亚洲区域AMSR2与SMOS土壤水分产品对比研究
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摘要
遥感反演土壤水分(SM)产品越来越多地应用于农业、气象、水文等研究,而微波土壤水分数据产品的区域适用性分析是其合理使用的必要前提。使用MERRA-2(Modern Era Retrospective-analysis for Research and Applications,Version 2)模拟土壤水分为参考数据,运用传统统计方法(原始数据相关性、距平相关性、偏差以及无偏均方根差)和TC(Triple-Collocation)不确定性误差模型分析的方法,对亚洲区域2012年7月～2016年7月两种被动微波土壤水分SMOS-L3-SM(Soil Moisture and Ocean Salinity,L3)和AMSR2-LPRM-SM(The Advanced Microwave Scanning Radiometer 2,Land Parameter Retrieval Model Product)进行对比评估。结果表明:①空间上SMOS-L3较AMSR2-LPRM数据与参考数据MERRA-2土壤水分的相关性较好,表现为SMOS-L3-SM具有较好的空间连续性,且在亚洲大多数地区有较小的无偏均方根差;②湿季条件下遥感土壤水分与参考值的相关性比干季条件下的相关性更好,且干季出现高纬地区(约>55°)缺失值较多的情况;③两遥感土壤水分的TC误差呈现相似的分布,区域TC平均误差两者均为0.076 m~3/m~3。总之,SMOS-L3-SM和AMSR2-LPRM-SM在空间相关性及TC误差评价方面都具有合理性,为遥感土壤水分在农业、气象、水文等方面的应用提供参考。
Soil Moisture(SM)products derived from satellite missions have been widely applied in agriculture,meteorology,hydrology,and other fields.It is very necessary to assess the reliability of satellite soil moisture products over regional scale before using them.Two passive satellite soil moisture products,obtained from SMOS(the Soil Moisture Ocean Salinity;L3)and AMSR2(the Advanced Microwave Scanning Radiometer 2;LPRM),were evaluated over Asia with reference to MERRA-2(the Modern Era Retrospective-analysis data for Research and Applications,Version 2)simulated products.The evaluation was performed by adopting a classic statistical method(including Pearson correlation(R)for original SM data and anomalies,bias and unbiased root mean square root)and Triple Collocation(TC)approach based on the SMOS-L3 and AMSR-LPRM daily SM products during July 2012～July 2016.The results reveal that:(1)in space,the performance of SMOS-L3-SM is better than AMSR2-LPRM-SM both for the original SM data and anomalies.Because the SMOS-L3-SM performed consistent correlation over Asia and the smaller unbiased root mean squared difference(ubRMSD)of SMOS-L3-SM is found in most parts of Asia;(2)the correlation between satellite and simulated SM is better in the wet season than in the dry season.Additionally there is a quite high probability of a lack of value in high latitude(about >55°)areas in the dry season to appear;(3)SMOS-L3-SM and AMSR2-LPRM-SM have relatively similar TC errors distribution with a mean error of 0.076 m~3/m~3 for both of them.Overall,both SMOS-L3-SM and AMSR2-LPRM-SM give reasonable results on correlation and TC error,thus providing an additional reference for application of soil moisture in agriculture,meteorology,hydrology and other studies.
Soil Moisture(SM)products derived from satellite missions have been widely applied in agriculture,meteorology,hydrology,and other fields.It is very necessary to assess the reliability of satellite soil moisture products over regional scale before using them.Two passive satellite soil moisture products,obtained from SMOS(the Soil Moisture Ocean Salinity;L3)and AMSR2(the Advanced Microwave Scanning Radiometer 2;LPRM),were evaluated over Asia with reference to MERRA-2(the Modern Era Retrospective-analysis data for Research and Applications,Version 2)simulated products.The evaluation was performed by adopting a classic statistical method(including Pearson correlation(R)for original SM data and anomalies,bias and unbiased root mean square root)and Triple Collocation(TC)approach based on the SMOS-L3 and AMSR-LPRM daily SM products during July 2012～July 2016.The results reveal that:(1)in space,the performance of SMOS-L3-SM is better than AMSR2-LPRM-SM both for the original SM data and anomalies.Because the SMOS-L3-SM performed consistent correlation over Asia and the smaller unbiased root mean squared difference(ubRMSD)of SMOS-L3-SM is found in most parts of Asia;(2)the correlation between satellite and simulated SM is better in the wet season than in the dry season.Additionally there is a quite high probability of a lack of value in high latitude(about >55°)areas in the dry season to appear;(3)SMOS-L3-SM and AMSR2-LPRM-SM have relatively similar TC errors distribution with a mean error of 0.076 m~3/m~3 for both of them.Overall,both SMOS-L3-SM and AMSR2-LPRM-SM give reasonable results on correlation and TC error,thus providing an additional reference for application of soil moisture in agriculture,meteorology,hydrology and other studies.
