Hurricane Observations Research Articles

Wind field reconstruction based on dual-polarized synthetic aperture radar during a tropical cyclone

ABSTRACT A wind field reconstruction method for dual-polarized (vertical-vertical [VV] and vertical-horizontal [VH]) Sentinel-1 (S-1) synthetic aperture radar (SAR) images collected during tropical cyclones (TCs) that does not require external information is proposed. Forty S-1 images acquired in interferometric-wide (IW) and extra-wide (EW) modes during the Satellite Hurricane Observation Campaign in 2015–2022 were collected. Stepped-frequency microwave radiometer (SFMR) observations made onboard the National Oceanic and Atmospheric Administration’s hurricane aircraft are available for 13 images. The geophysical model functions, namely VV-polarized C-SARMOD and cross-polarized S-1 IW/EW mode wind speed retrieval model after noise removal (S1IW.NR/S1EW.NR), were employed to invert the wind fields from the collected images. TC wind fields were reconstructed based on SAR-derived winds, enhancing TC intensity representation in the VV-polarized SAR retrievals and minimizing the error of the VH-polarized SAR retrievals at the sub-swath edge. The wind speeds retrieved from the SAR IW image were validated against the remote-sensing products from the soil moisture active passive (SMAP) radiometer, yielding a root mean squared error (RMSE) of approximately 4.3 m s−1, which is slightly smaller than the RMSE (4.4 m s−1) for the operational CyclObs wind product provided by the French Research Institute for Exploitation of the Sea (IFREMER). However, the CyclObs wind product has better performance than the approach proposed in this paper for the S-1 EW mode. Moreover, the RMSE of the wind speed between SAR-derived wind speed obtained using the proposed approach and the CyclObs wind product is within 3 m s−1 in all flow directions clockwise relative to north centered on the TC’s eye. This study provides an alternative method for TC wind retrieval from dual-polarized S-1 images without suffering saturation problem and external information; however, the pattern of the wind field around the TC’s eye needs to be further improved, especially at the head and back of the TC’s eye.

Hurricane Observations by Uncrewed Systems

Abstract On 30 September 2021, a saildrone uncrewed surface vehicle (USV) was steered into category 4 Hurricane Sam, the most intense storm of the 2021 Atlantic hurricane season. It measured significant wave heights up to 14 m (maximum wave height = 27 m) and near-surface winds exceeding 55 m s−1. This was the first time in more than seven decades of hurricane observations that in real time a USV transmitted scientific data, images, and videos of the dynamic ocean surface near a hurricane’s eyewall. The saildrone was part of a five-saildrone deployment of the NOAA 2021 Atlantic Hurricane Observations Mission. These saildrones observed the atmospheric and oceanic near-surface conditions of five other tropical storms, of which two became hurricanes. Such observations inside tropical cyclones help to advance the understanding and prediction of hurricanes, with the ultimate goal of saving lives and protecting property. The 2021 deployment pioneered a new practice of coordinating measurements by saildrones, underwater gliders, and airborne dropsondes to make simultaneous and near-collocated observations of the air–sea interface, the ocean immediately below, and the atmosphere immediately above. This experimental deployment opened the door to a new era of using remotely piloted uncrewed systems to observe one of the most extreme phenomena on Earth in a way previously impossible. This article provides an overview of this saildrone hurricane observations mission, describes how the saildrones were coordinated with other observing platforms, presents preliminary scientific results from these observations to demonstrate their potential utility and motivate further data analysis, and offers a vision of future hurricane observations using combined uncrewed platforms.

