2019
DOI: 10.1002/met.1865
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Improvement of the 24 hr forecast of surface UV radiation using an ensemble approach

Abstract: A methodology is proposed to improve the 24 hr forecast of the ultraviolet (UV) index and the duration of exposure to obtain the minimal erythemal dose (MED). A forecast ensemble consisting of 10 members (differing in initial and boundary conditions) is examined to search for the best performed ensemble member. Routine UV measurements are used for the forecast validation. These are carried out at Belsk (20.8 ° E, 51.8 ° N) and in Racibórz (18.2 ° E, 50.1 ° N) representing a rural and an urban site in Poland, r… Show more

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“…National weather services and other agencies use models to predict the diurnal course of the UVI (e.g., every hour) for one or several days into the future (e.g., the Israel Meteorological Service ( https://ims.gov.il/en/UVIHourly ), the German Meteorological Service ( https://kunden.dwd.de/uvi/index.jsp ), and the Copernicus Atmosphere Monitoring Service ( https://climate-adapt.eea.europa.eu/observatory/evidence/projections-and-tools/cams-uv-index-forecast ). New methods for improving UVI forecasts have recently been proposed based on an “ensemble member” approach, where a model is executed multiple times with different initial conditions [ 330 ], and a machine learning algorithm [ 331 ].…”
Section: Advances In Uv Monitoring and Modelingmentioning
confidence: 99%
“…National weather services and other agencies use models to predict the diurnal course of the UVI (e.g., every hour) for one or several days into the future (e.g., the Israel Meteorological Service ( https://ims.gov.il/en/UVIHourly ), the German Meteorological Service ( https://kunden.dwd.de/uvi/index.jsp ), and the Copernicus Atmosphere Monitoring Service ( https://climate-adapt.eea.europa.eu/observatory/evidence/projections-and-tools/cams-uv-index-forecast ). New methods for improving UVI forecasts have recently been proposed based on an “ensemble member” approach, where a model is executed multiple times with different initial conditions [ 330 ], and a machine learning algorithm [ 331 ].…”
Section: Advances In Uv Monitoring and Modelingmentioning
confidence: 99%