Development of GHRSST L2Pcore for MODIS Bryan Franz NASA Ocean Biology Processing Group Goddard Space Flight Center.

Slides:



Advertisements
Similar presentations
Status of the GHRSST GDAC (Global Data Assembly Center) at the JPL PO.DAAC Ed Armstrong, Jorge Vazquez and Andrew Bingham
Advertisements

1 MODAPS - Land Processing Status Robert Wolfe and Ed Masuoka Code 619, NASA GSFC Sadashiva Devadiga Sigma Space MODIS Science Team Meeting April 15-17,
MODIS Ocean Filenames, Structures, and useful metadata Kay Kilpatrick University of Miami/RSMAS.
Global Processing of MODIS for Operational SST, Ocean Color, and GHRSST Bryan Franz and the NASA Ocean Biology Processing Group 8th GHRSST-PP Science Team.
SeaDAS Training ~ NASA Ocean Biology Processing Group 1 Sea surface temperature (SST) basics NASA Ocean Biology Processing Group Goddard Space Flight Center,
Pathfinder –> MODIS -> VIIRS Evolution of a CDR Robert Evans, Peter Minnett, Guillermo Podesta Kay Kilpatrick (retired), Sue Walsh, Vicki Halliwell, Liz.
MODIS Ocean Products MODIS/AIRS Workshop Pretoria, South Africa April 4-7, 2006 Liam Gumley Space Science and Engineering Center University of Wisconsin-Madison.
1 Overview LTSRF Status GHRSST Reanalysis Example L4 Analyses Future Activities GlobColour Connection Villefranche sur mer,
Xin Kong, Lizzie Noyes, Gary Corlett, John Remedios, Simon Good and David Llewellyn-Jones Earth Observation Science, Space Research Centre, University.
Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 NOAA Operational Geostationary Sea Surface Temperature Products from NOAA.
Satellite Data Provided by the NASA Ocean Biology Processing Group (OBPG)
User Services Experience GSFC DAAC MODIS Science Team Meeting Greenbelt, MD July 2002
Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Image: MODIS Land Group, NASA GSFC March 2000 POES-GOES Blended SST Analysis.
Earth Observing System Data and Information System (EOSDIS) provides access to more than 3,000 types of Earth science data products and specialized services.
Erich Franz Stocker * and Yimin Ji + * NASA Goddard Space Flight Center, + Wyle Inc/PPS The Global Precipitation Measurement (GPM) Mission: GPM Near-realtime.
Spatially Complete Global Surface Albedos Derived from MODIS Data
NASA Support for MODIS Direct Broadcast: Level-0 to Standard Ocean Products Bryan Franz & Mike MacDonald Ocean Biology Processing Group NASA Goddard Space.
Yimin Ji - Page 1 October 5, 2010 Global Precipitation Measurement (GPM) mission Precipitation Processing System (PPS) Yimin Ji NASA/GSFC,
1 MODIS Land C6 Schedule and Status Sadashiva Devadiga 1,2, Ye Gang 1,2 and Edward Masuoka 1 1 NASA GSFC 2 Science Systems and Applications Inc. MODIS/VIIRS.
High Resolution MODIS Ocean Color Fred Patt 1, Bryan Franz 1, Gerhard Meister 2, P. Jeremy Werdell 3 NASA Ocean Biology Processing Group 1 Science Applications.
MODIS Sea-Surface Temperatures for GHRSST-PP Robert H. Evans & Peter J. Minnett Otis Brown, Erica Key, Goshka Szczodrak, Kay Kilpatrick, Warner Baringer,
Jasmine S. Nahorniak Mark R. Abbott Ricardo M. Letelier Curt Vandetta Bridges to the Community NASA grant NNG05GA73G International EOS/NPP Direct Broadcast.
Harmful Algal Blooms A marine ecosystem manager is interested in using satellite and ocean model products to find precursors for the determination of harmful.
8th IOCCG Meeting in Florence, Italy (24-26 Feb 03) Current Status of MODIS (Terra and Aqua) by Chuck Trees for the MODIS Team Members.
25 June 2009 Dawn Conway, AMSR-E TLSCF Lead Software Engineer AMSR-E Team Leader Science Computing Facility.
Continuation and improvement of the NRT system for the remotely sensed data Task 1.1 Emanuele Böhm, Roberto Sciarra & Rosalia Santoleri Satellite Oceanography.
AN ENHANCED SST COMPOSITE FOR WEATHER FORECASTING AND REGIONAL CLIMATE STUDIES Gary Jedlovec 1, Jorge Vazquez 2, and Ed Armstrong 2 1NASA/MSFC Earth Science.
MODIS Ocean Color Processing Chuck McClain* Processing Approach Calibration/Validation Gene Feldman* Data Processing & Distribution MODIS Team Meeting/
EOS Terra MODIS Land Processing and Distribution Overview Joseph M Glassy, Director, MODIS Software Development at NTSG School of Forestry, Numerical Terradynamics.
September 4, 2003MODIS Ocean Data Products Workshop, Oregon State University1 Goddard Earth Sciences (GES) Distributed Active Archive Center (DAAC) MODIS.
MODIS OCEAN QA Browse Imagery (MQABI Browse Tool) NASA Goddard Space Flight Center Sept 4, 2003
NASA Ocean Color Research Team Meeting, Silver Spring, Maryland 5-7 May 2014 II. Objectives Establish a high-quality long-term observational time series.
Suhung Shen James G. Acker Denis Nadeau George Serafino Goddard Earth Sciences (GES) Data and Information Services Center (DISC) Distributed Active Archive.
