Launch-Ready Operations Code Chain ESDT ShortNames, LongNames, and Generating PGE or Ingest Source
|
|
|
- Ophelia Fields
- 10 years ago
- Views:
Transcription
1 Launch-Ready Operations Code Chain ESDT ShortNames, LongNames, and Generating PGE or Ingest Source Generating PGE Name/Description or Ingest Source Product ESDT ShortName Product ESDT LongName NPP_VMAE_L1 VIIRS/NPP Moderate Resolution 5- Min L1 Swath SDR and Geo NPP_VIAE_L1 VIIRS/NPP Imagery Resolution 5- Min L1 Swath SDR 375m NPP_IMFT_L1 NPP_VDNE_L1 NPP_VOBCIP_L1 NPP_VCDGIP_L1 NPP_CMIP_L2 NPP_VAOT_L2 NPP_VAOTIP_L2 NPP_VAMIIP_L2 NPP_VSUM_L2 NPP_VCOPIP_L2 NPP_WCTTIP_L2 NPP_VSCD_L2 NPP_VSCM_L2 NPP_VIQIP_L2 VIIRS/NPP Imagery Resolution Terrain Corrected 5-Min L1 VIIRS/NPP Day/Night Band 5-Min L1 Swath SDR 375m (also contains VIIRS/NPP Day/Night Band Elliptical 5-Min L1 Swath IP 375m) VIIRS/NPP On Board Calibrator (OBC) IP VIIRS/NPP Calibrated Dual Gain Band IP VIIRS/NPP Cloud Mask 5-Min L2 Swath IP Thickness 5-Min L2 Swath EDR 6km Thickness 5-Min L2 Swath IP VIIRS/NPP Aerosol Model Information 5-Min L2 Swath IP VIIRS/NPP Suspended Matter 5-Min L2 Swath EDR VIIRS/NPP Cloud Optical Properties 5-Min L2 Swath IP VIIRS/NPP Ice & Night Water Cloud Top Temperature 5-Min L2 Swath IP VIIRS/NPP Snow Cover 5-Min L2 Swath EDR VIIRS/NPP Snow Cover Map 5-Min L2 Swath EDR 375m VIIRS/NPP Ice Quality 5-Min L2 NPP_VIWIP_L2 NPP_VSTIP_L2 NPP_VICIP_L2 NPP_VIRTIP_L2 VIIRS/NPP Ice Weights 5-Min L2 VIIRS/NPP Surface Temperature Ice 5-Min L2 VIIRS/NPP Ice Concentration 5-Min L2 VIIRS/NPP Ice Reflectance/Temperature 5-Min L2
2 NPP_VSIC_L2 VIIRS/NPP Sea Ice Characterization/Ice Age 5-Min L2 Swath EDR 375m NPP_SRFLIP_L2 VIIRS/NPP Land Surface Reflectance 5-Min L2 & (In EDR-IR; not produced in LPEATE unless requested) NPP_SRFLMIP_L2 VIIRS/NPP Surface Reflectance 5- Min L2 Swath IP NPP_SRFLIIP_L2 VIIRS/NPP Surface Reflectance 5- Min L2 PGE301 VIIRS L0 Verified RDR PGE302b VIIRS L1 SDR/Calibration PGE302b VIIRS L1 SDR/ Calibration PGE302b VIIRS L1 SDR/ Calibration NPP_VLST_L2 NPP_VSUT_L2 NPP_VLAIP_L2 NPP_VRVI_L2 NPP_VIST_L2 NPP_VIIRS_L0 NPP_IMFT_L1 NPP_IMGO_L1 NPP_UDGTGIP_L1 NPP_DNFT_L1 NPP_MOFT_L1 NPP_MDGO_L1 NPP_GRCDNE_L1 NPP_GRCIAE_L1 VIIRS/NPP Land Surface Temperature 5-Min L2 Swath EDR VIIRS/NPP Surface Type 5-Min L2 Swath EDR VIIRS/NPP Land Albedo 5-Min L2 Swath IP VIIRS/NPP Vegetation Index 5-Min L2 Swath EDR 375m VIIRS/NPP Ice Surface Temperature 5-Min L2 Swath EDR VIIRS/NPP Decompressed Raw Instrument Packets 5-Min L0 RDR VIIRS/NPP Imagery Resolution Terrain Corrected 5-Min L1 VIIRS/NPP Imagery Resolution 5-Min L1 Swath IP 375m VIIRS/NPP Unaggregated Dual Gain Band Elliptical 5-Min L1 Swath IP VIIRS/NPP Day/Night Band Elliptical 5-Min L1 Swath IP 375m VIIRS/NPP Moderate Resolution Terrain Corrected 5-Min L1 Swath IP VIIRS/NPP Moderate Resolution 5-Min L1 Swath IP Day/Night IP Imagery Resolution IP NPP_GRCMAE_L1 Moderate Resolution IP NPP_VIAE_L1 VIIRS/NPP Imagery Resolution 5- Min L1 Swath SDR 375m NPP_VMAE_L1 VIIRS/NPP Moderate Resolution 5- Min L1 Swath SDR and Geo (also contains VIIRS/NPP Moderate Resolution Terrain Corrected 5-Min L1 Swath IP ) NPP_VDNE_L1 VIIRS/NPP Day/Night Band 5-Min L1 Swath SDR 375m (also contains
