Bryan W. Stiles

Titan Radar Mapper observations from Cassini's T3 fly-by

Cassinis Titan Radar Mapper imaged the surface of Saturns moon Titan on its February 2005 fly-by (denoted T3), collecting high-resolution synthetic-aperture radar and larger-scale radiometry and scatterometry data. These data provide the first definitive identification of impact craters on the surface of Titan, networks of fluvial channels and surficial dark streaks that may be longitudinal dunes. Here we describe this great diversity of landforms. We conclude that much of the surface thus far imaged by radar of the haze-shrouded Titan is very young, with persistent geologic activity.

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.

Challenges to Satellite Sensors of Ocean Winds: Addressing Precipitation Effects

AbstractMeasurements of global ocean surface winds made by orbiting satellite radars have provided valuable information to the oceanographic and meteorological communities since the launch of the Seasat in 1978, by the National Aeronautics and Space Administration (NASA). When Quick Scatterometer (QuikSCAT) was launched in 1999, it ushered in a new era of dual-polarized, pencil-beam, higher-resolution scatterometers for measuring the global ocean surface winds from space. A constant limitation on the full utilization of scatterometer-derived winds is the presence of isolated rain events, which affect about 7% of the observations. The vector wind sensors, the Ku-band scatterometers [NASA’s SeaWinds on the QuikSCAT and Midori-II platforms and Indian Space Research Organisation’s (ISRO’s) Ocean Satellite (Oceansat)-2], and the current C-band scatterometer [Advanced Wind Scatterometer (ASCAT), on the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT)’s Meteorological Operation ...

Trends and Variation in Ku-Band Backscatter of Natural Targets on Land Observed in QuikSCAT Data

It has been well known that a few areas on the Earths surface have a relatively constant backscattering coefficient and can serve as radar calibration targets. Examples include the Amazon rain forest, the Greenland ice sheet, parts of Antarctica, etc. However, there has not been any extensive investigation and quantitative evaluation of these targets in terms of their time variation, isotropy, and spatial variation. Here, we have analyzed a consistent set of Ku-band radar measurements for more than ten years from the QuikSCAT mission. This valuable set of data provides an unprecedented opportunity for us to study the long-term variability of observed backscattering from the Earths surface at Ku-band. In this paper, we performed a global survey of potential constant land targets and evaluated their variability. Quantitative measurements of temporal and spatial variabilities (homogeneity) and isotropy are used to identify the locations of the best natural calibration targets. We also discuss annual and long-term trends in the data and offer potential explanations for these trends. We examine small regions with the least overall variation. By concentrating on low-variation areas, we can identify useful calibration targets for future radar missions and for intercalibration between existing radars. At the same time, by focusing on regions with little spatial or temporal heterogeneity, we can analyze the temporal variation on diurnal, seasonal, and decadal scales in homogenous natural terrain types including rain forest, dry brushy areas, and ice sheets. We found that rain forest targets in the Amazon and Congo are very stable in time and homogeneous. However, they are subjected to diurnal difference. On the other hand, the Antarctica ice sheet is another good candidate for stable target, but it has seasonal variability. The Greenland ice sheet shows a significant trend in backscatter in recent years, and therefore, may not be a suitable calibration site anymore. Another location for a good stable target is a dry brushy area in the Sahara, which shows comparable stability and isotropy with those of the Amazon, Congo, and Antarctica.

Evaluating and Extending the Ocean Wind Climate Data Record

Satellite microwave sensors, both active scatterometers and passive radiometers, have been systematically measuring near-surface ocean winds for nearly 40 years, establishing an important legacy in studying and monitoring weather and climate variability. As an aid to such activities, the various wind datasets are being intercalibrated and merged into consistent climate data records (CDRs). The ocean wind CDRs (OW-CDRs) are evaluated by comparisons with ocean buoys and intercomparisons among the different satellite sensors and among the different data providers. Extending the OW-CDR into the future requires exploiting all available datasets, such as OSCAT-2 scheduled to launch in July 2016. Three planned methods of calibrating the OSCAT-2 σo measurements include 1) direct Ku-band σo intercalibration to QuikSCAT and RapidScat; 2) multisensor wind speed intercalibration; and 3) calibration to stable rainforest targets. Unfortunately, RapidScat failed in August 2016 and cannot be used to directly calibrate OSCAT-2. A particular future continuity concern is the absence of scheduled new or continuation radiometer missions capable of measuring wind speed. Specialized model assimilations provide 30-year long high temporal/spatial resolution wind vector grids that composite the satellite wind information from OW-CDRs of multiple satellites viewing the Earth at different local times.

