scholarly journals On the Impact of Sea State on GNSS-R Polarimetric Observations

2020 ◽  
Author(s):  
Mostafa Hoseini ◽  
Maximilian Semmling ◽  
Erik Rennspiess ◽  
Markus Ramatschi ◽  
Rüdiger Haas ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Tide Gauge ◽  
Empirical Relation ◽  
Sea Surface ◽  
Sea State ◽  
Sea Levels ◽  
Wind Speeds ◽  
Sea Surface Roughness ◽  
Different Response ◽  
The Impact

<p>We investigate a long-term ground-based GNSS-R dataset to evaluate the effect of sea state on the polarization of the reflected signals. The dataset consists of one-year polarimetric observations recorded at Onsala space observatory in Sweden in 2016 using right- and left-handed circular polarization (RHCP and LHCP) antennas. One up-looking antenna to receive direct signal and two side-looking antennas to collect reflections are installed at about 3 meters above sea level. The data is collocated with the measurements from a nearby tide-gauge and meteorological station.</p><p>We focus on precise power estimation using a polarimetric processor based on Lomb–Scargle periodogram at precisely observed sea levels. The processor converts 0.1 Hz coherent in-phase and quadrature correlation sums provided by a reflectometry receiver to power estimates of the direct and reflected signals. The power estimates are reduced to three power ratios, i.e. cross-, co-, and cross to co-polarization. A model, describing the elevation dependent power loss due to sea surface roughness, is then utilized to invert the calculated power ratios to the standard deviation of sea surface height.</p><p>Analysis of about 14000 events found in the dataset (~40 continuous tracks per day) shows a fair agreement with the wind speeds as an indicator of the sea state. Although an increasing sensitivity to sea state is observed for all the power ratios at elevation angles above 10 degrees, the measurements from the co-polar link seem to be less affected by the surface roughness. The results reveal that the existing model cannot predict the effect of sea surface roughness in a comprehensive way. The different response of RHCP and LHCP observations to roughness is evident, however, the polarization dependence is not covered by the model. The deviations from the model are particularly clear at lowest elevations (<5 deg) where the roughness effect is expected to vanish. The results indicate that roughness also affect observations at lowest elevation angles. In this elevation range the expected dominance of the RHCP component above the LHCP component is not observed.  A different approach is required to model the influence of sea state in GNSS-R. The increasing amount of reflectometry data may allow to retrieve an empirical relation between coherent reflection power and sea state in future investigation.</p>

scholarly journals A Novel Sea Surface Roughness Parameterization Based on Wave State and Sea Foam

2021 ◽  
Vol 9 (3) ◽  
pp. 246
Author(s):  
Difu Sun ◽  
Junqiang Song ◽  
Xiaoyong Li ◽  
Kaijun Ren ◽  
Hongze Leng
Keyword(s):  
Surface Roughness ◽  
Wind Speed ◽  
Drag Coefficient ◽  
Sea Surface ◽  
High Wind Speed ◽  
Wave State ◽  
Wind Speeds ◽  
Sea Surface Roughness ◽  
Extreme Wind ◽  
The Impact

A wave state related sea surface roughness parameterization scheme that takes into account the impact of sea foam is proposed in this study. Using eight observational datasets, the performances of two most widely used wave state related parameterizations are examined under various wave conditions. Based on the different performances of two wave state related parameterizations under different wave state, and by introducing the effect of sea foam, a new sea surface roughness parameterization suitable for low to extreme wind conditions is proposed. The behaviors of drag coefficient predicted by the proposed parameterization match the field and laboratory measurements well. It is shown that the drag coefficient increases with the increasing wind speed under low and moderate wind speed conditions, and then decreases with increasing wind speed, due to the effect of sea foam under high wind speed conditions. The maximum values of the drag coefficient are reached when the 10 m wind speeds are in the range of 30–35 m/s.

