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NOAA-18 Instrument Cal/Val Studies and DMSP F-16 SSMIS Assessments Fuzhong Weng and Mitch Goldberg Satellite Meteorology and Climatology Division NOAA/NESDIS/Office of Research and Applications Monthly Satellite Briefing (Polar) September 9, 2005
Activities of the ORA NOAA-18 Cal/Val Team • Monitor and quantify instrument noise though analyzing calibration target counts and channel space view measurements • Assess instrument geolocation biases and co-registration and provide recommended solutions for satellite roll and pitch adjustments • Characterize other systematic biases in radiance through rigorous forward modeling and inter and intra-satellite calibrations • Provide initial demonstration and assessments of NOAA-18 data for improving numerical weather prediction • Validate product algorithms (e.g. ATOVS and MSPPS, TOAST, UV index, NDVI, SST, AOD) for transition into operation • Communicate with NOAA-18 OV team, instrument vendors and users with timeliness diagnostics of instrument performances and provide root cause analyses
NOAA-18 Instrument Assessments • Advanced Very High Resolution Radiometer (AVHRR/3) • High Resolution Infrared Sounder (HIRS/4) • Advanced Microwave Sounding Unit-A (AMSU-A) • Microwave Humidity Sounder (MHS) • Solar Backscattered Ultraviolet Radiometer (SBUV/2)
G G G Y Y Y R R R ORA NOAA-18 Instrument Cal/Val Status Report Support to NOAA’s Critical Satellite Program Noise, Bias and Anomaly Navigation and Co-registration Navigation errors are more than one scan lines and/or fov and their causes have not been identified All channels do not meet the noise specification, or large unknown biases and anomaly Some channels do not meet the noise specification, no major anomaly and biases Small navigation errors which can be fixed through recommended roll and pitch adjustments All channels meet the noise specification No navigation errors NWP Readiness and Product Demo Analysis and Recommended Solutions Measurements are assessed and not ready for product and NWP applications No analyses and recommended solutions for out-of spec instrument parameters R Analysis for out-of spec parameters but solutions have not been recommended Y Some channels are assessed and may be useful for product and NWP applications Analysis and recommended solutions are proposed for out-of spec instrument parameters G Measurements are fully tested and ready for product and NWP applications
G G Y R ORA NOAA-18 HIRS/4 Cal/Val Findings Support to NOAA’s Critical Satellite Program Noise, Bias and Anomaly Navigation and Co-registration • More HIRS/4 LW channels start meeting noise spec. • Channel 1 can not be calibrated because the spaceview is out of range most of the time. • NEDN relatively stable • None NWP Readiness and Product Demo Analysis and Recommended Solutions • Tests have been done: • Space/blackbody dwell tests (better noise characterization), • Filterwheel in high power mode (filterwheel related), • AMSU parked at warm target (interference) • ….. • Coefficients in radiative transfer model and data assimilation system are updated • NCEP starts experiments of uses of HIRS channels in NWP and has made software changes to QC individual HIRS channels.
G G G G ORA NOAA-18 AMSU-A Cal/Val Findings Support to NOAA’s Critical Satellite Program Noise, Bias and Anomaly Navigation and Co-registration • AMSU-A noise is evaluated and shows all channels meet the specification. • Overall AMSU calibration algorithms are healthy with reasonable gains, and variability in cold and warm calibration targets • AMSU-A1 module displays a slightly larger cross-track asymmetry • None • AMSU-A1 is correctly navigated Analysis and Recommended Solutions NWP Readiness and Product Demo • Coefficients in radiative transfer model and data assimilation system are updated • Large positive impacts of AMSU on weather prediction reported from the Metoffice. EMC is assessing the impacts • AMSU microwave surface and precipitation products are demonstrated
G G G G ORA NOAA-18 MHS Cal/Val Findings Support to NOAA’s Critical Satellite Program Noise, Bias and Anomaly Navigation and Co-registration • Display 1 MHS scanline error along track associated with a time delay of 8/3 seconds • MHS noises are quantified and show all channels meet the specification and are better than AMSU-B NWP Readiness and Product Demo Analysis and Recommended Solutions • Coefficients in radiative transfer model and data assimilation system are updated • Impacts of MHS on weather prediction are being assessed • MHS microwave surface and precipitation products are demonstrated • Lockheed Martin find an undocumented buffering of 8/3 seconds in MHS Interface Unit • Recommend OSDPD to fix this time delay
