Wang Huijun, Chen Lijuan, Li Weijing, Zhang Peiqun, Liu Luliu. 2007: PREDICTABILITY OF DERF ON MONTHLY MEAN TEMPERATURE ANDPRECIPITATION OVER CHINA. Acta Meteorologica Sinica, (5): 725-732. DOI: 10.11676/qxxb2007.068
Citation: Wang Huijun, Chen Lijuan, Li Weijing, Zhang Peiqun, Liu Luliu. 2007: PREDICTABILITY OF DERF ON MONTHLY MEAN TEMPERATURE ANDPRECIPITATION OVER CHINA. Acta Meteorologica Sinica, (5): 725-732. DOI: 10.11676/qxxb2007.068

PREDICTABILITY OF DERF ON MONTHLY MEAN TEMPERATURE AND PRECIPITATION OVER CHINA

  • The predictability of monthly mean temperature and precipitation over China was spatially/temporally analyzed by using the 160 station monthly temperature and rainfall observation data from 1951 to 2005 and the hindcast experiment products of Dynamical Extended Range Forecast of National Climate Center (DERF/NCC) from 1982 to 2005. The persistence forecast was used as a reference in order to assess the skill of the DERF of monthly temperature and precipitation. The skill of the persistence forecast of monthly temperature and precipitation has clear interannual and decadal variations: low skills occurred in the end of spring, the beginning of summer, and autumn. Under the background of climate warming and average rainfall rate increasing, the skill of monthly temperature persistence forecast has significantly improved whereas that of monthly precipitation persistence forecast has slightly decreased since 1982. The DERF/NCC of monthly temperature and precipitation also showed similar interannual and decadal variation characters, but the skill of the DERF/NCC was higher than that of the persistent forecast. The precipitation/temperature predictability of DERF/NCC was low in early spring /August, respectively. The annual root mean square skill scores (RMSSS) of the DERF/NCC relative to persistence forecast for monthly temperature and precipitation were greater than zero which suggests that the DERF/NCC has higher skill than the persistent forecast. At the same time, the interannual variation of precipitation RMSSS indicated a relative improvement in the skill of DERF/NCC. The assessment of spatial distributions of the DERF/NCC and persistent forecast of monthly temperature and precipitation showed that the skill of DERF/NCC is generally higher than that of persistent forecast because the DERF/NCC combined the predictable information both from the external forcing (persistence forecast) and atmospheric interior dynamic processes. The areas where forecast reached the significant test level by the DERF/NCC are usually larger than those by the persistence forecast.
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