Microwave emissivity of land surfaces: experiments and models

Size: px
Start display at page:

Download "Microwave emissivity of land surfaces: experiments and models"

Transcription

1 Microwave emissivity of land surfaces: experiments and models M. Brogioni, G.Macelloni, S.Paloscia, P.Pampaloni, S.Pettinato, E.Santi IFAC-CNR Florence, Italy

2 Introduction Experimental investigations conducted by the Microwave Remote Sensing Group made it possible to realize a wide archive of microwave emissivity of the following surface types: bare soil with different levels of moisture and types of surface roughness soil covered with wheat, corn, alfalfa, sunflower, natural grass at various level of biomass deciduous and coniferous forests with different woody volumes soil covered with snow in different conditions (dry and wet) and depth. Ice sheet in Antarctica

3 Experimental equipments Dome-C Antarctica

4 Ground measurements

5 Experimental results: sensitivity to land features

6 TnH 1 0,95 0,9 0,85 0,8 0,75 0,7 0,65 0,6 0,55 0,5 Emissivity spectra of land surfaces FREQUENCY WHEAT CORN ALFALFA SUNFL BS (wet) BS (dry) SNOW (wet) SNOW (dry) FOREST Emissivity spectra of forests (poplar)

7 Emissivity of agricultural surfaces TnH Ka band X band L-band Soil moisture Smooth bare SMCg (%) X band L-band TnH Km Rough slightly vegetated SMCg (%)

8 Sensitivity to Plant Water Content of crops emissivity Broad leaf L X Ka Small leaf

9 NDVI from SPOT4 Sensitivity to vegetation (AMSR-E) NDVI from AMSR-E

10 Sensitivity to snow cover: dry snow accumulation Brightness Temperature (K) Snow Depth (cm) TbV meas 10GHz TbV DMRT 10GHz 170 TbV meas 37GHz TbV DMRT 37GHz Snow Water Equivalent (mm)

11 Sensitivity to snow wetness TB (37 GHz) V H T b [K] Melt-refreezing cycles W % Liquid water content

12 Sensitivity to snow cover (AMSR-E) FI Snow Depth (cm) 12/2006

13 Antarctica: Temporal variability L-band Ground based 2 week Time stability Mean = K Dev. st. = 0.18 K

14 Antarctica: Spatial variability AMSR-E (Tb 37 GHz V - Yearly average)

15 220 Antarctica: Temporal variability AMSR-E AMSR-E Brightness Temperature [K] C X Ku Ka Tsnow Retrieved [ C] cm 160 Jan-05 Apr-05 Jul-05 Oct-05 Jan-06 Apr-06 Jul-06 Oct-06 Jan-07 Date Tsnow Measured [ C] Snow Temperature [ C] Snow temp. -80 Jan-05 Apr-05 Jul-05 Oct-05 Jan-06 Apr-06 Jul-06 Oct-06 Jan-07 Date Tsnow Retrieved [ C] cm Tsnow Measured [ C]

16 Electromagnetc modelling Surface scattering: soil Volume scattering: snow vegetation crops forests

17 Sensitivity to forest biomass Emissivity Forest - Radiative Transfer ( L-Band) Trunk Total Crown Soil Incidence Angle (degs) e v eh ev eh Emissivity Data Disc. Model Cont. Model Woody Volume (m 3 /ha)

18 Model sensitivity to soil roughness V H V H ε = 7 j2 θ = 55 ε = 20 j 5 θ = 55

19 Model sensitivity to snow parameters Snow depth Grain size Snow density

20 Conclusions Microwave emissivity of land surfaces in the frequency range 1-40 GHz strongly depends on Frequency, polarization and incidence agle of the observing sensor Cover type and physical conditions Bare soil: moisture, surface roughness Vegetation: crop/forest type, biomass Snow: depth, density (water equivalent), wetness, grain dimension

Multi- Sensor Ground- based Microwave Snow Experiment at Altay, CHINA

Multi- Sensor Ground- based Microwave Snow Experiment at Altay, CHINA Multi- Sensor Ground- based Microwave Snow Experiment at Altay, CHINA Jiancheng Shi 1, Chuan Xiong 1, Jinmei Pan 1, Tao Che 2, Tianjie Zhao 1, Haokui Xu 1, Lu Hu 1, Xiang Ji 1, Shunli Chang 3, Suhong Liu

More information

RETRIEVAL OF SOIL MOISTURE OVER SOUTH AMERICA DERIVED FROM MICROWAVE OBSERVATIONS

RETRIEVAL OF SOIL MOISTURE OVER SOUTH AMERICA DERIVED FROM MICROWAVE OBSERVATIONS 2nd Workshop on Remote Sensing and Modeling of Surface Properties 9-11 June 2009, Toulouse, France Météo France Centre International de Conférences RETRIEVAL OF SOIL MOISTURE OVER SOUTH AMERICA DERIVED

More information

Advancing Remote-Sensing Methods for Monitoring Geophysical Parameters

Advancing Remote-Sensing Methods for Monitoring Geophysical Parameters Advancing Remote-Sensing Methods for Monitoring Geophysical Parameters Christian Mätzler (Retired from University of Bern) Now consultant for Gamma Remote Sensing, Switzerland matzler@iap.unibe.ch TERENO

More information

Microwave Remote Sensing of Soil Moisture. Y.S. Rao CSRE, IIT, Bombay

Microwave Remote Sensing of Soil Moisture. Y.S. Rao CSRE, IIT, Bombay Microwave Remote Sensing of Soil Moisture Y.S. Rao CSRE, IIT, Bombay Soil Moisture (SM) Agriculture Hydrology Meteorology Measurement Techniques Survey of methods for soil moisture determination, Water

