Mapping Daily Temperature and Precipitation in the Qilian Mountains of Northwest China

Daily meteorological data are the critical inputs for distributed hydrological and ecological models. This study modified mountain microclimate simulation model(MTCLIM) with the data from 19 weather stations, and compared and validated two methods(the MTCLIM and the modified MTCLIM) in the Qilian Mountains of Northwest China to estimate daily temperature(i.e., maximum temperature,minimum temperature) and precipitation at six weather stations from 1 January 2000 to 31 December2009. The algorithm of temperature in modified MTCLIM was improved by constructing the daily linear regression relationship between temperature and elevation, aspect and location information. There are two steps to modify the MTCLIM to predict daily precipitation: firstly, the linear regression relationship was built between annual average precipitation and elevation, location, and vegetation index; secondly, the distance weight for measuring the contribution of each weather station on target point was improved by average wind direction during the rainy season. Several regression analysis and goodness-of-fit indices(i.e., Pearson's correlation coefficient, coefficient of determination, mean absolute error, root-mean-square error and modeling efficiency) were used to validate these estimated values. The result showed that the modified MTCLIM had a better performance than the MTCLIM.Therefore, the modified MTCLIM was used to map daily meteorological data in the study area from 2000 to 2009. These results were validated using weather stations with short time data and the predicted accuracy was acceptable. The meteorological data mapped could become inputs for distributed hydrological and ecological models applied in the Qilian Mountains.

Daily meteorological data are the critical inputs for distributed hydrological and ecological models. This study modified mountain microclimate simulation model （MTCLIM） with the data from 19 weather stations, and compared and validated two methods （the MTCLIM and the modified MTCLIM） in the Qilian Mountains of Northwest China to estimate daily temperature （i.e., maximum temperature, minimum temperature） and precipitation at six weather stations from i January 2000 to 31December 2009. The algorithm of temperature in modified MTCLIM was improved by constructing the daily linear regression relationship between temperature and elevation, aspect and location information. There are two steps to modify the MTCLIM to predict daily precipitation： firstly, the linear regression relationship was built between annual average precipitation and elevation, location, and vegetation index; secondly, the distance weight for measuring the contribution of each weather station on target point was improved by average wind direction during the rainy season. Several regression analysis and goodness-of-fit indices （i.e., Pearson＇s correlation coefficient, coefficient of determination, mean absolute error, root-mean-square error and modelingefficiency） were used to validate these estimated values. The result showed that the modified MTCLIM had a better performance than the MTCLIM. Therefore, the modified MTCLIM was used to map daily meteorological data in the study area from 2000 to 2009. These results were validated using weather stations with short time data and the predicted accuracy was acceptable. The meteorological data mapped could become inputs for distributed hydrological and ecological models applied in the Qilian Mountains.