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Citation link: http://nbn-resolving.de/urn:nbn:de:gbv:46-00106738-16
00106738-1.pdf
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Improving an optimal estimation algorithm for surface and atmospheric parameter retrieval using passive microwave data in the Arctic


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Other Titles: Verbesserung einer Optimierungsmethode zur Bestimmung von Erdoberflächen- und Atmosphärenparametern mit Daten von passiven Mikrowellensensoren in der Arktis
Authors: Scarlat, Raul Cristian  
Supervisor: Heygster, Georg
1. Expert: Spreen, Gunnar 
2. Expert: Pedersen, Leif Toudal 
Abstract: 
In this study we present improvements on an integrated retrieval method for atmospheric and surface parameters in the Arctic. The instrument used is the Advanced Microwave Scanning Radiometer - Earth Observing System (EOS) (AMSR-E) radiometer on board NASAa s Aqua satellite. The core of the method is a forward model which can ingest bulk data for seven geophysical parameters to reproduce the brightness temperatures observed by a passive microwave radiometer. The method inverts the forward model and produces ensembles of the seven parameters: wind speed, integrated water vapor, liquid water path, sea and ice temperature, sea ice concentration and multi-year ice fraction. The method is constrained using numerical weather prediction data in order to retrieve a set of geophysical parameters that best fit the measurements. An iterative method minimizes the cost function and finds the optimal ensemble of the seven parameters that best match the observed brightness temperatures.
Keywords: Arctic, optimal estimation, satellite remote sensing, sea ice, radiative transfer model, information content analysis
Issue Date: 23-Aug-2018
Type: Dissertation
URN: urn:nbn:de:gbv:46-00106738-16
Institution: Universität Bremen 
Faculty: FB1 Physik/Elektrotechnik 
Appears in Collections:Dissertationen

  

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