Hurricane Wind Speed and Rain Rate Measurements

using the Airborne Hurricane Imaging Radiometer

(HIRAD)

Saleem Sahawneh*, Student Member, IEEE, Spencer Farrar, Student Member, IEEE. James Johnson, Senior

Member, IEEE, Linwood Jones, Life Fellow, IEEE

Central Florida Remote Sensing Lab

Department of EECS

University of Central Florida

Orlando, FL 32816-2362 *sahawneh@knights.ucf.edu

Abstract— Microwave remote sensing of surface wind speed

and rain rate in hurricanes is critical to predict their growth and

movement as they develop and make landfall. The Hurricane

Imaging Radiometer (HIRAD) is an experimental airborne

microwave radiometer developed by NASA Marshall Space

Flight Center (MSFC) to provide ocean surface wind speed and

rain rate measurements in hurricanes. It is intended to expand

the current NOAA and US Air Force hurricane surveillance

capability, particularly by extending the operational Stepped

Frequency Microwave Radiometer (SFMR) measurement to a

large swath. HIRAD also has potential for space applications.

This paper will describe the HIRAD instrument and its flight

history, to date, and present wind speed and rain rate retrievals

from observed brightness temperatures (Tb’s) in a flight over

Hurricane Earl in 2010 as part of NASA’s GRIP mission. A

comparison between HIRAD and SFMR retrievals will be shown.

Keywords—synthetic aperture imaging; microwave

radiometry; remote sensing; hurricane observation; SFMR

I. INTRODUCTION

The Hurricane Imaging Radiometer (HIRAD) is currently under development by NASA Marshall Space Flight Center, NOAA’s Hurricane Research Division, the University of Michigan and the University of Central Florida. For the past two decades, the airborne Stepped Frequency Microwave Radiometer (SFMR) has provided real-time measurements of surface wind speed (WS) and rain rates (RR) in hurricanes, and is currently operational on all surveillance aircrafts for Gulf of Mexico and Eastern Atlantic storms. The SFMR is nadir viewing and has a narrow measurement swath beneath the aircraft [ 1 ], while HIRAD has a wide swath (± 60° off nadir) that images the hurricane eye and eye-wall region in a single aircraft pass. From an altitude of 20 km, HIRAD will image approximately 60 km of the storm.

Microwave radiometers are used to measure wind speed at the ocean surface in the presence of heavy rain since the wind blowing over the ocean surface produces relatively high

emissivity foam and spray; thus, brightness temperature (Tb)

increases. This increase in Tb can be measured if rain attenuation is accounted for by using multiple frequencies.

The HIRAD concept includes the multi-frequency C-band capability of the SFMR and adds a form of electronic scanning that is relatively new to earth remote sensing [2]. HIRAD operates as an interferometer, sampling the spatial Fourier components of the cross-track brightness temperature scene. It does this using a large, stationary, multi-frequency microstrip array antenna to synthesize individual surface sampling beams across the swath. Image reconstruction techniques are then used to produce the continuous cross track Tb scene.

The HIRAD instrument was completed in 2010 and initially flew in Hurricane Earl off the east coast of Florida on September 1, 2010 as part of NASA’s GRIP (Genesis and Rapid Intensification Processes) mission, and in Hurricane Karl in the Gulf of Mexico on September 16, 2010. These flights were on the NASA WB-57 aircraft flying at approximately 18 km altitude. Currently HIRAD is installed on one of NASA’s Global Hawk pilot-less aircraft and flew in a Pacific storm on November 5-6, 2012. This paper emphasizes the performance of HIRAD in Hurricane Earl. Fig. 1 shows the location of HIRAD installed on the Global Hawk.

Fig. 1. HIRAD installation on the Global Hawk

The Central Florida Remote Sensing Lab (CFRSL) has developed empirical wind speed and rain rate geophysical retrieval algorithms using regression techniques on modeled Hurricane Frances data. These algorithms have been applied to

well calibrated Earl Tb data with good results when compared

to collocated SFMR measurements, and the results are presented in this paper.

