Uncertainty Analysis of Assessing Climate Change Over the North China Plain in the 2050s Using the WRF Model

This study uses a WRF model to simulate the climate for 2000-2008 and the future climate change for 2051-2059 over the North China Plain under A2, A1B, and B1 emission scenarios. To validate the accuracy of a WRF simulation, the global land data assimilation system (GLDAS) data are introduced in this paper. Considering the effectiveness of GLDAS data first is necessary because these data are the products generated by employing satellite and ground-based observational data. The observations of 49 weather stations (MET) over the North China Plain are selected. The spatial-temporal characteristics of temperature and precipitation of GLDAS are highly consistent with those of the MET. A comparison of temperature and precipitation between that of WRF and GLDAS shows that the temperature generated by WRF is overestimated, but the precipitation rate it obtains is consistent with that of GLDAS (R = 0.94). The temperature obtained by WRF that is corrected by a bias correction technique, which is based on the cumulative distribution function, has a high correlation with that of GLDAS. The results of this study can be used to learn the influence of climate change on agriculture and water resources by deriving a crop model and a hydrological model on a regional scale. Results show that the mean temperature will increase by 0.21°C, 1.20°C and 1.55°C; the daily maximum temperature by 0.74°C, 1.76°C and 2.20°C; and the daily minimum temperature by -0.41°C, 0.52°C and 0.79°C under B1, A1B and A2, respectively. On the other hand, to a certain extent, precipitation will decrease by 6.1%, 13.7% and 7.8% under B1, A1B and A2 in the future.