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Title: A global DSCOVR/EPIC-based hourly/daily shortwave radiation/PAR dataset (in EN)

Abstract

Downward shortwave radiation (SW) and photosynthetically active radiation (PAR) play crucial roles in Earth system dynamics. Spaceborne remote sensing techniques provide a unique approach for mapping accurate spatio-temporally-continuous SW/PAR. However, any individual polar-orbiting or geostationary satellite cannot satisfy the desired high temporal resolution (sub-daily) and global coverage simultaneously, while integrating and fusing multi-source data from complementary satellites/sensors is challenging because of co-registration, inter-calibration, near real-time data delivery and the effects of discrepancies in orbital geometry. The Earth Polychromatic Imaging Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR), launched in February 2015, opens an unprecedented possibility to bridge the gap between high temporal resolution and global coverage, and characterize the diurnal cycles of SW/PAR globally. In this paper, we adopt a suite of well-validated data-driven machine-learning models to generate the first global land products of SW/PAR, from June 2015 to June 2019, based on DSCOVR/EPIC data. The generated products have high temporal resolution (hourly) and medium spatial resolution (0.1°×0.1°), and include estimates of the direct and diffuse components of SW/PAR. We used widely-distributed ground station data from the Baseline Surface Radiation Network (BSRN), the Surface Radiation Budget Network (SURFRAD), NOAA’s Global Monitoring Division and the U.S. Department of Energy’s Atmosphericmore » System Research (ASR) program to evaluate the performance of our products, and further analyzed and compared the spatio-temporal characteristics of the derived products with the benchmarking Clouds and the Earth's Radiant Energy System Synoptic (CERES) data. Both the hourly and daily products are consistent with ground observations (e.g., hourly and daily total SWs have low biases of -3.96 and -0.71 W/m2 and root mean square errors (RMSEs) of 103.50 and 35.40 W/m2, respectively). The developed products capture complex spatio-temporal patterns well and accurately track substantial diurnal, monthly, and seasonal variations of SW/PAR when compared to CERES data. They provide a reliable and valuable alternative for solar photovoltaic applications and improve our understanding the diurnal variabilities of the terrestrial water, carbon and energy fluxes at various spatial scales. The hourly data are grouped by day in distinct NetCDF files, which are named as “EPIC_SW_PAR_Hourly_yyyymmdd.nc” where “yyyy”, “mm”, and “dd” denote year, month, and day (UTC time). The daily data are grouped by month in distinct NetCDF files, which are named as “EPIC_SW_PAR_Daily_yyyymm.nc” where “yyyy”, and “mm” denote year and month (UTC time). Each NetCDF file contains latitude, longitude, time, diffuse SW, direct SW, diffuse PAR, direct PAR, and the corresponding quality flags which indicates where the pixel is gap-filled or not. The scale factor for the direct and diffuse SW/PAR is 0.1. The total SW/PAR can be calculated by combining the direct and diffuse components. The information about the version, creation date, reference, contact mails, and other comments are also included in the file.« less

Creator(s)/Author(s):
; ; ; ; ; ;
Publication Date:
Other Number(s):
Project ID: 205768; Instrument ID: 85000; Upload ID: 1112
DOE Contract Number:  
AC05-76RL01830
Product Type:
Dataset
Research Org.:
Pacific Northwest National Laboratory 2; PNNL
Sponsoring Org.:
USDOE Office of Science (SC)
Subject:
58 GEOSCIENCES; 14 SOLAR ENERGY
OSTI Identifier:
1595069
DOI:
10.25584/1595069

