A global coupled ensemble data assimilation system using the Community Earth System Model and the Data Assimilation Research Testbed

被引:30
作者
Karspeck, Alicia R. [1 ,4 ]
Danabasoglu, Gokhan [1 ]
Anderson, Jeffrey [1 ]
Karol, Svetlana [2 ]
Collins, Nancy [1 ]
Vertenstein, Mariana [1 ]
Raeder, Kevin [1 ]
Hoar, Tim [1 ]
Neale, Richard [1 ]
Edwards, Jim [1 ]
Craig, Anthony [3 ]
机构
[1] Natl Ctr Atmospher Res, Climate & Global Dynam Lab, POB 3000, Boulder, CO 80307 USA
[2] CIRES, Boulder, CO USA
[3] NCAR, Boulder, CO USA
[4] Jupiter Intelligence, Boulder, CO USA
基金
美国国家科学基金会;
关键词
Community Earth System Model; coupled data assimilation; coupled reanalysis; Data Assimilation Research Testbed; ensemble assimilation; ensemble Kalman filter; modular data assimilation; BACKGROUND ERROR COVARIANCE; UPPER-OCEAN RESPONSE; KALMAN FILTER; SEA-ICE; PART I; REANALYSIS; PREDICTION; INITIALIZATION; FRAMEWORK; SHOCKS;
D O I
10.1002/qj.3308
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
This paper presents a description of the CESM/DART ensemble coupled data assimilation (DA) system based on the Community Earth System Model (CESM) and the Data Assimilation Research Testbed (DART) assimilation software. The CESM/DART should be viewed as a flexible system to support the DA needs of the CESM research community and not as a static reanalysis product. In this implementation of the CESM/DART, conventional insitu observations of the ocean and atmosphere are assimilated into the respective component models of the CESM using a 30-member ensemble adjustment Kalman filter (EAKF). CESM/DART is run in a weakly coupled configuration wherein observations native to each climate system component only directly impact the state vector for that component. Information is passed between components indirectly through the short-term coupled model forecasts that provide the EAKF background ensemble. This system leverages previous ensemble DA development for the Community Atmosphere Model and Parallel Ocean Program models using the DART EAKF. The CESM/DART project is a step towards providing increasingly useful DA capabilities for the CESM research community. Results are presented for our prototype 12-year reanalysis, run from 1970 to mid 1982. Multiple lines of evidence demonstrate that the system is capable of constraining the CESM coupled model to simulate the historical variability of the climate system in the well-observed Northern Hemisphere. A collection of monthly average variables, climate mode indices, observation diagnostics and snapshots of synoptic weather in the ocean and atmosphere are compared to established datasets, showing especially good agreement in the Northern Hemisphere. A discussion of the CESM/DART as a modular, community facility and the benefits and challenges associated with this vision is also included.
引用
收藏
页码:2404 / 2430
页数:27
相关论文
共 102 条
  • [1] A new globally complete monthly historical gridded mean sea level pressure dataset (HadSLP2): 1850-2004
    Allan, Rob
    Ansell, Tara
    [J]. JOURNAL OF CLIMATE, 2006, 19 (22) : 5816 - 5842
  • [2] THE DATA ASSIMILATION RESEARCH TESTBED A Community Facility
    Anderson, Jeffrey
    Hoar, Tim
    Raeder, Kevin
    Liu, Hui
    Collins, Nancy
    Torn, Ryan
    Avellano, Avelino
    [J]. BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY, 2009, 90 (09) : 1283 - 1296
  • [3] Scalable implementations of ensemble filter algorithms for data assimilation
    Anderson, Jeffrey L.
    Collins, Nancy
    [J]. JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY, 2007, 24 (08) : 1452 - 1463
  • [4] Spatially and temporally varying adaptive covariance inflation for ensemble filters
    Anderson, Jeffrey L.
    [J]. TELLUS SERIES A-DYNAMIC METEOROLOGY AND OCEANOGRAPHY, 2009, 61 (01) : 72 - 83
  • [5] Anderson JL, 2003, MON WEATHER REV, V131, P634, DOI 10.1175/1520-0493(2003)131<0634:ALLSFF>2.0.CO
  • [6] 2
  • [7] Anderson JL, 2001, MON WEATHER REV, V129, P2884, DOI 10.1175/1520-0493(2001)129<2884:AEAKFF>2.0.CO
  • [8] 2
  • [9] [Anonymous], 2004, 8 S INTEGRATED OBSER
  • [10] [Anonymous], 2016, Q J ROY METEOR SOC, DOI DOI 10.1002/qj.2629