An Estimate of Structural Uncertainty in QuikSCAT Wind Vector Retrievals

Abstract

Differences between Quick Scatterometer (QuikSCAT) level-2b wind vectors from the Jet Propulsion Laboratory [JPL; the Direction Interval Retrieval with Thresholded Nudging (DIRTH) product] and from the Remote Sensing Systems Co. (RSS; smoothed versions 3.0 and 4.0) for one sample month are presented. Each dataset is derived from the same observations, but processing methods result in differences between wind vectors. These differences originate from 1) uncertainty in the geophysical model functions that relate backscatter to wind, 2) noise in the backscatter measurements, and 3) spatial filtering. Statistics of wind vector differences from RSS and JPL are used as an indication of structural uncertainty in QuikSCAT wind retrievals. When grouped by 1 m s 21 bins, systematic differences are largest beyond 20 m s 21 , where wind speeds from version 3.0 (version 4.0) of RSS can be more than 15 (10) m s 21 higher (lower) than JPL wind speeds. Below 20 m s 21 , systematic differences on the order of tenths of a meter per second are attributed to differences in the retrieval methods, rain and ice contamination, and cross-swath position. Even once the recommended data flags are applied, differences in individual wind speed retrievals exceed 10 m s 21 in a few cases but are much smaller in regions of the swath for which the viewing geometry allows more reliable retrievals. In all parts of the swath, the standard deviations of the differences are smaller than 1.0 m s 21 . The analyses provide a measure of the structural uncertainty in QuikSCAT wind velocity that is due to the retrieval process, although such comparisons are not able to determine which dataset is closest to the actual wind.

Insights on the OAFlux ocean surface vector wind analysis merged from scatterometers and passive microwave radiometers (1987 onward)

“…One is that the near-surface wind measurements provided by the global tropical moored buoy array are a reliable ground truth for calibrating and validating the GMFs under low-wind conditions. This appears to be supported by the findings of Fangohr and Kent [2012], who evaluated four QuikSCAT products generated from different GMFs and found that systematic differences between products tend to be small, of order 0.1 m s 21 and between 3 and 20 m s 21 , but for high wind speeds exceeding 20 m s 21 , the average absolute differences can be of 10 m s 21 . The second factor is that, except for ASCAT, all the other satellite data sets were generated by RSS.…”

“…The latter appears to be explainable from the theoretical viewpoint that the two types of sensors have opposite dependences on the incidence angle at high wind speeds-yet, we caution that this may not be the only explanation. The lack of reliable high wind speed ground truth to calibrate the high-wind Geophysical Model Functions (GMFs) as well as a less pronounced dependence of the normalized radar cross section (r 0 ) on wind speed at high winds could be a significant contributor to the uncertainty of high wind retrievals [e.g., Yueh et al, 2001;Fangohr and Kent, 2012].…”

A Satellite Study of Tropical Moist Convection and Environmental Variability: A Moisture and Thermal Budget Analysis

“…The QuikSCAT wind has a root-mean-square (rms) error less than 1 m s 21 and a bias of 0.1 m s 21 at most, except for very rare occasions with extremely high winds (Ebuchi et al 2002;Bourassa et al 2003;Fangohr and Kent 2012). These values are adopted for the error estimates of evaporation and SC convergence.…”

A comparative assessment of monthly mean wind speed products over the global ocean

“…The Jet Propulsion Laboratory (JPL) and Remote Sensing Systems (RSS) have each produced their own level 2b (swath) and level 3 (gridded) wind data since the launch of the instrument. Whilst generally consistent with each other, the datasets are based on different geophysical model functions that relate sea-surface roughness to wind and subtle differences exist (Fangohr and Kent, 2012). In April 2011, RSS reprocessed their entire data from version 3.0 to version 4.0 reducing some of the more substantial discrepancies at high wind speeds.…”