摘要
基于1991 2010年东北地区91站逐月降水资料、NCEP/NCAR再分析资料以及国家气候中心第二代月动力延伸预报模式(BCC_DERF2.0)共20年回报资料,分析了夏季各月影响东北降水的环流型,检验了BCC_DERF2.0对东北各月降水和主要环流系统的预测能力,并建立了东北地区降水的解释应用预测模型。诊断分析显示,东北地区6月降水异常主要受东北冷涡和鄂霍茨克海阻塞高压的影响,7月主要受西太平洋副热带高压(下称西太副高)的影响,而8月主要受西太副高和东北冷涡的影响;模式性能分析显示,BCC_DERF2.0模式对东北南部的个别站点降水趋势有一定的预测能力,对6月偏南风、7月西太副高、8月西太副高和东北冷涡的预测效果较好。在此基础上,提取影响我国东北夏季降水异常的关键环流区的高技巧预测信息,建立线性回归模型,交叉检验显示提高了对8月的降水预测技巧,通过了显著性检验。进一步对比分析发现,BCC_DERF2.0直接输出的20年回报夏季各月东北降水效果好于同期国家气候中心业务发布预报,而利用模式输出的高技巧环流信息建立的东北降水回归预测模型交叉检验效果高于模式直接输出降水预报。因此,基于诊断分析和BCC_DERF2.0模式超前预报时间为10天的高技巧环流信息解释降水,可以明显提高东北夏季月尺度降水的预测能力。
Based on 91 station monthly data, NCEP/NCAR Reanalysis data and monthly dynamic extended range forecast 2.0(BCC_DERF2.0)products from National Climate Center for 1991-2010,the circulation patterns for summer precipitation in Northeast China in each month are analyzed,the prediction skills of precipitation and main circulation systems by BCC_DERF2.0 are tested,and the precipitation prediction regression models are established. Precipitation in June is mainly influenced by Northeast cold vortex and Okhotsk blocking high, while in July mainly by western Pacific subtropical high, and in August by western Pacific subtropical high and Northeast cold vortex. On the analysis of model validation,BCC_DERF2.0 outputs are found to provide skillful predictions for precipitation in a fewsites in Northeast China,and can predict the southerly wind in June,western Pacific subtropical high in July and August and Northeast cold vortex in August well. On the basis of validation for DERF2.0 model products,high-skilled prediction information of key circulation regions for precipitation anomalies in Northeast China is selected,and linear regression models are established. The cross-validation for precipitation regression model for August shows good prediction skill,and the correlation between observation and hindcasts is significant. By comparison, the rawBCC_DERF2.0 precipitation outputs for 1991-2010 in each month showbetter prediction skills than the operational prediction from National Climate Center in the same period, while the prediction skills for cross- validation of the prediction regression models are better than the rawBCC_DERF2.0 precipitation outputs in the corresponding month. The precipitation prediction by high-skilled circulation information from BCC_DERF2.0 10 days ahead of forecast time can improve the prediction ability for summer monthly precipitation in Northeast China.
出处
《高原气象》
CSCD
北大核心
2015年第4期1119-1130,共12页
Plateau Meteorology
基金
国家重点基础研究发展计划项目(2013CB430203)
国家自然科学基金项目(41205039)
公益性行业(气象)科研专项(GYHY201306033)
中国气象局气候研究开放室青年基金
中国气象局短期气候预测创新团队项目
关键词
夏季降水
气候模式
线性回归
解释应用
Summer precipitation
Climate model
Linear regression
Interpretation and application
