Faraday Rotation David Le Vine Aquarius Algorithm Workshop March 9-11, 2010.

Slides:

Advertisements

Similar presentations

F. Wentz, T. Meissner, J. Scott and K. Hilburn Remote Sensing Systems 2014 Aquarius / SAC-D Science Team Meeting November ,

Advertisements

SMOS L2 Ocean Salinity Level 2 Ocean Salinity Using TEC estimated from Stokes 3 24 October 2012 ACRI-st, LOCEAN & ARGANS SMOS+polarimetry.

1 © ACRI-ST, all rights reserved – 2012 TEC estimation Jean-Luc Vergely (ACRI-ST) Jacqueline Boutin (LOCEAN)

On Estimation of Soil Moisture & Snow Properties with SAR Jiancheng Shi Institute for Computational Earth System Science University of California, Santa.

Aquarius Status Salinity Retrieval and Applications D. M. Le Vine NASA/GSFC, Greenbelt, MD E. P. Dinnat, G. Lagerloef, P. de Matthaeis, H. Kao, F.

The Aquarius Salinity Retrieval Algorithm Frank J. Wentz and Thomas Meissner, Remote Sensing Systems Gary S. Lagerloef, Earth and Space Research David.

1 Analysis of Airborne Microwave Polarimetric Radiometer Measurements in the Presence of Dynamic Platform Attitude Errors Jean Yves Kabore Central Florida.

Sea water dielectric constant, temperature and remote sensing of Sea Surface Salinity E. P. Dinnat 1,2, D. M. Le Vine 1, J. Boutin 3, X. Yin 3, 1 Cryospheric.

ATS 351 Lecture 8 Satellites

Aquarius/SAC-D Mission Mission Simulators - Gary Lagerloef 6 th Science Meeting; Seattle, WA, USA July 2010.

Aquarius/SAC-D Mission Error Validation and Early Orbit Corrections Gary Lagerloef 6 th Science Meeting; Seattle, WA, USA July 2010.

This poster concerns the on-orbit validation of the antenna beam pointing and corresponding instantaneous field of view (IFOV) earth location for the CONAE.

Polarimetric Radiometer and Scatterometer Measurements Simon H. Yueh Jet Propulsion Laboratory Operational SVW Requirement Workshop, Miami 7 June 2006.

Aquarius Algorithm Meeting To Do Lists. From Frank Wentz:  Implement Ruf RFI flagging  Implement other QC flags  Further test review, and finalize.

MWR Roughness Correction Algorithm for the Aquarius SSS Retrieval W. Linwood Jones, Yazan Hejazin, Salem Al-Nimri Central Florida Remote Sensing Lab University.

Experiments with the microwave emissivity model concerning the brightness temperature observation error & SSM/I evaluation Henning Wilker, MIUB Matthias.

Introduction Knowledge of the snow microstructure (correct a priori parameterization of grain size) is relevant for successful retrieval of snow parameters.

ECE 1100: Introduction to Electrical and Computer Engineering David R. Jackson Professor, ECE Dept. Notes 12 Antennas Spring 2008.

SMOS Science Workshop, Arles, th Sept, 2011 IMPROVING SMOS SALINITY RETRIEVAL: SYSTEMATIC ERROR DIAGNOSTIC J. Gourrion, R. Sabia, M. Portabella,

Remote Sensing Microwave Remote Sensing. 1. Passive Microwave Sensors ► Microwave emission is related to temperature and emissivity ► Microwave radiometers.

IGARSS’11 Compact Polarimetry Potentials My-Linh Truong-Loï, Jet Propulsion Laboratory / California Institue of Technology Eric Pottier, IETR, UMR CNRS.

SAR Contributions to Ship Detection and Characterization J.K.E. Tunaley London Research and Development Corporation, 114 Margaret Anne Drive, Ottawa, Ontario.

Aquarius Algorithm Workshop March 2007 College of Engineering Department of Atmospheric, Oceanic & Space Sciences Chris Ruf Space Physics Research.

SMOS+ STORM Evolution Kick-off Meeting, 2 April 2014 SOLab work description Zabolotskikh E., Kudryavtsev V.

