Multiangle cloud remote sensing from
|
|
|
- Alaina Emma Conley
- 10 years ago
- Views:
Transcription
1 Multiangle cloud remote sensing from POLDER3/PARASOL Cloud phase, optical thickness and albedo F. Parol, J. Riedi, S. Zeng, C. Vanbauce, N. Ferlay, F. Thieuleux, L.C. Labonnote and C. Cornet Laboratoire d'optique Atmosphérique, Université des Sciences et Technologies de Lille 1/27
2 Instrumental Background CNES/LOA instrument, Parasol launched Dec ~ 705 km polar orbits, ascending (13:30 a.m.) Data available from March 2005 to Jan 2010 within A-TRAIN and more Sensor Characteristics 10 spectral bands ranging from to µm 3 polarised channels Wide FOV CCD Camera with 1800 km swath width +/- 43 degrees cross track +/- 51degrees along track Multidirectionnal observations (up to 16 directions) Spatial resolution : 6x7 km No onboard calibration system - Inflight vicarious calibration : 2-3% absolute calibration accuracy 1% interband 0.1% interpixel over clouds 2/27
3 ERB, WV and Clouds Level 2 processing scheme Level 1 georeferenced data Int. Sinusoidal grid 6km x 6km Gazeous absorption correction Clear sky only Cloud detection Water vapor content Cloud phase Ice only Cloud Optical Thickness and spectral albedo SW albedo integration Microphysical index from polarisation Rayleigh and Oxygen cloud pressure Level 2 gridded product Int. Sinusoidal 20km x 20km Apparent pressure determination 3/27
4 Multiangle polarisation measurements and Cloud Phase Liquid Ice 4/27
5 MODIS/Aqua and PARASOL Observation of Clouds and Aerosols Properties MODIS Sci. Team Meeting Oct Multiangle polarisation measurements and Cloud Phase Cloud phase at 20x20 km resolution Liquid, Ice, Mixed, Unknow with individual quality index within each. 5/30
6 MODIS/Aqua and PARASOL Observation of Clouds and Aerosols Properties MODIS Sci. Team Meeting Oct Multiangle multispectral measurements Cloud optical thickness is retrieved under up to 16 directions Directional product provided at = 670nm (land) and 865 nm (ocean) 6/30
7 MODIS/Aqua and PARASOL Observation of Clouds and Aerosols Properties MODIS Sci. Team Meeting Oct Multiangle multispectral measurements Cloud spherical albedo is retrieved under up to 16 directions Directional product provided at = 670nm (land) and 865 nm (ocean) 7/30
8 Multiangle multispectral measurements λ = 443 nm nm 3 Spectral λ = 670 nm nm Cloud Albedo λ = 865 nm nm SW CLOUD ALBEDO 8/27
9 Analysis of cloud phase against MODIS and CALIOP 9/27
10 Cloud phase as seen by POLDER, MODIS & CALIOP Level 2 official data POLDER MODIS CALIOP PM dataset: (Level 2 of MODIS & POLDER data ) resolution : 20 x 20km2 sinusoidal grid MODIS averaged over POLDER pixel CALTRACK dataset: (Level 2 of MODIS, POLDER & CALIOP data ) resolution : 5km available through ICARE Data & Services Center lille1.fr Period: From 12/2007 to 11/ /27
11 MODIS / POLDER global match & mismatch Data: PM dataset, 12/ /2008, [90 S 90 N] 11/27
12 Geographical Distributions of Phase Frequency 4/10 Data: PM dataset, 12/ /2008, [90 S 90 N] 12/27
13 5/10 View zenith angle analysis of Phase detection Data: PM dataset, 12/ /2008, [90 S 90 N] CALIOP SAMPLING LOCATION 13/27
14 POLDER/MODIS phase in CALIOP space Data: CALTRACK dataset, 12/ /2008, [90 S 90 N] 14/27
15 POLDER/MODIS vs CALIOP phase product Data: CALTRACK dataset, 12/ /2008, [90 S 90 N] 15/27
16 Sensitivity to thin cirrus 16/27
17 Analysis of cloud optical thickness/albedo POLDER / MODIS 17/27
