CGMS-43-NOAA-WP-16 Coordination Group for Meteorological Satellites - CGMS NOAA Report on Satellite Data Calibration and Validation – SNPP/JPSS Cal/Val Update Presented to CGMS-43 Working Group 2 session, agenda item 3 Authors: Zhou & Goldberg Slide: 1

CGMS-43-NOAA-WP-16 Coordination Group for Meteorological Satellites - CGMS Introduction The purpose of this paper is to provide an update of the JPSS/SNPP cal/val activities. Paper includes the overview of the 3 year performance of the SNPP instruments, and its well characterized long-term performance. Algorithm Theoretical Basis Documents, Validation Plans, and Validation results are all carefully documented and easily accessible. Slide: 2

Suomi NPP and JPSS-1 Instruments Instrument TypeMeasurement ATMS - Advanced Technology Microwave Sounder ATMS and CrIS together provide high vertical resolution temperature and water vapor information needed to maintain and improve forecast skill out to 5 to 7 days in advance for extreme weather events, including hurricanes and severe weather outbreaks CrIS - Cross-track Infrared Sounder VIIRS – Visible Infrared Imaging Radiometer Suite VIIRS provides many critical imagery products including snow/ice cover, clouds, fog, aerosols, fire, smoke plumes, vegetation health, phytoplankton abundance/chlorophyll OMPS - Ozone Mapping and Profiler Suite Ozone spectrometers for monitoring ozone hole and recovery of stratospheric ozone and for UV index forecasts CERES - Clouds and the Earth’s Radiant Energy System Scanning radiometer which supports studies of Earth Radiation Budget Slide: 3

CGMS-43-NOAA-WP-16 Coordination Group for Meteorological Satellites - CGMS Cal/Val Process Overview Four Phases of Cal/Val: 1.Pre-Launch – Algorithm verification, sensor testing, and validation preparation 2.Early Orbit Check-out (first days) – System Calibration & Characterization 3.Intensive Cal/Val (ICV) – xDR Validation 4.Long-Term Monitoring (LTM); through life of sensors LAUNCH ICVEOCLTM Build Team Resource ID & Development Sensor Characterization Post-Launch Plan Dev. Alg. Assessment & Verifications Cal/Val Tool Development Sensor Charar. &Calibration Quick-Look Analysis SDRs/EDRs SDR/EDR Alg. Tuning Estab. Sensor Stability SDR Validation Key EDR Validation Mission Integration Product Ops Viability Monitor Sensor Stability EDR Validation PRE-LAUNCH ICVEOC LTM Build Team Resource ID & Development Sensor Characterization Post-Launch Plan Dev. Alg. Assessment & Verifications Cal/Val Tool Development Sensor Charar. &Calibration Quick-Look Analysis SDRs/EDRs SDR/EDR Alg. Tuning Estab. Sensor Stability SDR Validation Key EDR Validation Mission Integration Product Ops Viability Monitor Sensor Stability EDR Validation PRE-LAUNCH Product Operationalization We Are Here for SNPP We Are Here for JPSS-1 Slide: 4

CGMS-43-NOAA-WP-16 Coordination Group for Meteorological Satellites - CGMS JPSS Product Maturity 5 DEFINITIONSARTIFACTS (DELIVERABLES) Beta o Product is minimally validated, and may still contain significant identified and unidentified errors. o Information/data from validation efforts can be used to make initial qualitative or very limited quantitative assessments regarding product fitness-for-purpose. o Documentation of product performance and identified product performance anomalies, including recommended remediation strategies, exists. Beta o Beta PowerPoint Presentation: o Performance Evaluation o Products Status and Error Matrix o Considerations/Know Risks o Summary of Findings and Recommendations o Readme Document for Data Users (goes to CLASS) Provisional o Product performance has been demonstrated through analysis of a large, but still limited (i.e., not necessarily globally or seasonally representative) number of independent measurements obtained from selected locations, time periods, or field campaign efforts. o Product analyses are sufficient for qualitative, and limited quantitative, determination of product fitness-for-purpose. o Documentation of product performance, testing involving product fixes, identified product performance anomalies, including recommended remediation strategies, exists. o Product is recommended for operational use (user decision) and in scientific publications. Provisional o Provisional PowerPoint Presentation o Performance Evaluation o Product status and accuracy assessment including error budget o Considerations/Know Risks (Closed DRs, and Assessment of any Open DRs) o Feedback from key users o Summary of Findings and Recommendations o Readme Document for Data Users (goes to CLASS) o ATBD o Users Manuals Validated o Product performance has been demonstrated over a large and wide range of representative conditions (i.e., global, seasonal). o Comprehensive documentation of product performance exists that includes all known product anomalies and their recommended remediation strategies for a full range of retrieval conditions and severity level. o Product analyses are sufficient for full qualitative and quantitative determination of product fitness-for-purpose. o Product is ready for operational use based on documented validation findings and user feedback. o Product validation, quality assurance, and algorithm stewardship continue through the lifetime of the instrument. Validated o Validated PowerPoint Presentation o Product Evaluation including Quality Flags analysis/validation o Product status and accuracy assessment including error budget o Identify know issues and assessment (Closed DRs, and Assessment of any Open DRs) o Feedback from key users o Summary of Findings and Recommendations o Readme Document for Data Users (goes to CLASS) o ATBD o Users Manuals

