典型文献
Identifying the sensitive areas in targeted observation for pre-dicting the Kuroshio large meander path in a regional ocean model
文献摘要：
With the Regional Ocean Modeling System (ROMS), this paper investigates the sensitive areas in targetedobservation for predicting the Kuroshio large meander (LM) path using the conditional nonlinear optimal perturbation approach. To identify the sensitive areas, the optimal initial errors (OIEs) featuring the largest nonlinear evolution in the LM prediction are first calculated; the resulting OIEs are localized mainly in the upper 2500 m over the LM upstream region, and their spatial structure has certain similarities with that of the optimal triggering perturbation. Based on this spatial structure, the sensitive areas are successfully identified, located southeast of Kyushu in the region (29°–32°N, 131°–134°E). A series of sensitivity experiments indicate that both the positions and the spatial structure of initial errors have important effects on the LM prediction, verifying the validity of the sensitive areas. Then, the effect of targeted observation in the sensitive areas is evaluated through observing system simulation experiments. When targeted observation is implemented in the identified sensitive areas, the prediction errors are effectively reduced, and the prediction skill of the LM event is improved significantly. This provides scientific guidance for ocean observations related to enhancing the prediction skill of the LM event.
文献关键词：
中图分类号：
作者姓名：
Xia Liu;Qiang Wang;Mu Mu
作者机构：
School of Mathematics,Zhengzhou University of Aeronautics,Zhengzhou 450046,China;Key Laboratory of Marine Hazards Forecasting of Ministry of Natural Resources,Hohai University,Nanjing 210098,China;College of Oceanography,Hohai University,Nanjing 210098,China;Institute of Atmospheric Sciences,Fudan University,Shanghai 200438,China
文献出处：
引用格式：
[1]Xia Liu;Qiang Wang;Mu Mu-.Identifying the sensitive areas in targeted observation for pre-dicting the Kuroshio large meander path in a regional ocean model)[J].海洋学报（英文版）,2022(02):3-14
A类：
targetedobservation,OIEs
B类：
Identifying,sensitive,areas,Kuroshio,meander,path,regional,ocean,model,With,Regional,Ocean,Modeling,System,ROMS,this,paper,investigates,predicting,LM,using,conditional,nonlinear,optimal,perturbation,approach,To,identify,initial,errors,featuring,largest,evolution,prediction,first,calculated,resulting,localized,mainly,upper,over,upstream,their,spatial,structure,has,certain,similarities,that,triggering,Based,successfully,identified,located,southeast,Kyushu,series,sensitivity,experiments,indicate,both,positions,have,important,effects,verifying,validity,Then,evaluated,through,observing,system,simulation,When,implemented,effectively,reduced,skill,event,improved,significantly,This,provides,scientific,guidance,observations,related,enhancing
AB值：
0.490983
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