18 Measured reflectance (a1) SZA = deg (b1) SZA = deg 0.7 Measured Reflectance Measured Reflectance Retrieved albedo should be independant of viewing geometry Viewing Zenith Angle (deg) Viewing Zenith Angle (deg) Retrieved «directionnal» albedo (a2) SZA = deg (b2) SZA = deg 0.7 "Directional" Albedo 0.7 "Directional" Albedo Viewing Zenith Angle (deg) Retrieved «average» albedo Albedo RMS of : 0.8 (a3) SZA = deg (b3) SZA = deg 0.7 Averaged Albedo 0.6 Averaged Albedo Red : clouds Green : clear sky land Blue : clear sky ocean Viewing Zenith Angle (deg) Plots here for 2 sun elevations, as a function of view zenith angle for clouds in clear sky Viewing Zenith Angle (deg) Viewing Zenith Angle (deg) 18/27
19 Testing cloud models from multiangle observation 19/27
20 Testing cloud models from multiangle observation Baran & Labonnote (2001) 20/27
21 From Zhang et al, 2009 (ACP) 21/27
22 From Zhang et al, 2009 (ACP) 22/27
23 POLDER vs MODIS Optical thickness for different phase categories 23/27
24 POLDER vs MODIS Scaled Optical thickness for different phase categories 24/27
25 Optical thickness and scaled optical thickness zonal variation 25/27
26 View zenith angle analysis MODIS POLDER 26/27
27 Summary POLDER phase product provides a reliable information on thermodynamic phase independant of cloud temperature and particle size In conjunction, POLDER and MODIS can be used to create a reference cloud phase dataset for benchmark studies of models or other sensors POLDER multiangle observations provide a unique way to constrain cloud models (micro and macro physics) and get «less biased» optical thickness/albedo Comparing scaled optical thickness (or albedo) can make our life easier in a first stage for this GEWEX exercise 27/27
Remote Sensing of Clouds from Polarization
Remote Sensing of Clouds from Polarization What polarization can tell us about clouds... and what not? J. Riedi Laboratoire d'optique Atmosphérique University of Science and Technology Lille / CNRS FRANCE
Cloud Oxygen Pressure Algorithm for POLDER-2
Cloud Oxygen ressure Algorithm for OLDER-2 1/7 Cloud Oxygen ressure Algorithm for OLDER-2 Aim of the : Determination of cloud gen pressure from arent pressure by removing the contribution. Date of the
Studying cloud properties from space using sounder data: A preparatory study for INSAT-3D
Studying cloud properties from space using sounder data: A preparatory study for INSAT-3D Munn V. Shukla and P. K. Thapliyal Atmospheric Sciences Division Atmospheric and Oceanic Sciences Group Space Applications
Electromagnetic Radiation (EMR) and Remote Sensing
Electromagnetic Radiation (EMR) and Remote Sensing 1 Atmosphere Anything missing in between? Electromagnetic Radiation (EMR) is radiated by atomic particles at the source (the Sun), propagates through
Passive Remote Sensing of Clouds from Airborne Platforms
Passive Remote Sensing of Clouds from Airborne Platforms Why airborne measurements? My instrument: the Solar Spectral Flux Radiometer (SSFR) Some spectrometry/radiometry basics How can we infer cloud properties
Retrieval of cloud spherical albedo from top-of-atmosphere reflectance measurements performed at a single observation angle
Atmos. Chem. Phys., 7, 3633 3637, 2007 Author(s) 2007. This work is licensed under a Creative Commons License. Atmospheric Chemistry and Physics Retrieval of cloud from top-of-atmosphere reflectance measurements
Comparison of NOAA's Operational AVHRR Derived Cloud Amount to other Satellite Derived Cloud Climatologies.
