YANG Haipeng,CHEN Quanliang,LIN Renping,et al.Satellite Altimetry Data Assimilation in CAS-ESM-C:Benefits for Improving the Simulations of Upper Ocean Temperature[J].Journal of Chengdu University of Information Technology,2019,(06):615-624.[doi:10.16836/j.cnki.jcuit.2019.06.010]
同化卫星高度计观测对CAS-ESM-C上层海洋温度模拟的改进
- Title:
- Satellite Altimetry Data Assimilation in CAS-ESM-C:Benefits for Improving the Simulations of Upper Ocean Temperature
- 文章编号:
- 2096-1618(2019)06-0615-10
- Keywords:
- meteorology; satellite altimetry data assimilation; mean dynamic topography; upper ocean temperature simulations; CAS-ESM-C
- 分类号:
- P456.7
- 文献标志码:
- A
- 摘要:
- 为有效改进中国科学院地球系统模式气候分量系统(CAS-ESM-C)对年际海洋变化信号的模拟,利用集合最优插值同化方法(ensemble optimal interpolation,EnOI)将海表高度(sea surface height, SSH)数据同化入CAS-ESM-C。通过对比3种不同来源的平均动力地形(mean dynamic topography, MDT)数据对SSH同化性能的影响,筛选出针对CAS-ESM-C海洋资料同化最优的MDT。在此基础上,实施了1994-2000年的SSH观测同化试验,检验其对CAS-ESM-C海洋状态模拟的改进效果。结果表明,正是由于海洋上层(温跃层以内)的温度变化与SSH有着较强的动力相关性,同化SSH观测可以显著地改进CAS-ESM-C对海洋上层温度变化、海气耦合循环和物理过程的模拟。0～400 m全球平均的均方根误差能控制在1.0 ℃以内; 温跃层深度附近的改进效果最为显著; 热带太平洋上层海洋热含量的年际变化以及赤道太平洋地区海温年际异常演变明显优于仅同化海表温度(sea surface temperature, SST)的改进效果。由此可以得到,同化SSH改进了CAS-ESM-C对海洋上层年际变率的模拟,为下一步利用CAS-ESM-C开展短期气候预测奠定了基础。
- Abstract:
- With the motivation to improve the simulation of oceanic interannual variations effectively, the sea surface height(SSH)satellite altimetry data was assimilated into CAS-ESM-C by using Ensemble Optimal Interpolation(EnOI).In this study, the best MDT was selected firstly based on its influences on simulation performance. Using the selected MDT,a SSH assimilation experiment was conducted from 1994 to 2000, comparing with a SST assimilation experiment. Comparing with SST assimilation, the SSH assimilation during 0-400 m subsurface temperature showed better performance, the global mean RMSE was lower than 1.0 ℃.The most improvement region was located at the depth around thermocline.The reason was that SSH showed better correlations with the subsurface temperature than SST. Meanwhile,the simulated interannual variations of upper oceanic heat content and Tropical Pacific SST anomalies were largely improved in SSH assimilation, which means that the simulated air-sea coupling and physical process were improved in SSH assimilation. This study showed that the oceanic interannual variability could be largely improved by assimilating SSH rather than SST. This study implied that the SSH assimilation should be considered in short-term climate prediction.
参考文献/References:
[1] Zheng F,Zhu J,Zhang R H.Impact of altimetry data on ENSO ensemble initializations and predictions[J].Geophysical Research Letters,2007,34(13).
[2] FuW,Zhu J,Yan C,et al.Toward a global ocean data assimilation system based on ensemble optimum interpolation:altimetry data assimilation experiment[J].Ocean Dynamics,2009,59(4):587-602.
[3] Cheney RE.Comparison data for SEASAT altimetry in the western North Atlantic[J].Journal of Geophysical Research Oceans, 1982,87(C5):3247-3253.
[4] Hurlburt,HarleyE.The potential for ocean prediction and the role of altimeter data[J].Marine Geodesy,1984,8(1-4):17-66.
[5] Carnes MR,Mitchell J L,Witt P W D.Synthetic temperature profiles derived from Geosat altimetry:Comparison with air-dropped expendable bathythermograph profiles[J].Journal of Geophysical Research Oceans,1990,95(C10).
[6] Oschlies A,Ja1/4rgen Willebrand. Assimilation of Geosat altimeter data into an eddy-resolving primitive equation model of the North Atlantic Ocean[J].Journal of Geophysical Research Oceans,1996,101(C6):14175-14190.
[7] White WB,Tai C K,Holland W R.Continuous assimilation of simulated Geosat altimetric sea level into an eddy-resolving numerical ocean model:2.Referenced sea level differences[J].Journal of Geophysical Research Oceans,1990,95(C3):3235-3251.