引文
[1] Molero B,Merlin O,Malbeteau Y,et al.SMOS Disaggregated Soil Moisture Product at 1 km Resolution:Processor Overview and First Validation Results[J].Remote Sensing of Environment,2016,180:361-376.
[2] 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.
[3] Wang Zengyan,Wang Jian,Che Tao.Surface Soil Moisture Retrieval from Airborne L-band Microwave Radiometer Data[J].Remote Sensing Technology and Application,2017,32(2):185-194.[王增艳,王建,车涛.遥机载L波段微波辐射计数据反演表层土壤水分研究[J].遥感技术与应用,2017,32(2):185-194.]
[4] Martinez-Fernandez J,Gonzalez-Zamora A,Sanchez N,et al.Satellite Soil Moisture for Agricultural Drought Monitoring:Assessment of the SMOS Derived Soil Water Deficit Index[J].Remote Sensing of Environment,2016,177:277-286.
[5] Guo Ni,Wang Xiaoping.Advances and Developing Opportunities in Remote Sensing of Drought[J].Journal of Arid Meteorology,2015,33(1):1-18.[郭铌,王小平.遥感干旱应用技术进展及面临的技术问题与发展机遇[J].干旱气象,2015,33(1):1-18.]
[6] Bai Yu,Meng Zhiguo,Zhao Ka,et al.Pixel-scalesoil Moisture Monitoring Network and Its Preliminary Validation of L-band Soil Moisture Product[J].Remote Sensing Technology and Application,2018,33(1):78-87.[白瑜,孟治国,赵凯,等.像元尺度土壤水分监测网络及其对L波段土壤水分产品的初步验证结果[J].遥感技术与应用,2018,33(1):78-87.]
[7] Mladenova I,Lakshmi V,Jackson T J,et al.Validation of AMSR-E Soil Moisture Using L-Band Airborne Radiometer Data from National Airborne Field Experiment 2006[J].Remote Sensing of Environment,2011,115(8):2096-2103.
[8] Lin Libin,Bao Yansong,Zuo Quan,et al.Soil Moisture Retrieval over Vegetated Areas based on Sentinel-1 and FY-3C Data[J].Remote Sensing Technology and Application,2018,33(4):750-758.[林利斌,鲍艳松,左泉,等.基于Sentinel-1与FY-3C数据反演植被覆盖地表土壤水分[J].遥感技术与应用,2018,33(4):750-758.]
[9] Dorigo W A,Xaver A,Vreugdenhil M,et al.Global Automated Quality Control of In-situ Soil Moisture Data from the International Soil Moisture Network[J].Vadose Zone Journal,2013,12(3):918-924.
[10] Wu Q S,Liu H X,WangL,et al.Evaluation of AMSR2 Soil Moisture Products over the Contiguous United States Using in Situ Data from the International Soil Moisture Network[J].International Journal of Applied Earth Observation and Geoinformation,2016,45:187-199.
[11] Smith A B,Walker J P,Western A W,et al.The Murrumbidgee Soil Moisture Monitoring Network Data Set[J].Water Resources Research,2012,48(7):7701.
[12] 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):4256-4272.
[13] Al Bitar A,Leroux D,Kerr Y H,et al.Evaluation of SMOS Soil Moisture Products over Continental Us Using the Scan/Snotel Network[J].IEEE Transactions on Geoscience and Remote Sensing,2012,50(5):1572-1586.