More information

A New Microwave Snow Emissivity Model

A New Microwave Snow Emissivity Model A New Microwave Snow Emissivity Model Fuzhong Weng 1,2 1. Joint Center for Satellite Data Assimilation 2. NOAA/NESDIS/Office of Research and Applications Banghua Yan DSTI. Inc The 13 th International TOVS

More information

The DMRT-ML model: numerical simulations of the microwave emission of snowpacks based on the Dense Media Radiative Transfer theory

The DMRT-ML model: numerical simulations of the microwave emission of snowpacks based on the Dense Media Radiative Transfer theory The DMRT-ML model: numerical simulations of the microwave emission of snowpacks based on the Dense Media Radiative Transfer theory Ludovic Brucker 1,2, Ghislain Picard 3 Alexandre Roy 4, Florent Dupont

More information

Soil Moisture Prediction and Assimilation

Soil Moisture Prediction and Assimilation Soil Moisture Prediction and Assimilation Analysis and Prediction in Agricultural Landscapes Saskatoon, June 19-20, 2007 STEPHANE BELAIR Meteorological Research Division Prediction and Assimilation Atmospheric

More information

Passive Microwave Physics & Basics. Edward Kim NASA/GSFC

Passive Microwave Physics & Basics. Edward Kim NASA/GSFC Passive Microwave Physics & Basics Edward Kim NASA/GSFC ed.kim@nasa.gov NASA Snow Remote Sensing Workshop, Boulder CO, Aug 14 16, 2013 1 Contents How does passive microwave sensing of snow work? What are

More information

Modeling microwave emission in Antarctica. influence of the snow grain size

Modeling microwave emission in Antarctica. influence of the snow grain size Modeling microwave emission at 9 and 37 GHz in Antarctica : influence of the snow grain size Ludovic Brucker, Ghislain Picard and Michel Fily Laboratoire de Glaciologie et Géophysique de l Environnement

More information

Effect of Antireflective Surface at the Radiobrightness Observations for the Topsoil Covered with Coniferous Litter

Effect of Antireflective Surface at the Radiobrightness Observations for the Topsoil Covered with Coniferous Litter 966 PIERS Proceedings, Moscow, Russia, August 18 21, 2009 Effect of Antireflective Surface at the Radiobrightness Observations for the Topsoil Covered with Coniferous Litter V. L. Mironov 1, P. P. Bobrov

More information

Many of remote sensing techniques are generic in nature and may be applied to a variety of vegetated landscapes, including

Many of remote sensing techniques are generic in nature and may be applied to a variety of vegetated landscapes, including Remote Sensing of Vegetation Many of remote sensing techniques are generic in nature and may be applied to a variety of vegetated landscapes, including 1. Agriculture 2. Forest 3. Rangeland 4. Wetland,

More information

CMEM: Community Microwave Emission Model

CMEM: Community Microwave Emission Model CMEM: Community Microwave Emission Model SMOS forward operator for Numerical Weather Prediction P. de Rosnay, M. Drusch, J.-P. Wigneron T. Holmes, G. Balsamo, Y. Kerr, J.-C. Calvet SMOS Workshop 29-31

More information

Assimilation of satellite derived soil moisture for weather forecasting

Assimilation of satellite derived soil moisture for weather forecasting Assimilation of satellite derived soil moisture for weather forecasting www.cawcr.gov.au Imtiaz Dharssi and Peter Steinle February 2011 SMOS/SMAP workshop, Monash University Summary In preparation of the

More information

GCOM-W1 now on the A-Train

GCOM-W1 now on the A-Train GCOM-W1 now on the A-Train GCOM-W1 Global Change Observation Mission-Water Taikan Oki, K. Imaoka, and M. Kachi JAXA/EORC (& IIS/The University of Tokyo) Mini-Workshop on A-Train Science, March 8 th, 2013

More information

SIMULATION OF SPACEBORNE MICROWAVE RADIOMETER MEASUREMENTS OF SNOW COVER FROM IN-SITU DATA AND EMISSION MODELS

SIMULATION OF SPACEBORNE MICROWAVE RADIOMETER MEASUREMENTS OF SNOW COVER FROM IN-SITU DATA AND EMISSION MODELS SIMULATION OF SPACEBORNE MICROWAVE RADIOMETER MEASUREMENTS OF SNOW COVER FROM IN-SITU DATA AND EMISSION MODELS Anna Kontu 1 and Jouni Pulliainen 1 1. Finnish Meteorological Institute, Arctic Research,

More information

Astronaut Ellison Shoji Onizuka Memorial Downtown Los Angeles, CA. Los Angeles City Hall

Astronaut Ellison Shoji Onizuka Memorial Downtown Los Angeles, CA. Los Angeles City Hall Astronaut Ellison Shoji Onizuka Memorial Downtown Los Angeles, CA Los Angeles City Hall Passive Microwave Radiometric Observations over Land The performance of physically based precipitation retrievals

More information

Evaluation of sub-kilometric numerical simulations of C-band radar backscatter over the french Alps against Sentinel-1 observations

Evaluation of sub-kilometric numerical simulations of C-band radar backscatter over the french Alps against Sentinel-1 observations Evaluation of sub-kilometric numerical simulations of C-band radar backscatter over the french Alps against Sentinel-1 observations Gaëlle Veyssière, Fatima Karbou, Samuel Morin, Matthieu Lafaysse Monterey,

More information

Estimates of surface soil moisture under wet grass using L-band radiometry:

Estimates of surface soil moisture under wet grass using L-band radiometry: Estimates of surface soil moisture under wet grass using L-band radiometry: KAUZAR SALEH, JEAN-PIERRE WIGNERON, PATRICIA DE ROSNAY, JEAN-CHRISTOPHE CALVET, YANN KERR, MARIA J ESCORIHUELA, PHILIPPE WALDTEUFEL

More information

Snow property extraction based on polarimetry and differential SAR interferometry

