Synthetic aperture radar (SAR) imagery is routinely acquired at HH-polarization in high-latitude areas for measuring surface wind over the ocean. However, in the contrary of VV-polarization, there is no HH-polarization geophysical model function (GMF) exists to directly retrieve wind speed from SAR images. In general, HH-polarized normalized radar cross section (NRCS) is thus converted into VV-polarization and then conventional CMOD functions are used with auxiliary wind direction information for wind speed retrieval. In this letter, we propose a new GMF for SAR ocean surface wind speed retrieval, called CMODH, which relates the C-band NRCS acquired at HH-polarization over the ocean, to the 10-m height wind speed, incident angle, and relative wind direction. We first use more than 220 000 ENVISAT ASAR radar backscatter measurements collocated with ASCAT winds to derive the CMODH coefficients. Subsequently, 1459 RADARSAT-2 (RS-2) and 428 Sentinel-1A/B (Sl-1A/B) HH-polarized SAR acquisitions under different wind speeds are matched to in situ buoy observations to validate CMODH. The statistical comparisons between SAR-observed and simulated NRCS show a bias of -0.07 dB and a root-mean-square error of 1.62 dB for RS-2, and -0.01 dB and 2.48 dB for S1-1A/B. These results suggest that the proposed CMODH has the potential to directly retrieve ocean surface wind speeds using C-band SAR images acquired at HH-polarization, with no need for NRCS transformation by using various empirical and theoretical polarization ratio models.

Hurricane tangential wind profiles are routinely observed by aircraft reconnaissance in order to estimate the surface winds. However, these wind profile estimates are occasionally biased because along-track aircraft observations might not determine the nonaxisymmetric hurricane structure characteristics. In this paper, we resolve this problem by calculating the mean wind speed in all radial directions using cross-polarization SAR wide-swath images. Moreover, we propose a one-half modified Rankine vortex (OHMRV) model to describe the hurricane wind profile, particularly for those wind profiles with a wind speed maximum and an inflection point possibly associated with the degeneration of the inner wind maximum in the hurricane reintensification phase. OHMRV characterizes the hurricane wind profile and represents a model that complements the previously established single-modified Rankine vortex model and the double-modified Rankine vortex model. Moreover, the OHMRV-derived wind profiles are used to estimate hurricane intensity and structure parameters, such as the maximum wind speed and the radius of maximum wind. For validation of the method, the estimated ISPs are compared with measurements by the stepped-frequency microwave radiometer on board the National Oceanic and Atmospheric Administration aircraft. These parameters contribute to a description of hurricane inner-core intensity and structure associated with eyewall replacement cycles.

This work discusses the accuracy of C-2PO (C-band cross-polarized ocean backscatter) and CMOD4 (C-band model) geophysical model functions (GMF) for sea surface wind speed retrieval from satellite-born Synthetic Aperture Radar (SAR) images over in the Northwest Pacific off the coast of China. In situ observations are used for comparison of the retrieved wind speed using two established wind retrieval models: C-2PO model and CMOD4 GMF. Using 439 samples from 92 RADARSAT-2 fine quad-polarization SAR images and corresponding reference winds, we created two subset wind speed databases: the training and testing subsets. From the training data subset, we retrieve ocean surface wind speeds (OSWSs) from different models at each polarization and compare with reference wind speeds. The RMSEs of SAR-retrieved wind speeds are: 2.5 m/s: 2.11 m/s (VH-polarized), 2.13 m/s (HV-polarized), 1.86 m/s (VV-polarized) and 2.26 m/s (HH-polarized) and the correlation coefficients are 0.86 (VH-polarized), 0.85(HV-polarized), 0.87(VV-polarized) and 0.83 (HH-polarized), which are statistically significant at the 99.9% significance level. Moreover, we found that OSWSs retrieved using C-2PO model at VH-polarized are most suitable for moderate-to-high winds while CMOD4 GMF at VV-polarized tend to be best for low-to-moderate winds. A hybrid wind retrieval model is put forward composed of the two models, C-2PO and CMOD4 and sets of SAR test data are used in order to establish an appropriate wind speed threshold, to differentiate the wind speed range appropriate for one model from that of the other. The results show that the OSWSs retrieved using our hybrid method has RMSE of 1.66 m/s and the correlation coefficient are 0.9, thereby significantly outperforming both the C-2PO and CMOD4 models.

We propose a methodology to estimate the tropical cyclone (TC) center location associated with the additional TC parameters of the radius of maximum wind (RMW) and intensity, purely from ocean winds observed by the Soil Moisture Active Passive (SMAP) radiometer. This method assumes a symmetric vortex. To demonstrate the method, we analyze 28 SMAP wind fields collected during 11 TCs. Verification of the estimated hurricane centers and wind distributions along the radius is compared with measurements provided by the airborne stepped-frequency microwave radiometer (SFMR) collected during its flying through hurricane cores and to sea surface wind fields derived from spaceborne synthetic aperture radar data. The significance of this simple method is that TC centers, intensities, and RMW can be estimated purely from SMAP wind products, despite SMAP’s low spatial resolution. Comparing these 28 model results to the aircraft measurement (f-deck) and the best track (BT) data, we show that, for the latitudes and longitudes of the TC centers, the standard deviations are 0.28° and 0.29°, respectively, both with a correlation of 1.00. For the detected intensity, the standard deviation is 8.11 m/s, and the correlation is 0.84. We note that the TC intensity detected by this method can be even stronger than the maximum winds observed by the relatively low-resolution SMAP observations.