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JPSS and GOES-R SST Sasha Ignatov

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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, https://cs.star.nesdis.noaa.gov/NCC/VIIRS 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


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