Quality Control and Evaluation of the Observed Daily Data in the North American Soil Moisture Database
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摘要
The North American Soil Moisture Database(NASMD) was initiated in 2011 to assemble and homogenize in situ soil moisture measurements from 32 observational networks in the United States and Canada encompassing more than 1800 stations. Although statistical quality control(QC) procedures have been applied in the NASMD, the soil moisture content tends to be systematically underestimated by in situ sensors in frozen soils, and using a single maximum threshold(i.e., 0.6 m~3 m~(–3)) may not be sufficient for robust QC because of the diverse soil textures in North America. In this study, based on the in situ soil porosity and North American Land Data Assimilation System phase 2(NLDAS-2) Noah soil temperature, the simple automated QC method is revised to supplement the existing QC approach. This revised QC method is first validated based on the assessment at 78 of the Soil Climate Analysis Network(SCAN) stations where the manually checked data are available, and is then applied to all stations in the NASMD to produce a more strict quality-controlled dataset. The results show that the revised automated QC procedure can flag the spurious and erroneous soil moisture measurements for the SCAN stations, especially for those located in high altitudes and latitudes. Relative to station measurements in the original NASMD, the quality-controlled data show a slightly better agreement with the manually checked soil moisture content. It should be noted that this qualitycontrolled dataset may be over-flagged for some valid soil moisture measurements due to potential errors of the soil temperature and soil porosity data, and validation in this study is limited by the availability of benchmark soil moisture data. The updated QC and additional validation will be desirable to boost confidence in the product when highquality data become available in the future.
The North American Soil Moisture Database(NASMD) was initiated in 2011 to assemble and homogenize in situ soil moisture measurements from 32 observational networks in the United States and Canada encompassing more than 1800 stations. Although statistical quality control(QC) procedures have been applied in the NASMD, the soil moisture content tends to be systematically underestimated by in situ sensors in frozen soils, and using a single maximum threshold(i.e., 0.6 m~3 m~(–3)) may not be sufficient for robust QC because of the diverse soil textures in North America. In this study, based on the in situ soil porosity and North American Land Data Assimilation System phase 2(NLDAS-2) Noah soil temperature, the simple automated QC method is revised to supplement the existing QC approach. This revised QC method is first validated based on the assessment at 78 of the Soil Climate Analysis Network(SCAN) stations where the manually checked data are available, and is then applied to all stations in the NASMD to produce a more strict quality-controlled dataset. The results show that the revised automated QC procedure can flag the spurious and erroneous soil moisture measurements for the SCAN stations, especially for those located in high altitudes and latitudes. Relative to station measurements in the original NASMD, the quality-controlled data show a slightly better agreement with the manually checked soil moisture content. It should be noted that this qualitycontrolled dataset may be over-flagged for some valid soil moisture measurements due to potential errors of the soil temperature and soil porosity data, and validation in this study is limited by the availability of benchmark soil moisture data. The updated QC and additional validation will be desirable to boost confidence in the product when highquality data become available in the future.
The North American Soil Moisture Database(NASMD) was initiated in 2011 to assemble and homogenize in situ soil moisture measurements from 32 observational networks in the United States and Canada encompassing more than 1800 stations. Although statistical quality control(QC) procedures have been applied in the NASMD, the soil moisture content tends to be systematically underestimated by in situ sensors in frozen soils, and using a single maximum threshold(i.e., 0.6 m~3 m~(–3)) may not be sufficient for robust QC because of the diverse soil textures in North America. In this study, based on the in situ soil porosity and North American Land Data Assimilation System phase 2(NLDAS-2) Noah soil temperature, the simple automated QC method is revised to supplement the existing QC approach. This revised QC method is first validated based on the assessment at 78 of the Soil Climate Analysis Network(SCAN) stations where the manually checked data are available, and is then applied to all stations in the NASMD to produce a more strict quality-controlled dataset. The results show that the revised automated QC procedure can flag the spurious and erroneous soil moisture measurements for the SCAN stations, especially for those located in high altitudes and latitudes. Relative to station measurements in the original NASMD, the quality-controlled data show a slightly better agreement with the manually checked soil moisture content. It should be noted that this qualitycontrolled dataset may be over-flagged for some valid soil moisture measurements due to potential errors of the soil temperature and soil porosity data, and validation in this study is limited by the availability of benchmark soil moisture data. The updated QC and additional validation will be desirable to boost confidence in the product when highquality data become available in the future.