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CGMS-43-NOAA-WP-16 Coordination Group for Meteorological Satellites - CGMS JPSS Product Cal Val Maturity Process JPSS STAR (JSTAR) validates all Sensor and Environmental Data Records and conducts products validation maturity reviews. Review Panel is comprised of JPSS Program and Project Scientists, key NOAA users (NWS, NOS, NMFS, OAR), external users, Low-earth Orbiting Working Group (LORWG) advisors, product development managers (NDE and IDPS), the algorithm science manager (STAR). JPSS Program Scientist is the chair of the review panel. During the review process we assess how well the products are meeting specification and make an overall assessment of each algorithm. Slide: 7

CGMS-43-NOAA-WP-16 Coordination Group for Meteorological Satellites - CGMS Suomi NPP TDR/SDR Algorithm Maturity C CCCCCCCCC CC C C Sensor Beta ProvisionalValidated CrIS February 10, 2012February 6, 2013March 18, 2014 ATMS May 2, 2012February 12, 2013March 18, 2014 OMPS March 7, 2012 March 12, 2013April, 2015 VIIRSMay 2, 2012March 13, 2013April 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 applications Provisional 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 evaluation Validated 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 Slide: 8

CGMS-43-NOAA-WP-16 Coordination Group for Meteorological Satellites - CGMS JPSS SDR/EDR Products & Priorities JPSS SDR/EDR Algorithms Priority 2 (9) KPP (6) Priority 3 (33) Priority 4 (20) VIIRS SDR CrIS SDR ATMS TDR/SDR VIIRS Sea Ice Ozone Nadir Profile Sounding (AVMP, AVTP) VIIRS Sea Surface Temp VIIRS Imagery Ocean Color / Chlorophyll OMPS SDR Suspended Matter VIIRS Cloud (CCL,CEPS,CTH) VIIRS Cloud Mask VIIRS Snow (Map, Frac) Ice Surface Temp Ozone Total Column VIIRS Active Fires Vegetation Indices VIIRS Surface Type, QST LST (VIIRS/ATMS) VIIRS Cloud (CBH, CTP, CTT) Surface Albedo Aerosol Particle Size Par. Aerosol Optical Thickness Surface Reflectance Green Vegetation Frac. Land Surface Emissivity Polar Winds AMSR Sea Surface Temp ATMS Cloud Liquid Water CrIS Ozone Profile CrIS OLR AMSR Precipitation ATMS Rain-Rate AMSR Sea Ice ATMS Sea Ice AMSR Sea Surf Wind Speed ATMS Snow Cover/Depth AMSR Snow Cover/Depth ATMS Snow-Water Equ. AMSR Snow-Water Equ. AMSR Soil Moisture ATMS TPW AMSR TPW Trace Gas (CO, CO2, CH4) ATMS Moisture Profile AMSR Surface Type ATMS Temperature Profile Veg Health Index Suite NDE OCC AMSR TDR/SDR AMSR Cloud Liquid Water ATMS Imagery VIIRS Cloud (COT Day/Ngt) Color Code: IDPS Products (Blue) ESPC Products (Salmon) Slide: 9

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CGMS-43-NOAA-WP-16 Coordination Group for Meteorological Satellites - CGMS SNPP Maturity Status (Will Include all NOAA Unique Products for JPSS-1) Slide: 12