Cross-Calibration Between QuikSCAT and Oceansat-2

This paper presents the procedure to perform cross-calibration of radar backscatter between the QuikSCAT and Oceansat-2 ocean wind scatterometers. Both QuikSCAT and Oceansat-2 are Ku-band dual pencil beam, rotating antenna scatterometers with similar design. There has been a joint effort by the Indian Space Research Organization, NASA, KNMI, and NOAA to perform calibration and validation of Oceansat-2 in order to extend the climate data record of ocean surface vector winds obtained by QuikSCAT. This has resulted in significant improvement in the quality of the normalized radar cross section (NRCS) data and the quality of the resultant winds produced using the Oceansat-2 NRCS measurements. An important aspect of this calibration is the reduction of the calibration bias between QuikSCAT and Oceansat-2. The nonspinning QuikSCAT scatterometer was repointed to achieve the same incidence angles for its two HH and VV polarized antenna beams as those utilized by Oceansat-2. The magnitudes of the NRCS (backscatter) measurements of the two scatterometers were then compared for two years in order to determine NRCS bias in decibels as a function of time. Biases for both antenna beams were computed. A wind speed/wind-relative azimuth angle histogram-matched method was applied to ocean data from the two scatterometers to determine the time series of the bias between the two. It has been determined that there was an ~0.5 dB drop in Oceansat-2 radar backscatter on August 20, 2010. As a result, we compute cross-calibration adjustments to apply to Oceansat-2 data before and after this distinct drop in backscatter.

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.

The shape of Saturn's moon Titan from Cassini radar altimeter and SAR monopulse observations

We have estimated global elevations on Titan using a combination of nadir-looking altimetry and SAR monopulse measurements acquired by the Cassini spacecraft radar on multiple Titan encounters. These data correspond to a set of one-dimensional tracks spread over much of the moons surface, but with fewer observations in the southern hemisphere than in the north. We fit the measured points with spheres, biaxial ellipsoids, and a set of spherical harmonic functions to produce global elevation estimates.

QuikSCAT wind retrievals for tropical cyclones

The use of QuikSCAT data for wind retrievals of tropical cyclones is described. The evidence of QuikSCAT sigma-0 dependence on wind direction for >30 m/s wind speeds is presented. The QuikSCAT sigma-0s show a peak-to-peak wind direction modulation of /spl sim/1 dB at 35 m/s wind speed, and the amplitude of modulation decreases with wind speed. The decreasing directional sensitivity to wind speed agrees well with the trend of QSCAT1 model function at near 20 m/s. A correction of the QSCAT1 model function for above 23 m/s wind speed is proposed. We explored two microwave radiative transfer models to correct the attenuation and scattering effects of rain for wind retrievals. One is derived from the collocated QuikSCAT and SSM/I data set, and the other one is a published parametric model developed for rain radars. These two radiative transfer models account for the effects of volume scattering, scattering from rain-roughened surfaces and rain attenuation. The models suggest that the sigma-0s of wind-roughened sea surfaces for 40-50 m/s winds are comparable to the contributions of rain for up to about 10-15 mm/h. Both radiative transfer models have been used to retrieve the ocean wind vectors from the collocated QuikSCAT and SSM/I rain rate data for several tropical cyclones. The resulting wind speed estimates of these tropical cyclones show improved agreement with the wind fields derived from the best track analysis and Hollands model for up to about 15 mm/h SSM/I rain rate. A comparative analysis of maximum wind speed estimates suggests that other rain parameters likely have to be considered for further improvements.

Rain, wind, and backscatter: modeling rain effects on Ku-band ocean wind scatterometers

Spaceborne Ku-band ocean wind scatterometers (SeaWinds, NSCAT) enable frequent global coverage of meso-scale ocean surface winds. These instruments measure the normalized backscatter cross-section (/spl sigma//sub 0/) of the oceans surface from multiple look directions and use this information to estimate ocean surface wind vectors. Although /spl sigma//sub 0/ is strongly related to surface winds, at Ku-band it is also impacted to varying degrees by rain. Arguably, the most important error source for Ku-band wind scatterometers is rain contamination. In order to calibrate out the effects of rain as much as possible, we must understand the impact of rain on the backscatter measurements which are used to retrieve wind vectors.