Remote sensing of sea ice
|
|
|
- Jack Carson
- 5 years ago
- Views:
Transcription
1 Remote sensing of sea ice Ice concentration/extent Age/type Drift Melting Thickness Christian Haas
2 Remote Sensing Methods Passive: senses shortwave (visible), thermal (infrared) or microwave radiation emitted by Earth SSMI/AMSR: microwave GHz, V and H polarization Global ice coverage (25 km resolution) AVHRR: optical & thermal (5 bands) Ice coverage, ice temperature, ice drift (1 km resolution) MODIS: optical & thermal (36 bands) Ice coverage & processes, melt (250 m resolution) Active: actively transmits microwave (radar) or shortwave Radar (e.g. Radarsat, Quikscat) C- & Ku-band (5-13 GHz) Ice types, surface roughness, ice drift, ice melt (3-75 m resolution) Altimeters (laser and radar; e.g. ICESat, CryoSat) Ice freeboard & thickness (300 m resolution, onedimensional)
3 Microwave Remote Sensing Can see through clouds and snow Independent of daytime/solar radiation Passive: Low spatial resolution, but daily, global coverage Active (radar): High spatial resolution, narrow swaths Exclusive use of polar orbiting satellites
4 Satellite-measured surface brightness temperature T b T b = e T 0 e: Emissivity T 0 : Surface temperature Water: low emissivity Multiyear ice: intermediate emissivity First-year ice: high emissivity Varies with frequency and polarization H- and V-pol emissivity at 50 incidence angle (Spreen et al., 2008)
5 Brightness temperature of the Arctic Ocean September 2007 April 2008 Advanced Microwave Scanning Radiometer (higher spatial resolution 6.25 km) Died on October 4, 2011 Koji Shimada of JAMSTEC (Japan Agency for Marine-Earth Science and Technology )
6 Ice concentration The ice cover is composed of ice floes and is discontinuous, often with a gradual transition to open water Ice coverage is normally given as ice concentration, in 1/10s or %
7 Retrieval of ice concentration: NASA Team Algorithm Ice/water mixture Polarization ratio Gradient ratio EAS 221 D: based on observed T b s
8 NASA Team algorithm 8 FYI Tie points MYI
9 Ice extent vs. area Ice Extent: area A e enclosed by 15% ice concentration isoline Ice Area: Actual area covered by ice, accounting for ice concentration < 100%, i.e. A e * C
10 Advanced Very High Resolution Radiometer (AVHRR) Based on SW reflectivity and IR emission; 1 km resolution (@ nadir) First-of its kind, valuable mesoscale ice information Leads often appear exaggerated
11 MODIS: Moderate Resolution Imaging Spectroradiometer Sensor on NASA s Earth Observing System (EOS) mission program Operated on Terra and Aqua satellites GLOBAL products 250 m resolution (@ nadir) EAS 221 Christian Haas
12 Thin ice in Jones Sound MODIS SAR Thin ice in fjords due to enhanced ocean heat flux Possible future polynyas?
13 Polynyas and primary productivity Melling, Haas, Brossier, unpublished
14 Typical radar frequencies & wavelengths Radar waves can penetrate into matter, e.g. into snow, ice, dry sand, through vegetation
15 Backscatter as function of surface roughness Backscatter s 0 = Lambertian scattering backscattered power incident power radar reflectivity ; scattering albedo
16 Synthetic-Aperture Radar (SAR) e.g. ERS, Envisat, Radarsat C-Band SAR Very high spatial resolution achieved by along-track (azimuth) synthetic-aperture (Doppler) radar processing
17 Radar microwave interaction with ice
18 FYI vs MYI microstructure & properties FYI: saline, low porosity low backscatter MYI: desalinated by melt, porous, low density high (volume) backscatter
19 Backscatter of different ice types bright dark Mid-late summer Christian Haas
20 Grease ice MYI MYI FYI SYI SYI
21 Envisat SAR image Jan 26, 2009 High backscatter: MYI regions
22 Ice information from satellite Synthetic Aperture Radar data Shows ice dynamics and deformation Retrieval of geophysical ice properties has yet to be improved Envisat (C-Band) Jan-May 2007 DTU
23 Radarsat geophysical processor system RGPS: Drift and Deformation Christian Haas
24 Surface roughness and melt MODIS (June 10, 2012) Radarsat SAR (April 7, 2012) Rougher ice: High backscatter; less melt ponding due to better drainage/runoff
25 Arctic/Antarctic contrasts: Seasonal cycle of radar backscatter Haas, 2001
26 Antarctic/Arctic contrasts: Superimposed ice versus melt ponding Antarctic Arctic
27 Superimposed ice and ice layer formation / melt freeze cycles Warming and reversal of T-gradients Snow melting Meltwater percolation Refreezing within colder snow layers or at the colder snow/ice interface; or: Refreezing above slush layer by double diffusion
