Based on the high‐resolution gridding data (CN05) from 2416 station observations, a grid dataset of temperature and precipitation extreme indices with the resolution of 0.5° × 0.5° for China region was developed using the approach recommended by the Expert Team on Climate Change Detection and Indices. This article comprehensively presents temporal and spatial changes of these indices for the time period 1961–2010. Results showed widespread significant changes in temperature extremes consistent with warming, for instance, decreases in cold extremes and increases in warm extremes over China. The warming in the coldest day and night is larger than the warmest day and night, respectively, which is concurrent with the coldest night larger than the coldest day and the warmest night larger than the warmest day. Changes in the number of the cold and warm nights are more remarkable than the cold and warm days. Changes in precipitation extremes are, in general, spatially more complex and exhibit a less widespread spatial coverage than the temperature indices, for instance, the patterns of annual total precipitation amount, average daily precipitation rate, and the proportion of heavy precipitation in total annual precipitation are similar with negative trends in a southwest–northeast belt from Southwest China to Northeast China while positive trends in eastern China and northwestern China. The consistency of changes in climate extremes from the CN05 with other datasets based on the stations and reanalyses is also analysed.

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IntroductionThere is a great health services disparity between urban and rural areas in China. The percentage of people who are unable to access health services due to long travel times increases. This paper takes Donghai County as the study unit to analyse areas with physician shortages and characteristics of the potential spatial accessibility of health services. We analyse how the unequal health services resources distribution and the New Cooperative Medical Scheme affect the potential spatial accessibility of health services in Donghai County. We also give some advice on how to alleviate the unequal spatial accessibility of health services in areas that are more remote and isolated.MethodsThe shortest traffic times of from hospitals to villages are calculated with an O-D matrix of GIS extension model. This paper applies an enhanced two-step floating catchment area (E2SFCA) method to study the spatial accessibility of health services and to determine areas with physician shortages in Donghai County. The sensitivity of the E2SFCA for assessing variation in the spatial accessibility of health services is checked using different impedance coefficient valuesa. Geostatistical Analyst model and spatial analyst method is used to analyse the spatial pattern and the edge effect of potential spatial accessibility of health services.ResultsThe results show that 69% of villages have access to lower potential spatial accessibility of health services than the average for Donghai County, and 79% of the village scores are lower than the average for Jiangsu Province. The potential spatial accessibility of health services diminishes greatly from the centre of the county to outlying areas. Using a smaller impedance coefficient leads to greater disparity among the villages. The spatial accessibility of health services is greater along highway in the county.ConclusionsMost of villages are in underserved health services areas. An unequal distribution of health service resources and the reimbursement policies of the New Cooperative Medical Scheme have led to an edge effect regarding spatial accessibility of health services in Donghai County, whereby people living on the edge of the county have less access to health services. Comprehensive measures should be considered to alleviate the unequal spatial accessibility of health services in areas that are more remote and isolated.