Pang-Wei Liu 1, Roger De Roo 2, Anthony England 2,3, Jasmeet Judge 1 1. Center for Remote Sensing, Agri. and Bio. Engineering, U. of Florida 2. Atmosphere,

Calibration and Validation Studies for Aquarius Salinity Retrieval PI: Shannon Brown Co-Is: Shailen Desai and Anthony Scodary Jet Propulsion Laboratory,

Boundary layer temperature profile observations using ground-based microwave radiometers Bernhard Pospichal, ISARS 2006 Garmisch-Partenkirchen AMMA - Benin.

SCIENCE PROCESSING OVERVIEW David Le Vine Aquarius Deputy PI 07 July 2009.

7 th SMOS Workshop, Frascati, October /17 AMIRAS campaign Fernando Martin-Porqueras.

APPLICATIONS OF THE INTEGRAL EQUATION MODEL IN MICROWAVE REMOTE SENSING OF LAND SURFACE PARAMETERS In Honor of Prof. Adrian K. Fung Kun-Shan Chen National.

SMOS L2 Ocean Salinity Level 2 Ocean Salinity PM # November 2010 ARGANS & L2OS LOCEAN, Paris.

PASSIVE MICROWAVE TECHNIQUES FOR HYDROLOGICAL APPLICATIONS by : P. Ferrazzoli Tor Vergata University Roma, Italy

Microwave Engineering, 3rd Edition by David M. Pozar Copyright © 2004 John Wiley & Sons Figure 13.1 (p. 634) Photograph of various millimeter wave antennas.

Level 2 Algorithm. Definition of Product Levels LevelDescription Level 1 1A Reconstructed unprocessed instrument data 1B Geolocated, calibrated sensor.

Space Reflecto, November 4 th -5 th 2013, Plouzané Characterization of scattered celestial signals in SMOS observations over the Ocean J. Gourrion 1, J.

Remote Sensing Microwave Image. 1. Penetration of Radar Signal ► ► Radar signals are able to penetrate some solid features, e.g. soil surface and vegetative.

2011 IEEE International Geoscience And Remote Sensing Symposium IGARSS’11  July 24-29, 2011  Vancouver, C ANADA A synergy between SMOS & AQUARIUS: resampling.

Sea Surface Salinity from Space Simulation of Aquarius brightness temperature, Tb, at spacecraft during one orbit Top Panel –Ground track (red) –Outer.

USING SMOS POLARIMETRIC BRIGHTNESS TEMPERATURES TO CORRECT FOR ROUGH SURFACE EMISSION BEFORE SALINITY INVERSION.

Workshop Agenda: Day One 9:30 IntroductionLagerloef / Le Vine 9:45 Workshop objectivesG. Feldman 10:00 Overview of the Aquarius Data Processing System:G.

NPOESS Conical Scanning Microwave Imager/ Sounder (CMIS) Overview

Design Features of a Boresighted GPM Core Radiometer Christopher S. Ruf Dept. of Atmospheric, Oceanic & Space Sciences University of Michigan, Ann Arbor,

Radiometer Physics GmbH

Simulator Wish-List Gary Lagerloef Aquarius Principal Investigator Cal/Val/Algorithm Workshop March GSFC.

Mission Operations Review February 8-10, 2010 Cordoba, ARGENTINA SECTION 16.x Aquarius Science Commissioning and Acceptance Draft 2 Prepared by: Gary Lagerloef,

Use of AMSR-E Land Parameter Modeling and Retrievals for SMAP Algorithm Development Steven Chan Eni Njoku Joint AMSR Science Team Meeting Telluride, Colorado.

Level 2 Scatterometer Processing Alex Fore Julian Chaubell Adam Freedman Simon Yueh.

Challenges and Strategies for Combined Active/Passive Precipitation Retrievals S. Joseph Munchak 1, W. S. Olson 1,2, M. Grecu 1,3 1: NASA Goddard Space.

Aquarius Simulation Studies Gary Lagerloef Aquarius Principal Investigator Algorithm Workshop 9-11 March 2010.

Developing Synergistic Data Assimilation Approaches for Passive Microwave and Thermal Infrared Soil Moisture Retrievals Christopher R. Hain SPoRT Data.