Comparison of NOAA's Operational AVHRR Derived Cloud Amount to other Satellite Derived Cloud Climatologies. Sarah M. Thomas University of Wisconsin, Cooperative Institute for Meteorological Satellite Studies
Evaluation of the Effect of Upper-Level Cirrus Clouds on Satellite Retrievals of Low-Level Cloud Droplet Effective Radius
Evaluation of the Effect of Upper-Level Cirrus Clouds on Satellite Retrievals of Low-Level Cloud Droplet Effective Radius F.-L. Chang and Z. Li Earth System Science Interdisciplinary Center University
MOD09 (Surface Reflectance) User s Guide
MOD09 (Surface ) User s Guide MODIS Land Surface Science Computing Facility Principal Investigator: Dr. Eric F. Vermote Web site: http://modis-sr.ltdri.org Correspondence e-mail address: [email protected]
Measurement of the effect of biomass burning aerosol on inhibition of cloud formation over the Amazon
Supporting Online Material for Koren et al. Measurement of the effect of biomass burning aerosol on inhibition of cloud formation over the Amazon 1. MODIS new cloud detection algorithm The operational
GOES-R AWG Cloud Team: ABI Cloud Height
GOES-R AWG Cloud Team: ABI Cloud Height June 8, 2010 Presented By: Andrew Heidinger 1 1 NOAA/NESDIS/STAR 1 Outline Executive Summary Algorithm Description ADEB and IV&V Response Summary Requirements Specification
Cloud Climatology for New Zealand and Implications for Radiation Fields
Cloud Climatology for New Zealand and Implications for Radiation Fields G. Pfister, R.L. McKenzie, J.B. Liley, A. Thomas National Institute of Water and Atmospheric Research, Lauder, New Zealand M.J. Uddstrom
16 th IOCCG Committee annual meeting. Plymouth, UK 15 17 February 2011. mission: Present status and near future
16 th IOCCG Committee annual meeting Plymouth, UK 15 17 February 2011 The Meteor 3M Mt satellite mission: Present status and near future plans MISSION AIMS Satellites of the series METEOR M M are purposed
ARM SWS to study cloud drop size within the clear-cloud transition zone
ARM SWS to study cloud drop size within the clear-cloud transition zone (GSFC) Yuri Knyazikhin Boston University Christine Chiu University of Reading Warren Wiscombe GSFC Thanks to Peter Pilewskie (UC)
Sky Monitoring Techniques using Thermal Infrared Sensors. sabino piazzolla Optical Communications Group JPL
Sky Monitoring Techniques using Thermal Infrared Sensors sabino piazzolla Optical Communications Group JPL Atmospheric Monitoring The atmospheric channel has a great impact on the channel capacity at optical
FRESCO. Product Specification Document FRESCO. Authors : P. Wang, R.J. van der A (KNMI) REF : TEM/PSD2/003 ISSUE : 3.0 DATE : 30.05.
PAGE : 1/11 TITLE: Product Specification Authors : P. Wang, R.J. van der A (KNMI) PAGE : 2/11 DOCUMENT STATUS SHEET Issue Date Modified Items / Reason for Change 0.9 19.01.06 First Version 1.0 22.01.06
Advances in Cloud Imager Remote Sensing
Advances in Cloud Imager Remote Sensing Andrew Heidinger NOAA/NESDIS/ORA Madison, Wisconsin With material from Mike Pavolonis, Robert Holz, Amato Evan and Fred Nagle STAR Science Symposium November 9,
CALIPSO, CloudSat, CERES, and MODIS Merged Data Product
CALIPSO, CloudSat, CERES, and MODIS Merged Data Product Seiji Kato 1, Sunny Sun-Mack 2, Walter F. Miller 2, Fred G. Rose 2, and Victor E. Sothcott 2 1 NASA Langley Research Center 2 Science and Systems
SATELLITE OBSERVATION OF THE DAILY VARIATION OF THIN CIRRUS
SATELLITE OBSERVATION OF THE DAILY VARIATION OF THIN CIRRUS Hermann Mannstein and Stephan Kox ATMOS 2012 Bruges, 2012-06-21 Folie 1 Why cirrus? Folie 2 Warum Eiswolken? Folie 3 Folie 4 Folie 5 Folie 6
Retrieval of vertical cloud properties of deepconvective clouds by spectral radiance measurements
Faculty of Physics and Earth Sciences Retrieval of vertical cloud properties of deepconvective clouds by spectral radiance measurements Tobias Zinner Evi Jäkel, Sandra Kanter, Florian Ewald, Tobias Kölling
Comparison of Cloud and Radiation Variability Reported by Surface Observers, ISCCP, and ERBS
Comparison of Cloud and Radiation Variability Reported by Surface Observers, ISCCP, and ERBS Joel Norris (SIO/UCSD) Cloud Assessment Workshop April 5, 2005 Outline brief satellite data description upper-level
Best practices for RGB compositing of multi-spectral imagery
Best practices for RGB compositing of multi-spectral imagery User Service Division, EUMETSAT Introduction Until recently imagers on geostationary satellites were limited to 2-3 spectral channels, i.e.