3 PGE302b VIIRS L1 SDR/ Calibration PGE302b VIIRS L1 SDR/ Calibration PGE303 VIIRS L2 Cloud Mask PGE306 VIIRS L2 Cloud Optical Properties PGE306 VIIRS L2 Cloud Optical Properties PGE307 VIIRS L2 Snow Cover PGE307 VIIRS L2 Snow Cover PGE308 VIIRS L2 Ice Quality PGE308 VIIRS L2 Ice Quality PGE308 VIIRS L2 Ice Quality PGE309 VIIRS L2 Ice Concentration NPP_VOBCIP_L1 NPP_VCDGIP_L1 NPP_CMIP_L2 NPP_VCOPIP_L2 NPP_WCTTIP_L2 NPP_VSCD_L2 NPP_VSCM_L2 NPP_VIQIP_L2 NPP_VIWIP_L2 NPP_VSTIP_L2 NPP_VICIP_L2 VIIRS/NPP Day/Night Band Elliptical 5-Min L1 Swath IP 375m) VIIRS/NPP On Board Calibrator (OBC) IP VIIRS/NPP Calibrated Dual Gain Band IP VIIRS/NPP Cloud Mask 5-Min L2 Swath IP VIIRS/NPP Cloud Optical Properties 5-Min L2 Swath IP VIIRS/NPP Ice & Night Water Cloud Top Temperature 5-Min L2 Swath IP VIIRS/NPP Snow Cover 5-Min L2 Swath EDR VIIRS/NPP Snow Cover Map 5-Min L2 Swath EDR 375m VIIRS/NPP Ice Quality 5-Min L2 VIIRS/NPP Ice Weights 5-Min L2 VIIRS/NPP Surface Temperature Ice 5-Min L2 VIIRS/NPP Ice Concentration 5-Min L2 PGE309 VIIRS L2 Ice Concentration PGE310 VIIRS L2 Sea Ice Characterization/Ice Age PGE311 VIIRS L2 Land Surface Reflectance PGE311 VIIRS L2 Land Surface Reflectance PGE311 VIIRS L2 Land Surface Reflectance NPP_VIRTIP_L2 VIIRS/NPP Ice Reflectance/Temperature 5-Min L2 NPP_VSIC_L2 VIIRS/NPP Sea Ice Characterization/Ice Age 5-Min L2 Swath EDR 375m NPP_SRFLIP_L2 VIIRS/NPP Land Surface Reflectance 5-Min L2 & (In EDR-IR; not produced in LPEATE) NPP_SRFLMIP_L2 VIIRS/NPP Surface Reflectance 5- Min L2 Swath IP NPP_SRFLIIP_L2 VIIRS/NPP Surface Reflectance 5- Min L2 PGE312 VIIRS Area Weight Moderate Swath GridIP PGE313 VIIRS Daily Surface Reflectance Collection Gridding PGE314 VIIRS Snow/Ice Cover Gridding PGE316 VIIRS L2 Land Surface Temperature PGE317 VIIIRS 17_Day NBAR NDVI Gridding NPP_DAWIP_L2G NPP_DSRFIP_L3 VIIRS/NPP Area Weight Moderate Swath Grid IP L2G VIIRS/NPP Gridded Surface Reflectance Daily L3 Tiled IP 1km NPP_DVSNICIP_L3 VIIRS/NPP Gridded Snow/Ice Cover Cont. L3 Tiled IP 1km NPP_VLST_L2 VIIRS/NPP Land Surface Temperature 5-Min L2 Swath EDR NPP_D17NDVI_L3 VIIRS/NPP Gridded NBAR NDVI 17- Day L3 Tiled IP 5km
4 PGE318 VIIRS Monthly SRBTVI Gridding PGE319 VIIRS 17-Day Land Albedo Gridding PGE319 VIIRS 17-Day Land Albedo Gridding PGE320 VIIRS Monthly NBAR NDVI Gridding NPP_MSRBTVIIP_L3 VIIRS/NPP Gridded Surface Reflectance, Brightness Temperature, & Vegetation Index Monthly L3 Tiled IP 1km NPP_D17LALBIP_L3 VIIRS/NPP Gridded Land Albedo 17- Day L3 Tiled IP 1km NPP_D17BRDFIP_L3 NPP_MNDVI_L3 VIIRS/NPP Gridded BRDF Archetypal 17-Day L3 Tiled IP 1km VIIRS/NPP Gridded Nbar NDVI Monthly L3 Tiled IP 5km PGE321 VIIRS Rolling NBAR NDVI Gridding PGE330 VIIRS L2 Active Fires NPP_D17RNDVI_L3 NPP_AVAF_L2 VIIRS/NPP Gridded NBAR NDVI Rolling L3 Tiled IP 5km VIIRS/NPP Active Fires 5-Min L2 Swath ARP PGE330 VIIRS L2 Active Fires PGE341 VIIRS Quarterly Surface Type Gridding PGE341 VIIRS Quarterly Surface Type Gridding PGE341 VIIRS Quarterly Surface Type Gridding PGE349 VIIRS L2 Surface Type NPP_VAFIP_L2 NPP_QSTIP_L3 NPP_QSTLWMIP_L3 NPP_QMMVIIP_L3 NPP_VSUT_L2 VIIRS/NPP Fire Mask & Quality Flags 5-Min L2 Swath IP (Output of Mx4 OPs code; not in EDR-IR) VIIRS/NPP Gridded Surface Type Quarterly L3 Tiled IP 1km (as received, not yet produced at LPEATE due to lack of code) VIIRS/NPP Gridded Surface Type/Land Water Mask Quarterly L3 Tiled IP 