Subdaily to Seasonal Change of Surface Energy and Water Flux of the Haihe River Basin in China: Noah and Noah-MP Assessment
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摘要
The land surface processes of the Noah-MP and Noah models are evaluated over four typical landscapes in the Haihe River Basin(HRB) using in-situ observations. The simulated soil temperature and moisture in the two land surface models(LSMs) is consistent with the observation, especially in the rainy season. The models reproduce the mean values and seasonality of the energy fluxes of the croplands, despite the obvious underestimated total evaporation. Noah shows the lower deep soil temperature. The net radiation is well simulated for the diurnal time scale. The daytime latent heat fluxes are always underestimated, while the sensible heat fluxes are overestimated to some degree. Compared with Noah, Noah-MP has improved daily average soil heat flux with diurnal variations. Generally, Noah-MP performs fairly well for different landscapes of the HRB. The simulated cold bias in soil temperature is possibly linked with the parameterized partition of the energy into surface fluxes. Thus, further improvement of these LSMs remains a major challenge.
The land surface processes of the Noah-MP and Noah models are evaluated over four typical landscapes in the Haihe River Basin(HRB) using in-situ observations. The simulated soil temperature and moisture in the two land surface models(LSMs) is consistent with the observation, especially in the rainy season. The models reproduce the mean values and seasonality of the energy fluxes of the croplands, despite the obvious underestimated total evaporation. Noah shows the lower deep soil temperature. The net radiation is well simulated for the diurnal time scale. The daytime latent heat fluxes are always underestimated, while the sensible heat fluxes are overestimated to some degree. Compared with Noah, Noah-MP has improved daily average soil heat flux with diurnal variations. Generally, Noah-MP performs fairly well for different landscapes of the HRB. The simulated cold bias in soil temperature is possibly linked with the parameterized partition of the energy into surface fluxes. Thus, further improvement of these LSMs remains a major challenge.
The land surface processes of the Noah-MP and Noah models are evaluated over four typical landscapes in the Haihe River Basin(HRB) using in-situ observations. The simulated soil temperature and moisture in the two land surface models(LSMs) is consistent with the observation, especially in the rainy season. The models reproduce the mean values and seasonality of the energy fluxes of the croplands, despite the obvious underestimated total evaporation. Noah shows the lower deep soil temperature. The net radiation is well simulated for the diurnal time scale. The daytime latent heat fluxes are always underestimated, while the sensible heat fluxes are overestimated to some degree. Compared with Noah, Noah-MP has improved daily average soil heat flux with diurnal variations. Generally, Noah-MP performs fairly well for different landscapes of the HRB. The simulated cold bias in soil temperature is possibly linked with the parameterized partition of the energy into surface fluxes. Thus, further improvement of these LSMs remains a major challenge.
引文
Blyth,E.,J.Gash,A.Lloyd,M.Pryor,G.P.Weedon,and J.Shuttleworth,2010:Evaluating the JULES land surface model energy fluxes using FLUXNET data.Journal of Hydrometeorology,11(2),509-519,https://doi.org/10.1175/2009JHM1183.1.
Cai,X.T.,Z.-L.Yang,Y.L.Xia,M.Y.Huang,H.L.Wei,L.R.Leung,and M.B.Ek,2014a:Assessment of simulated water balance from Noah,Noah-MP,CLM,and VIC over CONUSusing the NLDAS test bed.J.Geophys.Res.,119(24),13 751-13 770,https://doi.org/10.1002/2014JD022113.
Cai,X.T.,Z.-L.Yang,C.H.David,G.-Y.Niu,and M.Rodell,2014b:Hydrological evaluation of the Noah-MP land surface model for the Mississippi River Basin.J.Geophys.Res.,119(1),23-38,https://doi.org/10.1002/2013JD020792.
Chen,F.,and J.Dudhia,2001:Coupling an advanced land surfacehydrology model with the Penn state-NCAR MM5 modeling system.Part I:model implementation and sensitivity.Mon.Wea.Rev.,129(4),569-585,https://doi.org/10.1175/1520-0493(2001)129<0569:CAALSH>2.0.CO;2.
Chen,F.,and Coauthors,2014:Modeling seasonal snowpack evolution in the complex terrain and forested Colorado Headwaters region:a model intercomparison study.J.Geophys.Res.,119(24),13 795-13 819,https://doi.org/10.1002/2014JD022167.
