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5 results on '"Earth and Space Research Institute [Seattle] (ESR)"'

1. Local-scale valley wind retrieval using an artificial neural network applied to routine weather observations

Author

Pierre Durand, Florian Dupuy, Eric R. Pardyjak, Thierry Hedde, Gert-Jan Duine, Pierre Roubin, CEA-Direction de l'Energie Nucléaire (CEA-DEN), Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Earth and Space Research Institute [Seattle] (ESR), CEA-Direction des Energies (ex-Direction de l'Energie Nucléaire) (CEA-DES (ex-DEN)), University of Utah, and CEA, Sud-PACA region, and Fulbright Scholarship Program are thanked for the financial support

Subjects
Atmospheric Science, Local effects, 010504 meteorology & atmospheric sciences, Artificial neural network, [PHYS.NUCL]Physics [physics]/Nuclear Theory [nucl-th], Computer science, 020209 energy, Orographic effects, Local scale, 02 engineering and technology, [PHYS.NEXP]Physics [physics]/Nuclear Experiment [nucl-ex], computer.software_genre, 01 natural sciences, Boundary layer, 0202 electrical engineering, electronic engineering, information engineering, Data mining, Wind retrieval, Valley-mountain flows, computer, Neural networks, 0105 earth and related environmental sciences
Abstract

We hereby present a new method with which to nowcast a thermally driven, downvalley wind using an artificial neural network (ANN) based on remote observations. The method allows the retrieval of wind speed and direction. The ANN was trained and evaluated using a 3-month winter-period dataset of routine weather observations made in and above the valley. The targeted valley winds feature two main directions (91% of the total dataset) that are aligned with the valley axis. They result from downward momentum transport, channeling mechanisms, and thermally driven flows. A selection procedure of the most pertinent ANN input variables, among the routine observations, highlighted three key variables: a potential temperature difference between the top and the bottom of the valley and the two wind components above the valley. These variables are directly related to the mechanisms that generate the valley winds. The performance of the ANN method improves on an earlier-proposed nowcasting method, based solely on a vertical temperature difference, as well as a multilinear regression model. The assessment of the wind speed and direction indicates good performance (i.e., wind speed bias of −0.28 m s−1 and 84% of calculated directions stray from observations by less than 45°). Major sources of error are due to the misrepresentation of cross-valley winds and very light winds. The validated method was then successfully applied to a 1-yr period with a similar performance. Potentially, this method could be used to downscale valley wind characteristics for unresolved valleys in mesoscale simulations.

Published
2018
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2. Satellite and In Situ Salinity: Understanding Near-Surface Stratification and Subfootprint Variability

Author

Ludovic Brucker, Andrea Santos-Garcia, Tong Lee, Jacqueline Boutin, Alexander Soloviev, Emmanuel P. Dinnat, Brian Ward, Wenqing Tang, Nicolas Reul, William E. Asher, Nadya T. Vinogradova, Nicolas Kolodziejczyk, Julian Schanze, Kyla Drushka, Jessica Anderson, Thomas Meissner, Yi Chao, Christophe Maes, Thierry Delcroix, W.L. Jones, R. Drucker, Lisan Yu, Gilles Reverdin, Interactions et Processus au sein de la couche de Surface Océanique (IPSO), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), UCLA Joint Institute for Regional Earth System Science and Engineering (JIFRESSE), University of California [Los Angeles] (UCLA), University of California-University of California-NASA, Remote Sensing Solutions, University of Washington [Seattle], Laboratoire d'études en Géophysique et océanographie spatiales (LEGOS), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS), School of Oceanography [Seattle], Jet Propulsion Laboratory (JPL), NASA-California Institute of Technology (CALTECH), Ifremer, Centre de Toulon, Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER), Earth and Space Research Institute [Seattle] (ESR), Nova Southeastern University (NSU), Woods Hole Oceanographic Institution (WHOI), Universities Space Research Association (USRA), GSFC Cryospheric Sciences Laboratory, NASA Goddard Space Flight Center (GSFC), Electrical and Computer Engineering Department [Orlando], University of Central Florida [Orlando] (UCF), Laboratoire de physique des océans (LPO), Institut de Recherche pour le Développement (IRD)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS), Remote Sensing Systems [Santa Rosa] (RSS), Atmospheric and Environmental Research, Inc. (AER), National University of Ireland [Galway] (NUI Galway), CNES, Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), University of California (UC)-University of California (UC)-NASA, Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), and Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)

