Development Of An Improved Microwave Ocean Surface Emissivity Radiative Transfer Model

An electromagnetic model is developed for predicting the microwave blackbody emission from the ocean surface over a wide range of frequencies, incidence angles, and wind vector (speed and direction) for both horizontal and vertical polarizations. This ocean surface emissivity model is intended to be incorporated into an oceanic radiative transfer model to be used for microwave radiometric applications including geophysical retrievals over oceans. The model development is based on a collection of published ocean emissivity measurements obtained from satellites, aircraft, field experiments, and laboratory measurements. This dissertation presents the details of methods used in the ocean surface emissivity model development and comparisons with current emissivity models and aircraft radiometric measurements in hurricanes. Especially, this empirically derived ocean emissivity model relates changes in vertical and horizontal polarized ocean microwave brightness temperature measurements over a wide range of observation frequencies and incidence angles to physical roughness changes in the ocean surface, which are the result of the air/sea interaction with surface winds. Of primary importance are the Stepped Frequency Microwave Radiometer (SFMR) brightness temperature measurements from hurricane flights and independent measurements of surface wind speed that are used to define empirical relationships between C-band (4 - 7 GHz) microwave brightness temperature and surface wind speed. By employing statistical regression techniques, we develop a physical-based ocean emissivity model with empirical coefficients that depends on geophysical parameters, such as wind speed, wind direction, sea surface temperature, and observational parameters, such as electromagnetic frequency, electromagnetic polarization, and incidence angle

Hurricane Imaging Radiometer (HIRAD) Wind Speed Retrievals and Validation Using Dropsondes

Surface wind speed retrievals have been generated and evaluated using Hurricane Imaging Radiometer (HIRAD) measurements from flights over Hurricane Joaquin, Hurricane Patricia, Hurricane Marty, and the remnants of Tropical Storm Erika, all in 2015. Procedures are described here for producing maps of brightness temperature, which are subsequently used for retrievals of surface wind speed and rain rate across a approx.50 km wide swath for each flight leg. An iterative retrieval approach has been developed to take advantage of HIRAD's measurement characteristics. Validation of the wind speed retrievals has been conducted, using 636 dropsondes released from the same WB-57 high altitude aircraft carrying HIRAD during the Tropical Cyclone Intensity (TCI) experiment. The HIRAD wind speed retrievals exhibit very small bias relative to the dropsondes, for winds tropical storm strength (17.5 m/s) or greater. HIRAD has reduced sensitivity to winds weaker than tropical storm strength, and a small positive bias (approx.2 m/s) there. Two flights with predominantly weak winds according to the dropsondes have abnormally large errors from HIRAD, and large positive biases. From the other flights, root mean square errors are 4.1 m/s (33%) for winds below tropical storm strength, 5.6 m/s (25%) for tropical storm strength winds, and 6.3 m/s (16%) for hurricane strength winds. Mean absolute errors for those categories are 3.2 m/s (25%), 4.3 m/s (19%), and 4.8 m/s (12%), with bias near zero for tropical storm and hurricane strength winds

A Roughness Correction for Aquarius Ocean Brightness Temperature Using the CONAE MicroWave Radiometer

Aquarius/SAC-D is a joint NASA/CONAE (Argentine Space Agency) Earth Sciences satellite mission to measure global sea surface salinity (SSS), using an L-band radiometer that measures ocean brightness temperature (Tb). The application of L-band radiometry to retrieve SSS is a difficult task, and therefore, precise Tb corrections are necessary to obtain accurate measurements. One of the major error sources is the effect of ocean roughness that warms the ocean Tb. The Aquarius (AQ) instrument (L-band radiometer/scatterometer) baseline approach uses the radar scatterometer to provide this ocean roughness correction, through the correlation of radar backscatter with the excess ocean emissivity. In contrast, this dissertation develops an ocean roughness correction for AQ measurements using the MicroWave Radiometer (MWR) instrument Tb measurements at Ka-band to remove the errors that are caused by ocean wind speed and direction. The new ocean emissivity radiative transfer model was tuned using one year (2012) of on-orbit combined data from the MWR and the AQ instruments that are collocated in space and time. The roughness correction in this paper is a theoretical Radiative Transfer Model (RTM) driven by numerical weather forecast model surface winds, combined with ancillary satellite data from WindSat and SSMIS, and environmental parameters from NCEP. This RTM provides an alternative approach for estimating the scatterometer-derived roughness correction, which is independent. The theoretical basis of the algorithm is described and results are compared with the AQ baseline scatterometer method. Also results are presented for a comparison of AQ SSS retrievals using both roughness corrections

