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AGU Ocean Sciences Conference 28 February 2014, Honolulu, HI. Towards Stable and Consistent Long-Term SST and Brightness Temperature Records from Multiple AVHRRs and QCed in situ Data Advanced Clear-Sky Processor for Ocean AVHRR Reanalysis (ACSPO AVHRR RAN) Sasha Ignatov , Xinjia Zhou,

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AGU Ocean Sciences Conference28 February 2014, Honolulu, HI

Towards Stable and Consistent Long-Term SST

and Brightness Temperature Records

from Multiple AVHRRs and QCed in situ Data

Advanced Clear-Sky Processor for Ocean

AVHRR Reanalysis (ACSPO AVHRR RAN)

Sasha Ignatov, Xinjia Zhou,

Boris Petrenko, Xingming Liang, Prasanjit Dash

NOAA STAR, CIRA, GST Inc

ACSPO AVHRR Reanalysis


NOAA Coral Reef Watch Program: Mark Eakin (Lead), Jacqueline Rauenzahn

POES-GOES Blended Team: Eileen Maturi (Lead), Andy Harris, Jon Mittaz

NOAA Ocean Remote Sensing Program: Paul DiGiacomo (Program Manager); Marilyn Yuen-Murphy (DPM)

ACSPO SST Team: John Sapper, Yury Kihai, John Stroup

NOAA in situ SST Quality Monitor (iQuam): Feng Xu

NOAA Community Radiative Transfer (CRTM) Team: Mark Liu, Yong Chen, Yong Han, Fuzhong Weng

Acknowledgements

ACSPO AVHRR Reanalysis


Motivation and Objective of ACSPO RAN

ACSPO – Advanced Clear-Sky Processor for Oceans

  • NOAA polar SST retrieval system

    • Operational with AVHRR (GAC, FRAC) and SNPP VIIRS

    • Experimental with Terra and Aqua MODIS

  • Fast CRTM is used to simulate TOA BTs, for improved cloud mask, physical SST retrievals, sensors monitoring, and CRTM validation

    Why ACSPO AVHRR Reanalysis?

  • NOAA Coral Reef Watch (CRW) and POES-GOES Blended Teams are ACSPO users

  • Long-term time series of ACSPO SST will be blended with GOES SST, and “L4 climatology” generated for CRW anomaly analyses

    Current Status (ACSPO-RAN1)

  • GAC data of NOAA-15, -16, -17, -18, -19, Metop-A , -B have been processed from 2002-pr and analyzed using NOAA Cal/Val Tools

  • Preliminary analyses summarized in this presentation

ACSPO AVHRR Reanalysis


NOAA SST/Radiance Monitoring System

SQUAM - SST Quality Monitor www.star.nesdis.noaa.gov/sod/sst/squam/

  • Monitor SST Products (L2/3/4) for Self- and Cross-Consistency

  • Validate against in situ SSTs (from iQuam)

    iQuam - In situ Quality Monitor www.star.nesdis.noaa.gov/sod/sst/iquam/

  • QC in situ SSTs

  • Monitor on the Web

  • Distribute to Users(including SQUAM)

    MICROS - Monitoring IR Clear-sky Radiances over Oceans for SST www.star.nesdis.noaa.gov/sod/sst/micros/

  • Monitor Clear-sky ocean radiances for Self- / Cross-Consistency

  • Validate against CRTM simulations

ACSPO AVHRR Reanalysis


SST Monitoring in SQUAM

www.star.nesdis.noaa.gov/sod/sst/squam/

Nighttime data are shown

(see SQUAM for daytime data)

Dash, et al: SST Quality Monitor. JTECH, 2010.

