In this study, surface air temperature from 75 meteorological stations above 3000 m on the Tibetan Plateau are applied for evaluation of the European Centre for Medium-Range Weather Forecasts(ECMWF) third-generation r...In this study, surface air temperature from 75 meteorological stations above 3000 m on the Tibetan Plateau are applied for evaluation of the European Centre for Medium-Range Weather Forecasts(ECMWF) third-generation reanalysis product ERA-Interim in the period of 1979-2010. High correlations ranging from 0.973 to 0.999 indicate that ERA-Interim could capture the annual cycle very well. However, an average root-meansquare error(rmse) of 3.7°C for all stations reveals that ERA-Interim could not be applied directly for the individual sites. The biases can be mainly attributed to the altitude differences between ERA-Interim grid points and stations. An elevation correction method based on monthly lapse rates is limited to reduce the bias for all stations. Generally, ERA-Interim captured the Plateau-Wide annual and seasonal climatologies very well. The spatial variance is highly related to the topographic features of the TP. The temperature increases significantly(10°C- 15°C) from the western to the eastern Tibetan Plateau for all seasons, in particular during winter and summer. A significant warming trend(0.49°C/decade) is found over the entire Tibetan Plateau using station time series from 1979-2010. ERA-Interim captures the annual warming trend with an increase rate of 0.33°C /decade very well. The observation data and ERA-Interim data both showed the largest warming trends in winter with values of 0.67°C/decade and 0.41°C/decade, respectively. We conclude that in general ERA-Interim captures the temperature trends very well and ERA-Interim is reliable for climate change investigation over the Tibetan Plateau under the premise of cautious interpretation.展开更多
Atmospheric winds from observations and medium-range weather forecast model predictions can be physically decomposed as daily climate wind,planetary-scale anomalous wind,and synoptic-scale anomalous wind.The 850 hPa s...Atmospheric winds from observations and medium-range weather forecast model predictions can be physically decomposed as daily climate wind,planetary-scale anomalous wind,and synoptic-scale anomalous wind.The 850 hPa synoptic-scale anomalous winds were extracted from the numerical model outputs of the European Centre for Medium-Range Weather Forecasts(ECMWF) and the NCEP Global Forecast System(GFS).The results showed that most rain bands in eastern China in 2010 were located along the anomalous convergence lines.To predict the major rain bands by these convergence lines in 2010,the accuracies of the ECMWF products were 100%,85%,and 15% for leading 3,6,and 9 days,while the GFS products showed 53%,15%,and 6% accuracies,respectively.In comparison of the regional heavy rainfalls between observation and the ECMWF model prediction,the useful leading information was about 3.1 days for direct model rain prediction and 6.7 days for convergence systems predicted by ECMWF model.展开更多
基金funded by Fujian Bureau of Surveying,Mapping and Geoinformation(Grant No.2013S17)Natural Science Foundation of China(Grant No.71373130)+2 种基金Non-Profit Research Projects of Fujian Province,China(Grant No2013R04)Key Project of the Department of Science and Technology of Fujian Province,China(Grant No.2012Y4001)supported by the ECMWF’s public web server(http://apps.ecmwf.int/datasets/)
文摘In this study, surface air temperature from 75 meteorological stations above 3000 m on the Tibetan Plateau are applied for evaluation of the European Centre for Medium-Range Weather Forecasts(ECMWF) third-generation reanalysis product ERA-Interim in the period of 1979-2010. High correlations ranging from 0.973 to 0.999 indicate that ERA-Interim could capture the annual cycle very well. However, an average root-meansquare error(rmse) of 3.7°C for all stations reveals that ERA-Interim could not be applied directly for the individual sites. The biases can be mainly attributed to the altitude differences between ERA-Interim grid points and stations. An elevation correction method based on monthly lapse rates is limited to reduce the bias for all stations. Generally, ERA-Interim captured the Plateau-Wide annual and seasonal climatologies very well. The spatial variance is highly related to the topographic features of the TP. The temperature increases significantly(10°C- 15°C) from the western to the eastern Tibetan Plateau for all seasons, in particular during winter and summer. A significant warming trend(0.49°C/decade) is found over the entire Tibetan Plateau using station time series from 1979-2010. ERA-Interim captures the annual warming trend with an increase rate of 0.33°C /decade very well. The observation data and ERA-Interim data both showed the largest warming trends in winter with values of 0.67°C/decade and 0.41°C/decade, respectively. We conclude that in general ERA-Interim captures the temperature trends very well and ERA-Interim is reliable for climate change investigation over the Tibetan Plateau under the premise of cautious interpretation.
基金supported by the R&D Special Fund for Public Welfare Industry (Meteorology) (Grant No. GYHY201306013)
文摘Atmospheric winds from observations and medium-range weather forecast model predictions can be physically decomposed as daily climate wind,planetary-scale anomalous wind,and synoptic-scale anomalous wind.The 850 hPa synoptic-scale anomalous winds were extracted from the numerical model outputs of the European Centre for Medium-Range Weather Forecasts(ECMWF) and the NCEP Global Forecast System(GFS).The results showed that most rain bands in eastern China in 2010 were located along the anomalous convergence lines.To predict the major rain bands by these convergence lines in 2010,the accuracies of the ECMWF products were 100%,85%,and 15% for leading 3,6,and 9 days,while the GFS products showed 53%,15%,and 6% accuracies,respectively.In comparison of the regional heavy rainfalls between observation and the ECMWF model prediction,the useful leading information was about 3.1 days for direct model rain prediction and 6.7 days for convergence systems predicted by ECMWF model.
