[Show abstract][Hide abstract] ABSTRACT: Satellite microwave scatterometers are the principal source of global synoptic-scale ocean vector wind (OVW) measurements for a number of scientific and operational oceanic wind applications. However, for extreme wind events such as tropical cyclones, their performance is significantly degraded. This paper presents a novel OVW retrieval algorithm for tropical cyclones which improves the accuracy of scatterometer based ocean surface winds when compared to low-flying aircraft with in-situ and remotely sensed observations. Unlike the traditional maximum likelihood estimation (MLE) wind vector retrieval technique, this new approach sequentially estimates scalar wind directions and wind speeds. A detailed description of the algorithm is provided along with results for ten QuikSCAT hurricane overpasses (from 2003–2008) to evaluate the performance of the new algorithm. Results are compared with independent surface wind analyses from the National Oceanic and Atmospheric Administration (NOAA) Hurricane Research Division's H*Wind surface analyses and with the corresponding SeaWinds Project's L2B-12.5 km OVW products. They demonstrate that the proposed algorithm extends the SeaWinds capability to retrieve wind speeds beyond the current range of approximately 35 m/s (minimal hurricane category-1) with improved wind direction accuracy, making this new approach a potential candidate for current and future conically scanning scatterometer wind retrieval algorithms.
[Show abstract][Hide abstract] ABSTRACT: This paper presents a conceptual conical-scanning radiometer/scatterometer (RadScat) instrument design for the purpose of improving satellite ocean vector wind retrievals under rain-free conditions. This technique combines the wind vector signature in the passive linearly polarized ocean brightness temperatures with the anisotropic signature of multiazimuthal radar cross-sectional measurements to retrieve oceanic surface wind vectors. The performance of the RadScat is evaluated using a Monte Carlo simulation based on actual measurements from the SeaWinds scatterometer and the Advanced Microwave Scanning Radiometer onboard the Advanced Earth Observing Satellite II. The results demonstrate significant improvements in wind vector retrievals, particularly in the near-subtrack swath, where the performance of conical-scanning scatterometers degrades.
IEEE Transactions on Geoscience and Remote Sensing 10/2011; · 3.47 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: The SeaWinds scatterometer, onboard the QuikSCAT satellite, infers global ocean vector winds (OVWs); however, for a number of reasons, these measurements in hurricanes are significantly degraded. This paper presents an improved hurricane OVW retrieval approach, known as Q-Winds, which is derived from combined SeaWinds active and passive measurements. In this technique, the effects of rain are implicitly included in a new geophysical model function, which relates oceanic brightness temperature and radar backscatter measurements (at the top of the atmosphere) to the surface wind vector under both clear sky and in the presence of light to moderate rain. This approach extends the useful wind speed measurement range for tropical cyclones beyond that exhibited by the standard SeaWinds Project Level-2B (L2B) 12.5-km wind vector algorithm. A description of the Q-Winds algorithm is given, and examples of OVW retrievals are presented for the Q-Winds and L2B 12.5-km algorithms for ten hurricane overpasses in 2003-2008. These data are also compared to independent surface wind vector estimates from the National Oceanic and Atmospheric Administration Hurricane Research Division's objective hurricane surface wind analysis technique known as H*Wind. These comparisons suggest that the Q-Winds OVW product agrees better with independently derived H^ Wind analysis winds than does the conventional L2B OVW product.
IEEE Transactions on Geoscience and Remote Sensing 08/2010; · 3.47 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Microwave scatterometers are the standard for satellite ocean vector winds (OVW) measurements, and they provide the major source of global ocean surface winds observations for scientific and operational applications. A major challenge for Ku-band scatterometry missions is to provide reliable retrievals in the presence of precipitation, particularly in extreme ocean wind events that are usually associated with intense rain. This paper explores the advantages of combining dual frequency (C- and Ku-band) scatterometer measurements and passive microwave observations to improve high wind speed retrievals. For this study, a conceptual design proposed by the Jet Propulsion Laboratory for a Dual Frequency Scatterometer (DFS) to fly onboard the future Japan Aerospace Exploration Agency (JAXA) GCOM-W2 mission with the Advanced Microwave Scanning Radiometer (AMSR) was adopted. A computer simulation that combines the DFS and AMSR measurements was used to develop an artificial neural network OVW retrieval algorithm. The Weather Research and Forecasting (WRF) numerical weather model of Hurricane Katrina (2005) was used as the nature run (surface truth), and simulated OVW retrievals demonstrate that this new technique offers a robust option to extend the useful wind speed measurements range beyond the current operating scatterometers for future satellite missions.