978-1-4799-0053-4/13/$31.00 ©2013 IEEE

II. BRIGHTNESS TEMPERATURE

Remote measurements of wind speed over the ocean using

microwave radiometry is possible because of the relationship

between surface brightness temperature and wind speed.

Brightness Temperature (Tb) can be expressed as,

Tb = ε * Tphy, (1)

where ε is the surface emissivity of the media and Tphy is the

physical temperature of the media. The calculation of the

microwave emissions from the earth and atmosphere is

described by radiation transfer theory. This is illustrated in

Fig. 2.

Fig. 2. Brightness temperature signal as seen by an airborne radiometer.

The relationship between the total radiometric received

signal, Tapp and the individual contributors to the received

brightness temperature is defined in equation 2.

Tapp = Tup+ e−τ

(Tb + Trefl), (2)

where Tup is the upwelling component, Tb is the surface

emission [3], Trefl is the reflected down-welling atmospheric

component, and e−τ

is the atmospheric transmissivity. The exponent τ is the atmospheric absorption. The ability of a microwave radiometer to make observations of surface characteristics looking through the atmosphere depends on removal of atmospheric absorption which includes the effects of rain in the atmospheric column along the line of sight [4].

III. INSTRUMENT OVERVIEW

HIRAD uses a thinned planar microstrip array that operates

simultaneously at four frequencies over approximately an

octave bandwidth to perform a one dimensional cross-track

radiometric imaging of the ocean brightness scene . A stacked

patch array element has been designed to resonate at the

discrete frequencies of 4,5,6 and 6.6 GHz, with 37 × 16 of

these elements making up the entire array antenna [5]. The

array is “thinned” so that 10 linear arrays (1 × 16 each) are

cross-correlated, using 10 mutually coherent radiometers, to

synthesize an aperture 37 elements wide and horizontally

polarized [6]. The overall dimensions are .82m × .57m.

HIRAD’s instantaneous field of view (IFOV) is about 2 Km at

nadir and 5 Km at the end of swath. When HIRAD flew on the

Fig. 3. Typical HIRAD measurement swath and beam geometry.

the WB-57 at about 60,000 feet (~20Km), the measurement

swath of HIRAD was approximately 60 km (3 × Altitude) as

shown in Fig. 3.

IV. FLIGHTS PATTERNS

The 2010 flights in Earl and Karl were both at high altitude on the WB-57 where Earl was in the Atlantic and Karl was in the Gulf of Mexico but with different flight patterns. As shown in Fig. 4, a “box” pattern was flown in Earl where successive legs at 90 deg. angles form a box and in Karl a crisscrossing pattern was used to better capture the center of the storm. Fig. 4a is excess brightness temperature (Fresnel incidence angle dependence removed) (Earl) and total brightness temperature (Karl) over the HIRAD swath from the 5 GHz channel. Since the storm was moving during the time taken to complete a flight, all location data is registered to the storm center and plots are in storm centric coordinates. Eight legs were flown in Earl over 7 hours and 6 of these are shown in the figure. Observations were made over Hurricane Karl in 10 flight legs. Three of the flight legs passed over the hurricane eye and are shown overlayed in the Fig. 4b.

The SFMR was flown on the NOAA P-3 aircraft at approximately 10,000 ft. and provided simultaneous estimates

of Tb, WS, and RR to be used as calibration for the HIRAD

measurements. SFMR typically flies in a “Figure-4” pattern that is centered on the hurricane eye and includes two perpendicular legs that cross at the storm center. Two SFMR legs crossed perpendicular to HIRAD legs 1, 3, 4, and 6, in Earl and have been used for full swath comparisons of WS and RR retrievals.

V. HIRAD COMPARISON TO SFMR

Hurricane Earl data for Legs 1, 3, 4, and 6 were selected for detailed analyses and for comparison to SFMR WS and RR in order to judge the initial performance of HIRAD. These 4 were chosen for analysis because they captured the essential features of the storm. Since the SFMR flies in a Figure-4 pattern, it’s path completely traversed the HIRAD swath, perpendicular to the HIRAD tracks, and at the center of the storm on all 4 of these legs. Thus it was possible to identify storm centric HIRAD/SFMR collocations within approximately 30 minutes of each other on all 4 transects.

