A Study of Coupling Parameter Estimation Implemented by 4D-Var and EnKF with a Simple Coupled System

被引：8

作者：

Han, Guijun ^{[1
]}

Wu, Xinrong ^{[1
]}

Zhang, Shaoqing ^{[2
]}

Liu, Zhengyu ^{[3
,4
,5
]}

Navon, Ionel Michael ^{[6
]}

Li, Wei ^{[1
]}

机构：

[1] State Ocean Adm, Natl Marine Data & Informat Serv, Key Lab Marine Environm Informat Technol, Tianjin 300171, Peoples R China

[2] Princeton Univ, NOAA, Geophys Fluid Dynam Lab, Princeton, NJ 08542 USA

[3] Univ Wisconsin, Ctr Climate Res, Madison, WI 53706 USA

[4] Univ Wisconsin, Dept Atmospher & Ocean Sci, Madison, WI 53706 USA

[5] Peking Univ, Lab Ocean Atmosphere Studies, Beijing 100871, Peoples R China

[6] Florida State Univ, Dept Comp Sci, Tallahassee, FL 32306 USA

来源：

ADVANCES IN METEOROLOGY | 2015年 / 2015卷

基金：

美国国家科学基金会;

关键词：

ENSEMBLE KALMAN FILTER; ADAPTIVE COVARIANCE INFLATION; VARIATIONAL DATA ASSIMILATION; SEQUENTIAL DATA ASSIMILATION; MEMORY BUNDLE METHOD; OPERATIONAL IMPLEMENTATION; CLIMATE ESTIMATION; ADJUSTMENT; ATMOSPHERE; IMPACT;

D O I：

10.1155/2015/530764

中图分类号：

P4 [大气科学（气象学）];

学科分类号：

0706 ; 070601 ;

摘要：

Coupling parameter estimation (CPE) that uses observations to estimate the parameters in a coupled model through error covariance between variables residing in different media may increase the consistency of estimated parameters in an air-sea coupled system. However, it is very challenging to accurately evaluate the error covariance between such variables due to the different characteristic time scales at which flows vary in different media. With a simple Lorenz-atmosphere and slab ocean coupled system that characterizes the interaction of two-timescale media in a coupled "climate" system, this study explores feasibility of the CPE with four-dimensional variational analysis and ensemble Kalman filter within a perfect observing system simulation experiment framework. It is found that both algorithms can improve the representation of air-sea coupling processes through CPE compared to state estimation only. These simple model studies provide some insights when parameter estimation is implemented with a coupled general circulation model for improving climate estimation and prediction initialization.

引用

页数：16

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