Chen,H.S.,R.E.Dickinson,Y.J.Dai,and L.M.Zhou,2011:Sensitivity of simulated terrestrial carbon assimilation and canopy transpiration to different stomatal conductance and carbon assimilation schemes.Climate Dyn.,36(5),1037-1054,https://doi.org/10.1007/s00382-010-0741-2.
Chen,Y.Y.,K.Yang,D.G.Zhou,J.Qin,and X.F.Guo,2010:Improving the Noah land surface model in arid regions with an appropriate parameterization of the thermal roughness length.Journal of Hydrometeorology,11(4),995-1006,https://doi.org/10.1175/2010JHM1185.1.
Chen,Y.Y.,K.Yang,W.J.Tang,J.Qin,and L.Zhao,2012:Parameterizing soil organic carbon’s impacts on soil porosity and thermal parameters for Eastern Tibet grasslands.Science China Earth Sciences,55(6),1001-1011,https://doi.org/10.1007/s11430-012-4433-0.
Dan,L.,and J.J.Ji,2007:The surface energy,water,carbon flux and their intercorrelated seasonality in a global climatevegetation coupled model.Tellus B:Chemical and Physical Meteorology,59(3),425-438,https://doi.org/10.1111/j.1600-0889.2007.00274.x.
Dan,L.,F.Q.Cao,and R.Gao,2015:The improvement of a regional climate model by coupling a land surface model with eco-physiological processes:a case study in 1998.Climatic Change,129(3-4),457-470,https://doi.org/10.1007/s10584-013-0997-8.
De Gonc?alves,L.G.G.,and Coauthors,2013:Overview of the large-scale biosphere-atmosphere experiment in Amazonia data model intercomparison project(LBA-DMIP).Agricultural and Forest Meteorology,182-183,111-127,https://doi.org/10.1016/j.agrformet.2013.04.030.
Dickinson,R.E.,1995:Land-atmosphere interaction.Rev.Geophys.,33(S2),917-922,https://doi.org/10.1029/95RG00284.
Ek,M.B.,K.E.Mitchell,Y.Lin,E.Rogers,P.Grunmann,V.Koren,G.Gayno,and J.D.Tarpley,2003:Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational mesoscale eta model.J.Geophys.Res.,108(D22),8851,https://doi.org/10.1029/2002jd003296.
Gao,Y.H.,K.Li,F.Chen,Y.S.Jiang,and C.G.Lu,2015:Assessing and improving Noah-MP land model simulations for the central Tibetan Plateau.J.Geophys.Res.,120(18),9258-9278,https://doi.org/10.1002/2015JD023404.
Gayler,S.,and Coauthors,2014:Incorporating dynamic root growth enhances the performance of Noah-MP at two contrasting winter wheat field sites.Water Resour.Res.,50(2),1337-1356,https://doi.org/10.1002/2013WR014634.
Gulden,L.E.,E.Roseroe,Z.L.Yang,T.Wagener,and G.Y.Niu,2008:Model performance,model robustness,and model fitness scores:a new method for identifying good land-surface models.Geophys.Res.Lett.,35(11),L11404,https://doi.org/10.1029/2008gl033721.
Jia,Z.Z.,S.M.Liu,Z.W.Xu,Y.J.Chen,and M.J.Zhu,2012:Validation of remotely sensed evapotranspiration over the Hai River Basin,China.J.Geophys.Res.,117(D13),D13113,https://doi.org/10.1029/2011JD017037.
Jin,J.,X.Gao,Z.-L.Yang,R.C.Bales,S.Sorooshian,R.E.Dickinson,S.F.Sun,and G.X.Wu,1999:Comparative analyses of physically based snowmelt models for climate simulations.J.Climate,12(8),2643-2657,https://doi.org/10.1175/1520-0442(1999)012<2643:CAOPBS>2.0.CO;2.
Liu,S.M.,Z.W.Xu,Z.L.Zhu,Z.Z.Jia,and M.J.Zhu,2013:Measurements of evapotranspiration from eddy-covariance systems and large aperture scintillometers in the Hai River Basin,China.J.Hydrol.,487,24-38,https://doi.org/10.1016/j.jhydrol.2013.02.025.
Niu,G.-Y.,and Coauthors,2011:The community Noah land surface model with multiparameterization options(Noah-MP):1.Model description and evaluation with local-scale measurements.J.Geophys.Res.,116(D12),D12109,https://doi.org/10.1029/2010JD015139.
