Editorial Type:
Article
Article Type:
Research Article

How Accurate Are Satellite-Derived Surface Solar Radiation Products over Tropical Oceans?

Wenjun Tang National Tibetan Plateau Data Center, Key Laboratory of Tibetan Environmental Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China
Center for Excellence in Tibetan Plateau Earth Sciences, Chinese Academy of Sciences, Beijing, China

Search for other papers by Wenjun Tang in
Current site
Google Scholar
PubMed Close
,
Kun Yang Department of Earth System Science, Tsinghua University, Beijing, China
Center for Excellence in Tibetan Plateau Earth Sciences, Chinese Academy of Sciences, Beijing, China

Search for other papers by Kun Yang in
Current site
Google Scholar
PubMed Close
,
Jun Qin National Tibetan Plateau Data Center, Key Laboratory of Tibetan Environmental Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China
Center for Excellence in Tibetan Plateau Earth Sciences, Chinese Academy of Sciences, Beijing, China

Search for other papers by Jun Qin in
Current site
Google Scholar
PubMed Close
,
Jun Li National Tibetan Plateau Data Center, Key Laboratory of Tibetan Environmental Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China
University of Chinese Academy of Sciences, Beijing, China

Search for other papers by Jun Li in
Current site
Google Scholar
PubMed Close
, and
Jiangang Ye Shaoxing Meteorological Bureau, Shaoxing, China

Search for other papers by Jiangang Ye in
Current site
Google Scholar
PubMed Close
Online Publication:
10 Feb 2021
Print Publication:
01 Feb 2021
DOI:
https://doi.org/10.1175/JTECH-D-20-0099.1
Page(s):
283–291
Restricted access

Abstract

Surface solar radiation (SSR) over the ocean is essential for studies of ocean–atmosphere interactions and marine ecology, and satellite remote sensing is a major way to obtain the SSR over ocean. A new high-resolution (10 km; 3 h) SSR product has recently been developed, mainly based on the newly released cloud product of the International Satellite Cloud Climatology Project H series (ISCCP-HXG), and is available for the period from July 1983 to December 2018. In this study, we compared this SSR product with in situ observations from 70 buoy sites in the Global Tropical Moored Buoy Array (GTMBA) and also compared it with another well-known satellite-derived SSR product from the Clouds and the Earth’s Radiant Energy System (CERES; edition 4.1), which has a spatial resolution of approximately 100 km. The results show that the ISCCP-HXG SSR product is generally more accurate than the CERES SSR product for both ocean and land surfaces. We also found that the accuracy of both satellite-derived SSR products (ISCCP-HXG and CRERS) was higher over ocean than over land and that the accuracy of ISCCP-HXG SSR improves greatly when the spatial resolution of the product is coarsened to ≥ 30 km.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Wenjun Tang, tangwj@itpcas.ac.cn

Abstract

Surface solar radiation (SSR) over the ocean is essential for studies of ocean–atmosphere interactions and marine ecology, and satellite remote sensing is a major way to obtain the SSR over ocean. A new high-resolution (10 km; 3 h) SSR product has recently been developed, mainly based on the newly released cloud product of the International Satellite Cloud Climatology Project H series (ISCCP-HXG), and is available for the period from July 1983 to December 2018. In this study, we compared this SSR product with in situ observations from 70 buoy sites in the Global Tropical Moored Buoy Array (GTMBA) and also compared it with another well-known satellite-derived SSR product from the Clouds and the Earth’s Radiant Energy System (CERES; edition 4.1), which has a spatial resolution of approximately 100 km. The results show that the ISCCP-HXG SSR product is generally more accurate than the CERES SSR product for both ocean and land surfaces. We also found that the accuracy of both satellite-derived SSR products (ISCCP-HXG and CRERS) was higher over ocean than over land and that the accuracy of ISCCP-HXG SSR improves greatly when the spatial resolution of the product is coarsened to ≥ 30 km.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Wenjun Tang, tangwj@itpcas.ac.cn
Save
Cover Journal of Atmospheric and Oceanic Technology
Journal of Atmospheric and Oceanic Technology

  • Bourlès, B., R. Lumpkin, M. J. McPhaden, F. Hernandez, P. Nobre, E. Campos, and J. Servain, 2008: The PIRATA program: History, accomplishments, and future directions. Bull. Amer. Meteor. Soc., 89, 1111–1126, https://doi.org/10.1175/2008BAMS2462.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Cronin, M. F., and M. J. McPhaden, 1997: The upper ocean heat balance in the western equatorial Pacific warm pool during September–December 1992. J. Geophys. Res., 102, 8533–8553, https://doi.org/10.1029/97JC00020.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Fu, Q., and K.-N. Liou, 1993: Parameterization of the radiative properties of cirrus clouds. J. Atmos. Sci., 50, 2008–2025, https://doi.org/10.1175/1520-0469(1993)050<2008:POTRPO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Gupta, S. K., P. W. Stackhouse Jr., S. J. Cox, J. C. Mikovitz, and T. Zhang, 2006: Surface radiation budget project completes 22-year data set. GEWEX News, Vol. 16, No. 4, International GEWEX Project Office, Silver Spring, MD, 12–13.

