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Coupling Atmospheric Dynamics and Ocean with Winds from Satellites
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An accurate description of air-sea interaction in atmospheric, ocean and coupled models remains problematic due to unresolved processes in atmospheric models. Systematic differences in winds occur (amongst others) due to undetermined geophysical dependencies. Systematic model errors in ocean winds found on large scale and atmospheric mesoscale propagate to the ocean circulation when used to force ocean models and affect coupled earth system dynamics. Geolocated scatterometer-based corrections of wind forcing products already successfully correct for local wind vector biases, but this correction method is highly dependent on sampling. The growing virtual scatterometer constellation is very promising to better capture the detailed forcing errors over the day.  Biases of the order of 0.5m/s in wind speed can introduce a large bias in wind stress, causing significant errors in ocean–atmosphere coupling and climate prediction.Our focus is on unresolved processes in atmospheric Numerical Weather Prediction (NWP) models, namely systematic errors in boundary layer parameterizations such as lack of ocean currents and/or other biases that persist over time. An improved representation of surface turbulent fluxes relies on better estimates of: the roughness length, the stability function, the sea skin temperature, ocean currents and convective gustiness. The goal is to apply model bias reduction schemes with respect to scatterometer winds. Consistent scatterometer corrections will lead to an improved understanding of the coupled atmospheric and oceanic model dynamical processes in the evolving earth system. In addition, corrected model winds reduce errors in ocean forcing and will be helpful in scatterometer data assimilation.
Title: Coupling Atmospheric Dynamics and Ocean with Winds from Satellites
Description:
An accurate description of air-sea interaction in atmospheric, ocean and coupled models remains problematic due to unresolved processes in atmospheric models.
Systematic differences in winds occur (amongst others) due to undetermined geophysical dependencies.
Systematic model errors in ocean winds found on large scale and atmospheric mesoscale propagate to the ocean circulation when used to force ocean models and affect coupled earth system dynamics.
 Geolocated scatterometer-based corrections of wind forcing products already successfully correct for local wind vector biases, but this correction method is highly dependent on sampling.
The growing virtual scatterometer constellation is very promising to better capture the detailed forcing errors over the day.
 Biases of the order of 0.
5m/s in wind speed can introduce a large bias in wind stress, causing significant errors in ocean–atmosphere coupling and climate prediction.
Our focus is on unresolved processes in atmospheric Numerical Weather Prediction (NWP) models, namely systematic errors in boundary layer parameterizations such as lack of ocean currents and/or other biases that persist over time.
An improved representation of surface turbulent fluxes relies on better estimates of: the roughness length, the stability function, the sea skin temperature, ocean currents and convective gustiness.
 The goal is to apply model bias reduction schemes with respect to scatterometer winds.
Consistent scatterometer corrections will lead to an improved understanding of the coupled atmospheric and oceanic model dynamical processes in the evolving earth system.
In addition, corrected model winds reduce errors in ocean forcing and will be helpful in scatterometer data assimilation.
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