Toward a strongly coupled assimilation in the Earth System Prediction Capability system

Author:

Yaremchuk M.1ORCID,Barron C. N.1,Crawford W.2,DeHaan C.1,Rowley C.1,Ruston B.3,Townsend T.1

Affiliation:

1. Naval Research Laboratory Stennis Space Center Hancock County Mississippi USA

2. Naval Research Laboratory Monterrey California USA

3. Joint Center for Satellite Data Assimilation Boulder Colorado USA

Abstract

AbstractWe assess a possibility to efficiently represent the strongly coupled increment in an ocean–atmosphere coupled data assimilation (DA) system by applying an iterative procedure involving uncoupled solvers and the weakly coupled analysis as a first guess approximation to the strongly coupled increment. Using the output of the ensemble‐based weakly coupled DA system, we explore convergence of the approximations to the strongly coupled DA solution by applying the uncoupled solver to a sequence of innovation vectors at various spacetime locations over the global ocean grid. The results demonstrate that, in general, fewer than two iterations are required to approximate the coupled increment in the majority of the locations tested with sufficient (3%) accuracy given the uncertainty of the background error covariance estimated from the limited number of the ensemble members. We assess the impact of data thinning and hybridization of the background error covariance model on the convergence of the iterative approximations to the strongly coupled increment. An empirical relationship between the spectral radius of the expansion matrix and convergence rate is obtained.

Funder

Office of Naval Research

Publisher

Wiley

Subject

Atmospheric Science

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3