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At least 19 records

SeaWinds Scatterometer on QuikSCAT Mission and the Emerging Land and Ocean Applications

Spaceborne scatterometers are active microwave radar instruments designed to acquire near-simultaneous, spatially collocated measurements of the normalized radar backscattering cross section (sigma0) of the global surface from several azimuth and/or incidence angles. The primary objective of the scatterometer mission is to measure the near-surface wind speed and direction over the global ocean using sigma0 measurements together with a wind geophysical model function. However, since sigma0 measurements are collected globally all the time, sigma0 data can also be used for global land and ice applications. In this paper, we will first present the objectives of the QSCAT mission, the instrument design, and the unique features of the Ku-band scatterometer currently in operation, called SeaWinds on QuikSCAT (QSCAT). We will then present some emerging land and ocean applications of the QSCAT data, which include (1) global snow detection and monitoring, (2) melt region mapping on the Greenland ice sheet, (3) Monsoon flood detection and monitoring, (4) soil wetness application at large scale, and (5) hurricane monitoring and tracking.

Tsai, W.-Y.↗

[Measurement of Speed and Direction of Ocean Surface Winds Using Quik Scat Scatterometer]

The SeaWinds on QuikSCAT scatterometer was developed by NASA JPL to measure the speed and direction of ocean surface winds. Simulations performed to estimate the performance of the instrument prior to its launch have indicated that the mid-swath accuracy is worse than that of the rest of the swath. This behavior is a general characteristic of scanning pencil beam scatterometers. For SeaWinds, the accuracy of the rest of the swath, and the size of the swath are such that the instrument meets its science requirements despite mid-swath shortcomings. However, by understanding the problem at mid-swath, we can improve the performance there as well. We discuss the underlying causes of the problem in detail and propose a new wind retrieval algorithm which improves mid-swath performance. The directional discrimination ability of the instrument varies with cross track distance wind speed, and direction. By estimating the range of likely wind directions for each measurement cell, one can optimally apply information from neighboring cells where necessary in order to reduce random wind direction errors without significantly degrading the resolution of the resultant wind field. In this manner we are able to achieve mid-swath RMS wind direction errors as low as 15 degrees for low winds and 10 degrees for moderate to high winds, while at the same time preserving high resolution structures such as cyclones and fronts.

Stiles, Bryan↗

A Probabilistic Technique for Improving the Mid-Swath Wind Direction Accuracy of Scanning Pencil Beam Scatterometers

The SeaWinds on QuikSCAT scatterometer is a device developed by NASA JPL to measure the speed and direction of ocean surface winds. Simulations performed in order to determine the expected performance of the instrument prior to its launch have indicated that the accuracy of the retrieved wind vectors varies across the swath. In particular the mid-swath accuracy is worse than that of the rest of the swath. This behavior is a general characteristic of scanning pencil beam scatterometers. For SeaWinds, the accuracy of the rest of the swath, and the size of the swath are such that the instrument meets its science requirements despite mid-swath shortcomings. However, by understanding the problem at mid-swath, we can improve the performance there as well, yielding even better coverage and accuracy than was originally intended. The mid-swath performance degradation is due to suboptimal viewing geometry. In particular mid-swath measurements contains measurements from two azimuths, roughly 180 degrees apart. With the standard wind retrieval technique, mid-swath root mean square (RMS) wind direction errors are approximately 30 degrees for low wind speeds (3 - 5.5 m/s) and 20 degrees for moderate to high wind speeds (5.5 - 30 m/s). We discuss the underlying causes of this phenomenon in detail and propose a modification to the wind retrieval technique in order to improve mid-swath performance. By estimating the range of likely wind directions for each measurement cell, one can optimally apply information from neighboring cells in order to reduce random wind direction errors without significantly degrading the resolution of the resultant wind field. In this manner we are able to achieve mid-swath RMS wind direction errors as low as 15 degrees for low winds and 10 degrees for moderate to high winds, while at the same time preserving high resolution structures such as cyclones and fronts. Since our results are based on simulated data, we also outline a procedure for making use of real data to optimize the technique after launch.