Subjects
Atmospheric Science, 010504 meteorology & atmospheric sciences, 0211 other engineering and technologies, Mesoscale meteorology, Stratification (water), 02 engineering and technology, [SDU.STU.ME]Sciences of the Universe [physics]/Earth Sciences/Meteorology, Atmospheric sciences, 01 natural sciences, western equatorial pacific, barrier layer, tropical oceans, north-atlantic, ocean salinity, 14. Life underwater, Water cycle, [SDU.STU.OC]Sciences of the Universe [physics]/Earth Sciences/Oceanography, 021101 geological & geomatics engineering, 0105 earth and related environmental sciences, Remote sensing, Radiometer, boundary-layer, pacific warm pool, Salinity, Ocean dynamics, band radiometer/scatterometer observations, 13. Climate action, polar-regions, air-sea interaction, Environmental science, Satellite, Microwave
Abstract

Remote sensing of salinity using satellite-mounted microwave radiometers provides new perspectives for studying ocean dynamics and the global hydrological cycle. Calibration and validation of these measurements is challenging because satellite and in situ methods measure salinity differently. Microwave radiometers measure the salinity in the top few centimeters of the ocean, whereas most in situ observations are reported below a depth of a few meters. Additionally, satellites measure salinity as a spatial average over an area of about 100 × 100 km2. In contrast, in situ sensors provide pointwise measurements at the location of the sensor. Thus, the presence of vertical gradients in, and horizontal variability of, sea surface salinity complicates comparison of satellite and in situ measurements. This paper synthesizes present knowledge of the magnitude and the processes that contribute to the formation and evolution of vertical and horizontal variability in near-surface salinity. Rainfall, freshwater plumes, and evaporation can generate vertical gradients of salinity, and in some cases these gradients can be large enough to affect validation of satellite measurements. Similarly, mesoscale to submesoscale processes can lead to horizontal variability that can also affect comparisons of satellite data to in situ data. Comparisons between satellite and in situ salinity measurements must take into account both vertical stratification and horizontal variability.

Published
2016
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3. Bivariate Empirical Mode Decomposition

Author

Patrick Flandrin, P. Gonalves, Jonathan M. Lilly, Gabriel Rilling, Laboratoire de Physique de l'ENS Lyon (Phys-ENS), École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), Laboratoire de l'Informatique du Parallélisme (LIP), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS), Earth and Space Research Institute [Seattle] (ESR), École normale supérieure - Lyon (ENS Lyon)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon, École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL), Flandrin, Patrick, and Gonçalves, Paulo

Subjects
Bivariate time series, Mathematical optimization, [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing, 02 engineering and technology, Bivariate analysis, Hilbert–Huang transform, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, 0202 electrical engineering, electronic engineering, information engineering, Applied mathematics, Electrical and Electronic Engineering, MATLAB, ComputingMilieux_MISCELLANEOUS, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing, Mathematics, computer.programming_language, Signal processing, Complex-valued signals, Series (mathematics), Applied Mathematics, SIGNAL (programming language), 020206 networking & telecommunications, Extension (predicate logic), Nonlinear system, Signal Processing, Empirical Mode Decomposition, 020201 artificial intelligence & image processing, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, computer
Abstract

10 pages, 3 figures. Submitted to Signal Processing Letters, IEEE. Matlab/C codes and additional material are downloadable from http://perso.ens-lyon.fr/patrick.flandrin; The Empirical Mode Decomposition (EMD) has been introduced quite recently to adaptively decompose nonstationary and/or nonlinear time series. The method being initially limited to real-valued time series, we propose here an extension to bivariate (or complex-valued) time series which generalizes the rationale underlying the EMD to the bivariate framework. Where the EMD extracts zero-mean oscillating components, the proposed bivariate extension is designed to extract zero-mean rotating components. The method is illustrated on a real-world signal and properties of the output components are discussed. Free Matlab/C codes are available at http://perso.ens-lyon.fr/patrick.flandrin.

