[1] Reichle R H, Entekhabi D, McLaughlin D B. Downscaling of radio brightness measurements for soil moisture estimation: A four-dimensional variational data assimilation approach[J].Water Resources Research, 2001, 37(9): 2 353-2 364. [2] Walker J P, Houser P R. A methodology for initializing soil moisture in a global climate model: Assimilation of near-surface soil moisture observations[J]. Journal of Geophysical Research, 2001, 106(D11): 11 761-11 774. [3] Ni-Meister W. Recent advances on soil moisture data assimilation[J]. Physical Geography, 2008, 29(1): 19-37. [4] Njoku E G, Li L. Retrieval of land surface parameters using passive microwave measurements at 6 to 18 GHz[J]. IEEE Transactions on Geoscience and Remote Sensing, 1999, 37:79-93. [5] McLaughlin D. Recent developments in hydrologic data assimilation[J]. Reviews of Geophysics, 1995, 33(S2): 977-984. [6] Jia B, Xie Z, Tian X, et al. A soil moisture assimilation scheme based on the Ensemble Kalman Filter using microwave brightness temperature[J]. Science in China(Series D), 2009, 52(11): 1 835-1 848. [7] Yang K, Koike T, Kaihotsu I, et al. Validation of a dual-pass microwave land data assimilation system for estimating surface soil moisture in semiarid regions[J]. Journal of Hydrometeorology, 2009, 10(3): 780-793. [8] 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),doi:10.1029/2010WR01026. [9] Jin R, Li X. Improving the estimation of hydrothermal state variables in the active layer of frozen ground by assimilating in situ observations and SSM/I data[J]. Science in China(Series D), 2009, 52(11): 1 732-1 745. [10] Crosson W L, Laymon C A, Inguva R, et al. Assimilating remote sensing data in a surface flux-soil moisture model[J]. Hydrological Processes, 2002, 16(8): 1 645-1 662. [11] Hunt B R, Kostelich E J, Szunyogh I. Efficient data assimilation for spatiotemporal chaos: A local ensemble transform Kalman filter[J]. Physica D: Nonlinear Phenomena, 2007, 230(1): 112-126. [12] 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 Transactions on Geoscience and Remote Sensing, 1994, 32(2): 438-448. [13] Walker J P, Willgoose G R, Kalma J D. One-dimensional soil moisture profile retrival by assimilation of near-surface observations:A comparison of retrival algorithms[J]. Advances in Water Resources, 2001, 24(6): 631-650. [14] Huang C, Li X, Lu L, et al. Experiments of one-dimensional soil moisture assimilation system based on ensemble Kalman filter[J]. Remote Sensing of Environment, 2008, 112(3): 888-900. [15] Reichle R H, Crow W T, Keppenne C L. An adaptive ensemble Kalman filter for soil moisture data assimilation[J]. Water Resources Research, 2008, 44(3),doi:10.1029/2007WR006351. [16] Han X, Li X. An evaluation of the nonlinearnon-Gaussian filters for the sequential data assimilation[J]. Remote Sensing of Environment, 2008, 112(4): 1 434-1 449. [17] Moradkhani H, Hsu K L, Gupta H, et al. Uncertainty assessment of hydrologic model states and parameters: Sequential data assimilation using the particle filter[J]. Water Resources Research, 2005, 41(5),doi:10.1029/2004WR003604. [18] Moradkhani H, Sorooshian S, Gupta H V, et al. Dual state-parameter estimation of hydrological models using ensemble Kalman filter[J]. Advances in Water Resources, 2005, 28(2): 135-147. [19] Moradkhani H, DeChant C M, Sorooshian S. Evolution of ensemble data assimilation for uncertainty quantification using the particle filter-Markov chain Monte Carlo method[J]. Water Resources Research, 2012, 48(12),doi:10.1029/2012 WR012144. [20] Pauwels