[14] Yang Na,Cui Huizhen,Xiang Feng.Validation Study on SMOSL2 Soil Moisture Product on Agricultural Area of China[J].Journal of Henan Polytechnic University:Natural Science Edition,2015,34(2):287-291.[杨娜,崔慧珍,向峰.SMOSL2土壤水分数据产品在我国农区的验证[J].河南理工大学学报:自然科学版,2015,34(2):287-291.]
[15] Lu Zheng,Chai Linna,Zhang Tao,et al.Evaluation of AMSR2 Retrievals Using Observation of Soil Moisture Network on the Upper and Middle Reaches of Heihe River Basin[J].Remote Sensing Technology and Application,2017,32(2):324-337.[陆峥,柴琳娜,张涛,等.AMSR2土壤水分产品在黑河流域中上游的验证[J].遥感技术与应用,2017,32(2):324-337.]
[16] Xiang Yiheng,Zhang Mingmin,Zhang Lanhui,et al.Validation of SMOS Soil Moisture Products on Different VegetationTypes in Qilian Mountain[J].Remote Sensing Technology and Application,2017,32(5):835-843.[向怡衡,张明敏,张兰慧,等.祁连山区不同植被类型上的 SMOS遥感土壤水分产品质量评估[J].遥感技术与应用,2017,32(5):835-843.]
[17] McColl K A,Roy A,Derksen C,et al.Triple Collocation for Binary and Categorical Variables:Application to Validating Landscape Freeze/Thaw Retrievals[J].Remote Sensing of Environment,2016,176:31-42.
[18] Scipal K,Dorigo W,deJeu R,et al.Triple Collocation:A New Tool to Determine the Error Structure of Global Soil Moisture Products[C]//IEEE International Geoscience and Remote Sensing Symposium,2010:4426-4429.
[19] Stoffelen A.Toward the True Near-surface Wind Speed:Error Modeling and Calibration Using Triple Collocation[J].Journal of Geophysical Research-Oceans,1998,103(C4):7755-7766.
[20] Vogelzang J,Stoffelen A,Verhoef A,et al.On the Quality of High-Resolution Scatterometer Winds[J].Journal of Geophysical Research-Oceans,2011,116(C10).doi:https://doi.org/10.1029/2010JC006640.
[21] O'Carroll A G,Eyre J R,Saunders R W.Three-Way Error Analysis between Aatsr,AMSR-E,and In-situ Sea Surface Temperature Observations[J].Journal of Atmospheric and Oceanic Technology,2008,25(7):1197-1207.
[22] Fang H,Wei S,Jiang C,et al.Theoretical Uncertainty Analysis of Global Modis,Cyclopes,and Globcarbon Lai Products Using a Triple Collocation Method[J].Remote Sensing of Environment,2012,124:610-621.
[23] Scipal K,Holmes T,de Jeu R,et al.A Possible Solution for the Problem of Estimating the Error Structure of Global Soil Moisture Data Sets[J].Geophysical Research Letters,2008,35(24):101-106.
[24] Leroux D J,Kerr Y H,Richaume P,et al.Spatial Distribution and Possible Sources of SMOS Errors at the Global Scale[J].Remote Sensing of Environment,2013,133:240-250.
[25] Pierdicca N,Fascetti F,Pulvirenti L,et al.Analysis of Ascat,SMOS,In-situ and Land Model Soil Moisture as a Regionalized Variable over Europe and North Africa[J].Remote Sensing of Environment,2015,170:280-289.
[26] Zhang X,Zhang T,Zhou P,et al.Validation Analysis of Smap and AMSR2 Soil Moisture Products over the United States Using Ground-Based Measurements[J].Remote Sensing,2017,9(2):104.
[27] Chakravorty A,Chahar B R,Sharma O P,et al.A Regional Scale Performance Evaluation of SMOS and ESA-CCI Soil Moisture Products over India with Simulated Soil Moisture from MERRA-Land[J].Remote Sensing of Environment,2016,186:514-527.
[28] Rahmoune R,Ferrazzoli P,Kerr Y H,et al.SMOS Level 2 Retrieval Algorithm over Forests:Description and Generation of Global Maps[J].IEEE Journal of Selected Topics in Applied Earth Observations & Remote Sensing,2013,6(3):1430-1439.
[29] Lievens H,Tomer S K,Al Bitar A,et al.SMOS Soil Moisture Assimilation for Improved Hydrologic Simulation in the Murray Darling Basin,Australia[J].Remote Sensing of Environment,2015,168:146-162.