The impact of atmosphere-ocean-wave coupling on extreme surface wind forecasts

2021 ◽  
Author(s):  
Emanuele Silvio Gentile ◽  
Suzanne L. Gray ◽  
Janet F. Barlow ◽  
Huw W. Lewis ◽  
John M. Edwards
Keyword(s):  
Wind Speed ◽  
Wind Waves ◽  
Surface Wind ◽  
Computational Cost ◽  
Sea Surface ◽  
Model Systems ◽  
Sea State ◽  
Extreme Surface ◽  
Wind Speeds ◽  
The Impact

<p>Accurate modelling of air-sea surface exchanges is crucial for reliable extreme surface wind forecasts.  While atmosphere-only weather forecast models represent ocean and wave effects through sea-state independent parametrizations, coupled multi-model systems capture sea-state dynamics by integrating feedbacks between atmosphere, ocean and wave model components.</p><p>Here, we present the results of studying the sensitivity of extreme surface wind speeds to air-sea exchanges at kilometre scale using coupled and uncoupled configurations of the Met Office's UK Regional Coupled Environmental Prediction (UKC4) system. The case period includes the passage of extra-tropical cyclones Helen, Ali, and Bronagh, which brought maximum gusts of 36 ms<sup>-1</sup> over the UK.</p><p>Compared to the atmosphere-only results, coupling to ocean decreases the domain-average sea surface temperature by up to 0.5 K. Inclusion of coupling to waves decreases the 98th percentile 10-m wind speed by up to 2 ms<sup>-1</sup> as young, growing wind waves decrease wind speed by increasing the sea aerodynamic roughness. Impacts on gusts are more modest, with local reductions of up to 1ms <sup>-1,</sup> due to enhanced boundary-layer turbulence which partially offsets air-sea momentum transfer.</p><p>Using a new drag parametrization based on the COARE~4.0 scheme, with a cap on the neutral drag coefficient and decrease for wind speeds exceeding 27 ms<sup>-1 </sup>, the atmosphere-only model achieves equivalent impacts on 10-m wind speeds and gusts as from coupling to waves. Overall, the new drag parametrization achieves the same 20% improvement in forecast 10-m wind skill as coupling to waves, with  the  advantage  of saving the computational cost of the ocean and wave models. </p>

scholarly journals On the Wave State Dependence of the Sea Surface Roughness at Moderate Wind Speeds under Mixed Wave Conditions

2020 ◽  
Vol 50 (11) ◽  
pp. 3295-3307
Author(s):  
Shuiqing Li ◽  
Zhongshui Zou ◽  
Dongliang Zhao ◽  
Yijun Hou
Keyword(s):  
Surface Roughness ◽  
Wind Wave ◽  
Wind Waves ◽  
Sea Surface ◽  
Wave Steepness ◽  
Threshold Behavior ◽  
Wind Speeds ◽  
Dominant Wave ◽  
Sea Surface Roughness ◽  
Mixed Wave

AbstractWind stress depends on the sea surface roughness, which can be significantly changed by surface wind waves. Based on observations from a fixed platform, we examined the dependences of the sea surface roughness length on dominant wave characteristic parameters (wave age, wave steepness) at moderate wind speeds and under mixed-wave conditions. No obvious trend was found in the wave steepness dependence of sea surface roughness, but a wave steepness threshold behavior was readily identified in the wave age dependence of sea surface roughness. The influence of dominant wind waves on the surface roughness was illustrated using a wind–wave coupling model. The wave steepness threshold behavior is assumed to be related to the onset of dominant wave breaking. The important role of the interaction between swell and wind wave was highlighted, as swell can absorb energy from locally generated wind wave, which subsequently reduces the wave steepness and the probability of dominant wave breaking.

scholarly journals The Impact of Atmosphere–Ocean–Wave Coupling on the Near-Surface Wind Speed in Forecasts of Extratropical Cyclones

2021 ◽  
Author(s):  
Emanuele S. Gentile ◽  
Suzanne L. Gray ◽  
Janet F. Barlow ◽  
Huw W. Lewis ◽  
John M. Edwards
Keyword(s):  
Wind Speed ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Sea Surface ◽  
Model Systems ◽  
Sea State ◽  
Near Surface ◽  
Extreme Surface ◽  
Wind Speeds ◽  
The Impact