Pan,Y.,C.Zhang,H.L.Gong,P.J.-F.Yeh,Y.J.Shen,Y.Guo,Z.Y.Huang,and X.J.Li,2017:Detection of human-induced evapotranspiration using GRACE satellite observations in the Haihe River basin of China.Geophys.Res.Lett.,44(1),190-199,https://doi.org/10.1002/2016GL071287.
Peng,J.,and L.Dan,2015:Impacts of CO2concentration and climate change on the terrestrial carbon flux using six global climate-carbon coupled models.Ecological Modelling,304,69-83,https://doi.org/10.1016/j.ecolmodel.2015.02.016.
Peters-Lidard,C.D.,E.Blackburn,X.Liang,and E.F.Wood,1998:The effect of soil thermal conductivity parameterization on surface energy fluxes and temperatures.J.Atmos.Sci.,55(7),1209-1224,https://doi.org/10.1175/1520-0469(1998)055<1209:TEOSTC>2.0.CO;2.
Pilotto,I.L.,D.A.Rodr′?guez,J.Tomasella,G.Sampaio,and S.C.Chou,2015:Comparisons of the Noah-MP land surface model simulations with measurements of forest and crop sites in Amazonia.Meteor.Atmos.Phys.,127(6),711-723,https://doi.org/10.1007/s00703-015-0399-8.
Pitman,A.J.,2003:The evolution of,and revolution in,land surface schemes designed for climate models.International Journal of Climatology,23(5),479-510,https://doi.org/10.1002/joc.893.
Rosero,E.,Z.-L.Yang,T.Wagener,L.E.Gulden,S.Yatheendradas,and G.-Y.Niu,2010:Quantifying parameter sensitivity,interaction,and transferability in hydrologically enhanced versions of the Noah land surface model over transition zones during the warm season.J.Geophys.Res.,115(D3),D03106,https://doi.org/10.1029/2009JD012035.
Skamarock,W.C.,and Coauthors,2008:A description of the advanced research WRF version 3.NCAR Technical Note,NCAR/TN-475+STR,125 pp.
Twine,T.E.,and Coauthors,2000:Correcting eddy-covariance flux underestimates over a grassland.Agricultural and Forest Meteorology,103(3),279-300,https://doi.org/10.1016/S0168-1923(00)00123-4.
Yang,K.,and J.M.Wang,2008:A temperature predictioncorrection method for estimating surface soil heat flux from soil temperature and moisture data.Science in China Series D:Earth Sciences,51(5),721-729,https://doi.org/10.1007/s11430-008-0036-1.
Yang,K.,T.Koike,B.S.Ye,and L.Bastidas,2005:Inverse analysis of the role of soil vertical heterogeneity in controlling surface soil state and energy partition.J.Geophys.Res.,110(D8),D08101,https://doi.org/10.1029/2004JD005500.
Yang,Z.-L.,and Coauthors,2011:The community Noah land surface model with multiparameterization options(Noah-MP):2.Evaluation over global river basins.J.Geophys.Res.,116(D12),D12110,https://doi.org/10.1029/2010JD015140.
Zhang,G.,F.Chen,and Y.J.Gan,2016:Assessing uncertainties in the Noah-MP ensemble simulations of a cropland site during the Tibet Joint International Cooperation program field campaign.J.Geophys.Res.,121(16),9576-9596,https://doi.org/10.1002/2016JD024928.
Zheng,D.H.,R.Van Der Velde,Z.B.Su,J.Wen,M.J.Booij,A.Y.Hoekstra,and X.Wang,2015:Under-canopy turbulence and root water uptake of a Tibetan meadow ecosystem modeled by Noah-MP.Water Resour.Res.,51(7),5735-5755,https://doi.org/10.1002/2015wr017115.
Cai,X.T.,Z.-L.Yang,Y.L.Xia,M.Y.Huang,H.L.Wei,L.R.Leung,and M.B.Ek,2014a:Assessment of simulated water balance from Noah,Noah-MP,CLM,and VIC over CONUSusing the NLDAS test bed.J.Geophys.Res.,119(24),13 751-13 770,https://doi.org/10.1002/2014JD022113.
Cai,X.T.,Z.-L.Yang,C.H.David,G.-Y.Niu,and M.Rodell,2014b:Hydrological evaluation of the Noah-MP land surface model for the Mississippi River Basin.J.Geophys.Res.,119(1),23-38,https://doi.org/10.1002/2013JD020792.