1km (as received, not yet produced at LPEATE due to lack of code) VIIRS/NPP Gridded Annual Max/Min Vegetation Index Quarterly L3 Tiled IP 1km (as received, not yet produced at LPEATE due to lack of code) VIIRS/NPP Surface Type 5-Min L2 Swath EDR NCEP_AIRTIP_L2 NCEP Surface Air Temperature 5- Min L2 Swath IP NCEP_ATPIP_L2 NCEP_COZIP_L2 NCEP Atmospheric Temperature Profile 5-Min L2 Swath IP NCEP Total Column Ozone 5-Min L2 Swath IP NCEP_GHPIP_L2 NCEP Geopotential Height Profile 5- Min L2 Swath IP NCEP_HGHTIP_L2 NCEP_PRESIP_L2 NCEP_PRWIP_L2 NCEP Geopotential Surface Height 5-Min L2 Swath IP NCEP Surface Pressure 5-Min L2 Swath IP NCEP Total Column Precipitable Water 5-Min L2 Swath IP NCEP_SHASIP_L2 NCEP Specific Humidity at Surface
5 (Note (2)) NCEP_SKNTMPIP_L2 NCEP_WDIRIP_L2 NCEP_WSPDIP_L2 Level 5-Min L2 Swath IP NCEP Skin Temperature 5-Min L2 Swath IP NCEP Surface Wind Direction 5-Min L2 Swath IP NCEP Surface Wind Speed 5-Min L2 Swath IP NCEP_WVMRIP_L2 NCEP Water Vapor Mixing Ratio 5- Min L2 Swath IP NPP_TERRHTIP_L2 NCEP Terrain Geopotential Height 5- Min L2 Swath IP NCEP_GFSIP_L2 (EDR-IR has one file containing all parameters as output. OPS code has separate files for each parameter) NCEP Parameters 5-Min L2 Swath IP One file with contents: Geopotential Height of Surface Isobaric Level Temperature Relative Humidity at Pressure Levels Sea Level Pressure Sea Surface Winds (Speed & Direction; U & V) Specific Humidity at Surface Surface Air Temperature Surface Pressure (Adjusted) Total Column Ozone Total Column Precipitable Water Tropopause Height PGE351 VIIRS NAAPS Total Optical Depth NAAPS_TODIP_L2 Water Vapor Mixing Ratio at Pressure Levels NAAPS Total Optical Depth 5-Min L2 Swath IP NPP_D17LALBIP_L2 VIIRS/NPP Gridded Land Albedo 17- Day 5-Min L2 Swath IP
6 NPP_QMMVIIP_L2 PGE355 VIIRS L2 Land Albedo PGE356 VIIRS L2 Vegetation Index PGE373 VIIRS L2 Ice Surface Temperature PGE374 VIIRS L2 Nearest Neighbor NPP_QSIP_L2 NPP_QSLWMIP_L2 NPP_VNDVIIP_L2 NPP_VSNICIP_L2 NPP_VLAIP_L2 NPP_VRVI_L2 NPP_VIST_L2 NPP_VNNMIP_L2 VIIRS/NPP Gridded Annual Max/Min Vegetation Index Quarterly 5-Min L2 Swath IP VIIRS/NPP Gridded Surface Type Quarterly 5-Min L2 Swath IP VIIRS/NPP Gridded Surface Type Land Water Mask Quarterly 5-Min L2 Swath IP VIIRS/NPP Gridded Rolling 17-Day NBAR Vegetation Index 5-Min L2 Swath IP VIIRS/NPP Gridded Snow/Ice Cover 5-Min L2 Swath IP VIIRS/NPP Land Albedo 5-Min L2 Swath IP VIIRS/NPP Vegetation Index 5-Min L2 Swath EDR 375m VIIRS/NPP Ice Surface Temperature 5-Min L2 swath EDR VIIRS/NPP Nearest Neighbor Pointer 5-Min L2 Swath IP PGE374 VIIRS L2 Nearest Neighbor PGE376 VIIRS NOGAPS NPP_VNNIIP_L2 NOGAPS_GFSIP_L2 VIIRS/NPP Nearest Neighbor Pointer 5-Min L2 NOGAPS Parameters 5-Min L2 Swath IP One file or multiple parameter files with contents: Geopotential Height of Surface Isobaric Level Temperature Relative Humidity at Pressure Levels Sea Level Pressure Sea Surface Winds (Speed & Direction; U & V) Specific Humidity at Surface Surface Air Temperature Surface Pressure (Adjusted) Total Column Precipitable Water Tropopause Height
