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

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 (HIRAD) Tropical Rainfall Retrievals

The Hurricane Imaging Radiometer (HIRAD) is an airborne passive microwave remote sensor, developed to measure wind speed and rain rate in hurricanes. This dissertation concerns the development of a signal processing algorithm to infer tropical rainfall from HIRAD radiance (brightness temperature, Tb) measurements. The basis of the rain rate retrieval algorithm is an improved forward microwave radiative transfer model (RTM) that incorporates the HIRAD multi-antenna-beam geometry, and uses semi-empirical coefficients derived from an airborne experiment that occurred in the Gulf of Mexico off Tampa Bay in 2013. During this flight, HIRAD observed a squall line of thunderstorms simultaneously with an airborne meteorological radar (High Altitude Wind and Rain Profiler, HIWRAP), located on the same airplane. Also, ground based NEXRAD radars from the National Weather Service (located at Tampa and Tallahassee) provided high resolution simultaneous rain rate measurements. Using NEXRAD rainfall as the surface truth input to the HIRAD RTM, empirical rain microwave absorption coefficients were tuned to match the measured brightness temperatures. Also, the collocated HIWRAP radar reflectivity (dBZ) measurements were cross correlated with NEXRAD to derive the empirical HIWRAP radar reflectivity to rain rate relationship. Finally, the HIRAD measured Tbs were input to the HIRAD rain retrieval algorithm to derive estimates of rain rate, which were validated using the independent HIWRAP measurements of rain rate

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

Validation of Rain Rate Retrievals for the Airborne Hurricane Imaging Radiometer (HIRAD)

The NASA Hurricane and Severe Storm Sentinel (HS3) mission is an aircraft field measurements program using NASA's unmanned Global Hawk aircraft system for remote sensing and in situ observations of Atlantic and Caribbean Sea hurricanes. One of the principal microwave instruments is the Hurricane Imaging Radiometer (HIRAD), which measures surface wind speeds and rain rates. For validation of the HIRAD wind speed measurement in hurricanes, there exists a comprehensive set of comparisons with the Stepped Frequency Microwave Radiometer (SFMR) with in situ GPS dropwindsondes [1]. However, for rain rate measurements, there are only indirect correlations with rain imagery from other HS3 remote sensors (e.g., the dual-frequency Ka- & Ku-band doppler radar, HIWRAP), which is only qualitative in nature. However, this paper presents results from an unplanned rain rate measurement validation opportunity that occurred in 2013, when HIRAD flew over an intense tropical squall line that was simultaneously observed by the Tampa NEXRAD meteorological radar (Fig. 1). During this experiment, Global Hawk flying at an altitude of 18 km made 3 passes over the rapidly propagating thunderstorm, while the TAMPA NEXRAD perform volume scans on a 5-minute interval. Using the well-documented NEXRAD Z-R relationship, 2D images of rain rate (mm/hr) were obtained at two altitudes (3 km & 6 km), which serve as surface truth for the HIRAD rain rate retrievals. A preliminary comparison of HIRAD rain rate retrievals (image) for the first pass and the corresponding closest NEXRAD rain image is presented in Fig. 2 & 3. This paper describes the HIRAD instrument, which 1D synthetic-aperture thinned array radiometer (STAR) developed by NASA Marshall Space Flight Center [2]. The rain rate retrieval algorithm, developed by Amarin et al. [3], is based on the maximum likelihood estimation (MLE) technique, which compares the observed Tb's at the HIRAD operating frequencies of 4, 5, 6 and 6.6 GHz with corresponding theoretical Tb values from a forward radiative transfer model (RTM). The optimum solution is the integrated rain rate that minimizes the difference between RTM and observed values. Because the excess Tb from rain comes from the direct upwelling and the indirect reflected downwelling paths through the atmosphere, there are several assumptions made for the 2D rain distribution in the antenna incident plane (crosstrack to flight direction). The opportunity to knowing 2D rain surface truth from NEXRAD at two different altitudes will enable a comprehensive evaluation to be preformed and reported in this paper

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

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

Remote Sensing of Tropical Cyclones: Applications from Microwave Radiometry and Global Navigation Satellite System Reflectometry

Tropical cyclones (TCs) are important to observe, especially over the course of their lifetimes, most of which is spent over the ocean. Very few in situ observations are available. Remote sensing has afforded researchers and forecasters the ability to observe and understand TCs better. Every remote sensing platform used to observe TCs has benefits and disadvantages. Some remote sensing instruments are more sensitive to clouds, precipitation, and other atmospheric constituents. Some remote sensing instruments are insensitive to the atmosphere, which allows for unobstructed observations of the ocean surface. Observations of the ocean surface, either of surface roughness or emission can be used to estimate ocean surface wind speed. Estimates of surface wind speed can help determine the intensity, structure, and destructive potential of TCs. While there are many methods by which TCs are observed, this thesis focuses on two main types of remote sensing techniques: passive microwave radiometry and Global Navigation Satellite System reflectometry (GNSS-R). First, we develop and apply a rain rate and ocean surface wind speed retrieval algorithm for the Hurricane Imaging Radiometer (HIRAD). HIRAD, an airborne passive microwave radiometer, operates at C-band frequencies, and is sensitive to rain absorption and emission, as well as ocean surface emission. Motivated by the unique observing geometry and high gradient rain scenes that HIRAD typically observes, a more robust rain rate and wind speed retrieval algorithm is developed. HIRAD’s observing geometry must be accounted for in the forward model and retrieval algorithm, if high rain gradients are to be estimated from HIRAD’s observations, with the ultimate goal of improving surface wind speed estimation. Lastly, TC science data products are developed for the Cyclone Global Navigation Satellite System (CYGNSS). The CYGNSS constellation employs GNSS-R techniques to estimate ocean surface wind speed in all precipitating conditions. From inputs of CYGNSS level-2 wind speed observations and the storm center location, a variety of products are created: integrated kinetic energy, wind radii, radius of maximum wind speed, and maximum wind speed. These products provide wind structure and intensity information—valuable for situational awareness and science applications.PHDAtmospheric, Oceanic & Space ScienceUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/137109/1/marygm_1.pd