High Spectral Resolution Lidar – generation 2 (HSRL-2) retrievals of ocean surface wind speed: methodology and evaluation

<p>Ocean surface wind speed (i.e., wind speed 10 m above sea level) is a critical parameter used by atmospheric models to estimate the state of the marine atmospheric boundary layer (MABL). Accurate surface wind speed measurements in diverse locations are required to improve characterization of MABL dynamics and assess how models simulate large-scale phenomena related to climate change and global weather patterns. To provide these measurements, this study introduces and evaluates a new surface wind speed data product from the NASA Langley Research Center nadir-viewing High Spectral Resolution Lidar – generation 2 (HSRL-2) using data collected as part of the NASA Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) mission. The HSRL-2 can directly measure vertically resolved aerosol backscatter and extinction profiles without additional constraints or assumptions, enabling the instrument to accurately derive atmospheric attenuation and directly determine surface reflectance (i.e., surface backscatter). Also, the high horizontal spatial resolution of the HSRL-2 retrievals (0.5 s or <span class="inline-formula">∼</span> 75 m along track) allows the instrument to probe the fine-scale spatial variability in surface wind speeds over time along the flight track and over breaks in broken cloud fields. A rigorous evaluation of these retrievals is performed by comparing coincident HSRL-2 and National Center for Atmospheric Research (NCAR) Airborne Vertical Atmosphere Profiling System (AVAPS) dropsonde data, owing to the joint deployment of these two instruments on the ACTIVATE King Air aircraft. These comparisons show correlations of 0.89, slopes of 1.04 and 1.17, and <span class="inline-formula"><i>y</i></span> intercepts of <span class="inline-formula">−</span>0.13 and <span class="inline-formula">−</span>1.05 <span class="inline-formula">m s⁻¹</span> for linear and bisector regressions, respectively, and the overall accuracy is calculated to be 0.15 <span class="inline-formula">±</span> 1.80 <span class="inline-formula">m s⁻¹</span>. It is also shown that the dropsonde surface wind speed data most closely follow the HSRL-2 distribution of wave slope variance using the distribution proposed by Hu et al. (2008) rather than the ones proposed by Cox and Munk (1954) and Wu (1990) for surface wind speeds below 7 <span class="inline-formula">m s⁻¹</span>, with this category comprising most of the ACTIVATE data set. The retrievals are then evaluated separately for surface wind speeds below 7 <span class="inline-formula">m s⁻¹</span> and between 7 and 13.3 <span class="inline-formula">m s⁻¹</span> and show that the HSRL-2 retrieves surface wind speeds with a bias of <span class="inline-formula">∼</span> 0.5 <span class="inline-formula">m s⁻¹</span> and an error of <span class="inline-formula">∼</span> 1.5 <span class="inline-formula">m s⁻¹</span>, a finding not apparent in the cumulative comparisons. Also, it is shown that the HSRL-2 retrievals are more accurate in the summer (<span class="inline-formula">−</span>0.18 <span class="inline-formula">±</span> 1.52 <span class="inline-formula">m s⁻¹</span>) than in the winter (0.63 <span class="inline-formula">±</span> 2.07 <span class="inline-formula">m s⁻¹</span>), but the HSRL-2 is still able to make numerous (<span class="inline-formula"><i>N</i>=236</span>) accurate retrievals in the winter. Overall, this study highlights the abilities and assesses the performance of the HSRL-2 surface wind speed retrievals,<span id="page3516"/> and it is hoped that further evaluation of these retrievals will be performed using other airborne and satellite data sets.</p>