Retrieval of Rain Rates for Tropical Cyclones From Sentinel-1 Synthetic Aperture Radar Images

The purpose of this study was to develop a method for retrieving the rain rate from C-band (∼5.3 GHz) synthetic aperture radar (SAR) images during tropical cyclones (TCs). Seven dual-polarized (vertical-vertical [VV] and vertical-horizontal [VH]) Sentinel-1 (S-1) SAR images were acquired in the interferometric-wide (IW) swath mode during the Satellite Hurricane Observation Campaign. These images were collocated with rain rates measured by the Stepped-Frequency Microwave Radiometers onboard National Oceanic and Atmospheric Administration aircraft. Wind speeds were retrieved from the VH-polarized SAR images using the geophysical model function (GMF) S1IW.NR. We determined the difference between the measured normalized radar cross section (NRCS) based on VV-polarized SAR and the predicted NRCS derived using the geophysical model function CMOD5.N forced with wind speeds retrieved from VH-polarized SAR images. Rain cells were identified as regions in the images where the NRCS difference was greater than 0.5 dB or smaller than −0.5 dB. We found that the difference in the NRCS decreased and the VH-polarized wind speed increased with increasing rain rate. Based on these findings, we developed an empirical function for S-1 SAR rain retrieval in a TC, naming it CRAIN_S1. The validation of the CRAIN_S1 results with Tropical Rainfall Measuring Mission data resulted in a root mean square error of 0.58 mm/hr and a correlation of 0.89. This study provides an alternate method for rain monitoring utilizing SAR data with a fine spatial resolution.

Wind Field Retrieval with Rain Correction from Dual-Polarized Sentinel-1 SAR Imagery Collected during Tropical Cyclones

The purpose of this study is to include rain effects in wind field retrieval from C-band synthetic aperture radar (SAR) imagery collected under tropical cyclone conditions. An effective and operationally attractive approach to detect rain cells in SAR imagery is proposed and verified using four Sentinel-1 (S-1) SAR images collected in dual-polarized (vertical-vertical (VV) and vertical-horizontal (VH)) interferometric-wide swath imaging mode during the Satellite Hurricane Observation Campaign. SAR images were collocated with ancillary observations that include sea surface wind and rain rate from the Stepped-Frequency Microwave Radiometer (SFMR) on board of the National Oceanic and Atmospheric Administration aircraft. The winds are inverted from VV- and VH-polarized S-1 image using the CMOD5.N and S1IW.NR geophysical model functions (GMFs), respectively. Location and radius of cyclone’s eye, together with the TC central pressure, are calculated from the VV-polarized SAR-derived wind and a parametric model. A cost function is proposed that consists of the difference between the measured VV-polarized SAR normalized radar cross section (NRCS) and the NRCS predicted using CMOD5.N forced with the wind speed retrieved by the VH-polarized SAR images using S1IW.NR GMF and the wind direction retrieved from the patterns visible in the SAR image. This cost function is related to the SFMR rain rate. Experimental results show that the difference between measured and predicted NRCS values range from 0.5 dB to 5 dB within a distance of 100 km from the cyclone’s eye, while the difference increases spanning from 3 dB to 6 dB for distances larger than 100 km. Following this rationale, first the rain bands are extracted from SAR imagery and, then, the composite wind fields are reconstructed by replacing: (1) dual-polarized SAR-derived winds over the rain-free regions; (2) winds simulated using the radial-vortex model over the rain-affected regions. The validation of the composite wind speed against SFMR winds yields a <2 m s−1 and >0.7 correlation (COR) at all flow directions up to retrieval speeds of 70 m s−1. This result outperforms the winds estimated using the VH-polarized S1IW.NR GMF, which call for high error accuracy, such as about 4 m s−1 with a 0.45 COR ranged from 330° to 360°.

The basic wind characteristics of idealized hurricanes of different intensity levels

In the current study, we conducted four idealized hurricane simulation cases to investigate the basic wind characteristics of hurricanes at different sea surface temperatures. First, the relationship of the minimum of sea surface pressure and the maximum of time-averaged wind speed shows good agreement with observational data and theoretical considerations. Then, the tangential, radial, and vertical wind field are analyzed, both the value and the height of the maximum tangential wind increase with increasing sea surface temperature. The peak value and the height of radial inflow also increase with sea surface temperature increases. An important feature is for the depth of the inflow layer, which always increases for weak hurricanes and beginning increases then decreases for intense hurricanes locates from hurricane eye to three times radius of maximum wind, this can also be seen in hurricane observation data. More importantly, this is the first study that found it begins to increase then becomes steady for medium-strength hurricanes. Furthermore, extreme updrafts are found for intense hurricanes, while not for weak and medium-strength hurricanes, and this also shows good agreement between the observational and simulation data, which is related to coherent subkilometer-scale vortices. Also, the average surface inflow angle is −22.1°, similar to −22.6° ± 2.2° and −23° that are obtained in other studies, and the distribution of surface inflow angle displays good agreement with previous studies. The relationship of tangential velocity and radial velocity is similar to the shape of a tilted infinity symbol. Finally, by analyzing the fluctuating wind characteristics, a 200 m grid size is sufficient except for the weak hurricane, which requires a 62 m grid size for turbulence structures. From the relationship of mean and fluctuating wind characteristics, the hurricane simulation results of different intensity levels converged for 185 m and 62 m grid size.

