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Title: Global Surface Net-Radiation at 5 km from MODIS Terra

Abstract

Reliable and fine resolution estimates of surface net-radiation are required for estimating latent and sensible heat fluxes between the land surface and the atmosphere. However, currently, fine resolution estimates of net-radiation are not available and consequently it is challenging to develop multi-year estimates of evapotranspiration at scales that can capture land surface heterogeneity and are relevant for policy and decision-making. We developed and evaluated a global net-radiation product at 5 km and 8-day resolution by combining mutually consistent atmosphere and land data from the Moderate Resolution Imaging Spectroradiometer (MODIS) on board Terra. Comparison with net-radiation measurements from 154 globally distributed sites (414 site-years) from the FLUXNET and Surface Radiation budget network (SURFRAD) showed that the net-radiation product agreed well with measurements across seasons and climate types in the extratropics (Wilmott's index ranged from 0.74 for boreal to 0.63 for Mediterranean sites). Mean absolute deviation between the MODIS and measured net-radiation ranged from 38.0 ± 1.8 W.m-2 in boreal to 72.0 ± 4.1 W.m-2 in the tropical climates. The mean bias was small and constituted only 11%, 0.7%, 8.4%, 4.2%, 13.3%, and 5.4% of the mean absolute error in daytime net-radiation in boreal, Mediterranean, temperate-continental, temperate, semi-arid, and tropical climate, respectively.more » To assess the accuracy of the broader spatiotemporal patterns, we upscaled error-quantified MODIS net-radiation and compared it with the net-radiation estimates from the coarse spatial (1° x 1°) but high temporal resolution gridded net-radiation product from the Clouds and Earth's Radiant Energy System (CERES). Our estimates agreed closely with the net-radiation estimates from the CERES. Difference between the two was less than 10W.m-2 in 94% of the total land area. MODIS net-radiation product will be a valuable resource for the science community studying turbulent fluxes and energy budget at the Earth's surface.« less

Authors:
 [1]; ORCiD logo [1]; ORCiD logo [2];  [3];  [4];  [1];  [1];  [5];  [5]; ORCiD logo [6];  [1];  [7];  [8];  [9];  [10]; ORCiD logo [11];  [12];  [13]
  1. California Inst. of Technology (CalTech), La Canada Flintridge, CA (United States). Jet Propulsion Lab.
  2. Luxembourg Institute of Science and Technology (LIST) (Luxembourg). Department of Environmental Research and Innovation (ERIN)
  3. Seoul National University (Korea). Department of Landscape Architecture and Rural Systems Engineering
  4. Japan Agency for Marine-Earth Science and Technology, Yokohama (Japan)
  5. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  6. ETH Zurich (Switzerland). Department of Environmental Systems Science
  7. University College, Cork (Ireland). Environmental Research Institute, Civil and Environmental Engineering Department
  8. University of Innsbruck (Austria). Institute of Ecology
  9. University of Antwerp (Belgium). Research Group of Plant and Vegetation Ecology, Department of Biology
  10. CIRAD, UMR Eco & Sols (Ecologie Fonctionnelle & Biogeochimie des Sols & Agroecosystemes), Montpellier (France); CATIE (Tropical Agricultural Centre for Research and Higher Education), Turrialba (Costa Rica)
  11. Institute of Biometeorology (IBIMET—CNR) (Italy)
  12. McMaster Univ., Hamilton, ON (Canada). School of Geography and Earth Sciences, McMaster Centre for Climate Change
  13. European Commission, Joint Research Centre, Directorate for Sustainable Resources, Ispra (Italy)
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
OSTI Identifier:
1377449
Grant/Contract Number:  
AC02-05CH11231; FG02-04ER63917; FG02-04ER63911
Resource Type:
Accepted Manuscript
Journal Name:
Remote Sensing
Additional Journal Information:
Journal Volume: 8; Journal Issue: 9; Journal ID: ISSN 2072-4292
Publisher:
MDPI
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; surface net-radiation; MODIS; FLUXNET; SURFRAD; modeling; validation