28 Effect on backscatter increase (and decreasing emissivity) Haas, 2001
29 Scatterometry QuikSCAT radar scatterometer Independent of clouds or daylight Low spatial resolution Cannot easily be used for ice concentration due to variable backscatter of water
30 Loss and replenishment of MYI Kwok et al., 2009
31 Laser & radar altimetry ICESat (Laser, small footprint, NASA) CryoSat (Radar, large footprint, ESA) Large uncertainties due to unknown sea surface, and snow cover
32 Sea ice thickness vs. freeboard Different definitions of freeboard! ICESat Laser altimetry: Freeboard Elevation of snow surface T i F w w i T s w w s 7 i f d hs hi snow ice water s i w CryoSat Radar altimetry: Freeboard Elevation of ice surface h i f w w i h s s w 3 i
33 ICESat sea ice thickness results Laser altimeter Kwok et al., 2004
34 Sea ice freeboard measurement with SAR radar altimeter F S Snow T Ice Water h i f w ( w i ) h s s ( w i )
35 Fall Spring ICESat ( ) CryoSat ( ) CryoSat Model Laxon et al., 2013 No data during melt season
36 Validation Agreement with validation measurements within 5-8 cm (5 km mean thicknesses)
37 Snow the last frontier!
Spectral Albedos. a: dry snow. b: wet new snow. c: melting old snow. a: cold MY ice. b: melting MY ice. d: frozen pond. c: melting FY white ice
Spectral Albedos a: dry snow b: wet new snow a: cold MY ice c: melting old snow b: melting MY ice d: frozen pond c: melting FY white ice d: melting FY blue ice e: early MY pond e: ageing ponds Extinction
Observations of Arctic snow and sea ice thickness from satellite and airborne surveys. Nathan Kurtz NASA Goddard Space Flight Center
Observations of Arctic snow and sea ice thickness from satellite and airborne surveys Nathan Kurtz NASA Goddard Space Flight Center Decline in Arctic sea ice thickness and volume Kwok et al. (2009) Submarine
Mass balance of sea ice in both hemispheres Airborne validation and the AWI CryoSat-2 sea ice data product
Mass balance of sea ice in both hemispheres Airborne validation and the AWI CryoSat-2 sea ice data product Stefan Hendricks Robert Ricker Veit Helm Sandra Schwegmann Christian Haas Andreas Herber Airborne
Merged sea-ice thickness product from complementary L-band and altimetry information
Merged sea-ice thickness product from complementary L-band and altimetry information Contributors AWI Team Stefan Hendricks Robert Ricker Stephan Paul University Hamburg Team Lars Kaleschke Xiangshan Tian-Kunze
Observing Arctic Sea Ice Change. Christian Haas
Observing Arctic Sea Ice Change Christian Haas Decreasing Arctic sea ice extent in September Ice extent is decreasing, but regional patterns are very different every year The Cryosphere Today, http://arctic.atmos.uiuc.edu;
GEOSC/METEO 597K Kevin Bowley Kaitlin Walsh
GEOSC/METEO 597K Kevin Bowley Kaitlin Walsh Timeline of Satellites ERS-1 (1991-2000) NSCAT (1996) Envisat (2002) RADARSAT (2007) Seasat (1978) TOPEX/Poseidon (1992-2005) QuikSCAT (1999) Jason-2 (2008)
Using Remote-sensed Sea Ice Thickness, Extent and Speed Observations to Optimise a Sea Ice Model
Using Remote-sensed Sea Ice Thickness, Extent and Speed Observations to Optimise a Sea Ice Model Paul Miller, Seymour Laxon, Daniel Feltham, Douglas Cresswell Centre for Polar Observation and Modelling
Sea Ice Growth And Decay. A Remote Sensing Perspective
Sea Ice Growth And Decay A Remote Sensing Perspective Sea Ice Growth & Decay Add snow here Loss of Sea Ice in the Arctic Donald K. Perovich and Jacqueline A. Richter-Menge Annual Review of Marine Science
COLD REGIONS SCIENCE AND MARINE TECHNOLOGY - Polar Ice By Satellite Remote Sensing - Antony Liu
POLAR ICE BY SATELLITE REMOTE SENSING Antony Liu Ocean Sciences Branch, NASA Goddard Space Flight Center, Greenbelt MD USA Keywords: Satellite remote sensing, Sea ice drift, Ice extent, Ice concentration,
SMOSIce L-Band Radiometry for Sea Ice Applications
Institute of Environmental Physics University of Bremen SMOSIce L-Band Radiometry for Sea Ice Applications Georg Heygster 1), Christian Haas 2), Lars Kaleschke 3), Helge Rebhan 5), Detlef Stammer 3), Rasmus
Fri. Apr. 06, Map Projections Environmental Applications. Reading: Finish Chapter 9 ( Environmental Remote Sensing )
Fri. Apr. 06, 2018 Map Projections Environmental Applications Reading: Finish Chapter 9 ( Environmental Remote Sensing ) Once again -- Satellites old but principles still apply Skim Sabins Chapter 10.