Snow property extraction based on polarimetry and differential SAR interferometry Snow property extraction based on polarimetry and differential SAR interferometry S. Leinß, I. Hajnsek Earth Observation and Remote Sensing, Institute of Enviromental Science, ETH Zürich TerraSAR X and

More information

Improved parameterization of the emissivity of soil surfaces and forests at L-band (L-MEB in the Level-2 SMOS algorithm)

Improved parameterization of the emissivity of soil surfaces and forests at L-band (L-MEB in the Level-2 SMOS algorithm) Improved parameterization of the emissivity of soil surfaces and forests at L-band (L-MEB in the Level-2 SMOS algorithm) J-P Wigneron, A. Mialon, J. Grant, Y. Kerr, J-C Calvet, M. Crapeau, F. Demontoux,

More information

Assimilation of ASCAT soil wetness

Assimilation of ASCAT soil wetness EWGLAM, October 2010 Assimilation of ASCAT soil wetness Bruce Macpherson, on behalf of Imtiaz Dharssi, Keir Bovis and Clive Jones Contents This presentation covers the following areas ASCAT soil wetness

More information

RADAR Remote Sensing Application Examples

RADAR Remote Sensing Application Examples RADAR Remote Sensing Application Examples! All-weather capability: Microwave penetrates clouds! Construction of short-interval time series through cloud cover - crop-growth cycle! Roughness - Land cover,

More information

ECMWF. ECMWF Land Surface Analysis: Current status and developments. P. de Rosnay M. Drusch, K. Scipal, D. Vasiljevic G. Balsamo, J.

ECMWF. ECMWF Land Surface Analysis: Current status and developments. P. de Rosnay M. Drusch, K. Scipal, D. Vasiljevic G. Balsamo, J. Land Surface Analysis: Current status and developments P. de Rosnay M. Drusch, K. Scipal, D. Vasiljevic G. Balsamo, J. Muñoz Sabater 2 nd Workshop on Remote Sensing and Modeling of Surface Properties,

More information

Meteorological Satellite Image Interpretations, Part III. Acknowledgement: Dr. S. Kidder at Colorado State Univ.

Meteorological Satellite Image Interpretations, Part III. Acknowledgement: Dr. S. Kidder at Colorado State Univ. Meteorological Satellite Image Interpretations, Part III Acknowledgement: Dr. S. Kidder at Colorado State Univ. Dates EAS417 Topics Jan 30 Introduction & Matlab tutorial Feb 1 Satellite orbits & navigation

More information

GEOGG141 Principles & Practice of Remote Sensing (PPRS) RADAR III: Applications Revision

GEOGG141 Principles & Practice of Remote Sensing (PPRS) RADAR III: Applications Revision UCL DEPARTMENT OF GEOGRAPHY GEOGG141 Principles & Practice of Remote Sensing (PPRS) RADAR III: Applications Revision Dr. Mathias (Mat) Disney UCL Geography Office: 113, Pearson Building Tel: 7670 0592

More information

SOIL MOISTURE EXPERIMENTS 2005 (SMEX05): PASSIVE MICROWAVE POLARIMETRIC SIGNATURES OF SOIL MOISTURE AND VEGETATION

SOIL MOISTURE EXPERIMENTS 2005 (SMEX05): PASSIVE MICROWAVE POLARIMETRIC SIGNATURES OF SOIL MOISTURE AND VEGETATION SOIL MOISTURE EXPERIMENTS 25 (SMEX5): PASSIVE MICROWAVE POLARIMETRIC SIGNATURES OF SOIL MOISTURE AND VEGETATION Jackson, T. a, Bindlish, R.a, Du, J. a, Cosh, M. a Li, L b, Gaiser, P b, Kabela, E. c, and

More information

The GCOM- W1 AMSR2 snow depth and snow water equivalent product: update

The GCOM- W1 AMSR2 snow depth and snow water equivalent product: update The GCOM- W1 AMSR2 snow depth and snow water equivalent product: update Richard Kelly, Nastaran Saberi & Qinghuan Li Department of Geography and Environmental Management University of Waterloo, Waterloo,

More information

Climate Roles of Land Surface

Climate Roles of Land Surface Lecture 5: Land Surface and Cryosphere (Outline) Climate Roles Surface Energy Balance Surface Water Balance Sea Ice Land Ice (from Our Changing Planet) Surface Albedo Climate Roles of Land Surface greenhouse

More information

Aquarius/SAC-D Soil Moisture Product using V3.0 Observations

Aquarius/SAC-D Soil Moisture Product using V3.0 Observations Aquarius/SAC-D Soil Moisture Product using V3. Observations R. Bindlish, T. Jackson, M. Cosh November 214 Overview Soil moisture algorithm Soil moisture product Validation Linkage between Soil Moisture

More information

The role of soil moisture in influencing climate and terrestrial ecosystem processes

The role of soil moisture in influencing climate and terrestrial ecosystem processes 1of 18 The role of soil moisture in influencing climate and terrestrial ecosystem processes Vivek Arora Canadian Centre for Climate Modelling and Analysis Meteorological Service of Canada Outline 2of 18

More information

ECMWF. ECMWF Land Surface modelling and land surface analysis. P. de Rosnay G. Balsamo S. Boussetta, J. Munoz Sabater D.

