Comparison of Geophysical Model Functions for SAR Wind Speed Retrieval in Japanese Coastal Waters

Abstract

This work discusses the accuracies of geophysical model functions (GMFs) for retrieval of sea surface wind speed from satellite-borne Synthetic Aperture Radar (SAR) images in Japanese coastal waters characterized by short fetches and variable atmospheric stability conditions. In situ observations from two validation sites, Hiratsuka and Shirahama, are used for comparison of the retrieved sea surface wind speeds using CMOD (C-band model)4, CMOD_IFR2, CMOD5 and CMOD5.N. Of all the geophysical model functions (GMFs), the latest C-band GMF, CMOD5.N, has the smallest bias and root mean square error at both sites. All of the GMFs exhibit a negative bias in the retrieved wind speed. In order to understand the reason for this bias, all SAR-retrieved wind speeds are separated into two categories: onshore wind (blowing from sea to land) and offshore wind (blowing from land to sea). Only offshore winds were found to exhibit the large negative bias, and short fetches from the coastline may be a possible reason for this. Moreover, it is clarified that in both the unstable and stable conditions, CMOD5.N has atmospheric stability effectiveness, and can keep the same accuracy with CMOD5 in the neutral condition. In short, at the moment, CMOD5.N is thought to be the most promising GMF for the SAR wind speed retrieval with the atmospheric stability correction in Japanese OPEN ACCESS Remote Sens. 2013, 5 1957 coastal waters, although there is ample room for future improvement for the effect from short fetch.

On the feasibility of the use of wind SAR to downscale waves on shallow water

“…Although CMOD5.N GMF for SAR wind estimation has the smallest bias and root-mean-square error based on the recent literature, all of the GMFs exhibit a negative bias in the retrieved wind speed (Takeyama et al, 2013). This research study is in the context of operational oceanography research development for the Copernicus CMEMS service, and therefore made use of a wind forcing data set similar to what oceanographers will operationally use from Sentinel-1A SAR-derived products.…”

Validation of Sentinel-1A SAR Coastal Wind Speeds Against Scanning LiDAR

“…Unlike previous validation studies in coastal areas [9][10][11][12][13][14][15][16], the use of scanning LiDARs made comparisons to SAR wind speeds on a transect possible. The effect of currents, waves and limited fetch on e.g., the Charnock parameter in coastal waters has not been taken into account in this study.…”

“…Hasager et al [9] 149 to 197 Denmark/The Netherlands 1.27 to 1.65 Envisat Chang et al [10] 552 South Chinese Sea 2.09 Envisat Takeyama et al [11] 42 Japan 0.75 to 2.24 Envisat Chang et al [12] 522 East Chinese Sea 1.99 Envisat Takeyama et al [13] 33 to 73 Japan 0.64 to 2.34 Envisat Hasager et al [14] 875 Baltic Sea 1.17 Envisat Christiansen et al [15] 91 Denmark 1.1 to 1.8 ERS2 Hasager et al [16] 61 Denmark 0.9 to 1.14 ERS2…”

“…These RMSEs are comparable to results from validation studies in the open ocean using buoy data, scatterometer derived winds, atmospheric modelling [5,[17][18][19] that ranged between 0.65 ms −1 and 1.76 ms −1 . Large influences of the wind directions from land or from the sea with high RMSEs above 2 ms −1 were found in Takeyama et al [13] and Takeyama et al [11] while very little influence was found in Chang et al [10]. Validation studies for coastal sites in Table 1 were done with point measurements from meteorological masts and indicate that SAR can measure wind speeds in the coastal zone.…”

“…The influence of those effects can change when moving from the open ocean to the coastal zone. Table 1 shows an overview of selected past studies validating C-band SAR winds in coastal regions using meteorological masts [9][10][11][12][13][14][15][16]. Resulting Root Mean Square Errors (RMSE) ranged between 0.64 ms −1 and 2.34 ms −1 .…”