1 / 13

GPS-Based Tropical Storm Sensing

GPS-Based Tropical Storm Sensing. Results from 2003-2007 Storm Seasons. Stephen J. Katzberg (Distinguished Research Associate) And Bing Lin NASA-Langley Research Center.

achenbach
Download Presentation

GPS-Based Tropical Storm Sensing

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. GPS-Based Tropical Storm Sensing Results from 2003-2007 Storm Seasons Stephen J. Katzberg (Distinguished Research Associate) And Bing Lin NASA-Langley Research Center

  2. Background on the GPS techniqueThe GPS technique is a bi-static, quasi specular configuration that operates on a principle different from microwave radiometers and scatterometers • GPS is L-Band 1.575 GHz and water reflectivity is 63% • Under calm conditions signal appear to arise from couple Fresnel zones near the “specular” point • Outside the specular point ellipses of constant delay form annuli, or range bins. • As the surface becomes rougher, surface slopes begin to “fill” the range bins.

  3. Increasing roughness Effect of increasing surface roughness on GPS receiver correlation function Background • Wind speed retrieval is based upon knowledge of the surface slope probability density and its convolution with the internal receiver correlation function. • Using model waveforms, a matched filter is implemented to determine the correct wind speed.

  4. Calibration in High Wind Regimes • Early results from wind • Speed retrievals indicated that the mss dependence with wind speed might saturate or show nonlinearities. • A study was done to compare retrieved wind speeds with COAMPS model results. • The results were reported in GRL September 2006 This is the only calibration required to use the GPS hardware

  5. Hurricane Dennis with DropsondesFirst Use of COAMPS Calibration Wind speed > 57 m/s

  6. Dropping in on Dennis July 8, 2005

  7. Dennis July 8, 2005 Near Land and Islands

  8. Hurricane Ophelia September 2005

  9. Hurricane Isabel September 16, 2003

  10. Hurricane Felix September 2, 2007Abnormally Low signal to noise

  11. Wind Direction • There is an upwind-downwind vs. crosswind anisotropy in the slope probability density. • One manifestation is an apparent change in retrieved wind speed with satellite to wind direction angle, although the change is not large (~10 percent.) • Current SNR for receiver is marginal. • Demonstrating wind direction will yield the ocean surfacewind field

  12. September 13, 2005 September 16, 2005 Current Research: Wind Direction Hurricane Ophelia September 2005

  13. Conclusions • The GPS technique has been shown to provide an alternate method to infer high wind speeds. • The GPS technique shows promise to provide wind direction for wind fields. • The GPS technique is low-impact, UAV compatible, and cheap.

More Related