Open AccessImprovement of the 24 hr forecast of surface UV radiation using an ensemble approach
Author(s) -
Krzyścin Janusz W.,
Guzikowski Jakub,
Pietruczuk Aleksander,
Sobolewski Piotr S.
Publication year - 2019
Publication title -
meteorological applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.672
H-Index - 59
eISSN - 1469-8080
pISSN - 1350-4827
DOI - 10.1002/met.1865
Subject(s) - environmental science , cloud cover , weather research and forecasting model , sky , ensemble forecasting , meteorology , irradiance , bootstrapping (finance) , mean squared error , statistics , mathematics , computer science , cloud computing , econometrics , physics , quantum mechanics , operating system
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, respectively. Each ensemble member is built using the clear‐sky simulations by a radiative transfer model. The clear‐sky irradiance is attenuated using the cloud modification factor (CMF) depending on the cloud cover by low‐ and mid‐level clouds. The 24 hr forecast of cloudiness is obtained by the Weather Research and Forecasting (WRF) model. Every day, for each ensemble member, the optimal CMF values are built by the offline bootstrapping of the original CMF matrix. The performance of all ensemble members is evaluated for the day preceding the forecast. The best one is subsequently used for the next‐day forecast. This procedure provides a more accurate forecast than that based on a single member of the ensemble. For both sites, the root mean square percentage error for the duration of the MED exposure changes from about 30% to about 15%, and mean absolute percentage error from about 20–25% to about 10%.