Potential improvements of tropical storm forecasts with remote sensing of ocean surface air pressure

Currently, sea surface air pressure measurements can only be obtained from in situ observations including buoy and dropsonde measurements, which are sparse in spatial coverage and expensive to implement. There are no operational remote sensing methods available even in experimental stages. The study considers uses of absorption features of microwave radiative transfer, especially the differential O2 absorption for active microwave systems working at 50-56 GHz bands, to fill the observational gap. Numerical analysis for homogeneous sea surface backgrounds shows that rms errors of instantaneous surface pressure estimates can be as low as 4 mb. Based on this theoretical analysis, a prototype system of the DIfferential O2 Absorption Radar for Barometry (DIAR-BAR) has been developed and integrated it into an aircraft. Flight test results show the instrument performance meets or exceeds the all system requirements indicting the concept of the differential O2 absorption for remote sensing of sea surface air pressure could be realized with existing radar technologies. With the progress in the barometry of sea surface air pressure, a series of observational system simulation has been conducted. With remotely sensed sea surface barometric pressure data, the errors of hurricane center pressure, the most important indicator of hurricane intensity, in weather prediction models could be reduced significantly. The uncertainties in the weather model predicted landfall positions or tracks of hurricanes could also shrink greatly from ~350 km to within 100 km. The investigation of the case of hurricane Katrina further demonstrates the importance of using surface pressure fields in three dimensional variational data assimilation system for WRF. Hurricane Katrina crossed Florida peninsula on August 26, 2005, which provides us surface pressure data with good spatial distribution that is rarely available for other hurricanes in their developing stage over the ocean. Various patterns of surface pressure distribution are assimilated, and the bias in landfall position for 84-hour forecasting decreases from 360 km in the control run to 38 km in assimilation runs. These results exhibit the DIAR-BAR system will have great potential for weather observations and other meteorological applications, especially for forecasts of hurricanes.