Investigation of GLDAS1 Meteorological Focing Data and Bias Correction of Precipitation Data for Application in Land Surface Model (Case Study :Neishaboor Basin)

Document Type : Original Article

Authors

1 PhD Student of Water Engineering Department, Ferdowsi University of Mashhad

2 Professor of Water Engineering Department, Ferdowsi University of Mashhad

3 Professor of Water Engineering Department, Faculty of Agriculture, Ferdowsi University of Mashhad

4 Associate Professor of Water Engineering Department, Faculty of Agriculture, Ferdowsi University of Mashhad

Abstract

In many climate studies, land surface models are forced by meteorological data, and there is no attempt to check the quality of the data. The purpose of this study is to evaluation of GLDAS1 meteorological forcing data and application of bias correction method for these data. The weather data corrected will be input into the Noah-MP model in the next study.
Observations for the Neyshaboor Basin have been collected at a temporal resolution of one day during the period 2000–2009 for ten years from fourteen stations and evaporation stations and a meteorological station in the basin. The variables of temperature, relative humidity, short solar wavelength, and air pressure, with correlation coefficients of 0.94, 0.77, 0.74 and 0.6, respectively, were in good agreement with the observations. The GLDAS1 precipitation data for most of this basin is less than observations. The precipitation has been corrected by matching the mean and the coefficient of variation of GLDAS data with observational data. The results of applying the correction method were satisfactory, so that difference in average daily precipitate between GLDAS1 data and observational data was effectively reduced to 0.048 mm. Also, the correlation between the number of wet days (precipitation over 0.3 mm) in the observational data with the corrected data compared to the uncorrected data improved from -1.17 to 0.93 and the first-order autocorrelation in the observational data with corrected data has improved better than uncorrected data and has grown from -2.4 to 0.41. The corrections were the highest during January, February, October, November and December. the bias correction applied seems to correct the precipitation well during May to September.

Keywords

References

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Iranian Journal of Irrigation & Drainage
Volume 12, Issue 6 - Serial Number 72
March and April 2019
Pages 1327-1336

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