Reducing Weather Influences on Sea Ice Concentration Retrieval using Spaceborne 89 GHz Passive Microwave Observations

The major challenge of deriving sea ice concentration from the high resolution 89 GHz passive microwave observation is the strong atmospheric attenuation caused by water vapor and liquid water path, and surface variability induced by wind and temperature. In this study, we improve an 89 GHz sea ice...

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Bibliographic Details
Main Author: Lu, Junshen
Format: Thesis
Language:English
Published: Universität Bremen 2020
Subjects:
530
Online Access:https://dx.doi.org/10.26092/elib/389
https://media.suub.uni-bremen.de/handle/elib/4592
Description
Summary:The major challenge of deriving sea ice concentration from the high resolution 89 GHz passive microwave observation is the strong atmospheric attenuation caused by water vapor and liquid water path, and surface variability induced by wind and temperature. In this study, we improve an 89 GHz sea ice concentration retrieval algorithm called the Arctic Radiation and Turbulence Interaction STudy (ARTIST) Sea Ice (ASI) algorithm, by correcting the observed brightness temperatures for these weather influences before they enter the algorithm. The instrument used is the Advanced Microwave Scanning Radiometer - Earth Observing System (EOS) (AMSR-E) on board NASA’s Aqua satellite. The weather correction is realized by simulating changes induced by weather influences in the top of atmosphere brightness temperatures through a radiative transfer model. Two correction schemes are tested, one utilizing the numerical weather prediction data as input, and the other the retrievals of an optimal estimation method. Two improved versions of the ASI algorithm, ASI2 and ASI3, are developed respectively based on the corrected brightness temperatures and new tie points. For both the influence of the atmosphere on the 89 GHz brightness temperature is successfully reduced. Main results are a better representation of low ice concentration in the marginal ice zone, and a reduction in RMS of 2.3% over high ice compared to Landsat data.