ECMWF. ECMWF Land Surface modelling and land surface analysis. P. de Rosnay G. Balsamo S. Boussetta, J. Munoz Sabater D. Land Surface modelling and land surface analysis P. de Rosnay G. Balsamo S. Boussetta, J. Munoz Sabater D. Vasiljevic M. Drusch, K. Scipal SRNWP 12 June 2009 Slide 1 Surface modelling (G. Balsamo) HTESSEL,

More information

Light Up Your World Adapted from Reflecting on Reflectivity,

Light Up Your World Adapted from Reflecting on Reflectivity, Climate Change I m Supposed To Know What That Is? Light Up Your World Adapted from Reflecting on Reflectivity, http://www.climatechangenorth.ca Overview: Students often confuse global warming and the depletion

More information

ANALYSIS OF LEAF AREA INDEX AND SOIL WATER CONTENT RETRIEVAL FROM AGRISAR DATA SETS

ANALYSIS OF LEAF AREA INDEX AND SOIL WATER CONTENT RETRIEVAL FROM AGRISAR DATA SETS ANALYSIS OF LEAF AREA INDEX AND SOIL WATER CONTENT RETRIEVAL FROM AGRISAR DATA SETS D'Urso, G. () ; Dini, L. () ; Richter, K. () ; Palladino M. () () DIIAT, Faculty of Agraria, University of Naples Federico

More information

CHAPTER-7 INTERFEROMETRIC ANALYSIS OF SPACEBORNE ENVISAT-ASAR DATA FOR VEGETATION CLASSIFICATION

CHAPTER-7 INTERFEROMETRIC ANALYSIS OF SPACEBORNE ENVISAT-ASAR DATA FOR VEGETATION CLASSIFICATION 147 CHAPTER-7 INTERFEROMETRIC ANALYSIS OF SPACEBORNE ENVISAT-ASAR DATA FOR VEGETATION CLASSIFICATION 7.1 INTRODUCTION: Interferometric synthetic aperture radar (InSAR) is a rapidly evolving SAR remote

More information

Global SWE Mapping by Combining Passive and Active Microwave Data: The GlobSnow Approach and CoReH 2 O

Global SWE Mapping by Combining Passive and Active Microwave Data: The GlobSnow Approach and CoReH 2 O Global SWE Mapping by Combining Passive and Active Microwave Data: The GlobSnow Approach and CoReH 2 O April 28, 2010 J. Pulliainen, J. Lemmetyinen, A. Kontu, M. Takala, K. Luojus, K. Rautiainen, A.N.

More information

ANALYSIS OF MICROWAVE EMISSION OF EXPONEN- TIALLY CORRELATED ROUGH SOIL SURFACES FROM 1.4 GHz TO 36.5 GHz

ANALYSIS OF MICROWAVE EMISSION OF EXPONEN- TIALLY CORRELATED ROUGH SOIL SURFACES FROM 1.4 GHz TO 36.5 GHz Progress In Electromagnetics Research, Vol. 18, 25 219, 21 ANALYSIS OF MICROWAVE EMISSION OF EXPONEN- TIALLY CORRELATED ROUGH SOIL SURFACES FROM 1.4 GHz TO 36.5 GHz P. Xu and K.-S. Chen Communication Research

More information

Remote Sensing of SWE in Canada

Remote Sensing of SWE in Canada Remote Sensing of SWE in Canada Anne Walker Climate Research Division, Environment Canada Polar Snowfall Hydrology Mission Workshop, June 26-28, 2007 Satellite Remote Sensing Snow Cover Optical -- Snow

More information

Central Asia Regional Flash Flood Guidance System 4-6 October Hydrologic Research Center A Nonprofit, Public-Benefit Corporation

Central Asia Regional Flash Flood Guidance System 4-6 October Hydrologic Research Center A Nonprofit, Public-Benefit Corporation http://www.hrcwater.org Central Asia Regional Flash Flood Guidance System 4-6 October 2016 Hydrologic Research Center A Nonprofit, Public-Benefit Corporation FFGS Snow Components Snow Accumulation and

More information

Comparison of NASA AIRS and MODIS Land Surface Temperature and Infrared Emissivity Measurements from the EOS AQUA platform

Comparison of NASA AIRS and MODIS Land Surface Temperature and Infrared Emissivity Measurements from the EOS AQUA platform Comparison of NASA AIRS and MODIS Land Surface Temperature and Infrared Emissivity Measurements from the EOS AQUA platform Robert Knuteson, Steve Ackerman, Hank Revercomb, Dave Tobin University of Wisconsin-Madison

More information

Agricultural land-use from space. David Pairman and Heather North

Agricultural land-use from space. David Pairman and Heather North Agricultural land-use from space David Pairman and Heather North Talk Outline Motivation Challenges Different approach Paddock boundaries Classifications Examples Accuracy Issues Data sources Future possibilities

More information

Spectral reflectance: When the solar radiation is incident upon the earth s surface, it is either

Spectral reflectance: When the solar radiation is incident upon the earth s surface, it is either Spectral reflectance: When the solar radiation is incident upon the earth s surface, it is either reflected by the surface, transmitted into the surface or absorbed and emitted by the surface. Remote sensing

More information

Copernicus Global Land Service

Copernicus Global Land Service Copernicus Global Land Service Cryosphere Products Kari Luojus on behalf the consortium Follow us on: Copernicus EU CopernicusEU www.copernicus.eu Copernicus Services Land Marine Atmosphere Emergency Security

More information

School on Modelling Tools and Capacity Building in Climate and Public Health April Remote Sensing

School on Modelling Tools and Capacity Building in Climate and Public Health April Remote Sensing 2453-5 School on Modelling Tools and Capacity Building in Climate and Public Health 15-26 April 2013 Remote Sensing CECCATO Pietro International Research Institute for Climate and Society, IRI The Earth

More information

CHARACTERISTICS OF SNOW AND ICE MORPHOLOGICAL FEATURES DERIVED FROM MULTI-POLARIZATION TERRASAR-X DATA

CHARACTERISTICS OF SNOW AND ICE MORPHOLOGICAL FEATURES DERIVED FROM MULTI-POLARIZATION TERRASAR-X DATA CHARACTERISTICS OF SNOW AND ICE MORPHOLOGICAL FEATURES DERIVED FROM MULTI-POLARIZATION TERRASAR-X DATA Dana Floricioiu 1, Helmut Rott 2, Thomas Nagler 2, Markus Heidinger 2 and Michael Eineder 1 1 DLR,