V, Verhoest N E C, De Lannoy G J M, et al. Optimization of a coupled hydrology-crop growth model through the assimilation of observed soil moisture and leaf area index values using an ensemble Kalman filter[J]. Water Resources Research, 2007, 43(4),doi:10.1029/2006WR004942. [21] Lee J H, Pellarin T, Kerr Y H. Inversion of soil hydraulic properties from the DEnKF analysis of SMOS soil moisture over West Africa[J]. Agricultural and Forest Meteorology, 2014, 188:76-88. [22] Tian X, Xie Z, Dai A. An ensemble-based explicit four-dimensional variational assimilation method[J]. Journal of Geophysical Research: Atmospheres (1984-2012), 2008, 113(D21),doi:10.1029/2008JD010358. [23] Tian X, Xie Z, Dai A, et al. A microwave land data assimilation system: Scheme and preliminary evaluation over China[J]. Journal of Geophysical Research: Atmospheres (1984-2012), 2010, 115(D21),doi:10.1029/2010JD014370. [24] Tian X, Feng X. A non-linear least squares enhanced POD-4DVar algorithm for data assimilation[J]. Tellus A, 2015, 67,doi:10.3402/tellusa.v0725340. [25] Zhang F, Zhang M, Hansen J A. Coupling ensemble Kalman filter with four-dimensional variational data assimilation[J]. Advances in Atmospheric Sciences, 2009, 26(1): 1-8. [26] Zhang M, Zhang F. E4DVar: Coupling an ensemble Kalman filter with four-dimensional variational data assimilation in a limited-area weather prediction model[J]. Monthly Weather Review, 2012, 140(2): 587-600. [27] Zhang F, Zhang M, Poterjoy J. E3DVar: Coupling an ensemble Kalman filter with three-dimensional variational data assimilation in a limited-area weather prediction model and comparison to E4DVar[J]. Monthly Weather Review, 2013, 141(3): 900-917. [28] Ma Jianwen, Qin Sixian. Recent advances and development of data assimilation algorithms[J]. Advances in Earth Science, 2012, 27(7):747-757.[马建文,秦思娴. 数据同化算法研究现状综述[J]. 地球科学进展, 2012, 27(7): 747-757.] [29] Tian Jing, Su Hongbo, Sun Xiaomin, et al. Accuracy test for the application of GDAS data and NOAH land surface model to China[J].Progress in Geography, 2011, 30(11) : 1 422-1 430.[田静,苏红波,孙晓敏,等. GDAS数据和NOAH陆面模式在中国应用的精度检验[J]. 地理科学进展, 2011, 30(11): 1 422-1 430.] [30] Chen F, Dudhia J. Coupling an 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. [31] Ek M B, Mitchell K E, Lin Y, et al. Implementation of Noah land surface model advances in the National Centers for environmental Prediction operational mesoscale Eta model[J]. Journal of Geophysical Research, 2003, 108(D22),doi:10.1029/2002JD003296. [32] Yang Xiaofeng, Lu Qifeng,Yang Zhongdong. Assimilation experiment of LIS based on AMSR-E soil moisture products[J]. Journal of Applied Meteorological Science, 2013, 24(4): 435-445.[杨晓峰,陆其峰,杨忠东. 基于AMSR-E土壤湿度产品的LIS同化试验[J]. 应用气象学报, 2013, 24(4): 435-445.] [33] Bagayoko F, Yonkeu S, Van De Giesen N C. Effect of seasonal dynamics of vegetation cover on land surface models: A case study of NOAH LSM over a savanna farm land in eastern Burkina Faso, West Africa[J]. Hydrology and Earth System Sciences Discussions, 2006, 3(5): 2 757-2 788. [34] Alfieri J G, Niyogi D, Blanken P D, et al. Estimation of the minimum canopy resistance for croplands and grasslands using data from the 2002 international H 2 O Project[J]. Monthly Weather Review, 2008, 136(11): 4 452-4 469. [35] Bonan G B. Land surface model (LSM version 1.0) for Ecological, Hydrological, and Atmospheric Studies: Technical Description and Users Guide. Technical note[R]. Boulder, CO (United States): National Center for Atmospheric Research, Climate and Global Dynamics