A feasibility study of the estimation of net solar radiation at the sea surface using NOAA-9 AVHRR data
Jiujing Gu
1991
A feasibility study is presented of the use of a simple physical parameterization to estimate sea-surface net solar flux from radiance measurements taken by the Advanced Very High Resolution Radiometer (AVHRR) on board National Oceanic and Atmospheric Administration (NOAA) polar orbiting satellites. The scheme, which is based on Gautier's parameterization for geostationary satellite data, is revised for application to AVHRR data at high latitudes. The revised technique employs relationships
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... g cloud optical and microphysical parameters, cloud broadband radiative properties, and the AVHRR channel radiances derived using a 24-band δ-Eddington radiative transfer model. The δ-Eddington model is used to test the sensitivity of the daily mean surface net flux to variations in ozone amount, column water vapor amount, surface albedo, cloud optical thickness, cloud fraction and droplet size. Over typical ranges of these variabilities, the uncertainty of daily mean surface net solar flux is less than 6 W m⁻² for the clear case. For the cloud case, the main uncertainty of surface net flux is due to the variations in cloud optical depth and cloud fraction. The typical sensitivities in cloud optical depth and cloud amount introduce variations in the surface net flux of 17 W m⁻²and 9 W m⁻², respectively. Based on these sensitivity studies, a modification of Gautier's simple physical model is proposed. This modification calculates cloud optical depth and droplet effective radius from the top of the atmosphere (TOA) upward fluxes in AVHRR channel 1 and 3, and then uses these derived parameters, with solar zenith angle, to estimate cloud albedo and absorptance. To compare the original and the modified Gautier model, the Slingo δ-Eddington model is used to simulate the satellite and pyrometer measurements in the real world. Simulation studies under standard midlatitude summer conditions show that the original model may produce surface net flux errors of over 30 W m⁻², mainly due to the poor estimation of cloud broadband absorpt [...]
doi:10.14288/1.0052643
fatcat:a232474lsbfv7dphi37q7zllgi