AIRS Radiance and Geophysical Products: Methodology and Validation Mitch Goldberg, Larry McMillin NOAA/NESDIS Walter Wolf, Lihang Zhou, Yanni Qu and M.
1 RTM/NWP-BASED SST ALGORITHMS FOR VIIRS USING MODIS AS A PROXY B. Petrenko 1,2, A. Ignatov 1, Y. Kihai 1,3, J. Stroup 1,4, X. Liang 1,5 1 NOAA/NESDIS/STAR,
7/13/04 Shaida Johnston MODIS Science Team Meeting 1 Current MODIS Data System: Processing, Archiving and Distribution Shaida Johnston July 13, 2004.
Robert Wolfe NASA Goddard Space Flight Center Code 614.5, Greenbelt, MD Robert Wolfe NASA Goddard Space Flight Center Code 614.5,
SNPP Ocean SIPS status SNPP Applications Workshop 18 November 2014 Bryan Franz and the Ocean Biology Processing Group.
Sea-surface Temperature from GHRSST/MODIS – recent progress in improving accuracy Peter J. Minnett & Robert H. Evans with Kay Kilpatrick, Ajoy Kumar, Warner.
Integrating the Scientific Community with a Measurement Based, Multi-Sensor Data Processing and Distribution System Bryan Franz, Donna Thomas, Sean Bailey,
Early Results from AIRS and Risk Reduction Benefits for other Advanced Infrared Sounders Mitchell D. Goldberg NOAA/NESDIS Center for Satellite Applications.
ADPS Science Software Development Bryan Franz NASA Ocean Biology Processing Group Aquarius Data Processing Workshop, NASA/GSFC, March 2007.
0 0 Robert Wolfe NASA GSFC, Greenbelt, MD GSFC Hydrospheric and Biospheric Sciences Laboratory, Terrestrial Information System Branch (614.5) Carbon Cycle.
MODIS Cryosphere Science Data Product Metrics Prepared by the ESDIS SOO Metrics Team for the Cryosphere Science Data Review January 11-12, 2006.
Retrieval Algorithms The derivations for each satellite consist of two steps: 1) cloud detection using a Bayesian Probabilistic Cloud Mask; and 2) application.
MODIS SDST, STTG and SDDT MODIS Science Team Meeting (Land Discipline Breakout Session) July 13, 2004 Robert Wolfe Raytheon NASA GSFC Code 922.
Operational Transition of MODIS Experimental Winds to NOAA/NESDIS Jaime Daniels NESDIS/Office of Research and Applications Camp Springs, Maryland Wayne.
MODIS-Terra cross-calibration for ocean color bands Ewa Kwiatkowska Bryan Franz, Gerhard Meister, Gene Eplee OBPG 30 January 2008.
OBPG Status Report Chuck McClain & Gene Feldman Ocean Biology Processing Group Leaders NASA Ocean Biogeochemistry Science Team Meeting April 11-13, 2006.
1 LANCE-AIRS LANCE-MLS Status Bruce Vollmer Mike Theobald LANCE User Working Group Meeting November.
Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 NOAA CoastWatch/OceanWatch Ocean Color Activities: Contributions to Ocean.
Goddard Earth Sciences Data and Information Services Center, NASA/GSFC, Code 902, Greenbelt, Maryland 20771, USA INTRODUCTION  NASA Goddard Earth Sciences.
Data acquisition From satellites with the MODIS instrument.
From Missions to Measurements: an Ocean Discipline Experience.
NASA OBPG Update OCRT Meeting 23 April 2012 Bryan Franz and the NASA Ocean Biology Processing Group.
AIRS Land Surface Temperature and Emissivity Validation Bob Knuteson Hank Revercomb, Dave Tobin, Ken Vinson, Chia Lee University of Wisconsin-Madison Space.
8 January 2007 From Missions to Measurements: an Ocean Color Experience.
The MODIS SST hypercube is a multi-dimensional look up table of SST retrieval uncertainty, bias and standard deviation, determined from comprehensive analysis.
GHRSST Science Team Meeting st – 5 th June, 2009, Santa Rosa ESA L2P Operational Service Nigel Houghton ESA / ESRIN NRT and Archive L2P Processing.
9th June 2008 GHRSST-9, Perros-Guirec SST framework at European level Medspiration, Marine Core Services & SAF O&SI Status and products Jean-François Piollé.
High Resolution MODIS Ocean Color Bryan Franz NASA Ocean Biology Processing Group MODIS Science Team Meeting, 4-6 January 2006, Baltimore, MD.
International GHRSST User Symposium Santa Rosa, California, USA 28-29th May 2009 MODIS Sea-Surface Temperatures Peter J Minnett & Robert H. Evans With.
NOAA Near Real-Time AIRS Processing and Distribution System Walter Wolf Mitch Goldberg Lihang Zhou NESDIS/ORA/CRAD.
New Australian High Resolution AVHRR SST Products from the Integrated Marine Observing System Presented at the GHRSST Users Symposium, Santa Rosa, USA,
Sea Surface Temperature Distribution from the Physical Oceanography DAAC Ed Armstrong JPL PO.DAAC MODIS Science Team Meeting.
7/13/04 Edward Masuoka MODIS Science Team Meeting 1 MODAPS Reprocessing Collections 4 and 5 Ed Masuoka July 13, 2004.
MODIS Atmosphere Group Summary Summary of modifications and enhancements in collection 5 Summary of modifications and enhancements in collection 5 Impacts.
NOAA Report on Ocean Parameters - SST Presented to CGMS-43 Working Group 2 session, agenda item 9 Author: Sasha Ignatov.
MODIS SST Processing and Support for GHRSST at OBPG
MODIS Ocean Products MODIS/AIRS Workshop Pretoria, South Africa
Presentation transcript:

Development of GHRSST L2Pcore for MODIS Bryan Franz NASA Ocean Biology Processing Group Goddard Space Flight Center

Science Community PO.DAAC GHRSST product reformatting and ancillary merge (L2P) GHRSST L2P distribution Level-3 distribution MODIS SST Interaction OBPG software development and algorithm integration production processing quality assessment archive & distribution RSMAS algorithm development and coefficient updates error fields (tables) quality assessment Level-3 Standard Products GHRSST L2Pcore Products Level-2 & Level-3 Standard Products Level-3Standard coefficients error tables L2P GHRSST Users algorithms

MODIS SST Activities at OBPG Standard Global Production (transitioning from MODAPS/DAAC) –Level-0 through Level-3 –Terra & Aqua, Day and Night, 11-12um and 4um SST products –Online archive and distribution (L1A, L2, L3) GHRSST L2Pcore Production –Parallel production effort, at no additional cost –Level-0 through L2Pcore is operational –Terra & Aqua, Day and Night, 11-12um and 4um SST products –Distribution to PO.DAAC for L2P conversion User Support –SeaDAS: distributed processing software, display and analysis –OCForum: online user support forum, monitored by project staff

Nighttime 11-12um SST RSMAS (modsst)OBPG (msl12)

Nighttime 4um SST RSMAS (modsst)OBPG (msl12)

Verification of Algorithm Implementation OBPG - RSMAS 11-12um SST Differences 4um SST Differences

Status of MODIS GHRSST Production L2Pcore files have been available to PO.DAAC via rolling ftp archive since October File content evolving: recent updates incorporate SSES.

11-12um SSES Error Fields SSES BiasSSES Std Dev

Status of MODIS GHRSST Production L2Pcore files have been available to PO.DAAC via rolling ftp archive since October File content evolving: recent updates incorporate SSES –static tables developed by RSMAS –function of SST day or night season view zenith BT difference latitude quality level

Quality Levels 4um Night11-12um Night QL=0 QL=1 QL=2 QL=3

Quality Levels 4um Night QL4um Night SST QL=0 QL=1 QL=2 QL=3

11-12um Night Quality 3 Land Radiance bad (saturated, masked at Level-1) BT out of range (-4 to 33 deg-C) SST out of range (-2 to 45 deg-C) 4um BT difference too different from reference SST too different from reference (5 deg-C absolute) 11-12um Night Quality 2 BT spatial non-uniformity (3x3 max-min > 1.2 deg-C) SST too different from 4um SST (1 deg-C absolute) Additional information is available here

L2Pcore File Content ~65MB per 5-min MODIS granule, uncompressed ~20GB (288 granules) per day per sensor