7 Water Vapor Mixing Ratio at Pressure Levels PGE392 VIIRS Cloud SubSampler IDPS Operational Data Jet Propulsion Laboratory (JPL) NAAPS External Ancillary Data NCEP External Ancillary Data NPP_VAMIIP_L2 NPP_VAOTHIP_L2 NPP_VAOTIP_L2 NPP_VAOT_L2 NPP_VGAERO_L2 NPP_VSUM_L2 VIIRS/NPP Aerosol Model Information 5-Min L2 Swath IP Thickness Heap 5-Min L2 Swath IP Thickness 5-Min L2 Swath IP Thickness 5-Min L2 Swath EDR 6km Thickness 5-Min L2 Swath EDR VIIRS/NPP Suspended Matter 5-Min L2 Swath EDR NPP_VIMD_SS VIIRS/NPP Cloud SubSampler 5-Min L1 NPP_VMAE_L1 VIIRS/NPP Moderate Resolution 5- Min L1 Swath SDR and Geo NPP_VIAE_L1 VIIRS/NPP Imagery Resolution 5- Min L1 Swath SDR 375m NPP_IMFT_L1 NPP_VDNE_L1 NPP_GRCDNE_L1 NPP_GRCIAE_L1 NPP_GRCMAE_L1 RNSCA-RVIRS (HDF5) (Internal ESDT NP5_RVIRS_L0) N/A NAAPS_TOD_ANC NCEP_GFS_ANC (NPP variation of GFS files) VIIRS/NPP Imagery Resolution Terrain Corrected 5-Min L1 VIIRS/NPP Day/Night Band 5-Min L1 Swath SDR 375m (also contains VIIRS/NPP Day/Night Band Elliptical 5-Min L1 Swath IP 375m) Day/Night IP Imagery Resolution IP Moderate Resolution IP VIIRS/NPP Compressed Raw Instrument Science Packets 86- second L0 RDR containing Spacecraft Ephemeris and Attitude Planetary Ephemeris Files NAAPS Total Optical Depth L3 Global NCEP Parameters 6-Hour L3 Global 1Deg 1 Degree NCEP GDAS consists of one Time Interpolated file with
8 contents: Geopotential Height of Surface Isobaric Level Temperature Relative Humidity at Pressure Levels Sea Level Pressure Sea Surface Winds ( U & V Components) Specific Humidity at Surface Surface Air Temperature Surface Pressure Total Column Ozone Total Column Precipitable Water Tropopause Height NOGAPS External Ancillary Data United States Naval Observatory United States Naval Observatory NOGAPS_GFS_ANC N/A N/A Water Vapor Mixing Ratio at Pressure Levels NOGAPS Parameters 6-Hour L3 Global 1Deg Leap Second TAI-UTC & Julian Date UTC Pole UT1-UTC & UTC Date Earth Wobble in Rotation
STAR Algorithm and Data Products (ADP) Beta Review. Suomi NPP Surface Reflectance IP ARP Product
STAR Algorithm and Data Products (ADP) Beta Review Suomi NPP Surface Reflectance IP ARP Product Alexei Lyapustin Surface Reflectance Cal Val Team 11/26/2012 STAR ADP Surface Reflectance ARP Team Member
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]
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,
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
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
Joint Polar Satellite System (JPSS) Algorithm Specification Volume II: Data Dictionary for the Ozone Total Column. Block 2.0.0
GSFC JPSS CMO August 04, 2015 Released Joint Polar Satellite System (JPSS) Ground Project Code 474 Joint Polar Satellite System (JPSS) Algorithm Specification Volume II: Data Dictionary for the Ozone Total
Joint Polar Satellite System (JPSS)
Joint Polar Satellite System (JPSS) John Furgerson, User Liaison Joint Polar Satellite System National Environmental Satellite, Data, and Information Service National Oceanic and Atmospheric Administration
Outline of RGB Composite Imagery
Outline of RGB Composite Imagery Data Processing Division, Data Processing Department Meteorological Satellite Center (MSC) JMA Akihiro SHIMIZU 29 September, 2014 Updated 6 July, 2015 1 Contents What s
Application of Numerical Weather Prediction Models for Drought Monitoring. Gregor Gregorič Jožef Roškar Environmental Agency of Slovenia