Published
2007
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4. Wavelet ridge diagnosis of time-varying elliptical signals with application to an oceanic eddy

Author

Jonathan M. Lilly, Jean-Claude Gascard, Earth and Space Research Institute [Seattle] (ESR), Laboratoire d'océanographie dynamique et de climatologie (LODYC), and Institut de Recherche pour le Développement (IRD)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)

Subjects
010504 meteorology & atmospheric sciences, [SDU.STU]Sciences of the Universe [physics]/Earth Sciences, [PHYS.PHYS.PHYS-GEO-PH]Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph], 02 engineering and technology, Ellipse, 01 natural sciences, Instantaneous phase, [PHYS.ASTR.CO]Physics [physics]/Astrophysics [astro-ph]/Cosmology and Extra-Galactic Astrophysics [astro-ph.CO], Wavelet, Control theory, Position (vector), 0202 electrical engineering, electronic engineering, information engineering, Elliptic integral, lcsh:Science, 0105 earth and related environmental sciences, Mathematics, Series (mathematics), [SDU.ASTR]Sciences of the Universe [physics]/Astrophysics [astro-ph], Mathematical analysis, lcsh:QC801-809, 020206 networking & telecommunications, Ridge (differential geometry), lcsh:QC1-999, lcsh:Geophysics. Cosmic physics, Orbital motion, lcsh:Q, lcsh:Physics
Abstract

A method for diagnosing the physical properties of a time-varying ellipse is presented. This essentially involves extending the notion of instantaneous frequency to the bivariate case. New complications, and possibilities, arise from the fact that there are several meaningful forms in which a time-varying ellipse may be represented. A perturbation analysis valid for the near-circular case clarifies these issues. Diagnosis of the ellipse properties may then be performed using wavelet ridge analysis, and slowly-varying changes in the ellipse structure may be decoupled from the fast orbital motion through the use of elliptic integrals, without the need for additional explicit filtering. The theory is presented in parallel with an application to a position time series of a drifting subsurface float trapped in an oceanic eddy.

Published
2006
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5. SMOS: a satellite mission to measure ocean surface salinity

Author

Meric Srokosz, J. Etcheto, Yann Kerr, Adriano Camps, Jordi Font, Gary Lagerloef, Philippe Waldteufel, Institute of Marine Sciences / Institut de Ciències del Mar [Barcelona] (ICM), Consejo Superior de Investigaciones Científicas [Madrid] (CSIC), Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), National Oceanography Centre [Southampton] (NOC), University of Southampton, Université Pierre et Marie Curie - Paris 6 (UPMC), Earth and Space Research Institute [Seattle] (ESR), Universitat Politècnica de Catalunya [Barcelona] (UPC), Service d'aéronomie (SA), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), John D. Gonglewski, Gary W. Kamerman, Anton Kohnle, Ulrich Schreiber, Christian H. Werner (Eds.), Centre d'étude des environnements terrestre et planétaires (CETP), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions, Universitat Politècnica de Catalunya. RSLAB - Grup de Recerca en Teledetecció, Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), and Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)

Subjects
L band, 010504 meteorology & atmospheric sciences, Meteorology, Satellites, 0211 other engineering and technologies, Cosmic background radiation, 02 engineering and technology, Physical oceanography, 01 natural sciences, Telecomunicació, Surface roughness, 14. Life underwater, 021101 geological & geomatics engineering, 0105 earth and related environmental sciences, Remote sensing, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, [PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph], Radiation, Interferometers, Enginyeria de la telecomunicació [Àrees temàtiques de la UPC], Salinity, Geography, Brightness temperature, Telecommunication, Radiometry, Satellite
Abstract

International audience; The ESA's SMOS (Soil Moisture and Ocean Salinity) Earth Explorer Opportunity Mission will be launched by 2005. Its baseline payload is a microwave L-band (21 cm, 1.4 GHz) 2D interferometric radiometer, Y shaped, with three arms 4.5 m long. This frequency allows the measurement of brightness temperature (Tb) under the best conditions to retrieve soil moisture and sea surface salinity (SSS). Unlike other oceanographic variables, until now it has not been possible to measure salinity from space. However, large ocean areas lack significant salinity measurements. The 2D interferometer will measure Tb at large and different incidence angles, for two polarizations. It is possible to obtain SSS from L-band passive microwave measurements if the other factors influencing Tb (SST, surface roughness, foam, sun glint, rain, ionospheric effects and galactic/cosmic background radiation) can be accounted for. Since the radiometric sensitivity is low, SSS cannot be recovered to the required accuracy from a single measurement as the error is about 1-2 psu. If the errors contributing to the uncertainty in Tb are random, averaging the independent data and views along the track, and considering a 200 km square, allow the error to be reduced to 0.1-0.2 pus, assuming all ancillary errors are budgeted.

Published
2000
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