Strong winds in a coupled wave-atmosphere model during a North - - PowerPoint PPT Presentation

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Strong winds in a coupled wave-atmosphere model during a North Atlantic storm event: evaluation against observations

Lucia Pineau-Guillou (Ifremer/LOPS), Fabrice Ardhuin, Marie-Noëlle Bouin, Jean-Luc Redelsperger, Bertrand Chapron, Jean Bidlot (ECMWF), Yves Quilfen AMS 21st Conference on Air-Sea Interaction, 11-15 June 2018, Oklahoma City

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• 1. Introduction
• 2. Case study: storm description
• 3. Model & observations
• 4. Comparison between simulated winds & observations
• 5. Sensitivity to wind stress parameterization
• 6. Conclusions

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• 1. Introduction
• Motivations

➔ Underestimation of large wave heights in wave models (up to 15% Rascle & Ardhuin, 2013),

as well as storm surges in ocean models (Muller et al., 2014)

➔ Could be partly due to: ➔ underestimation of strong winds in atmospheric models ➔ inappropriate representation of wind stress in numerical models

• Objectives

1) Evaluate strong winds against observations (buoys, platforms & satellites) 2) Test how alternative wind stress parameterizations could reduce the bias and lead to a more accurate model

• Method

➔ Use of ECMWF Integrated Forecasting System (IFS CY41R1), which provides a drag as a

function of the sea state

➔ Numerical simulation of two extratropical storms

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• 2. Case study: storm description
• Event selection : analysis of ERA-Interim database over the last 10 years (2005-2015) of North

East Atlantic (30°W 10°E 30°N 65°N)

• 10 more energetic events classified
• Kaat and Lilli storms, which crossed the North Atlantic in January 2014

Kaat and Lilli storm tracks In black dotted line, principal tracks from Hoskins and Hodges (2002)

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• 3. Model & observations
• Model: ECMWF atmosphere model IFS coupled with ECWAM (cycle CY41R1), simulations

without data assimilation

• Wind measurements

Buoys and platforms come from GTS. Correction to 10m based on a logarithmic law.

scatterometers radiometers altimeter 20 buoys 59 platforms

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Wind measurements

• 3. Model & observations

Wind field on 26 January 2014 estimated from ASCAT-KNMI Metop-A (a), ASCAT-RSS Metop-A (b), AMSR2 (c), WindSat (d) for descending passes, and for SMOS (e) and JASON-2 (f) ASCAT winds from RSS (right) stronger than those from KNMI (left)

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Wind biases

Negative bias, except for ASCAT-KNMI and buoys

• 4. Comparison between simulated winds

and observations

Wind correlations from 23 to 27 of January 2014 between default ECMWF parameterization (CY41R1) and ASCAT-KNMI (a), ASCAT-RSS (b), AMSR2 (c), WindSat (d), SMOS (e), JASON-2 (f), buoys (g) and platforms (h)

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Wind biases

• 4. Comparison between simulated winds

and observations

5-20 m/s good agreement Group 1 : ASCAT-KNMI/buoys 20-40 m/s underestimation

• Strong winds are generally underestimated compared with observations
• Biases exist between observations: group 1 gives lower strong winds than group 2
• Difficult to conclude which dataset should be used as a reference

Group 2 : satellites (except ASCAT-KNMI)/platforms

7 m/s

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• 5. Sensitivity to wind stress parameterization

[1] Default ECMWF parameterization (CY41R1) Janssen (1991) Effect of wave through roughness length [2] WW3 physics β given by Ardhuin et al. (2010) and E(f,θ) influenced by a different dissipation term [3] Wave age dependent parameterization given by Oost et al. (2002) [4] Empirically-adjusted Charnock parameterization To obtain a maximum Cd of 2.5 10-3 for wind speed around 30 m/s [5] Constant Charnock 0.018

z0wave= z1

√1− τw

τ

α=50 ξ

−2.5

ξ=C p/u*

with wave age

⃗ τ w=g∫

∞

⃗ k∫

2 π

β (f,θ ) E (f,θ )/(2πf )dfdθ

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• 5. Sensitivity to wind stress parameterization

[1] Default ECMWF parameterization [1] Default ECMWF parameterization

(CY41R1)

[5] Empirically-adjusted Charnock parameterization Drag values more consistent with observations

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• 5. Sensitivity to wind stress parameterization

The wave age formulation gives too high drag values (due to unrealistic extrapolation to high winds of a relation based on winds 6-18 m/s)

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Results

• 5. Sensitivity to wind stress parameterization

Larger Charnock → larger z0, higher Cd and stress and lower wind Wave age parameterization New parameterization reduces the wind bias ~2 m/s at 30 m/s

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• Moderate simulated winds (5-20 m/s) match well with observations
• For strong winds, mean differences appear as much as -7 m/s at 30 m/s
• Significant differences also exist between observations

➔ Buoys and ASCAT winds generally lower than platforms and other remote sensing

data (AMSR2, ASCAT-RSS, WindSat, SMOS and Jason-2)

➔ Difficult to conclude which dataset should be used as a reference ➔ However, buoy and ASCAT-KNMI are likely to underestimate the real wind

• Concerning parameterizations

➔ Wave age not appropriate for coupling ➔ New parameterization leads to higher winds

• To go further: looking at the ocean response through storm surges in the North Sea
• 6. Conclusions