Impact of Different Guidances on Sensitive Areas of Targeting Observations Based on the CNOP Method

The conditional nonlinear optimal perturbations (CNOPs) obtained by a fast algorithm are applied to determining the sensitive area for the targeting observation of Typhoon Matsa in 2005 using an operational regional prediction model the Global/Regional Assimilation and PrEdiction System (GRAPES). Through a series of sensitivity experiments, several issues on targeting strategy design are discussed, including the effectivity of different guidances to determine the sensitive area (or targeting area) and the impact of sensitive area size on improving the 24-h forecast. In this study, three guidances are used along with the CNOP to find sensitive area for improving the 24-h prediction of sea level pressure and accumulated rainfall in the verification region. The three guidances are based on winds only; on winds, geopotential height, and specific humidity; and on winds, geopotential height, specific humidity, and observation error, respectively. The distribution and effectivity of the sensitive areas are compared with each other, and the results show that the sensitive areas identified by the three guidances are different in terms of convergence and effectivity. All the sensitive areas determined by these guidances can lead to improvement of the 24-h forecast of interest. The second and third guidances are more effective and can identify more similar sensitive areas than the first one. Further, the size of sensitive areas is changed the same way for three guidances and the 24-h accumulated rainfall prediction is examined. The results suggest that a larger sensitive area can result in better prediction skill, provided that the guidance is sensitive to the size of sensitive areas.