a new climatology of sea surface wind speed under...

A NEW CLIMATOLOGY OF SEA SURFACE WIND SPEED UNDER CLOUD‐FREECONDITIONS FOR THE ESTIMATION OF THE IMPACT OF SUNGLINT IN GMES

PHASE‐A SENTINEL‐3

Mounir Lekouara1, Bernardo Carnicero Dominguez2 and Miguel Aguirre2

1 National Oceanography Centre, Southampton, UK2 EO Future missions, ESTEC-ESA, Noordwijk, The Netherlands

MERIS L2 RR15/07/2003 10h01

pink : medium_glint/high_glintyellow: haze

Introduction

Sun glint: specular reflection of sun light by suitably tilted facets of the water surface into the sensor

Extent and radiance of sunglint = f (imaging geometry , surface roughness)

= f (lat, time)

= f (lat, time)

≈ f ( surface wind speed )

To be significative, sun glint needs moderate to high winds

MERIS L2 products: detection and correction for ocean pixels that are contaminated by sunglint, are based on the Cox‐Munk model (1954). It uses external knowledge of the wind speed and direction, the illumination and observation geometry.

Traditionally coverage taking into account sun‐glint has been estimated using a constant value of wind speed (typically 7.5 m/s) identical for the whole Earth and for the whole year.

Introduction

Optical instruments do not see through clouds.

For any optical mission, we need an estimation of the value of the surface wind speed under cloud free conditions for

• the global determination of the impact of wind speed in the sun glint extent

• the proper, accurate, and optimum coverage estimation and design of the mission and instruments

We expect a lower value of wind speed to simulate the sun glint, looking at cloud‐free areas.

Phase‐A Sentinel‐3 benefit from the outputs of this study by decreasing the degree of uncertainty on this topic.

The study should replace the 7.5 m/s value with

spatial / temporal climatology of wind speedwind speed under cloud‐free conditions

Introduction

MERIS L2 Reduced Resolution

The entire MERIS_RR_2 archive is accessed and processed using the Grid Processing on Demand Services and Architecture in ESRIN.

Archives and Computational Capabilities

The whole archive until April 20075 years from May 2002 to April 2007

Cloud CoverageMERIS L2 cloud flag, 1.2 km resolution

Instantaneous Wind SpeedECMWF analysis, auxiliary data, 19.2 km resolution

Data set

G‐POD

Climatology of wind speed under all type of cloud conditions

ESMWF wind speed (m/s)

Global monthly average wind speed varies from 1‐2 m/s up to 15 m/s

Climatology of wind speed under cloud and haze free conditions


Global monthly average wind speed varies from 1‐2 m/s up to 15 m/s

Wind speed selection for sun‐glint extent estimation.

First level of precision: global wind speed value

Mean Wind Speed Standard deviation

up to now 7.5 m/s

global value from the study 7.15 m/s 3.38 m/s

global value from the study UNDER

CLOUD_HAZE FREE CONDITIONS

6.72 m/s 3.22 m/s

Second level of precision: Average wind speed over latitudinal bands


Monthly averaged wind speed under cloud free conditions appears to be lower than in all kind of cloud conditions from 50 south to 50 North



Third level of precision: 50x50 km monthly averaged wind speed under cloud_haze_free conditions


A coverage analysis is carried out, based on • real wind speed data (cloud free conditions)• satellite/ Sun geometry simulations• Cox‐Munk model

Estimation of the phase-A Sentinel 3 swath decrease sensitivity to wind speed Equator, September 21WS = 7 m/sWS= 6 m/sWS= 5 m/s


Coverage simulations forPhase‐A Sentinel‐3

Satellite/Sun geometry

Real WS data

+

Cox-Munk model

geometrical coverage simulations for Sentinel‐3

Number of valid observations per month


Effective coverage simulations for Sentinel‐3: (clouds + sun glint)

×


Conclusions

A new climatology of global ocean wind speed under cloud free and all kind of cloud conditions has been processed.

This can be used for:

Improvement of accuracy on the estimation of sun glint extent impact during the early definition of Remote Sensing ocean optical instruments and missions.

Improvement on the worldwide estimation the coverage taking into account sun glint and clouds.

Early assessment on temporal expected distribution of products.

More accurate information to optimize instrument and mission design during the very early project phases

Acknowledgments

We would like to thank

• the G‐POD team in ESRIN, in particular to Olivier Colin, Miguel Angel Rubioand Emmanuel Mathot for providing us with a well‐appreciated amount of support and flexibility.

• Marc Bouvet, Jean‐Paul Huot, Steven Delwart, and Jean‐Loup Bézy for their consistent support and expertise on a wide range of technical aspects.

THANK YOU

a new climatology of sea surface wind speed under...

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