Citation Formats

Hao, Dalei, Chen, Min, Asrar, Ghassem, Zeng, Yelu, Zhu, Qing, Wen, Jianguang, and Xiao, Qing. A global DSCOVR/EPIC-based hourly/daily shortwave radiation/PAR dataset. United States: N. p., 2020. Web. doi:10.25584/1595069.
Hao, Dalei, Chen, Min, Asrar, Ghassem, Zeng, Yelu, Zhu, Qing, Wen, Jianguang, & Xiao, Qing. A global DSCOVR/EPIC-based hourly/daily shortwave radiation/PAR dataset. United States. doi:10.25584/1595069.
Hao, Dalei, Chen, Min, Asrar, Ghassem, Zeng, Yelu, Zhu, Qing, Wen, Jianguang, and Xiao, Qing. 2020. "A global DSCOVR/EPIC-based hourly/daily shortwave radiation/PAR dataset". United States. doi:10.25584/1595069. https://www.osti.gov/servlets/purl/1595069. Pub date:Mon Jan 27 00:00:00 EST 2020
@article{osti_1595069,
title = {A global DSCOVR/EPIC-based hourly/daily shortwave radiation/PAR dataset},
author = {Hao, Dalei and Chen, Min and Asrar, Ghassem and Zeng, Yelu and Zhu, Qing and Wen, Jianguang and Xiao, Qing},
abstractNote = {Downward shortwave radiation (SW) and photosynthetically active radiation (PAR) play crucial roles in Earth system dynamics. Spaceborne remote sensing techniques provide a unique approach for mapping accurate spatio-temporally-continuous SW/PAR. However, any individual polar-orbiting or geostationary satellite cannot satisfy the desired high temporal resolution (sub-daily) and global coverage simultaneously, while integrating and fusing multi-source data from complementary satellites/sensors is challenging because of co-registration, inter-calibration, near real-time data delivery and the effects of discrepancies in orbital geometry. The Earth Polychromatic Imaging Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR), launched in February 2015, opens an unprecedented possibility to bridge the gap between high temporal resolution and global coverage, and characterize the diurnal cycles of SW/PAR globally. In this paper, we adopt a suite of well-validated data-driven machine-learning models to generate the first global land products of SW/PAR, from June 2015 to June 2019, based on DSCOVR/EPIC data. The generated products have high temporal resolution (hourly) and medium spatial resolution (0.1°×0.1°), and include estimates of the direct and diffuse components of SW/PAR. We used widely-distributed ground station data from the Baseline Surface Radiation Network (BSRN), the Surface Radiation Budget Network (SURFRAD), NOAA’s Global Monitoring Division and the U.S. Department of Energy’s Atmospheric System Research (ASR) program to evaluate the performance of our products, and further analyzed and compared the spatio-temporal characteristics of the derived products with the benchmarking Clouds and the Earth's Radiant Energy System Synoptic (CERES) data. Both the hourly and daily products are consistent with ground observations (e.g., hourly and daily total SWs have low biases of -3.96 and -0.71 W/m2 and root mean square errors (RMSEs) of 103.50 and 35.40 W/m2, respectively). The developed products capture complex spatio-temporal patterns well and accurately track substantial diurnal, monthly, and seasonal variations of SW/PAR when compared to CERES data. They provide a reliable and valuable alternative for solar photovoltaic applications and improve our understanding the diurnal variabilities of the terrestrial water, carbon and energy fluxes at various spatial scales. The hourly data are grouped by day in distinct NetCDF files, which are named as “EPIC_SW_PAR_Hourly_yyyymmdd.nc” where “yyyy”, “mm”, and “dd” denote year, month, and day (UTC time). The daily data are grouped by month in distinct NetCDF files, which are named as “EPIC_SW_PAR_Daily_yyyymm.nc” where “yyyy”, and “mm” denote year and month (UTC time). Each NetCDF file contains latitude, longitude, time, diffuse SW, direct SW, diffuse PAR, direct PAR, and the corresponding quality flags which indicates where the pixel is gap-filled or not. The scale factor for the direct and diffuse SW/PAR is 0.1. The total SW/PAR can be calculated by combining the direct and diffuse components. The information about the version, creation date, reference, contact mails, and other comments are also included in the file.},
doi = {10.25584/1595069},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2020},
month = {1}
}

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