
Short‐term forecasts of biologically effective UV radiation: Comparison between modelled and measured irradiation
Author(s) -
Feister Uwe
Publication year - 1996
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.5060030108
Subject(s) - environmental science , cloud cover , ozone , atmospheric sciences , meteorology , radiation , aerosol , biosphere , ultraviolet , climatology , materials science , cloud computing , physics , geology , optoelectronics , quantum mechanics , computer science , operating system , astronomy
Ultraviolet (UV) radiation from the sun affects the biosphere and chemical processes of atmospheric trace gases. The amount of atmospheric ozone as well as the amount of clouds and atmospheric aerosols determine the UV radiation reaching the earth's surface at a definite place and time. Using numerically forecast meteorological parameters such as temperature and relative vorticity at different pressure levels, a short‐term forecast of atmospheric ozone was calculated. This ozone value and the numerically forecast cloud cover were fed into a UV forecasting model to determine a short‐term forecast of biologically effective UV radiation. UV radiation forecasts were calculated for three stations in the northern, central and southern part of Germany. Comparisons between ozone forecasts and ground‐based as well as satellite‐based ozone measurements for the summer months of 1994 showed the uncertainty of ozone forecasts to be within ±3% and ±6%. Values of the modelled biologically effective UV radiation were compared with measured UV radiation data taken with UV filter instruments and with a spectro‐radidmeter at Potsdam in the period September 1993 to September 1994. It turned out that for a cloud cover of less than 4/8 to 5/8, the model calculations overestimated the measured irradiation by about 10 to 15%. The main reason for the discrepancy between model calculations and measurements may be the cloud parameterization in the model. Also, the method of estimating the aerosol load as well as uncertainties in the measured UV radiation may have contributed to the differences.