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United States Department of Agriculture

Agricultural Research Service

Research Project: INTEGRATION OF CLIMATE VARIABILITY AND FORECASTS INTO RISK-BASED MANAGEMENT TOOLS FOR AGRICULTURE PRODUCTION AND RESOURCE CONSERVATION

Location: Great Plains Agroclimate and Natural Resources Research Unit

Title: Assessment and improvement of CLIGEN non-precipitation parameters for the Loess Plateau of China

Authors
item Chen, J - SOIL & WATER CONS. CHINA
item Zhang, Xunchang
item Liu, W - SOIL & WATER CONS. CHINA
item Li, Z - SOIL & WATER CONS. CHINA

Submitted to: Transactions of the ASABE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: April 1, 2008
Publication Date: June 1, 2008
Citation: Chen, J., Zhang, X.J., Liu, W.Z., Li, Z. 2008. Assessment and improvement of CLIGEN non-precipitation parameters for the Loess Plateau of China. Transactions of the ASABE. 51(3):901-913.

Interpretive Summary: Computer models of weather generators are often used to generate daily weather data to drive hydrologic and crop models. This study was to evaluate and improve the ability of the latest version of a weather generator (CLIGEN) to generate non-precipitation parameters, including daily temperatures, solar radiation (SR), and wind velocity (WV). We used daily weather data at 12 stations in the Loess Plateau of China to evaluate the latest model and to improve SR and WV generation. The results showed that CLIGEN reproduced daily maximum temperature (Tmax) and minimum temperature (Tmin) reasonably well. Means and distributions of daily dew point temperature (Tdp) were reproduced very well, but the standard deviations were less well reproduced. The means and standard deviations of daily SR were much better produced by the modified CLIGEN, but the distributions were slightly worsened. Daily WV was reproduced very well after fixing a unit conversion error. Means of the same-day temperature range (Tmax1-Tmin1) and one-day lag temperature ranges for both Tmax1-Tmin2 and Tmax2-Tmin1 of the CLIGEN-generated data were reproduced well. However, compared with the measured data, standard deviations of Tmax1-Tmin1 were consistently underestimated, and those of Tmax1-Tmin2 and Tmax2-Tmin1 were consistently overestimated on all stations. Seasonal serial correlations of SR and cross correlation between temperatures and SR were much better reproduced by the modified model. Overall, results showed that non-precipitation variables were much better generated by the modified latest version than the previous versions. CLIGEN can be used by modelers for studying climatic impacts on crop production and natural resources conservation.

Technical Abstract: Stochastic weather generators are often used to generate daily weather input for hydrologic and crop models. The objective of this study was to evaluate and improve the ability of the CLImate GENerator (CLIGEN v5.22564) to generate non-precipitation parameters, including daily temperatures, solar radiation (SR), and wind velocity (WV) at 12 meteorological stations dispersed in the Loess Plateau of China. We used daily weather data at 12 stations to evaluate the latest version and to improve SR and WV generation. The results showed that v5.22564 reproduced daily maximum temperature (Tmax) and minimum temperature (Tmin) reasonably well. Means and distributions of daily dew point temperature (Tdp) were reproduced very well, but the standard (std) deviations were less well reproduced. The means and std deviations of daily SR were much better produced by the modified v5.22564, but the distributions were slightly worsened. Daily WV was reproduced very well after fixing a unit conversion error. Means of the same-day temperature range (Tmax1-Tmin1) and one-day lag temperature ranges for both Tmax1-Tmin2 and Tmax2-Tmin1 of the v5.22564-generated data were reproduced well. However, compared with the measured data, std deviations of Tmax1-Tmin1 were consistently underestimated, and those of Tmax1-Tmin2 and Tmax2-Tmin1 were consistently overestimated on all stations. Seasonal serial correlations of SR and cross correlation between temperatures and SR were much better reproduced by the modified model. Overall, results showed that non-precipitation variables were much better generated by the modified latest version of 5.22564 than the previous versions in which Tmax, Tmin and Tdp were generated independently.

Last Modified: 4/18/2014
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