(1) 中国科学院烟台海岸带研究所

With large population density, rapid urbanization process and high-speed economic development, the coastal area of China is prone to vulnerable to climate change because of the frequently nature disasters and fragile eco-environment. Based on daily maximum and minimum temperature of 156 meteorological station records from 1961 to 2014,16 extreme temperature indices including cool days (TX10p), cool nights (TN10p), warm days (TX90p), warm nights (TN90p), frost days (FD0),ice days (ID0),summer days (SU25), tropical nights (TR20), maximum value of daily maximum temperature (TXx), maximum value of daily minimum temperature (TNx), minimum value of daily maximum temperature (TXn), minimum value of daily minimum temperature (TNn), warm spell duration index (WSDI), cold spell duration index (CSDI),growing season length (GSL) and diurnal temperature range (DTR) were calculated by RCIimDex model, respectively. And Inverse Distance Weight interpolation method was employed to produce the extreme temperature raster dataset, which includes two types of raster data, the first of which refers to the multi-year average, and the other is the inter-annual magnitude in 16 extreme temperature indices in the coastal area of China during 1961-2014. With an 8.934 km spatial resolution,the dataset is archived in .tif format, including 32 sets of data files, and is compressed in 1 .zip file with the data size of 12.5 MB. Related research results of this dataset were published in the Acta Ecologica Sinica, 2017, Volume 37,Issue 21.