# Characterization of CYGNSS Ocean Surface Wind Speed Products
## 4 Discussion of Sensitivity to Persistence  
The behavior of CYGNSS wind speed retrieval bias--in particular how it varies as a function of wind speed, wind persistence, Significant Wave Height, and the approach used by the retrieval algorithm to deal with these dependencies--provides insights into the inherent sensitivity of GNSS-R measurements to portions of the ocean surface roughness spectrum not directly forced by the local wind stress. Some of these dependencies are highlighted in Table 6, which reports the bias at both typical and high wind speeds and for moderate, large negative, and large positive values of wind speed persistence. The table also reports the bias individually for the FDS and NOAA wind speed products to highlight the effects of the different retrieval algorithm approaches they use. The full range of dependencies across all wind speed and persistence values was illustrated in Figures 18 and 19. As reported in Table 6, typical (5-10 m/s) wind speeds account for 62% of the total samples observed in all conditions. Moderate persistence values (wind speed changes over the previous 2 h of between \(-\)25% and +25% of the present wind speed) account for 95% of those samples. Under these jointly typical conditions of wind speed and persistence, the retrieval bias is very low, at 0.00 m/s for the FDS and \(-\)0.03 m/s for the NOAA product. This is to be expected since both retrieval algorithms are based on empirically derived regressions that are weighted toward the most commonly occurring conditions. For atypical persistence conditions at typical wind speeds, however, the bias can grow significantly. In the FDS case, a large negative persistence (\(<\)\(-\)25%) resulted in a bias of 2.3 m/s whereas a large positive persistence (>25%) resulted in a bias of 0.4 m/s, which is still low. The situation is similar with the NOAA product. A persistence below \(-\)25% resulted in a bias of 1.9 m/s and a persistence above 25% in a bias of 0.1 m/s. Note that the anomalously large negative persistence values only occur \(\sim\)3% of the time, so they do not contribute significantly to the overall global performance statistics. A negative persistence implies that the past winds were higher than in the present. The fact that the bias is more sensitive to these conditions suggests that the retrieval algorithm is essentially tuned to expect a long wave portion of the roughness spectrum that is more consistent with lower winds. Figure 19: Bias in the CYGNSS NOAA wind speed product as a function wind speed persistence prior to the measurement for wind speed ranges of (**a**) 0–5 m/s, (**b**) 5–10 m/s, (**c**) 10–15 m/s, (**d**) 15–20 m/s, (**e**) >20 m/s. Persistence \(<\) 0 implies prior winds were higher. Bias is the average (NOAA–ERA5) difference for all of CY2022. Error bars are the standard deviation of all samples averaged in each wind speed and persistence bin. The fact that a large positive persistence (in which case past wind speed is significantly lower than at present) does not result in a similar retrieval bias suggests that the time scale of the energy cascade from shorter to longer wavelengths of the roughness spectrum may be shorter in high wind than low wind conditions. Table 6 also includes bias results for high wind (>20 m/s) conditions while similarly partitioning the samples into moderate, large negative, and large positive persistence. Such high winds occur infrequently (~0.02% of all samples) but the behavior of the retrieval algorithm under these conditions can nonetheless be informative. The FDS bias at moderate levels of persistence was still fairly low at 2.1 m/s, it was slightly lower (1.3 m/s) with a large positive persistence, and it had a very high bias of 9.5 m/s when there was a large negative persistence. The explanation for the high bias is similar to the lower wind speed case. A large negative persistence implies that the past wind speed was higher, in this case much higher, since the wind speed range considered was > 20 m/s.