IEEE International Geoscience & Remote Sensing Symposium, IGARSS 2010, July 25-30, 2010, Honolulu, Hawaii, USA, Proceedings; 01/2010
[Show abstract][Hide abstract] ABSTRACT: This paper describes the advantages of combining passive and active microwave remote sensing observations for the purpose of ocean wind vectors retrievals. Previous studies have shown that a linear combination of horizontal and vertical polarized brightness temperatures contains a robust wind direction signal. In this paper, we present results from an end-to-end simulation of ocean measurements from a Ku-band (13.4 GHz) active/passive conical scanning satellite instrument. For this simulation, realistic wind fields from the NOAA National Center for Environmental Prediction (NCEP) numerical weather model were used to produce simultaneous brightness temperatures and radar backscatter measurements. These measurements were processed using a maximum likelihood estimation technique to yield ocean wind vector retrievals that were compared to NCEP fields. Results demonstrate significant improvements over simulated measurements for an active (radar scatterometer) sensor.
Microwave Radiometry and Remote Sensing of the Environment (MicroRad), 2010 11th Specialist Meeting on; 01/2010
[Show abstract][Hide abstract] ABSTRACT: Microwave scatterometer measurements are the standard for satellite ocean vector winds (OVW) measurements. Unfortunately, in extreme weather events, where high wind speeds are frequently associated with strong rain bands, precipitation can significantly degrade the OVW retrieval accuracy. This study addresses the feasibility of exploiting passive measurements to improve high wind speed retrievals for such extreme weather events. The Jet Propulsion Laboratory (JPL) has developed a conceptual design for a Dual Frequency Scatterometer (DFS) proposed to fly onboard the future Japan Aerospace Exploration Agency (JAXA) GCOM-W2 mission with the Advanced Microwave Scanning Radiometer (AMSR). These two instruments will provide a complimentary dataset of simultaneous and coincident active/passive measurements, which can correct for rain effects and thereby improve the OVW retrievals. End-to-end computer simulations are performed using the Weather Research and Forecasting (WRF) numerical weather model tuned to Hurricane Katrina (2005) for the 3D nature run (surface truth). Results show that the new OVW retrievals compare well to the nature run surface wind vectors and that this active/passive technique offers a robust option to extend the useful wind speed measurements range beyond the current operating scatterometers for future satellite missions.
Microwave Radiometry and Remote Sensing of the Environment (MicroRad), 2010 11th Specialist Meeting on; 01/2010
[Show abstract][Hide abstract] ABSTRACT: The purpose of this study is to investigate the potential of the next generation Dual Frequency Scatterometer (DFS) proposed to fly onboard the Japanese Aerospace Exploration Agency (JAXA)/GCOM-W2 future mission to measure surface ocean vector winds. An end-to-end simulation was performed to retrieve ocean vector winds in extreme weather conditions, where high winds are usually associated with high rain rates. Both C-and Ku-bands DFS active measurements were combined in the retrieval algorithm. The simultaneous observations of JAXA's Advanced Microwave Scanning Radiometer (AMSR) were used to passively model both the atmospheric attenuation and rain volume backscatter to correct for rain effects and to further improve the retrievals range for tropical cyclones beyond that exhibited by the current operating scatterometers.