First Quasi-Synchronous Hurricane Quad-Polarization Observations by C-Band Radar Constellation Mission and RADARSAT-2

This is the first presentation of quasi-synchronous spaceborne synthetic aperture radar (SAR) high-resolution images acquired from C-band Radar Constellation Mission (RCM) and RADARSAT-2 consisting of quad-polarization (HH + HV + VH + VV) wide-swath observations of Hurricane Epsilon. These measurements clearly show that the denoised HV- and VH-polarized normalized radar cross sections (NRCSs) have great consistency. NRCS values at HV- and VH-polarizations are more sensitive to wind speeds and less sensitive to incidence angles or wind directions than those at HH and VV for hurricane force winds. For large incidence angles and high wind speeds, the sensitivity of HH-polarized NRCS to wind speed is higher than that of VV. HH- and VV-polarized NRCSs gradually lose wind direction dependency at high winds. It is notable that the time interval between the two SAR acquisitions is only 3 min. This allows for a direct comparison of HV- and VH-polarized images to investigate the variations in high-resolution backscattering within the hurricane vortex, thereby revealing the most dynamical areas. An asymmetric dynamic is observed around the eye of Hurricane Epsilon, based on positive and negative differences (VH–HV) in the western and eastern parts of the eye. The impacts of rain on quad-polarized NRCS are also examined using collocated rain rates from the Global Precipitation Mission (GPM) and wind speeds from the Soil Moisture Active Passive (SMAP). Significant rain-induced NRCS attenuations are about 1.7 dB for HH and VV, and 2.2 dB for HV and VH, when the rain rate is 20 mm/h. These attenuations are associated with rain-induced turbulence and atmospheric absorption. This work shows that the collocated RCM and RADARSAT-2 hurricane observations provide a unique analysis of synoptic and joint C-band measurements of the ocean surface in quad-polarization; this is noteworthy in view of preparations for the next generation of dual-polarization scatterometer (SCA) onboard second-generation meteorological operational satellite program (MetOp-SG).

A Framework for Simulating the Tropical-Cyclone Boundary Layer Using Large-Eddy Simulation and Its Use in Evaluating PBL Parameterizations

AbstractBoundary layer turbulent processes affect tropical cyclone (TC) structure and intensity change. However, uncertainties in the parameterization of the planetary boundary layer (PBL) under high-wind conditions remain challenging, mostly due to limited observations. This study presents and evaluates a framework of numerical simulation that can be used for a small-domain [O(5 km)] large-eddy simulation (LES) and single-column modeling (SCM) to study the TC boundary layer. The framework builds upon a previous study that uses a few input parameters to represent the TC vortex and adds a simple nudging term for temperature and moisture to account for the complex thermodynamic processes in TCs. The reference thermodynamic profiles at different wind speeds are retrieved from a composite analysis of dropsonde observations of mature hurricanes. Results from LES show that most of the turbulence kinetic energy and vertical momentum flux is associated with resolved processes when horizontal grid spacing is O(10 m). Comparison to observations of turbulence variables such as momentum flux, effective eddy viscosity, and turbulence length scale show that LES produces reasonable results but highlight areas where further observations are necessary. LES results also demonstrate that compared to a classic Ekman-type boundary layer, the TC boundary layer is shallower, develops steady conditions much quicker, and exhibits stronger wind speed near the surface. The utility of this framework is further highlighted by evaluating a first-order PBL parameterization, suggesting that an asymptotic turbulence length scale of 40 m produces a good match to LES results.

