Modeling Evapotranspiration over China's Landmass from 1979 to 2012 Using Multiple Land Surface Models: Evaluations and Analyses

AbstractLand surface models (LSMs) are useful tools to estimate land evapotranspiration at a grid scale and for long-term applications. Here, the Community Land Model, version 4.0 (CLM4.0); Dynamic Land Model (DLM); and Variable Infiltration Capacity model (VIC) were driven with observation-based forcing datasets, and a multiple-LSM ensemble-averaged evapotranspiration (ET) product (LSMs-ET) was developed and its spatial–temporal variations were analyzed for the China landmass over the period 1979–2012. Evaluations against measurements from nine flux towers at site scale and surface water budget–based ET at regional scale showed that the LSMs-ET had good performance in most areas of China’s landmass. The intercomparisons between the ET estimates and the independent ET products from remote sensing and upscaling methods suggested that there were fairly consistent patterns between each dataset. The LSMs-ET produced a mean annual ET of 351.24 ± 10.7 mm yr−1 over 1979–2012, and its spatial–temporal variation a...

[1]  Maosheng Zhao,et al.  Development of a global evapotranspiration algorithm based on MODIS and global meteorology data , 2007 .

[2]  Eric F. Wood,et al.  A Global Intercomparison of Modeled and Observed Land–Atmosphere Coupling* , 2012 .

[3]  Xiaotong Zhang,et al.  Review on Estimation of Land Surface Radiation and Energy Budgets From Ground Measurement, Remote Sensing and Model Simulations , 2010, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[4]  P. Ciais,et al.  Changes in climate and land use have a larger direct impact than rising CO2 on global river runoff trends , 2007, Proceedings of the National Academy of Sciences.

[5]  T. Foken The energy balance closure problem: an overview. , 2008, Ecological applications : a publication of the Ecological Society of America.

[6]  Baozhang Chen,et al.  Improving soil organic carbon parameterization of land surface model for cold regions in the Northeastern Tibetan Plateau, China , 2016 .

[7]  S. Seneviratne,et al.  Investigating soil moisture-climate interactions in a changing climate: A review , 2010 .

[8]  Chad W. Higgins,et al.  Evapotranspiration: A process driving mass transport and energy exchange in the soil‐plant‐atmosphere‐climate system , 2012 .

[9]  X. Lee,et al.  Overview of ChinaFLUX and evaluation of its eddy covariance measurement , 2006 .

[10]  Shaoqiang Wang,et al.  Diagnostic analysis of interannual variation of global land evapotranspiration over 1982–2011: Assessing the impact of ENSO , 2013 .

[11]  M. Mccabe,et al.  Multi-site evaluation of terrestrial evaporation models using FLUXNET data , 2014 .

[12]  J. Chen,et al.  Comparison of remotely-sensed and modeled soil moisture using CLM4.0 with in situ measurements in the central Tibetan Plateau area , 2016 .

[13]  D. Baldocchi,et al.  Global estimates of the land–atmosphere water flux based on monthly AVHRR and ISLSCP-II data, validated at 16 FLUXNET sites , 2008 .

[14]  Joshua B. Fisher,et al.  What controls the error structure in evapotranspiration models , 2013 .

[15]  Donglin Guo,et al.  Simulation of permafrost and seasonally frozen ground conditions on the Tibetan Plateau, 1981–2010 , 2013 .

[16]  Yi Luo,et al.  Spatial and seasonal variations in evapotranspiration over Canada's landmass , 2013 .

[17]  Naota Hanasaki,et al.  GSWP-2 Multimodel Analysis and Implications for Our Perception of the Land Surface , 2006 .

[18]  Markus Reichstein,et al.  Benchmark products for land evapotranspiration: LandFlux-EVAL multi-data set synthesis , 2013 .

[19]  Wolfgang Grabs,et al.  High‐resolution fields of global runoff combining observed river discharge and simulated water balances , 2002 .

[20]  A. Dai,et al.  The uncertainties and causes of the recent changes in global evapotranspiration from 1982 to 2010 , 2017, Climate Dynamics.

[21]  Jeffrey P. Walker,et al.  THE GLOBAL LAND DATA ASSIMILATION SYSTEM , 2004 .

[22]  Xiaodong Liu,et al.  Quantifying the hydrological responses to climate change in an intact forested small watershed in Southern China , 2011 .

[23]  R. Dickinson,et al.  A review of global terrestrial evapotranspiration: Observation, modeling, climatology, and climatic variability , 2011 .

[24]  David M. Lawrence,et al.  Improved simulation of the terrestrial hydrological cycle in permafrost regions by the Community Land Model , 2012 .

[25]  Jie He,et al.  On downward shortwave and longwave radiations over high altitude regions: Observation and modeling in the Tibetan Plateau , 2010 .

[26]  Atul K. Jain,et al.  Disentangling climatic and anthropogenic controls on global terrestrial evapotranspiration trends , 2015, Environmental Research Letters.