Application of Numerical Weather Prediction Models for Drought Monitoring Gregor Gregorič Jožef Roškar Environmental Agency of Slovenia Contents 1. Introduction 2. Numerical Weather Prediction Models -
The NASA NEESPI Data Portal to Support Studies of Climate and Environmental Changes in Non-boreal Europe
The NASA NEESPI Data Portal to Support Studies of Climate and Environmental Changes in Non-boreal Europe Suhung Shen NASA Goddard Space Flight Center/George Mason University Gregory Leptoukh, Tatiana Loboda,
Marcus A. Watkins Director of the Joint Agency Satellite Division, Science Mission Directorate, NASA HQ, Washington DC
Marcus A. Watkins Director of the Joint Agency Satellite Division, Science Mission Directorate, NASA HQ, Washington DC Leads the Joint Agency Satellite Division (JASD) at NASA HQ in Washington, DC and
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
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
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
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
Overview of the IR channels and their applications
Ján Kaňák Slovak Hydrometeorological Institute [email protected] Overview of the IR channels and their applications EUMeTrain, 14 June 2011 Ján Kaňák, SHMÚ 1 Basics in satellite Infrared image interpretation
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
Comparative Evaluation of High Resolution Numerical Weather Prediction Models COSMO-WRF
3 Working Group on Verification and Case Studies 56 Comparative Evaluation of High Resolution Numerical Weather Prediction Models COSMO-WRF Bogdan Alexandru MACO, Mihaela BOGDAN, Amalia IRIZA, Cosmin Dănuţ
T.A. Tarasova, and C.A.Nobre
SEASONAL VARIATIONS OF SURFACE SOLAR IRRADIANCES UNDER CLEAR-SKIES AND CLOUD COVER OBTAINED FROM LONG-TERM SOLAR RADIATION MEASUREMENTS IN THE RONDONIA REGION OF BRAZIL T.A. Tarasova, and C.A.Nobre Centro
Satellite'&'NASA'Data'Intro'
Satellite'&'NASA'Data'Intro' Research'vs.'Opera8ons' NASA':'Research'satellites' ' ' NOAA/DoD:'Opera8onal'Satellites' NOAA'Polar'Program:'NOAA>16,17,18,19,NPP' Geosta8onary:'GOES>east,'GOES>West' DMSP'series:'SSM/I,'SSMIS'
Climate Models: Uncertainties due to Clouds. Joel Norris Assistant Professor of Climate and Atmospheric Sciences Scripps Institution of Oceanography
Climate Models: Uncertainties due to Clouds Joel Norris Assistant Professor of Climate and Atmospheric Sciences Scripps Institution of Oceanography Global mean radiative forcing of the climate system for
NCDC s SATELLITE DATA, PRODUCTS, and SERVICES
**** NCDC s SATELLITE DATA, PRODUCTS, and SERVICES Satellite data and derived products from NOAA s satellite systems are available through the National Climatic Data Center. The two primary systems are
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
Guy Carpenter Asia-Pacific Climate Impact Centre, School of energy and Environment, City University of Hong Kong
Diurnal and Semi-diurnal Variations of Rainfall in Southeast China Judy Huang and Johnny Chan Guy Carpenter Asia-Pacific Climate Impact Centre School of Energy and Environment City University of Hong Kong
SAFNWC/MSG Cloud type/height. Application for fog/low cloud situations
SAFNWC/MSG Cloud type/height. Application for fog/low cloud situations 22 September 2011 Hervé LE GLEAU, Marcel DERRIEN Centre de météorologie Spatiale. Lannion Météo-France 1 Fog or low level clouds?
