江西区域多元变量背景误差协方差特征分析
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摘要
江西省暴雨灾害频繁发生,改善同化系统性能是提高数值天气预报水平的有效手段,构建合理的背景误差协方差是做好资料同化的关键工作。基于WRF模式的江西区域一个月控制预报为样本,计算得到多元变量相关的背景误差协方差,分析其平衡约束特征、特征值、特征向量以及特征长度尺度。结果表明,江西区域模式层中的低层和高层风场辐合、辐散分量的作用更大,各个变量对水汽场的贡献也集中在低层和高层,其中温度场起主导作用;模式层高层温度场的模拟效果偏差,各个变量的垂直相关性较大;相较于风场,温度场和水汽场在水平方向影响范围小,具有较强的局地性。
Heavy rainstorms occurred frequently in Jiangxi province.Ameliorated performance in the assimilation system was an effective way to improve the numerical weather prediction(NWP).A reasonable background error covariance(BE)modeling was significant to obtain a good data assimilation result.The multivariate background error covariance(MBE)was calculated based on the one-month forecast in Jiangxi province,and the major parameters of BE,such as correlation coefficients,eigenvalues,eigen-vectors and eigen-length scales were compared and analyzed.Results indicated that the convergence and divergence of wind field played a more important role at bottom and top of the model,where each variable made a significant contribution to the water vapor field,especially the temperature field.In addition,the temperature field simulation at the top of model was not satisfactory and the vertical correlation among each variable was relatively strong.The influence of temperature and water vapor field was smaller than that of wind field in the horizontal lengthscales,which presented strong local features.
Heavy rainstorms occurred frequently in Jiangxi province.Ameliorated performance in the assimilation system was an effective way to improve the numerical weather prediction(NWP).A reasonable background error covariance(BE)modeling was significant to obtain a good data assimilation result.The multivariate background error covariance(MBE)was calculated based on the one-month forecast in Jiangxi province,and the major parameters of BE,such as correlation coefficients,eigenvalues,eigen-vectors and eigen-length scales were compared and analyzed.Results indicated that the convergence and divergence of wind field played a more important role at bottom and top of the model,where each variable made a significant contribution to the water vapor field,especially the temperature field.In addition,the temperature field simulation at the top of model was not satisfactory and the vertical correlation among each variable was relatively strong.The influence of temperature and water vapor field was smaller than that of wind field in the horizontal lengthscales,which presented strong local features.
引文
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Lorenc A C,Ballard S P,Bell R S,et al.2000.The Met.Office global three-dimensional variational data assimilation scheme[J].Quart J Roy Meteor Soc,126(570):2991-3012.
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孙素琴,许爱华,郑婧,等.2016.江西省汛期暴雨时空分布及区域性暴雨分区[J].气象与减灾研究,39(2):90-97.Sun S Q,Xu AH,Zheng J,et al.2016.The regionalization and spatial-temporal characteristics of the torrential-rain in Jiangxi province during the flood season[J].Meteor Disaster Reduction Res,39(2):90-97.(in Chinese)
Wang X,Barker D M,Snyder C,et al.2008.A hybrid ETKF-3DVAR data assimilation scheme for the WRF model.Part II:Real observation experiments[J].Mon Wea Rev,136(12):5132-5147.
Barker D M,Huang W,Guo Y R,et al.2004.A three-dimensional variational data assimilation system for MM5[J].Mon Wea Rev,132(4):897-914.
Berre L,Desroziers G.2010.Filtering of background error variances and correlations by local spatial averaging:A review[J].Mon Wea Rev,138(10):3693-3720.
Chen Y,Rizvi S R,Huang X Y,et al.2013.Balance characteristics of multivariate background error covariances and their impact on analyses and forecasts in tropical and Arctic regions[J].Meteor Atmos Phys,121(1):79-98.
Chen Y,Xia X,Min J,et al.2016.Balance characteristics of multivariate background-error covariance for rainy and dry seasons and their impact on precipitation forecasts of two rainfall events[J].Meteor Atmos Phy,128(5):579-600.
曹小群,黄思训,张卫民,等.2008.区域三维变分同化中背景误差协方差的模拟[J].气象科学,28(1):8-14.Cao X C,Huang SX,Zhang W M,et al.2008.Modeling background error covariance in regional 3DVAR[J].Scientia Meteor Sinica,28(1):8-14.(in Chinese)
陈耀登,赵幸,闵锦忠,等.2015.青藏高原和华东地区背景误差协方差特征的对比研究[J].大气科学学报,38(5):650-657.Chen Y D,Zhao X,Min J Z,et al.2015.Comparative analysis of characteristics for background error covariances in East-China and Plateau region[J].Trans Atmos Sci,38(5):650-657.(in Chinese)
Dance S L.2004.Issues in high resolution limited area data assimilation for quantitative precipitation forecasting[J].Physica D:Nonlinear Phenomena,196(1):1-27.
Derber J C,Bouttier F.1999.A reformulation of the background-error covariance in the ECMWF global data assimilation system[J].Tellus,51(2):195-221.
范水勇,张朝林,仲跻芹.2006.MM5三维变分系统在北京地区冷暖季背景场误差的对比分析[J].高原气象,25(5):855-861.Fan S Y,Zhang C L,Zhong J Q.2006.Contrast analysis of background error of MM5 3DVAR system in cold and warm seasons in Beijing[J].Plateau Meteor,25(5):855-861.(in Chinese)
龚建东,魏丽,陶士伟,等.2006a.全球资料同化中误差协方差三维结构的准确估计与应用Ⅰ:观测空间协方差的准确估计[J].气象学报,64(6):669-683.Gong J D,Wei L,Tao S W,et al.2006a.Accurate estimate and application of 3-D error covariance structures in global data assimilation.partⅠ:Accurate estimation of error covariance in observation space[J].Acta Meteor Sinica,64(6):669-683.(in Chinese)
龚建东,赵刚.2006b.全球资料同化中误差协方差三维结构的准确估计与应用Ⅱ:背景误差协方差调整与数值试验分析[J].气象学报,64(6):684-698.Gong J D,Zhang G.2006b.Accurate estimate and application of 3-D error covariance structures in global data assimilation.partⅡ:Background error covariance structure adjustments and numerical experiments[J].Acta Meteor Sinica,64(6):684-698.(in Chinese)
Lorenc A C,Ballard S P,Bell R S,et al.2000.The Met.Office global three-dimensional variational data assimilation scheme[J].Quart J Roy Meteor Soc,126(570):2991-3012.
Parrish D F,Derber J C.1992.The national meteorological center's spectral statistical-interpolation analysis system[J].Mon Wea Rev,120(8):1747-1763.
Pu Z,Zhang S,Wang M,et al.2016.Influence of the self-consistent regional ensemble background error covariance on hurricane inner-core data assimilation with the GSI-based hybrid system for HWRF[J].J Atmos Sci,73(12):4911-4925.
孙素琴,许爱华,郑婧,等.2016.江西省汛期暴雨时空分布及区域性暴雨分区[J].气象与减灾研究,39(2):90-97.Sun S Q,Xu AH,Zheng J,et al.2016.The regionalization and spatial-temporal characteristics of the torrential-rain in Jiangxi province during the flood season[J].Meteor Disaster Reduction Res,39(2):90-97.(in Chinese)
Wang X,Barker D M,Snyder C,et al.2008.A hybrid ETKF-3DVAR data assimilation scheme for the WRF model.Part II:Real observation experiments[J].Mon Wea Rev,136(12):5132-5147.