Measuring currents, ice drift, and waves from space: the Sea Surface KInematics Multiscale monitoring (SKIM) concept

We propose a new satellite mission that uses a near-nadir Ka-band Doppler radar to measure surface currents, ice drift and ocean waves at spatial scales of 40?km and more, with snapshots at least every day for latitudes 75 to 82, and every few days otherwise. The use of incidence angles at 6 and 12 degrees allows a measurement of the directional wave spectrum which yields accurate corrections of the wave-induced bias in the current measurements. The instrument principle, algorithm for current velocity and mission performance are presented here. The proposed instrument can reveal features on tropical ocean and marginal ice zone dynamics that are inaccessible to other measurement systems, as well as a global monitoring of the ocean mesoscale that surpasses the capability of today?s nadir altimeters. Measuring ocean wave properties facilitates many applications, from wave-current interactions and air-sea fluxes to the transport and convergence of marine plastic debris and assessment of marine and coastal hazards

ETUDE DES PROPRIETES OPTIQUES ET MICROPHYSIQUES DE NUAGES ELEVES PAR TELEDETECTION LIDAR ET SATELLITAIRE

RENNES1-BU Sciences Philo (352382102) / SudocSudocFranceF

Weather types prediction at medium-range from ensemble forecasts

International audienceMedium-range weather forecasts can be ofhigh economic value in many fields: agriculture, renewableenergy production, maintenance operations planning.Such forecasts can be based on ensembles derivedfrom weather models, and the postprocessing of suchensembles is an active research problem in the statisticalweather community. In this work, we try to face theproblem of long forecasting horizons, and focus on themultivariate case where different meteorological variablesinteract. The prediction problem is simplified and definedas the prediction of a weather type, which is a categoricalvariable defined by the interaction of the meteorologicalvariables. We use machine learning techniques to predictthis weather type from the multivariate ensembleforecasts. The algorithms are applied to a 5 to 10 daysweather forecasting in the north-west of France, based onwind and precipitation data from the ECMWF ensemblesystem

Weather types prediction at medium-range from ensemble forecasts

International audienceMedium-range weather forecasts can be ofhigh economic value in many fields: agriculture, renewableenergy production, maintenance operations planning.Such forecasts can be based on ensembles derivedfrom weather models, and the postprocessing of suchensembles is an active research problem in the statisticalweather community. In this work, we try to face theproblem of long forecasting horizons, and focus on themultivariate case where different meteorological variablesinteract. The prediction problem is simplified and definedas the prediction of a weather type, which is a categoricalvariable defined by the interaction of the meteorologicalvariables. We use machine learning techniques to predictthis weather type from the multivariate ensembleforecasts. The algorithms are applied to a 5 to 10 daysweather forecasting in the north-west of France, based onwind and precipitation data from the ECMWF ensemblesystem

Gaussian mixture models for clustering and calibration of ensemble weather forecasts

International audienceNowadays, most weather forecasting centers produce ensemble forecasts. Ensemble forecasts provide information about probability distribution of the weather variables. They give a more complete description of the atmosphere than a unique run of the meteorological model. However, they may suffer from bias and under/over dispersion errors that need to be corrected. These distribution errors may depend on weather regimes. In this paper, we propose various extensions of the Gaussian mixture model and its associated inference tools for ensemble data sets. The proposed models are then used to identify clusters which correspond to different types of distribution errors. Finally, a standard calibration method known as Non homogeneous Gaussian Regression (NGR) is applied cluster by cluster in order to correct ensemble forecast distributions. It is shown that the proposed methodology is effective, interpretable and easy to use. The clustering algorithms are illustrated on simulated and real data. The calibration method is applied to real data of temperature and wind medium range forecast for 3 stations in France.</p

Measuring ocean total surface current velocity with the KuROS and KaRADOC airborne near-nadir Doppler radars: a multi-scale analysis in preparation for the SKIM mission

International audienceSurface currents are poorly known over most of the oceans. Satellite-borne Doppler Waves and Current Scatterom-eters (DWCS) can be used to fill this observation gap. The Sea surface KInematics Multiscale (SKIM) proposal, is the first satellite concept built on a DWCS design at near-nadir angles, and now one of the two candidates to become the 9th mission of the European Space Agency Earth Explorer program. As part of the detailed design and feasibility studies (phase A) funded by ESA, airborne measurements were carried out with both a Ku-Band and a Ka-Band Doppler radars looking at the sea surface at 5 near nadir-incidence in a real-aperture mode, i.e. in a geometry and mode similar to that of SKIM. The airborne radar KuROS was deployed to provide simultaneous measurements of the radar backscatter and Doppler velocity, in a side-looking configuration , with an horizontal resolution of about 5 to 10 m along the line of sight and integrated in the perpendicular direction over the real-aperture 3-dB footprint diameter (about 580 m). The KaRADOC system has a much narrower beam, with a circular footprint only 45 m in diameter. 10 The experiment took place in November 2018 off the French Atlantic coast, with sea states representative of the open ocean and a well known tide-dominated current regime. The data set is analyzed to explore the contribution of non-geophysical velocities to the measurement and how the geophysical part of the measured velocity combines wave-resolved and wave-averaged scales. We find that the measured Doppler velocity contains a characteristic wave phase speed, called here C 0 that is analogous to the Bragg phase speed of coastal High Frequency radars that use a grazing measurement geometry, with little 15 variations ∆ C associated to changes in sea state. The Ka-band measurements at an incidence of 12 • are 10% lower than the theoretical estimate C 0 2.4 m/s for typical oceanic conditions defined by a wind speed of 7 m/s and a significant wave height of 2 m. For Ku-band the measured data is 1 https://doi. 30% lower than the theoretical estimate 2.8 m/s. ∆ C is of the order of 0.2 m/s for a 1 m change in wave height, and cannot be confused with a 1 m/s change in tidal current. The actual measurement of the current velocity from an aircraft at 4 to 18 • incidence angle is, however, made difficult by uncertainties on the measurement geometry, which are much reduced in satellite measurements

Measuring currents, ice drift, and waves from space: the Sea surface KInematics Multiscale monitoring (SKIM) concept

We propose a satellite mission that uses a near-nadir Ka-band Doppler radar to measure surface currents, ice drift and ocean waves at spatial scales of 40 km and more, with snapshots at least every day for latitudes 75 to 82°, and every few days for other latitudes. The use of incidence angles of 6 and 12° allows for measurement of the directional wave spectrum, which yields accurate corrections of the wave-induced bias in the current measurements. The instrument's design, an algorithm for current vector retrieval and the expected mission performance are presented here. The instrument proposed can reveal features of tropical ocean and marginal ice zone (MIZ) dynamics that are inaccessible to other measurement systems, and providing global monitoring of the ocean mesoscale that surpasses the capability of today's nadir altimeters. Measuring ocean wave properties has many applications, including examining wave–current interactions, air–sea fluxes, the transport and convergence of marine plastic debris and assessment of marine and coastal hazards