|本期目录/Table of Contents|

[1]郭雅凯,王国杰,沈菲菲,等.两类订正方案在集合均方根滤波土壤湿度同化中的对比研究[J].江苏农业科学,2018,46(12):210-218.
 Guo Yakai,et al.Comparison of two types of correction schemes in soil moisture assimilation of set root mean square filter[J].Jiangsu Agricultural Sciences,2018,46(12):210-218.
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两类订正方案在集合均方根滤波土壤
湿度同化中的对比研究
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《江苏农业科学》[ISSN:1002-1302/CN:32-1214/S]

卷:
第46卷
期数:
2018年第12期
页码:
210-218
栏目:
资源与环境
出版日期:
2018-06-20

文章信息/Info

Title:
Comparison of two types of correction schemes in soil moisture assimilation of set root mean square filter
作者:
郭雅凯1 王国杰2 沈菲菲3 闵锦忠1
1.南京信息工程大学大气科学学院,江苏南京 210044; 2.南京信息工程大学地理与遥感学院,江苏南京 210044;
3.南京信息工程大学大气物理学院,江苏南京 210044
Author(s):
Guo Yakaiet al
关键词:
集合均方根滤波土壤湿度观测订正模式订正融合同化方案
Keywords:
-
分类号:
S152.7
DOI:
-
文献标志码:
A
摘要:
利用Noah陆面模式,基于集合均方根滤波(ensemble square-root filter,简称ENSRF)算法,结合观测和模式2类订正方法,通过构建多个融合同化方案,进行土壤湿度同化研究。其中,模式订正采用粒子群优化算法估计模式参数,观测订正则将观测季节性尺度的特征调整到与模式气候态相当的水平。结果表明,观测订正能够有效减少观测与模式季节尺度差异,从而间接减少同化中的观测误差,而模式订正则有效减少模式参数在同化中产生的误差;引入观测和模式订正后的同化都要优于原始观测且未订正模式的传统同化方案,而单独引入模式或者观测订正并不能够提供给同化方案最佳误差订正信息;结合尺度化的观测订正和参数优化的模式订正,能够使传统土壤湿度ENSRF估计方案得到最大程度的改善。
Abstract:
-

参考文献/References:

