Spatial Interpolation of Daily Precipitation in China: 1951-2005
2010 (English)In: Advances in Atmospheric Sciences, ISSN 0256-1530, Vol. 27, no 6, 1221-1232 p.Article in journal (Refereed) Published
Climate research relies heavily on good quality instrumental data; for modeling efforts gridded data are needed. So far, relatively little effort has been made to create gridded climate data for China. This is especially true for high-resolution daily data. This work, focuses on identifying an accurate method to produce gridded daily precipitation in China based on the observed data at 753 stations for the period 1951-2005. Five interpolation methods, including ordinary nearest neighbor, local polynomial, radial basis function, inverse distance weighting, and ordinary kriging, have been used and compared. Cross-validation shows that the ordinary kriging based on seasonal semi-variograms gives the best performance, closely followed by the inverse distance weighting with a power of 2. Finally the ordinary kriging is chosen to interpolate the station data to a 18 kmx 18 km grid system covering the whole country. Precipitation for each 0.5A degrees x 0.5A degrees latitude-longitude block is then obtained by averaging the values at the grid nodes within the block. Owing to the higher station density in the eastern part of the country, the interpolation errors are much smaller than those in the west (west of 100A degrees E). Excluding 145 stations in the western region, the daily, monthly, and annual relative mean absolute errors of the interpolation for the remaining 608 stations are 74%, 29%, and 16%, respectively. The interpolated daily precipitation has been made available on the internet for the scientific community.
Place, publisher, year, edition, pages
2010. Vol. 27, no 6, 1221-1232 p.
daily precipitation, spatial interpolation, ordinary kriging, gridded data, China
Earth and Related Environmental Sciences
IdentifiersURN: urn:nbn:se:uu:diva-133839DOI: 10.1007/s00376-010-9151-yISI: 000283136900001OAI: oai:DiVA.org:uu-133839DiVA: diva2:370958