背景误差协方差变量平衡特征及其对台风同化和预报的影响

构造合理的背景场误差协方差是做好资料同化的关键。分析了背景误差协方差中变量相关关系在台风季节和非台风季节隐含的不同动力平衡特征，并讨论其对台风同化和预报的影响。分析发现，与非台风季节相比，在台风季节温度与非平衡速度势具有更强的动力相关性，拟相对湿度与其他控制变量的相关性也更显著。这些动力相关性在背景场误差中协方差的引入，将在同化分析过程中使得观测信息可以合理地对同化分析场产生影响。台风循环同化和预报的结果验证了对变量平衡特征的分析:背景误差协方差中新平衡关系的建立，对同化和预报有较大的正面影响，尤其是相对湿度和其他控制变量相关的建立，明显改善了台风路径、强度和降水的预报效果。 

BALANCE CHARACTERISTICS OF MULTIVARIATE BACKGROUND ERROR COVARIANCE FOR TYPHOON SEASON AND ITS IMPACT ON TYPHOON DATA ASSIMILATION AND FORECAST

Building a reasonable background error covariance is the key to data assimilation. The different statistical characteristics of the multivariate background error covariance in WRFDA system for typhoon season and non-typhoon season and its impact on the analysis and forecasting of the typhoon "Fitow" (2013) are discussed. The statistical characteristics analysis indicates that compared to non-typhoon season, unbalanced velocity potential and temperature has better dynamic correlation and the correlations of relative humidity and other control variables is larger in typhoon season. Via the correlations introduced in the background error covariance, the observations can reasonably influence the analysis field in data assimilation. The cycle data assimilation and forecast results show that the new correlations built in multivariate background error covariance play an important role in the analysis and forecast of typhoon, and especially the correlations between relative humidity and other control variables obviously improve the analysis and forecast of typhoon track, intensity and precipitation.