Analysis of Antarctic Sea Ice Extent based on NIC and AMSR-E data Burcu Cicek and Penelope Wagner
Analysis of Antarctic Sea Ice Extent based on NIC and AMSR-E data Burcu Cicek and Penelope Wagner 1. Abstract The extent of the Antarctica sea ice is not accurately defined only using low resolution microwave
Remote Sensing I: Basics
Remote Sensing I: Basics Kelly M. Brunt Earth System Science Interdisciplinary Center, University of Maryland Cryospheric Science Laboratory, Goddard Space Flight Center kelly.m.brunt@nasa.gov (Based on
Sinéad Louise Farrell1,2,3 Thomas Newman1,2,, Alek Petty 1,2, Jackie Richter-Menge4, Dave McAdoo1,2, Larry Connor2
Sinéad Louise Farrell1,2,3 Thomas Newman1,2,, Alek Petty 1,2, Jackie Richter-Menge4, Dave McAdoo1,2, Larry Connor2 1 Earth System Science Interdisciplinary Center, University of Maryland, USA 2 NOAA Laboratory
Linking Different Spatial Scales For Retrieval Of Sea Ice Conditions From SAR Images
Linking Different Spatial Scales For Retrieval Of Sea Ice Conditions From SAR Images Matt Arkett 2, Wolfgang Dierking 1, Jakob Griebel 1, Thomas Hollands 1, Stefanie Linow 1, Eero Rinne 3, Markku Similä
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
OCEAN SURFACE DRIFT BY WAVELET TRACKING USING ERS-2 AND ENVISAT SAR IMAGES
OCEAN SURFACE DRIFT BY WAVELET TRACKING USING ERS-2 AND ENVISAT SAR IMAGES Antony K. Liu, Yunhe Zhao Ocean Sciences Branch, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA Ming-Kuang Hsu Northern
EUMETSAT STATUS AND PLANS
1 EUM/TSS/VWG/15/826793 07/10/2015 EUMETSAT STATUS AND PLANS François Montagner, Marine Applications Manager, EUMETSAT WMO Polar Space Task Group 5 5-7 October 2015, DLR, Oberpfaffenhofen PSTG Strategic
Sea Ice Motion: Physics and Observations Ron Kwok Jet Propulsion Laboratory California Institute of Technology, Pasadena, CA
Sea Ice Motion: Physics and Observations Ron Kwok Jet Propulsion Laboratory California Institute of Technology, Pasadena, CA 7 th ESA Earth Observation Summer School ESRIN, Frascati, Italy 4-14 August
Sea ice extent from satellite microwave sensors
Sea ice extent from satellite microwave sensors Maria Belmonte Rivas Introduction In 2007, the summer extent of Arctic sea ice observed by the Special Sensor Microwave Imager (SSM/I) reached its lowest
Sea Ice Monitoring in the European Arctic Seas Using a Multi-Sensor Approach
Sea Ice Monitoring in the European Arctic Seas Using a Multi-Sensor Approach Stein Sandven Nansen Environmental and Remote Sensing Center, Bergen, Norway Abstract. Advances in satellite remote sensing
DLR s TerraSAR-X contributes to international fleet of radar satellites to map the Arctic and Antarctica
DLR s TerraSAR-X contributes to international fleet of radar satellites to map the Arctic and Antarctica The polar regions play an important role in the Earth system. The snow and ice covered ocean and
We greatly appreciate the thoughtful comments from the reviewers. According to the reviewer s comments, we revised the original manuscript.
