posted on 2019-08-09, 13:35authored byBikhtiyar Ameen, Heiko Balzter, Claire Jarvis
Solar Radiation (SR) data are required for many disciplines and applications. The ground measurement of SR data is hampered by technical and operational errors. Therefore, several approaches have been developed to detect these errors. This study aimed to compare two quality tests of hourly Global Horizontal Irradiance (GHI) estimates through the Baseline Surface Radiation Network (BSRN) of the World Meteorological Organization (WMO) and Top of Atmosphere irradiance and Clear sky (TOACs) on a horizontal plane. Each of these tests has a threshold to pass data, which leads to different results. A newly developed quality test method is presented that uses Sunshine Duration (SD) and Air Temperature (AT) to check hourly GHI and is applied to data from 20 meteorological stations in northeast Iraq. The new method was validated using independent high quality data from six stations in various regions with the same climate regime. The method consists of several tests that compare ground data with upper and lower limits of radiation at the top of the atmosphere, using a clear sky radiation model and the relation between SD and AT with SR to determine data values of dubious quality. The rate of error flags generally range from 1% to 27%. The findings show that SD and AT can be used to support other quality tests and to detect nearly 2% additional dubious data values compared to BSRN and TOACs tests. The SD test tends to work like a consistency check but AT does not work like that according to the validation result. However, AT can be used to test the plausibility of data. The argument for using AT in this study may be impractical for other climate conditions. The results suggest that a combination of tests can lead to a better quality of ground data, especially when the components of SR are unviable. Using climate variables for further checks is another possibility.
Funding
B.A. wish to thank the Higher Committee for Education Development in Iraq (HCED) for
funding this study as a scholarship, the Center for Landscape and Climate Research (CLCR), and the National
Centre for Earth Observation’s (NERC) University of Leicester, United Kingdom for their support. The authors
thank gratefully to the KRG Ministry of electricity and Directorate of Meteorology-Sulaimanyiah, for providing
meteorological data. The authors are grateful to Australian Bureau of Meteorology, Commonwealth of Australia,
NREL, BSRN, and Soda Services for accessing and using their data for free. A special thanks to the Lucien Wald,
MINES ParisTech-France for his oral advice to the study
History
Citation
Climate, 2018, 6 (3), 69
Author affiliation
/Organisation/COLLEGE OF SCIENCE AND ENGINEERING/School of Geography, Geology and the Environment/GIS and Remote Sensing