,and mist weather phenomena proved to be well able to determine the possible occurrence of freezing days.The accuracy of model outputs is well above 60% for northwestern Yunnan,Guizhou,northern Guangxi,southern Hunan,and southern Jiangxi,among other regions where icing events are more frequent,and the average false alarms are few.Using observations or forecast products of conventional meteorological variables,this model has high performance and is practical and applicable for early warning and monitoring of icing events.
