Mapping daily and monthly radiation components using METEOSAT data

A. Rimóczi-Paál, J. Kerényi, J. Mika, R. Randriamampianina, I. Dobi, Z. Imecs, T. Szentimrey

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Abstract

The aim of the study is to present actual daily and climatically representative monthly maps of the surface radiation balance components derived from METEOSAT data. The encrypted digital images are now available in every three hours in Hungary. Hence, the first problem to solve is the estimation of diurnal mean radiation components from the archived 1-3 observations of the day between 8 and 15 UTC (+1-2 hours in local time). This computation is performed by Lagrange-interpolation. Since the skill of these day-to-day estimations is not at all obvious, the estimation of monthly averages is performed in two steps. First, the hourly observations from the 1992-1996 period are averaged for each hour separately, and these, more regularly varying values are smoothed by the Lagrange-interpolation, in the second step. For the monthly radiation maps, our purpose was also to improve their climatic representativity by using stratified sampling, based on macrosynoptic classification, first described by Mika et al (1994). This classification considers the surface pressure patterns in Central Europe and the reference climatology for them is originated from the 1961-1990 period. The differences between sample means and stratified means are in some cases considerable, as presented in the parallel figures of some months and components presented in the paper.

Original languageEnglish
Pages (from-to)967-970
Number of pages4
JournalAdvances in Space Research
Volume24
Issue number7
DOIs
Publication statusPublished - Jan 1 1999

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ASJC Scopus subject areas

  • Aerospace Engineering
  • Astronomy and Astrophysics
  • Geophysics
  • Atmospheric Science
  • Space and Planetary Science
  • Earth and Planetary Sciences(all)

Cite this

Rimóczi-Paál, A., Kerényi, J., Mika, J., Randriamampianina, R., Dobi, I., Imecs, Z., & Szentimrey, T. (1999). Mapping daily and monthly radiation components using METEOSAT data. Advances in Space Research, 24(7), 967-970. https://doi.org/10.1016/S0273-1177(99)00369-5