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
Rosaly Lopes, Jet Propulsion Laboratory, California Institute of Technology
Saturn s Moon Titan: Cassini-Huygens Reveals a New World Rosaly Lopes, Jet Propulsion Laboratory, California Institute of Technology The year 2005 will be remembered in the history of space exploration
The USGS Landsat Big Data Challenge
The USGS Landsat Big Data Challenge Brian Sauer Engineering and Development USGS EROS [email protected] U.S. Department of the Interior U.S. Geological Survey USGS EROS and Landsat 2 Data Utility and Exploitation
How does snow melt? Principles of snow melt. Energy balance. GEO4430 snow hydrology 21.03.2006. Energy flux onto a unit surface:
Principles of snow melt How does snow melt? We need energy to melt snow/ ice. GEO443 snow hydrology 21.3.26 E = m L h we s K = ρ h = w w we f E ρ L L f f Thomas V. Schuler [email protected] E energy
GCOS science conference, 2 Mar. 2016, Amsterdam. Japan Meteorological Agency (JMA)
GCOS science conference, 2 Mar. 2016, Amsterdam Status of Surface Radiation Budget Observation for Climate Nozomu Ohkawara Japan Meteorological Agency (JMA) Contents 1. Background 2. Status t of surface
What the Heck are Low-Cloud Feedbacks? Takanobu Yamaguchi Rachel R. McCrary Anna B. Harper
What the Heck are Low-Cloud Feedbacks? Takanobu Yamaguchi Rachel R. McCrary Anna B. Harper IPCC Cloud feedbacks remain the largest source of uncertainty. Roadmap 1. Low cloud primer 2. Radiation and low
2. VIIRS SDR Tuple and 2Dhistogram MIIC Server-side Filtering. 3. L2 CERES SSF OPeNDAP dds structure (dim_alias and fixed_dim)
MIIC Server-side Filtering Outline 1. DEMO Web User Interface (leftover from last meeting) 2. VIIRS SDR Tuple and 2Dhistogram MIIC Server-side Filtering 3. L2 CERES SSF OPeNDAP dds structure (dim_alias
Geostationary Operational Environmental Satellite (GOES) GOES-R Series Level I Requirements (LIRD)
410-R-LIRD-0137 Effective Date: 08-29-2011 Expiration Date: five years from date of last change Version: 3.4 Responsible Organization: GOES-R Program/Code 410 Geostationary Operational Environmental Satellite
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
Fundamentals of Climate Change (PCC 587): Water Vapor
Fundamentals of Climate Change (PCC 587): Water Vapor DARGAN M. W. FRIERSON UNIVERSITY OF WASHINGTON, DEPARTMENT OF ATMOSPHERIC SCIENCES DAY 2: 9/30/13 Water Water is a remarkable molecule Water vapor
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
Vulnerability assessment of ecosystem services for climate change impacts and adaptation (VACCIA)
Vulnerability assessment of ecosystem services for climate change impacts and adaptation (VACCIA) Action 2: Derivation of GMES-related remote sensing data Deliverable 1: Time-series of Earth Observation
Multiangle cloud remote sensing from
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
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
Ocean Level-3 Standard Mapped Image Products June 4, 2010
Ocean Level-3 Standard Mapped Image Products June 4, 2010 1.0 Introduction This document describes the specifications of Ocean Level-3 standard mapped archive products that are produced and distributed
6.9 A NEW APPROACH TO FIRE WEATHER FORECASTING AT THE TULSA WFO. Sarah J. Taylor* and Eric D. Howieson NOAA/National Weather Service Tulsa, Oklahoma
6.9 A NEW APPROACH TO FIRE WEATHER FORECASTING AT THE TULSA WFO Sarah J. Taylor* and Eric D. Howieson NOAA/National Weather Service Tulsa, Oklahoma 1. INTRODUCTION The modernization of the National Weather
Observed Cloud Cover Trends and Global Climate Change. Joel Norris Scripps Institution of Oceanography