引文
Anderson,W.B.,B.F.Zaitchik,C.R.Hain,et al.,2012:Towards an integrated soil moisture drought monitor for East Africa.Hydrol.Earth Syst.Sci.,16,2893-2913,doi:10.5194/hess-16-2893-2012.
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Brocca,L.,L.Ciabatta,C.Massari,et al.,2017:Soil moisture for hydrological applications:Open questions and new opportun-ities.Water,9,140,doi:10.3390/w9020140.
Cai,X.T.,Z.-L.Yang,Y.L.Xia,et al.,2014:Assessment of simulated water balance from Noah,Noah-MP,CLM,and VICover CONUS using the NLDAS test bed.J.Geophys.Res.At-mos.,119,13751-13770,doi:10.1002/2014JD022113.
Collow,T.W.,A.Robock,J.B.Basara,et al.,2012:Evaluation of SMOS retrievals of soil moisture over the central United States with currently available in situ observations.J.Geo-phys.Res.Atmos.,117,D09113,doi:10.1029/2011JD017095.
De Lannoy,G.J.M.,and R.H.Reichle,2016:Assimilation of SMOS brightness temperatures or soil moisture retrievals into a land surface model.Hydrol.Earth Syst.Sci.,20,4895-4911,doi:10.5194/hess-20-4895-2016.
Dirmeyer,P.A.,2011:The terrestrial segment of soil moistureclimate coupling.Geophys.Res.Lett.,38,L16702,doi:10.1029/2011GL048268.
Dorigo,W.A.,W.Wagner,R.Hohensinn,et al.,2011:The international soil moisture network:A data hosting facility for global in situ soil moisture measurements.Hydrol.Earth Syst.Sci.,15,1675-1698,doi:10.5194/hess-15-1675-2011.
Dorigo,W.A.,A.Xaver,M.Vreugdenhil,et al.,2013:Global automated quality control of in situ soil moisture data from the international soil moisture network.Vadose Zone J.,12,1-21,doi:10.2136/vzj2012.0097.
El Sharif,H.,J.F.Wang,and A.P.Georgakakos,2015:Modeling regional crop yield and irrigation demand using SMAP type of soil moisture data.J.Hydrometeor.,16,904-916,doi:10.1175/JHM-D-14-0034.1.
Ford,T.W.,and S.M.Quiring,2014:In situ soil moisture coupled with extreme temperatures:A study based on the Oklahoma Mesonet.Geophys.Res.Lett.,41,4727-4734,doi:10.1002/2014GL060949.
Gruhier,C.,P.de Rosnay,S.Hasenauer,et al.,2010:Soil moisture active and passive microwave products:Intercomparison and evaluation over a Sahelian site.Hydrol.Earth Syst.Sci.,14,141-156,doi:10.5194/hess-14-141-2010.
Hallikainen,M.T.,F.T.Ulaby,M.C.Dobson,et al.,1985:Microwave dielectric behavior of wet soil-part 1:Empirical models and experimental observations.IEEE Trans.Geosci.Remote Sens.,GE-23,25-34,doi:10.1109/TGRS.1985.289497.
Holgate,C.M.,R.A.M.De Jeu,A.I.J.M.van Dijk,et al.,2016:Comparison of remotely sensed and modelled soil moisture data sets across Australia.Remote Sens.Environ.,186,479-500,doi:10.1016/j.rse.2016.09.015.
