Analysing observation based source terms: validations and spatial analysis of high-resolution wave hindcast in the Arabian Sea, emphasizing low wind conditions
The performance of third-generation spectral wave models under low-wind conditions remains insufficiently evaluated despite the prevalence of such conditions across large portions of the global ocean. This study evaluates the WAVEWATCH III (WW3) model with the observation-based ST6 source-term parameterization in the Arabian Sea, where the low-wind pre-monsoon and post-monsoon seasons together span approximately eight months of the annual cycle. ERA-5 and CFSR/CFSv2 reanalysis wind datasets are first validated against the subset of globally calibrated satellite altimeter dataset for the year 2016 and used to force two independent WW3 simulations. Both wind products overestimate wind speed at very low winds and underestimate at low to moderate winds, while at high winds ERA-5 underestimates and CFSR/CFSv2 overestimates. The time series analysis further reveals that, during the low wind non-monsoon seasons, the CFSR/CFSv2-forced simulation produces a relatively higher positive Hs bias than the ERA-5 forced simulation, even though both wind fields carry a negative bias during the low wind periods. To examine this further with a statistically robust sample, a 5-year CFSR/CFSv2-forced hindcast (2014–2018) is conducted, which shows that the Hs overestimation is strongest during the pre-monsoon, with an Hs bias of + 0.10 m coexisting with a CFSR/CFSv2 wind bias of − 0.08 m s⁻¹ at mean winds of 4–7 m s⁻¹, and weaker during the post-monsoon, with an Hs bias of + 0.04 m coexisting with a CFSR/CFSv2 wind bias of − 0.12 m s⁻¹ at mean winds of 5–9 m s⁻¹. This counter-intuitive combination of positive Hs bias with negative wind bias during the low wind seasons is diagnostically significant, as a negative wind bias would normally be expected to produce a negative Hs bias, and cannot be explained by wind forcing errors alone. Spatially, this positive Hs bias is concentrated in the northern Arabian Sea, where Southern Ocean swells, Shamal swells, and Makran swells converge under weak local winds and where the CFSR/CFSv2 wind bias is near-zero to negative. The combined spatial and seasonal pattern is inconsistent with a wind-forcing induced error in Hs. The Hs overestimation is plausibly linked to two established physical low-wind thresholds that are absent from the ST6 physics, namely the viscous dissipation threshold for wave generation and the wave breaking onset threshold at low wind speeds. These findings establish the baseline for the implementation of low-wind thresholds in the ST6 source-term package.
A coupled WRF–ROMS–SWAN framework is used to investigate the long-term wave characteristics of the Bohai Sea through a 20-year hindcast from 2002 to 2022. The model results are validated against CMEMS current data, field wave measurements, and CCMP wind products, showing good agreement with the reference datasets. Thre...
Qing-Xun Yan, Peng Li, Xue-Chun Bai et al.· Water· 0 citations
Reliable characterization of dependent wind–wave extremes is essential for offshore wind engineering in monsoon- and tropical-cyclone-affected seas. Using a 2002–2020 COAWST hindcast for an offshore site in the northern South China Sea, we analyze 161,400 common-valid hourly samples of 10-m wind speed (U10), significan...
Bai-Ping Wang, Bo Jiang, Jie Ding et al.· Journal of Marine Science an...· 0 citations
Abstract This study assesses the performance of four reanalysis datasets, ERA5, NORA3, CERRA, and EMD WRF Europe+, by comparing them to Doppler LiDAR measurements taken at 192 m in Riga, Latvia. The analysis focused on wind speed, wind direction, Weibull distribution, turbulence intensity (TI), and its diurnal variatio...
N. Dmitrijevs, M. Mironova, S. Orlova· Latvian Journal of Physics a...· 0 citations
This study assesses the impact of assimilating remote sensing observations of significant wave height (SWH) and 10 m wind speed (WSPD) into the analysis using a weakly coupled data assimilation (WCDA) framework to improve ocean surface monitoring offshore of the Contiguous US (CONUS). We assimilated SWH and WSPD data f...
Panagiotis Mitsopoulos, Malaquias Peña, S. Flampouris et al.· Remote Sensing· 0 citations
The rapid expansion of wind farm installations in the North Sea results in an increased need for understanding their influence on the local atmosphere, as well as the interactions between them. Wind farm operation and power production are affected by wakes produced both within and upstream of the wind farms. Accurately...
Alexandros Palatos-Plexidas, S. Gremmo, J. van Beeck et al.· Wind Energy Science· 0 citations
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