Response to the reviews of TC-2018-108 The potential of sea ice leads as a predictor for seasonal Arctic sea ice extent prediction by Yuanyuan Zhang, Xiao Cheng, Jiping Liu, and Fengming Hui We greatly
Satellite Oceanography and Applications 2: Altimetry, scatterometry, SAR, GRACE. RMU Summer Program (AUGUST 24-28, 2015)
Satellite Oceanography and Applications 2: Altimetry, scatterometry, SAR, GRACE RMU Summer Program (AUGUST 24-28, 2015) Altimetry 2 Basic principles of satellite altimetry Altimetry: the measurements of
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
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,
Recent Improvements in the U.S. Navy s Ice Modeling Efforts Using CryoSat-2 Ice Thickness for Model Initialization
Recent Improvements in the U.S. Navy s Ice Modeling Efforts Using CryoSat-2 Ice Thickness for Model Initialization Richard Allard 1, David Hebert 1, Pamela Posey 1, Alan Wallcraft 1, Li Li 2, William Johnston
CITATION Dierking, W Sea ice monitoring by synthetic aperture radar. Oceanography 26(2): ,
The Official Magazine of the Oceanography Society CITATION Dierking, W. 2013. Sea ice monitoring by synthetic aperture radar. Oceanography 26(2):100 111, http://dx.doi.org/10.5670/oceanog.2013.33. DOI
REVISION OF THE STATEMENT OF GUIDANCE FOR GLOBAL NUMERICAL WEATHER PREDICTION. (Submitted by Dr. J. Eyre)
WORLD METEOROLOGICAL ORGANIZATION Distr.: RESTRICTED CBS/OPAG-IOS (ODRRGOS-5)/Doc.5, Add.5 (11.VI.2002) COMMISSION FOR BASIC SYSTEMS OPEN PROGRAMME AREA GROUP ON INTEGRATED OBSERVING SYSTEMS ITEM: 4 EXPERT
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
Optimizing Observations of Sea Ice Thickness and Snow Depth in the Arctic
DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Optimizing Observations of Sea Ice Thickness and Snow Depth in the Arctic Jacqueline A. Richter-Menge CRREL, 72 Lyme Road,
In-situ and airborne sea ice observations for better sea ice prediction and climate analysis. Christian Haas
In-situ and airborne sea ice observations for better sea ice prediction and climate analysis Christian Haas Data assimilation improves sea ice forecasts Most important parameters are: Concentration (SIC),
Optimizing Observations of Sea Ice Thickness and Snow Depth in the Arctic
DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Optimizing Observations of Sea Ice Thickness and Snow Depth in the Arctic Sinead L. Farrell University of Maryland, ESSIC
Sea ice thickness estimations from ICESat Altimetry over the Bellingshausen and Amundsen Seas,
JOURNAL OF GEOPHYSICAL RESEARCH: OCEANS, VOL. 118, 2438 2453, doi:10.1002/jgrc.20179, 2013 Sea ice thickness estimations from ICESat Altimetry over the Bellingshausen and Amundsen Seas, 2003 2009 Hongjie
HY-2A Satellite User s Guide
National Satellite Ocean Application Service 2013-5-16 Document Change Record Revision Date Changed Pages/Paragraphs Edit Description i Contents 1 Introduction to HY-2 Satellite... 1 2 HY-2 satellite data
PREDICTION AND MONITORING OF OCEANIC DISASTERS USING MICROWAVE REMOTE SENSING TECHNIQUES
PREDICTION AND MONITORING OF OCEANIC DISASTERS USING MICROWAVE REMOTE SENSING TECHNIQUES O P N Calla International Centre for Radio Science, OM NIWAS A-23, Shastri Nagar, Jodhpur-342 003 Abstract The disasters
Snow and Sea Ice Physics, Thermodynamics, Dynamics and Remote Sensing
Snow and Sea Ice Physics, Thermodynamics, Dynamics and Remote Sensing Ryan Galley Center for Earth Observation Science Clayton H. Riddell Faculty of Earth, Environment and Resources Freezing point of seawater
Monitoring Sea Ice with Space-borne Synthetic Aperture Radar
Monitoring Sea Ice with Space-borne Synthetic Aperture Radar Torbjørn Eltoft UiT- the Arctic University of Norway CIRFA A Centre for Research-based Innovation cirfa.uit.no Sea ice & climate Some basic
Evaluation of Regressive Analysis Based Sea Surface Temperature Estimation Accuracy with NCEP/GDAS Data
Evaluation of Regressive Analysis Based Sea Surface Temperature Estimation Accuracy with NCEP/GDAS Data Kohei Arai 1 Graduate School of Science and Engineering Saga University Saga City, Japan Abstract
Airborne sea ice thickness sounding
Airborne sea ice thickness sounding 1, Christian Haas 2, Lasse Rabenstein 1, John Lobach 3 1. Alfred Wegener Institute for Polar and Marine Research, Germany 2. University of Alberta, Canada 3. Ferra Dynamics
REMOTE SENSING KEY!!