Kishné,A.S.,Y.T.Yimam,C.L.S.Morgan,et al.,2017:Evaluation and improvement of the default soil hydraulic parameters for the Noah land surface model.Geoderma,285,247-259,doi:10.1016/j.geoderma.2016.09.022.
Koster,R.D.,Y.H.Chang,H.L.Wang,et al.,2016:Impacts of local soil moisture anomalies on the atmospheric circulation and on remote surface meteorological fields during boreal summer:A comprehensive analysis over North America.J. Climate,29,7345-7364,doi:10.1175/JCLI-D-16-0192.1.
Kumar,S.V.,C.D.Peters-Lidard,D.Mocko,et al.,2014a:Assimilation of remotely sensed soil moisture and snow depth retrievals for drought estimation.J.Hydrometeor.,15,2446-2469,doi:10.1175/JHM-D-13-0132.1.
Kumar,S.,P.A.Dirmeyer,D.M.Lawrence,et al.,2014b:Effects of realistic land surface initializations on subseasonal to seasonal soil moisture and temperature predictability in North America and in changing climate simulated by CCSM4.J.Geophys.Res.Atmos.,119,13250-13270,doi:10.1002/2014JD022110.
Kumar,S.V.,B.F.Zaitchik,C.D.Peters-Lidard,et al.,2016:Assimilation of gridded GRACE terrestrial water storage estimates in the North American land data assimilation system.J.Hydrometeor.,17,1951-1972,doi:10.1175/JHM-D-15-0157.1.
Legates,D.R.,R.Mahmood,D.F.Levia,et al.,2011:Soil moisture:A central and unifying theme in physical geography.Prog.Phys.Geog.Earth Environ.,35,65-86,doi:10.1177/0309133310386514.
Liao,W.L.,A.J.Rigden,and D.Li,2018:Attribution of local temperature response to deforestation.J.Geophys.Res Biogeosci.,123,1572-1587,doi:10.1029/2018JG004401.
Liu,Q.,R.H.Reichle,R.Bindlish,et al.,2011:The contributions of precipitation and soil moisture observations to the skill of soil moisture estimates in a land data assimilation system.J.Hydrometeor.,12,750-765,doi:10.1175/JHM-D-10-05000.1.
Morgan,C.L.S.,Y.T.Yimam,M.Barlage,et al.,2017:Valuing of soil capability in land surface modeling.Global Soil Security,D.J.Field,C.L.S.Morgan,and A.B.McBratney,Eds.,Springer International Publishing,Cham,doi:10.1007/978-3-319-43394-3_5.
Pal,J.S.,and E.A.B.Eltahir,2001:Pathways relating soil moisture conditions to future summer rainfall within a model of the land-atmosphere system.J.Climate,14,1227-1242,doi:10.1175/1520-0442(2001)014<1227:PRSMCT>2.0.CO;2.
Parrens,M.,E.Zakharova,S.Lafont,et al.,2012:Comparing soil moisture retrievals from SMOS and ASCAT over France.Hydrol.Earth Syst.Sci.,16,423-440,doi:10.5194/hess-16-423-2012.
Pozzi,W.,J.Sheffield,R.Stefanski,et al.,2013:Toward global drought early warning capability:Expanding international cooperation for the development of a framework for monitoring and forecasting.Bull.Amer.Meteor.Soc.,94,776-785,doi10.1175/BAMS-D-11-00176.1.
Quiring,S.M.,T.W.Ford,J.K.Wang,et al.,2016:The North American soil moisture database:Development and applications.Bull.Amer.Meteor.Soc.,97,1441-1459,doi:10.1175/BAMS-D-13-00263.1.
Seneviratne,S.I.,M.Wilhelm,T.Stanelle,et al.,2013:Impact of soil moisture-climate feedbacks on CMIP5 projections:First results from the GLACE-CMIP5 experiment.Geophys.Res.Lett.,40,5212-5217,doi:10.1002/grl.50956.
