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Validation of Hourly Global Horizontal Irradiance for Two Satellite-Derived Datasets in Northeast Iraq

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journal contribution
posted on 2019-09-02, 13:39 authored by B Ameen, H Balzter, C Jarvis, E Wey, C Thomas, M Marchand
Several sectors need global horizontal irradiance (GHI) data for various purposes. However, the availability of a long-term time series of high quality in situ GHI measurements is limited. Therefore, several studies have tried to estimate GHI by re-analysing climate data or satellite images. Validation is essential for the later use of GHI data in the regions with a scarcity of ground-recorded data. This study contributes to previous studies that have been carried out in the past to validate HelioClim-3 version 5 (HC3v5) and the Copernicus Atmosphere Monitoring Service, using radiation service version 3 (CRSv3) data of hourly GHI from satellite-derived datasets (SDD) with nine ground stations in northeast Iraq, which have not been used previously. The validation is carried out with station data at the pixel locations and two other data points in the vicinity of each station, which is something that is rarely seen in the literature. The temporal and spatial trends of the ground data are well captured by the two SDDs. Correlation ranges from 0.94 to 0.97 in all-sky and clear-sky conditions in most cases, while for cloudy-sky conditions, it is between 0.51–0.72 and 0.82–0.89 for the clearness index. The bias is negative for most of the cases, except for three positive cases. It ranges from −7% to 4%, and −8% to 3% for the all-sky and clear-sky conditions, respectively. For cloudy-sky conditions, the bias is positive, and differs from one station to another, from 16% to 85%. The root mean square error (RMSE) ranges between 12–20% and 8–12% for all-sky and clear-sky conditions, respectively. In contrast, the RMSE range is significantly higher in cloudy-sky conditions: above 56%. The bias and RMSE for the clearness index are nearly the same as those for the GHI for all-sky conditions. The spatial variability of hourly GHI SDD differs only by 2%, depending on the station location compared to the data points around each station. The variability of two SDDs is quite similar to the ground data, based on the mean and standard deviation of hourly GHI in a month. Having station data at different timescales and the small number of stations with GHI records in the region are the main limitations of this analysis.

Funding

The Higher Committee for Education Development in Iraq (HCED) funded this study as a scholarship, the Center for Landscape and Climate Research (CLCR) and the National Centre for Earth Observation (NERC) supported it. The authors are extremely grateful for the assistance of the Directorate of Meteorology—Sulaymaniyah and KRG Ministry of electricity for providing meteorological data. The authors are grateful to Soda Service for allowing access and free use of GHI SDD of CRSv3 data and for a subscription to use the HC3v5 data.

History

Citation

Remote Sensing, 2018, 10(10), 1651

Author affiliation

/Organisation/COLLEGE OF SCIENCE AND ENGINEERING/School of Geography, Geology and the Environment/GIS and Remote Sensing

Version

  • VoR (Version of Record)

Published in

Remote Sensing

Publisher

MDPI

issn

2072-4292

Acceptance date

2018-10-15

Copyright date

2018

Available date

2019-09-02

Publisher version

https://www.mdpi.com/2072-4292/10/10/1651

Notes

The following are Available online at http://www.mdpi.com/2072-4292/10/10/1651/s1, Figures S1–S5: Cumulative frequency function of ground data compared to SDDs for all-sky conditions for the available period of data pairs. The closer red and green lines (SDDs) are to the black line (ground data) shows better performance of SDDs. A difference between lines shows the errors. Figures S6–S15 as in Figure S1 but for clear-sky and cloudy-sky conditions respectively

Language

en