{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:08:00Z","timestamp":1760242080580,"version":"build-2065373602"},"reference-count":46,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2018,12,12]],"date-time":"2018-12-12T00:00:00Z","timestamp":1544572800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Since the main attenuation of solar irradiance reaching the earth\u2019s surface is due to clouds, it has been hypothesized that global horizontal irradiance attenuation and its temporal variability at a given location could be characterized simply by cloud properties at that location. This hypothesis is tested using global horizontal irradiance measurements at two stations in San Antonio, Texas, and satellite estimates of cloud types and cloud layers from the Geostationary Operational Environmental Satellite (GOES) Surface and Insolation Product. A modified version of an existing solar attenuation variability index, albeit having a better physical foundation, is used. The analysis is conducted for different cloud conditions and solar elevations. It is found that under cloudy-sky conditions, there is less attenuation under water clouds than those under opaque ice clouds (optically thick ice clouds) and multilayered clouds. For cloud layers, less attenuation was found for the low\/mid layers than for the high layer. Cloud enhancement occurs more frequently for water clouds and less frequently for mixed phase and cirrus clouds and it occurs with similar frequency at all three levels. The temporal variability of solar attenuation is found to decrease with an increasing temporal sampling interval and to be largest for water clouds and smallest for multilayered and partly cloudy conditions. This work presents a first step towards estimating solar energy potential in the San Antonio area indirectly using available estimates of cloudiness from GOES satellites.<\/jats:p>","DOI":"10.3390\/rs10122016","type":"journal-article","created":{"date-parts":[[2018,12,12]],"date-time":"2018-12-12T10:54:26Z","timestamp":1544612066000},"page":"2016","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Characterizing Variability of Solar Irradiance in San Antonio, Texas Using Satellite Observations of Cloudiness"],"prefix":"10.3390","volume":"10","author":[{"given":"Shuang","family":"Xia","sequence":"first","affiliation":[{"name":"Texas Sustainable Energy Research Institute, University of Texas at San Antonio, San Antonio, TX 78249, USA"},{"name":"Laboratory for Remote Sensing and Geoinformatics, Department of Geological Sciences, University of Texas at San Antonio, San Antonio, TX 78249, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3546-3668","authenticated-orcid":false,"given":"Alberto M.","family":"Mestas-Nu\u00f1ez","sequence":"additional","affiliation":[{"name":"Laboratory for Remote Sensing and Geoinformatics, Department of Geological Sciences, University of Texas at San Antonio, San Antonio, TX 78249, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3516-1210","authenticated-orcid":false,"given":"Hongjie","family":"Xie","sequence":"additional","affiliation":[{"name":"Laboratory for Remote Sensing and Geoinformatics, Department of Geological Sciences, University of Texas at San Antonio, San Antonio, TX 78249, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7069-1044","authenticated-orcid":false,"given":"Jiakui","family":"Tang","sequence":"additional","affiliation":[{"name":"Laboratory for Remote Sensing and Geoinformatics, Department of Geological Sciences, University of Texas at San Antonio, San Antonio, TX 78249, USA"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"given":"Rolando","family":"Vega","sequence":"additional","affiliation":[{"name":"CPS Energy, San Antonio, TX 78205, USA"}]}],"member":"1968","published-online":{"date-parts":[[2018,12,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"186","DOI":"10.1016\/j.astropartphys.2013.03.001","article-title":"Cosmic rays and terrestrial life: A brief review","volume":"53","author":"Atri","year":"2014","journal-title":"Astropart. Phys."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"284","DOI":"10.1016\/j.rser.2014.08.046","article-title":"Global prospects, progress, policies, and environmental impact of solar photovoltaic power generation","volume":"41","author":"Hosenuzzaman","year":"2015","journal-title":"Renew. Sust. Energy Rev."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1016\/S0038-092X(03)00124-5","article-title":"A method to calibrate a solar pyranometer for measuring reference diffuse irradiance","volume":"74","author":"Reda","year":"2003","journal-title":"Sol. Energy"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Hodge, B.-M., and Milligan, M. (2011, January 24\u201329). Wind power forecasting error distributions over multiple timescales. Proceedings of the 2011 IEEE Power and Energy Society General Meeting, Detroit, MI, USA.","DOI":"10.1109\/PES.2011.6039388"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"902","DOI":"10.1016\/j.apenergy.2017.01.013","article-title":"Output power variation of different PV array configurations during irradiance transitions caused by moving clouds","volume":"190","author":"Lappalainen","year":"2017","journal-title":"Appl. Energy"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"2867","DOI":"10.1016\/j.renene.2010.05.013","article-title":"Solar variability of four sites across the state of Colorado","volume":"35","author":"Lave","year":"2010","journal-title":"Renew. Energy"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"2190","DOI":"10.1016\/j.solener.2011.06.031","article-title":"High-frequency irradiance fluctuations and geographic