88th Annual Meeting (20-24 January 2008)

Tuesday, 22 January 2008
Oxygen band radar for sea surface air pressure measurements: Applications for tropical storm forecasts
Exhibit Hall B (Ernest N. Morial Convention Center)
Bing Lin, NASA/LaRC, Hampton, VA; and Y. Hu, S. Harrah, D. Fralick, and R. Lawrence
Currently, sea surface air pressure measurements can only be obtained from in situ observations including buoy, ship and dropsonde measurements, which are sparse in spatial coverage and expensive to implement. There are no pressure remote sensing methods available even in experimental stages. This study considers use active microwave systems to obtain the differential O2 absorption at 50-56 GHz bands to fill the observational gap. The numerical simulation results for homogeneous sea surface backgrounds show that the rms errors of the instantaneous surface pressure estimates can be as low as 4 mb. With multiple radar measurements the uncertainty in radar sea surface pressure estimates would drop to about 1 mb which is similar to conventional in situ buoy measurements. This considered active system will have great potential for weather observations and other meteorological applications, especially for forecasts of hurricanes. Case studies show that with remotely sensed sea surface barometric pressure data, the errors of hurricane center sea level pressures, the most important indicator of hurricane intensity, in weather prediction models would reduce from about 48 mb to about 1.5 mb. The increased accuracy is about 1/3 of the whole range of possible variations of hurricane center pressure. The uncertainties in predicted landfall positions or hurricane tracks would also shrink greatly from ~350 km to within 100 km.

Currently, we have developed the prototype O2-band radar system and integrated it into an aircraft for the test to prove the concept of the differential O2 absorption for the pressure remote sensing measurements. Our first field campaign results of pressure measurements and the simulation of the pressure remote sensing for weather forecasts will be presented.

Supplementary URL: