1. JPSS and GOES-R SST Sasha Ignatov
2015 NOAA Satellite Science Week February 2015, Boulder, CO
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

2. Outline JPSS SST GOES-R SST: Work in progress
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
25 February 2015
JPSS and GOES-R SST

3. JPSS, S-NPP, VIIRS
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)
Specific for nesdis
25 February 2015
JPSS and GOES-R SST

4. NPOESS Data Products: IDPS – Interface Data Processing Segment
Role / Responsibility
NOAA POES, NASA EOS
NPOESS
JPSS (Owned by NOAA, 2010)
Platform, Launch Vehicle
Private Industry
Instruments
Algorithms
Government
Data Products
Cal/Val
Archival & Distribution
Algorithms: NPOESS/IPO/Northrop Grumman
Operational Products: NPOESS/IPO/Raytheon IDPS (RDR, SDR, EDR)
25 February 2015
JPSS and GOES-R SST

5. VIIRS SST Products at NOAA
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: & 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”
Specific for nesdis
25 February 2015
JPSS and GOES-R SST

6. NOAA SST Monitoring
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
25 February 2015
JPSS and GOES-R SST 6

7. DAY: ACSPO L2 minus CMC L4 16 February 2015
Delta close to zero as expected
Cold spots – Residual Cloud/Aerosol leakages
Warm spots – Diurnal warming
25 February 2015
JPSS and GOES-R SST

8. DAY: IDPS L2 minus CMC L4 16 February 2015
IDPS SST Algorithms consistent with ACSPO
Residual cloud leakages more pronounced
Diurnal Warming spots consistent with ACSPO
25 February 2015
JPSS and GOES-R SST

9. DAY: ACSPO L2 minus in situ SST
16 February 2014
Shape close to Gaussian, cold tail suggests residual cloud
Performance Stats well within specs (Bias<0.2K, STD<0.6K)
25 February 2015
JPSS and GOES-R SST

10. NIGHT: IDPS L2 minus in situ SST
16 February 2015
Cold tail more pronounced – more residual cloud
Performance Stats degraded compared to ACSPO
On this particular day, IDPS is not meeting specs
25 February 2015
JPSS and GOES-R SST

11. DAY STD DEV wrt. in situ SST
IDPS SST improved but still
out of family & not meeting specs
OSISAF Metop-A
ACSPO Metop-A
All ACSPO products from AVHRR, MODIS,
and VIIRS in family and meeting specs
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
25 February 2015
JPSS and GOES-R SST

12. Some Early Results Assimilating ACSPO VIIRS L2P Datasets
Bruce Brasnett
Canadian Meteorological Centre
May, 2014

13. 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)
25 February 2015
JPSS and GOES-R SST

14. Assessing relative value of 2 VIIRS datasets: NAVO vs. ACSPO
Period: Jan. 1 to Feb. 5, A data outage of the NAVO data made it impossible to use a 3-month comparison period.
Using ACSPO improves CMC assimilation, at all latitudes
25 February 2015
JPSS and GOES-R SST

15. 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
25 February 2015
JPSS and GOES-R SST

16. JPSS and GOES-R SST S-NPP VIIRS MSG SEVIRI
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
S-NPP VIIRS
MSG SEVIRI
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
25 February 2015
JPSS and GOES-R SST 16

17. Conclusion and Ongoing Work
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
Specific for nesdis
25 February 2015
JPSS and GOES-R SST

18. Thank You! Questions? Alex.Ignatov@noaa.gov 25 February 2015
Specific for nesdis
25 February 2015
JPSS and GOES-R SST

19. Back Up Slides 25 February 2015 JPSS and GOES-R SST
Specific for nesdis
25 February 2015
JPSS and GOES-R SST

20. Examples of ACSPO Imagery
Specific for nesdis
25 February 2015
JPSS and GOES-R SST

21. ACSPO Florida 25 February 2015 JPSS and GOES-R SST
ACSPO_V2.30b01_NPP_VIIRS_ _ _ _NAVO
Florida
ACSPO
25 February 2015
JPSS and GOES-R SST

22. ACSPO China Korea 25 February 2015 JPSS and GOES-R SST
ACSPO_V2.30b01_NPP_VIIRS_ _ _ _NAVO
China
Korea
ACSPO
25 February 2015
JPSS and GOES-R SST

23. ACSPO Africa 25 February 2015 JPSS and GOES-R SST
ACSPO_V2.30b01_NPP_VIIRS_ _ _ _NAVO
Africa
ACSPO
25 February 2015
JPSS and GOES-R SST

24. ACSPO destriping capability
Currently under testing for NOAA Operations
Specific for nesdis
25 February 2015
JPSS and GOES-R SST

25. DAY – SST from original BTs in M15 and M16
Striping affects quality of SST imagery and Ocean Dynamics Analyses
25 February 2015
JPSS and GOES-R SST

26. DAY – SST from destriped BTs in M15 and M16
Destriping is applied to brightness temperatures and improves SST
25 February 2015
JPSS and GOES-R SST

27. VIIRS vs. AVHRR and MODIS
Specific for nesdis
25 February 2015
JPSS and GOES-R SST

28. AVHRR, MODIS and VIIRS Characteristics
AVHRR FRAC
MODIS
VIIRS
File compression No
Yes
Swath width, km
2,900
2,330
3,000
Pixel km 1
0.76
# of FOVs (Pixels) per scan line
2,048
1,354
3,200
# of Detectors 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
# of L1b files/24hr
28 ×Half-orbits
576 × 5min
~4,000 × 86sec (3 bands+1 geo)
25 February 2015
JPSS and GOES-R SST

29. NEdT in SST Bands (BB-based; Not aggregated pixels)
VIIRS1
MODIS – Aqua2
AVHRR3
(A)ATSR4
λ, µm
NEDT,
3.7
0.11
0.04
3.75
0.05
0.03
0.12
0.08
0.02
Not available on VIIRS
3.96
0.07
Used by U. Miami
for producing MO(Y)D28
4.0
4.02
Currently not used
8.55
8.52
10.8
11.03
10.5
12.0
12.02
11.5
Specs
On-Orbit
1Cao and VIIRS SDR Team,
2Xiong et al., IEEE/TGRS, 2009; 3Trishchenko et al., JGR, 2002 (NOAA9-16);
4Merchant and Embury, Personal communication, 2012
25 February 2015
JPSS and GOES-R SST