JPSS and GOES-R SST

Sasha Ignatov

John Stroup, Yury Kihai, Boris Petrenko, Prasanjit Dash, Xingming Liang,Irina Gladkova, John Sapper, Feng Xu, Xinjia Zhou, Maxim Kramar,

Yaoxian Huang, Marouan Bouali, Karlis Mikelsons

NOAA; CIRA; GST Inc; CUNY

Bruce Brasnett

Canadian Met Centre

25 February 2015 JPSS and GOES-R SST 1

2015 NOAA Satellite Science Week 23-27 February 2015, Boulder, CO

Outline

JPSS SST– From POES/EOS to JPSS (via NPOESS)– JPSS SST Product – ACSPO

(Advanced Clear-Sky Processor for Oceans)– ACSPO SST replaces the initial “IDPS SST EDR”– NOAA SST Monitoring– Users

GOES-R SST: Work in progress– Himawari-8 SST Project– NOAA SST Monitoring is updated to include Geo– Polar and Geo ACSPO codes are consolidated

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JPSS – Joint Polar Satellite System (1:30 am/pm orbit) S-NPP (Oct’2011) J1 (2017), J2 (2023)

S-NPP – The Suomi National Polar-orbiting Partnership Bridge between NOAA POES / NASA EOS and JPSS Successfully launched on 28 October 2011

VIIRS – Visible Infrared Imager Radiometer Suite Replaces AVHRR – workhorse onboard NOAA / METOP Builds on MODIS heritage: Multispectral, high spatial

resolution, high radiometric performance and imagery VIIRS Data Products

- RDRs: Raw Data Records (L1A)- SDRs: Sensor Data Records (L1B)- EDRs: Environmental Data Records (L2)

JPSS, S-NPP, VIIRS

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Role / Responsibility

NOAA POES, NASA EOS NPOESS

JPSS (Owned by NOAA, 2010)

Platform, Launch Vehicle Private Industry Private Industry Private Industry

Instruments Private Industry Private Industry Private Industry

Algorithms Government Private Industry Government

Data Products Government Private Industry Government

Cal/Val Government Private Industry Government

Archival & Distribution Government Government Government

NPOESS Data Products:IDPS – Interface Data Processing Segment

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Algorithms: NPOESS/IPO/Northrop Grumman Operational Products: NPOESS/IPO/Raytheon IDPS (RDR, SDR, EDR)

ACSPO – NOAA Advanced Clear-Sky Processor for Ocean (ACSPO) NOAA heritage SST system, operational with AVHRR 4km/GAC & 1km/FRAC Jan 2012: Experimental with VIIRS and Terra/Aqua MODIS Mar –May 2014: Operational with VIIRS: Archived @PO.DAAC & NODC Reported in10min granules (aggregate of original 86sec granules)

IDPS – Interface Data Processing Segment (IDPS) NPOESS SST EDR was developed by Northrop Grumman Operated by Raytheon, Archived at CLASS. Transitioned to NOAA in 2010 Reported in original 86sec granules

NOAA ended up with two VIIRS SST Products Evaluation of IDPS EDR has shown large room for improvement IDPS SST has substantially improved, but still outperformed by ACSPO There was a confusion in users’ community about 2 JPSS products at NOAA Users requested ACSPO SST and expressed no interest in IDPS EDR In Jan 2014, JPSS Program Office recommends “discontinue the IDPS SST

EDR, and concentrate on ACSPO sustainment, development, and Cal/Val”

VIIRS SST Products at NOAA

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STAR leads monitoring and Cal/Val of NOAA and partners’ SST products

Products are monitored online in near-real time, to ensure high quality & consistency, to support and facilitate SST applications

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

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

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

NOAA SST Monitoring

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DAY: ACSPO L2 minus CMC L416 February 2015

25 February 2015

• Delta close to zero as expected• Cold spots – Residual Cloud/Aerosol leakages• Warm spots – Diurnal warming

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DAY: IDPS L2 minus CMC L416 February 2015

25 February 2015

• IDPS SST Algorithms consistent with ACSPO• Residual cloud leakages more pronounced• Diurnal Warming spots consistent with ACSPO

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DAY: ACSPO L2 minus in situ SST16 February 2014

25 February 2015

• Shape close to Gaussian, cold tail suggests residual cloud• Performance Stats well within specs (Bias<0.2K, STD<0.6K)

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NIGHT: IDPS L2 minus in situ SST16 February 2015

25 February 2015

• Cold tail more pronounced – more residual cloud• Performance Stats degraded compared to ACSPO• On this particular day, IDPS is not meeting specs

DAY STD DEV wrt. in situ SST

IDPS SST improved but still out of family & not meeting specs

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• Wrt. OSTIA SST, the pedestal is smaller– OSTIA “internal noise” smaller

• Both OSISAF and ACSPO STDs are reduced, but OSISAF to a greater extent. Recall that OSISAF L2 is assimilated in OSTIA L4 and ACSPO is not