Stiles, Bryan↗

Evaluation of High-Resolution Ocean Surface Vector Winds Measured by QuikSCAT Scatterometer in Coastal Regions

The SeaWinds scatterometer onboard QuikSCAT covers approximately 90% of the global ocean under clear and cloudy condition in 24 h, and the standard data product has 25-km spatial resolution. Such spatial resolution is not sufficient to resolve small-scale processes, especially in coastal oceans. Based on range-compressed normalized backscatter and a modified wind retrieval algorithm, a coastal wind dataset at 12.5-km resolution was produced. Even with larger error, the high-resolution winds, in medium to high strength, would still be useful over coastal ocean. Using measurements from moored buoys from the National Buoy Data Center, the high-resolution QuikSCAT wind data are found to have similar accuracy as standard data in the open ocean. The accuracy of both high- and standard-resolution winds, particularly in wind directions, is found to degrade near shore. The increase in error is likely caused by the inadequacy of the geophysical model function/ambiguity removal scheme in addressing coastal conditions and light winds situations. The modified algorithm helps to bring the directional accuracy of the high-resolution winds to the accuracy of the standard-resolution winds in near-shore regions, particularly in the nadir and far zones across the satellite track.

scatterometer↗

Polarimetric Ku-Band Scatterometer for High Accuracy, Large Swath Global Wind Vector Measurements

In the past, wind measurements from space using fan-beam antennas, such as Seasat Scatterometer (SASS-1), ERS-1 &2, and NASA scatterometer (NSCAT), required up to six large stick-like antennas and suffered a nadir gap of up to 400 km. In the near future, a spinning pencil-beam scatterometer system is to be used for the SeaWinds scatterometer on QuikSCAT (QSCAT) and on ADEOS-2 (SeaWinds). This scatterometer, though offering wind measurements in the nadir region, still suffers from degraded performance in the nadir and outer swath. The purpose of this paper is to present an advanced polarimetric spinning pencil-beam scatterometer system, which can significantly improve the wind performance across the entire swath. The polarimetric scatterometer simultaneously measures co-polarized backscatter and the polarimetric correlation of co- and cross-polarized radar returns from the ocean surface. The advantage over the conventional scatterometer system is that, while the co-polarization radar returns are even function of the wind direction, the polarimetric correlation is an odd function of wind direction due to the reflection symmetry of the wind roughened surface. Therefore, this polarimetric scatterometer system can provide additional, equivalent measurements at azimuth angle 45degree away from the corresponding co-polarization measurements. The combined co-polarization and correlation measurements enable good wind performance across the whole swath to be obtained. In this paper, we will first present the theoretical formulation of all of the key components required for designing a polarimetric scatterometer. Then, we show that good wind performance can be achieved by a slight improvement in the signal-to-noise ratio of the current QSCAT/SeaWinds design. We then present the predicated wind performance using computer simulation based on a model function for the co-polarized backscatter obtained from actual spaceborne scatterometer data and an estimated model function for the polarimetric correlation based on the asymmetry observed in backscatter data. Finally, we will show that, aside from ocean applications, this polarimetric scatterometer can also be used for ice and land applications.

Tsai, Wu-Yang↗

The QuikSCAT wind scatterometer mission

In this paper, we describe the QuikSCAT mission, outline the key design features of the SeaWinds scatterometer, and mention some of the current and emerging science applications.

scatterometer SeaWinds QuikSCAT↗

The SeaWinds Scatterometer Antenna Subsystem on the QuikScat Spacecraft

In today's environment of "Better, Faster, Cheaper", the ability to produce reliable, flight-proven mechanisms for mission critical applications is more important than ever. Such a mechanism was produced for the QuikScat satellite. The Scatterometer Antenna Subsystem (SAS) is a spin mechanism that continuously rotates a scatterometer antenna, and includes the necessary features (rotary interfaces, drives, launch locks, etc) to allow collection of the scatterometry data that will insure mission success. This paper will discuss the evolution of the SAS from its design heritage on the GGS Polar mission to qualification on the ADEOS II satellite to being a key enabler for the rapid development of the QuikScat Satellite.

Workman, Brian J.↗