A « European » Perspective Short term: SMOS L2 processor validation Long term: DA in an hydrological models.

Slides:



Advertisements
Similar presentations
Environmental Application of Remote Sensing: CE 6900 Tennessee Technological University Department of Civil and Environmental Engineering Course Instructor:
Advertisements

MoistureMap: Mixed-pixel Retrieval Ye Nan Master of research University of Melbourne Jeffrey Walker, Dongryeol Ryu, Christoph Rüdiger, Robert Gurney, Edward.
AMS’04, Seattle, WA. January 12, 2004Slide 1 HYDROS Radiometer and Radar Combined Soil Moisture Retrieval Using Kalman Filter Data Assimilation X. Zhan,
Second NAFE Workshop NAFE’06: A Proposed Campaign Strategy J Walker, O Merlin and R Panciera Dept Civil and Env Engg The University of Melbourne, Australia.
OSE meeting GODAE, Toulouse 4-5 June 2009 Interest of assimilating future Sea Surface Salinity measurements.
The ESA CoSMOS study for the validation of the SMOS L2 prototype K Saleh Contell, Y. Kerr, MJ Escorihuela, G. Boulet, P. Maisongrande, P. de Rosnay, JP.
YHKGEWEX May June 2007 Land Surface Flux Workshop Soil moisture retrieval from space a review? Claire Gruhier, Silvia Juglea, Patricia deRosnay and Yann.
Surface control on albedo and radiation balance over the Gourma site Laurent Kergoat, Olivier Samain, Françoise Guichard, Pierre Hiernaux, Franck Timouk,
Carbon dynamics at the hillslope and catchment scale Greg Hancock 1, Jetse Kalma 1, Jeff McDonnell 2, Cristina Martinez 1, Barry Jacobs 1, Tony Wells 1.
Scaling and Assimilation of Soil Moisture and Streamflow (SASMAS): project overview and preliminary results G Willgoose (U. Leeds, UK), H Hemakumara (U.
ElectroScience Lab Studies of Radio Frequency Interference in SMOS Observations IGARSS 2011 Joel T. Johnson and Mustafa Aksoy Department of Electrical.
NAFE’06 Planning Workshop 1 A BMRC and eWater Perspective Clara Draper Dr. Jeffrey Walker & Dr. Peter Steinle (BMRC)
AGU 2004 Fall Meeting, May 19, 2015Slide 1 Jointly Retrieving Surface Soil Moisture from Active and Passive Microwave Observations using Cubist Data-Mining.
US Calibration/Validation Activities for the ADM/Aeolus Mission Mike Hardesty and Lars-Peter Riishojgaard.
Near Surface Soil Moisture Estimating using Satellite Data Researcher: Dleen Al- Shrafany Supervisors : Dr.Dawei Han Dr.Miguel Rico-Ramirez.
Walker, Merlin, Panciera, Kalma and Hacker NAFE National Airborne Field Experiment 2 nd Workshop – Feb
Remote Sensing of Hydrological Variables over the Red Arkansas Eric Wood Matthew McCabe Rafal Wojcik Hongbo Su Huilin Gao Justin Sheffield Princeton University.
Identifying Soil Types using Soil moisture data CVEN 689 BY Uday Sant April 26, 2004.
SMOS – The Science Perspective Matthias Drusch Hamburg, Germany 30/10/2009.
Princeton University Global Evaluation of a MODIS based Evapotranspiration Product Eric Wood Hongbo Su Matthew McCabe.
STAR-Light: Enabling a New Vision for Land Surface Hydrology in the Arctic A. W. England and Roger De Roo Atmospheric, Oceanic, and Space Sciences Electrical.
SMOS SAG Meeting, ESAC-Villafranca del Castillo, 2-3 Nov 2006 KAUZAR SALEH YANN H. KERR COSMOS PROPOSAL TEAM Presentation of the study.
SMOS SAG, Villafranca November 2-3, 2006 Development of a Global In-Situ Soil Moisture Network: A SMOS Project Contribution P.J. van Oevelen.
Disaggregation of passive microwave data and assimilation into distributed hydrological models: The National Airborne Field Experiment (NAFE’05/06) Jetse.
VENUS (Vegetation and Environment New µ-Spacecraft) A demonstration space mission dedicated to land surface environment (Vegetation and Environment New.
Catchment Monitoring for Scaling and Assimilation of Soil Moisture and Streamflow C. Rüdiger a, R.E. Davidson b, H.M. Hemakumara b, J.P. Walker a, J.D.
Hydrologic/Watershed Modeling Glenn Tootle, P.E. Department of Civil and Environmental Engineering University of Nevada, Las Vegas
Aquarius Soil Moisture Working Group July 21, 2010.
Abstract In the case of the application of the Soil Moisture and Ocean Salinity (SMOS) mission to the field of hydrology, the question asked is the following:
6th SMOS Workshop, DTU Lyngby, Denmark, May 2006 Summary of ESA’s SMOS Science Activities Michael Berger ESA – ESTEC Earth Observation Programmes.
SMEX04/NAME Soil Moisture Remote Sensing Field Experiment Status Report 11/6/03.
Soil Carbon Dynamics: A Catchment Based Approach C. Martinez, G. Hancock, J.D. Kalma & T. Wells NAFE’06 Workshop February 13-14, 2006.
CSIRO LAND and WATER Estimation of Spatial Actual Evapotranspiration to Close Water Balance in Irrigation Systems 1- Key Research Issues 2- Evapotranspiration.
