Title

Improved Hurricane Active/Passive Simulated Wind Vector Retrievals

Keywords

AMSR; Artificial neural network; DFS; Ocean vector wind; Tropical cyclone

Abstract

Microwave scatterometers are the standard for satellite ocean vector winds (OVW) measurements, and they provide the major source of global ocean surface winds observations for scientific and operational applications. A major challenge for Ku-band scatterometry missions is to provide reliable retrievals in the presence of precipitation, particularly in extreme ocean wind events that are usually associated with intense rain. This paper explores the advantages of combining dual frequency (C- and Ku-band) scatterometer measurements and passive microwave observations to improve high wind speed retrievals. For this study, a conceptual design proposed by the Jet Propulsion Laboratory for a Dual Frequency Scatterometer (DFS) to fly onboard the future Japan Aerospace Exploration Agency (JAXA) GCOM-W2 mission with the Advanced Microwave Scanning Radiometer (AMSR) was adopted. A computer simulation that combines the DFS and AMSR measurements was used to develop an artificial neural network OVW retrieval algorithm. The Weather Research and Forecasting (WRF) numerical weather model of Hurricane Katrina (2005) was used as the nature run (surface truth), and simulated OVW retrievals demonstrate that this new technique offers a robust option to extend the useful wind speed measurements range beyond the current operating scatterometers for future satellite missions. © 2010 IEEE.

Publication Date

1-1-2010

Publication Title

International Geoscience and Remote Sensing Symposium (IGARSS)

Number of Pages

2535-2538

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1109/IGARSS.2010.5652385

Socpus ID

78650853209 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/78650853209

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