All ACSPO products from AVHRR, MODIS,and VIIRS in family and meeting specs

OSISAF Metop-AACSPO Metop-A

Some Early Results Assimilating ACSPO VIIRS L2P Datasets

Bruce BrasnettCanadian Meteorological CentreMay, 2014

ACSPO VIIRS L2P Datasets

• Received courtesy of colleagues at STAR

• Two periods: 1 Jan – 31 Mar 2014 & 15 Aug – 9 Sep 2013

• Experiments carried out assimilating VIIRS data only and VIIRS data in combination with other satellite products

• Rely on independent data from Argo floats to verify results (Argo floats do not sample coastal regions or marginal seas)

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Assessing relative value of 2 VIIRS datasets: NAVO vs. ACSPO

Using ACSPO improves CMC assimilation, at all latitudes

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CMC Summary

• ACSPO VIIRS L2P is an excellent product

• Daily coverage with this product is very good over internal and coastal waters, in the Tropics, and in the High Latitudes

• Based on the Jan – Mar 2014 sample, ACSPO VIIRS contains more information than either the NAVO VIIRS, OSI-SAF Metop-A or the RSS AMSR2 datasets

• CMC assimilated ACSPO VIIRS SST in May 2014, as soon as it was archived at PO.DAAC and NODC

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SST is an essential climate variable

VIIRS/ABI unprecedented imagery, accuracy, precision, spatial/temporal resolution lead to superior SST analysis, forecast, applications

JPSS SST is fused with other satellite and in situ SSTs, to produce blended L4 products. GOES-R SST will be included in analyses

VIIRS/ABI resolution & quality is unique, and allows exploration of new techniques: Pattern recognition, Temporal analysis, and Radiative transfer methodology

Continuous monitoring and validation of the products in near real time is needed, for optimal applications

S-NPP VIIRSMSG SEVIRI

JPSS and GOES-R SST

ACSPO SST and Monitoring JPSS SST: Retrieval and Monitoring in advanced stage ACSPO retrieval domain and performance statistics

comparable, or superior to other community products JPSS SST used in blended products (NOAA geo-polar blended,

CMC L4; UK MO OSTIA, BoM GAMSSA, JMA MGD) Focus on users – working individually, addressing concerns

Geo work underway Himawari SST Project Consolidation of Geo/Polar ACSPO SST codes Incorporation of Geo SST in NOAA SST Monitoring

Polar work underway Generation of JPSS L3 (requested by CMC, UK MO, BoM, JMA) Reprocessing L2 and L3 back to Jan 2012 and Archival

Conclusion and Ongoing Work

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Thank You!

Questions?Alex.Ignatov@noaa.gov

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Back Up Slides

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Examples of ACSPO Imagery

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ACSPO

Florida

ACSPO_V2.30b01_NPP_VIIRS_2014-01-18_1810-1819_20140314.184153_NAVO

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Korea

China

ACSPO

ACSPO_V2.30b01_NPP_VIIRS_2014-01-18_0440-0450_20140314.145310_NAVO

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ACSPO

Africa

ACSPO_V2.30b01_NPP_VIIRS_2014-01-18_1440-1450_20140314.174252_NAVO

ACSPO destriping capability

Currently under testing for NOAA Operations

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DAY – SST from original BTs in M15 and M16

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Striping affects quality of SST imagery and Ocean Dynamics Analyses

DAY – SST from destriped BTs in M15 and M16

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Destriping is applied to brightness temperatures and improves SST

VIIRS vs. AVHRR and MODIS

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Characteristic AVHRR FRAC MODIS VIIRS

File compression No Yes No

Swath width, km 2,900 2,330 3,000

Pixel size @Nadir, km

1 1 0.76

# of FOVs (Pixels) per scan line

2,048 1,354 3,200

# of Detectors 1 10 16

# of push brooms per 5 min interval

3,600 203 167.4

# of scan lines per 5 min interval

3,600*1=3,600 203*10=2,030 167.4*16=2,679

L1b file aggregation

All bands + Geo = 1 file

All bands = 1file + Geo = 1file

Each band = 1file + Geo = 1file

# of L1b files/24hr 28 ×Half-orbits 576 × 5min~4,000 × 86sec

(3 bands+1 geo)

AVHRR, MODIS and VIIRS Characteristics

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VIIRS1 MODIS – Aqua2 AVHRR3 (A)ATSR4

λ, µm NEDT, K @300K

λ, µm NEDT, K @300K

λ, µm NEDT, K @300K

λ, µm NEDT, K @300K

3.70.110.04

3.75 0.050.03

3.750.12

0.08-0.353.7

0.080.02

Not available on VIIRS 3.96

0.070.02

Used by U. Miamifor producing MO(Y)D28

4.00.110.04

4.020.070.02

Currently not used

8.550.050.03

8.520.050.02

Currently not used

10.80.070.03

11.030.050.02

10.50.12

0.03-0.1010.8

0.050.03

12.00.070.03

12.020.050.03

11.50.12

0.08-0.1312.0

0.050.03

SpecsOn-Orbit

1Cao and VIIRS SDR Team, https://cs.star.nesdis.noaa.gov/NCC/VIIRS2Xiong et al., IEEE/TGRS, 2009; 3Trishchenko et al., JGR, 2002 (NOAA9-16);

4Merchant and Embury, Personal communication, 2012

NEdT in SST Bands (BB-based; Not aggregated pixels)

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