Open AccessJournal Article
A gridded daily observation dataset over China region and comparison with the other datasets
TLDR
In this paper, a new gridded daily dataset with the resolution of 0.25°latitude by 0.75°longitude, CN05.1, is constructed for the purpose of high resolution climate model validation over China region.Abstract:
A new gridded daily dataset with the resolution of 0.25°latitude by 0.25°longitude,CN05.1,is constructed for the purpose of high resolution climate model validation over China region.The dataset is based on the interpolation from over 2400observing stations in China,includes 4variables : daily mean,minimum and maximum temperature,daily precipitation.The " anomaly approach " is applied in this interpolation.The climatology is first interpolated by thinplate smoothing splines and then a gridded daily anomaly derived from angular distance weighting method is added to climatology to obtain the final dataset.Intercomparison of the dataset with other three daily datasets,CN05for temperature,and EA05and APHRO for precipitation is conducted.The analysis period is from 1961to 2005.For multi-annual mean temperature variables,results show small differences over eastern China with dense observation stations,but larger differences(warmer) over western China with less stations between CN05.1and CN05.The temperature extremes are measured by TX3D(mean of the 3greatest maximum temperatures in a year) and TN3D(mean of the 3lowest minimum temperatures).CN05.1in general shows a warmer TX3Dover China,while a lower TN3Din the east and greater TN3Din the west are found compared to CN05.A greater value of annual mean precipitation compared to EA05and APHRO,especially to the latter,is found in CN05.1.For precipitation extreme of R3D(mean of the 3largest precipitations in a year),CN05.1presents lower value of it in western China compared to EA05.read more
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Two different propagation patterns of spatiotemporally contiguous heatwaves in China
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CWRF downscaling and understanding of China precipitation projections
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Multi-Model Ensemble Projection of Precipitation Changes over China under Global Warming of 1.5 and 2°C with Consideration of Model Performance and Independence
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