Assimilation of MODIS and AMSR-E Land Products into the NOAH LSM Xiwu Zhan 1, Paul Houser 2, Sujay Kumar 1 Kristi Arsenault 1, Brian Cosgrove 3 1 UMBC-GEST/NASA-GSFC;
Synergy of L-band and optical data for soil moisture monitoring O. Merlin, J. Walker and R. Panciera 3 rd NAFE workshop sept
The University of Mississippi Geoinformatics Center NASA MRC RPC: April 2008 Greg Easson, Ph.D.- (PI) Robert Holt, Ph.D.- (Co-PI) A. K. M. Azad Hossain.
Multi-mission synergistic activities: A new era of integrated missions Christa Peters- Lidard Deputy Director, Hydrospheric and Biospheric Sciences, Goddard.
Scale Effect of Vegetation Index Based Thermal Sharpening: A Simulation Study Based on ASTER Data X.H. Chen a, Y. Yamaguchi a, J. Chen b, Y.S. Shi a a.
1 Ground-based monitoring plans NAFE workshop Melbourne, 10 February 2005.
Data assimilation in land surface schemes Mathew Williams University of Edinburgh.
Antwerp march A Bottom-up Approach to Characterize Crop Functioning From VEGETATION Time series Toulouse, France Bucharest, Fundulea, Romania.
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,
The University of Mississippi Geoinformatics Center NASA MRC RPC – 11 July 2007 Greg Easson, Ph.D. Robert Holt, Ph.D. A. K. M. Azad Hossain University.
Status report from the Lead Centre for Surface Processes and Assimilation E. Rodríguez-Camino (INM) and S. Gollvik (SMHI)
PASSIVE MICROWAVE TECHNIQUES FOR HYDROLOGICAL APPLICATIONS by : P. Ferrazzoli Tor Vergata University Roma, Italy
EMIRAD Data coSMOS2 campaign. coSMOS2 campaign objectives Validation of SMOS SM L2 prototype processor Assimilation of root zone moisture Investigation.
Remote sensing for surface water hydrology RS applications for assessment of hydrometeorological states and fluxes –Soil moisture, snow cover, snow water.
Two modes: (1) stop and measure (SAM); (2) drive and measure (DAM). Can do: (1) 1-D transects. (2) 2-D maps. Mobile sensing of surface moisture: COSMOS.
Land Surface Modeling Studies in Support of AQUA AMSR-E Validation PI: Eric F. Wood, Princeton University Project Goal: To provide modeling support to.
Comparison of L and P band radar time series for the monitoring of Sahelian area P.-L. Frison, G. Mercier, E. Mougin, P. Hiernaux.
ICM/UTM - CSIC Hymex activities Joaquim Ballabrera Jordi Font Jordi Salat Marta Umbert.
Goal: to understand carbon dynamics in montane forest regions by developing new methods for estimating carbon exchange at local to regional scales. Activities:
AOM 4643 Principles and Issues in Environmental Hydrology.
Airborne Passive microwave response to soil moisture: A case study for the Rur catchment Sayeh Hasan (1), Carsten Montzka (1), Heye Bogena (1), Chris Rüdiger.
NAME Enhanced Observation Period 5 th NAME Science Working Group Meeting November 5-7, 2003 NAME Homepage:
Use of AMSR-E Land Parameter Modeling and Retrievals for SMAP Algorithm Development Steven Chan Eni Njoku Joint AMSR Science Team Meeting Telluride, Colorado.
国家 863 计划微波遥感技术实验室 The National Microwave Remote Sensing Laboratory 11/15/2007 Preparation for Vicarious Calibration of SMOS using Takelimgan Sand Desert.
A Remote Sensing Approach for Estimating Regional Scale Surface Moisture Luke J. Marzen Associate Professor of Geography Auburn University Co-Director.
Recent SeaWiFS view of the forest fires over Alaska Gene Feldman, NASA GSFC, Laboratory for Hydrospheric Processes, Office for Global Carbon Studies
QWG-10 – 4-6 February 2013 – ESRIN (Italy) SMOS Level3 and Level 4 Research Products Provided by the Barcelona Expert Center Jordi Font and BEC team SMOS.
APPLICATION OF A SOIL WATER BALANCE MODEL TO THE MERCOSUR AREA. J. Tomasella, J.A. Marengo M. Doyle and G. Coronel MAR DEL PLATA OCTOBER 2002.
Sarah Abelen and Florian Seitz Earth Oriented Space Science and Technology (ESPACE) IAPG, TUM Geodätische Woche 2010 Contributions of different water storage.
The ESA call for the 9 th Earth Explorer mission (EE9)
New Projects: Collaborators Sought NSF OPP Instrumentation Project: STAR-Light – a 1.4 GHz aperture synthesis radiometer for use on light aircraft in arctic.
CGMS-43-NOAA-WP-25 Coordination Group for Meteorological Satellites - CGMS NOAA Use of Soil Moisture Products Presented to CGMS-43 Working Group 2 session,
39 th Conference of Directors of EU Paying Agencies ESTEC, 25 May 2016 M. Drusch, Principal Scientist Earth Observation Programmes Directorate Science,
Passive Microwave Remote Sensing
Alexander Loew1, Mike Schwank2
Scaling Properties of L-band Passive Microwave Soil Moisture: From SMOS to Paddock Scale My work is focused on the scaling properties of L-band retrieval.
Presentation transcript:

A « European » Perspective Short term: SMOS L2 processor validation Long term: DA in an hydrological models

SMOS Data type ► multi-angular; dual polarization L band ► SM 4 % vol; 3 day revisit ► Spatial resolution better than 50 km ► Launched ► Level 1: brightness temperature at H and V polarisation ► Level 2: daily soil moisture and ocean salinity (swath) maps at basic temporal and spatial resolutions

2 / 1 parameter retrieval

SMOS L2 Algorithm

SM L2 retrieval: simplifications ► 200 LCC (ECOCLIMAP) aggregated into 10 ► Auxillary data not always available ► No direct model for every LCC ► Lack of info on very dry soils / sandy soils ► Only a limited number of emission sources > Algorithm Theoretical Basis Document (ATBD) 1st issue 12/2005 last issue 12/2006

How NAFE can contribute ? ► Scaling: do simple strategies/algorithms (such as the L2 SM processor) perform well ? ► A lot of the RT parameters have been calibrated on local experiments  SMOSREX = « typical » grassland  « La Londe » = « typical » forest etc  -> need to be checked at larger scales / other locations ► Interested in typical scales o(>1km) with sub-pixel variability of o( 1km) with sub-pixel variability of o(<1km)

CESBIO/INRA: short term ► AMSR: radiometric extrapolation C -> L (Philippe Richaume and Patricia De Rosnay) ► Intercomparison of 2 soil emissivity models for soil moisture retrieval algorithms (Patricia De Rosnay)  the tau-omega model and a coherent model;  focus on AMSR data;  compare the SM inversion performance with what one gets in sahelian environments (African Monsoon project) ► Forward RT modelling for forested envt, Litter effects and litter/surface soil moisture relationship (Jennifer Grant) ► L2 algorithm evaluation over several NAFE LCC (?)

CESBIO/INRA: long term ► “Development and evaluation of disagregation and assimilation methods of SMOS radiobrightness into hydrological models” ► Multispectral RS Data Assimilation  TIR (disagregation and/or data assimilation)  L-band (SMOS resolution)  NDVI (forcing/disagregation) ► DA of RS data directly, or disaggregated SM ? ► Evaluation on variables (e.g. root zone SM) and fluxes (e.g. streamflow)

Disagregation study ► What’s written in the 2005 proposals:  “1 km airborne brightness temperature maps will be aggregated to produce a coarse-resolution brightness temperature corresponding to the size of one SMOS pixel.  A geostatistical procedure based on LC, Soil Type and Topography will be used together with the SMOS generated brightness temperature to produce field scale surface soil moisture maps  Surface soil moisture maps produced will be compared to soil moisture fields obtained by inversion of the L- band brightness temperature maps acquired by the aircraft as well as ground-based soil moisture measurements.” (Philippe Maisongrande ?)

Data Assimilation: NAFE’05 data ► A coupled SVAT-Lateral redistribution model (ISBA3L/TOPMODEL/Isochrones) will be calibrated against streamflow and in-situ soil moisture data obtained for the network of continuous monitoring sites (Hélène Roux is building up on previous work by Jennifer Pellenq + ?) ► The performance of the data assimilation methods will be assessed by comparing predictions and measurements of streamflow and soil moisture content during NAFE’05  HR TIR info alone (Hélène ?)  disagregated L-band / SM info alone (Olivier ?)  combined HR TIR/ LR L-band info (Gilles ?)

Proposals/Fundings ► Chances to get a coSMOS3 campaign during NAFE’06 are small ► ESA cal/val project: provides ESA data but no $ !  Jetse is PI / Jeff and Gilles co-I  Data will be accessible for validation after launch ► CNES TOSCA 2005 application:  funding for at least 2 pers. for ~3 weeks for NAFE’06  Focus on SMOS calib. for TOSCA 2006 application ► SMOS data flow should start by the end of 2007 ► Commissioning phase ends up ~6 months after launch

NAFE’06 ? ► if Murrumbidgee wins: it sounds like we’ll replace « streamflow » by « evaporation » in the proposal, but objectives won’t change much (or I’m totally wrong ???) > still very relevant for SMOS ► if Goulburn wins: cool, we’ll build on previous studies ! (good for long-term DA)