CGMS-43-NOAA-WP-16 Coordination Group for Meteorological Satellites - CGMS ATMS SDR Reached Validated Maturity (Mar 2014) Note: ATMS Nyquist sampling enables significant noise reduction ATMS on-orbit performance is significantly better than specification RSDR – AMSU fov constructed from ATMS oversampled fovs. Averaging ATMS fovs into AMSU fov reduces original noise by about factor of 3. Fuzhong Weng, NOAA/NESDIS/STAR ATMS SDR Lead Slide: 13

ATMS is outperforming AMSU in noise and long-term stability 14 SNPP ATMS channel 8 - upper tropospheric channel “equivalent” AMSU channel 7 Impact to NWP degrades over time because noise increases When ATMS is averaged to AMSU spatial resolution the noise is reduced by a factor of 3 Slide: 14

CGMS-43-NOAA-WP-16 Coordination Group for Meteorological Satellites - CGMS S-NPP: radiance spectra in 3 IR bands with the normal spectral resolutions of 0.625, 1.25 and 2.5 cm -1 for the SWIR, MWIR and SWIR bands, respectively JPSS-1: radiance spectra in 3 IR bands with the full spectral resolution (FSR) of cm -1 for all the 3 bands CrIS SDR Product 15 Δσ = cm -1 Δσ = 1.25 cm -1 Δσ = cm -1 Δσ = 2.5 cm -1 Δσ = cm -1 Red lines – full resolution; black lines – normal resolution Product component: CrIS radiance spectra Slide: 15

CGMS-43-NOAA-WP-16 Coordination Group for Meteorological Satellites - CGMS SDR reached Beta, Provisional and Validated maturity levels on 4/19/2012, 1/31/2013 and 11/14/2013, respectively All RDR and SDR requirements are met with significant margins More than 99.9% of the SDR data have a quality status Good S-NPP CrIS SDR Validation Band BB mW/m 2 /sr/cm -1 Radiometric BB (%) Frequency Uncertainty (ppm) Geolocation Uncertainty (km) * LW0.098 (0.14)0.12 (0.45)3 (10)1.2 (1.5) MW (0.06)0.15(0.58)3 (10)1.2 (1.5) SW0.003 (0.007)0.2 (0.77) 3 (10)1.2 (1.5) Validated CrIS SDR Uncertainties vs. (Requirements) Slide: 16

CGMS-43-NOAA-WP-16 Coordination Group for Meteorological Satellites - CGMS S-NPP CrIS Noise Performance NEdN computed from Internal Calibration Target (ICT), Deep Space (DS) & Earth Scene (ES) Specification ICT NEdN time series 2 Feb Sep 2014 Noise well below specification Stable instrument performance | Page 17

CGMS-43-NOAA-WP-16 Coordination Group for Meteorological Satellites - CGMS VIIRS: Next Gen Operational Polar Orbiting Imaging Radiometer 22 spectral bands – Visible to LWIR – Spatially registered Better spatial resolution – Reduced variation over scan – Higher resolution imaging bands High radiometric accuracy – NIST-traceable – Supported by on- board calibrators Slide: 18

CGMS-43-NOAA-WP-16 Coordination Group for Meteorological Satellites - CGMS VIIRS RTA mirror responsitivity degradation (1/F-factor) is leveling off For M7, initially > 2% per week; Currently <0.1% per week Slide: 19

CGMS-43-NOAA-WP-16 Coordination Group for Meteorological Satellites - CGMS BEFORE accounting for SRF difference AFTER accounting for SRF difference Cao VIIRS and MODIR RSB Inter-comparison at SNO-x ( over desert) Slide: 20

VIIRS-CrIS SDR Comparisons VIIRS SDR accuracy/stability plus RVS performance Global; 2.9 million matchups daily from SNPP platform CrIS radiances anticipating Mx8.1 In-band spectral radiance for M13, M15, M16 and I5 Long term high quality data record to assess stability M14M15M16 M13M12 I5 I4 CrIS convolved with VIIRS SRFVIIRS mean within CrIS FOVs CrIS spectrum covers VIIRS M13, M15, M16, and I5 but does not include OOB response in M15 and M16 Scene Temperature Courtesy of C. Moeller, U. of Wisc.