Stéfanon,M.,P.Drobinski,F.D’Andrea,et al.,2014:Soil moisture-temperature feedbacks at meso-scale during summer heat waves over Western Europe.Climate Dyn.,42,1309-1324,doi:10.1007/s00382-013-1794-9.
Tang,C.L.,and T.C.Piechota,2009:Spatial and temporal soil moisture and drought variability in the Upper Colorado River Basin.J.Hydrol.,379,122-135,doi:10.1016/j.jhydrol.2009.09.052.
Taylor,K.E.,2001:Summarizing multiple aspects of model performance in a single diagram.J.Geophys.Res.Atmos.,106,7183-7192,doi:10.1029/2000JD900719.
Taylor,C.M.,R.A.M.de Jeu,F.Guichard,et al.,2012:Afternoon rain more likely over drier soils.Nature,489,423-426,doi:10.1038/nature11377.
Wanders,N.,D.Karssenberg,A.de Roo,et al.,2014:The suitability of remotely sensed soil moisture for improving operational flood forecasting.Hydrol.Earth Syst.Sci.,18,2343-2357,doi:10.5194/hess-18-2343-2014.
Wang,A.H.,D.P.Lettenmaier,and J.Sheffield,2011:Soil moisture drought in China,1950-2006.J.Climate,24,3257-3271,doi:10.1175/2011JCLI3733.1.
Wang,Z.L.,P.W.Xie,C.G.Lai,et al.,2017:Spatiotemporal variability of reference evapotranspiration and contributing climatic factors in China during 1961-2013.J.Hydrol.,544,97-108,doi:10.1016/j.jhydrol.2016.11.021.
Wu,X.S.,S.L.Guo,J.B.Yin,et al.,2018:On the event-based extreme precipitation across China:Time distribution patterns,trends,and return levels.J.Hydrol.,562,305-317,doi:10.1016/j.jhydrol.2018.05.028.
Xia,Y.L.,K.Mitchell,M.Ek,et al.,2012a:Continental-scale water and energy flux analysis and validation for the North American Land Data Assimilation System project phase 2(NLDAS-2):1.Intercomparison and application of model products.J.Geophys.Res.Atmos.,117,D03109,doi:10.1029/2011JD016048.
Xia,Y.L.,K.Mitchell,M.Ek,et al.,2012b:Continental-scale water and energy flux analysis and validation for North American Land Data Assimilation System project phase 2(NLDAS-2):2.Validation of model-simulated streamflow.J.Geophys.Res.Atmos.,117,D03110,doi:10.1029/2011JD016051.
Xia,Y.L.,M.Ek,J.Sheffield,et al.,2013:Validation of Noahsimulated soil temperature in the North American Land Data Assimilation System phase 2.J.Appl.Meteor.Climatol.,52,455-471,doi:10.1175/JAMC-D-12-033.1.
Xia,Y.L.,J.Sheffield,M.B.Ek,et al.,2014:Evaluation of multimodel simulated soil moisture in NLDAS-2.J.Hydrol.,512,107-125,doi:10.1016/j.jhydrol.2014.02.027.
Xia,Y.L.,M.B.Ek,Y.H.Wu,et al.,2015a:Comparison of NL-DAS-2 simulated and NASMD observed daily soil moisture.Part I:Comparison and analysis.J.Hydrometeor.,16,1962-1980,doi:10.1175/JHM-D-14-0096.1.
Xia,Y.L.,M.B.Ek,Y.H.Wu,et al.,2015b:Comparison of NL-DAS-2 simulated and NASMD observed daily soil moisture.Part II:Impact of soil texture classification and vegetation type mismatches.J.Hydrometeor.,16,1981-2000,doi:10.1175/JHM-D-14-0097.1.