Chen,F.,and J.Dudhia,2001:Coupling an advanced land surfacehydrology model with the Penn state-NCAR MM5 modeling system.Part I:model implementation and sensitivity.Mon.Wea.Rev.,129(4),569-585,https://doi.org/10.1175/1520-0493(2001)129<0569:CAALSH>2.0.CO;2.
Chen,F.,and Coauthors,2014:Modeling seasonal snowpack evolution in the complex terrain and forested Colorado Headwaters region:a model intercomparison study.J.Geophys.Res.,119(24),13 795-13 819,https://doi.org/10.1002/2014JD022167.
Chen,H.S.,R.E.Dickinson,Y.J.Dai,and L.M.Zhou,2011:Sensitivity of simulated terrestrial carbon assimilation and canopy transpiration to different stomatal conductance and carbon assimilation schemes.Climate Dyn.,36(5),1037-1054,https://doi.org/10.1007/s00382-010-0741-2.
Chen,Y.Y.,K.Yang,D.G.Zhou,J.Qin,and X.F.Guo,2010:Improving the Noah land surface model in arid regions with an appropriate parameterization of the thermal roughness length.Journal of Hydrometeorology,11(4),995-1006,https://doi.org/10.1175/2010JHM1185.1.
Chen,Y.Y.,K.Yang,W.J.Tang,J.Qin,and L.Zhao,2012:Parameterizing soil organic carbon’s impacts on soil porosity and thermal parameters for Eastern Tibet grasslands.Science China Earth Sciences,55(6),1001-1011,https://doi.org/10.1007/s11430-012-4433-0.
Dan,L.,and J.J.Ji,2007:The surface energy,water,carbon flux and their intercorrelated seasonality in a global climatevegetation coupled model.Tellus B:Chemical and Physical Meteorology,59(3),425-438,https://doi.org/10.1111/j.1600-0889.2007.00274.x.
Dan,L.,F.Q.Cao,and R.Gao,2015:The improvement of a regional climate model by coupling a land surface model with eco-physiological processes:a case study in 1998.Climatic Change,129(3-4),457-470,https://doi.org/10.1007/s10584-013-0997-8.
De Gonc?alves,L.G.G.,and Coauthors,2013:Overview of the large-scale biosphere-atmosphere experiment in Amazonia data model intercomparison project(LBA-DMIP).Agricultural and Forest Meteorology,182-183,111-127,https://doi.org/10.1016/j.agrformet.2013.04.030.
Dickinson,R.E.,1995:Land-atmosphere interaction.Rev.Geophys.,33(S2),917-922,https://doi.org/10.1029/95RG00284.
Ek,M.B.,K.E.Mitchell,Y.Lin,E.Rogers,P.Grunmann,V.Koren,G.Gayno,and J.D.Tarpley,2003:Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational mesoscale eta model.J.Geophys.Res.,108(D22),8851,https://doi.org/10.1029/2002jd003296.
Gao,Y.H.,K.Li,F.Chen,Y.S.Jiang,and C.G.Lu,2015:Assessing and improving Noah-MP land model simulations for the central Tibetan Plateau.J.Geophys.Res.,120(18),9258-9278,https://doi.org/10.1002/2015JD023404.
Gayler,S.,and Coauthors,2014:Incorporating dynamic root growth enhances the performance of Noah-MP at two contrasting winter wheat field sites.Water Resour.Res.,50(2),1337-1356,https://doi.org/10.1002/2013WR014634.
Gulden,L.E.,E.Roseroe,Z.L.Yang,T.Wagener,and G.Y.Niu,2008:Model performance,model robustness,and model fitness scores:a new method for identifying good land-surface models.Geophys.Res.Lett.,35(11),L11404,https://doi.org/10.1029/2008gl033721.
Jia,Z.Z.,S.M.Liu,Z.W.Xu,Y.J.Chen,and M.J.Zhu,2012:Validation of remotely sensed evapotranspiration over the Hai River Basin,China.J.Geophys.Res.,117(D13),D13113,https://doi.org/10.1029/2011JD017037.
Jin,J.,X.Gao,Z.-L.Yang,R.C.Bales,S.Sorooshian,R.E.Dickinson,S.F.Sun,and G.X.Wu,1999:Comparative analyses of physically based snowmelt models for climate simulations.J.Climate,12(8),2643-2657,https://doi.org/10.1175/1520-0442(1999)012<2643:CAOPBS>2.0.CO;2.
