Peth Laupattarakasem

Improved Hurricane Ocean Vector Winds Using SeaWinds Active/Passive Retrievals

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 Divisions 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.

A Non-MLE Approach for Satellite Scatterometer Wind Vector Retrievals in Tropical Cyclones

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 Divisions H*Wind surface analyses and with the corresponding SeaWinds Projects 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.

A Novel Ku-Band Radiometer/Scatterometer Approach for Improved Oceanic Wind Vector Measurements

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.

Improved hurricane active/passive simulated wind vector retrievals

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.

An improved active/passive oceanic wind vector retrieval technique

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.

Improved high wind speed retrievals using AMSR and the next generation NASA Dual Frequency Scatterometer

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.

A Ku-Band Active/Passive Wind Vector Retrieval Over the Ocean

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 JAXAs 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.

SeaWinds Hurricane Wind Retrievals and Comparisons with H * Wind Surface Winds Analyses

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 NASAs 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 Divisions H*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*Wind are presented for Q-Winds and the SeaWinds Projects new L2B-12.5 km ocean vector winds products.