More information

Retrieval of Surface Properties Based on Microwave Emissivity Spectra

Retrieval of Surface Properties Based on Microwave Emissivity Spectra Retrieval of Surface Properties Based on Microwave Emissivity Spectra S-A. Boukabara, W. Chen, C. Kongoli, C. Grassotti and K. Garrett NOAA/NESDIS/STAR & JCSDA Camp Springs, Maryland, USA 2nd Workshop

More information

EMPIRICAL ESTIMATION OF VEGETATION PARAMETERS USING MULTISENSOR DATA FUSION

EMPIRICAL ESTIMATION OF VEGETATION PARAMETERS USING MULTISENSOR DATA FUSION EMPIRICAL ESTIMATION OF VEGETATION PARAMETERS USING MULTISENSOR DATA FUSION Franz KURZ and Olaf HELLWICH Chair for Photogrammetry and Remote Sensing Technische Universität München, D-80290 Munich, Germany

More information

An experimental study of angular variations of brightness surface temperature for some natural surfaces

An experimental study of angular variations of brightness surface temperature for some natural surfaces An experimental study of angular variations of brightness surface temperature for some natural surfaces Juan Cuenca, José A. Sobrino, and Guillem Soria University of Valencia, c./ Dr. Moliner 5, 46 Burjassot,

More information

THE ROLE OF MICROSTRUCTURE IN FORWARD MODELING AND DATA ASSIMILATION SCHEMES: A CASE STUDY IN THE KERN RIVER, SIERRA NEVADA, USA

THE ROLE OF MICROSTRUCTURE IN FORWARD MODELING AND DATA ASSIMILATION SCHEMES: A CASE STUDY IN THE KERN RIVER, SIERRA NEVADA, USA MICHAEL DURAND (DURAND.8@OSU.EDU), DONGYUE LI, STEVE MARGULIS Photo: Danielle Perrot THE ROLE OF MICROSTRUCTURE IN FORWARD MODELING AND DATA ASSIMILATION SCHEMES: A CASE STUDY IN THE KERN RIVER, SIERRA

More information

GLOBAL LAND COVER CLASSIFICATION BASED ON MICROWAVE POLARIZATION AND GRADIENT RATIO (MPGR)

GLOBAL LAND COVER CLASSIFICATION BASED ON MICROWAVE POLARIZATION AND GRADIENT RATIO (MPGR) GLOBAL LAND COVER CLASSIFICATION BASED ON MICROWAVE POLARIZATION AND GRADIENT RATIO (MPGR) Mukesh, BOORI 1, Ralph, FERRARO 2 1 National Research Council (NRC) USA: Visiting Scientist 2 NOAA/NESDIS/STAR/

More information

Toward a better modeling of surface emissivity to improve AMSU data assimilation over Antarctica GUEDJ Stephanie, KARBOU Fatima and RABIER Florence

Toward a better modeling of surface emissivity to improve AMSU data assimilation over Antarctica GUEDJ Stephanie, KARBOU Fatima and RABIER Florence Toward a better modeling of surface emissivity to improve AMSU data assimilation over Antarctica GUEDJ Stephanie, KARBOU Fatima and RABIER Florence International TOVS Study Conference, Monterey, California

More information

Assimilating terrestrial remote sensing data into carbon models: Some issues

Assimilating terrestrial remote sensing data into carbon models: Some issues University of Oklahoma Oct. 22-24, 2007 Assimilating terrestrial remote sensing data into carbon models: Some issues Shunlin Liang Department of Geography University of Maryland at College Park, USA Sliang@geog.umd.edu,

More information

Description of Snow Depth Retrieval Algorithm for ADEOS II AMSR

Description of Snow Depth Retrieval Algorithm for ADEOS II AMSR 1. Introduction Description of Snow Depth Retrieval Algorithm for ADEOS II AMSR Dr. Alfred Chang and Dr. Richard Kelly NASA/GSFC The development of a snow depth retrieval algorithm for ADEOS II AMSR has

More information

Field Emissivity Measurements during the ReSeDA Experiment

Field Emissivity Measurements during the ReSeDA Experiment Field Emissivity Measurements during the ReSeDA Experiment C. Coll, V. Caselles, E. Rubio, E. Valor and F. Sospedra Department of Thermodynamics, Faculty of Physics, University of Valencia, C/ Dr. Moliner

More information

Lecture 3A: Interception

Lecture 3A: Interception 3-1 GEOG415 Lecture 3A: Interception What is interception? Canopy interception (C) Litter interception (L) Interception ( I = C + L ) Precipitation (P) Throughfall (T) Stemflow (S) Net precipitation (R)

More information

SNOW cover is the major component of the cryosphere

SNOW cover is the major component of the cryosphere IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, VOL. 10, NO. 1, JANUARY 2013 9 The Potential of COSMO-SkyMed SAR Images in Monitoring Snow Cover Characteristics S. Pettinato, Member, IEEE, E. Santi, Member,

More information

METR 130: Lecture 2 - Surface Energy Balance - Surface Moisture Balance. Spring Semester 2011 February 8, 10 & 14, 2011

METR 130: Lecture 2 - Surface Energy Balance - Surface Moisture Balance. Spring Semester 2011 February 8, 10 & 14, 2011 METR 130: Lecture 2 - Surface Energy Balance - Surface Moisture Balance Spring Semester 2011 February 8, 10 & 14, 2011 Reading Arya, Chapters 2 through 4 Surface Energy Fluxes (Ch2) Radiative Fluxes (Ch3)

More information

+SOI Neutral SOI -SOI. Melt+ Melt- Melt+ Melt- Melt+ Melt- +SAM 1 (0.76) 6 (3.02) 1 (1.13) 5 (4.92) 1 (2.27) 0 (1.89) 14