Improving Sea-Surface Remote Sensing of Ocean Wind Vectors by Scatterometers

Though scatterometers have been used to sense global ocean surface wind vectors for over 40 years, there remain some significant shortcomings. The largest problems appear in retrieving the wind vector when the ocean is being driven by high wind speeds or when rain is present in the beam-illuminated volume. Geophysical model functions (GMFs) developed using data from high-wind events can improve retrievals at high wind speeds, but only if sufficient ground truth measurements exist in the scatterometer swath. Airborne scatterometers, such as the Imaging Wind and Rain Airborne Profiler (IWRAP) developed by the Microwave Remote Sensing Laboratory (MIRSL) at the University of Massachusetts Amherst (UMass), are well-suited for collecting such high-wind data, largely due to their abilities to reposition to areas of interest, sample the ocean surface on a small scale, and use complementary in-situ sensors. The IWRAP system is also able to investigate the effect of precipitation impact (the “splash effect”) on the sea surface normalized radar cross-section (NRCS), since it can discriminate between volume and surface effects of precipitation. This dissertation will improve upon the existing IWRAP GMF and quantify the effect of precipitation on wind vector retrievals. Additionally, IWRAP is used to observe the effects of Earth-incidence angle and polarization on the sea-surface radar backscatter, helping scatterometer GMFs to be applicable to other satellite sensors. IWRAP and collocated Stepped Frequency Microwave Radiometer (SFMR) data were gathered from 4 years of flight experiments. Using this data, the high-wind IWRAP GMF is extended to incidence angles near 22° at C- and Ku-band VV- and HH-polarization from 15 m s−1 to 45 m s−1. There is also a revision made to the higher harmonics of the GMF near 50° incidence, but the mean NRCS appears to be modeled appropriately. There is no splash effect observed in the mean NRCS or first harmonic at wind speeds from 15 m s−1 to 45 m s−1. The second harmonic shows some muted behavior in precipitation. Lastly, a wind speed dependence is observed in the VV/HH NRCS polarization ratio in both incidence angle and azimuth

A comparison of synoptic and Skylab S193/194 determinations of ocean surface windspeeds

There are no author-identified significant results in this report

J Atmos Ocean Technol

Surface wind speed retrievals have been generated and evaluated using Hurricane Imaging Radiometer (HIRAD) measurements from flights over Hurricane Joaquin, Hurricane Patricia, Hurricane Marty, and the remnants of Tropical Storm Erika, all in 2015. Procedures are described here for producing maps of brightness temperature, which are subsequently used for retrievals of surface wind speed and rain rate across a ~50 km wide swath for each flight leg. An iterative retrieval approach has been developed to take advantage of HIRAD's measurement characteristics. Validation of the wind speed retrievals has been conducted, using 636 dropsondes released from the same WB-57 high altitude aircraft carrying HIRAD during the Tropical Cyclone Intensity (TCI) experiment. The HIRAD wind speed retrievals exhibit very small bias relative to the dropsondes, for winds tropical storm strength (17.5 m s|) or greater. HIRAD has reduced sensitivity to winds weaker than tropical storm strength, and a small positive bias (~2 m s|) there. Two flights with predominantly weak winds according to the dropsondes have abnormally large errors from HIRAD, and large positive biases. From the other flights, root mean square differences between HIRAD and the dropsonde winds are 4.1 m s| (33%) for winds below tropical storm strength, 5.6 m s| (25%) for tropical storm strength winds, and 6.3 m s| (16%) for hurricane strength winds. Mean absolute differences for those categories are 3.2 m s| (25%), 4.3 m s| (19%), and 4.8 m s| (12%), with bias near zero for tropical storm and hurricane strength winds.20172018-08-01T00:00:00ZU01 IP000056/IP/NCIRD CDC HHS/United States28919665PMC5597242663

The Proof of Concept of The Hurricane Imaging Radiometer: Hurricane Wind Speed and Rain Rate Retrievals

This dissertation presents the proof of concept for the Hurricane Imaging Radiometer (HIRAD), where remote sensing retrievals of the 2-dimensional wind and rain fields for several hurricanes are validated with independent measurements. A significant contribution of this dissertation is the development of a novel statistical calibration technique, whereby the HIRAD instrument is radiometrically calibrated, using modeled brightness temperatures (Tb) generated using a priori hurricane wind and rain fields that are statistically representative of the actual hurricane conditions at the time of the HIRAD brightness temperature measurements. For this calibration technique, the probability distribution function of the measured HIRAD Tb\u27s is matched to the modeled Tb distribution. After applying this Tb calibration, hurricane wind speeds and rain rates are retrieved for six hurricane surveillance flights between 2013-2015. These HIRAD results are compared with available, statistically independent, surface measurements from in-situ GPS dropwindsondes and remote sensing: Stepped Frequency Microwave Radiometer (SFMR), and the High-Altitude Imaging Wind and Rain Aerial Profiler (HIWRAP). Since there is good agreement in the intercomparisons, it is concluded that the HIRAD hurricane measurement technique performs as intended, after the corresponding Tb images are properly calibrated. Furthermore, based upon the above comparisons, it is concluded that the retrieved HIRAD 2-dimensional wind field improves upon the a priori calibration source, regardless of quality of this model used in the calibration. This shows that HIRAD is not simply replicating results of the calibration source, but rather, it adds useful information

Hurricane Imaging Radiometer Wind Speed and Rain Rate Retrievals during the 2010 GRIP Flight Experiment

Microwave remote sensing observations of hurricanes, from NOAA and USAF hurricane surveillance aircraft, provide vital data for hurricane research and operations, for forecasting the intensity and track of tropical storms. The current operational standard for hurricane wind speed and rain rate measurements is the Stepped Frequency Microwave Radiometer (SFMR), which is a nadir viewing passive microwave airborne remote sensor. The Hurricane Imaging Radiometer, HIRAD, will extend the nadir viewing SFMR capability to provide wide swath images of wind speed and rain rate, while flying on a high altitude aircraft. HIRAD was first flown in the Genesis and Rapid Intensification Processes, GRIP, NASA hurricane field experiment in 2010. This paper reports on geophysical retrieval results and provides hurricane images from GRIP flights. An overview of the HIRAD instrument and the radiative transfer theory based, wind speed/rain rate retrieval algorithm is included. Results are presented for hurricane wind speed and rain rate for Earl and Karl, with comparison to collocated SFMR retrievals and WP3D Fuselage Radar images for validation purposes