'Developments and benefits of hydrographic surveying using multispectral imagery in the coastal zone
Abstract With the recent launch of enhanced high-resolution commercial satellites, available imagery has improved from four-bands to eight-band multispectral. Simultaneously developments in remote sensing
A climatology of cirrus clouds from ground-based lidar measurements over Lille
A climatology of cirrus clouds from ground-based lidar measurements over Lille Rita Nohra, Frédéric Parol, Philippe Dubuisson Laboratoire d Optique Atmosphérique université de Lille, CNRS UMR 8518 Objectives
VIIRS-CrIS mapping. NWP SAF AAPP VIIRS-CrIS Mapping
NWP SAF AAPP VIIRS-CrIS Mapping This documentation was developed within the context of the EUMETSAT Satellite Application Facility on Numerical Weather Prediction (NWP SAF), under the Cooperation Agreement
Validation of SEVIRI cloud-top height retrievals from A-Train data
Validation of SEVIRI cloud-top height retrievals from A-Train data Chu-Yong Chung, Pete N Francis, and Roger Saunders Contents Introduction MO GeoCloud AVAC-S Long-term monitoring Comparison with OCA Summary
Cloud Masking and Cloud Products
Cloud Masking and Cloud Products MODIS Operational Algorithm MOD35 Paul Menzel, Steve Ackerman, Richard Frey, Kathy Strabala, Chris Moeller, Liam Gumley, Bryan Baum MODIS Cloud Masking Often done with
Remote sensing of precipitable water vapour and cloud cover for site selection of the European Extremely Large Telescope (E-ELT) using MERIS
Remote sensing of precipitable water vapour and cloud cover for site selection of the European Extremely Large Telescope (E-ELT) using MERIS H. Kurlandczyk 1 M.Sarazin 1 1 European Organisation for Astronomical
Volcanic Ash Monitoring: Product Guide
Doc.No. Issue : : EUM/TSS/MAN/15/802120 v1a EUMETSAT Eumetsat-Allee 1, D-64295 Darmstadt, Germany Tel: +49 6151 807-7 Fax: +49 6151 807 555 Date : 2 June 2015 http://www.eumetsat.int WBS/DBS : EUMETSAT
MSG-SEVIRI cloud physical properties for model evaluations
Rob Roebeling Weather Research Thanks to: Hartwig Deneke, Bastiaan Jonkheid, Wouter Greuell, Jan Fokke Meirink and Erwin Wolters (KNMI) MSG-SEVIRI cloud physical properties for model evaluations Cloud
Evaluations of the CALIPSO Cloud Optical Depth Algorithm Through Comparisons with a GOES Derived Cloud Analysis
Generated using V3.0 of the official AMS LATEX template Evaluations of the CALIPSO Cloud Optical Depth Algorithm Through Comparisons with a GOES Derived Cloud Analysis Katie Carbonari, Heather Kiley, and
An Airborne A-Band Spectrometer for Remote Sensing Of Aerosol and Cloud Optical Properties
An Airborne A-Band Spectrometer for Remote Sensing Of Aerosol and Cloud Optical Properties Michael Pitts, Chris Hostetler, Lamont Poole, Carl Holden, and Didier Rault NASA Langley Research Center, MS 435,
Total radiative heating/cooling rates.