Xia,Y.L.,T.W.Ford,Y.H.Wu,et al.,2015c:Automated quality control of in situ soil moisture from the North American soil moisture database using NLDAS-2 products.J.Appl.Meteor.Climatol.,54,1267-1282,doi:10.1175/JAMC-D-14-0275.1.
Balsamo,G.,A.Beljaars,K.Scipal,et al.,2009:A revised hydrology for the ECMWF model:Verification from field site to terrestrial water storage and impact in the integrated forecast system.J.Hydrometeor.,10,623-643,doi:10.1175/2008JHM1068.1.
Brocca,L.,L.Ciabatta,C.Massari,et al.,2017:Soil moisture for hydrological applications:Open questions and new opportun-ities.Water,9,140,doi:10.3390/w9020140.
Cai,X.T.,Z.-L.Yang,Y.L.Xia,et al.,2014:Assessment of simulated water balance from Noah,Noah-MP,CLM,and VICover CONUS using the NLDAS test bed.J.Geophys.Res.At-mos.,119,13751-13770,doi:10.1002/2014JD022113.
Collow,T.W.,A.Robock,J.B.Basara,et al.,2012:Evaluation of SMOS retrievals of soil moisture over the central United States with currently available in situ observations.J.Geo-phys.Res.Atmos.,117,D09113,doi:10.1029/2011JD017095.
De Lannoy,G.J.M.,and R.H.Reichle,2016:Assimilation of SMOS brightness temperatures or soil moisture retrievals into a land surface model.Hydrol.Earth Syst.Sci.,20,4895-4911,doi:10.5194/hess-20-4895-2016.
Dirmeyer,P.A.,2011:The terrestrial segment of soil moistureclimate coupling.Geophys.Res.Lett.,38,L16702,doi:10.1029/2011GL048268.
Dorigo,W.A.,W.Wagner,R.Hohensinn,et al.,2011:The international soil moisture network:A data hosting facility for global in situ soil moisture measurements.Hydrol.Earth Syst.Sci.,15,1675-1698,doi:10.5194/hess-15-1675-2011.
Dorigo,W.A.,A.Xaver,M.Vreugdenhil,et al.,2013:Global automated quality control of in situ soil moisture data from the international soil moisture network.Vadose Zone J.,12,1-21,doi:10.2136/vzj2012.0097.
El Sharif,H.,J.F.Wang,and A.P.Georgakakos,2015:Modeling regional crop yield and irrigation demand using SMAP type of soil moisture data.J.Hydrometeor.,16,904-916,doi:10.1175/JHM-D-14-0034.1.
Ford,T.W.,and S.M.Quiring,2014:In situ soil moisture coupled with extreme temperatures:A study based on the Oklahoma Mesonet.Geophys.Res.Lett.,41,4727-4734,doi:10.1002/2014GL060949.
Gruhier,C.,P.de Rosnay,S.Hasenauer,et al.,2010:Soil moisture active and passive microwave products:Intercomparison and evaluation over a Sahelian site.Hydrol.Earth Syst.Sci.,14,141-156,doi:10.5194/hess-14-141-2010.
Hallikainen,M.T.,F.T.Ulaby,M.C.Dobson,et al.,1985:Microwave dielectric behavior of wet soil-part 1:Empirical models and experimental observations.IEEE Trans.Geosci.Remote Sens.,GE-23,25-34,doi:10.1109/TGRS.1985.289497.
Holgate,C.M.,R.A.M.De Jeu,A.I.J.M.van Dijk,et al.,2016:Comparison of remotely sensed and modelled soil moisture data sets across Australia.Remote Sens.Environ.,186,479-500,doi:10.1016/j.rse.2016.09.015.
Kishné,A.S.,Y.T.Yimam,C.L.S.Morgan,et al.,2017:Evaluation and improvement of the default soil hydraulic parameters for the Noah land surface model.Geoderma,285,247-259,doi:10.1016/j.geoderma.2016.09.022.