REMOTE SENSING KEY!! This is a really ugly cover page I m sorry. Name Key. Score / 100 Directions: You have 50 minutes to take this test. You may use a cheatsheet (2 pages), a non-graphing calculator,
GLAS Team Member Quarterly Report
GLAS Team Member Quarterly Report Thomas A. Herring, Katherine J. Quinn, An Nguyen, Monchaya Piboon Massachusetts Institute of Technology Period: 4/1/2002 to 6/30/2002 Options for Estimating Multiple Scattering
The ICESat 2 Mission Laser altimetry of ice, clouds and land elevation
OSTM SWT San Diego October 2011 The ICESat 2 Mission Laser altimetry of ice, clouds and land elevation and also ocean, coastal, and continental waters Charon Birkett, ESSIC/UMD on behalf of T. Markus,
Lake ice cover and surface water temperature II: Satellite remote sensing
Lake ice cover and surface water temperature II: Satellite remote sensing Claude Duguay University of Waterloo (Canada) Earth Observation Summer School ESA-ESRIN, Frascati, Italy (4-14 August 2014) Lecture
Remote Sensing and GIS. Microwave Remote Sensing and its Applications
Subject Paper No and Title Module No and Title Module Tag Geology Remote Sensing and GIS Microwave Remote Sensing and its Applications RS & GIS XVII Principal Investigator Co-Principal Investigator Co-Principal
THIN ICE AREA EXTRACTION IN THE SEASONAL SEA ICE ZONES OF THE NORTHERN HEMISPHERE USING MODIS DATA
THIN ICE AREA EXTRACTION IN THE SEASONAL SEA ICE ZONES OF THE NORTHERN HEMISPHERE USING MODIS DATA K. Hayashi 1, K. Naoki 1, K. Cho 1 *, 1 Tokai University, 2-28-4, Tomigaya, Shibuya-ku, Tokyo, Japan,
Arctic Regional Ocean Observing System Arctic ROOS Report from 2012
Arctic Regional Ocean Observing System Arctic ROOS Report from 2012 By Stein Sandven Nansen Environmental and Remote Sensing Center (www.arctic-roos.org) Focus in 2012 1. Arctic Marine Forecasting Center
Floating Ice: Progress in Addressing Science Goals
Polar Floating Ice: Progress in Addressing Science Goals Stephen Howell 1, Leif Toudal Pedersen 2 and Roberto Saldo 3 1 Environment Canada, Climate Research Division, Toronto, Canada 2 Danish Meteorological
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
Detection, tracking and study of polar lows from satellites Leonid P. Bobylev
Detection, tracking and study of polar lows from satellites Leonid P. Bobylev Nansen Centre, St. Petersburg, Russia Nansen Centre, Bergen, Norway Polar lows and their general characteristics International
Product Validation Report Polar Ocean
Product Validation Report Polar Ocean Lars Stenseng PVR, Version 1.0 July 24, 2014 Product Validation Report - Polar Ocean Lars Stenseng National Space Institute PVR, Version 1.0, Kgs. Lyngby, July 24,
Is the Number of Icebergs Around Antarctica Really Increasing?
