Improved estimations of gross primary production using satellite‐derived photosynthetically active radiation

Terrestrial vegetation gross primary production (GPP) is an important variable in determining the global carbon cycle as well as the interannual variability of the atmospheric CO2 concentration. The accuracy of GPP simulation is substantially affected by several critical model drivers, one of the most important of which is photosynthetically active radiation (PAR) which directly determines the photosynthesis processes of plants. In this study, we examined the impacts of uncertainties in radiation products on GPP estimates in China. Two satellite‐based radiation products (GLASS and ISCCP), three reanalysis products (MERRA, ECMWF, and NCEP), and a blended product of reanalysis and observations (Princeton) were evaluated based on observations at hundreds of sites. The results revealed the highest accuracy for two satellite‐based products over various temporal and spatial scales. The three reanalysis products and the Princeton product tended to overestimate radiation. The GPP simulation driven by the GLASS product exhibited the highest consistency with those derived from site observations. Model validation at 11 eddy covariance sites suggested the highest model performance when utilizing the GLASS product. Annual GPP in China driven by GLASS was 5.55 Pg C yr−1, which was 68.85%–94.87% of those derived from the other products. The results implied that the high spatial resolution, satellite‐derived GLASS PAR significantly decreased the uncertainty of the GPP estimates at the regional scale.

[1]  R. Reynolds,et al.  The NCEP/NCAR 40-Year Reanalysis Project , 1996, Renewable Energy.

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

[3]  Kasturi Devi Kanniah,et al.  Exploring the link between clouds, radiation, and canopy productivity of tropical savannas , 2013 .

[4]  P. Cox,et al.  Evaluating the Land and Ocean Components of the Global Carbon Cycle in the CMIP5 Earth System Models , 2013 .

[5]  J. Townshend,et al.  A long-term Global LAnd Surface Satellite (GLASS) data-set for environmental studies , 2013 .

[6]  Shaomin Liu,et al.  Measurements of evapotranspiration from eddy-covariance systems and large aperture scintillometers in the Hai River Basin, China , 2013 .

[7]  Jimy Dudhia,et al.  Introducing subgrid-scale cloud feedbacks to radiation for regional meteorological and climate modeling , 2012 .

[8]  Philippe Ciais,et al.  Terrestrial biosphere model performance for inter‐annual variability of land‐atmosphere CO2 exchange , 2012 .

[9]  Liu Huizhi,et al.  Seasonal and Interannual Variations of Evapotranspiration and Energy Exchange over Different Land Surfaces in a Semiarid Area of China , 2012 .

[10]  Shaomin Liu,et al.  A comparison of eddy-covariance and large aperture scintillometer measurements with respect to the energy balance closure problem , 2011 .

[11]  J. Thepaut,et al.  The ERA‐Interim reanalysis: configuration and performance of the data assimilation system , 2011 .

[12]  Maosheng Zhao,et al.  Impact of satellite based PAR on estimates of terrestrial net primary productivity , 2010 .

[13]  Maosheng Zhao,et al.  Drought-Induced Reduction in Global Terrestrial Net Primary Production from 2000 Through 2009 , 2010, Science.

[14]  Charles N. Long,et al.  Exploiting diurnal variations to evaluate the ISCCP-FD flux calculations and radiative-flux-analysis-processed surface observations from BSRN, ARM, and SURFRAD , 2010 .

[15]  K. Davis,et al.  Global estimates of evapotranspiration and gross primary production based on MODIS and global meteorology data , 2010 .

[16]  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.

[17]  Shunlin Liang,et al.  Estimation of daily-integrated PAR from sparse satellite observations: comparison of temporal scaling methods , 2010 .

[18]  Hirofumi Hashimoto,et al.  Evaluating the impacts of climate and elevated carbon dioxide on tropical rainforests of the western Amazon basin using ecosystem models and satellite data , 2010 .

[19]  T. Vesala,et al.  Latitudinal patterns of magnitude and interannual variability in net ecosystem exchange regulated by biological and environmental variables , 2009 .

[20]  Z. Niu,et al.  Watershed Allied Telemetry Experimental Research , 2009 .