[30] Draper C,Mahfouf J F,Calvet J C,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):3829-3841.
[31] 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.
[32] dall'Amico J T,Schlenz F,Loew A,et al.First Results of SMOS Soil Moisture Validation in the Upper Danube Catchment[J].IEEE Transactions on Geoscience and Remote Sensing,2012,50(5):1507-1516.
[33] Kerr Y H,Al-Yaari A,Rodriguez-Fernandez N,et al.Overview of SMOS Performance in Terms of Global Soil Moisture Monitoring after Six Years in Operation[J].Remote Sensing of Environment,2016,180:40-63.
[34] Scipal K,Drusch M,Wagner W.Assimilation of a Ers Scatterometer derived Soil Moisture Index in the Ecmwf Numerical Weal-Her Prediction System[J].Advances in Water Resources,2008,31(8):1101-1112.
[35] Liu Y Y,Dorigo W A,Parinussa R M,et al.Trend-Preserving Blending of Passive and Active Microwave Soil Moisture Retrievals[J].Remote Sensing of Environment,2012,123:280-297.
[36] Gruber A,Su C H,Crow W T,et al.Estimating Error Cross-Correlations in Soil Moisture Data Sets Using Extended Collocation Analysis[J].Journal of Geophysical Research Atmospheres,2016,121(3):1208-1219.
[37] Kim S,Liu Y Y,Johnson F M,et al.A Global Comparison of Alternate AMSR2 Soil Moisture Products:Why Do They Differ?[J].Remote Sensing of Environment,2015,161:43-62.
[38] Reichle R H,Liu Q,Koster R D,et al.Land Surface Precipitation in MERRA-2[J].Journal of Climate,2017,30(5):1643-1664.
[39] Sawada Y,Tsutsui H,Koike T,et al.A Field Verification of an Algorithm for Retrieving Vegetation Water Content from Passive Microwave Observations[J].IEEE Transactions on Geoscience and Remote Sensing,2016,54(4):2082-2095.
[40] Konings A G,Piles M,Das N,et al.L-band Vegetation Optical Depth and Effective Scattering Albedo Estimation from SMAP[J].Remote Sensing of Environment,2017,198:460-470.
[41] Chen Y,Yang K,Qin J,et al.Evaluation of SMAP,SMOS,and AMSR2 Soil Moisture Retrievals Against Observations from Two Networks on the Tibetan Plateau[J].Journal of Geophysical Research Atmospheres,2017,122(11):5780-5792.
[42] Sawada Y,Tsutsui H,Koike T,et al.A Field Verification of an Algorithm for Retrieving Vegetation Water Content from Passive Microwave Observations[J].IEEE Transactions on Geoscience and Remote Sensing,2016,54(4):2082-2095.
[43] Albergel C,Dorigo W,Reichle R H,et al.Skill and Global Trend Analysis of Soil Moisture from Reanalyses and Microwave Remote Sensing[J].Journal of Hydrometeorology,2013,14(4):1259-1277.
[2] 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.
[3] Wang Zengyan,Wang Jian,Che Tao.Surface Soil Moisture Retrieval from Airborne L-band Microwave Radiometer Data[J].Remote Sensing Technology and Application,2017,32(2):185-194.[王增艳,王建,车涛.遥机载L波段微波辐射计数据反演表层土壤水分研究[J].遥感技术与应用,2017,32(2):185-194.]
[4] Martinez-Fernandez J,Gonzalez-Zamora A,Sanchez N,et al.Satellite Soil Moisture for Agricultural Drought Monitoring:Assessment of the SMOS Derived Soil Water Deficit Index[J].Remote Sensing of Environment,2016,177:277-286.
[5] Guo Ni,Wang Xiaoping.Advances and Developing Opportunities in Remote Sensing of Drought[J].Journal of Arid Meteorology,2015,33(1):1-18.[郭铌,王小平.遥感干旱应用技术进展及面临的技术问题与发展机遇[J].干旱气象,2015,33(1):1-18.]