[1]Paul R. Remote-sensing soil moisture using four-dimensional data assimilation[D]. Arizona:The University of Arizona,1996:19-394.
[2]Entekhabi D,Nakamura H,Njoku E G. Solving the inverse problem for soil moisture and temperature profiles by sequential assimilation of multifrequency remotely sensed observations[J]. IEEE Geoscience and Remote Sensing Society,1994,32(2):438-448.
[3]Walker J P,Willgoose G R,Kalma J D. One-dimensional soil moisture profile retrieval by assimilation of near-surface measurements:a simplified soil moisture model and field application[J]. Journal of Hydrometeorology,2001,2(4):356-373.
[4]张生雷,谢正辉,田向军,等. 基于土壤水模型及站点资料的土壤湿度同化方法[J]. 地球科学进展,2006,21(12):1350-1362.
[5]Tian X J,Xie Z H,Dai A G. A land surface soil moisture data assimilation system based on the dual-UKF method and the community land model[J]. Journal of Geophysical Research:Atmosopheres 2008,113(D14):1-11.
[6]李昊睿. 陆面数据同化方法的研究[D]. 兰州:兰州大学,2007:1-141.
[7]Tian X J,Xie Z H,Dai A G. An ensemble-based explicit four-dimensional variational assimilation method[J]. Journal of Geophysical Research(Atmospheres),2008,113(D21):1-13.
[8]Tian X J,Xie Z H. An ensemble-based three-dimensional variational assimilation method for land data assimilation[J]. Atmospheric and Oceanic Science Letters,2009,2(3):125-129.
[9]田向军,谢正辉. 基于本征正交分解的显式四维变分同化方法:理论与验证[J]. 中国科学(地球科学),2009,39(4):529-536.
[10]Tian X J,Xie Z H,Dai A G,et al. A dual-pass variational data assimilation framework for estimating soil moisture profiles from AMSR-E microwave brightness temperature[J]. Journal of Geophysical Research(Atmospheres),2009,114(D16):1-12.
[11]韩旭军,李新. 非线性滤波方法与陆面数据同化[J]. 地球科学进展,2008,23(8):813-820.
[12]Reichle R H,Walker J P,Koster R D,et al. Extended versus ensemble kalman filtering for land data assimilation[J]. Journal of Hydrometeorology,2002,3(6):728-740.
[13]Reichle R H,Mclaughlin D B,Entekhabi D. Hydrologic data assimilation with the ensemble kalman filter[J]. Monthly Weather Review,2002,130(1):103-114.
[14]Han X J,Li X. An evaluation of the nonlinear/non-gaussian filters for the sequential data assimilation[J]. Remote Sensing of Environment,2008,112(4):1434-1449.
[15]张生雷,谢正辉,师春香,等. 集合Kalman滤波在土壤湿度同化中的应用[J]. 大气科学,2008,32(6):1419-1430.
[16]Yilmaz M T,Delsole T,Houser P R. Improving land data assimilation performance with a water budget constraint[J]. Journal of Hydrometeorology,2011,12(5):1040-1055.
[17]Yilmaz M T,Delsole T,Houser P R. Reducing water imbalance in land data assimilation:ensemble filtering without perturbed observations[J]. Journal of Hydrometeorology,2012,13(1):413-420.
[18]Yin J F,Zhan X W,Zheng Y F,et al. Enhancing model skill by assimilating SMOPS blended Soil moisture product into Noah land surface model[J]. Journal of Hydrometeorology,2015,16(2):917-931.
[19]田向军,谢正辉. 考虑次网格变异性和土壤冻融过程的土壤湿度同化方案[J]. 中国科学(地球科学),2008,38(6):741-749.
[20]师春香,谢正辉,钱辉,等. 基于卫星遥感资料的中国区域土壤湿度EnKF数据同化[J]. 中国科学(地球科学),2011,41(3):375-385.
[21]米素娟,唐家奎,张显峰,等. 基于VIC模型与集合卡尔曼滤波的土壤水分同化研究[J]. 地理与地理信息科学,2013,29(1):91-95.
[22]黄春林,李新. 陆面数据同化系统的研究综述[J]. 遥感技术与应用,2004,19(5):424-430.
[23]李新,黄春林,车涛,等. 中国陆面数据同化系统研究的进展与前瞻[J]. 自然科学进展,2007,17(2):163-173.
[24]摆玉龙,李新,韩旭军. 陆面数据同化系统误差问题研究综述[J]. 地球科学进展,2011,26(8):795-804.
[25]Reichle R H,Koster R D,Dong J R,et al. Global soil moisture from satellite observations,land surface models,and ground data:implications for data assimilation[J]. Journal of Hydrometeorology,2004,5(3):430-442.
[26]Crow W T,Koster R D,Reichle R H,et al. Relevance of time-varying and time-invariant retrieval error sources on the utility of spaceborne soil moisture products[J]. Geophysical Research Letters,2005,32(24):1064-1067.
[27]de Lannoy G J M,Houser P R,Pauwels V R N,et al. State and bias estimation for soil moisture profiles by an ensemble kalman filter:effect of assimilation depth and frequency[J]. Water Resources Research,2007,43(6):813-816.
