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Global Space-Based Inter-Calibration System
(GSICS)
NOAA GPRC Report for EP-15
Presented by Mitch Goldberg NOAA GSICS EP Member
NOAA GSICS Team
Fuzhong Weng, Larry Flynn, Manik Bali, Chengzhi Zou, Likun Wang, Xiaolei Zou, Fangfang Yu, Changyong Cao, Fred Wu ,Jian Zeng
22
� Detail validation and assessment of SUOMI NPP for GSICS reference
instruments
� Use of SUOMI NPP instruments in current GSICS monitoring tools
Current Focus
33
Review Outcomes: SNPP SDR Products Review Meeting was held on Dec. 18-20, 2013. NESDIS Senior Management Leads: Ms. Mary Kicza and Dr. Al Powell attended the review. The Cal/Val team scientists presented the results on their specific calval tasks and NWP and other users NWS/NOS offered their independent assessments of data product quality based on their intensive cal/val analyses. The review panel recommended that the CrIS, ATMS and VIIRS SDR products be ready to be declared validated scientifically. And three remaining issues were recommended to resolve before OMPS EV SDR goes to the validated stage: cross-track effects in NM need to be addressed; Stray-light improvements still needed in NP SDR; Artificial separation between EV SDR and Cal SDR should be eliminated
Significance: Suomi NPP CrIS and ATMS SDR products are continuing NOAA afternoon orbits sounding data for NWS NWP radiance assimilation. It is shown from CEP global forecast system (GFS) and ECMWF global models that uses of CrIS and ATMS data have similar or slightly better impacts on the global medium-range forecasts
SNPP SDR Products Review for Declaring the Validated Maturity
Attendees for SUOMI NPP SDR Product Review Meeting in NOAA Center for Weather and Climate Prediction Auditorium
3
44
JPSS Science POCs and Leads at NOAA/NASA
ProgramMitch Goldberg – NOAA Program
ScientistJim Gleason – NASA Project Scientist
Flight ProjectJim Butler – Project Scientist
ATMSEd Kim – Instrument Scientist
CrISDave Johnson – Instrument Scientist
OMPSGlen Jaross – Instrument Scientist
VIIRSKurt Thome – Instrument Scientist
CERESKory Priestley – Instrument Scientist
Ground Segment -SDR
Fuzhong Weng – STAR SDR LeadBruce Guenther – DPA SDR Lead
Ground Segment - EDRIvan Csiszar , Ingrid Guch, Paul Digacomo–
STAR EDR LeadRay Godin– DPA EDR Lead
ATMS SDRFuzhong Weng – ATMS SDR Lead
CrIS SDRYong Han – CrIS SDR Lead
OMPS SDRXianqian Wu –OMPS SDR Lead
VIIRS SDRChangyong Cao – VIIRS SDR Lead
EDR AlgorithmsJeff Key – Cryosphere EDRsLarry Flynn – Ozone EDRsIvan Csiszar – Land EDRs
Alexander Ignatov – SST EDRsDon Hilger – Imagery EDRs
Tony Reale (acting) – Sounding EDRs
Andy Heidinger – Cloud EDRsIstvan Laszlo – Radiation Budget
EDRsMenghua Wang – Ocean Color EDRShobha Kondragunta – Aerosol EDRs
4
55 5
Suomi NPP TDR/SDR Algorithm Schedule
C
CCCCCCCCCCCCC
Sensor Beta Provisional ValidatedCrIS February 10, 2012 February 6, 2013 March 18, 2014
ATMS May 2, 2012 February 12, 2013 March 18, 2014
OMPS March 7, 2012 March 12, 2013 June, 2014VIIRS May 2, 2012 March 13, 2013 April 16, 2014
Beta• Early release product.• Initial calibration applied• Minimally validated and may still contain significant errors (rapid changes can be expected. Version changes will not be identified as errors are corrected as on-orbit baseline is not established)• Available to allow users to gain familiarity with data formats and parameters• Product is not appropriate as the basis for quantitative scientific publications studies and applicationsProvisional• Product quality may not be optimal• Incremental product improvements are still occurring as calibration parameters are adjusted with sensor on-orbit characterization (versions will be tracked)• General research community is encouraged to participate in the QA and validation of the product, but need to be aware that product validation and QA are ongoing• Users are urged to consult the SDR product status document prior to use of the data in publications• Ready for operational evaluationValidated• On-orbit sensor performance characterized and calibration parameters adjusted accordingly• Ready for use in applications and scientific publications• There may be later improved versions• There will be strong versioning with documentation
66
JGR Special Issue on Suomi NPP CalVal
34 papers have been accepted in AGU Journal Geophysical Research Special Issue on Suomi NPP satellite calibration, validation and applications.
Guest Editor: Fuzhong Weng
6
77
Suomi NPP Calibration/Validation Schedule
• Four Phases of Cal/Val:1. Pre-Launch; all time prior to launch – Algorithm verification, sensor testing, and validation preparation2. Early Orbit Check-out (first 30-90 days) – System Calibration & Characterization3. Intensive Cal/Val (ICV); extending to approximately 24 months post-launch – xDR Validation4. Long-Term Monitoring (LTM); through life of sensors after ICV
• For each phase:– Exit Criteria established– Activities summarized– Products mature through phases independently
LA
UN
CH
ICVEOC LTM
NPP Launch
Build Team
Resource ID& Development
Sensor Characterization
Post-LaunchPlan Dev.