Is the Number of Icebergs Around Antarctica Really Increasing? David G. Long* and Jarom Ballantyne Brigham Young University 459 Clyde Building Provo UT 84601 long@ee.byu.edu Cheryl Bertoia U. S. National
Dual-Frequency Ku- Band Radar Mission Concept for Snow Mass
Dual-Frequency Ku- Band Radar Mission Concept for Snow Mass Chris Derksen Environment and Climate Change Canada Study Team: Climate Research Division/Meteorological Research Division, ECCC Canadian Space
History of Aerosol Remote Sensing. Mark Smithgall Maria Zatko 597K Spring 2009
History of Aerosol Remote Sensing Mark Smithgall Maria Zatko 597K Spring 2009 Aerosol Sources Anthropogenic Biological decomposition from fertilizer and sewage treatment (ex. ammonium) Combustion of fossil
CNES Activity Report. Patrice Henry - CNES WGCV Plenary # 41 Tokyo Sept. 5-7, Working Group on Calibration and Validation
Activity Report Patrice Henry - Tokyo Sept. 5-7, 2016 Working Group on Calibration and Validation SUMMARY Calibration Monitoring of in-flight Missions Preparation of future Missions Involvement in CEOS/WGCV
Radiative Climatology of the North Slope of Alaska and the Adjacent Arctic Ocean
Radiative Climatology of the North Slope of Alaska and the Adjacent Arctic Ocean C. Marty, R. Storvold, and X. Xiong Geophysical Institute University of Alaska Fairbanks, Alaska K. H. Stamnes Stevens Institute
MASTER'S THESIS. Sea Ice Monitoring in the Arctic Using Satellite SAR Images
MASTER'S THESIS 2007:221 CIV Sea Ice Monitoring in the Arctic Using Satellite SAR Images Johan Wåhlin Luleå University of Technology MSc Programmes in Engineering Space Engineering Department of Applied
Snow on sea ice retrieval using microwave radiometer data. Rasmus Tonboe and Lise Kilic Danish Meteorological Institute Observatoire de Paris
Snow on sea ice retrieval using microwave radiometer data Rasmus Tonboe and Lise Kilic Danish Meteorological Institute Observatoire de Paris We know something about snow The temperature gradient within
Determining the Impact of Sea Ice Thickness on the
US NAVAL RESEARCH LABORATORY FIVE YEAR RESEARCH OPTION Determining the Impact of Sea Ice Thickness on the Arctic s Naturally Changing Environment (DISTANCE) Co-PI s for NRL John Brozena, Joan Gardner (Marine
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
Observing Snow: Conventional Measurements, Satellite and Airborne Remote Sensing. Chris Derksen Climate Research Division, ECCC
Observing Snow: Conventional Measurements, Satellite and Airborne Remote Sensing Chris Derksen Climate Research Division, ECCC Outline Three Snow Lectures: 1. Why you should care about snow 2. How we measure
GEOG Lecture 8. Orbits, scale and trade-offs
Environmental Remote Sensing GEOG 2021 Lecture 8 Orbits, scale and trade-offs Orbits revisit Orbits geostationary (36 000 km altitude) polar orbiting (200-1000 km altitude) Orbits revisit Orbits geostationary
A two-season impact study of the Navy s WindSat surface wind retrievals in the NCEP global data assimilation system
A two-season impact study of the Navy s WindSat surface wind retrievals in the NCEP global data assimilation system Li Bi James Jung John Le Marshall 16 April 2008 Outline WindSat overview and working
Lectures 7 and 8: 14, 16 Oct Sea Surface Temperature
Lectures 7 and 8: 14, 16 Oct 2008 Sea Surface Temperature References: Martin, S., 2004, An Introduction to Ocean Remote Sensing, Cambridge University Press, 454 pp. Chapter 7. Robinson, I. S., 2004, Measuring
Variability of Sea Ice Extent Along The East Coast of Greenland
Variability of Sea Ice Extent Along The East Coast of Greenland 2013-06-01 Author: Isabella Grönfeldt Bachelor thesis, 15 hp Lund University Supervisors: Martin Nissen, Centre for Ocean and Ice, DMI Elna
Ice Station POLarstern (ISPOL 1)
Ice Station POLarstern (ISPOL 1) ANT XXI/2: 18.12003-8.2004 (51 days) (N.B.: Earlier start and extension of 10 days is highly desirable (70 days duration)) Overall Objective The main goal of this project
EVALUATION OF ARCTIC OPERATIONAL PASSIVE MICROWAVE PRODUCTS: A CASE STUDY IN THE BARENTS SEA DURING OCTOBER 2001
Ice in the Environment: Proceedings of the 16th IAHR International Symposium on Ice Dunedin, New Zealand, 2nd 6th December 2002 International Association of Hydraulic Engineering and Research EVALUATION
Atmospheric Lidar The Atmospheric Lidar (ATLID) is a high-spectral resolution lidar and will be the first of its type to be flown in space.
www.esa.int EarthCARE mission instruments ESA s EarthCARE satellite payload comprises four instruments: the Atmospheric Lidar, the Cloud Profiling Radar, the Multi-Spectral Imager and the Broad-Band Radiometer.
Lecture 4b: Meteorological Satellites and Instruments. Acknowledgement: Dr. S. Kidder at Colorado State Univ.