Div., 1996. [36] Bonan G B, Lawrence P J, Oleson K W, et al. Improving canopy processes in the Community Land Model version 4 (CLM4) using global flux fields empirically inferred from FLUXNET data[J]. Journal of Geophysical Research,2011, 116(G2),doi:10.1029/2010JG001593. [37] Sun Y, Gu L, Dickinson R E. A numerical issue in calculating the coupled carbon and water fluxes in a climate model[J]. Journal of Geophysical Research: Atmospheres, 2012, 117(D22),doi:10.1029/2012JD018059. [38] Mitchell T D, Jones P D. An improved method of constructing a database of monthly climate observations and associated high-resolution grids[J]. International Journal of Climatology, 2005, 25(6): 693-712. [39] Tian Xiangjun, Xie Zhenghui. Consider sub-grid variability and soil freezing and thawing of soil moisture assimilation scheme[J]. Science in China (Serise D), 2008, 38(6): 741-749. [40] Shi C X, Xie Z H, Qian H, et al. China land soil moisture EnKFdata assimilation based on satellite remote sensing data[J]. Science in China (Serise D), 2011, 54(9): 1 430-1 440. [41] Serpetzoglou E, Anagnostou E N, Papadopoulos A, et al. Error propagation of remote sensing rainfall estimates in soil moisture prediction from a land surface model[J]. Journal of Hydrometeorology, 2010, 11(3): 705-720. [42] Hoppe C M, Elbern H, Schwinger J. A variational data assimilation system for soil-atmosphere flux estimates for the Community Land Model (CLM3.5)[J]. Geoscientific Model Development, 2014, 7(3): 1 025-1 036. [43] Sellers P J, Randall D A, Collatz G J, et al. A Revised Land Surface Parameterization(SiB2) for atmospheric GCMs. Part I: Model formulation[J]. Journal of Climate, 1996, 9(4): 676-705. [44] Sellers P J, Tucker C J, Collatz G J, et al. A revised lan Surface Parameterization (SiB2) for atmospheric GCMs. Part II: The Generation of Global Fields of Terrestrial Biophysical Parameters from Satellite Data[J].Journal of Climate,1996, 9(4): 706-737. [45] Huang Chunlin, Li Xin. Experiments of soil moisture data assimilation system based on Ensemble Kalman Filter[J]. Plateau Meteorology, 2006, 25(4): 665-671.[黄春林,李新. 基于集合卡尔曼滤波的土壤水分同化试验[J]. 高原气象, 2006, 25(4): 665-671.] [46] 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:229-242. [47] Gao Z, Chae N, Kim J, et al. Modeling of surface energy partitioning, surface temperature, and soil wetness in the Tibetan prairie using the Simple Biosphere Model 2 (SiB2)[J]. Journal of Geophysical Research, 2004, 109(D6),doi:10.1029/2003JD004089. [48] Fu X, Yu Z, Luo L, et al. Investigating soil moisture sensitivity to precipitation and evapotranspiration errors using SiB2 model and ensemble Kalman filter[J]. Stochastic Environmental Research and Risk Assessment, 2014, 28(3): 681-693. [49] Govind A, Chen J M, Margolis H, et al. A spatially explicit hydro-ecological modeling framework (BEPS-TerrainLab V2.0): Model description and test in a boreal ecosystem in Eastern North America[J]. Journal of Hydrology, 2009, 367(3/4): 200-216. [50] Liu Zhao, Zhou Yanlian, Ju Weimin, et al. Simulation of soil water content in farm lands with the BEPS ecological model[J]. Transactions of the CSAE, 2011, 27(3): 67-72.[刘昭,周艳莲,居为民, 等. 基于BEPS生态模型模拟农田土壤水分动态[J]. 农业工程学报, 2011, 27(3): 67-72.] [51] Wang Jinliang, Qin Qiming, Liu Mingchao, et al. Soil moisture data assimilation based on NDVI optimization[J]. Transactions of the Chinese Society of Agricultural Engineering, 2011, 27(12): 161-167.[王金梁,秦其明,刘明超,等. 基于NDVI优化选择的土壤水分数据同化[J]. 