Martin Rutherford Technical Director Oceanography and Meteorology Royal Australian Navy 02 Jun 2009 Towards a Bias Corrected L4 Median.

Slides:

Advertisements

Similar presentations

GHRSST XI Science Team Meeting, ST-VAL, June 2010, Lima, Peru Recent developments to the SST Quality Monitor (SQUAM) and SST validation with In situ.

Advertisements

MODIS Web Fire Mapper an example of internet GIS technology to support decision making Diane Davies and Suresh Kumar Department of Geography University.

1 High resolution SST products for 2001 Satellite SST products and coverage In situ observations, coverage Quality control procedures Satellite error statistics.

1 Overview LTSRF Status GHRSST Reanalysis Example L4 Analyses Future Activities GlobColour Connection Villefranche sur mer,

Medspiration user meeting, dec 4-6 Use of Medspiration and GHRSST data in the Northern Seas Jacob L. Høyer & Søren Andersen Center for Ocean and Ice, Danish.

Characterizing and comparison of uncertainty in the AVHRR Pathfinder SST field, Versions 5 & 6 Robert Evans Guilllermo Podesta’ RSMAS Nov 8, 2010 with.

1 High Resolution Daily Sea Surface Temperature Analysis Errors Richard W. Reynolds (NOAA, CICS) Dudley B. Chelton (Oregon State University)

1 A High Resolution Daily SST Analysis Richard W. Reynolds (NOAA, CICS) Dudley B. Chelton (Oregon State University) Thomas M. Smith (NOAA, STAR)

Progress in Data Merging/Gridding & CDR and Differences Between Global SST Averages in Gridded Data Sets Alexey Kaplan Lamont-Doherty Earth Observatory.

1 Improved Sea Surface Temperature (SST) Analyses for Climate NOAA’s National Climatic Data Center Asheville, NC Thomas M. Smith Richard W. Reynolds Kenneth.

1 NOAA’s National Climatic Data Center April 2005 Climate Observation Program Blended SST Analysis Changes and Implications for the Buoy Network 1.Plans.

1 Overview LTSRF Status GHRSST Reanalysis Example L4 Analyses Future Activities Beijing, October 2006 The GODAE High Resolution.

GHRSST Data Access Tutorial GHRSST Data Access How to Access GODAE High Resolution SST Products from the GDAC and LTSRF Kenneth.

Recent activities on utilization of microwave imager data in the JMA NWP system - Preparation for AMSR2 data assimilation - Masahiro Kazumori Japan Meteorological.

1 Comparisons of Daily SST Analyses for NOAA’s National Climatic Data Center Asheville, NC Richard W. Reynolds (NOAA, NCDC) Dudley B. Chelton.

MISST FY1 team meeting April 5-6, Miami, FL NOAA: Gary Wick, Eric Bayler, Ken Casey, Andy Harris, Tim Mavor Navy: Bruce Mckenzie, Charlie Barron NASA:

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.

Dataset Development within the Surface Processes Group David I. Berry and Elizabeth C. Kent.

Other Related Activities Gary Jedlovec transitioning unique NASA data and research technologies to operations Single image MODIS Composite.

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.

Page 1© Crown copyright HadISST2: progress and plans Nick Rayner, 14 th March 2007.

On the Model’s Ability to Capture Key Measures Relevant to Air Quality Policies through Analysis of Multi-Year O 3 Observations and CMAQ Simulations Daiwen.

General Objective: Conduct R&D activities to improve the quality of SST products used by MERSEA modeling and assimilation centers and produce global, Atlantic.

1 Agenda Review Issues Melbourne, May 2007 Kenneth S. Casey NOAA National Oceanographic Data Center May 2007 Gary Wick, Rapporteur GHRSST-8 Session-8 Reanalysis.

GHRSST XIV STM – AUS TAG. Woods Hole 18 June 2013, Cape Cod, MA 1 GHRSST 2013 Annual Meeting – AUS TAG breakout session 18 June, 2013, Woods Hole, MA SQUAM.

AMSR-E SSTs in the Multi-sensor Improved SST (MISST) for GODAE : A US contribution to GHRSST-PP Research, Data, and Impacts.

General Objective: Conduct R&D activities to improve the quality of SST products used by MERSEA modeling and assimilation centers and produce global, Atlantic.

ISAC Contribution to Ocean Color activity Mediterranean high resolution surface chlorophyll mapping Use available bio-optical data sets to estimate the.

Meeting Description 8th GHRSST-PP Science Team MeetingMelbourne, Victoria - 14th - 18th May 2007 Status and Application of the HR-DDS Dave Poulter Ocean.