Koster,R.D.,Y.H.Chang,H.L.Wang,et al.,2016:Impacts of local soil moisture anomalies on the atmospheric circulation and on remote surface meteorological fields during boreal summer:A comprehensive analysis over North America.J. Climate,29,7345-7364,doi:10.1175/JCLI-D-16-0192.1.
Kumar,S.V.,C.D.Peters-Lidard,D.Mocko,et al.,2014a:Assimilation of remotely sensed soil moisture and snow depth retrievals for drought estimation.J.Hydrometeor.,15,2446-2469,doi:10.1175/JHM-D-13-0132.1.
Kumar,S.,P.A.Dirmeyer,D.M.Lawrence,et al.,2014b:Effects of realistic land surface initializations on subseasonal to seasonal soil moisture and temperature predictability in North America and in changing climate simulated by CCSM4.J.Geophys.Res.Atmos.,119,13250-13270,doi:10.1002/2014JD022110.
Kumar,S.V.,B.F.Zaitchik,C.D.Peters-Lidard,et al.,2016:Assimilation of gridded GRACE terrestrial water storage estimates in the North American land data assimilation system.J.Hydrometeor.,17,1951-1972,doi:10.1175/JHM-D-15-0157.1.
Legates,D.R.,R.Mahmood,D.F.Levia,et al.,2011:Soil moisture:A central and unifying theme in physical geography.Prog.Phys.Geog.Earth Environ.,35,65-86,doi:10.1177/0309133310386514.
Liao,W.L.,A.J.Rigden,and D.Li,2018:Attribution of local temperature response to deforestation.J.Geophys.Res Biogeosci.,123,1572-1587,doi:10.1029/2018JG004401.
Liu,Q.,R.H.Reichle,R.Bindlish,et al.,2011:The contributions of precipitation and soil moisture observations to the skill of soil moisture estimates in a land data assimilation system.J.Hydrometeor.,12,750-765,doi:10.1175/JHM-D-10-05000.1.
Morgan,C.L.S.,Y.T.Yimam,M.Barlage,et al.,2017:Valuing of soil capability in land surface modeling.Global Soil Security,D.J.Field,C.L.S.Morgan,and A.B.McBratney,Eds.,Springer International Publishing,Cham,doi:10.1007/978-3-319-43394-3_5.
Pal,J.S.,and E.A.B.Eltahir,2001:Pathways relating soil moisture conditions to future summer rainfall within a model of the land-atmosphere system.J.Climate,14,1227-1242,doi:10.1175/1520-0442(2001)014<1227:PRSMCT>2.0.CO;2.
Parrens,M.,E.Zakharova,S.Lafont,et al.,2012:Comparing soil moisture retrievals from SMOS and ASCAT over France.Hydrol.Earth Syst.Sci.,16,423-440,doi:10.5194/hess-16-423-2012.
Pozzi,W.,J.Sheffield,R.Stefanski,et al.,2013:Toward global drought early warning capability:Expanding international cooperation for the development of a framework for monitoring and forecasting.Bull.Amer.Meteor.Soc.,94,776-785,doi10.1175/BAMS-D-11-00176.1.
Quiring,S.M.,T.W.Ford,J.K.Wang,et al.,2016:The North American soil moisture database:Development and applications.Bull.Amer.Meteor.Soc.,97,1441-1459,doi:10.1175/BAMS-D-13-00263.1.
Seneviratne,S.I.,M.Wilhelm,T.Stanelle,et al.,2013:Impact of soil moisture-climate feedbacks on CMIP5 projections:First results from the GLACE-CMIP5 experiment.Geophys.Res.Lett.,40,5212-5217,doi:10.1002/grl.50956.
Stéfanon,M.,P.Drobinski,F.D’Andrea,et al.,2014:Soil moisture-temperature feedbacks at meso-scale during summer heat waves over Western Europe.Climate Dyn.,42,1309-1324,doi:10.1007/s00382-013-1794-9.