Impact of rain on wave retrieval from Sentinel-1 synthetic aperture radar images in tropical cyclones

The main objective of our work was to investigate the impact of rain on wave observations from C-band (~5.3 GHz) synthetic aperture radar (SAR) in tropical cyclones. In this study, 10 Sentinel-1 SAR images were available from the Satellite Hurricane Observation Campaign, which were taken under cyclonic conditions during the 2016 hurricane season. The third-generation wave model, known as Simulating WAves Nearshore (SWAN) (version 41.31), was used to simulate the wave fields corresponding to these Sentinel-1 SAR images. In addition, rainfall data from the Tropical Rainfall Measuring Mission satellite passing over the spatial coverage of the Sentinel-1 SAR images were collected. The simulated results were validated against significant wave heights (SWHs) from the Jason-2 altimeter and European Centre for Medium-Range Weather Forecasts data, revealing a root mean square error (RMSE) of ~0.5 m with a 0.25 scatter index. Winds retrieved from the VH-polarized Sentinel-1 SAR images using the Sentinel-1 Extra Wide-swath Mode Wind Speed Retrieval Model after Noise Removal were taken as prior information for wave retrieval. It was discovered that rain did indeed affect the SAR wave retrieval, as evidenced by the 3.21-m RMSE of SWHs between the SAR images and the SWAN model, which was obtained for the ~1000 match-ups with raindrops. The raindrops dampened the wave retrieval when the rain rate was < ~5 mm/hr; however, they enhanced wave retrieval for higher rain rates. It was also found that the portion of the rain-induced ring wave with a wave number > 0.05 rad/m (~125 m wavelength) was clearly observed in the SAR-derived wave spectra.

CrossVis: A visual analytics system for exploring heterogeneous multivariate data with applications to materials and climate sciences

We present a new visual analytics system, called CrossVis, that allows flexible exploration of multivariate data with heterogeneous data types. After presenting the design requirements, which were derived from prior collaborations with domain experts, we introduce key features of CrossVis beginning with a tabular data model that coordinates multiple linked views and performance enhancements that enable scalable exploration of complex data. Next, we introduce extensions to the parallel coordinates plot, which include new axis representations for numerical, temporal, categorical, and image data, an embedded bivariate axis option, dynamic selections, focus+context axis scaling, and graphical indicators of key statistical values. We demonstrate the practical effectiveness of CrossVis through two scientific use cases; one focused on understanding neural network image classifications from a genetic engineering project and another involving general exploration of a large and complex data set of historical hurricane observations. We conclude with discussions regarding domain expert feedback, future enhancements to address limitations, and the interdisciplinary process used to design CrossVis.

Aircraft Observations of Tropical Cyclone Boundary Layer Turbulence over the South China Sea

Abstract There have been no high-frequency aircraft observations of tropical cyclone (TC) eyewall boundary layer turbulence since two flights into Atlantic hurricanes in the 1980s. We present an analysis of the first TC boundary layer flight observations in the South China Sea by the Hong Kong Observatory comprising four eyewall penetrations. We derive the vertical flux of momentum and vertical momentum diffusivity from observed turbulence parameters. We observe negative (upward) vertical fluxes of tangential momentum near the eyewall consistent with a jet below the flight level near the radius of maximum wind. Our observations of vertical momentum diffusivity support a superlinear relationship between diffusivity and wind speed at the high wind speeds in the inner-core of TCs (power-law exponent of 1.73 ± 0.20) while the few existing boundary layer hurricane observations in the North Atlantic suggest a more linear relationship.

