Downscaling of Air Temperature in the Yarlung Zangbo River Basin Based on the Random Forest Model

REN Meifang; PANG Bo; XU Zongxue; ZHAO Yanjun

doi:10.7522/j.issn.1000-0534.2018.00026

Plateau Meteorology >

2018 , Vol. 37 >Issue 5: 1241 - 1253

DOI: https://doi.org/10.7522/j.issn.1000-0534.2018.00026

Downscaling of Air Temperature in the Yarlung Zangbo River Basin Based on the Random Forest Model

REN Meifang ,
PANG Bo ,
XU Zongxue ,
ZHAO Yanjun

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Key Laboratory for Water and Sediment Science, Ministry of Education, College of Water Sciences, Beijing Normal University/Beijing Key Laboratory of Urban Hydrological Cycle and Sponge City Technology, Beijing 100875, China

Received date: 2017-11-11

Online published: 2018-10-28

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Abstract

Random forest (RF) model was used to downscale the daily air temperature at 20 meteorological stations in and around the Yarlung Zangbo River basin.For the purpose to explore the better downscaling method of air temperature in the study area, three methods were used to compare, namely, the Multiple Linear Regression (MLR), Artificial Neural Network (ANN), and Support Vector Machine (SVM).Principal Component Analysis (PCA) and Partial Correlation Analysis (PAR) were used to select the characteristic variables.The model performance was assessed using four criteria, namely, the NASH coefficient of efficiency (NASH), the root mean squared error (RMSE), the mean absolute error (MAE), and the coefficient of correlation (r).The results showed that the performance of RF model was obviously better than other models; the results obtained by PAR to select characteristic variables were not only better than those used by PCA method, but also more stable.In addition, the NASH efficiency coefficients of various models were all above 0.86 and the correlation coefficients were all above 0.93 in the validation periods.Therefore, all of models used in this study can well simulate the average temperature in the Yarlung Zangbo River basin.The experimental data of two typical extreme concentration paths(Representative Concentration Pathway, RCP)emission scenarios RCP2.6 and RCP8.5 of MPI-ESM-LR model in the future (2016-2050)were chosen to study the future trend of temperature in the Yarlung Zangbo River basin.The results showed increasing trend of daily air temperature both under RCP2.6 and RCP8.5 scenarios in the future years of 2016-2050 in the Yarlung Zangbo River basin.The daily air temperature will increase by 0.14℃ under RCP2.6 scenario, and 0.30℃ under RCP8.5 scenario from 2016 to 2050.

Key words： Statistical downscal; random forest; Yarlung Zangbo River; temperature

Cite this article

REN Meifang , PANG Bo , XU Zongxue , ZHAO Yanjun . Downscaling of Air Temperature in the Yarlung Zangbo River Basin Based on the Random Forest Model[J]. Plateau Meteorology, 2018 , 37(5) : 1241 -1253 . DOI: 10.7522/j.issn.1000-0534.2018.00026

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