  • Huang, G., S. Liang, N. Lu, M. Ma, and D. Wang, 2018: Toward a broadband parameterization scheme for estimating surface solar irradiance: Development and preliminary results on MODIS products. J. Geophys. Res. Atmos., 123, 12 180–12 193, https://doi.org/10.1029/2018JD028905.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Huang, G., Z. Li, X. Li, S. Liang, K. Yang, D. Wang, and Y. Zhang, 2019: Estimating surface solar irradiance from satellites: Past, present, and future perspectives. Remote Sens. Environ., 233, 111371, https://doi.org/10.1016/j.rse.2019.111371.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Jiang, H., N. Lu, J. Qin, W. Tang, and L. Yao, 2019: A deep learning algorithm to estimate hourly global solar radiation from geostationary satellite data. Renewable Sustainable Energy Rev., 114, 109327, https://doi.org/10.1016/j.rser.2019.109327.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Jin, Z., T. P. Charlock, and K. Rutledge, 2002: Analysis of broadband solar radiation and albedo over the ocean surface at COVE. J. Atmos. Oceanic Technol., 19, 1585–1601, https://doi.org/10.1175/1520-0426(2002)019<1585:AOBSRA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Karlsson, K.-G., and Coauthors, 2017: CLARA-A2: CM SAF Cloud, Albedo and Surface Radiation dataset from AVHRR data, edition 2. Satellite Application Facility on Climate Monitoring, accessed 1 November 2020, https://doi.org/10.5676/EUM_SAF_CM/CLARA_AVHRR/V002.

    • Crossref
    • Export Citation

  • Kato, S., N. G. Loeb, F. G. Rose, D. R. Doelling, D. A. Rutan, T. E. Caldwell, L. Yu, and R. A. Weller, 2013: Surface irradiances consistent with CERES-derived top-of-atmosphere shortwave and longwave irradiances. J. Climate, 26, 2719–2740, https://doi.org/10.1175/JCLI-D-12-00436.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Letu, H., and Coauthors, 2020: High-resolution retrieval of cloud microphysical properties and surface solar radiation using Himawari-8/AHI next-generation geostationary satellite. Remote Sens. Environ., 239, 111583, https://doi.org/10.1016/j.rse.2019.111583.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Li, Z. Q., and H. G. Leighton, 1993: Global climatologies of solar radiation budgets at the surface and in the atmosphere from 5 years of ERBE data. J. Geophys. Res., 98, 4919–4930, https://doi.org/10.1029/93JD00003.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Lu, N., R. Liu, J. Liu, and S. Liang, 2010: An algorithm for estimating downward shortwave radiation from GMS 5 visible imagery and its evaluation over China. J. Geophys. Res., 115, D18102, https://doi.org/10.1029/2009JD013457.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Lu, N., J. Qin, K. Yang, and J. Sun, 2011: A simple and efficient algorithm to estimate daily global solar radiation from geostationary satellite data. Energy, 36, 3179–3188, https://doi.org/10.1016/j.energy.2011.03.007.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Ma, R., and Coauthors, 2020: Estimation of surface shortwave radiation from Himawari-8 satellite data based on a combination of radiative transfer and deep neural network. IEEE Trans. Geosci. Remote Sens., 58, 5304–5316, https://doi.org/10.1109/TGRS.2019.2963262.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Ma, Y., and R. T. Pinker, 2012: Modeling shortwave radiative fluxes from satellites. J. Geophys. Res., 117, D23202, https://doi.org/10.1029/2012JD018332.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • McPhaden, M. J., and Coauthors, 1998: The Tropical Ocean-Global Atmosphere observing system: A decade of progress. J. Geophys. Res., 103, 14 169–14 240, https://doi.org/10.1029/97JC02906.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • McPhaden, M. J., and Coauthors, 2009: RAMA: The Research Moored Array for African–Asian–Australian monsoon analysis and prediction. Bull. Amer. Meteor. Soc., 90, 459–480, https://doi.org/10.1175/2008BAMS2608.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Mueller, R., C. Matsoukas, A. Gratzki, H. Behr, and R. Hollmann, 2009: The CM–SAF operational scheme for the satellite based retrieval of solar surface irradiance—A LUT based eigenvector hybrid approach. Remote Sens. Environ., 113, 1012–1024, https://doi.org/10.1016/j.rse.2009.01.012.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Pinker, R. T., H. Wang, and S. A. Grodsky, 2009: How good are ocean buoy observations of radiative fluxes? Geophys. Res. Lett., 36, L10811, https://doi.org/10.1029/2009GL037840.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Pinker, R. T., B. Zhang, R. A. Weller, and W. Chen, 2018: Evaluating surface radiation fluxes observed from satellites in the southeastern Pacific Ocean. Geophys. Res. Lett., 45, 2404–2412, https://doi.org/10.1002/2017GL076805.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Posselt, R., R. Mueller, R. Stöckli, and J. Trentmann, 2012: Remote sensing of solar surface radiation for climate monitoring—The CM-SAF retrieval in international comparison. Remote Sens. Environ., 118, 186–198, https://doi.org/10.1016/j.rse.2011.11.016.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Qin, J., W. Tang, K. Yang, N. Lu, X. Niu, and S. Liang, 2015: An efficient physically based parameterization to derive surface solar irradiance based on satellite atmospheric products. J. Geophys. Res. Atmos., 120, 4975–4988, https://doi.org/10.1002/2015JD023097.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Ramesh Kumar, M. R., R. T. Pinker, S. Mathew, R. Venkatesan, and W. Chen, 2018: Evaluation of radiative fluxes over the north Indian Ocean. Theor. Appl. Climatol., 132, 983–988, https://doi.org/10.1007/s00704-017-2141-6.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Rienecker, M. M., and Coauthors, 2008: The GOES-5 Data Assimilation System—Documentation of versions 5.0.1, 5.1.0, and 5.2.0. NASA Tech. Memo. NASA/TM-2009-104606, Vol. 27, 97 pp., http://gmao.gsfc.nasa.gov/pubs/docs/Rienecker369.pdf.

