3.2 Retrieving Hurricane Sustained Surface Winds Using the Cyclone Global Navigation Satellite System (CYGNSS) Mission’s Special Modes of Operation

Thursday, 16 January 2020: 1:45 PM
252B (Boston Convention and Exhibition Center)
Mohammad Al-Khaldi, The Ohio State Univ., Columbus, OH; and J. Johnson, S. J. Katzberg, Y. Kang, and E. Kubatko

Monitoring maximum wind speeds of tropical storms from space is of high interest due to the importance of this parameter in forecasting storm impact and evolution. While existing systems for remotely sensing ocean winds can provide some information on maximum winds, their performance may be limited by the impact of rain attenuation or by infrequent temporal sampling. The Cyclone Global Navigation Satellite System (CYGNSS) is well suited to address these challenges. CYGNSS’s constellation of eight satellites receives reflected signals from Earth’s surface produced by GPS satellite transmitters, thereby forming a bistatic radar geometry that can achieve wind speed estimation over ocean surfaces. The frequent revisits provided by the eight satellite constellation provides new opportunities for observing and forecasting storm properties

The primary scientific mission of CYGNSS is to measure incoherent scattering from the ocean's surface and to utilize these measurements for ocean wind speed retrieval. Wind speed retrievals are based on the relationship between ocean surface roughness (which impacts incoherent forward scatter) and ocean surface wind speed using empirically developed descriptions of this process. Several previous studies have illustrated the potential of using CYGNSS for the purposes of improving tropical cyclone feature characterization through analysis of retrieved wind speeds under CYGNSS's standard wind speed retrieval algorithms as a track of specular points traverses through a storm. The small surface area (limited delay extent) spanned by the standard Level-1 CYGNSS measurements, from which the standard wind retrievals are derived, together with the tendency of the received signal power to decrease monotonically at a slow rate with increasing surface wind speed have can impact the results obtained from this approach.

An alternative approach is adopted in this study, in which CYGNSS DDM returns over storms are forward modelled and compared against measurements with a focus on the maximum sustained surface wind (SSW) parameter. CYGNSS is capable of providing measurements in three modes: Standard DDM (SD), Full DDM (FD), and Raw Intermediate Frequency (I/F), with the latter two considered special acquisition modes that are not operated routinely. The SD product reports only 11 doppler (approximately 5.5 kHz at the CYGNSS 500 Hz Doppler sampling rate) × 17 delay (approximately 4.25 μsec at the CYGNSS ~0.25 μsec sampling rate) “pixels” per DDM. In contrast, the FD product reports 20 Doppler (approximately 10 kHz at the CYGNSS 500 Hz Doppler sampling rate) × 128 delay (approximately 32 μsec at the CYGNSS ~0.25 μsec sampling rate) pixels. Depending on incidence angle, the SD product spans a maximum radius of roughly 65 km from the specular point while the FD product can span contributions as far as 200 km from the specular point for incidence angles θi ≤ 60o. The Raw I/F mode records the CYGNSS intermediate frequency data stream before any correlation with the GNSS code or integration, and can span areas as large as 500 km. An FD or Raw I/F DDM therefore accounts for returns from a much larger surface area due to its larger delay extent. Due to the increased information this facilitates about the state of the surface, and therefore about the state of the storm, the results of this study place particular emphasis on performance comparisons of the retrieval algorithm using the CYGNSS FD and Raw I/F products.

CYGNSS returns are forward modelled across synthetic storm model(s) as the parameters of the storm are varied. The storm model is used to create a non-uniform wind field over which a forward model is applied to simulate DDMs for a selected CYGNSS track. An assessment of available storm models showed the Willoughby Model to be useful for this application. The Willoughby storm model is a function of a relatively small number of input parameters, namely the storm latitude and SSW. The model then describes an exponentially decaying wind speed function within the eye wall radius, a transition wind speed function between and the radial extent of the transition region, and a second exponentially decaying wind speed function beyond. Due to the importance of accurately representing a storm of interest, more complicated storm models like the Generalized Asymmetric Holland Model (GAHM) are also being incorporated as part of the retrieval procedure. GAHM is a quadrant specific generalization of the 1980 Holland model in which storm profiles are described by parametric relationships given by rectangular hyperbolas scaled by a shape parameter and location parameter. This allows for the introduction of true asymmetries within the storm profile, in contrast to the Willoughby model. This work will therefore also aim to assess the sensitivity of the retrieval approach to the employed storm model.

For every specular point a library of DDMs is created across different storm SSWs. The retrieval is then performed by identifying the library DDMs that best match observations over the track. More specifically the retrieval seeks to maximize the correlation between measured and simulated DDMs and minimizes root mean square error. Due to the fact that the retrieval approach focuses on the use of the DDM “shape” rather than “amplitude” in the matching process, uncertainties associated with CYGNSS absolute power calibration are bypassed. Studies of the performance of the method will be reported as well as initial use of the method with CYGNSS measurements.

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