{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,3]],"date-time":"2025-11-03T13:43:29Z","timestamp":1762177409344,"version":"build-2065373602"},"reference-count":95,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2021,4,29]],"date-time":"2021-04-29T00:00:00Z","timestamp":1619654400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Australian Research Council","award":["FT140100610","DP140104178"],"award-info":[{"award-number":["FT140100610","DP140104178"]}]},{"name":"The Scientific and Technological Research Council of Turkey","award":["118C329"],"award-info":[{"award-number":["118C329"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Atmospheric transmissivity (\u03c4) is a critical factor in climatology, which affects surface energy balance, measured at a limited number of meteorological stations worldwide. With the limited availability of meteorological datasets in remote areas across different climatic regions, estimation of \u03c4 is becoming a challenging task for adequate hydrological, climatic, and crop modeling studies. The availability of solar radiation data is comparatively less accessible on a global scale than the temperature and precipitation datasets, which makes it necessary to develop methods to estimate \u03c4. Most of the previous studies provided region specific datasets of \u03c4, which usually provide local assessments. Hence, there is a necessity to give the empirical models for \u03c4 estimation on a global scale that can be easily assessed. This study presents the analysis of the \u03c4 relationship with varying geographic features and climatic factors like latitude, aridity index, cloud cover, precipitation, temperature, diurnal temperature range, and elevation. In addition to these factors, the applicability of these relationships was evaluated for different climate types. Thus, empirical models have been proposed for each climate type to estimate \u03c4 by using the most effective factors such as cloud cover and aridity index. The cloud cover is an important yet often overlooked factor that can be used to determine the global atmospheric transmissivity. The empirical relationship and statistical indicator provided the best performance in equatorial climates as the coefficient of determination (r2) was 0.88 relatively higher than the warm temperate (r2 = 0.74) and arid regions (r2 = 0.46). According to the results, it is believed that the analysis presented in this work is applicable for estimating the \u03c4 in different ecosystems across the globe.<\/jats:p>","DOI":"10.3390\/rs13091716","type":"journal-article","created":{"date-parts":[[2021,4,29]],"date-time":"2021-04-29T04:30:11Z","timestamp":1619670611000},"page":"1716","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":29,"title":["Global Analysis of Atmospheric Transmissivity Using Cloud Cover, Aridity and Flux Network Datasets"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3963-265X","authenticated-orcid":false,"given":"Ankur","family":"Srivastava","sequence":"first","affiliation":[{"name":"Center for Water Security and Environmental Sustainability and School of Engineering, The University of Newcastle, Callaghan 2308, Australia"}]},{"given":"Jose F.","family":"Rodriguez","sequence":"additional","affiliation":[{"name":"Center for Water Security and Environmental Sustainability and School of Engineering, The University of Newcastle, Callaghan 2308, Australia"}]},{"given":"Patricia M.","family":"Saco","sequence":"additional","affiliation":[{"name":"Center for Water Security and Environmental Sustainability and School of Engineering, The University of Newcastle, Callaghan 2308, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3765-529X","authenticated-orcid":false,"given":"Nikul","family":"Kumari","sequence":"additional","affiliation":[{"name":"Center for Water Security and Environmental Sustainability and School of Engineering, The University of Newcastle, Callaghan 2308, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1593-3519","authenticated-orcid":false,"given":"Omer","family":"Yetemen","sequence":"additional","affiliation":[{"name":"Center for Water Security and Environmental Sustainability and School of Engineering, The University of Newcastle, Callaghan 2308, Australia"},{"name":"Eurasia Institute of Earth Sciences, Istanbul Technical University, Maslak, Istanbul 34469, Turkey"}]}],"member":"1968","published-online":{"date-parts":[[2021,4,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"305","DOI":"10.1016\/S0065-2687(08)60176-4","article-title":"Land surface processes and climate\u2014Surface albedos and energy balance","volume":"Volume 25","author":"Dickinson","year":"1983","journal-title":"Advances in Geophysics"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1121","DOI":"10.1002\/joc.1060","article-title":"Atmospheric transmissivity: Distribution and empirical estimation around the central Andes","volume":"24","author":"Baigorria","year":"2004","journal-title":"Int. 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