A GNSS-R forward model for delay-Doppler map assimilation

Huang, Feixiong; Garrison, James L.; Leidner, Mark; Annane, Bachir; Hoffman, Ross

doi:10.1109/igarss.2018.8518987

i

A GNSS-R forward model for delay-Doppler map assimilation

2018
By Huang, Feixiong ; Garrison, James L. ; Leidner, Mark ; ...

Details

Journal Title:

International Geoscience and Remote Sensing Symposium
Personal Author:

Huang, Feixiong ; Garrison, James L. ; Leidner, Mark ; Annane, Bachir ; Hoffman, Ross
Corporate Authors:

Purdue University System ; Atmospheric and Environmental Research ; Cooperative Institute for Marine and Atmospheric Studies
Conference Authors:

IGARSS 2018 - 2018
NOAA Program & Office:

CIMAS (Cooperative Institute for Marine and Atmospheric Studies)
Description:

The Cyclone Global Navigation Satellite System (CYGNSS) constellation was launched for the purpose of improving tropical cyclone forecasts using GNSS Refiectometry (GNSS-R). CYGNSS wind speed estimates have been based on only a small window of the Delay-Doppler Maps (DDM) due to the resolution requirement. Direct assimilation of DDM data into a forecast model is an alternative approach, that could take advantage of contribution to the DDM from regions on the ocean away from the specular point. This paper will present a generalized forward model for assimilation of DDMs into a weather model. The forward operator and Jacobian matrix are derived and structured for use in data assimilation systems. The model has also been assessed using CYGNSS Level 1 data from the 2017 Hurricane season.
Keywords:

Analytical Form Computational Modeling Cyclone Data Assimilation Data Assimilation System Data Models DDM Delay-Doppler Map Empirical Model Finite Difference Forecasting Model Forward Model Global Navigation Satellite System GNSS-R GPS Hurricanes Input Structure Jacobian Matrices Jacobian Matrix Numerical Weather Prediction Ocean Wind Output Structure Partial Differential Power Parameter VAM Wind Field Wind Forecasting Wind Speed
Source:

International Geoscience and Remote Sensing Symposium
DOI:

https://doi.org/10.1109/igarss.2018.8518987
ISBN:

978-1-5386-7150-4 ; 978-1-5386-7149-8 ; 978-1-5386-7151-1
ISSN:

2153-7003 ; 2153-6996
Format:

PDF
Publisher:

Institute of Electrical and Electronics Engineers (IEEE)
Document Type:

Journal Article
Rights Information:

Accepted Manuscript
Compliance:

Submitted
Main Document Checksum:

urn:sha-512:6f223a009f51b0971990516c7b9dfa7ac93974131bb658c7152bb4e131afcfd7d2d8e558b837a05619118736389bab3f65970eca7cfb0d4aa8672bcc607d88a5
Download URL:

https://repository.library.noaa.gov/view/noaa/65876/noaa_65876_DS1.pdf
File Type:

[PDF - 480.23 KB ]

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