[27]  Julie A. Vano,et al.  Hydrologic Sensitivities of Colorado River Runoff to Changes in Precipitation and Temperature , 2012 .

[28]  Deliang Chen,et al.  Aridity changes in the Tibetan Plateau in a warming climate , 2015 .

[29]  A. Thomas Development and properties of 0.25-degree gridded evapotranspiration data fields of China for hydrological studies , 2008 .

[30]  S. Seneviratne,et al.  Recent decline in the global land evapotranspiration trend due to limited moisture supply , 2010, Nature.

[31]  A. Bondeau,et al.  Towards global empirical upscaling of FLUXNET eddy covariance observations: validation of a model tree ensemble approach using a biosphere model , 2009 .

[32]  P. Ciais,et al.  Global evapotranspiration over the past three decades: estimation based on the water balance equation combined with empirical models , 2012 .

[33]  Eric F. Wood,et al.  One-dimensional statistical dynamic representation of subgrid spatial variability of precipitation in the two-layer variable infiltration capacity model , 1996 .

[34]  Xia Jun,et al.  Water problems and opportunities in the hydrological sciences in China , 2001 .

[35]  Tandong Yao,et al.  Third Pole Environment (TPE) , 2012 .

[36]  J. Monteith Evaporation and environment. , 1965, Symposia of the Society for Experimental Biology.

[37]  Zhuguo Ma,et al.  Comparison of satellite-based evapotranspiration models over terrestrial ecosystems in China , 2014 .

[38]  Chong-Yu Xu,et al.  Trend of estimated actual evapotranspiration over China during 1960-2002 , 2007 .

[39]  D. Lettenmaier,et al.  Twentieth-Century Drought in the Conterminous United States , 2005 .

[40]  Jiquan Chen,et al.  Evapotranspiration in Northern Eurasia: Impact of forcing uncertainties on terrestrial ecosystem model estimates , 2015 .

[41]  Yi Y. Liu,et al.  Multi-decadal trends in global terrestrial evapotranspiration and its components , 2016, Scientific Reports.

[42]  Zhuguo Ma,et al.  Estimation of evapotranspiration over the terrestrial ecosystems in China , 2014 .

[43]  Xingguo Mo,et al.  Trends in land surface evapotranspiration across China with remotely sensed NDVI and climatological data for 1981–2010 , 2015 .

[44]  Shaohong Wu,et al.  Past and future spatiotemporal changes in evapotranspiration and effective moisture on the Tibetan Plateau , 2013 .

[45]  Li Zhengquan,et al.  Energy balance closure at ChinaFLUX sites , 2005 .

[46]  B. Rudolf,et al.  World Map of the Köppen-Geiger climate classification updated , 2006 .

[47]  A. Pitman,et al.  Diagnosing the seasonal land-atmosphere correspondence over northern Australia: dependence on soil moisture state and correspondence strength definition , 2015 .

[48]  B. Scanlon,et al.  Uncertainty in evapotranspiration from land surface modeling, remote sensing, and GRACE satellites , 2014 .

[49]  M. Mccabe,et al.  Estimating Land Surface Evaporation: A Review of Methods Using Remotely Sensed Surface Temperature Data , 2008 .

[50]  Nicholas C. Coops,et al.  Understanding of Coupled Terrestrial Carbon, Nitrogen and Water Dynamics—An Overview , 2009, Sensors.

[51]  A. Arneth,et al.  Global patterns of land-atmosphere fluxes of carbon dioxide, latent heat, and sensible heat derived from eddy covariance, satellite, and meteorological observations , 2011 .

[52]  Maoyi Huang,et al.  Spatiotemporal patterns of evapotranspiration in response to multiple environmental factors simulated by the Community Land Model , 2013 .

[53]  S. Kanae,et al.  Global Hydrological Cycles and World Water Resources , 2006, Science.

[54]  Baozhang Chen,et al.  Modeling and Scaling Coupled Energy, Water, and Carbon Fluxes Based on Remote Sensing: An Application to Canada's Landmass , 2007 .

[55]  S. Seneviratne,et al.  Evaluation of global observations‐based evapotranspiration datasets and IPCC AR4 simulations , 2011 .

[56]  D. Shepard,et al.  Computer Mapping: The SYMAP Interpolation Algorithm , 1984 .

[57]  D. Mocko,et al.  Multimodel Analysis of Energy and Water Fluxes: Intercomparisons between Operational Analyses, a Land Surface Model, and Remote Sensing , 2012 .

[58]  S. Running,et al.  Regional evaporation estimates from flux tower and MODIS satellite data , 2007 .

[59]  Xiaomin Sun,et al.  CO2 fluxes over an old, temperate mixed forest in northeastern China , 2006 .

[60]  A. Pitman,et al.  Modelling evapotranspiration during precipitation deficits: identifying critical processes in a land surface model , 2015 .