ACSPO AVHRR Reanalysis


ACSPO-RAN Metop-A/GAC L2 – OSTIA L4

1 October 2013

  • Deviation from Reference SST is flat & close to 0

  • Residual Cloud/Aerosol leakages & limb cooling (likely due to SST algorithm) are seen as cold spots

ACSPO AVHRR Reanalysis


ACSPO-RAN Metop-A/GAC L2 – OSTIA L4

1 October 2013

  • Overall shape of the histogram is close to Gaussian as expected

  • Skewed negatively due to residual cloud/aerosol contamination

ACSPO AVHRR Reanalysis


Validation vs. iQuam in situ SSTs

www.star.nesdis.noaa.gov/sod/sst/iquam/

Xu, Ignatov: In situ SST Quality Monitor. JTECH, 2014.

ACSPO AVHRR Reanalysis



ACSPO-RAN Metop-A/GAC L2 – in situ SST

1 October 2013

  • Match-ups of AVHRR GAC with in situ data ~2,300 fewer than with L4

  • VAL stats maybe geographically biased & not globally representative

ACSPO AVHRR Reanalysis


ACSPO-RAN Metop-A/GAC L2 – in situ SST

1 October 2013

  • Shape close to Gaussian

  • Long tail on the left is indicative of residual cloud

ACSPO AVHRR Reanalysis


Validation in SQUAM

against iQuam SSTs

Nighttime data are shown

(see SQUAM for daytime data)

ACSPO AVHRR Reanalysis


NIGHT ACSPO-RAN Robust STD wrt. In situ SST

  • Typically, robust STDs are within (0.40±0.05)K

  • Some platforms are closer to this “norm” (Metop-A, -B, N-17, -18)

  • Other platforms (N-15, and some periods of N-16 and -19) are more deviant

ACSPO AVHRR Reanalysis


NIGHT ACSPO-RAN Median Bias wrt. In situ SST

  • Daily VAL vs. in situ SST is noisy (small match-up sample, geographic biases)

  • Some platforms are more stable (Metop-A, -B, N-17, -19)

  • Other platforms (N-15, -16, -19) are less stable

ACSPO AVHRR Reanalysis


Brightness Temperatures Monitoring in MICROS

www.star.nesdis.noaa.gov/sod/sst/micros/

Nighttime data are shown

(see MICROS for daytime data)

Liang and Ignatov: Monitoring IR Clear-sky Radiances over Ocean for SST. JTECH, 2011

ACSPO AVHRR Reanalysis


NIGHT Double Differences SST (Ref = N-17/Metop-A)

  • Shape of DDs similar to VAL vs. In situ

  • Most stable N-17 and Metop-A were used as references; N-19 relatively stable

  • Least stable are N-15, -16 (after mid-2006), -18 (especially after mid-2011)

ACSPO AVHRR Reanalysis


NIGHT Double Differences Brightness Temp @3.7µm

  • General shape of biases vs. Reynolds similar to vs. In situ

  • Most stable Metop-A and -B, and N-17 and -19

  • Least stable are N-15, -16 after 2006), -18 (after 2011)

ACSPO AVHRR Reanalysis


ACSPO-RAN1 Summary

  • ~12 years of ACSPO AVHRR RAN1

    • N-15, -16, -17, -18, -19, Metop-A, -B processed

    • Matched up with iQuam in situ SSTs

    • Displayed in SQUAM (SSTs) and in MICROS (BTs)

    • Working with POES-GOES Blended Team to test

      Observations & Critical Need

    • N-17, -19, Metop-A, -B SSTs more stable; N-15, -16, -18 less stable

    • Instabilities in SSTs are strongly linked with instabilities in BTs

    • Fixing AVHRR BTs (FCDR) is needed for high-quality SST CDR

      ACSPO-RAN2 is underway

    • Extend ACSPO-RAN time series (initially, to 1992)

    • ACSPO: Improved 1st guess (ERA-Interim profiles, CMC SST); Cloud mask; SST algorithms; Handling pre-KLM AVHRRs

    • iQuam v2 (time series 1981-pr, ARGO floats, improved QC)

    • SQUAM: Improved handling outliers; Efficiency; Display

ACSPO AVHRR Reanalysis


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