Citation Formats

Verma, Manish, Fisher, Joshua, Mallick, Kaniska, Ryu, Youngryel, Kobayashi, Hideki, Guillaume, Alexandre, Moore, Gregory, Ramakrishnan, Lavanya, Hendrix, Valerie, Wolf, Sebastian, Sikka, Munish, Kiely, Gerard, Wohlfahrt, Georg, Gielen, Bert, Roupsard, Olivier, Toscano, Piero, Arain, Altaf, and Cescatti, Alessandro. Global Surface Net-Radiation at 5 km from MODIS Terra. United States: N. p., 2016. Web. doi:10.3390/rs8090739.
Verma, Manish, Fisher, Joshua, Mallick, Kaniska, Ryu, Youngryel, Kobayashi, Hideki, Guillaume, Alexandre, Moore, Gregory, Ramakrishnan, Lavanya, Hendrix, Valerie, Wolf, Sebastian, Sikka, Munish, Kiely, Gerard, Wohlfahrt, Georg, Gielen, Bert, Roupsard, Olivier, Toscano, Piero, Arain, Altaf, & Cescatti, Alessandro. Global Surface Net-Radiation at 5 km from MODIS Terra. United States. doi:10.3390/rs8090739.
Verma, Manish, Fisher, Joshua, Mallick, Kaniska, Ryu, Youngryel, Kobayashi, Hideki, Guillaume, Alexandre, Moore, Gregory, Ramakrishnan, Lavanya, Hendrix, Valerie, Wolf, Sebastian, Sikka, Munish, Kiely, Gerard, Wohlfahrt, Georg, Gielen, Bert, Roupsard, Olivier, Toscano, Piero, Arain, Altaf, and Cescatti, Alessandro. Tue . "Global Surface Net-Radiation at 5 km from MODIS Terra". United States. doi:10.3390/rs8090739. https://www.osti.gov/servlets/purl/1377449.
@article{osti_1377449,
title = {Global Surface Net-Radiation at 5 km from MODIS Terra},
author = {Verma, Manish and Fisher, Joshua and Mallick, Kaniska and Ryu, Youngryel and Kobayashi, Hideki and Guillaume, Alexandre and Moore, Gregory and Ramakrishnan, Lavanya and Hendrix, Valerie and Wolf, Sebastian and Sikka, Munish and Kiely, Gerard and Wohlfahrt, Georg and Gielen, Bert and Roupsard, Olivier and Toscano, Piero and Arain, Altaf and Cescatti, Alessandro},
abstractNote = {Reliable and fine resolution estimates of surface net-radiation are required for estimating latent and sensible heat fluxes between the land surface and the atmosphere. However, currently, fine resolution estimates of net-radiation are not available and consequently it is challenging to develop multi-year estimates of evapotranspiration at scales that can capture land surface heterogeneity and are relevant for policy and decision-making. We developed and evaluated a global net-radiation product at 5 km and 8-day resolution by combining mutually consistent atmosphere and land data from the Moderate Resolution Imaging Spectroradiometer (MODIS) on board Terra. Comparison with net-radiation measurements from 154 globally distributed sites (414 site-years) from the FLUXNET and Surface Radiation budget network (SURFRAD) showed that the net-radiation product agreed well with measurements across seasons and climate types in the extratropics (Wilmott's index ranged from 0.74 for boreal to 0.63 for Mediterranean sites). Mean absolute deviation between the MODIS and measured net-radiation ranged from 38.0 ± 1.8 W.m-2 in boreal to 72.0 ± 4.1 W.m-2 in the tropical climates. The mean bias was small and constituted only 11%, 0.7%, 8.4%, 4.2%, 13.3%, and 5.4% of the mean absolute error in daytime net-radiation in boreal, Mediterranean, temperate-continental, temperate, semi-arid, and tropical climate, respectively. To assess the accuracy of the broader spatiotemporal patterns, we upscaled error-quantified MODIS net-radiation and compared it with the net-radiation estimates from the coarse spatial (1° x 1°) but high temporal resolution gridded net-radiation product from the Clouds and Earth's Radiant Energy System (CERES). Our estimates agreed closely with the net-radiation estimates from the CERES. Difference between the two was less than 10W.m-2 in 94% of the total land area. MODIS net-radiation product will be a valuable resource for the science community studying turbulent fluxes and energy budget at the Earth's surface.},
doi = {10.3390/rs8090739},
journal = {Remote Sensing},
number = 9,
volume = 8,
place = {United States},
year = {2016},
month = {9}
}

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