Lecture 4b: Meteorological Satellites and Instruments Acknowledgement: Dr. S. Kidder at Colorado State Univ. US Geostationary satellites - GOES (Geostationary Operational Environmental Satellites) US
Some NOAA Products that Address PSTG Satellite Observing Requirements. Jeff Key NOAA/NESDIS Madison, Wisconsin USA
Some NOAA Products that Address PSTG Satellite Observing Requirements Jeff Key NOAA/NESDIS Madison, Wisconsin USA WMO Polar Space Task Group, 4 th meeting, Greenbelt, 30 September 2014 Relevant Missions
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
Prospects of microwave remote sensing for snow hydrology
Hydrologie Applications of Space Technology (Proceedings of the Cocoa Beach Workshop, Florida, August 1985). IAHS Publ. no. 160,1986. Prospects of microwave remote sensing for snow hydrology HELMUT ROTT
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
Investigations into the Spatial Pattern of Annual and Interannual Snow Coverage of Brøgger Peninsula, Svalbard,
Investigations into the Spatial Pattern of Annual and Interannual Snow Coverage of Brøgger Peninsula, Svalbard, 2000-2007 Manfred F. Buchroithner Nadja Thieme Jack Kohler 6th ICA Mountain Cartography Workshop
Earth Exploration-Satellite Service (EESS)- Active Spaceborne Remote Sensing and Operations
Earth Exploration-Satellite Service (EESS)- Active Spaceborne Remote Sensing and Operations SRTM Radarsat JASON Seawinds TRMM Cloudsat Bryan Huneycutt (USA) Charles Wende (USA) WMO, Geneva, Switzerland
MULTISENSORY SATELLITE STUDY OF MESOSCALE CYCLONES OVER THE NORTHERN PACIFIC
MULTISENSORY SATELLITE STUDY OF MESOSCALE CYCLONES OVER THE NORTHERN PACIFIC 13B.2 Irina A. Gurvich *, Leonid M. Mitnik, Maia L. Mitnik, and Michael K. Pichugin V.I. Il ichev Pacific Oceanological Institute,
SPACEBORNE scatterometers are currently used to monitor
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, VOL. 35, NO. 5, SEPTEMBER 1997 1201 Azimuthal Modulation of C-Band Scatterometer Over Southern Ocean Sea Ice David S. Early, Student Member, IEEE, and
Sea Ice Observations: Where Would We Be Without the Arctic Observing Network? Jackie Richter-Menge ERDC-CRREL
Sea Ice Observations: Where Would We Be Without the Arctic Observing Network? Jackie Richter-Menge ERDC-CRREL Sea Ice Observations: Where Would We Be Without the Arctic Observing Network? Jackie Richter-Menge
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
Ice Surface temperatures, status and utility. Jacob Høyer, Gorm Dybkjær, Rasmus Tonboe and Eva Howe Center for Ocean and Ice, DMI
Ice Surface temperatures, status and utility Jacob Høyer, Gorm Dybkjær, Rasmus Tonboe and Eva Howe Center for Ocean and Ice, DMI Outline Motivation for IST data production IST from satellite Infrared Passive
GLOBAL SATELLITE OBSERVATION REQUIREMENTS FOR FLOATING ICE
GLOBAL SATELLITE OBSERVATION REQUIREMENTS FOR FLOATING ICE FOCUSING ON SYNTHETIC APERTURE RADAR MARCH 2014 JOHN C. FALKINGHAM Contact: John.Falkingham@rogers.com (Contract report for Environment Canada:
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),
EVALUATION OF WINDSAT SURFACE WIND DATA AND ITS IMPACT ON OCEAN SURFACE WIND ANALYSES AND NUMERICAL WEATHER PREDICTION
5.8 EVALUATION OF WINDSAT SURFACE WIND DATA AND ITS IMPACT ON OCEAN SURFACE WIND ANALYSES AND NUMERICAL WEATHER PREDICTION Robert Atlas* NOAA/Atlantic Oceanographic and Meteorological Laboratory, Miami,
SATELLITE DATA COLLECTION BY THE UPRM-TCESS SPACE INFORMATION LABORATORY
SATELLITE DATA COLLECTION BY THE UPRM-TCESS SPACE INFORMATION LABORATORY Visita a la Estación De Satélites De UPRM En el CID 16 sep. 4:30 pm Nos reuniremos al frente del CID. CID L-BAND ANTENNA Orbview
Snow thickness retrieval from L-band brightness temperatures: a model comparison
Annals of Glaciology 56(69) 2015 doi: 10.3189/2015AoG69A886 9 Snow thickness retrieval from L-band brightness temperatures: a model comparison Nina MAASS, 1 Lars KALESCHKE, 1 Xiangshan TIAN-KUNZE, 1 Rasmus
Sea Ice Lecture Notes ESS 431. Bonnie Light Polar Science Center / Applied Physics Lab 11/26/18, 11/28/18
Sea Ice Lecture Notes ESS 431 Bonnie Light Polar Science Center / Applied Physics Lab bonnie@apl.washington.edu 11/26/18, 11/28/18 What is sea ice? - Frozen ocean water - Forms, grows, melts in the ocean
Calibrating SeaWinds and QuikSCAT scatterometers using natural land targets
Brigham Young University BYU ScholarsArchive All Faculty Publications 2005-04-01 Calibrating SeaWinds and QuikSCAT scatterometers using natural land targets David G. Long david_long@byu.edu Lucas B. Kunz
Remote Sensing in Meteorology: Satellites and Radar. AT 351 Lab 10 April 2, Remote Sensing
Remote Sensing in Meteorology: Satellites and Radar AT 351 Lab 10 April 2, 2008 Remote Sensing Remote sensing is gathering information about something without being in physical contact with it typically
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
Ku-band radar penetration into snow cover on Arctic sea ice using airborne data
Annals of Glaciology 52(57) 2011 197 Ku-band radar penetration into snow cover on Arctic sea ice using airborne data Rosemary WILLATT, 1 Seymour LAXON, 1 Katharine GILES, 1 Robert CULLEN, 2 Christian HAAS,
Land Surface Temperature Measurements From the Split Window Channels of the NOAA 7 Advanced Very High Resolution Radiometer John C.