农业工程学报, 2011, 27(12): 161-167.] [52] Zhu L, Chen J M, Qin Q, et al. Optimization of ecosystem model parameters using spatio-temporal soil moisture information[J]. Ecological Modelling, 2009, 220(18): 2 121-2 136. [53] de Lange R, Beck R, Van De Giesen N, et al. Scatterometer-derived soil moisture calibrated for soil texture with a one-dimensional water-flow model[J]. IEEE Transactions on Geoscience and Remote Sensing, 2008, 46(12): 4 041-4 049. [54] Zhang Xiuying, Jiang Hong, Han Ying. Land surface data assimilati on systems and their usage in global change studies[J]. Remote Sensing Information, 2010,(4): 135-143.[张秀英, 江洪, 韩英. 陆面数据同化系统及其在全球变化研究中的应用[J]. 遥感信息, 2010,(4): 135-143.] [55] Rodell M, Houser P R, Jambor U, et al. The global land data assimilation system[J]. Bulletin of the American Meteorological Society, 2004, 85(3): 381-394. [56] Mitchell K E, Lohmann D, Houser P R, et al. The multi-institution North American Land Data Assimilation System (NLDAS): Utilizing multiple GCIP products and partners in a continental distributed hydrological modeling system[J]. Journal of Geophysical Research, 2004, 109(D7),doi:10.1029/2003JD003823. [57] Xia Y L, Sheffield J, Ek M B, et al. Evaluation of multi-model simulated soil moisture in NLDAS-2[J]. Journal of Hydrology, 2014, 512:107-125. [58] Xia Y, Sheffield J, Ek M B, et al. Uncertainties, correlations, and optimal blends of drought indices from the NLDAS multiple land surface model ensemble[J]. Journal of Hydrometeorology, 2014, 15(4): 1 636-1 650. [59] Liu Y, McCabe M, Evans J, et al. Comparison of soil moisture in GLDAS model simulations and satellite observations over the Murray Darling Basin[C]//Proceedings of the International Congress on Modelling and Simulation, 2009. [60] Zawadzki J, Kçdzior M A. Statistical analysis of soil moisture content changes in Central Europe using GLDAS database over three past decades[J]. Central European Journal of Geosciences, 2014, 6(3): 344-353. [61] Li Xia, Gao Yanhong, Wang Wanzhao,et al. Climate change and applicability of GLDAS in the headwater of the Yellow River Basin[J]. Advances in Earth Science, 2014, 29(4): 531-540.[李霞, 高艳红, 王婉昭, 等. 黄河源区气候变化与 GLDAS 数据适用性评估[J]. 地球科学进展, 2014, 29(4): 531-540.] [62] Jacobs C M J, Moors E J, Ter Maat H W, et al. Evaluation of European Land Data Assimilation System (ELDAS) products using in situ observations[J]. Tellus A, 2008, 60 (5): 1 023-1 037. [63] Qi Yuanyuan, Chen Yingying, Shi Jiancheng. Review on European land data assimilation system[J]. Remote Sensing Information, 2007, (4): 93-97.[齐媛媛,陈莹莹,施建成. 欧洲陆面数据同化系统组成,系统设计和原理简介[J]. 遥感信息, 2007, (4): 93-97.] [64] Naeimi V, Bartalis Z, Wagner W. ASCAT soil moisture: An assessment of the data quality and consistency with the ERS Scatterometer heritage[J]. Journal of Hydrometeorology,2009, 10 (2): 555-563. [65] Naeimi V, Bartalis Z, Wagner W. The ASCAT soil moisture product: A review of its specifications, validation results, and emerging applications[J]. Meteorologische Zeitschrift, 2013, 22 (1): 5-33. [66] Bartalis Z, Wagner W, Naeimi V, et al. Initial soil moisture retrievals from the METOP—A Advanced Scatterometer (ASCAT)[J]. Geophysical Research Letters, 2007, 34(20),doi:10.1029/2007GL031088. [67] Bartalis Z, Wagner W, Naeimi V, et al. Assimilation of ASCAT near-surface soil moisture into the SIM hydrological model over France[J]. Hydrology and Earth System Sciences, 2011, 15(12): 3 829-3 841. [68] Albergel C, Rüdiger C, Pellarin T, et al. From near-surface to root-zone soil moisture using an exponential filter: An assessment of the method based on in-situ observations