  • Rigollier, C., M. Lefèvre, and L. Wald, 2004: The method Heliosat-2 for deriving shortwave solar radiation data from satellite images. Sol. Energy, 77, 159–169, https://doi.org/10.1016/j.solener.2004.04.017.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Rutan, D. A., and Coauthors, 2015: CERES synoptic product: Methodology and validation of surface radiant flux. J. Atmos. Oceanic Technol., 32, 1121–1143, https://doi.org/10.1175/JTECH-D-14-00165.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Sengupta, M., Y. Xie, A. Lopez, A. Habte, G. Maclaurin, and J. Shelby, 2018: The National Solar Radiation Data Base (NSRDB). Renewable Sustainable Energy Rev., 89, 51–60, https://doi.org/10.1016/j.rser.2018.03.003.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Sun, Z., J. Liu, X. Zeng, and H. Liang, 2012: Parameterization of instantaneous global horizontal irradiance: Cloudy sky component. J. Geophys. Res., 117, D14202, https://doi.org/10.1029/2012JD017557.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Sun, Z., X. Zeng, J. Liu, H. Liang, and J. Li, 2014: Parametrization of instantaneous global horizontal irradiance: Clear sky component. Quart. J. Roy. Meteor. Soc., 140, 267–280, https://doi.org/10.1002/qj.2126.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Tang, W., J. Qin, K. Yang, S. Liu, N. Lu, and X. Niu, 2016: Retrieving high-resolution surface solar radiation with cloud parameters derived by combining MODIS and MTSAT data. Atmos. Chem. Phys., 16, 2543–2557, https://doi.org/10.5194/acp-16-2543-2016.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Tang, W., K. Yang, Z. Sun, J. Qin, and X. Niu, 2017: Global performance of a fast parameterization scheme for estimating surface solar radiation from MODIS data. IEEE Trans. Geosci. Remote Sens., 55, 3558–3571, https://doi.org/10.1109/TGRS.2017.2676164.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Tang, W., K. Yang, J. Qin, X. Li, and X. Niu, 2019: A 16-year dataset (2000–2015) of high-resolution (3 h, 10 km) global surface solar radiation. Earth Syst. Sci. Data, 11, 1905–1915, https://doi.org/10.5194/essd-11-1905-2019.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Wang, H., and R. T. Pinker, 2009: Shortwave radiative fluxes from MODIS: Model development and implementation. J. Geophys. Res., 114, D20201, https://doi.org/10.1029/2008JD010442.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Wei, Y., X. Zhang, N. Hou, W. Zhang, K. Jia, and Y. Yao, 2019: Estimation of surface downward shortwave radiation over China from AVHRR data based on four machine learning methods. Sol. Energy, 177, 32–46, https://doi.org/10.1016/j.solener.2018.11.008.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Xie, Y., M. Sengupta, and J. Dudhia, 2016: A Fast All-Sky Radiation Model for Solar Applications (FARMS): Algorithm and performance evaluation. Sol. Energy, 135, 435–445, https://doi.org/10.1016/j.solener.2016.06.003.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Zhang, X., S. Liang, G. Zhou, H. Wu, and X. Zhao, 2014: Generating Global Land Surface Satellite incident shortwave radiation and photosynthetically active radiation products from multiple satellite data. Remote Sens. Environ., 152, 318–332, https://doi.org/10.1016/j.rse.2014.07.003.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Zhang, Y. C., W. B. Rossow, A. L. Lacis, O. Valdar, and I. M. Michael, 2004: 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. J. Geophys. Res., 109, D19105, https://doi.org/10.1029/2003JD004457.

    • Crossref
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 373 0 0
Full Text Views 399 118 8
PDF Downloads 289 84 6