Land Surface Temperature Measurements From the Split Window Channels of the NOAA 7 Advanced Very High Resolution Radiometer John C. Price Published in the Journal of Geophysical Research, 1984 Presented
Sea ice as a key climate indicator in the Arctic
Sea ice as a key climate indicator in the Arctic Leif Toudal Pedersen, DMI Natalia Ivanova, NERSC Eero Rinne, FMI Roberto Saldo, DTU Georg Heygster, U-Bremen Rasmus Tonboe, DMI Thomas Lavergne, Met Norway
Ice sheet mass balance from satellite altimetry. Kate Briggs (Mal McMillan)
Ice sheet mass balance from satellite altimetry Kate Briggs (Mal McMillan) Outline Background Recap 25 year altimetry record Recap Measuring surface elevation with altimetry Measuring surface elevation
China France. Oceanography S A T. The CFOSAT project. e l l i t e. C. Tison (1), D. Hauser (2), A. Mouche (3) CNES, France (2)
China France The CFOSAT project C. Tison (1), D. Hauser (2), A. Mouche (3) (1) CNES, France (2) OVSQ, CNRS, LATMOS-IPSL, France (3) IFREMER, LOS, France celine.tison@cnes.fr Oceanography S A T e l l i
Towards the use of SAR observations from Sentinel-1 to study snowpack properties in Alpine regions
Towards the use of SAR observations from Sentinel-1 to study snowpack properties in Alpine regions Gaëlle Veyssière, Fatima Karbou, Samuel Morin et Vincent Vionnet CNRM-GAME /Centre d Etude de la Neige
Investigations of the Dry Snow Zone of the Greenland Ice Sheet Using QuikSCAT. Kevin R. Moon
Investigations of the Dry Snow Zone of the Greenland Ice Sheet Using QuikSCAT Kevin R. Moon A thesis submitted to the faculty of Brigham Young University in partial fulfillment of the requirements for
sentinel-3 A BIGGER PICTURE FOR COPERNICUS
sentinel-3 A BIGGER PICTURE FOR COPERNICUS SATELLITES TO SERVE By providing a set of key information services for a wide range of practical applications, Europe s Copernicus programme has been put in place
Joint Polar Satellite System. 3 rd Post-EPS User Consultation Workshop Mike Haas
3 rd Post-EPS User Consultation Workshop Mike Haas Overview Introduction - Policy Drivers - Management System Description - Space Segment - Ground Segment Partnerships Status Benefits 2 Introduction (Policy
LEGOS Altimetric Sea Ice Thickness Data Product v1.0
LEGOS Altimetric Sea Ice Thickness Data Product v1.0 (a) Ice thickness c2 02/2015 (m) 3.24 2.88 2.52 2.16 1.80 1.44 1.08 0.72 0.36 0.00 Authors: Kevin Guerreiro & Sara Fleury September 2017 (b) Incertitude
Ice, Cloud, and land Elevation Satellite (ICESat) over Arctic sea ice: Retrieval of freeboard
Click Here for Full Article JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 112,, doi:1.129/26jc3978, 27 Ice, Cloud, and land Elevation Satellite (ICESat) over Arctic sea ice: Retrieval of freeboard R. Kwok, 1 G.