AbstractAccurate modelling of air–sea surface exchanges is crucial for reliable extreme surface wind-speed forecasts. While atmosphere-only weather forecast models represent ocean and wave effects through sea-state independent parametrizations, coupled multi-model systems capture sea-state dynamics by integrating feedbacks between the atmosphere, ocean and wave model components. Here, we investigate the sensitivity of extreme surface wind speeds to air–sea exchanges at the kilometre scale using coupled and uncoupled configurations of the Met Office’s UK Regional Coupled Environmental Prediction system. The case period includes the passage of extra-tropical cyclones Helen, Ali, and Bronagh, which brought maximum gusts of 36 m s$$^{-1}$$ - 1 over the UK. Compared with the atmosphere-only results, coupling to the ocean decreases the domain-average sea-surface temperature by up to 0.5 K. Inclusion of coupling to waves reduce the 98th percentile 10-m wind speed by up to 2 m s$$^{-1}$$ - 1 as young, growing wind waves reduce the wind speed by increasing the sea-surface aerodynamic roughness. Impacts on gusts are more modest, with local reductions of up to 1 m s$$^{-1}$$ - 1 , due to enhanced boundary-layer turbulence which partially offsets air–sea momentum transfer. Using a new drag parametrization based on the Coupled Ocean–Atmosphere Response Experiment 4.0 parametrization, with a cap on the neutral drag coefficient and reduction for wind speeds exceeding 27 m s$$^{-1}$$ - 1 , the atmosphere-only model achieves equivalent impacts on 10-m wind speeds and gusts as from coupling to waves. Overall, the new drag parametrization achieves the same 20% improvement in forecast 10-m wind-speed skill as coupling to waves, with the advantage of saving the computational cost of the ocean and wave models.

scholarly journals Impact of Sea Spray and Sea Surface Roughness on the Upper Ocean Response to Super Typhoon Haitang (2005)

2021 ◽  
Author(s):  
Lianxin Zhang ◽  
Xuefeng Zhang ◽  
William Perrie ◽  
Changlong Guan ◽  
Bo Dan ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Ocean Waves ◽  
Sea Surface ◽  
Sea Spray ◽  
Upper Ocean ◽  
Surface Cooling ◽  
Super Typhoon ◽  
Sea Surface Roughness ◽  
Momentum Fluxes ◽  
The Right

AbstractA coupled ocean-wave-sea spray model system is used to investigate the impacts of sea spray and sea surface roughness on the response of the upper ocean to the passage of the super typhoon Haitang. Sea spray mediated heat and momentum fluxes are derived from an improved version of Fairall’s heat fluxes formulation (Zhang et al., 2017) and Andreas’s sea spray-mediated momentum flux models. For winds ranging from low to extremely high speeds, a new parameterization scheme for the sea surface roughness is developed, in which the effects of wave state and sea spray are introduced. In this formulation, the drag coefficient has minimal values over the right quadrant of the typhoon track, along which the typhoon-generated waves are longer, smoother, and older, compared to other quadrants. Using traditional interfacial air-sea turbulent (sensible, latent, and momentum) fluxes, the sea surface cooling response to typhoon Haitang is overestimated by 1 °C, which can be compensated by the effects of sea spray and ocean waves on the right side of the storm. Inclusion of sea spray-mediated turbulent fluxes and sea surface roughness, modulated by ocean waves, gives enhanced cooling along the left edges of the cooling area by 0.2 °C, consistent with the upper ocean temperature observations.

Passive Microwave Measurements Of Sea Surface Roughness During The Saxon Experiment

2005 ◽  
Author(s):  
G.D. Sandlin ◽  
L.A. Rose ◽  
G.L. Geernaert ◽  
J.P. Hollinger ◽  
F.A. Hansen
Keyword(s):  
Surface Roughness ◽  
Passive Microwave ◽  
Sea Surface ◽  
Microwave Measurements ◽  
Sea Surface Roughness

scholarly journals Monitoring Intense Oceanic Fronts Using Sea Surface Roughness: Satellite, Airplane, and In Situ Comparison

2020 ◽  
Vol 125 (8) ◽  
Author(s):  
Nicolas Rascle ◽  
Bertrand Chapron ◽  
Jeroen Molemaker ◽  
Frédéric Nouguier ◽  
Francisco J. Ocampo‐Torres ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Sea Surface ◽  
Oceanic Fronts ◽  
Sea Surface Roughness
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