Paper
18 April 2003 Retrieval of PAR-estimates using remote sensing data and radiation transfer models
Sascha Fistric, Gerhard Gesell, Kurt P. Guenther
Author Affiliations +
Proceedings Volume 4882, Remote Sensing of Clouds and the Atmosphere VII; (2003) https://doi.org/10.1117/12.462410
Event: International Symposium on Remote Sensing, 2002, Crete, Greece
Abstract
A new method is proposed for retrieving the photosynthetically active radiation (PAR) using remote sensing data (AVHRR) and a radiation transfer model (libRadtran). The approach applicable for clear and cloudy sky conditions takes into account atmospheric parameters affecting the radiation transfer through the atmosphere, namely, extinction by aerosols and clouds. Due to the high temporal variability of cloud distribution and cloud properties, a geostationary satellite as e.g. the future Meteosat Second Generation (MSG) with SEVIRI on board is proposed to derive inter-daily variation of cloud parameters. The upcoming SEVIRI sensor will deliver spectral information of clouds and atmosphere every 15 minutes. The spectral information content of SEVIRI is simulated by the existing polar orbiting sensor Advanced Very High Resolution Radiometer (AVHRR) on board of the NOAA satellites. Our first results are validated with ground truth data from the European Light Dosimeter Network (ELDONET). Up to 8 stations distributed over Europe are available for validation purposes. It is shown that for heterogeneous atmospheric conditions a good correlation exist between measured and estimated PAR values. Processing more AVHRR data over a longer time period and fine-adjustment of the algorithms combined with extended validation will consolidate our findings in the future.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sascha Fistric, Gerhard Gesell, and Kurt P. Guenther "Retrieval of PAR-estimates using remote sensing data and radiation transfer models", Proc. SPIE 4882, Remote Sensing of Clouds and the Atmosphere VII, (18 April 2003); https://doi.org/10.1117/12.462410
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KEYWORDS
Clouds

Data modeling

Aerosols

Atmospheric modeling

Remote sensing

Atmospheric particles

Commercial off the shelf technology

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