Open AccessEstimation of photosynthetically active radiation absorbed at the surface
Author(s) -
Li Zhanqing,
Moreau Louis,
Cihlar Josef
Publication year - 1997
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.67
H-Index - 298
eISSN - 2156-2202
pISSN - 0148-0227
DOI - 10.1029/97jd01219
Subject(s) - photosynthetically active radiation , downwelling , environmental science , albedo (alchemy) , satellite , remote sensing , atmospheric sciences , optical depth , flux (metallurgy) , atmosphere (unit) , solar zenith angle , aerosol , meteorology , upwelling , physics , photosynthesis , geology , art , oceanography , botany , materials science , astronomy , performance art , metallurgy , biology , art history
This paper presents a validation and application of an algorithm by Li and Moreau [1996] for retrieving photosynthetically active radiation (PAR) absorbed at the surface (APAR SFC ). APAR SFC is a key input to estimating PAR absorbed by the green canopy during photosynthesis. Extensive ground‐based and space‐borne observations collected during the BOREAS experiment in 1994 were processed, colocated, and analyzed. They include downwelling and upwelling PAR observed at three flux towers, aerosol optical depth from ground‐based photometers, and satellite reflectance measurements at the top of the atmosphere. The effects of three‐dimensional clouds, aerosols, and bidirectional dependence on the retrieval of APAR SFC were examined. While the algorithm is simple and has only three input parameters, the comparison between observed and estimated APAR SFC shows a small bias error (<10 W m −2 ) and moderate random error (36 W m ‐2 for clear, 61 W m −2 for cloudy). Temporal and/or spatial mismatch between satellite and surface observations is a major cause of the random error, especially when broken clouds are present. The algorithm was subsequently employed to map the distribution of monthly mean APAR SFC over the 1000×1000 km 2 BOREAS region. Considerable spatial variation is found due to variable cloudiness, forest fires, and nonuniform surface albedo.