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Satellite active and passive microwave remote sensing as a tool for improvement of the sea surface heat and water fluxes estimates

Ziel

In this proposal microwave scatterometry and radiometry methods for geophysical parameter retrievals are going to be developed for the purpose of air-sea fluxes estimates improvement. Sea Surface Wind Speed, Surface Wind Direction, Total Water Vapour Content of the atmosphere, Total Liquid Water of the clouds and Sea Surface Temperature are going to be retrieved. A combination of active and passive techniques is suggested for the retrieval accuracy improvement. Neural Networks approach is going to be used for the algorithms advancement.

Closed scheme of the numerical experiment for the real active and passive sensors is advanced. Simulation of the radiation transfer equation and backscattering will allow the computations of the brightness temperatures and normalized cross-sections at the frequencies of real active and passive sensors to be performed (forward problem). Numerical simulation of radiation transfer and backscattering inverse problem using developed algorithms, based on Neural Networks and some physical limitations, will allow to retrieve parameters from simulated brightness temperatures and normalized cross-sections calculated during forward problems solution. Comparison of the parameters known in advance (before forward problem solution) with estimates obtained after inverse problem solution will give us the values of errors for NNs-retrievals.

The development and validation of the algorithms is also supposed to be done through the following collocated in space and time real experimental data:
1. SSM/I - ERS-1,2 - ground-truth data
2. TMI ? ERS-2 - ground-truth data3. SSM/I - ADEOS-I NSCAT - ground-truth data
4. AMSR - Envisat SAR - ground-truth data.

The validation of the algorithms is also going to be done through the comprehensive analysis of SAR retrieved SSWS taking into numerical account the differences in the spatial resolution. Some of the case studies are going to be carried out for the demonstration of the effectiveness of the new synergistic approach.

The following major results are expected from the Project:
High quality theoretical database of ground truth experimental data and simulated satellite microwave passive and active measurements;
High quality experimental databases of collocated satellite microwave passive and active measurements and ground-truth data;
Computer program for calculating brightness temperatures recorded by current (SSM/I and TMI) and future (AMSR) microwave sensors;
Computer program for calculating normalized cross-section recorded by past (ERS-1), current (ERS-2, ADEOS-I NSCAT) and future (Envisat ASAR) scatterometers;
Neural Network algorithms for geophysical parameters retrieval (SSWS, SST, TWVC and TLWC - for TMI and AMSR; SSWS, TWVC and TLWC - for SSM/I), using satellite passive microwave measurements for different physical limitations;
Neural Networks algorithms for wind vector retrieval using satellite active microwave measurements;
Neural Networks algorithms for wind vector retrievals using combined active and passive microwave measurements.u

Aufforderung zur Vorschlagseinreichung

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Finanzierungsplan

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Koordinator

Nansen Environmental and Remote Sensing Center
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Edvard Griegsvei 3
5059 Bergen
Norwegen

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Beteiligte (3)