Radiometer RFI Mitigation Chad Forshee University of Kansas EECS 823 Fall 2014.

Basis of GV for Japan’s Hydro-Meteorological Process Modelling Research GPM Workshop Sep. 27 to 30, Taipei, Taiwan Toshio Koike, Tobias Graf, Mirza Cyrus.

SMOS L2 Ocean Salinity – PM#25 1/20 Level 2 Ocean Salinity May 2013 A3TEC.

South Pole North Pole South Pole DD, K CONAE Microwave Radiometer (MWR) Counts to Tb Algorithm and On orbit Validation Zoubair Ghazi 1, Andrea Santos-Garcia.

SMOS Science Meeting September 2011 Arles, FR Simulating Aquarius by Resampling SMOS Gary Lagerloef, Yann Kerr & Eric Anterrieu and Initial Results.

Impact of sea surface roughness on SMOS measurements A new empirical model S. Guimbard & SMOS-BEC Team SMOS Barcelona Expert Centre Pg. Marítim de la Barceloneta.

Universitat Politècnica de Catalunya CORRECTION OF SPATIAL ERRORS IN SMOS BRIGHTNESS TEMPERATURE IMAGES L. Wu, I. Corbella, F. Torres, N. Duffo, M. Martín-Neira.

21-23/04/2015PM27 ACRI-ST ARGANS LOCEAN TEC follow-up.

Spaceborne Polarimetric Microwave Radiometer Brandon Ravenscroft

Cassini Huygens EECS 823 DIVYA CHALLA.

Leena Leppänen1, Anna Kontu1, Juha Lemmetyinen1, Martin Proksch2

SOLab work description

Roughness Correction for Aquarius (AQ) Sea Surface Salinity (SSS) Algorithm using MicroWave Radiometer (MWR) W. Linwood Jones, Yazan Hejazin Central FL.

Hyperspectral Wind Retrievals Dave Santek Chris Velden CIMSS Madison, Wisconsin 5th Workshop on Hyperspectral Science 8 June 2005.

Wei Huang Class project presentation for ECE539

The fact that light WAVES are transverseand not longitudinal is demonstrated by the phenomenon of polarization.

Radiometer Physics GmbH

Improved Forward Models for Retrievals of Snow Properties

ORTHOGRAPHIC PROJECTIONS { MACHINE ELEMENTS }

ORTHOGRAPHIC PROJECTIONS { MACHINE ELEMENTS }

Presentation transcript:

Faraday Rotation David Le Vine Aquarius Algorithm Workshop March 9-11, 2010

Approach Rotation Angle Retrieved from 3 rd Stokes Parameter*: Ω F = 0.5 Atan[ T3 / (Tv – Th) ] * S. Yueh, “Estimation of Faraday Rotation with Passive Microwave Polarimetry for Microwave Remote Sensing of Earth Surfaces”, TGARS, Vol 38 (#5), pp. 2434, Sept

Example: Aquarius Simulator Antenna temperature for vertical polarization (top), horizontal polarization (middle) and third Stokes parameter (bottom) for the Aquarius middle beam.

Retrieved Faraday Rotation Angle (Top) Faraday rotation angle at boresight of the middle radiometer beam. (Bottom) Third Stokes parameter for the same antenna.

Plan Test – SMOS “full-pol” data Remove spurious signals – Filter at land/water boundaries – Match to theoretical profile Magnetic field + estimate of TEC Remove bias – Match ground truth (sounder) at selected locations Backup Plan – Use model (data assimilation) – Correct for altitude (SMOS algorithm)

Retrieved Faraday Rotation Angle (Top) Faraday rotation angle at boresight of the middle radiometer beam. (Bottom) Third Stokes parameter for the same antenna. Rotation Angle Retrieved from 3 rd Stokes Parameter*: Ω F = 0.5 Atan[ T3 / (Tv – Th) ] * S. Yueh, “Estimation of Faraday Rotation with Passive Microwave Polarimetry for Microwave Remote Sensing of Earth Surfaces”, TGARS, Vol 38 (#5), pp. 2434, Sept