Observed Cloud Cover Trends and Global Climate Change Joel Norris Scripps Institution of Oceanography Increasing Global Temperature from www.giss.nasa.gov Increasing Greenhouse Gases from ess.geology.ufl.edu
CrIS L1B Project Status
CrIS L1B Project Status Graeme Martin 1, Hank Revercomb 1, Larrabee Strow 2, Dave Tobin 1, Howard Moteller 2, Liam Gumley 1, Ray Garcia 1, Greg Quinn 1, Joe Taylor 1, Coda Phillips 1, Bob Knuteson 1, Jessica
Corso di Fisica Te T cnica Ambientale Solar Radiation
Solar Radiation Solar radiation i The Sun The Sun is the primary natural energy source for our planet. It has a diameter D = 1.39x10 6 km and a mass M = 1.989x10 30 kg and it is constituted by 1/3 of He
Very High Resolution Arctic System Reanalysis for 2000-2011
Very High Resolution Arctic System Reanalysis for 2000-2011 David H. Bromwich, Lesheng Bai,, Keith Hines, and Sheng-Hung Wang Polar Meteorology Group, Byrd Polar Research Center The Ohio State University
Water, Phase Changes, Clouds
TUESDAY: air & water & clouds Water, Phase Changes, Clouds How can freezing make something warmer? 'warm air can hold more water' why? How do clouds form? The (extraordinary) properties of Water Physical
Cloud Model Verification at the Air Force Weather Agency
2d Weather Group Cloud Model Verification at the Air Force Weather Agency Matthew Sittel UCAR Visiting Scientist Air Force Weather Agency Offutt AFB, NE Template: 28 Feb 06 Overview Cloud Models Ground
ENVIRONMENTAL MONITORING Vol. I - Remote Sensing (Satellite) System Technologies - Michael A. Okoye and Greg T. Koeln
REMOTE SENSING (SATELLITE) SYSTEM TECHNOLOGIES Michael A. Okoye and Greg T. Earth Satellite Corporation, Rockville Maryland, USA Keywords: active microwave, advantages of satellite remote sensing, atmospheric
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
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
MSG MPEF Products focus on GII Simon Elliott Meteorological Operations Division [email protected]
MSG MPEF focus on GII Simon Elliott Meteorological Operations Division [email protected] MSG Application Workshop, 15-19 March 2010, Alanya, Türkiye Slide: 1 1. What is the MPEF? Meteorological
AATSR Technical Note. Improvements to the AATSR IPF relating to Land Surface Temperature Retrieval and Cloud Clearing over Land
AATSR Technical Note Improvements to the AATSR IPF relating to Land Surface Temperature Retrieval and Cloud Clearing over Land Author: Andrew R. Birks RUTHERFORD APPLETON LABORATORY Chilton, Didcot, Oxfordshire
Tools for Viewing and Quality Checking ARM Data
Tools for Viewing and Quality Checking ARM Data S. Bottone and S. Moore Mission Research Corporation Santa Barbara, California Introduction Mission Research Corporation (MRC) is developing software tools
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
Roelof Bruintjes, Sarah Tessendorf, Jim Wilson, Rita Roberts, Courtney Weeks and Duncan Axisa WMA Annual meeting 26 April 2012
Aerosol affects on the microphysics of precipitation development in tropical and sub-tropical convective clouds using dual-polarization radar and airborne measurements. Roelof Bruintjes, Sarah Tessendorf,
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
Automated Spacecraft Scheduling The ASTER Example
Automated Spacecraft Scheduling The ASTER Example Ron Cohen [email protected] Ground System Architectures Workshop 2002 Jet Propulsion Laboratory The Concept Scheduling by software instead of
The Balance of Power in the Earth-Sun System
NASA Facts National Aeronautics and Space Administration www.nasa.gov The Balance of Power in the Earth-Sun System The Sun is the major source of energy for Earth s oceans, atmosphere, land, and biosphere.