Alg. Assessment& Verifications
Cal/Val ToolDevelopment
Sens or Charar.
&Calibration
Quick-Look Analysis
SDRs/EDRs
SDR/EDR Alg.Tuning
Estab. SensorStability
SDR Validation
Key EDR Validation
Mission Integration
Product Ops Viability
Monitor Sensor Stability
EDR Validation
PRE-LAUNCH
LA
UN
CH
ICVEOC LTM
NPP Launch
Build Team
Resource ID& Development
Sensor Characterization
Post-LaunchPlan Dev.
Alg. Assessment& Verifications
Cal/Val ToolDevelopment
Sens or Charar.
&Calibration
Quick-Look Analysis
SDRs/EDRs
SDR/EDR Alg.Tuning
Estab. SensorStability
SDR Validation
Key EDR Validation
Mission Integration
Product Ops Viability
Monitor Sensor Stability
EDR Validation
PRE-LAUNCH
10-28-2011 12-18-2013 Validated Review10-23-2012-Provisional Review
Joint Polar Satellite System
7
88
Time-Series of GEO- LEO ( GOES-15 - AIRS/CRIS/IASI Difference)
Figure: Time-series of GEO-LEO inter-calibration
between GOES and AIRS/CrIS/IASI trace each
other very well, indicating the long-term
radiometrical calibration stability of the three
hyperspectral radiometers
o GOES-15 Imager displays slight
seasonal variation at Ch4 and Ch6
o The mean Tb difference between
AIRS/CrIS/IASI is very small <0.1-0.2K
Key Results/Accomplishments
Fangfang Yu
Achieving 0.1 K absolute calibration is important for verifying real climate trends
• Through detail validation we have demonstrated that both CrIS and IASI have achieved a high level climate monitoring performance capability.
• Climate monitoring performance allows you to minimize the time to detect a real climate trend from natural variability.
• In the figure to the right, we see that a trend of 0.1 K per decade would take 20 years to confirm with perfect observations.
• While a calibration accuracy of 0.1 would take about 25-27 years
• While a calibration accuracy of 0.3 would take about 50 years.
• This chart would imply that CrIS and IASI are not good for monitoring trends. The accuracy noted in the chart for IASI, AIRS, CRIS are from the specification
• Good news - CrIS and IASI are approaching 0.1 K - beating the specification by significant margins 9
Wielicki, Bruce A., and Coauthors, 2013: Achieving Climate Change Absolute Accuracy in Orbit. Bull. Amer. Meteor. Soc., 94, 1519–1539.doi: http://dx.doi.org/10.1175/BAMS-D-12-00149.1
CriS Specifications (note the larger numbers)
10
(I do not have the actual IASI spec)
N A T I O N A L O C E A N I C A N D A T M O S P H E R I C A D M I N I S T R A T I O N
How do we know how accurate CriS and IASI are?
• We compare CrIS with airborne interferometer on
NASA’s ER-2. The airborne instrument are tied to SI
reference (NIST)
• We underfly the S-NPP satellite and compare
• We also compare IASI and CrIS and simultaneous
nadir overpass locations
11
12
JPSS PGRR Deep-Dive Validation First S-NPP ER-2 Aircraft Campaign to provide
validation for CrIS, ATMS and VIIRS
NIST traceable absolute calibration for CrIS
ER-2 with aircraft validation sensors under flies Suomi NPP sensors. In the case of CrIS,the validation sensor in this example is from the Scanning High-resolution InterferometerSounder (S-HIS) which has been tied to a NIST traceable calibration source.Quick look comparisons show excellent agreement. Significance – NIST traceable validation is criticalfor uncertainty analysis needed to fully assess data quality of S-NPP and JPSS sensors.
May 10, 2013 – first look
10/23-24/2012 NPP SDR Provisional Product Review 13
Atmospheric absorption above the aircraft
Window channels
CrIS versus IASI/MetOp-A
14
South Pole (1112)North Pole (987)
Bias: CrIS-IASI
STDEV: CrIS-IASI
Bias: CrIS-IASI
STDEV: CrIS-IASI
CrIS versus IASI/MetOp-B
15
South Pole (809)North Pole (774)
Bias: CrIS-IASI
STDEV: CrIS-IASI
Bias: CrIS-IASI
STDEV: CrIS-IASI
Next Steps
• Aircraft campaigns shows absolute accuracy between 0.1 – 0.2C
• SNOs over the arctic shows IASI and CrIS differences generally within 0.1 C
• However larger differences for Antarctic SNOs
– Water vapor band still within +- 0.1
– CO2 Longwave ~ 0.2 (MeTOP-B)
– Shortwave Infrared much larger (IASI high noise is this region).
• Next step - new campaigns over the Antarctic (or over cold extreme areas - Greenland) to
reconcile these difference
• CrIS and IASI are not just weather sensors. Results indicate high accuracy and stability.