OCEANS 2009, MTS/IEEE Biloxi - Marine Technology for Our Future: Global and Local Challenges; 11/2009
[Show abstract][Hide abstract] ABSTRACT: Over the last three decades, microwave remote sensing has played a significant role in ocean surface wind measurement, and several scatterometer missions have flown in space since early 1990�s. Although they have been extremely successful for measuring ocean surface winds with high accuracy for the vast majority of marine weather conditions, unfortunately, the conventional scatterometer cannot measure extreme winds condition such as hurricane. The SeaWinds scatterometer, onboard the QuikSCAT satellite is NASA�s only operating scatterometer at present. Like its predecessors, it measures global ocean vector winds; however, for a number of reasons, the quality of the measurements in hurricanes are significantly degraded. The most pressing issues are associated with the presence of precipitation and Ku-band saturation effects, especially in extreme wind speed regime such as tropical cyclones (hurricanes and typhoons). Under this dissertation, an improved hurricane ocean vector wind retrieval approach, named as Q-Winds, was developed using existing SeaWinds scatterometer data. This unique data processing algorithm uses combined SeaWinds active and passive measurements to extend the use of SeaWinds for tropical cyclones up to approximately 50 m/s (Hurricane Category-3). Results show that Q-Winds wind speeds are consistently superior to the standard SeaWinds Project Level 2B wind speeds for hurricane wind speed measurement, and also Q-Winds provides more reliable rain flagging algorithm for quality assurance purposes. By comparing to H*Wind, Q-Winds achieves ~9% of error, while L2B-12.5km exhibits wind speed saturation at ~30 m/s with error of ~31% for high wind speed (> 40 m/s).
[Show abstract][Hide abstract] ABSTRACT: This work investigates the design of an innovative conical scanning Ku-band (13.4 GHz) scatterometer/radiometer for measuring ocean vector winds. The sensor design is based upon actual measurements obtained by the SeaWinds scatterometer and the Advanced Microwave Scanning Radiometer (AMSR), which operated simultaneously on JAXA's Advanced Earth Observing Satellite-II (ADEOS-II) during 2003. This new design combines the conventional forward and aft-looking two-beam microwave scatterometer (SeaWinds) measurements with simultaneous linearly polarized passive microwave brightness temperatures. The unique aspect of this remote sensing technique is that it operates at a single microwave frequency, and it combines vertical and horizontal polarized microwave brightness temperatures with the scatterometer normalized cross sections to retrieve unambiguous ocean wind vectors. This technique has the potential to significantly improve the Ocean Vector Winds retrievals for future conical-scanning microwave scatterometers.
[Show abstract][Hide abstract] ABSTRACT: This paper describes recent developments of an improved geophysical ocean wind vector retrieval algorithm that uses both active and passive measurements from QuikSCAT. This algorithm results in significant improvements in wind vector measurements in hurricanes and better rain-flagging of severely rain contaminated areas than does NASA's standard wind vector product (L2B). By using a combined active/passive approach, we are able to infer wind estimates in the presence of light to moderate rain using the SeaWinds scatterometer. Rain effects (attenuation and volume scattering) are determined passively and then used to correct the measured ocean sigma-0 at 12.5 km wind vector cell resolution. Wind retrievals are performed using an improved geophysical model function (GMF) tuned for extreme wind events These ocean vector wind retrievals, known as Q-Winds, are compared with surface winds products from the NOAA Hurricane Research Division's H<sup>*</sup>Wind Analysis System, which assimilates near-simultaneous measurements from in-situ and remote sensors, such as, the Stepped Frequency Microwave Radiometer (SFMR), GPS dropsondes, and flight-level inertial navigation winds. Comparisons to H<sup>*</sup>Wind are presented for Q-Winds and the SeaWinds Project's new L2B-12.5 km ocean vector winds products.
[Show abstract][Hide abstract] ABSTRACT: The SeaWinds scatterometer, which has been flown on both the QuikSCAT and ADEOS-II satellites was designed to remotely sense ocean surface wind vectors. Because ocean wind retrievals are occasionally contaminated by rain in the tropics and because there is no independent rain measurement on QuikSCAT, a SeaWinds rain-estimation method was developed and implemented. This technique utilizes the SeaWinds receiver noise to measure ocean radiometric brightness temperature (T<sub>b</sub>) and then applies a statistical regression algorithm to estimate the integrated rain rate. This rain algorithm was originally "trained" with QuikSCAT SeaWinds T<sub>b</sub> and near-simultaneous rain rate measurements from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI). In this study, the SeaWinds instrument on ADEOS-II and the Advanced Microwave Scanning Radiometer (AMSR), also onboard ADEOS-II, were used to refine the algorithm. This provided truly simultaneous and collocated measurements from the same platform and over the same swath, which was ideal for improving the SeaWinds rain algorithm. The improved algorithm can now be applied on QuikSCAT using the SeaWinds radiometric measurement.