[21]  Eric F. Wood,et al.  Comparison and evaluation of gridded radiation products across northern Eurasia , 2009 .

[22]  Martin Wild,et al.  How well do IPCC‐AR4/CMIP3 climate models simulate global dimming/brightening and twentieth‐century daytime and nighttime warming? , 2009 .

[23]  P. Cox,et al.  Impact of changes in diffuse radiation on the global land carbon sink , 2009, Nature.

[24]  G. Yohe,et al.  Risk aversion, time preference, and the social cost of carbon , 2009 .

[25]  Ricardo Todling,et al.  The GEOS-5 Data Assimilation System-Documentation of Versions 5.0.1, 5.1.0, and 5.2.0 , 2008 .

[26]  Josep G. Canadell,et al.  Anthropogenic and biophysical contributions to increasing atmospheric CO 2 growth rate and airborne fraction , 2008 .

[27]  Lei Zhang,et al.  An overview of the Semi-arid Climate and Environment Research Observatory over the Loess Plateau , 2008 .

[28]  Yaoming Ma,et al.  Evaluation of satellite estimates of downward shortwave radiation over the Tibetan Plateau , 2008 .

[29]  P. Alton.  Reduced carbon sequestration in terrestrial ecosystems under overcast skies compared to clear skies , 2008 .

[30]  Markus Reichstein,et al.  Cross-site evaluation of eddy covariance GPP and RE decomposition techniques , 2008 .

[31]  S. Running,et al.  Satellite-based estimation of surface vapor pressure deficits using MODIS land surface temperature data , 2008 .

[32]  Martin Wild,et al.  Short-wave and long-wave surface radiation budgets in GCMs: a review based on the IPCC-AR4/CMIP3 models , 2008 .

[33]  D. Hodáňová.  An introduction to environmental biophysics , 1979, Biologia Plantarum.

[34]  Qiu Jinhuan,et al.  Absorption properties of urban/suburban aerosols in China , 2008 .

[35]  Markus Reichstein,et al.  Uncertainties of modeling gross primary productivity over Europe: A systematic study on the effects of using different drivers and terrestrial biosphere models , 2007 .

[36]  D. Schimel.  Carbon cycle conundrums , 2007, Proceedings of the National Academy of Sciences.

[37]  Corinne Le Quéré,et al.  Contributions to accelerating atmospheric CO2 growth from economic activity, carbon intensity, and efficiency of natural sinks , 2007, Proceedings of the National Academy of Sciences.

[38]  T. Vesala,et al.  Deriving a light use efficiency model from eddy covariance flux data for predicting daily gross primary production across biomes , 2007 .

[39]  Ke Zhang,et al.  Sensitivity of pan-Arctic terrestrial net primary productivity simulations to daily surface meteorology from NCEP-NCAR and ERA-40 reanalyses , 2007 .

[40]  Shunlin Liang,et al.  Mapping High-Resolution Incident Photosynthetically Active Radiation over Land from Polar-Orbiting and Geostationary Satellite Data , 2007 .

[41]  Christoph Schillings,et al.  Long-term variability of solar direct and global radiation derived from ISCCP data and comparison with reanalysis data , 2006 .

[42]  Hongliang Fang,et al.  Estimation of incident photosynthetically active radiation from Moderate Resolution Imaging Spectrometer data , 2006 .

[43]  E. Wood,et al.  Development of a 50-Year High-Resolution Global Dataset of Meteorological Forcings for Land Surface Modeling , 2006 .

[44]  Ramakrishna R. Nemani,et al.  Evaluation of remote sensing based terrestrial productivity from MODIS using regional tower eddy flux network observations , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[45]  Scott J. Goetz,et al.  Trends in Satellite-Observed Circumpolar Photosynthetic Activity from 1982 to 2003: The Influence of Seasonality, Cover Type, and Vegetation Density , 2006 .

[46]  Stefan Kinne,et al.  An assessment of radiation budget data provided by the ISCCP and GEWEX‐SRB , 2006 .