[6] Bai Yu,Meng Zhiguo,Zhao Ka,et al.Pixel-scalesoil Moisture Monitoring Network and Its Preliminary Validation of L-band Soil Moisture Product[J].Remote Sensing Technology and Application,2018,33(1):78-87.[白瑜,孟治国,赵凯,等.像元尺度土壤水分监测网络及其对L波段土壤水分产品的初步验证结果[J].遥感技术与应用,2018,33(1):78-87.]
[7] Mladenova I,Lakshmi V,Jackson T J,et al.Validation of AMSR-E Soil Moisture Using L-Band Airborne Radiometer Data from National Airborne Field Experiment 2006[J].Remote Sensing of Environment,2011,115(8):2096-2103.
[8] Lin Libin,Bao Yansong,Zuo Quan,et al.Soil Moisture Retrieval over Vegetated Areas based on Sentinel-1 and FY-3C Data[J].Remote Sensing Technology and Application,2018,33(4):750-758.[林利斌,鲍艳松,左泉,等.基于Sentinel-1与FY-3C数据反演植被覆盖地表土壤水分[J].遥感技术与应用,2018,33(4):750-758.]
[9] Dorigo W A,Xaver A,Vreugdenhil M,et al.Global Automated Quality Control of In-situ Soil Moisture Data from the International Soil Moisture Network[J].Vadose Zone Journal,2013,12(3):918-924.
[10] Wu Q S,Liu H X,WangL,et al.Evaluation of AMSR2 Soil Moisture Products over the Contiguous United States Using in Situ Data from the International Soil Moisture Network[J].International Journal of Applied Earth Observation and Geoinformation,2016,45:187-199.
[11] Smith A B,Walker J P,Western A W,et al.The Murrumbidgee Soil Moisture Monitoring Network Data Set[J].Water Resources Research,2012,48(7):7701.
[12] 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):4256-4272.
[13] Al Bitar A,Leroux D,Kerr Y H,et al.Evaluation of SMOS Soil Moisture Products over Continental Us Using the Scan/Snotel Network[J].IEEE Transactions on Geoscience and Remote Sensing,2012,50(5):1572-1586.
[14] Yang Na,Cui Huizhen,Xiang Feng.Validation Study on SMOSL2 Soil Moisture Product on Agricultural Area of China[J].Journal of Henan Polytechnic University:Natural Science Edition,2015,34(2):287-291.[杨娜,崔慧珍,向峰.SMOSL2土壤水分数据产品在我国农区的验证[J].河南理工大学学报:自然科学版,2015,34(2):287-291.]
[15] Lu Zheng,Chai Linna,Zhang Tao,et al.Evaluation of AMSR2 Retrievals Using Observation of Soil Moisture Network on the Upper and Middle Reaches of Heihe River Basin[J].Remote Sensing Technology and Application,2017,32(2):324-337.[陆峥,柴琳娜,张涛,等.AMSR2土壤水分产品在黑河流域中上游的验证[J].遥感技术与应用,2017,32(2):324-337.]
[16] Xiang Yiheng,Zhang Mingmin,Zhang Lanhui,et al.Validation of SMOS Soil Moisture Products on Different VegetationTypes in Qilian Mountain[J].Remote Sensing Technology and Application,2017,32(5):835-843.[向怡衡,张明敏,张兰慧,等.祁连山区不同植被类型上的 SMOS遥感土壤水分产品质量评估[J].遥感技术与应用,2017,32(5):835-843.]
[17] McColl K A,Roy A,Derksen C,et al.Triple Collocation for Binary and Categorical Variables:Application to Validating Landscape Freeze/Thaw Retrievals[J].Remote Sensing of Environment,2016,176:31-42.
[18] Scipal K,Dorigo W,deJeu R,et al.Triple Collocation:A New Tool to Determine the Error Structure of Global Soil Moisture Products[C]//IEEE International Geoscience and Remote Sensing Symposium,2010:4426-4429.
[19] Stoffelen A.Toward the True Near-surface Wind Speed:Error Modeling and Calibration Using Triple Collocation[J].Journal of Geophysical Research-Oceans,1998,103(C4):7755-7766.
[20] Vogelzang J,Stoffelen A,Verhoef A,et al.On the Quality of High-Resolution Scatterometer Winds[J].Journal of Geophysical Research-Oceans,2011,116(C10).doi:https://doi.org/10.1029/2010JC006640.