“Potential” Options for L2Pcore File Size Reduction

1)Deal with it ! The “H” stands for high-resolution. a)our only intended customer is Ed b)is this an L2Pcore or L2P issue ? 2)Sub-sample L2Pcore lon/lat along-scan by 8 (28% reduction) 3)4um SST a)eliminate from L2Pcore (19% reduction) b)produce separate L2Pcore for 4um (night) and 11-12um c)eliminate from daytime L2Pcore (mixed day/night?) 4)Quality Levels a)zero-out lower quality pixels to improve compression b)reformat from swath to time-ordered vectors and only include best quality pixels. 5)Reduction of Resolution a)sub-sample to every 4th pixel & line (4km at nadir, 84% reduction) b)average to 4km at nadir (raises many problems/concerns)

“Potential” Options for L2Pcore Expansion sensor zenith angle brightness temps chlorophyll concentration – daytime, cloud & glint-free aerosol optical thickness – daytime, cloud & glint-free

MODIS GHRSST L2Pcore Distribution and Latency Files distributed to JPL PO.DAAC via rolling ftp archive –Operational since 14 October 2005 –Recent updates to incorporate SSES fields –Aqua ( ftp://oceans.gsfc.nasa.gov/MODISA/GHRSST/ ) –Terra ( ftp://oceans.gsfc.nasa.gov/MODIST/GHRSST/ ) Quicklook Products –best available ancillary, predicted attitude/ephmerides –available ~5 hours from time of observation Refined Products –preferred ancillary, definitive attitude/ephmerides –available 2-8 days later

END

Nighttime 11-12um SST Quality RSMAS (modsst)OBPG (msl12)

Nighttime 4um SST Quality RSMAS (modsst)OBPG (msl12)

Ingest queue table L0 Ingest process L1A-L1B ( MOD_PR02 ) L1B-L2 (MSl12) MODISA L2 table Archive - Distrib Server L3BIN (l2bin) MODISA L3-bin table Archive - Distrib Server MODISA L3-map table Archive - Distrib Server Operational MODIS-Aqua Data Flow Software process Hardware system Database table Ancillary input data Sensor CAL Sensor attribs Atm corr Browser CGI / httpd Ocean Color Web Server User Community MySQL DB Ozone L3MAP (smigen) MET MET, Ozone, and OISST data are dynamically selected for each L1A granule Product meta data are populated from production DB December 4, 2015 OISST Level-0 Ingest MODISA L0 table Archive - Distrib Server ATT/EPH Ingest process MODISA atteph table Archive - Distrib Server L0-L1A ( MOD_PR01 ) Geo-Location ( MOD_PR03 ) MODISA L1 table Archive - Distrib Server Full-resolution day- and nighttime via SEN (~60 GB per day) NOAA Realtime System NASA EDOS System Level-2 Production Ocean Color (day) SST SST4 GHRSST Level-3 Production Ocean Color (day) SST SST4

OBPG Responsibilities for MODIS SST & GHRSST Processing will build on the Aqua MODIS data stream already implemented at OBPG (11µm, daytime). This will be extended to night-time 11µm SST retrievals. The 4µm SST fields will be added to the data stream, including the option to produce daytime data. The RSMAS cloud masking methodology will be implemented for both day-time and night-time data streams. OBPG will work with RSMAS in the testing of the integrity of the SST fields (i.e. there should be no significant difference in the products that are generated at MODAPS and those at OBPG when the same algorithms are implemented). OBPG will work with RSMAS to implement the GHRSST-specific, L2 processing code. To include both 11 µm (SST) and 4 µm (SST4) through implementation of SST and quality assessment algorithms developed at RSMAS. OBPG will work with JPL to ensure the delivery of GHRSST MODIS granules to JPL PO.DAAC via network with the least possible delay (generally within 4-6 hours of satellite observation time as dictated by the availability of the Level-0 MODIS data from the NOAA realtime system.) The Terra MODIS data stream will be added as soon as the Aqua SST stream is successfully implemented and when directed to do so by NASA Headquarters.

OBPG Responsibilities for MODIS SST & GHRSST (on-going activities) OBPG will work together with RSMAS to ensure the continuing accuracy of the SST fields, and implement upgrades to the processing algorithms and methodology when necessary. OBPG will work together with RSMAS to improve the efficacy of the cloud screening algorithms. OBPG will work with RSMAS on the periodic updating of algorithms and retrieval coefficients as required (anticipated to be no more than twice per year), and reprocess the past data to a consistent data set as necessary. OBPG will implement improved instrument models as recommended by MCST. OBPG will assemble L3 SST products (4km resolution with mutually agreed upon quality criteria ) for timely distribution to the SST community through the OBPG and JPL PO.DAAC. OBPG will provide archiving of the MODIS SST OBPG will support the web-based MODIS quality assurance utility (functions similar to MQABI) OBPG will implement MODIS SST algorithms in the SEADAS software suite using easily supported coding standards and methods.

SST Quality Flags SST Quality Levels