+SOI Neutral SOI -SOI. Melt+ Melt- Melt+ Melt- Melt+ Melt- +SAM 1 (0.76) 6 (3.02) 1 (1.13) 5 (4.92) 1 (2.27) 0 (1.89) 14 Supplementary Table 1. Contingency table tallying the respective counts of positive and negative surface melt index anomalies in the Ross sector as a function of the signs of the Southern Annular Mode

More information

Microwave Remote Sensing of Sea Ice

Microwave Remote Sensing of Sea Ice Microwave Remote Sensing of Sea Ice What is Sea Ice? Passive Microwave Remote Sensing of Sea Ice Basics Sea Ice Concentration Active Microwave Remote Sensing of Sea Ice Basics Sea Ice Type Sea Ice Motion

More information

Land Surface Remote Sensing II

Land Surface Remote Sensing II PROCEEDINGS OFSPIE Land Surface Remote Sensing II Thomas J. Jackson Jing Ming Chen Peng Gong Shunlin Liang Editors 13-16 October 2014 Beijing, China Sponsored by SPIE Cosponsored by State Key Laboratory

More information

SNOW DEPTH AND SURFACE CONDITIONS OF AUSTFONNA ICE CAP (SVALBARD) USING FIELD OBSERVATIONS AND SATELLITE ALTIMETRY

SNOW DEPTH AND SURFACE CONDITIONS OF AUSTFONNA ICE CAP (SVALBARD) USING FIELD OBSERVATIONS AND SATELLITE ALTIMETRY SNOW DEPTH AND SURFACE CONDITIONS OF AUSTFONNA ICE CAP (SVALBARD) USING FIELD OBSERVATIONS AND SATELLITE ALTIMETRY Alexei Kouraev (1,2), Benoît Legrésy (1), Frédérique Rémy (1), Andrea Taurisano (3,4),

More information

A Microwave Snow Emissivity Model

A Microwave Snow Emissivity Model A Microwave Snow Emissivity Model Fuzhong Weng Joint Center for Satellite Data Assimilation NOAA/NESDIS/Office of Research and Applications, Camp Springs, Maryland and Banghua Yan Decision Systems Technologies

More information

F O U N D A T I O N A L C O U R S E

F O U N D A T I O N A L C O U R S E F O U N D A T I O N A L C O U R S E December 6, 2018 Satellite Foundational Course for JPSS (SatFC-J) F O U N D A T I O N A L C O U R S E Introduction to Microwave Remote Sensing (with a focus on passive

More information

Soil frost from microwave data. Kimmo Rautiainen, Jouni Pulliainen, Juha Lemmetyinen, Jaakko Ikonen, Mika Aurela

Soil frost from microwave data. Kimmo Rautiainen, Jouni Pulliainen, Juha Lemmetyinen, Jaakko Ikonen, Mika Aurela Soil frost from microwave data Kimmo Rautiainen, Jouni Pulliainen, Juha Lemmetyinen, Jaakko Ikonen, Mika Aurela Why landscape freeze/thaw? Latitudinal variation in mean correlations (r) between annual

More information

Fractional Vegetation Cover Estimation from PROBA/CHRIS Data: Methods, Analysis of Angular Effects and Application to the Land Surface Emissivity

Fractional Vegetation Cover Estimation from PROBA/CHRIS Data: Methods, Analysis of Angular Effects and Application to the Land Surface Emissivity Fractional Vegetation Cover Estimation from PROBA/CHRIS Data: Methods, Analysis of Angular Effects and Application to the Land Surface Emissivity J.C. Jiménez-Muñoz 1, J.A. Sobrino 1, L. Guanter 2, J.

More information

Lecture 19: Operational Remote Sensing in Visible, IR, and Microwave Channels

Lecture 19: Operational Remote Sensing in Visible, IR, and Microwave Channels MET 4994 Remote Sensing: Radar and Satellite Meteorology MET 5994 Remote Sensing in Meteorology Lecture 19: Operational Remote Sensing in Visible, IR, and Microwave Channels Before you use data from any

More information

Lecture Topics. 1. Vegetation Indices 2. Global NDVI data sets 3. Analysis of temporal NDVI trends

Lecture Topics. 1. Vegetation Indices 2. Global NDVI data sets 3. Analysis of temporal NDVI trends Lecture Topics 1. Vegetation Indices 2. Global NDVI data sets 3. Analysis of temporal NDVI trends Why use NDVI? Normalize external effects of sun angle, viewing angle, and atmospheric effects Normalize

More information

Remote sensing with FAAM to evaluate model performance

Remote sensing with FAAM to evaluate model performance Remote sensing with FAAM to evaluate model performance YOPP-UK Workshop Chawn Harlow, Exeter 10 November 2015 Contents This presentation covers the following areas Introduce myself Focus of radiation research

More information

Global Biogeography. Natural Vegetation. Structure and Life-Forms of Plants. Terrestrial Ecosystems-The Biomes

Global Biogeography. Natural Vegetation. Structure and Life-Forms of Plants. Terrestrial Ecosystems-The Biomes Global Biogeography Natural Vegetation Structure and Life-Forms of Plants Terrestrial Ecosystems-The Biomes Natural Vegetation natural vegetation is the plant cover that develops with little or no human

More information

URSI-F Microwave Signatures Meeting 2010, Florence, Italy, October 4 8, Thomas Meissner Lucrezia Ricciardulli Frank Wentz

URSI-F Microwave Signatures Meeting 2010, Florence, Italy, October 4 8, Thomas Meissner Lucrezia Ricciardulli Frank Wentz URSI-F Microwave Signatures Meeting 2010, Florence, Italy, October 4 8, 2010 Wind Measurements from Active and Passive Microwave Sensors High Winds and Winds in Rain Thomas Meissner Lucrezia Ricciardulli

More information

The Canadian Land Data Assimilation System (CaLDAS)