Lecture. Total radiative heating/cooling rates. Objectives:. Solar heating rates.. Total radiative heating/cooling rates in a cloudy atmosphere.. Total radiative heating/cooling rates in different aerosol-laden
Obtaining and Processing MODIS Data
Obtaining and Processing MODIS Data MODIS is an extensive program using sensors on two satellites that each provide complete daily coverage of the earth. The data have a variety of resolutions; spectral,
Clouds and the Energy Cycle
August 1999 NF-207 The Earth Science Enterprise Series These articles discuss Earth's many dynamic processes and their interactions Clouds and the Energy Cycle he study of clouds, where they occur, and
Saharan Dust Aerosols Detection Over the Region of Puerto Rico
1 Saharan Dust Aerosols Detection Over the Region of Puerto Rico ARLENYS RAMÍREZ University of Puerto Rico at Mayagüez, P.R., 00683. Email:[email protected] ABSTRACT. Every year during the months
Assessing Cloud Spatial and Vertical Distribution with Infrared Cloud Analyzer
Assessing Cloud Spatial and Vertical Distribution with Infrared Cloud Analyzer I. Genkova and C. N. Long Pacific Northwest National Laboratory Richland, Washington T. Besnard ATMOS SARL Le Mans, France
Towards assimilating IASI satellite observations over cold surfaces - the cloud detection aspect
Towards assimilating IASI satellite observations over cold surfaces - the cloud detection aspect Tuuli Perttula, FMI + Thanks to: Nadia Fourrié, Lydie Lavanant, Florence Rabier and Vincent Guidard, Météo
Physical properties of mesoscale high-level cloud systems in relation to their atmospheric environment deduced from Sounders
Physical properties of mesoscale high-level cloud systems in relation to their atmospheric environment deduced from Sounders Claudia Stubenrauch, Sofia Protopapadaki, Artem Feofilov, Theodore Nicolas &
CERES Edition 2 & Edition 3 Cloud Cover, Cloud Altitude and Temperature
CERES Edition 2 & Edition 3 Cloud Cover, Cloud Altitude and Temperature S. Sun-Mack 1, P. Minnis 2, Y. Chen 1, R. Smith 1, Q. Z. Trepte 1, F. -L. Chang, D. Winker 2 (1) SSAI, Hampton, VA (2) NASA Langley
SAMPLE MIDTERM QUESTIONS
Geography 309 Sample MidTerm Questions Page 1 SAMPLE MIDTERM QUESTIONS Textbook Questions Chapter 1 Questions 4, 5, 6, Chapter 2 Questions 4, 7, 10 Chapter 4 Questions 8, 9 Chapter 10 Questions 1, 4, 7
Data processing (3) Cloud and Aerosol Imager (CAI)
Data processing (3) Cloud and Aerosol Imager (CAI) 1) Nobuyuki Kikuchi, 2) Haruma Ishida, 2) Takashi Nakajima, 3) Satoru Fukuda, 3) Nick Schutgens, 3) Teruyuki Nakajima 1) National Institute for Environmental
Microwave observations in the presence of cloud and precipitation
Microwave observations in the presence of cloud and precipitation Alan Geer Thanks to: Bill Bell, Peter Bauer, Fabrizio Baordo, Niels Bormann Slide 1 ECMWF/EUMETSAT satellite course 2015: Microwave 2 Slide
A review of cloud top height and optical depth histograms from MISR, ISCCP, and MODIS
JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 115,, doi:10.1029/2009jd013422, 2010 A review of cloud top height and optical depth histograms from MISR, ISCCP, and MODIS Roger Marchand, 1 Thomas Ackerman, 1 Mike
Climatology of aerosol and cloud properties at the ARM sites:
Climatology of aerosol and cloud properties at the ARM sites: MFRSR combined with other measurements Qilong Min ASRC, SUNY at Albany MFRSR: Spectral irradiances at 6 six wavelength passbands: 415, 500,
DISCRIMINATING CLEAR-SKY FROM CLOUD WITH MODIS ALGORITHM THEORETICAL BASIS DOCUMENT (MOD35) MODIS Cloud Mask Team
DISCRIMINATING CLEAR-SKY FROM CLOUD WITH MODIS ALGORITHM THEORETICAL BASIS DOCUMENT (MOD35) MODIS Cloud Mask Team Steve Ackerman, Richard Frey, Kathleen Strabala, Yinghui Liu, Liam Gumley, Bryan Baum,
Realization of a UV fisheye hyperspectral camera
Realization of a UV fisheye hyperspectral camera Valentina Caricato, Andrea Egidi, Marco Pisani and Massimo Zucco, INRIM Outline Purpose of the instrument Required specs Hyperspectral technique Optical
