Gaussian Weighting Method In The Ground Day Temperature Field In The Space Of The Yangtze River Basin

The remote sensing model is difficult to be adopted during the course of 1km-resolutioned spatial interpolation for daily air temperature in the reaches of Yangtze Rive for the limitations of remote technology and finance. The declining of confidence limit is the reason that makes the multiple-regression model not to fit for better precision any more. At the same time, during the course of 1km-resolutioned spatial interpolation for the daily surface air temperature in the reaches of Yangtze Rive, the altitudinal effect can't negligible.As a result, in the paper, considering the altitudinal effect (topography factor) and the influence on the temperature lapse rate by topography and latitude and longitude and moisture transfer, the study on the daily surface air mean ,max and min temperature in the reaches of Yangtze Rive is attempted by five models, which include the Gaussian weighted model, the Gaussian weighted model associated with the error-modification, the Gradient plus inverse distance squared model and the modified Gaussian weighted model A and B that take topography-factor into account. During the course of the research, the criterions of the interpolation effect are Mean error (ME), Mean absolute error (MAE), Root mean squared interpolation error (RMSE) and the difference of Mean square deviation between the measured and the estimated surface air temperature.The conclusions are as follows: (1)By contrasting the Gaussian weighted model associated with the error modification with the Gaussian weighted model, the error modification is proved to considerably ameliorate the precision of spatial interpolation; (2)On the base of the Gaussian weighted model, taking altitudinal effect into account can reflect the trend in which temperature changes according to the topographic altitude and may ameliorate the precision of spatial interpolation correspondingly and apparently, which indicates that topographical effect on the preciseness of spatial interpolation can not be disregarded in terms of the region with complicated topography; (3)The map of daily surface air temperature distribution, using the modified Gaussian weighted model A and B, can accurately reflect the temperature-changing-with-topographical-altitude trend. Among them, the better is the model A, whose ME is below 0.03癈. As far as daily surface air mean temperature, RMSIE is below 0.5CTC. As for daily surface air max and min temperature, the RMSIE are respectively lower than 0.74℃ and 0.58℃. (4)The model A takes into account the fact thattemperature lapse rate changes according to such factors as topography, latitude, longitude and moisture transfer, etc. The effect of spatial interpolation that uses it is not noticeably ameliorated by contrast with using the model A. There remains a need for further study.