[8] XuD,Zhu J,Qi Y,et al.The impact of mean dynamic topography on a sea-level anomaly assimilation in the South China Sea based on an eddy-resolving model[J].Acta Oceanologica Sinica,2012,31(5):11-25.
[9] Vidard A,Balmaseda M,Anderson D.Assimilation of altimeter data in the ECMWF ocean analysis system 3. in "Monthly Weather Review[J].Monthly Weather Review,2008,137(4):1393-1408.
[10] Storto A,Dobricic S,Masina S,et al.Assimilating Along-Track Altimetric Observations through Local Hydrostatic Adjustment in a Global Ocean Variational Assimilation System[J].Monthly Weather Review,2011,139(3):738-754.
[11] YanC,Zhu J,Tanajura C A S.Impacts of mean dynamic topography on a regional ocean assimilation system[J].Ocean Science,2015,11(5).
[12] Jin X Z,Zhang X H, Zhou T J.Fundamenta framework and experiments of the third generation of IAP/LASG world ocean general circulation model[J].Advances in Atmospheric Sciences,1999,16:197-215.
[13] Oleson K,Dai Y,Bonan G,et al.Technical description of the Community Land Model(CLM)[M].2004.
[14] Dickinson R E,Oleson K W,Bonan G,et al.JOURNAL OF CLIMATE VOLUME 19 The Community Land Model and Its Climate Statistics as a Component of the Community Climate System Model[J].Journal of Climate,2005,19(11):2302-2324.
[15] Briegleb B P,Bitz C M,Hunke E C,et al.Scientific description of the sea ice component in the Community Climate System Model[M].2004.
[16] BlackmonM,Boville B,Bryan F,et al.The Community Climate System Model[J].Bulletin of the American Meteorological Society,2001,82(11):2357-2376.
[17] Craig,A P.The New Extensible,High Performance Parallel Coupler for the Community,Climate System Model[J].International Journal of High Performance Computing Applications,2005,19(3):309-327.
[18] Drake JB,Jones P W,Carr G R.Overview of the software design of the CCSM[J]. International Journal of High Performance Computing Applications,2005,19.
[19] SSALTO/DUACS User Handbook:MSLA and(M)ADT Near-Real Time and Delayed Time Products[EB/OL].https:.www.aviso.altimetry.fr/en/data/product-information/updates-and-reprocessing/ssaltoduacs-product-changes-and-updates.html#c10930.
[20] Reynolds R W,Smith T M,Liu C,et al.Daily High-Resolution-Blended Analyses for Sea Surface Temperature[J].Journal of Climate,2010,20(22):5473-5496.
[21] Good SA,Martin M J,Rayner N A. EN4:Quality controlled ocean temperature and salinity profiles and monthly objective analyses with uncertainty estimates[J].Journal of Geophysical Research:Oceans,2013,118(12):6704-6716.
[22] Evensen G.The Ensemble Kalman Filter: theoretical formulation and practical implementation[J].Ocean Dynamics,2003,53(4):343-367.
[23] Oke,P R,G B Brassington,D A Griffin,et al.The Bluelink Ocean Data Assimilation System(BODAS)[J].Ocean Modelling,2007.21(1-2):46-70.
[24] Rio,M H,Schaeffer,P.,Moreaux,G.,Lemoine,J M,Bronner,E.A new Mean Dynamic Topography computed over the global ocean from GRACE data,altimetry and insitu measurements[DB/OL].Poster communication at OceanObs09 symposium,2009.
[25] 杜梦蛟,陈权亮,林壬萍,等.同化Argo海洋廓线观测对CAS-ESM-C的上层海洋温度模拟的改进[J].成都信息工程学院学报,2017,32(3):289-296.
[26] 张学洪,俞永强,宇如聪,等.一个大洋环流模式和相应的海气耦合模式的评估Ⅰ.热带太平洋年平均状态[J].大气科学,2003,27(6):949-970.
