15 May 2009ACSPO v1.10 GAC1 ACSPO upgrade to v1.10 Effective Date: 04 March 2009 Sasha Ignatov, XingMing Liang, Yury Kihai, Boris Petrenko, John Stroup.

Slides:

Advertisements

Similar presentations

Improvements to the NOAA Geostationary Sea Surface Temperature Product Suite Eileen Maturi, NOAA/NESDIS/STAR Andy Harris, Jonathan Mittaz, Prabhat Koner.

Advertisements

JPSS and GOES-R SST Sasha Ignatov

Pathfinder –> MODIS -> VIIRS Evolution of a CDR Robert Evans, Peter Minnett, Guillermo Podesta Kay Kilpatrick (retired), Sue Walsh, Vicki Halliwell, Liz.

Upgrades to the MODIS near-IR Water Vapor Algorithm and Cirrus Reflectance Algorithm For Collection 6 Bo-Cai Gao & Rong-Rong Li Remote Sensing Division,

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.

Satellite SST Radiance Assimilation and SST Data Impacts James Cummings Naval Research Laboratory Monterey, CA Sea Surface Temperature Science.

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

Xin Kong, Lizzie Noyes, Gary Corlett, John Remedios, Simon Good and David Llewellyn-Jones Earth Observation Science, Space Research Centre, University.

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

GOES-13 Science Team Report SST Images and Analyses Eileen Maturi, STAR/SOCD, Camp Springs, MD Andy Harris, CICS, University of Maryland, MD Chris Merchant,

NOAA Climate Obs 4th Annual Review Silver Spring, MD May 10-12, NOAA’s National Climatic Data Center 1.SSTs for Daily SST OI NOAA’s National.

Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 NOAA Operational Geostationary Sea Surface Temperature Products from NOAA.

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.

Improved NCEP SST Analysis

CRN Workshop, March 3-5, An Attempt to Evaluate Satellite LST Using SURFRAD Data Yunyue Yu a, Jeffrey L. Privette b, Mitch Goldberg a a NOAA/NESDIS/StAR.

4 June 2009GHRSST-X STM - SQUAM1 The SST Quality Monitor (SQUAM) 10 th GHRSST Science Team Meeting 1-5 June 2009, Santa Rosa, CA Alexander “Sasha” Ignatov*,

Walton McBride U.S. Naval Research Lab, Stennis Space Center MS Robert Arnone University of Southern Mississippi, Stennis Space Center MS Jean-François.

Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 CLOUD MASK AND QUALITY CONTROL FOR SST WITHIN THE ADVANCED CLEAR SKY PROCESSOR.

MODIS Sea-Surface Temperatures for GHRSST-PP Robert H. Evans & Peter J. Minnett Otis Brown, Erica Key, Goshka Szczodrak, Kay Kilpatrick, Warner Baringer,

Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 MAP (Maximum A Posteriori) x is reduced state vector [SST(x), TCWV(w)]

Number of match-ups Mean Anomaly Fig. 3. Time-series of night MUT SST anomaly statistics compared to daily OISST SST. SST from different platforms mostly.

Quantifying the effect of ambient cloud on clear-sky ocean brightness temperatures and SSTs Korak Saha 1,2, Alexander Ignatov 1, and XingMing Liang 1,2.

Satellite-derived Sea Surface Temperatures Corey Farley Remote Sensing May 8, 2002.

1 Center for S a t ellite A pplications and R esearch (STAR) Applicability of GOES-R AWG Cloud Algorithms for JPSS/VIIRS AMS Annual Meeting Future Operational.

1 GOES-R AWG Product Validation Tool Development Sea Surface Temperature (SST) Team Sasha Ignatov (STAR)

1 SST Near-Real Time Online Validation Tools Sasha Ignatov (STAR) AWG Annual Meeting June 2011, Ft Collins, CO.

Andrew Heidinger and Michael Pavolonis

Monitoring/Validation of HR SSTs in SQUAM GHRSST-XV, 2-6 June 2014, Cape Town, South Africa 1 The 15 th GHRSST 2014 meeting, ST-VAL Breakout session 2–6.

Which VIIRS product to use: ACSPO vs. NAVO GHRSST-XV, 2-6 June 2014, Cape Town, South Africa 1 Prasanjit Dash 1,2, Alex Ignatov 1, Yuri Kihai 1,3, John.

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,

Evaluation of OMI total column ozone with four different algorithms SAO OE, NASA TOMS, KNMI OE/DOAS Juseon Bak 1, Jae H. Kim 1, Xiong Liu 2 1 Pusan National.

