程丛兰,陈明轩,王建捷,高峰,杨汉贤. 2013. 基于雷达外推临近预报和中尺度数值预报融合技术的短时定量降水预报试验[J]. 气象学报, 71(3):397-415, doi:10.11676/qxxb2013.041
基于雷达外推临近预报和中尺度数值预报融合技术的短时定量降水预报试验
Short-term quantitative precipitation forecast experiments based on blending of nowcasting with numerical weather prediction
投稿时间:2012-11-12  修订日期:2013-02-17
DOI:10.11676/qxxb2013.041
中文关键词:  定量降水预报  融合  中尺度数值预报  临近预报
英文关键词:Quantitative precipitation forecast  Blending  Mesoscale numerical weather prediction  Nowcast
基金项目:国家自然科学基金(41105024和41075036);北京市科技计划课题(Z090506016609001)资助.
作者单位
程丛兰 中国气象局北京城市气象研究所, 北京, 100089 
陈明轩 中国气象局北京城市气象研究所, 北京, 100089 
王建捷 中国气象局数值预报中心, 北京, 100081 
高峰 中国气象局北京城市气象研究所, 北京, 100089 
杨汉贤 香港天文台, 香港, 999077 
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中文摘要:
      为克服目前中尺度数值模式在对流尺度定量降水短时预报方面的不足,弥补基于“外推”的临近预报技术在2h以上定量降水预报能力方面的缺陷,研究设计了一种基于“外推”临近预报技术和中尺度数值模式的定量降水预报(QPF)融合技术方案,并进行了试验应用.该方案首先基于雷达探测和自动气象站观测的定量降水估计(QPE)结果,对中尺度数值模式输出的定量降水预报在谱空间进行相位校正,分析计算出数值预报和观测的偏差,导出一个附加的数值预报校正场;其次,根据数值预报校正场满足一定时间变化分布的特征,调整相应时段的数值预报降水区域和强度;最后,利用双曲正切线权重函数,对校正后的数值模式定量降水预报和基于临近预报技术的定量降水预报进行融合,融合权重根据典型环流特征动态变化.融合后的定量降水预报在前1-2h表现出主要依赖“外推”临近预报结果,之后随着融合权重的变化,数值预报对融合结果的贡献逐渐加大,直至融合后5-6h占主导地位.通过对京津冀地区2011年夏季5个及2012年夏季2个典型强降水个例的80次预报试验及其检验,表明融合后的0-6h定量降水预报结果改进较为明显,总体优于单独的临近预报技术或者中尺度数值预报模式的结果.
英文摘要:
      In order to overcome the deficiency of the quantitative precipitation forecast (QPF) by a mesoscale numerical weather prediction (NWP) model for the very short range at connective scales and the vanishingly low skill of radar-based rainfall now castings beyond the first couple of hours, a QPF scheme to blend these two sources has been developed.It consists of the following three major steps.Firstly, a phase correction technique is applied to the NWP model QPF to correct their systematic timing or location errors by comparing to the corresponding quantitative precipitation estimation (QPE) derived from the radar reflectivity and automatic raingauge data.Secondly, an intensity calibration technique is applied to the phase-corrected model QPF to adjust its intensity so that the calibrated intensity distribution can match the actual distribution calculated from QPE.Thirdly, the blended QPF is obtained as a weighted average between the radar-based nowcast and the phase-corrected intensity-adjusted model QPF with the weights at the different lead times assigned according to a parameterized hyperbolic tangent funetion.Such parameters can vary dynamically according to an index that could quantify the skill of extrapolative nowcast relative to the model QPF and,such an index is found to be different for the different precipitation types.In general,higher weights are given to nowcast in the couple of hours.At about 3 hours and beyond,higher weights are given to model QPF as the now-cast skill drops.This blending scheme was applied to five typical heavy rain cases in 2011 and two in 2012 over the Bcijing-Tianjin-Hebei region with about eighty tests done.The QPF verification results indicated that the performance of the blended QPF was significantly improved in the 0-6 forecast range with the overall forecast skill generally higher than either radar-based nowcast or model QPF taken individually.Given such encouraging results, the present blending scheme is expected to be promising as an effective tool when deployed for operation.
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