刘帅,王建捷. 2021. GRAPES_GFS模式全球降水预报的主要偏差特征[J]. 气象学报, (0):-, doi:10.11676/qxxb2021.012
GRAPES_GFS模式全球降水预报的主要偏差特征
The main characteristics of GRAPES_GFS global precipitation forecast deviation
投稿时间:2020-04-14  修订日期:2020-07-30
DOI:10.11676/qxxb2021.012
中文关键词:  GRAPES_GFS全球模式,降水预报,偏差特征
英文关键词:GRAPES_GFS, Precipitation forecast, Model bias
基金项目:中国气象局GRAPES发展专项
作者单位E-mail
刘帅 中国气象科学研究院 liushuai614@126.com 
王建捷 国家气象中心 wangjj@cma.gov.cn 
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中文摘要:
      利用2017年1、4、7、10月“全球降水观测(global precipitation measurement, GPM)计划”每日08-08时的24h累积降水量和逐30min降水量观测产品,从降水量和频率等角度,对同期GRAPES全球模式(GRAPES_GFS)第一(D1)、三(D3)、五天(D5)的全球降水预报性能和偏差特征进行细致评估与分析,其中以低纬暖池和北半球中纬风暴路径区作为关键区进行重点观察,并初步探讨降水预报偏差特征在低纬和中纬明显不同的可能原因。结果显示:(1)GRAPES_GFS的D1-D5预报对全球日降水(量和频率)分布描述合理,准确再现出纬向平均降水(量和频率)的典型特征——降水 “双峰”极大位于南北纬20o之间、次极大位于南北纬40o~50o地区的特征,以及关键区日降水时空演变和降水日循环逐日演变的主要趋势特征。(2)在低纬,纬向平均湿日(≥0.1mm/d)频率预报正偏差很小,但日降水量和强降水日(>25mm/d)频率预报的正偏差明显、偏差极大值“双峰”位置恰是相应观测极大值所在处(南北纬5o~10o);在中纬,纬向平均日降水量预报基本无偏,但明显的湿日降水频率预报正偏差(20%~30%)和强降水日频率负偏差出现在南北纬40o~60o。降水偏差正负分布特征随季节和预报时效基本保持不变、预报均方根误差数倍于平均误差,暗示模式降水预报偏差有系统性、且性能表现波动较大。(3)日循环中,模式在暖池的降水量预报正偏差缘于降水强度预报偏强,降水频率预报的弱负偏差主要与降水落区预报偏小有关;而模式在北半球风暴路径区降水频率预报的正偏差,则是降水落区预报偏大和空报弱降水事件两方面因素造成。(4)模式降水(量和频率)预报偏差特征在低纬和中纬的明显差异性,与模式次网格尺度和网格尺度降水比例失调有关,改进线索指向模式对流参方案中深对流的启动和深对流降水量的处理以及对流参数化方案与云微物理方案的协同问题。
英文摘要:
      The performances of day1 (D1) to day5 (D5) precipitation forecasts of the operational global model system (GRAPES GFS) are evaluated in terms of amount, frequency, and diurnal cycle etc, against observation products of the Global Precipitation Measurement (GPM) data of 4 months (Jan, April, Jul and Oct) of 2017, in which special focus is put on the Warm Pool (WP) in the Western Pacific and the Storm Track in the North Hemisphere (STNH). Results show that: (1) the D1-D5 forecasts reasonably capture the global distributions of precipitation, especially reproduce accurately the typical observed maximum features of global zonal mean precipitation (amount and frequency) between 20oS~20oN and in latitudes of 40o~50o, and also resemble well the daily variation and diurnal cycle of precipitation over the WP and the STNH. (2) In low-latitudes, the “double peaks” of positive forecast biases of the daily precipitation amount and of the heavy rainfall day (>25mm/d) frequency occur in the same locations of observed precipitation maximums, while the positive forecast deviation of wet-day (≥0.1mm/d) frequency is quite small; whereas in mid-latitudes, the forecast of daily precipitation amount is nearly unbiased, but positive deviation of wet-day frequency and negative bias of heavy rainfall day frequency are obvious in latitudes of 40°~60°. There is nearly no change in the bias distribution pattern when deviation values vary a little in different season and increase from D1 to D5, also RMSE is several times of AME, indicating the model natures of systematic errors in precipitation and of variable performance in daily forecast. (3) In terms of diurnal cycle, the positive bias of prediction amount is due to over-prediction in precipitation intensity, and the slight negative deviation of precipitation frequency is because of under-prediction in the rainfall coverage in WP; however, the positive bias of precipitation frequency results from both factors in STNH, the over-prediction of rainfall coverage and the failed forecast of weak precipitation events. (4) The obvious differences of the precipitation (amount and frequency) deviation in low- and mid-latitudes, are related to the incongruity about the proportion of the grid and sub-grid scale precipitation in the model. The clues of model improvement point to the trigger function and process of deep convection precipitation in model cumulus parameterization scheme, and the coordination between the cumulus parameterization scheme and the cloud microphysics scheme.
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