Statistical Characterization of the Observed Cold Wake Induced by North Atlantic Hurricanes

This work quantifies the magnitude, spatial structure, and temporal evolution of the cold wake left by North Atlantic hurricanes. To this end we composited the sea surface temperature anomalies (SSTA) induced by hurricane observations from 2002 to 2018 derived from the international best track archive for climate stewardship (IBTrACS). Cold wake characteristics were distinguished by a set of hurricane and oceanic properties: Hurricane translation speed and intensity, and the characteristics of the upper ocean stratification represented by two barrier layer metrics: Barrier layer thickness (BLT) and barrier layer potential energy (BLPE). The contribution of the above properties to the amplitude of the cold wake was analyzed individually and in combination. The mean magnitude of the hurricane-induced cooling was of 1.7 °C when all hurricanes without any distinction were considered, and the largest cooling was found for slow-moving, strong hurricanes passing over thinner barrier layers, with a cooling above 3.5 °C with respect to pre-storm sea surface temperature (SST) conditions. On average the cold wake needed about 60 days to disappear and experienced a strong decay in the first 20 days, when the magnitude of the cold wake had decreased by 80%. Differences between the cold wakes yielded by mostly infrared and merged infrared and microwave remote sensed SST data were also evaluated, with an overall relative underestimation of the hurricane-induced cooling of about 0.4 °C for infrared-mostly data.

Logic tree approach for probabilistic typhoon wind hazard assessment

Abstract Global warming and climate change are increasing the intensity of typhoons and hurricanes and thus increasing the risk effects of typhoon and hurricane hazards on nuclear power plants (NPPs). To reflect these changes, a new NPP should be designed to endure design-basis hurricane wind speeds corresponding to an exceedance frequency of 10−7/yr. However, the short typhoon and hurricane observation records and uncertainties included in the inputs for an estimation cause significant uncertainty in the estimated wind speeds for return periods of longer than 100,000 years. A logic-tree framework is introduced to handle the epistemic uncertainty when estimating wind speeds. Three key parameters of a typhoon wind field model, i.e., the central pressure difference, pressure profile parameter, and radius to maximum wind, are used for constructing logic tree branches. The wind speeds of the simulated typhoons and the probable maximum wind speeds are estimated using Monte Carlo simulations, and wind hazard curves are derived as a function of the annual exceedance probability or return period. A logic tree decreases the epistemic uncertainty included in the wind intensity models and provides reasonably acceptable wind speeds.

First Spaceborne GNSS‐Reflectometry Observations of Hurricanes From the UK TechDemoSat‐1 Mission

AbstractWe present the first examples of Global Navigation Satellite Systems‐Reflectometry (GNSS‐R) observations of hurricanes using spaceborne data from the UK TechDemoSat‐1 (TDS‐1) mission. We confirm that GNSS‐R signals can detect ocean condition changes in very high near‐surface ocean wind associated with hurricanes. TDS‐1 GNSS‐R reflections were collocated with International Best Track Archive for Climate Stewardship (IBTrACS) hurricane data, MetOp ASCAT A/B scatterometer winds, and two reanalysis products. Clear variations of GNSS‐R reflected power (σ0) are observed as reflections travel through hurricanes, in some cases up to and through the eye wall. The GNSS‐R reflected power is tentatively inverted to estimate wind speed using the TDS‐1 baseline wind retrieval algorithm developed for low to moderate winds. Despite this, TDS‐1 GNSS‐R winds through the hurricanes show closer agreement with IBTrACS estimates than winds provided by scatterometers and reanalyses. GNSS‐R wind profiles show realistic spatial patterns and sharp gradients that are consistent with expected structures around the eye of tropical cyclones.

Combined Co- and Cross-Polarized SAR Measurements Under Extreme Wind Conditions

During summer 2016, the European Space Agency (ESA) set up the Satellite Hurricane Observations Campaign, a campaign dedicated to hurricane observations with Sentinel-1 synthetic aperture radar (SAR) in both vertical-vertical (VV) and vertical-horizontal (VH) polarizations acquired in wide swath modes. Among the 70 Sentinel-1 passes scheduled by the ESA mission planning team, more than 20 observations over hurricane eyes were acquired and tropical cyclones were captured at different development stages. This enables us to detail the sensitivity difference of VH and VV normalized radar cross section (NRCS) to the response of intense ocean surface winds. As found, the sensitivity of the VH-NRCS computed at 3-km resolution is reported to be more than 3.5 times larger than in VV. Taking opportunity of SAR high resolution, we also show that the decrease in resolution (up to 25 km) does not dramatically change the sensitivity difference between VV and VH polarizations. For wind speeds larger than 25 m/s, a new geophysical model function (MS1A) to interpret cross-polarized signal is proposed. Both channels are then combined to get ocean surface wind vectors. SAR winds are further compared at 40-km resolution against L-band soil moisture active and passive mission (SMAP) radiometer winds with co-locations less than 30 min. Overall excellent consistency is found between SMAP and this new SAR winds. This paper opens perspectives for MetOp-SG SCA, the next-generation C-band scatterometer with co- and cross-polarization capability.