Can be used as anchor points for NWP!
16
1717
BEFORE accounting for SRF difference AFTER accounting for SRF difference
Changyong Cao
Key Results/AccomplishmentsVIIRS and MODIR RSB InterVIIRS and MODIR RSB Inter--comparison at SNOcomparison at SNO--x ( over desert) x ( over desert)
1818
ATMS Post-launch Characterization of Calibration Accuracy through O-B
Bia
s (K
)
On-orbit ATMS calibration accuracy is characterized using GPSRO and ECMWF data as input to RT model and is better than specification for most of sounding channels.
O -
B (
K)
18
1919
SNPP ATMS Has Stable Noise
19 19
2020 20
Biases in the Tropics (NOAA-15, MetOp-A, SNPP)
before after
ATMS channel 10
ATMS channel 11
ATMS channel 13
ATMS channel 14
NOAA-18 is subtracted. The pentad data set within ±30o latitudinal band.
2121
� Deep Convective Cloud (DCC) is selected as
common reference target for visible instrument
inter-calibration
� Confirmed the seasonal and annual variation of
DCC reflectance
� Used long-term MODIS data to determine the
DCC reference reflectance for the area
o Calibration coefficient difference between
median DCC and desert method is less than
1%
� Demonstrated that less variations with median
values in the time-series of DCC reflectance
o The bias between the median and mode
reflectance is less than 0.4%
Key Results/AccomplishmentsCharacterization of Deep Convective Cloud as Calibration reference
Fangfang Yu
222222
� Reflectance of the lunar surface is extremely stable
� USGS ROLO lunar irradiance model make high accurate relatively calibration possible
� GOES-15 rolled northward to trace the Moon to characterize the scan mirror angular
dependent reflectivity during its PLT period
� Results showed that the EW oversampling factor is not constant for the GOES-15 Imager
visible channel
� Early result showed about 1.6% reflectance variation.
� Yu, F., X. Wu, T. Stone, and G. Sindic-Rancic, 2013b. Angular Variation of GOES Imager
scan-mirror visible reflectivity, GSICS Quarterly Newsletter, Vol. 7 (3), 9-10.
Fangfang Yu
Key Results/Accomplishments
Determination of Scan Mirror Angular Reflectivity using the Moon
2323
� NOAA Inter-Calibrated MSU/AMSU FCDR
products went through GSICS Review for
GSICS Procedure for Product
Acceptance (GPPA) on 12/03/2013
� After review, the products were approved
by GSICS Executive Panel to go to
GSICS Pre-Operational Phase
� A Link to NOAA NCDC product website
was provided in the GSICS products
catalog
� IMICA calibrated MSU/AMSU FCDR
products open to GSICS users
Figure: Overlapping orbital observations between
NOAA-15 and NOAA-18 during 07/01/2008. Inter-satellite
biases by the IMICA inter-calibration for randomly selected
geo-locations (the dotted square box) exhibited near zero
inter-satellite biases (the larger box pointed by the arrow)
Cheng-Zhi Zou
Key Results/Accomplishments
NOAA Calibrated MSU/AMSU FCDR went through GSICS Review
2424
OMPS Nadir Mapper(NM) versus GOME-2 METOp-A (left) and METOp-B (right) at SNOx
o The inter-calibration between OMPS and GOME-2 confirmed that the signals for GOME-2 on METOp-A have
been degradated for both the earthshine and solar measurements by up to 50% after more than seven years in
orbit. Since METOp-B was launched in September 2012, the comparison shows much better agreement.
o Also, the inter-calibration demonstrates that the GOME-2 diffuser has degraded more at shorter wavelengths
than at longer wavelengths, which leads to the current 10-15% discrepancy in reflectance for shorter
wavelengths.
Key Results/Accomplishments
0.7
0.8
0.9
1
1.1
1.2
2013-01 2013-03 2013-04 2013-08 2013-09 2014-01 2014-02
OM
PS
NM
Re
fl./
ME
TO
p-B
Re
fl.
Month
315nm 325nm 335nm
345nm 355nm 365nm0.7
0.8
0.9
1
1.1
1.2
OM
PS
NM
Re
fl./
ME
TO
p-A
Re
fl.
Month
315nm 325nm 335nm
345nm 355nm 365nm
Jian Zeng & Fred Wu
2525
OMPS Nadir Profiler(NP) versus GOME-2 METOp-A (left) and METOp-B (right)
Despite the large FOV difference, the reflectance discrepancy between OMPS NP and METOp-B
band 1B is within ~10%. For METOp-B band 1A, the discrepancy is a bit larger.
Key Results/Accomplishments
0.3
0.5
0.7
0.9
1.1
1.3
1.5
1.7
2013-012013-03 2013-042013-08 2013-092014-01 2014-02OMPS NP Refl./METOp-B Refl.
Month
259nm 269nm 279nm
289nm 299nm 309nm
0.3
0.5
0.7
0.9
1.1
1.3
1.5
1.7
OMPS NP Refl./METOp-A Refl.
Month
259nm 269nm 289nm
299nm 309nm
Jian Zeng & Fred Wu
2626
THANK YOU