Fig. 4. (a) Hurricane Earl: HIRAD 5 GHz Excess Tb Images (± 65° swath)

in storm centric coordinates.

Fig. 4. (b) Hurricane Karl: HIRAD 5 GHz Tb Images (± 65° swath) in storm

centric coordinates.

Excess Tb (ExTb), plotted in Fig. 5, is generally used in analysis and retrievals due to the large effect of incidence angle over the swath on the dynamic range of Tb. Excess Tb is the measured total Tb minus the smooth surface Tb according to the Fresnel emissivity equation for H-pol. Excess Tb is primarily the brightness contribution due to WS and RR and maximizes the sensitivity to them. Excess Tb was found to perform better in empirical retrieval algorithms than total Tb.

Fig. 5. Excess Tb at 5 GHz for Earl Legs 1, 3, 4, and 6.

Both wind speed and rain rate retrieval algorithms were developed using modeled data for Hurricane Frances 2004 provided by NOAA. The geophysical parameters describing the storm were used in the CFRSL radiative transfer model to compute brightness temperatures at the HIRAD frequencies. These were used to determine, by regression, optimal

relationships between WS and RR and the Excess Tb’s and Tb

differences at the 4 frequencies. The best results, in terms of comparing well to SFMR retrievals, were obtained with HIRAD retrievals given by

WS = a1 + a2 × ExTb (3)

with ExTb at 5 GHz, and

RR = b1 + b2 × ExTb + b3 × (ExTb)2

(4)

with ExTb at 6.6 GHz. These relatively simple model functions

were used to retrieve wind speed and rain rate from the Earl measured brightness temperature data for the SFMR comparisons.

The NOAA P-3 aircraft, with SFMR, flew 3 legs to make a Figure-4 with the first leg going from east to west through the center of Earl, a diagonal leg to a point south of the eye, and another transect of the eye going from south to north. The SFMR produced brightness temperatures at 6 different C-Band frequencies at nadir, and so a time series of wind speed and rain rate over the flight path directly under the aircraft. These two time series are plotted in Fig. 6. The horizontal scale is unit-less, as plotted, but equates to approximately 124 minutes. The plot goes from left to right as the aircraft passes through the eye of Earl on the east/west and south/north legs, where WS drops to approximately zero bordered by peak winds and rain bands in the eye-wall regions. The two sudden drops in WS in between are when the aircraft turned going into and out of Leg 2. The maximum wind speed reached the 40 – 50 m/sec. range and the maximum rain intensity reached 30 – 40 mm/hr.

Fig. 6. WS and RR retrieval time series for the entire SFMR FIGURE-4.

The shaded areas in this figure represent the times when SFMR was crossing the HIRAD swath. Fig. 4. (a) can be used to associate the right and left hand edges of the HIRAD swath with these passes

1. WS Retrieval Results

Comparisons of retrievals were made for HIRAD Legs 1, 3, 4, and 6 with good WS results over the entire swath. On Legs 1 and 3, WS ranged from 25 – 50 m/sec. and agreement with SFMR was within approximately 5 m/sec. over the entire WS range and measurement swath, except in the eye where the HIRAD estimation was high due to rain absorption along the line of sight. The time difference between the SFMR pass and the collocated HIRAD pixels was approximately 12 sec. on the Leg 1 transect and 7 sec. on the Leg 3 transect.

The SFMR retrieved WS was greatest on the Leg 4 transect, reaching a peak of approximately 55 m/sec. in the north eye-wall, and the maximum RR retrieval of 40 mm/hr. was recorded in this region also. Fig. 7. shows the HIRAD WS comparison for Leg 4. Since the WB-57 was flying from west to east on this leg, the zero point in the time series corresponds to the right hand side of the HIRAD swath and the left hand side of the swath corresponds to the end of the time series.

Fig. 7. HIRAD WS retrieval on Leg 4 transect compared to storm centric,

collocated SFMR retrievals.