Liu,S.M.,Z.W.Xu,Z.L.Zhu,Z.Z.Jia,and M.J.Zhu,2013:Measurements of evapotranspiration from eddy-covariance systems and large aperture scintillometers in the Hai River Basin,China.J.Hydrol.,487,24-38,https://doi.org/10.1016/j.jhydrol.2013.02.025.
Niu,G.-Y.,and Coauthors,2011:The community Noah land surface model with multiparameterization options(Noah-MP):1.Model description and evaluation with local-scale measurements.J.Geophys.Res.,116(D12),D12109,https://doi.org/10.1029/2010JD015139.
Pan,Y.,C.Zhang,H.L.Gong,P.J.-F.Yeh,Y.J.Shen,Y.Guo,Z.Y.Huang,and X.J.Li,2017:Detection of human-induced evapotranspiration using GRACE satellite observations in the Haihe River basin of China.Geophys.Res.Lett.,44(1),190-199,https://doi.org/10.1002/2016GL071287.
Peng,J.,and L.Dan,2015:Impacts of CO2concentration and climate change on the terrestrial carbon flux using six global climate-carbon coupled models.Ecological Modelling,304,69-83,https://doi.org/10.1016/j.ecolmodel.2015.02.016.
Peters-Lidard,C.D.,E.Blackburn,X.Liang,and E.F.Wood,1998:The effect of soil thermal conductivity parameterization on surface energy fluxes and temperatures.J.Atmos.Sci.,55(7),1209-1224,https://doi.org/10.1175/1520-0469(1998)055<1209:TEOSTC>2.0.CO;2.
Pilotto,I.L.,D.A.Rodr′?guez,J.Tomasella,G.Sampaio,and S.C.Chou,2015:Comparisons of the Noah-MP land surface model simulations with measurements of forest and crop sites in Amazonia.Meteor.Atmos.Phys.,127(6),711-723,https://doi.org/10.1007/s00703-015-0399-8.
Pitman,A.J.,2003:The evolution of,and revolution in,land surface schemes designed for climate models.International Journal of Climatology,23(5),479-510,https://doi.org/10.1002/joc.893.
Rosero,E.,Z.-L.Yang,T.Wagener,L.E.Gulden,S.Yatheendradas,and G.-Y.Niu,2010:Quantifying parameter sensitivity,interaction,and transferability in hydrologically enhanced versions of the Noah land surface model over transition zones during the warm season.J.Geophys.Res.,115(D3),D03106,https://doi.org/10.1029/2009JD012035.
Skamarock,W.C.,and Coauthors,2008:A description of the advanced research WRF version 3.NCAR Technical Note,NCAR/TN-475+STR,125 pp.
Twine,T.E.,and Coauthors,2000:Correcting eddy-covariance flux underestimates over a grassland.Agricultural and Forest Meteorology,103(3),279-300,https://doi.org/10.1016/S0168-1923(00)00123-4.
Yang,K.,and J.M.Wang,2008:A temperature predictioncorrection method for estimating surface soil heat flux from soil temperature and moisture data.Science in China Series D:Earth Sciences,51(5),721-729,https://doi.org/10.1007/s11430-008-0036-1.
Yang,K.,T.Koike,B.S.Ye,and L.Bastidas,2005:Inverse analysis of the role of soil vertical heterogeneity in controlling surface soil state and energy partition.J.Geophys.Res.,110(D8),D08101,https://doi.org/10.1029/2004JD005500.
Yang,Z.-L.,and Coauthors,2011:The community Noah land surface model with multiparameterization options(Noah-MP):2.Evaluation over global river basins.J.Geophys.Res.,116(D12),D12110,https://doi.org/10.1029/2010JD015140.
Zhang,G.,F.Chen,and Y.J.Gan,2016:Assessing uncertainties in the Noah-MP ensemble simulations of a cropland site during the Tibet Joint International Cooperation program field campaign.J.Geophys.Res.,121(16),9576-9596,https://doi.org/10.1002/2016JD024928.
Zheng,D.H.,R.Van Der Velde,Z.B.Su,J.Wen,M.J.Booij,A.Y.Hoekstra,and X.Wang,2015:Under-canopy turbulence and root water uptake of a Tibetan meadow ecosystem modeled by Noah-MP.Water Resour.Res.,51(7),5735-5755,https://doi.org/10.1002/2015wr017115.