VIIRS-CrIS SDR Comparisons VIIRS OBC thermistor calibration adjustment VIIRS WUCD Events After early March 2012 OBC calibration adjustment, VIIRS (and CrIS) exhibit excellent radiometric stability Daily avg spectral radiance bias within +/ K all bands Bias of each band very stable over time (< 0.05 K trend ) Courtesy of C. Moeller, U. of Wisc.

VIIRS SDR Reached Validated Maturity (Apr 2014) 23 Requirement (absolute uncertainty for uniform scenes) Prelaunch and onboard calibration Validation: Relative to MODIS/CrIS/IASI/other thru Inter-comparisons Note VIIRS RSB 2% typical reflectance; 0.3% stability; 0.1% desirable for Ocean Color Applications 1.2% for M1-M7; 1.5% for M8&9 1.4% for M10 1.3% for I1&I2 1.6% for I3 2% (±1%) for matching bands Except bands with very low signal (ex. M11); sub-percent accuracy for OC is very challenging. Geolocation error: achieved better than quarter I-band pixel (1-s) VIIRS TEB M12/M13: M14: 0.6% 270K M15/M16: 0.4% I4: 5% I5: 2.5% Better than 0.13K for all M bands except M13 (0.14); 0.47K for I4; 0.23K for I5 0.1K based on statistical comparison with MODIS and CrIS ER-2/SHIS Aircraft underflight shows excellent agreement M K bias relative to CrIS at 200K (in spec.) M15 at 190K requirement is 2.1% radiance or 0.56K Geolocation uncertainty: better than quarter I-band pixel (1-s) VIIRS DNB  5%, 10%,30% L min (LGS,MGS,HGS) 3.5%, 7.8%, and 11% (LGS, MGS, HGS)  4%, 7.7%, 11.8% (LGS, MGS, HGS) Geolocation error is a ~10th of a pixel (1-s) on the ellipsoid earth but can exceed 1km (up to 24 km at the edges of scan) without terrain correction Changyong Cao, NOAA/NESDIS/STAR VIIRS SDR Lead

CGMS-43-NOAA-WP-16 Coordination Group for Meteorological Satellites - CGMS Instrument Performance of OMPS NP & NM Requirement Nadir Mapper (NP) Nadir Profiler ( NM) Specification/Prediction Value On-Orbit Performance Specification/Prediction Value On-Orbit Performance Non-linearity< 2% full well< 0.46%< 2% full well< 0.46% Non-linearity Knowledge< 0.5%~0.1%< 0.5%~0.1% On-orbit Wavelength Calibration < 0.01 nm< 0.01 nm # < 0.01 nm0.01 nm # Stray Light NM Out-of-Band + Out-of- Field Response ≤ 2%average ~± 1% * ≤ 2average ~± Intra-Orbit Wavelength Stability <0.02 nm< 0.01 nm<0.02 nm< 0.01 nm $ SNRChannel Dependent As good as SBUV/2 at Alg. Channels & >1000> 1000 from SV and EV Inter-Orbital Thermal Wavelength Shift <0.02 nm 0.03-nm amplitude annual cycle ^ <0.02 nm<0.01 nm ^CCD Read Noise<60 –e RMS< 25 –e RMS<60 –e RMS< 25 –e RMS Detector Gain>43~45>46~42 Absolute Irradiance Calibration Accuracy < 7%1~10%, average: ~7%< 7%5% Absolute Radiance Calibration Accuracy < 8%< 5%< 8%< 5% # After new analysis of Day 1 Solar * After measurement-based correction using prelaunch characterization ^ Regular annual cycle affects accuracy and stability & Information concentration possible by using near-by channels. # After new analysis for Day 1 wavelength After ground-based correction for TOz algorithm channels. $ After intra-orbit adjustments. Slide: 24

CGMS-43-NOAA-WP-16 Coordination Group for Meteorological Satellites - CGMS Summary and Conclusions The SNPP Instruments are performing well within specification. Data are easily accessible via NOAA operations, direct readout, and CLASS. The scientific maturity of these products are well documented and are easily accessible from the STAR JPSS website and CLASS A CGMS-wide endorsement is recommended for a standard practice for the provision of artifacts needed to understand the science, the uncertainties and the maturity (independent validation and use) for operational and research products Slide: 25