Satellite Remote Sensing of Volcanic Ash
Marco Fulle www.stromboli.net Satellite Remote Sensing of Volcanic Ash Michael Pavolonis NOAA/NESDIS/STAR SCOPE Nowcasting 1 Meeting November 19 22, 2013 1 Outline Getty Images Volcanic ash satellite remote
Night Microphysics RGB Nephanalysis in night time
Copyright, JMA Night Microphysics RGB Nephanalysis in night time Meteorological Satellite Center, JMA What s Night Microphysics RGB? R : B15(I2 12.3)-B13(IR 10.4) Range : -4 2 [K] Gamma : 1.0 G : B13(IR
CBERS Program Update Jacie 2011. Frederico dos Santos Liporace AMS Kepler [email protected]
CBERS Program Update Jacie 2011 Frederico dos Santos Liporace AMS Kepler [email protected] Overview CBERS 3 and 4 characteristics Differences from previous CBERS satellites (CBERS 1/2/2B) Geometric
Labs in Bologna & Potenza Menzel. Lab 3 Interrogating AIRS Data and Exploring Spectral Properties of Clouds and Moisture
Labs in Bologna & Potenza Menzel Lab 3 Interrogating AIRS Data and Exploring Spectral Properties of Clouds and Moisture Figure 1: High resolution atmospheric absorption spectrum and comparative blackbody
ESCI 107/109 The Atmosphere Lesson 2 Solar and Terrestrial Radiation
ESCI 107/109 The Atmosphere Lesson 2 Solar and Terrestrial Radiation Reading: Meteorology Today, Chapters 2 and 3 EARTH-SUN GEOMETRY The Earth has an elliptical orbit around the sun The average Earth-Sun
Hyperspectral Satellite Imaging Planning a Mission
Hyperspectral Satellite Imaging Planning a Mission Victor Gardner University of Maryland 2007 AIAA Region 1 Mid-Atlantic Student Conference National Institute of Aerospace, Langley, VA Outline Objective
3.4 Cryosphere-related Algorithms
3.4 Cryosphere-related Algorithms GLI Algorithm Description 3.4.-1 3.4.1 CTSK1 A. Algorithm Outline (1) Algorithm Code: CTSK1 (2) Product Code: CLFLG_p (3) PI Name: Dr. Knut Stamnes (4) Overview of Algorithm
Global Moderate Resolution Imaging Spectroradiometer (MODIS) cloud detection and height evaluation using CALIOP
Click Here for Full Article JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 113,, doi:10.1029/2008jd009837, 2008 Global Moderate Resolution Imaging Spectroradiometer (MODIS) cloud detection and height evaluation
Data Processing Flow Chart
Legend Start V1 V2 V3 Completed Version 2 Completion date Data Processing Flow Chart Data: Download a) AVHRR: 1981-1999 b) MODIS:2000-2010 c) SPOT : 1998-2002 No Progressing Started Did not start 03/12/12
China Earth Observation
China High-resolution Earth Observation China Earth Observation System (CHEOS) and its Lastest Development The Earth Observation System and Data Center, CNSA 2014-2 Outlines 1 Introduction 2 The composition
2.3 Spatial Resolution, Pixel Size, and Scale
Section 2.3 Spatial Resolution, Pixel Size, and Scale Page 39 2.3 Spatial Resolution, Pixel Size, and Scale For some remote sensing instruments, the distance between the target being imaged and the platform,
Cloud detection and clearing for the MOPITT instrument
Cloud detection and clearing for the MOPITT instrument Juying Warner, John Gille, David P. Edwards and Paul Bailey National Center for Atmospheric Research, Boulder, Colorado ABSTRACT The Measurement Of
Technical note on MISR Cloud-Top-Height Optical-depth (CTH-OD) joint histogram product
Technical note on MISR Cloud-Top-Height Optical-depth (CTH-OD) joint histogram product 1. Intend of this document and POC 1.a) General purpose The MISR CTH-OD product contains 2D histograms (joint distributions)
Examination Space Missions and Applications I (AE2103) Faculty of Aerospace Engineering Delft University of Technology SAMPLE EXAM
Examination Space Missions and Applications I AE2103 Faculty of Aerospace Engineering Delft University of Technology SAMPLE EXAM Please read these instructions first: This are a series of multiple-choice
Blackbody radiation. Main Laws. Brightness temperature. 1. Concepts of a blackbody and thermodynamical equilibrium.