Sodankylä National Satellite Data Center (NSDC): Current and Future Satellite Missions and Products
Sodankylä National Satellite Data Center (NSDC): Current and Future Satellite Missions and Products Timo Ryyppö, CSPP Users Group Meeting 2015 Content Introduction to Sodankylä site Facilities Satellites
Received in revised form 24 March 2004; accepted 30 March 2004
Remote Sensing of Environment 91 (2004) 237 242 www.elsevier.com/locate/rse Cloud detection in Landsat imagery of ice sheets using shadow matching technique and automatic normalized difference snow index
An Introduction to Twomey Effect
An Introduction to Twomey Effect Guillaume Mauger Aihua Zhu Mauna Loa, Hawaii on a clear day Mauna Loa, Hawaii on a dusty day Rayleigh scattering Mie scattering Non-selective scattering. The impact of
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
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
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
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
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
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
Denis Botambekov 1, Andrew Heidinger 2, Andi Walther 1, and Nick Bearson 1
Denis Botambekov 1, Andrew Heidinger 2, Andi Walther 1, and Nick Bearson 1 1 - CIMSS / SSEC / University of Wisconsin Madison, WI, USA 2 NOAA / NESDIS / STAR @ University of Wisconsin Madison, WI, USA
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,
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,
Amy K. Huff Battelle Memorial Institute [email protected] BUSINESS SENSITIVE 1
Using NASA Satellite Aerosol Optical Depth Data to Create Representative PM 2.5 Fields for Use in Human Health and Epidemiology Studies in Support of State and National Environmental Public Health Tracking
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)
CloudSat Standard Data Products Handbook
CloudSat Project A NASA Earth System Science Pathfinder Mission CloudSat Standard Data Products Handbook Revised: April 25 th, 2008 Cooperative Institute for Research in the Atmosphere Colorado State University
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
TOPIC: CLOUD CLASSIFICATION
INDIAN INSTITUTE OF TECHNOLOGY, DELHI DEPARTMENT OF ATMOSPHERIC SCIENCE ASL720: Satellite Meteorology and Remote Sensing TERM PAPER TOPIC: CLOUD CLASSIFICATION Group Members: Anil Kumar (2010ME10649) Mayank
TECHNICAL REPORTS. Authors: Tatsuhiro Noguchi* and Takaaki Ishikawa*
Application and Evaluation of Observation Data by Advanced Microwave Scanning Radiometer 2 Achievement of World s Top-Class Microwave Radiometer AMSR Series Authors: Tatsuhiro Noguchi* and Takaaki Ishikawa*
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
NASA Earth System Science: Structure and data centers
SUPPLEMENT MATERIALS NASA Earth System Science: Structure and data centers NASA http://nasa.gov/ NASA Mission Directorates Aeronautics Research Exploration Systems Science http://nasascience.nasa.gov/
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
Impacts of a future city master plan on on thermal and wind environments in Vinh city, Vietnam
Impacts of a future city master plan on on thermal and wind environments in Vinh city, Vietnam Satoru Iizuka, Nagoya University, Japan Tatsunori Ito, Nagoya University, Japan Masato Miyata, Mitsubishi
The Wind Integration National Dataset (WIND) toolkit
The Wind Integration National Dataset (WIND) toolkit EWEA Wind Power Forecasting Workshop, Rotterdam December 3, 2013 Caroline Draxl NREL/PR-5000-60977 NREL is a national laboratory of the U.S. Department
Satellite Products and Dissemination: Visualization and Data Access
Satellite Products and Dissemination: Visualization and Data Access Gregory Leptoukh GES DISC, NASA GSFC Dana Ostrenga GES DISC, NASA GSFC Introduction The Goddard Earth Sciences Data and Information Services
7613-1 - Page 1. Weather Unit Exam Pre-Test Questions
Weather Unit Exam Pre-Test Questions 7613-1 - Page 1 Name: 1) Equal quantities of water are placed in four uncovered containers with different shapes and left on a table at room temperature. From which
SPARC Data Center. www.sparc.sunysb.edu. Peter Love Marvin Geller Institute for Terrestrial and Planetary Atmospheres Stony Brook University
SPARC Data Center www.sparc.sunysb.edu Peter Love Marvin Geller Institute for Terrestrial and Planetary Atmospheres Stony Brook University SPARC Data Centre Overview Exists to facilitate data exchange
Cloud/Hydrometeor Initialization in the 20-km RUC Using GOES Data
WORLD METEOROLOGICAL ORGANIZATION COMMISSION FOR BASIC SYSTEMS OPEN PROGRAMMME AREA GROUP ON INTEGRATED OBSERVING SYSTEMS EXPERT TEAM ON OBSERVATIONAL DATA REQUIREMENTS AND REDESIGN OF THE GLOBAL OBSERVING
How To Understand Cloud Properties From Satellite Imagery
P1.70 NIGHTTIME RETRIEVAL OF CLOUD MICROPHYSICAL PROPERTIES FOR GOES-R Patrick W. Heck * Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin-Madison Madison, Wisconsin P.
Description of zero-buoyancy entraining plume model
Influence of entrainment on the thermal stratification in simulations of radiative-convective equilibrium Supplementary information Martin S. Singh & Paul A. O Gorman S1 CRM simulations Here we give more
Satellite remote sensing using AVHRR, ATSR, MODIS, METEOSAT, MSG
Satellite remote sensing using AVHRR, ATSR, MODIS, METEOSAT, MSG Ralf Meerkötter, Luca Bugliaro, Knut Dammann, Gerhard Gesell, Christine König, Waldemar Krebs, Hermann Mannstein, Bernhard Mayer, presented
Update on EUMETSAT ocean colour services. Ewa J. Kwiatkowska
Update on EUMETSAT ocean colour services Ewa J. Kwiatkowska 1 st International Ocean Colour Science meeting, 6 8 May, 2013 EUMETSAT space data provider for operational oceanography Operational data provider
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