and model simulations[J]. Hydrology and Earth System Sciences Discussions, 2008, 12:1 323-1 337. [69] Albergel C, Rüdiger C, Carrer D, et al. An evaluation of ASCAT surface soil moisture products with in-situ observations in Southwestern France[J]. Hydrology and Earth System Sciences, 2009, 13 (2): 115-124. [70] Brocca L, Melone F, Moramarco T, et al. ASCAT soil wetness index validation through in situ and modeled soil moisture data in central Italy[J]. Remote Sensing of Environment, 2010, 114 (11): 2 745-2 755. [71] Wagner W, Hahn S, Kidd R, et al. The ASCAT soil moisture product: A review of its specifications, validation results, and emerging applications[J]. Meteorologische Zeitschrift, 2013, 22(1): 5-33. [72] Paulik C, Dorigo W, Wagner W, et al. Validation of the ASCAT soil water index using in situ data from the international soil moisture network[J]. International Journal of Applied Earth Observation and Geoinformation, 2014, 30:1-8. [73] Jackson T J, Cosh M H, Bindlish R, et al. Validation of advanced microwave scanning radiometer soil moisture products[J]. IEEE Transactions on Geoscience and Remote Sensing, 2010, 48(12): 4 256-4 272. [74] Sahoo A K, Zhan X, Arsenault K, et al. Cross-Validation of Soil Moisture Data from AMSR-E Using Field Observations and NASA’s Land Data Assimilation System Simulations[Z].American Meteorological Society, 2006. [75] 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, 2007, 112(D9), doi:10.1029/2006JD008033. [76] Brocca L, Hasenauer S, Lacava T, et al. Soil moisture estimation through ASCAT and AMSR-E sensors: An intercomparison and validation study across Europe[J]. Remote Sensing of Environment, 2011, 115 (12): 3 390-3 408. [77] Chen Y, Yang K, Qin J, et al. Evaluation of AMSR-E retrievals and GLDAS simulations against observations of a soil moisture network on the central Tibetan Plateau[J]. Journal of Geophysical Research: Atmospheres, 2013, 118 (10): 4 466-4 475. [78] Kerr Y H, Waldteufel P, Wigneron J P, et al. Soil moisture retrieval from space: The Soil Moisture and Ocean Salinity (SMOS) Mission[J]. IEEE Transactions on Geoscience and Remote Sensing, 2001, 39(8): 1 729-1 735. [79] Muoz-Sabater J, de Rosnay P, Jiménez C, et al. SMOS brightness temperature angular noise: Characterization, filtering, and validation[J]. IEEE Transactions on Geoscience and Remote Sensing, 2014, 52 (9): 5 827-5 839. [80] Zhao L, Yang K, Qin J, et al. The scale-dependence of SMOS soil moisture accuracy and its improvement through land data assimilation in the central Tibetan Plateau[J]. Remote Sensing of Environment, 2014, 152:345-355. [81] Al-Yaari A, Wigneron J P, Ducharne A, et al. Global-scale evaluation of two satellite-based passive microwave soil moisture datasets (SMOS and AMSR-E) with respect to Land Data Assimilation System estimates[J]. Remote Sensing of Environment, 2014, 149:181-195. [82] Al-Yaari A, Wigneron J P, Ducharne A, et al. Global-scale comparison of passive (SMOS) and active (ASCAT) satellite based microwave soil moisture retrievals with soil moisture simulations (MERRA-Land)[J]. Remote Sensing of Environment, 2014, 152:614-626. [83] Chen Shulin, Liu Yuanbo, Wen Zuomin. Satelliteretrieval of soil moisture: An overview[J]. Advances in Earth Science, 2012, 27(11) :1 192-1 203.[陈书林, 刘元波, 温作民. 卫星遥感反演土壤水分研究综述[J]. 地球科学进展, 2012, 27 (11): 1 192-1 203.] [84] Zhang S W, Li D Q, Qiu C J. A multimodel ensemble-based Kalman Filter for the retrieval of soil moisture profiles[J]. Advances in Atmospheric Sciences, 2011, 28(1): 195-206. |