Welcome to the PRECIS training workshop

AQUA AMSR-E MODIS POES AVHRR TRMM TMI ENVISAT AATSR GOES Imager Multi-sensor Improved SST (MISST) for GODAE Part I: Chelle Gentemann, Gary Wick Part II:

GHRSST XI Meeting, IC-TAG Breakout Session, 22 June 2010, Lima, Peru Cross-monitoring of L4 SST fields in the SST Quality Monitor (SQUAM)

1 Daily OI Analysis for Sea Surface Temperature NOAA’s National Climatic Data Center Asheville, NC Richard W. Reynolds (NOAA, NCDC) Thomas M. Smith (NOAA,

1 Overview LTSRF Status GHRSST Reanalysis Example L4 Analyses Future Activities D.C., Nov 2006 Long Term Stewardship and Reanalysis.

General Objective: to improve the quality of SST products used by EU-MERSEA modeling and assimilation centres and produce Mediterranean Sea analyzed SST.

Infrared and Microwave Remote Sensing of Sea Surface Temperature Gary A. Wick NOAA Environmental Technology Laboratory January 14, 2004.

NOAA Environmental Technology Laboratory Gary A. Wick Observed Differences Between Infrared and Microwave Products Detailed comparisons between infrared.

The GODAE High Resolution SST Project as an NDE Customer Presented By Ken Casey (NESDIS/NODC)

NOAA Climate Observation Annual Review Silver, Spring, MD Sept. 3-5, Intercomparisons Among Global Daily SST Analyses NOAA’s National Climatic Data.

Visualising spatial archaeological data The Aboriginal Sites Decision Support Tool (ASDST) Mal Ridges.

Quality Flags: Two separate sets of QFs are provided in IDPS Product: (1) SST QFs; and (2) VIIRS Cloud Mask. Analyses were aimed at identifying a suitable.

9th GHRSST-PP Science Team Meeting Perros-Guirec, Brittany France, 9-13 June 2008 Merging Satellite Infrared and Microwave Sea Surface Temperature in the.

BLUElink> Regional High-Resolution SST Analysis System – Verification and Inter-Comparison Helen Beggs Ocean & Marine Forecasting Group, BMRC, Bureau of.

CLIMAR-III, Gdynia, Poland, May 2008 Advances in the AVHRR Pathfinder Sea Surface Temperature Climate Data Record and its Connections with GHRSST Reanalysis.

The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology Ship SST data for satellite SST and ocean.

AQUA AMSR-E MODIS POES AVHRR TRMM TMI ENVISAT AATSR GOES Imager Multi-sensor Improved SST (MISST) for GODAE Part I: Chelle Gentemann, Gary Wick Part II:

AQUA AMSR-E MODIS POES AVHRR TRMM TMI ENVISAT AATSR Multi-satellite, multi-sensor data fusion: global daily 9 km SSTs from MODIS, AMSR-E, and TMI

Report from the Australian Regional Data Assembly Centre Helen Beggs 1, Leon Majewski 2 and Justin Freeman 1 1 Centre for Australian Weather and Climate.

1 Two- Stage High Resolution Daily SST Analysis Richard W. Reynolds (NOAA’s CICS) Dudley B. Chelton (Oregon State University) Thomas M. Smith (NOAA, STAR)

A comparison of AMSR-E and AATSR SST time-series A preliminary investigation into the effects of using cloud-cleared SST data as opposed to all-sky SST.

Use of high resolution global SST data in operational analysis and assimilation systems at the UK Met Office. Matt Martin, John Stark,

Ocean Monitoring and Forecasting A Commercial Perspective Dr Ralph Rayner Ocean Numerics/Fugro GEOS.

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.

How to Access Data from the Group for High Resolution Sea Surface Temperature (GHRSST) at the Global Data Assembly Center (GDAC) and the Long Term Stewardship.

2 Jun 09 UNCLASSIFIED 10th GHRSST Science Team Meeting Santa Rosa, CA 1 – 5 June Presented by Bruce McKenzie Charlie N. Barron, A.B. Kara, C. Rowley.

New HR-DDS User Services David J. S. Poulter, National Oceanography Centre, UK

Characterizing and comparison of uncertainty in the AVHRR Pathfinder Versions 5 & 6 SST field to various reference fields Robert Evans Guilllermo Podesta’

© Crown copyright Met Office Report of the GHRSST Inter-Comparison TAG (IC-TAG) Matt Martin GHRSST XI meeting, Lima, Peru, June 2010.