The Canadian Land Data Assimilation System (CaLDAS) The Canadian Land Data Assimilation System (CaLDAS) Marco L. Carrera, Stéphane Bélair, Bernard Bilodeau and Sheena Solomon Meteorological Research Division, Environment Canada Dorval, QC, Canada 2 nd Workshop

More information

Lambertian surface scattering at AMSU-B frequencies:

Lambertian surface scattering at AMSU-B frequencies: Lambertian surface scattering at AMSU-B frequencies: An analysis of airborne microwave data measured over snowcovered surfaces Chawn Harlow, 2nd Workshop on Remote Sensing and Modeling of Land Surface

More information

Remote sensing of sea ice

Remote sensing of sea ice Remote sensing of sea ice Ice concentration/extent Age/type Drift Melting Thickness Christian Haas Remote Sensing Methods Passive: senses shortwave (visible), thermal (infrared) or microwave radiation

More information

Global Climates. Name Date

Global Climates. Name Date Global Climates Name Date No investigation of the atmosphere is complete without examining the global distribution of the major atmospheric elements and the impact that humans have on weather and climate.

More information

Comparison of NASA AIRS and MODIS Land Surface Temperature and Infrared Emissivity Measurements from the EOS AQUA platform

Comparison of NASA AIRS and MODIS Land Surface Temperature and Infrared Emissivity Measurements from the EOS AQUA platform Comparison of NASA AIRS and MODIS Land Surface Temperature and Infrared Emissivity Measurements from the EOS AQUA platform Robert Knuteson, Hank Revercomb, Dave Tobin University of Wisconsin-Madison 16

More information

C. Jimenez, C. Prigent, F. Aires, S. Ermida. Estellus, Paris, France Observatoire de Paris, France IPMA, Lisbon, Portugal

C. Jimenez, C. Prigent, F. Aires, S. Ermida. Estellus, Paris, France Observatoire de Paris, France IPMA, Lisbon, Portugal All-weather land surface temperature estimates from microwave satellite observations, over several decades and real time: methodology and comparison with infrared estimates C. Jimenez, C. Prigent, F. Aires,

More information

Summary of the World s Major Terrestrial Biomes

Summary of the World s Major Terrestrial Biomes Summary of the World s Major Terrestrial Biomes Tropical Rainforests Precipitation Pattern: High yearly rainfall >100, generally during a long wet season and a short dry season. Temperature/Growing Season:

More information

SEA ICE MICROWAVE EMISSION MODELLING APPLICATIONS

SEA ICE MICROWAVE EMISSION MODELLING APPLICATIONS SEA ICE MICROWAVE EMISSION MODELLING APPLICATIONS R. T. Tonboe, S. Andersen, R. S. Gill Danish Meteorological Institute, Lyngbyvej 100, DK-2100 Copenhagen Ø, Denmark Tel.:+45 39 15 73 49, e-mail: rtt@dmi.dk

More information

Comparison of Wind Speed, Soil Moisture, and Cloud Cover to Relative Humidity to Verify Dew Formation

Comparison of Wind Speed, Soil Moisture, and Cloud Cover to Relative Humidity to Verify Dew Formation Meteorology Senior Theses Undergraduate Theses and Capstone Projects 12-1-2017 Comparison of Wind Speed, Soil Moisture, and Cloud Cover to Relative Humidity to Verify Dew Formation Kelly M. Haberichter

More information

September 2018 Weather Summary West Central Research and Outreach Center Morris, MN

September 2018 Weather Summary West Central Research and Outreach Center Morris, MN September 2018 Weather Summary The mean temperature for September was 60.6 F, which is 1.5 F above the average of 59.1 F (1886-2017). The high temperature for the month was 94 F on September 16 th. The

More information

Airborne Measurements of Forest and Agricultural Land Surface Emissivity at Millimeter Wavelengths

Airborne Measurements of Forest and Agricultural Land Surface Emissivity at Millimeter Wavelengths IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, VOL. 39, NO. 2, FEBRUARY 2001 393 Airborne Measurements of Forest and Agricultural Land Surface Emissivity at Millimeter Wavelengths Tim J. Hewison,

More information

Modelling and Validation of Combined Active and Passive Microwave Remote Sensing of Agricultural Vegetation at L-Band

Modelling and Validation of Combined Active and Passive Microwave Remote Sensing of Agricultural Vegetation at L-Band Progress In Electromagnetics Research B, Vol. 78, 91 124, 2017 Modelling and Validation of Combined Active and Passive Microwave Remote Sensing of Agricultural Vegetation at L-Band Huanting Huang 1, *,

More information

Interdisciplinary research for carbon cycling in a forest ecosystem and scaling to a mountainous landscape in Takayama,, central Japan.

Interdisciplinary research for carbon cycling in a forest ecosystem and scaling to a mountainous landscape in Takayama,, central Japan. Asia-Pacific Workshop on Carbon Cycle Observations (March 17 19, 2008) Interdisciplinary research for carbon cycling in a forest ecosystem and scaling to a mountainous landscape in Takayama,, central Japan.

More information

L-Band Radiometry Experiments with ELBARA

L-Band Radiometry Experiments with ELBARA L-Band Radiometry Experiments wit ELBARA 1. ELBARA, te ETH L-band radiometer for soil moisture researc. Bare-Soil Experiment 3. Frozen-Soil Experiment 4. Clover-Grass Experiment 5. Forest Experiment 6.