smoothing","volume":"86","author":"Lave","year":"2012","journal-title":"Sol. Energy"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"501","DOI":"10.1109\/TSTE.2012.2205716","article-title":"A wavelet-based variability model (WVM) for solar PV power plants","volume":"4","author":"Lave","year":"2013","journal-title":"IEEE Trans. Sustain. Energy"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Moumouni, Y., Baghzouz, Y., and Boehm, R.F. (2014, January 25\u201328). Power \u201csmoothing\u201d of a commercial-size photovoltaic system by an energy storage system. Proceedings of the 16th International Conference on Harmonics and Quality of Power (ICHQP), Bucharest, Romania.","DOI":"10.1109\/ICHQP.2014.6842838"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"4743","DOI":"10.1029\/1999JD901063","article-title":"Absorption of solar radiation by the atmosphere as determined using satellite, aircraft, and surface data during the Atmospheric Radiation Measurement Enhanced Shortwave Experiment (ARESE)","volume":"105","author":"Valero","year":"2000","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"207","DOI":"10.1016\/0038-092X(95)00092-6","article-title":"Modifications of the Heliosat procedure for irradiance estimates from satellite images","volume":"56","author":"Beyer","year":"1996","journal-title":"Sol. Energy"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"2649","DOI":"10.1029\/2000GL011743","article-title":"The clear-sky index to separate clear-sky from cloudy-sky situations in climate research","volume":"27","author":"Marty","year":"2000","journal-title":"Geophys. Res. Lett."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1016\/j.solener.2016.12.055","article-title":"Cloud cover effect of clear-sky index distributions and differences between human and automatic cloud observations","volume":"144","author":"Smith","year":"2017","journal-title":"Sol. Energy"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"160","DOI":"10.1016\/j.rse.2004.02.009","article-title":"Rethinking satellite-based solar irradiance modelling: The SOLIS clear-sky module","volume":"91","author":"Mueller","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_15","unstructured":"Reno, M.J., Hansen, C.W., and Stein, J.S. (2012). Global Horizontal Irradiance Clear Sky Models: Implementation and Analysis."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1016\/S0038-092X(02)00045-2","article-title":"A new airmass independent formulation for the Linke turbidity coefficient","volume":"73","author":"Ineichen","year":"2002","journal-title":"Sol. Energy"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"307","DOI":"10.1016\/S0038-092X(02)00122-6","article-title":"A new operational model for satellite-derived irradiances: Description and validation","volume":"73","author":"Perez","year":"2002","journal-title":"Sol. Energy"},{"key":"ref_18","unstructured":"Gueymard, C. (, January January). High performance model for clear-sky irradiance and illuminance. Proceedings of the Solar 2004 Conference, Portland, OR, USA."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"355","DOI":"10.1016\/S0038-092X(03)00195-6","article-title":"Direct solar transmittance and irradiance predictions with broadband models. Part I: Detailed theoretical performance assessment","volume":"74","author":"Gueymard","year":"2003","journal-title":"Sol. Energy"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"192","DOI":"10.1016\/j.renene.2015.10.049","article-title":"On the use of the coefficient of variation to measure spatial and temporal correlation of global solar radiation","volume":"88","author":"Calif","year":"2016","journal-title":"Renew. Energy"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1362","DOI":"10.1016\/j.renene.2015.09.058","article-title":"Quantitative evaluation of the impact of cloud transmittance and cloud velocity on the accuracy of short-term DNI forecasts","volume":"86","author":"Li","year":"2016","journal-title":"Renew. Energy"},{"key":"ref_22","unstructured":"Stein, J.S., Hansen, C.W., and Reno, M.J. (2012, January 13\u201317). The variability index: A new and novel metric for quantifying irradiance and PV output variability. Proceedings of the World Renewable Energy Forum, Denver, CO, USA."},{"key":"ref_23","unstructured":"Reno, M.J., and Stein, J. (2013, January 16\u201320). Using Cloud Classification to Model Solar Variability. Proceedings of the ASES National Solar Conference, Baltimore, MD, USA."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Schroedter-Homscheidt, M., Kosmale, M., Jung, S., and Kleissl, J. (2018). Classifying ground-measured 1 min temporal variability within hourly intervals for direct normal irradiances. Meteorol. Z.","DOI":"10.1127\/metz\/2018\/0875"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"2617","DOI":"10.1029\/2000GL012659","article-title":"Cloud cover variations over the United States: An influence of cosmic rays or solar variability?","volume":"28","author":"Udelhofen","year":"2001","journal-title":"Geophys. Res. Lett."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1016\/j.solener.2016.03.019","article-title":"High PV penetration impacts on five local distribution networks using high resolution solar resource assessment with sky imager and quasi-steady state distribution system simulations","volume":"132","author":"Nguyen","year":"2016","journal-title":"Sol. Energy"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Xia, S., Mestas-Nu\u00f1ez, A.M., Xie, H., and Vega, R. (2017). An evaluation of satellite estimates of solar surface irradiance using ground observations in San Antonio, Texas, USA. Remote Sens., 9.","DOI":"10.3390\/rs9121268"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1016\/j.rse.2017.04.002","article-title":"Investigations of improvements to an operational GOES-satellite-data-based insolation system using pyranometer data from the US Climate Reference Network (USCRN)","volume":"195","author":"Diak","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_29","unstructured":"Sengupta, M., Habte, A., Gotseff, P., Weekley, A., Lopez, A., Molling, C., and Heidinger, A. (2014, January 22\u201326). A Physics-based GOES Satellite Product for Use in NREL\u2019s National Solar Radiation Database. Proceedings of the European Photovoltaic Solar Energy Conference and Exhibition, Amsterdam, The Netherlands."