Rain effects on the hurricane observations over the ocean by C‐band Synthetic Aperture Radar

AbstractA composite radar scattering model composed of the atmosphere radiative transfer model, and the ocean surface Bragg wave theory is developed to analyze the impact of hurricane rain on the normalized radar‐backscatter cross section (NRCS) measured in the VV and cross‐polarized C‐band Synthetic Aperture Radar (SAR) channels. The model results are validated against SAR and SFMR measured wind speeds and rain rates for two hurricane cases. The contribution of rain to the NRCS is backscatter from two parts: the atmosphere column and the ocean surface. In the atmosphere, microwave attenuation and the rain‐induced volume backscattering are simulated by the model. We find that the impact of raindrops in the atmosphere is almost negligible for the VV polarization, but important for the cross polarization. On the ocean surface, comparisons between our model and other existing models without rain lead to the conclusion that the VV polarization NRCS can be simulated reasonably well without considering the non‐Bragg scattering mechanisms. Similar to the wave breaking mechanism, the microwave diffraction on the craters, crowns, and stalks, produced by rain drops, is also negligible for VV polarization. However, the non‐Bragg scattering is important for the cross‐polarized NRCS simulations. Finally, we performed simulations to understand the VV‐polarized NRCS behavior under different wind speeds at various rain rates.

The Effects of Sampling Errors on the EnKF Assimilation of Inner-Core Hurricane Observations

Abstract Atmospheric data assimilation methods that estimate flow-dependent forecast statistics from ensembles are sensitive to sampling errors. This sensitivity is investigated in the context of vortex-scale hurricane data assimilation by cycling an ensemble Kalman filter to assimilate observations with a convection-permitting mesoscale model. In a set of numerical experiments, airborne Doppler radar observations are assimilated for Hurricane Katrina (2005) using an ensemble size that ranges from 30 to 300 members, and a varying degree of covariance inflation through relaxation to the prior. The range of ensemble sizes is shown to produce variations in posterior storm structure that persist for days in deterministic forecasts, with the most substantial differences appearing in the vortex outer-core wind and pressure fields. Ensembles with 60 or more members converge toward similar axisymmetric and asymmetric inner-core solutions by the end of the cycling, while producing qualitatively similar sample correlations between the state variables. Though covariance relaxation has little impact on model variables far from the observations, the structure of the inner-core vortex can benefit from a more optimal tuning of the relaxation coefficient. Results from this study provide insight into how sampling errors may affect the performance of an ensemble hurricane data assimilation system during cycling.

Ensemble Kalman Filter Assimilation of Simulated HIWRAP Doppler Velocity Data in a Hurricane

Abstract This study utilizes ensemble Kalman filter (EnKF) observing system simulation experiments (OSSEs) to analyze the potential impact of assimilating radial velocity observations of hurricanes from the High-altitude Imaging Wind and Rain Airborne Profiler (HIWRAP). HIWRAP is a new Doppler radar mounted on the NASA Global Hawk unmanned airborne system that flies at roughly 19-km altitude and has the benefit of a 25–30-h flight duration, which is 2–3 times that of conventional aircraft. This research is intended as a proof-of-concept study for future assimilation of real HIWRAP data. The most important result from this research is that HIWRAP data can potentially improve hurricane analyses and prediction. For example, by the end of a 12-h assimilation period, the analysis error is much lower than that in deterministic forecasts. As a result, subsequent forecasts initialized with the EnKF analyses also improve. Furthermore, analyses and forecasts clearly benefit more from a 12-h assimilation period than for shorter periods, which highlights a benefit of the Global Hawk's potentially long on-station times.

