Signal Analysis Of Microwave Radiometric Emissions In Hurricanes: Part 1 - Ocean Wind Speed Dependence

Electrical engineering communications technologies contribute significantly to environmental remote sensing. In fact, microwave remote sensing is a primary tool for the measurement of critical environmental parameters, such as oceanic surface wind speed and rain rate, in hurricanes. Our understanding of hurricanes and, ultimately, the safety of people and property depend on our ability to monitor hurricanes as they develop and as they approach landfall. The Stepped Frequency Microwave Radiometer, SFMR, is a multi-frequency C-band remote sensing instrument that is routinely flown, on aircraft, into hurricanes by NOAA to measure surface wind speed and rain rate. This paper describes the development of a physics-based radiometric model to characterize surface wind speed dependent sea surface emissions. The model is validated against SFMR retrieval algorithms and measurements but, being physics-based, provides a broader, more general analysis capability, as will be described. © 2006 IEEE

An Improved C-Band Ocean Surface Emissivity Model At Hurricane-Force Wind Speeds Over A Wide Range Of Earth Incidence Angles

An improved microwave radiometric ocean surface emissivity model has been developed to support forward radiative transfer modeling of brightness temperature and geophysical retrieval algorithms for the next-generation airborne Hurricane Imaging Radiometer instrument. This physically based C-band emissivity model extends current model capabilities to hurricane-force wind speeds over a wide range of incidence angles. It was primarily developed using brightness temperature observations during hurricanes with coincident high-quality surface-truth wind speeds, which were obtained using the airborne Stepped-Frequency Microwave Radiometer. Also, other ocean emissivity models available through the published literature and the spaceborne WindSat radiometer measurements were used. © 2006 IEEE

A Roughness Correction For Aquarius Sea Surface Salinity Using The Conae Microwave Radiometer

Aquarius (AQ)/SAC-D is a joint National Aeronautics and Space Administration (NASA)/Comisión Nacional de Actividades Espaciales (CONAE; Argentine Space Agency) Earth Sciences satellite mission to measure global sea surface salinity (SSS), using a L-band radiometer/scatterometer that measures ocean brightness temperature (Tb) and radar backscatter (sigma-0). The application of L-band radiometry to retrieve SSS is a difficult task; therefore, precise Tb corrections are necessary to obtain accurate measurements. One of the major error sources is the effect of ocean roughness that \u27warms\u27 the ocean Tb. The baseline approach, to provide this ocean roughness correction, uses the AQ radar scatterometer measurement of ocean sigma-0 to infer the radiometric excess ocean emissivity. In contrast, this paper develops an alternate approach for the AQ ocean roughness correction using the MicroWave Radiometer (MWR) Tb measurements at Ka-band. The theoretical basis of this MWR ocean roughness correction algorithm is described, which translates these Ka-band measurements to L-band to remove the AQ Tb errors that are caused by ocean wind speed and direction. MWR ocean roughness correction results are compared with corresponding results from the AQ scatterometer method. Also, AQ SSS retrievals are presented using both sets of roughness corrections that demonstrate the relative effectiveness of the MWR and AQ scatterometer approaches

Hurricane Wind Speed Measurements In Rainy Conditions Using The Airborne Hurricane Imaging Radiometer (Hirad)

This paper describes a realistic computer simulation of airborne hurricane surveillance using the recently developed microwave remote sensor, the hurricane imaging radiometer (HIRAD). An end-to-end simulation is described of HIRAD wind speed and rain rate measurements during two hurricanes while flying on a high-altitude aircraft. This simulation addresses the particular challenge which is accurate hurricane wind speed measurements in the presence of intense rain rates. The objective of this research is to develop baseline retrieval algorithms and provide a wind speed measurement accuracy assessment for future hurricane flights including the NASA GRIP hurricane field program that was conducted in summer of 2010. Examples of retrieved hurricane wind speed and rain rate images are presented, and comparisons of the retrieved parameters with two different numerical hurricane models data are made. Special emphasis is provided on the wind speed measurement error, and statistical results are presented over a broad range of wind and rain conditions over the full measurement swath (earth incidence angle). © 2011 IEEE