Edward Armstrong Jorge Vazquez Mike Chin Mike Davis James Pogue JPL PO.DAAC California Institute of Technology 28 May 2009 GHRSST Symposium, Santa Rosa,

New Australian High Resolution AVHRR SST Products from the Integrated Marine Observing System Presented at the GHRSST Users Symposium, Santa Rosa, USA,

Martin Rutherford Technical Director Oceanography and Meteorology Royal Australian Navy 28 May 2009 Processing and Displaying GHRSST data using ESRI ArcGIS.

Earth Science Datacasting Informed Pull of GHRSST data using Really Simple Syndication (RSS)

SST and SIC in HIRLAM and HARMONIE Mariken Homleid ALADIN/HIRLAM Workshop/ASM, 14 May 2009.

The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology Systematic biases in satellite SST observations.

GHRSST-9 Perros-Guirec, France 9-13 June Intercomparisons Among Global Daily SST Analyses NOAA’s National Climatic Data Center Asheville, NC, USA.

Satellite-based air-sea heat fluxes using GHRSST L4 analysis products Chris Jeffery NOAA National Oceanographic Data Center.

1 Objective Determination of Feature Resolution in an SST Analysis Dudley B. Chelton (Oregon State University) Richard W. Reynolds (NOAA, CICS) Dimitris.

NOAA Report on Ocean Parameters - SST Presented to CGMS-43 Working Group 2 session, agenda item 9 Author: Sasha Ignatov.

Presentation transcript:

Martin Rutherford Technical Director Oceanography and Meteorology Royal Australian Navy 02 Jun 2009 Towards a Bias Corrected L4 Median

Scope n Motivation – Spoilt with choice! n Creating a simple median using ArcGIS n Analysing the Median n Bias corrections n What next!

Motivation n 1984 – CSIRO -Weekly ‘best image’ based on cloud content -AVHRR only -Hard copy by priority post -Customers were happy (previously had nothing) n 1992 – BoM regional SST image -Updated after each AVHRR pass -Weighted blend based on age, but no OI -Sourced using McIDAS, delivered via the web -Customers were happy (timely, fewer gaps)

Motivation n NAVO MCSST K10 -Global daily 10 km analysis -OI, no cloud holes -Processed as web map service and posted on internet -Customers were happy (more timely, higher resolution) n Added OSTIA as web map service -Added K10 – OSTIA differences ~ confidence -Customers NOT happy (which one do they use?)

Lessons Learned n Customers want: -Web-based delivery -Frequent updates -High resolution -A measure of confidence/uncertainty -Animation n Customers do NOT want: -Choice

A (Not so) Simple Median n Use Python and GIS tools to: -Download all L4 products -Interpolate to common grid -0.1, 0.25, 0.5?? -Bilinear, cubic ?? -Calculate median and standard deviation -Display as Web Map Service -Deliver as GIS compatible layer

Best Spatial Resolution ?

Best Interpolation Method ?

Decision Point ! n Re-sample to 0.1 Degree n Use Cubic Interpolation

The Daily Product

Contributing to the Median

Calculating the Bias n Find daily (Interpolated - Median) n Bias = Median of daily (Interpolated – Median)

Bias: ABOM GAMSSA

Bias: EUR ODYSSEA

Bias: NAVO K10

Bias: NCDC AVHRR

Bias: NCDC AVHRR + AMSR

Bias: REMSS MW+IR

Bias: UKMO OSTIA

Applying the Bias n Apply bias correction to daily Interpolated n Find new daily median

Testing for Impact n Compare Standard Deviation n Compare contributions to median

Testing for Impact – Std. Dev.

ABOM GAMSSA ‘Bias’

GAMSSA Uncorrected Contribution

GAMSSA Corrected Contribution

EUR ODYSSEA ‘Bias’

ODYSSEA Uncorrected Contribution

ODYSSEA Corrected Contribution

NAVO K10 ‘Bias’

K10 Uncorrected Contribution

K10 Corrected Contribution

NCDC AVHRR ‘Bias’

AVHRR Uncorrected Contribution

AVHRR Corrected Contribution

NCDC AVHRR + AMSR ‘Bias’

AVHRR + AMSR Uncorrected Contribution

AVHRR + AMSR Corrected Contribution

UKMO OSTIA ‘Bias’

OSTIA Contribution

OSTIA Corrected Contribution

REMSS MW + IR ‘Bias’

REMSS Uncorrected Contribution

REMSS Corrected Contribution

Percentage of Observations in Median

What Next? n Seek GHRSST Science Team Advice!! n Re-do all calculations! n Publish uncorrected median and Std. Dev. n Compare with GMPE

Bigger Questions! n Should users be correcting GHRSST products? n Has this technique any merit?? n How do I provide the ‘best’ information for my users from existing GHRSST products: -Global -10km or better -0.5 K or better -Six hourly -Near real time -Including diurnal variability

Comments?