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"762","DOI":"10.1175\/2099.1","article-title":"Daytime cloud overlap detection from AVHRR and VIIRS","volume":"43","author":"Pavolonis","year":"2004","journal-title":"J. Appl. Meteorol."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"804","DOI":"10.1175\/JAM2236.1","article-title":"Daytime global cloud typing from AVHRR and VIIRS: Algorithm description, validation, and comparisons","volume":"44","author":"Pavolonis","year":"2005","journal-title":"J. Appl. Meteorol."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"477","DOI":"10.1016\/0038-092X(92)90155-4","article-title":"The probability density and autocorrelation of short-term global and beam irradiance","volume":"49","author":"Skartveit","year":"1992","journal-title":"Sol. Energy"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"4735","DOI":"10.1364\/AO.28.004735","article-title":"Revised optical air mass tables and approximation formula","volume":"28","author":"Kasten","year":"1989","journal-title":"Appl. Opt."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"128","DOI":"10.1016\/j.solener.2016.02.011","article-title":"Cloud enhancement of global horizontal irradiance in California and Hawaii","volume":"130","author":"Inman","year":"2016","journal-title":"Sol. Energy"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"459","DOI":"10.1016\/j.renene.2013.08.001","article-title":"Enhanced values of global irradiance due to the presence of clouds in Eastern Mediterranean","volume":"62","author":"Tapakis","year":"2014","journal-title":"Renew. Energy"},{"key":"ref_36","unstructured":"Stephens, G.L. (1994). Remote Sensing of the Lower Atmosphere, Oxford University Press."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"2559","DOI":"10.1002\/2016JD025951","article-title":"The role of cloud phase in Earth\u2019s radiation budget","volume":"122","author":"Matus","year":"2017","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"224","DOI":"10.1126\/science.aad5300","article-title":"Observational constraints on mixed-phase clouds imply higher climate sensitivity","volume":"352","author":"Tan","year":"2016","journal-title":"Science"},{"key":"ref_39","first-page":"1151","article-title":"Impacts of solar variability on distribution networks performance","volume":"12","author":"Annathurai","year":"2017","journal-title":"Int. J. Appl. Eng. Res."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1016\/j.solener.2015.02.032","article-title":"Stochastic generation of synthetic minutely irradiance time series derived from mean hourly weather observation data","volume":"115","author":"Bright","year":"2015","journal-title":"Sol. Energy"},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Gan, C.K., Lau, C.Y., Baharin, K.A., and Pudjianto, D. (2017). Impact of the photovoltaic system variability on transformer tap changer operations in distribution networks. CIRED Open Access Proc. J., 1818\u20131821.","DOI":"10.1049\/oap-cired.2017.0476"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1433","DOI":"10.1016\/j.renene.2015.09.012","article-title":"Extreme global solar irradiance due to cloud enhancement in northeastern Brazil","volume":"86","author":"Tiba","year":"2016","journal-title":"Renew. Energy"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"755","DOI":"10.1016\/j.solener.2017.05.004","article-title":"Cloud and albedo enhancement impacts on solar irradiance using high-frequency measurements from thermopile and photodiode radiometers. Part 1: Impacts on global horizontal irradiance","volume":"153","author":"Gueymard","year":"2017","journal-title":"Sol. Energy"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1175\/1520-0477(1991)072<0002:ICDP>2.0.CO;2","article-title":"ISCCP cloud data products","volume":"72","author":"Rossow","year":"1991","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"2283","DOI":"10.1175\/JAMC-D-11-067.1","article-title":"Retrieval of ice cloud optical thickness and effective particle size using a fast infrared radiative transfer model","volume":"50","author":"Wang","year":"2011","journal-title":"J. Appl. Meteorol. Climatol."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"4439","DOI":"10.5194\/acp-18-4439-2018","article-title":"Comparing airborne and satellite retrievals of cloud optical thickness and particle effective radius using a spectral radiance ratio technique: Two case studies for cirrus and deep convective clouds","volume":"18","author":"Krisna","year":"2018","journal-title":"Atmos. Chem. Phys."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/12\/2016\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:33:29Z","timestamp":1760196809000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/12\/2016"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,12,12]]},"references-count":46,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2018,12]]}},"alternative-id":["rs10122016"],"URL":"https:\/\/doi.org\/10.3390\/rs10122016","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2018,12,12]]}}}