These results are good, given the simplicity of the retrieval algorithm in Eq. 3, except in the hurricane eye where HIRAD doesn’t respghond to the sudden drop in wind speed, and near the mid-point in the time series where the 10 m/sec. difference is relatively large. This is in the inner part of the swath where rain effects would be minimized, but the difference could still be due to one of the rain bands detected by the SFMR (Fig. 6).

The HIRAD Tb measurements provided here were not high

enough spatial resolution to map the peak wind indicated by the SFMR. Rain and fairly large incidence angle could be the

cause, or possibly smoothing done to remove Tb imaging

artifacts. The two data sets in this comparison were approximately 34 min. apart.

2. RR Retrieval Results

Comparison results for rain rate appeared to be, in general, not as good as for wind speed. Rain band detection by SFMR and HIRAD agreed about 50 % of the time over the 4 legs of comparisons. Also, HIRAD usually showed appreciable smoothing of features so that magnitudes lacked agreement. On Legs 1 and 3 the SFMR rain features were located in the HIRAD outer swath regions where the simplified algorithm in Eq. 4 might be less effective, and where the larger footprint and path length would tend to cause smoothing.

The SFMR retrieved RR was greatest on the Leg 4 transect with a 40 mm/hr. rain band in the northern eye-wall. Fig. 8. shows the HIRAD RR comparison for Leg 4. Again, the beginning of the plot is the right hand side of the HIRAD swath and the end corresponds to the left hand side of the swath.

HIRAD responded to the 40 mm/hr. rain in the eye wall to match SFMR, and showed good spatial resolution in the inner swath, but didn’t match SFMR with the rain cell on the left side of swath. This could easily be explained by the time difference between the two measurements and the relatively transient properties of rain band structure in hurricanes. Again, the RR algorithm did not respond well in the eye because of the intense rain in the eye-wall.

Fig. 8. HIRAD RR retrieval on Leg 4 transect compared to storm centric,

collocated SFMR retrievals.

VI. HIRAD WS AND RR IMAGES FOR HURRICANE

EARL

Figures 9 & 10 show HIRAD Wind Speed and Rain Rate images in storm centric coordinates for hurricane Earl. The major part of the storm was well covered with the 4 flight legs analyzed, and showed the greatest intensity in the north eye-wall region with 50 m/sec. winds and 40 mm/hr. rain. This data was good in showing the major structure of the storm as compared to the SFMR, the H-Wind analysis of NOAA/HRD, and the P-3 Fuselage Radar for imaging rain.

Fig. 9. HIRAD WS, in m/sec., using 5 GHz Algorithm for Hurricane Earl

Fig. 10. HIRAD RR, in mm/hr., using 6.6 GHz Algorithm for Hurricane Earl

VII. CONCLUSION

Two simple empirical WS and RR retrieval algorithms have

been used to make an initial evaluation of HIRAD on its first

science flight on September 1, 2010 in Hurricane Earl as part of

the NASA GRIP Mission. This evaluation relied primarily on

comparison of HIRAD retrievals to SFMR retrievals, but also

to other established sources defining the intensity and structure

of Earl. Comparisons to SFMR over the full HIRAD swath,

with WS and RR to 50 m/sec. and 40 mm/hr. showed good

results over the full swath. HIRAD did lack good response to

the rapid decrease in WS and RR in the eye, probably due to

the rain bands in the eye-wall. This was greatest on the swath

edges.

In the future we hope to improve HIRAD retrievals with

better calibrated Tb’s and use of radiative transfer theory for

retrievals. Data from Hurricane Karl and a recent Pacific storm

are available for further validation of the algorithms presented

in this paper, as well as continuing to improve retrieval

algorithms.

ACKNOWLEDGEMENTS

The authors wish to acknowledge the support of NOAA/AOML, Hurricane research Division with SFMR data, and the collaboration with colleagues at MSFC and the University of Michigan who provided the Tb data. This work was sponsored under a Grant with the Von Braun Center for Science and Innovation, Huntsville, AL.

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