[21] O'Carroll A G,Eyre J R,Saunders R W.Three-Way Error Analysis between Aatsr,AMSR-E,and In-situ Sea Surface Temperature Observations[J].Journal of Atmospheric and Oceanic Technology,2008,25(7):1197-1207.
[22] Fang H,Wei S,Jiang C,et al.Theoretical Uncertainty Analysis of Global Modis,Cyclopes,and Globcarbon Lai Products Using a Triple Collocation Method[J].Remote Sensing of Environment,2012,124:610-621.
[23] Scipal K,Holmes T,de Jeu R,et al.A Possible Solution for the Problem of Estimating the Error Structure of Global Soil Moisture Data Sets[J].Geophysical Research Letters,2008,35(24):101-106.
[24] Leroux D J,Kerr Y H,Richaume P,et al.Spatial Distribution and Possible Sources of SMOS Errors at the Global Scale[J].Remote Sensing of Environment,2013,133:240-250.
[25] Pierdicca N,Fascetti F,Pulvirenti L,et al.Analysis of Ascat,SMOS,In-situ and Land Model Soil Moisture as a Regionalized Variable over Europe and North Africa[J].Remote Sensing of Environment,2015,170:280-289.
[26] Zhang X,Zhang T,Zhou P,et al.Validation Analysis of Smap and AMSR2 Soil Moisture Products over the United States Using Ground-Based Measurements[J].Remote Sensing,2017,9(2):104.
[27] Chakravorty A,Chahar B R,Sharma O P,et al.A Regional Scale Performance Evaluation of SMOS and ESA-CCI Soil Moisture Products over India with Simulated Soil Moisture from MERRA-Land[J].Remote Sensing of Environment,2016,186:514-527.
[28] Rahmoune R,Ferrazzoli P,Kerr Y H,et al.SMOS Level 2 Retrieval Algorithm over Forests:Description and Generation of Global Maps[J].IEEE Journal of Selected Topics in Applied Earth Observations & Remote Sensing,2013,6(3):1430-1439.
[29] Lievens H,Tomer S K,Al Bitar A,et al.SMOS Soil Moisture Assimilation for Improved Hydrologic Simulation in the Murray Darling Basin,Australia[J].Remote Sensing of Environment,2015,168:146-162.
[30] Draper C,Mahfouf J F,Calvet J C,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):3829-3841.
[31] 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.
[32] dall'Amico J T,Schlenz F,Loew A,et al.First Results of SMOS Soil Moisture Validation in the Upper Danube Catchment[J].IEEE Transactions on Geoscience and Remote Sensing,2012,50(5):1507-1516.
[33] Kerr Y H,Al-Yaari A,Rodriguez-Fernandez N,et al.Overview of SMOS Performance in Terms of Global Soil Moisture Monitoring after Six Years in Operation[J].Remote Sensing of Environment,2016,180:40-63.
[34] Scipal K,Drusch M,Wagner W.Assimilation of a Ers Scatterometer derived Soil Moisture Index in the Ecmwf Numerical Weal-Her Prediction System[J].Advances in Water Resources,2008,31(8):1101-1112.
[35] Liu Y Y,Dorigo W A,Parinussa R M,et al.Trend-Preserving Blending of Passive and Active Microwave Soil Moisture Retrievals[J].Remote Sensing of Environment,2012,123:280-297.
[36] Gruber A,Su C H,Crow W T,et al.Estimating Error Cross-Correlations in Soil Moisture Data Sets Using Extended Collocation Analysis[J].Journal of Geophysical Research Atmospheres,2016,121(3):1208-1219.
[37] Kim S,Liu Y Y,Johnson F M,et al.A Global Comparison of Alternate AMSR2 Soil Moisture Products:Why Do They Differ?[J].Remote Sensing of Environment,2015,161:43-62.
[38] Reichle R H,Liu Q,Koster R D,et al.Land Surface Precipitation in MERRA-2[J].Journal of Climate,2017,30(5):1643-1664.
[39] Sawada Y,Tsutsui H,Koike T,et al.A Field Verification of an Algorithm for Retrieving Vegetation Water Content from Passive Microwave Observations[J].IEEE Transactions on Geoscience and Remote Sensing,2016,54(4):2082-2095.
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