相似文献/References:
[1]廖洪涛,肖天贵,魏 微,等.东亚梅雨季低频波波包传播特征[J].成都信息工程大学学报,2019,(02):143.[doi:10.16836/j.cnki.jcuit.2019.02.008]
LIAO Hongtao,XIAO Tiangui,WEI Wei,et al.Low Frequency Wave Packet Propagation
Characteristics in East Asian Meiyu Season[J].Journal of Chengdu University of Information Technology,2019,(06):143.[doi:10.16836/j.cnki.jcuit.2019.02.008]
[2]王雨歌,郑佳锋,朱克云,等.一次西南涡过程的云-降水毫米波云雷达回波特征分析[J].成都信息工程大学学报,2019,(02):172.[doi:10.16836/j.cnki.jcuit.2019.02.011]
WANG Yuge,ZHENG Jiafeng,ZHU Keyun,et al.Analysis of Cloud-Precipitation Echo Characteristics of a Southwest Vortex[J].Journal of Chengdu University of Information Technology,2019,(06):172.[doi:10.16836/j.cnki.jcuit.2019.02.011]
[3]青 泉,罗 辉,陈刚毅.基于L波段秒级探空数据V-3θ图形的四川盆地暴雨预报模型研究[J].成都信息工程大学学报,2019,(02):186.[doi:10.16836/j.cnki.jcuit.2019.02.013]
QING Quan,LUO Hui,CHEN Gangyi.Forecasting Model of Torrential Rain in Sichuan Basin based on V-3θ
Structural Graphs of L-Band Second Level Sounding Data[J].Journal of Chengdu University of Information Technology,2019,(06):186.[doi:10.16836/j.cnki.jcuit.2019.02.013]
[4]吴秋月,华 维,申 辉,等.基于湿位涡与螺旋度的一次西南低涡强降水分析[J].成都信息工程大学学报,2019,(01):63.[doi:10.16836/j.cnki.jcuit.2019.01.013]
WU Qiuyue,HUA Wei,SHEN Hui,et al.Diagnostic Analysis of a Southwest Vortex Rainstormbased on Moist Potential Vorticity and Helicity[J].Journal of Chengdu University of Information Technology,2019,(06):63.[doi:10.16836/j.cnki.jcuit.2019.01.013]
[5]李潇濛,赵琳娜,肖天贵,等.2000-2015年青藏高原切变线统计特征分析[J].成都信息工程大学学报,2018,(01):91.[doi:10.16836/j.cnki.jcuit.2018.01.016]
LI Xiao-meng,ZHAO Lin-na,XIAO Tian-gui,et al.Statistical Characteristics Analysis of the Shear Linein the Qinghai-Tibet Plateau from 2000 to 2015[J].Journal of Chengdu University of Information Technology,2018,(06):91.[doi:10.16836/j.cnki.jcuit.2018.01.016]
[6]喻乙耽,马振峰,范广洲.华西秋雨气候特征分析[J].成都信息工程大学学报,2018,(02):164.[doi:10.16836/j.cnki.jcuit.2018.02.011]
YU Yi-dan,MA Zhen-feng,FAN Guang-zhou.The Analysis of Climatic Feature of Autumn Rainfall in West China[J].Journal of Chengdu University of Information Technology,2018,(06):164.[doi:10.16836/j.cnki.jcuit.2018.02.011]
[7]孙康慧,巩远发.20世纪70年代末云南省雨季降水的突变及原因分析[J].成都信息工程大学学报,2018,(02):177.[doi:10.16836/j.cnki.jcuit.2018.02.012]
SUN Kang-hui,GONG Yuan-fa.Abrupt Change of Precipitation in Rainy Season in YunnanProvince in Late 1970s and its Cause Analysis[J].Journal of Chengdu University of Information Technology,2018,(06):177.[doi:10.16836/j.cnki.jcuit.2018.02.012]
[8]吴树炎,顾建峰,刘海文,等.高原冬季雪深与重庆夏季降水的年际关系研究[J].成都信息工程大学学报,2018,(02):184.[doi:10.16836/j.cnki.jcuit.2018.02.013]
WU Shu-yan,GU Jian-feng,LIU Hai-wen,et al.Interannual Relationship between Winter Snow Depth over TibetanPlateau and Summer Precipitation over Chongqing[J].Journal of Chengdu University of Information Technology,2018,(06):184.[doi:10.16836/j.cnki.jcuit.2018.02.013]
[9]魏 凡,李 超.利用气象雷达信息划设雷暴飞行限制区的方法研究[J].成都信息工程大学学报,2018,(02):205.[doi:10.16836/j.cnki.jcuit.2018.02.016]
WEI Fan,LI Chao.Study on the Method of Setting Up Limited Flying area ofThunderstorm by Using Weather Radar Information[J].Journal of Chengdu University of Information Technology,2018,(06):205.[doi:10.16836/j.cnki.jcuit.2018.02.016]
[10]朱 莉,张腾飞,李华宏,等.云南一次短时强降水过程的中尺度特征及成因分析[J].成都信息工程大学学报,2018,(03):335.[doi:10.16836/j.cnki.jcuit.2018.03.017]
ZHU Li,ZHANG Teng-fei,LI Hua-hong,et al.Analysis on Meso-scale Features and Forming Reasons of a Short TimeIntensive Precipitation Case in Yunnan Province[J].Journal of Chengdu University of Information Technology,2018,(06):335.[doi:10.16836/j.cnki.jcuit.2018.03.017]
备注/Memo
收稿日期:2019-02-25基金项目:国家自然科学基金资助项目(41875108)