Tang,C.L.,and T.C.Piechota,2009:Spatial and temporal soil moisture and drought variability in the Upper Colorado River Basin.J.Hydrol.,379,122-135,doi:10.1016/j.jhydrol.2009.09.052.
Taylor,K.E.,2001:Summarizing multiple aspects of model performance in a single diagram.J.Geophys.Res.Atmos.,106,7183-7192,doi:10.1029/2000JD900719.
Taylor,C.M.,R.A.M.de Jeu,F.Guichard,et al.,2012:Afternoon rain more likely over drier soils.Nature,489,423-426,doi:10.1038/nature11377.
Wanders,N.,D.Karssenberg,A.de Roo,et al.,2014:The suitability of remotely sensed soil moisture for improving operational flood forecasting.Hydrol.Earth Syst.Sci.,18,2343-2357,doi:10.5194/hess-18-2343-2014.
Wang,A.H.,D.P.Lettenmaier,and J.Sheffield,2011:Soil moisture drought in China,1950-2006.J.Climate,24,3257-3271,doi:10.1175/2011JCLI3733.1.
Wang,Z.L.,P.W.Xie,C.G.Lai,et al.,2017:Spatiotemporal variability of reference evapotranspiration and contributing climatic factors in China during 1961-2013.J.Hydrol.,544,97-108,doi:10.1016/j.jhydrol.2016.11.021.
Wu,X.S.,S.L.Guo,J.B.Yin,et al.,2018:On the event-based extreme precipitation across China:Time distribution patterns,trends,and return levels.J.Hydrol.,562,305-317,doi:10.1016/j.jhydrol.2018.05.028.
Xia,Y.L.,K.Mitchell,M.Ek,et al.,2012a:Continental-scale water and energy flux analysis and validation for the North American Land Data Assimilation System project phase 2(NLDAS-2):1.Intercomparison and application of model products.J.Geophys.Res.Atmos.,117,D03109,doi:10.1029/2011JD016048.
Xia,Y.L.,K.Mitchell,M.Ek,et al.,2012b:Continental-scale water and energy flux analysis and validation for North American Land Data Assimilation System project phase 2(NLDAS-2):2.Validation of model-simulated streamflow.J.Geophys.Res.Atmos.,117,D03110,doi:10.1029/2011JD016051.
Xia,Y.L.,M.Ek,J.Sheffield,et al.,2013:Validation of Noahsimulated soil temperature in the North American Land Data Assimilation System phase 2.J.Appl.Meteor.Climatol.,52,455-471,doi:10.1175/JAMC-D-12-033.1.
Xia,Y.L.,J.Sheffield,M.B.Ek,et al.,2014:Evaluation of multimodel simulated soil moisture in NLDAS-2.J.Hydrol.,512,107-125,doi:10.1016/j.jhydrol.2014.02.027.
Xia,Y.L.,M.B.Ek,Y.H.Wu,et al.,2015a:Comparison of NL-DAS-2 simulated and NASMD observed daily soil moisture.Part I:Comparison and analysis.J.Hydrometeor.,16,1962-1980,doi:10.1175/JHM-D-14-0096.1.
Xia,Y.L.,M.B.Ek,Y.H.Wu,et al.,2015b:Comparison of NL-DAS-2 simulated and NASMD observed daily soil moisture.Part II:Impact of soil texture classification and vegetation type mismatches.J.Hydrometeor.,16,1981-2000,doi:10.1175/JHM-D-14-0097.1.
Xia,Y.L.,T.W.Ford,Y.H.Wu,et al.,2015c:Automated quality control of in situ soil moisture from the North American soil moisture database using NLDAS-2 products.J.Appl.Meteor.Climatol.,54,1267-1282,doi:10.1175/JAMC-D-14-0275.1.