[28]de Lannoy G J M,Reichle R H,Houser P R,et al. Correcting for forecast bias in soil moisture assimilation with the ensemble kalman filter[J]. Water Resources Research,2007,43(9):2363-2367.
[29]Reichle R H,Koster R D,Liu P,et al. Comparison and assimilation of global soil moisture retrievals from the advanced microwave scanning radiometer for the earth observing system (amsr‐e) and the scanning multichannel microwave radiometer (SMMR)[J]. Journal of Geophysical Research(Atmospheres),2007,112(D9):139-155.
[30]Crow W T,Wood E F,Pan M. Multiobjective calibration of land surface model evapotranspiration predictions using streamflow observations and spaceborne surface radiometric temperature retrievals[J]. Journal of Geophysical Research(Atmospheres),2003,108(D23):2173-2181.
[31]Yapo P. A multiobjective global optimization algorithm with application to calibration of hydrologic models[D]. Arizona:The University of Arizona,1996:1-220.
[32]Liu Y. Parameter estimations for locally coupled land Surface-Atmosphere models[D]. Arizona:The University of Arizona,2003:1-240.
[33]Hogue T S,Bastidas L,Gupta H,et al. Evaluation and transferability of the Noah land surface model in semiarid environments[J]. Journal of Hydrometeorology,2005,6(1):68-84.
[34]Rosero E,Yang Z L,Gulden L E,et al. Evaluating enhanced hydrological representations in Noah LSM over transition zones:implications for model development[J]. Journal of Hydrometeorology,2009,10(3):600-622.
[35]Yang K,Watanabe T,Koike T,et al. Auto-calibration system developed to assimilate AMSR-E data into a land surface model for estimating soil moisture and the surface energy budget[J]. Journal of the Meteorological Society of Japan,2007,85A(2):229-242.
[36]Yang K,Zhu L,Chen Y Y,et al. Land surface model calibration through microwave data assimilation for improving soil moisture simulations[J]. Journal of Hydrology,2016,533:266-276.
[37]贾炳浩,谢正辉,田向军,等. 基于微波亮温及集合Kalman滤波的土壤湿度同化方案[J]. 中国科学(地球科学),2010,40(2):239-251.
[38]Liu Y Q,Gupta H V. Uncertainty in hydrologic modeling:toward an integrated data assimilation framework[J]. Water Resources Research,2007,43(7):126.
[39]Kumar S V,Reichle R H,Harrison K W,et al. A comparison of methods for a priori bias correction in soil moisture data assimilation[J]. Water Resources Research,2012,48(3):1346-1346.
[40]Whitaker J S,Hamill T M. Ensemble data assimilation without perturbed observations[J]. Monthly Weather Review,2002,130(7):1913-1924.
[41]Eberhart R C,Shi Y H. Particle swarm optimization:development,applications and resources[C]// Proceedings of the IEEE Congress on Evolutionary Computation,South Korea:Seoul,2001.
[42]Zhang S W,Liu Y H,Zhang W D. Ensemble square root filter assimilation of near-surface soil moisture and reference-level observations into a coupled land surface-boundary layer model[J]. Acta Meteorologica Sinica,2013,27(4):541-555.
[43]Chen F,Duhia J. Coupling and advanced land surface hydrology model with the Penn State-NCAR MM5 modeling system part Ⅰ:model implementation and sensitivity[J]. Monthly Weather Review, 2001,129(4):569-585.
[44]Schaake J C,Koren V I,Duan Q Y,et al. Simple water balance model for estimating runoff at different spatial and temporal scales[J]. Journal of Geophysical Research:Atmospheres,1996,101(D3):7461-7475.
[45]Janji c' Z I. The step-mountain eta coordinate model:Further developments of the convection,viscous sublayer,and turbulence closure schemes[J]. Monthly Weather Review,1994,122(5):927-945.

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备注/Memo

备注/Memo:
收稿日期:2017-01-04
基金项目:国家自然科学基金(编号:41561124014、41375099);江苏省自然科学基金青年科学基金(编号:BK20160954);江苏省北极阁基金(编号:BJG201510、BJG201604)。
作者简介:郭雅凯(1987—),男,河南南阳人,博士,工程师,从事陆面资料同化研究。E-mail:guoyk@nuist.edu.cn。
更新日期/Last Update: 2018-06-20