TOMS Ozone Retrieval Sensitivity to Assumption of Lambertian Cloud Surface Part 1. Scattering Phase Function Xiong Liu, 1 Mike Newchurch, 1,2 Robert Loughman.

MODIS Sea-Surface Temperatures for GHRSST-PP Peter J. Minnett & Robert H. Evans Otis Brown, Erica Key, Goshka Szczodrak, Kay Kilpatrick, Warner Baringer,

Daily observation of dust aerosols infrared optical depth and altitude from IASI and AIRS and comparison with other satellite instruments Christoforos.

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

Retrieval Algorithms The derivations for each satellite consist of two steps: 1) cloud detection using a Bayesian Probabilistic Cloud Mask; and 2) application.

CM-SAF Board Meeting, Helsinki, September 2006 CM-SAF TOA radiation status report D. Caprion Royal Meteorological Institute of Belgium.

Cloud property retrieval from hyperspectral IR measurements Jun Li, Peng Zhang, Chian-Yi Liu, Xuebao Wu and CIMSS colleagues Cooperative Institute for.

A step toward operational use of AMSR-E horizontal polarized radiance in JMA global data assimilation system Masahiro Kazumori Numerical Prediction Division.

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

AVHRR Radiance Bias Correction Andy Harris, Jonathan Mittaz NOAA Cooperative Institute for Climate Studies University of Maryland Some concepts and some.

November 28, 2006 Derivation and Evaluation of Multi- Sensor SST Error Characteristics Gary Wick 1 and Sandra Castro 2 1 NOAA Earth System Research Laboratory.

Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Monitoring of IR Clear-sky Radiances over Oceans for SST (MICROS) Alexander.

24 January th AMS Symposium on Future Operational Environmental Satellite Systems 22 – 26 January 2012, New Orleans, LA NPP VIIRS SST Algorithm.

2 November 2011JPSS SST at STAR 1 2 nd NASA SST Science Team Meeting 2 – 4 November 2011, Miami Beach, FL Joint Polar Satellite System (JPSS) SST Algorithm.

Preliminary results from the new AVHRR Pathfinder Atmospheres Extended (PATMOS-x) Data Set Andrew Heidinger a, Michael Pavolonis b and Mitch Goldberg a.

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.

GHRSST HL_TAG meeting Copenhagen, March 2010 Validation of L2P products in the Arctic Motivation: Consistent inter-satellite validation of L2p SST observations.

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.

Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Image: MODIS Land Group, NASA GSFC March 2000 Advanced Clear-Sky Processor.

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

International GHRSST User Symposium Santa Rosa, California, USA 28-29th May 2009 MODIS Sea-Surface Temperatures Peter J Minnett & Robert H. Evans With.

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.

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

EARWiG: SST retrieval issues for High Latitudes Andy Harris Jonathan Mittaz NOAA-CICS University of Maryland Chris Merchant U Edinburgh.

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

Validation in Arctic conditions Steinar Eastwood (met.no) David Poulter (NOCS) GHRSST9, Perros-Guirec OSI SAF METOP SST, days mean.

Prototyping SST Retrievals from GOES-R ABI with MSG SEVIRI Data Nikolay V. Shabanov 1,2, (301)

May 28-29, 2009GHRSST 2009 International Users Symposium National Oceanic and Atmospheric Administration Group for High Resolution Sea Surface Temperature.

29 May 2009GHRSST User's Symp - SQUAM1 The SST Quality Monitor (SQUAM) 1 st GHRSST Int’l User’s Symposium May 2009, Santa Rosa, CA Alexander “Sasha”

GSICS Telecon July 2012 AVHRR, MODIS, VIIRS Radiance Monitoring in MICROS and GSICS help to SST Sasha Ignatov.

Monitoring of SST Radiances

Joint GRWG and GDWG Meeting February 2010, Toulouse, France

SST – GSICS Connections

Tony Reale ATOVS Sounding Products (ITSVC-12)

Extending MICROS to include Solar Reflectance Bands (SRB)

Using Double Differences in MICROS for Cross-Sensor Consistency Checks

Towards Understanding and Resolving Cross-Platform Biases in MICROS

Radiometric Consistency between AVHRR, MODIS, and VIIRS in SST Bands

Presentation transcript:

15 May 2009ACSPO v1.10 GAC1 ACSPO upgrade to v1.10 Effective Date: 04 March 2009 Sasha Ignatov, XingMing Liang, Yury Kihai, Boris Petrenko, John Stroup NOAA/NESDIS/STAR John Sapper and Denise Frey NOAA/NESDIS/OSDPD