Cross-Polarized Synthetic Aperture Radar: A New Potential Measurement Technique for Hurricanes

We present an empirical C-band Cross-Polarization Ocean (C-2PO) model for wind retrievals from synthetic aperture radar (SAR) data collected by the RADARSAT-2 satellite. The C-2PO model relates normalized radar cross section (NRCS) in cross polarization to wind speed at 10-m height. This wind retrieval model has the characteristic that it is independent of wind direction and radar incidence angle but is quite linear with respect to wind speed. To evaluate the accuracy of the proposed model, winds with a resolution on the scale of 1 km were retrieved from a dual-polarization SAR image of Hurricane Earl on 2 September 2010, using the C-2PO model and compared with CMOD5.N, the newest available C-band geophysical model function (GMF), and validated with collocated airborne stepped-frequency microwave radiometer measurements and National Data Buoy Center data. Results suggest that for winds up to 38 m s−1, C-2PO has a bias of −0.89 m s−1 and a root-meansquare error of 3.23 m s−1 compared to CMOD5.N, which has a bias of −4.14 m s−1 and an rms difference of 6.24 m s−1. Similar results are obtained from Hurricane Ike, comparing wind retrievals from C-2PO and CMOD5.N with H*Wind data. The advantage of C-2PO over CMOD5.N and other GMFs is that it does not need any external wind direction and radar incidence angle inputs. Moreover, in the presently available quad-polarization dataset, C-2PO has the feature that the cross-polarized NRCS linearly increases even for wind speeds up to 26 m s−1 and reproduces the hurricane eye structure well, thereby providing a potential technique for hurricane observations from space.

Surge in North Atlantic hurricanes due to detectors, not climate change

A spate of research has indicated there may be a link between climate change and the prevalence of North Atlantic tropical cyclones. In a new paper, researchers note upon closer inspection that the prominent upswing in tropical cyclone detections beginning in the midtwentieth century is attributable predominantly to the detection of “shorties” tropical cyclones with durations of less than 2 days. That the apparent surge in cyclone activity could be attributable to changes in the quality and quantity of detections has gained ground as a potential alternative explanation. Using a database of hurricane observations stretching back to 1878, Villarini et al. try to tease out any detectable climate signal from the records. The authors note that between 1878 and 1943 there were 0.58 shorty detections per year, and between 1944 and 2008 there were 2.58 shorty detections per year. This increase in shorties, which the authors propose may be related to the end of World War II and the dawn of air‐based reconnaissance and weather tracking, was not mirrored by an increase in tropical cyclone activity for storms longer than 2 days. (Journal of Geophysical Research‐Atmospheres, doi:10.1029/2010JD015493, 2011

CloudSat measurements of landfalling hurricanes Gustav and Ike (2008)

[1] The spaceborne 94 GHz radar onboard the CloudSat polar orbiting satellite offers new opportunities in estimating parameters of precipitating cloud systems including hurricanes. CloudSat measurements can resolve the vertical extent of storms and hurricanes, thus providing a view of their complex structure. These measurements can be used to retrieve with high spatial resolution rainfall and ice content parameters in an atmospheric vertical column as the satellite moves over the precipitating systems. Two major Atlantic hurricanes of the 2008 season, Gustav and Ike, were observed by CloudSat near their landfalls on the coast of the Gulf of Mexico. CloudSat measurements indicated cloud top heights at around 14–16 km above the ground and extended areas of startiform-like precipitation with estimated rain rates in a range of about 3–12 mm h−1. The radar bright band features observed just below the freezing level were identifiable for most measured reflectivity profiles. Maximum retrieved ice water path values reached about 20,000 g m−2. CloudSat rain rate retrievals over land and water agreed reasonably well with approximately coincident estimates from surface precipitation radars in the areas where measurements from these radars were available and were not contaminated by melting layer returns. Hurricane Gustav remnants observed by CloudSat several days after the landfall were characterized by smaller values of rain rate and ice water path (∼2–3 mm h−1 and 1000–10,000 g m−2, correspondingly). The hurricane parameters retrieved from CloudSat measurements may complement data from other satellite sources, which are traditionally used for hurricane observations.