[61]  Jie He,et al.  Improving land surface temperature modeling for dry land of China , 2011 .

[62]  D. Lettenmaier,et al.  A simple hydrologically based model of land surface water and energy fluxes for general circulation models , 1994 .

[63]  Filipe Aires,et al.  Toward an estimation of global land surface heat fluxes from multisatellite observations , 2009 .

[64]  Weimin Ju,et al.  Remote sensing-based ecosystem–atmosphere simulation scheme (EASS)—Model formulation and test with multiple-year data , 2007 .

[65]  J. Diamond,et al.  China's environment in a globalizing world , 2005, Nature.

[66]  S. Running,et al.  A continuous satellite‐derived global record of land surface evapotranspiration from 1983 to 2006 , 2010 .

[67]  Che-sheng Zhan,et al.  Regional estimation and validation of remotely sensed evapotranspiration in China , 2015 .

[68]  A. Zhu,et al.  A China data set of soil properties for land surface modeling , 2013 .

[69]  S. Seneviratne,et al.  Energy balance closure of eddy-covariance data: a multisite analysis for European FLUXNET stations. , 2010 .

[70]  J. Qiu China: The third pole , 2008, Nature.

[71]  J.-G. Liu,et al.  Improving simulation of soil moisture in China using a multiple meteorological forcing ensemble approach , 2013 .

[72]  R. Dickinson,et al.  Evidence for decadal variation in global terrestrial evapotranspiration between 1982 and 2002: 1. Model development , 2010 .

[73]  Yan Li,et al.  Variations in water and CO2 fluxes over a saline desert in western China , 2012 .

[74]  D. Lawrence,et al.  Parameterization improvements and functional and structural advances in Version 4 of the Community Land Model , 2011 .

[75]  X. Kuang,et al.  Review on climate change on the Tibetan Plateau during the last half century , 2016 .

[76]  H. Tian,et al.  Effects of multiple environment stresses on evapotranspiration and runoff over eastern China , 2012 .

[77]  E. Wood,et al.  Global Trends and Variability in Soil Moisture and Drought Characteristics, 1950–2000, from Observation-Driven Simulations of the Terrestrial Hydrologic Cycle , 2008 .

[78]  John L. Innes,et al.  Comparison of terrestrial evapotranspiration estimates using the mass transfer and Penman‐Monteith equations in land surface models , 2013 .

[79]  Carlos Jimenez,et al.  On Uncertainty in Global Terrestrial Evapotranspiration Estimates from Choice of Input Forcing Datasets , 2015 .

[80]  T. Andrew Black,et al.  Numerical Terradynamic Simulation Group 8-2015 Comparing Evapotranspiration from Eddy Covariance Measurements , Water Budgets , Remote Sensing , and Land Surface Models over Canada , 2018 .

[81]  David C. Weindorf,et al.  Soil Database of 1:1,000,000 Digital Soil Survey and Reference System of the Chinese Genetic Soil Classification System , 2004 .

[82]  Alan H. Strahler,et al.  Global land cover mapping from MODIS: algorithms and early results , 2002 .

[83]  C. Shi,et al.  Ensemble simulation of land evapotranspiration in China based on a multi-forcing and multi-model approach , 2016, Advances in Atmospheric Sciences.

[84]  S. Seneviratne,et al.  Global intercomparison of 12 land surface heat flux estimates , 2011 .

[85]  Bin Wang,et al.  Tibetan Plateau warming and precipitation changes in East Asia , 2008 .

[86]  Q. Tang,et al.  A Long-Term Land Surface Hydrologic Fluxes and States Dataset for China , 2014 .

[87]  Fengting Yang,et al.  The ecosystem carbon accumulation after conversion of grasslands to pine plantations in subtropical red soil of South China , 2007 .

[88]  P. Dirmeyer,et al.  The Plumbing of Land Surface Models: Benchmarking Model Performance , 2015 .

[89]  Jun Qin,et al.  Recent climate changes over the Tibetan Plateau and their impacts on energy and water cycle: A review , 2014 .

[90]  H. Tian,et al.  Responses of global terrestrial evapotranspiration to climate change and increasing atmospheric CO2 in the 21st century , 2015 .

[91]  Atul K. Jain,et al.  Climate‐driven uncertainties in modeling terrestrial energy and water fluxes: a site‐level to global‐scale analysis , 2014, Global change biology.

[92]  Eric F. Wood,et al.  Global estimates of evapotranspiration for climate studies using multi-sensor remote sensing data: Evaluation of three process-based approaches , 2011 .

[93]  D. Zheng,et al.  Modeled effects of climate change on actual evapotranspiration in different eco-geographical regions in the Tibetan Plateau , 2013, Journal of Geographical Sciences.

[94]  Maosheng Zhao,et al.  Improvements to a MODIS global terrestrial evapotranspiration algorithm , 2011 .