[47]  Kazuaki Kawamoto,et al.  Importance of aerosols in satellite‐derived estimates of surface shortwave irradiance over China , 2006 .

[48]  Maosheng Zhao,et al.  Sensitivity of Moderate Resolution Imaging Spectroradiometer (MODIS) terrestrial primary production to the accuracy of meteorological reanalyses , 2006 .

[49]  A. Ito,et al.  A comparison of simulation results from two terrestrial carbon cycle models using three climate data sets , 2006 .

[50]  Hirofumi Hashimoto,et al.  Modeling the interannual variability and trends in gross and net primary productivity of tropical forests from 1982 to 1999 , 2005 .

[51]  Stephen Sitch,et al.  Effects of parameter uncertainties on the modeling of terrestrial biosphere dynamics , 2005 .

[52]  Jeffrey A. Hicke,et al.  NCEP and GISS solar radiation data sets available for ecosystem modeling: Description, differences, and impacts on net primary production , 2005 .

[53]  Martin Wild,et al.  Solar radiation budgets in atmospheric model intercomparisons from a surface perspective , 2005 .

[54]  Maosheng Zhao,et al.  Improvements of the MODIS terrestrial gross and net primary production global data set , 2005 .

[55]  E. Dutton,et al.  Do Satellites Detect Trends in Surface Solar Radiation? , 2004, Science.

[56]  A. Lacis,et al.  Calculation of radiative fluxes from the surface to top of atmosphere based on ISCCP and other global data sets: Refinements of the radiative transfer model and the input data , 2004 .

[57]  Javier Almorox,et al.  Global solar radiation estimation using sunshine duration in Spain , 2004 .

[58]  Patrick E. Van Laake,et al.  Simplified atmospheric radiative transfer modelling for estimating incident PAR using MODIS atmosphere products , 2004 .

[59]  W. Cohen,et al.  Scaling Gross Primary Production (GPP) over boreal and deciduous forest landscapes in support of MODIS GPP product validation , 2003 .

[60]  Michael G. Bosilovich,et al.  Intercomparison of water and energy budgets for five Mississippi subbasins between ECMWF reanalysis (ERA‐40) and NASA Data Assimilation Office fvGCM for 1990–1999 , 2003 .

[61]  C. Tucker,et al.  Climate-Driven Increases in Global Terrestrial Net Primary Production from 1982 to 1999 , 2003, Science.

[62]  Dennis D. Baldocchi,et al.  Response of a Deciduous Forest to the Mount Pinatubo Eruption: Enhanced Photosynthesis , 2003, Science.

[63]  Fujio Kimura,et al.  Relationship between Topography and Daytime Cloud Activity around Tibetan Plateau , 2002 .

[64]  T. Vesala,et al.  Advantages of diffuse radiation for terrestrial ecosystem productivity , 2002 .

[65]  Atusi Numaguti,et al.  Diurnal Variation of Water Vapor over the Central Tibetan Plateau during Summer. , 2001 .

[66]  Júlio Tóta da Silva,et al.  Cloud modulation of surface solar irradiance at a pasture site in southern Brazil , 2001 .

[67]  T. A. Black,et al.  Responses of net ecosystem exchanges of carbon dioxide to changes in cloudiness: Results from two North American deciduous forests , 1999 .

[68]  John S. Kimball,et al.  Sensitivity of boreal forest regional water flux and net primary production simulations to sub‐grid‐scale land cover complexity , 1999 .

[69]  W. Rossow,et al.  Advances in understanding clouds from ISCCP , 1999 .

[70]  William B. Rossow,et al.  Calculation of surface and top of atmosphere radiative fluxes from physical quantities based on ISCCP data sets: 2. Validation and first results , 1995 .

[71]  Robert Frouin,et al.  Estimating Photosynthetically Active Radiation (PAR) at the earth's surface from satellite observations , 1995 .

[72]  Rachel T. Pinker,et al.  Global distribution of photosynthetically active radiation as observed from satellites , 1992 .

[73]  Andrew A. Lacis,et al.  Global, seasonal cloud variations from satellite radiance measurements. II - Cloud properties and radiative effects , 1990 .