Lecture 4 lackbody radiation. Main Laws. rightness temperature. Objectives: 1. Concepts of a blackbody, thermodynamical equilibrium, and local thermodynamical equilibrium.. Main laws: lackbody emission:
Evaluating GCM clouds using instrument simulators
Evaluating GCM clouds using instrument simulators University of Washington September 24, 2009 Why do we care about evaluation of clouds in GCMs? General Circulation Models (GCMs) project future climate
The Effect of Droplet Size Distribution on the Determination of Cloud Droplet Effective Radius
Eleventh ARM Science Team Meeting Proceedings, Atlanta, Georgia, March 9-, The Effect of Droplet Size Distribution on the Determination of Cloud Droplet Effective Radius F.-L. Chang and Z. Li ESSIC/Department
REMOTE SENSING OF CLOUD-AEROSOL RADIATIVE EFFECTS FROM SATELLITE DATA: A CASE STUDY OVER THE SOUTH OF PORTUGAL
REMOTE SENSING OF CLOUD-AEROSOL RADIATIVE EFFECTS FROM SATELLITE DATA: A CASE STUDY OVER THE SOUTH OF PORTUGAL D. Santos (1), M. J. Costa (1,2), D. Bortoli (1,3) and A. M. Silva (1,2) (1) Évora Geophysics
Reprojecting MODIS Images
Reprojecting MODIS Images Why Reprojection? Reasons why reprojection is desirable: 1. Removes Bowtie Artifacts 2. Allows geographic overlays (e.g. coastline, city locations) 3. Makes pretty pictures for
The APOLLO cloud product statistics Web service The APOLLO cloud product statistics Web service
The APOLLO cloud product statistics Web service Introduction DLR and Transvalor are preparing a new Web service to disseminate the statistics of the APOLLO cloud physical parameters as a further help in
Level 3 Cloud Fraction by Altitude Algorithm Theoretical Basis
JPL D-62358 Earth Observing System Level 3 Cloud Fraction by Altitude Algorithm Theoretical Basis Larry Di Girolamo 1 Alex Menzies 2 Guangyu Zhao 1 Kevin Mueller 2 Catherine Moroney 2 David J. Diner 2
LANDSAT 8 Level 1 Product Performance
Réf: IDEAS-TN-10-QualityReport LANDSAT 8 Level 1 Product Performance Quality Report Month/Year: January 2016 Date: 26/01/2016 Issue/Rev:1/9 1. Scope of this document On May 30, 2013, data from the Landsat
Overview. What is EMR? Electromagnetic Radiation (EMR) LA502 Special Studies Remote Sensing
LA502 Special Studies Remote Sensing Electromagnetic Radiation (EMR) Dr. Ragab Khalil Department of Landscape Architecture Faculty of Environmental Design King AbdulAziz University Room 103 Overview What
Fourth Cloud Retrieval Evaluation Workshop 4-7 March 2014, Grainau, Germany
Extending error characterization of cloud masking: Exploring the validity and usefulness of the SPARC-type and Naïve Bayesian probabilistic cloud masking methods Fourth Cloud Retrieval Evaluation Workshop
The study of cloud and aerosol properties during CalNex using newly developed spectral methods
The study of cloud and aerosol properties during CalNex using newly developed spectral methods Patrick J. McBride, Samuel LeBlanc, K. Sebastian Schmidt, Peter Pilewskie University of Colorado, ATOC/LASP
Spectral Response for DigitalGlobe Earth Imaging Instruments
Spectral Response for DigitalGlobe Earth Imaging Instruments IKONOS The IKONOS satellite carries a high resolution panchromatic band covering most of the silicon response and four lower resolution spectral
Lake Monitoring in Wisconsin using Satellite Remote Sensing
Lake Monitoring in Wisconsin using Satellite Remote Sensing D. Gurlin and S. Greb Wisconsin Department of Natural Resources 2015 Wisconsin Lakes Partnership Convention April 23 25, 2105 Holiday Inn Convention
The APOLLO cloud product statistics Web service
The APOLLO cloud product statistics Web service Introduction DLR and Transvalor are preparing a new Web service to disseminate the statistics of the APOLLO cloud physical parameters as a further help in