More information

ASimultaneousRadiometricand Gravimetric Framework

ASimultaneousRadiometricand Gravimetric Framework Towards Multisensor Snow Assimilation: ASimultaneousRadiometricand Gravimetric Framework Assistant Professor, University of Maryland Department of Civil and Environmental Engineering September 8 th, 2014

More information

Soil moisture retrieval over periodic surfaces using PolSAR data

Soil moisture retrieval over periodic surfaces using PolSAR data Soil moisture retrieval over periodic surfaces using PolSAR data Sandrine DANIEL Sophie ALLAIN Laurent FERRO-FAMIL Eric POTTIER IETR Laboratory, UMR CNRS 6164, University of Rennes1, France Contents Soil

More information

Retrieving soil moisture and agricultural variables by microwave radiometry using neural networks

Retrieving soil moisture and agricultural variables by microwave radiometry using neural networks Remote Sensing of Environment 84 (2003) 174 183 www.elsevier.com/locate/rse Retrieving soil moisture and agricultural variables by microwave radiometry using neural networks F. Del Frate *, P. Ferrazzoli,

More information

Atmospheric Soundings of Temperature, Moisture and Ozone from AIRS

Atmospheric Soundings of Temperature, Moisture and Ozone from AIRS Atmospheric Soundings of Temperature, Moisture and Ozone from AIRS M.D. Goldberg, W. Wolf, L. Zhou, M. Divakarla,, C.D. Barnet, L. McMillin, NOAA/NESDIS/ORA Oct 31, 2003 Presented at ITSC-13 Risk Reduction

More information

Land Surface Processes and Their Impact in Weather Forecasting

Land Surface Processes and Their Impact in Weather Forecasting Land Surface Processes and Their Impact in Weather Forecasting Andrea Hahmann NCAR/RAL with thanks to P. Dirmeyer (COLA) and R. Koster (NASA/GSFC) Forecasters Conference Summer 2005 Andrea Hahmann ATEC

More information

Global Patterns Gaston, K.J Nature 405. Benefit Diversity. Threats to Biodiversity

Global Patterns Gaston, K.J Nature 405. Benefit Diversity. Threats to Biodiversity Biodiversity Definitions the variability among living organisms from all sources, including, 'inter alia', terrestrial, marine, and other aquatic ecosystems, and the ecological complexes of which they

More information

APPLICATION OF SATELLITE MICROWAVE IMAGES IN ESTIMATING SNOW WATER EQUIVALENT 1

APPLICATION OF SATELLITE MICROWAVE IMAGES IN ESTIMATING SNOW WATER EQUIVALENT 1 JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION Vol. 44, No. 6 AMERICAN WATER RESOURCES ASSOCIATION December 2008 APPLICATION OF SATELLITE MICROWAVE IMAGES IN ESTIMATING SNOW WATER EQUIVALENT 1 Amir

More information

Snowfall Detection and Retrieval from Passive Microwave Satellite Observations. Guosheng Liu Florida State University

Snowfall Detection and Retrieval from Passive Microwave Satellite Observations. Guosheng Liu Florida State University Snowfall Detection and Retrieval from Passive Microwave Satellite Observations Guosheng Liu Florida State University Collaborators: Eun Kyoung Seo, Yalei You Snowfall Retrieval: Active vs. Passive CloudSat

More information

Communicating Climate Change Consequences for Land Use

Communicating Climate Change Consequences for Land Use Communicating Climate Change Consequences for Land Use Site: Prabost, Skye. Event: Kyle of Lochalsh, 28 th February 28 Further information: http://www.macaulay.ac.uk/ladss/comm_cc_consequences.html Who

More information

Measuring and Analyzing of Thermal Infrared Emission Directionality over crop canopies with an airborne wide-angle thermal IR camera.

Measuring and Analyzing of Thermal Infrared Emission Directionality over crop canopies with an airborne wide-angle thermal IR camera. Measuring and Analyzing of Thermal Infrared Emission Directionality over crop canopies with an airborne wide-angle thermal IR camera. X. F. Gu 1, F. Jacob 1, J. F. Hanocq 1, T. Yu 1,2, Q. H. Liu 2, L.

More information

Remote Sensing of Snow GEOG 454 / 654

Remote Sensing of Snow GEOG 454 / 654 Remote Sensing of Snow GEOG 454 / 654 What crysopheric questions can RS help to answer? 2 o Where is snow lying? (Snow-covered area or extent) o How much is there? o How rapidly is it melting? (Area, depth,

More information

JRA-55 Product Users Handbook

JRA-55 Product Users Handbook Climate Prediction Division Global Environment and Marine Department Japan Meteorological Agency March 2014 Change record Version Date Remarks 1.0 3 March 2014 First version 2 Contents 1. Introduction...

More information

Hyperspectral Observations of Land Surfaces: Temperature & Emissivity

Hyperspectral Observations of Land Surfaces: Temperature & Emissivity Hyperspectral Observations of Land Surfaces: Temperature & Emissivity Isabel F. Trigo Contributions from: Frank Göttsche, Filipe Aires, Maxime Paul Outline Land Surface Temperature Products & Requirements

More information

Reflectivity in Remote Sensing

Reflectivity in Remote Sensing Reflectivity in Remote Sensing The amount of absorbance and reflection of white light by a substance is dependent upon the molecular makeup of the substance. Humans have used dyes for years to obtain colors-

More information

Interpretation of Polar-orbiting Satellite Observations. Atmospheric Instrumentation

Interpretation of Polar-orbiting Satellite Observations. Atmospheric Instrumentation Interpretation of Polar-orbiting Satellite Observations Outline Polar-Orbiting Observations: Review of Polar-Orbiting Satellite Systems Overview of Currently Active Satellites / Sensors Overview of Sensor

More information

Remote sensing of snow at SYKE Sari Metsämäki

Remote sensing of snow at SYKE Sari Metsämäki Remote sensing of snow at SYKE 2011-01-21 Sari Metsämäki Activities in different projects Snow extent product in ESA DUE-project GlobSnow Long term datasets (15-30 years) on Snow Extent (SE) and Snow Water

More information

November 2018 Weather Summary West Central Research and Outreach Center Morris, MN

November 2018 Weather Summary West Central Research and Outreach Center Morris, MN November 2018 Weather Summary Lower than normal temperatures occurred for the second month. The mean temperature for November was 22.7 F, which is 7.2 F below the average of 29.9 F (1886-2017). This November

More information