15 May 2009ACSPO v1.10 GAC2 Major upgrades in ACSPO v1.10  daily (AVHRR-based) 0.25º Reynolds SST (instead of weekly 1º)  new Community Radiative Transfer Model v1.1 (instead of r577)  CRTM built-in Wu-Smith emissivity model (instead of flat-surface Fresnel)  Plank-weighted (PW) CRTM coefficients for NOAA-17, -18, -19, and MetOp-A (for NOAA-16, ORD coefficients are still used)  Improved cloud detection -Using dynamic biases for brightness temperatures and SST filters estimated in real-time. (Before, biases were assumed to be constant) -Introducing ambient cloud filter  Day-night switch for cloud mask and SST algorithm occurs at 90° Solar Zenith Angle (instead of 85° in v1.00)

15 May 2009ACSPO v1.10 GAC3 Number of Observations

15 May 2009ACSPO v1.10 GAC4 During nighttime, number of OBS reduced due to -Change in day-night threshold from 85° to 90° SZA -Using ambient cloud filter Number of Observations: NIGHTTIME v1.00 v1.10

15 May 2009ACSPO v1.10 GAC5 During daytime, number of OBS increased due to -Change in day-night threshold from 85° to 90° SZA (despite adding ambient cloudiness filter) Number of Observations: DAYTIME v1.00 v1.10

15 May 2009ACSPO v1.10 GAC6 Cloud Mask

15 May 2009ACSPO v1.10 GAC7 “Sat-Reynolds” SST anomalies in ACSPO v1.00 (3 March 2009) -Note multiple areas with negative anomalies (likely due to cloud leakage) -Cold biases at swath edges Cloud Mask Quality: ACSPO v1.00 NightDay

15 May 2009ACSPO v1.10 GAC8 “Sat-Reynolds” SST anomalies in ACSPO v1.10 (4 March 2009) -Areas with negative anomalies reduced -Cold biases at swath edges reduced Cloud Mask Quality: ACSPO v1.10 NightDay

15 May 2009ACSPO v1.10 GAC9 SST

15 May 2009ACSPO v1.10 GAC10 -Standard Deviation of “SAT-Reynolds” SST reduced -Weekly cycle significantly reduced or removed Nighttime RMS “Sat-Reynolds” SST improved v1.00 v1.10

15 May 2009ACSPO v1.10 GAC11 Daytime RMS “Sat-Reynolds” SST improved v1.00 v1.10 -Standard Deviation of “SAT-Reynolds” SST reduced -Weekly cycle significantly reduced or removed

15 May 2009ACSPO v1.10 GAC12 Channel 4 Clear-Sky Brightness Temperatures

15 May 2009ACSPO v1.10 GAC13 Nighttime RMS “CRTM-AVHRR” v1.00 v1.10 -Standard Deviation of “CRTM-AVHRR” BT reduced -Weekly cycle significantly reduced or removed

15 May 2009ACSPO v1.10 GAC14 v1.00 v1.10 Daytime RMS “CRTM-AVHRR” -Standard Deviation of “CRTM-AVHRR” BT reduced -Weekly cycle significantly reduced or removed

15 May 2009ACSPO v1.10 GAC15  Number of nighttime observations slightly reduced  Number of daytime obs slightly increased  Cloud mask improved during both day and night  AVHRR SST in v1.10 agrees better with Reynolds SST  Brightness Temperatures agree better with CRTM  For more information see Summary of Performance ACSPO v1.10 vs1.00

15 May 2009ACSPO v1.10 GAC16  View Zenith Angle biases in retrieved SSTs have been reduced in v1.10 but we still do not recommend using SSTs beyond VZA>55º, at least for quantitative analyses. (Note that the clear-sky brightness temperatures are less subject to the angular biases.)  Residual cloud problem has been reduced in v1.10 but nighttime SSTs are still subject to residual cloud in the areas with persistent cloudiness (such as the roaring forties in the North and in the South and ITCZ). Caution should be used with the current nighttime product in those areas.  The aerosol optical depth parameters for channels 1, 2, and 3a have not been fully evaluated yet so please use caution if using these parameters Known Limitations in ACSPO v1.10

15 May 2009ACSPO v1.10 GAC17  ACSPO v1.20 -Land-sea mask (1km instead of 8km) + land proximity distance -Day-night twilight zone indication -Code modularization, stability, & error handling -Resolve remaining FRAC/GAC inconsistencies  ACSPO v1.30 -Graceful degradation (Reynolds SST & GFS) -Cloud mask improvements  ACSPO v1.40 -L1b converter as front end -Further code modularization & clean-up  Level 2P, 3 and 4 development -Currently, ACSPO products are only available in L2 (swath granules) -Development of L2P (GHRSST compliant), L3 (field analysis) and L4 (weekly and monthly composites) products is currently underway Ongoing ACSPO improvements