Fig.1. The DAWN spacecraft
Introduction Optical calibration of the DAWN framing cameras G. Abraham,G. Kovacs, B. Nagy Department of Mechatronics, Optics and Engineering Informatics Budapest University of Technology and Economics
Lectures Remote Sensing
Lectures Remote Sensing ATMOSPHERIC CORRECTION dr.ir. Jan Clevers Centre of Geo-Information Environmental Sciences Wageningen UR Atmospheric Correction of Optical RS Data Background When needed? Model
Generation of Cloud-free Imagery Using Landsat-8
Generation of Cloud-free Imagery Using Landsat-8 Byeonghee Kim 1, Youkyung Han 2, Yonghyun Kim 3, Yongil Kim 4 Department of Civil and Environmental Engineering, Seoul National University (SNU), Seoul,
WATER BODY EXTRACTION FROM MULTI SPECTRAL IMAGE BY SPECTRAL PATTERN ANALYSIS
WATER BODY EXTRACTION FROM MULTI SPECTRAL IMAGE BY SPECTRAL PATTERN ANALYSIS Nguyen Dinh Duong Department of Environmental Information Study and Analysis, Institute of Geography, 18 Hoang Quoc Viet Rd.,
A remote sensing instrument collects information about an object or phenomenon within the
Satellite Remote Sensing GE 4150- Natural Hazards Some slides taken from Ann Maclean: Introduction to Digital Image Processing Remote Sensing the art, science, and technology of obtaining reliable information
Radiative effects of clouds, ice sheet and sea ice in the Antarctic
Snow and fee Covers: Interactions with the Atmosphere and Ecosystems (Proceedings of Yokohama Symposia J2 and J5, July 1993). IAHS Publ. no. 223, 1994. 29 Radiative effects of clouds, ice sheet and sea
RESULTS FROM A SIMPLE INFRARED CLOUD DETECTOR
RESULTS FROM A SIMPLE INFRARED CLOUD DETECTOR A. Maghrabi 1 and R. Clay 2 1 Institute of Astronomical and Geophysical Research, King Abdulaziz City For Science and Technology, P.O. Box 6086 Riyadh 11442,
SPOT Satellite Earth Observation System Presentation to the JACIE Civil Commercial Imagery Evaluation Workshop March 2007
SPOT Satellite Earth Observation System Presentation to the JACIE Civil Commercial Imagery Evaluation Workshop March 2007 Topics Presented Quick summary of system characteristics Formosat-2 Satellite Archive
Sentinel-1 Mission Overview
Sentinel-1 Mission Overview Pierre Potin Sentinel-1 Mission Manager, ESA Advanced Course on Radar Polarimetry ESRIN, Frascati, 19 January 2011 Global Monitoring for Environment and Security GMES is established
Computer Vision: Machine Vision Filters. Computer Vision. Optical Filters. 25 August 2014
Computer Vision Optical Filters 25 August 2014 Copyright 2001 2014 by NHL Hogeschool, Van de Loosdrecht Machine Vision BV and Klaas Dijkstra All rights reserved [email protected], [email protected],
The Sentinel-4/UVN instrument on-board MTG-S
The Sentinel-4/UVN instrument on-board MTG-S Grégory Bazalgette Courrèges-Lacoste; Berit Ahlers; Benedikt Guldimann; Alex Short; Ben Veihelmann, Hendrik Stark ESA ESTEC European Space Technology & Research
RPG MWR PRO TN03 2012 09 Page 1 / 12 www.radiometer physics.de Radiometer Physics GmbH +49 2225 99981 0
Applications Tropospheric profiling of temperature, humidity and liquid water High resolution boundary layer temperature profiles, better resolution than balloons Input for weather and climate models (data
Surface Atmosphere Radia3on Budget (SARB) working group update
Surface Atmosphere Radia3on Budget (SARB) working group update Seiji Kato 1, Fred G. Rose 2, David A. Rutan 2, Alexander Radkevich 2, Thomas E. Caldwell 2, Antonio Viudez- Mora 2, Seung Hee Ham 2, and
Near Real Time Blended Surface Winds
Near Real Time Blended Surface Winds I. Summary To enhance the spatial and temporal resolutions of surface wind, the remotely sensed retrievals are blended to the operational ECMWF wind analyses over the