ORA NOAA-18 AVHRR/3 Cal/Val Findings Support to NOAA’s Critical Satellite Program G G G Y Noise, Bias and Anomaly Navigation and Co-registration • The blackbody temperature changes are monitored and shows in a small range of variability (only 2K) • Thermal channel (3-5) calibration is healthy • Wu’s Vis/IR calibration algorithms are working well • AVHRR/3 has possible 2-3 pixels navigation errors along track NWP Readiness and Product Demo Analysis and Recommended Solutions • AVHRR/3 produces a good quality of NDVI • AVHRR/3 produces SST and aerosol optical depth with smaller biases • Recommend to OV team to have a possible pitch correction
ORA NOAA-18 SBUV/2 Cal/Val Findings Support to NOAA’s Critical Satellite Program G G G G Noise, Bias and Anomaly Navigation and Co-registration • Solar irradiances are lower by 2-4% at channel 9-12 (312-339 nm), 6-10% at channel 1-8 (251-305nm) • Non-linearity error results in counts in Range 2 (counts > 45000) are processed in Range 3. -0.9% error in UV albedo, 1-1.5% error in ozone profile • Wavelength shifts by 0.9 grating position NWP Readiness and Product Demo Analysis and Recommended Solutions • Solar irradiances for ozone processing reduced by 3-8% • Range 2 correction revised for high count levels • Pre-launched wavelength calibration is adjusted by 0.9 grating position • Pitch error removal is planned with a s/c altitude control loop s/w fix • Products display small periodic biases
Comparison of equatorial zonal mean Ozone profiles for SBUV/2 Instruments Umkehr layer 9:43-48km 8:38-43km 7:33-38km 6:29-34 km 5:24-29km ………. NOAA-18 Blue NOAA-17 Green NOAA-16 Red 18-17 Blue 18-16 Green 17-16 Red TOMS Ozone Hole SBUV Ozone Hole
NOAA-18 Cal/Val Summary • ORA has completed the required calibration and characterization for five major NOAA-18 instruments • Most instruments are assessed under ORA cal/val project and their noise meets specification with the current exception of HIRS • Navigation and co-registration errors for all instruments are examined and quantified • AMSU instrument cross-track biases are quantified • The NOAA-18 MHS NET for each channel was calculated and is better than AMSU-B by a factor of ~2 • AMSU-A/MHS hydrological parameters (rainfall, total precip. water) appear to be better quality • ORA has delivered all required data assimilation software to NCEP for assimilating all NOAA-18 measurements • The Metoffice has demonstrated large positive impacts from assimilation of NOAA-18 AMSU/MHS • ORA cal/val website is developed for instrument trending analysis and other cal/val information • ORA is developing an integrated cal/val system for current and future instruments
NOAA-18 Web-Based Trending Analysis System • Monitoring calibration coefficients, instrument noise, calibration counts, and component temperatures • Very useful for monitoring instrument performance, trouble shooting, and instrument diagnosis Channel 12 slope Ch2 noise: SV > BB view Filterwheel housing temperature URL: http://www.orbit.nesdis.noaa.gov/smcd/spb/multisensor/hirs/nedn
Integrated Cal/Val System • Develop an Integrated Cal/Val System Framework to enhance ORA’s capability and efficiency to provide outstanding calibration and validation to METOP, NP, NPOESS, and GOES-R • Outcome >>> Provide timely and accurate assessments of NOAA instrument’s on-orbit performances and the impacts of noise and loss of channels on operational products and data assimilation
Assessment of Special Sensor Microwave Imager and Sounder (SSMIS) Data for NOAA Operational Applications
0600 • As of August 2005 1200 0000 N N18 DMSP LTANs F13 1818 F14 2012 F15 2130 F16 2000 NOAA LTANs N15 1903 N16 1430 N17 2204 N18 1359 N16 N17 F15 F14 F16 F13 N15 1800 DMSP and NOAA Constellation
Project Goals • Characterize and correct the anomalies due to SSMIS antenna emission • Characterize and correct SSMIS calibration target anomalies from solar heating and other stray light contamination • Evaluate the SSMIS imager products using SSM/I algorithms • Develop NOAA-unique SSMIS products (e.g. cloud ice water, surface temperature, emissivity) • Assess SSMIS products produced by DMSP and develop improved algorithms if needed • Improve forward RT models including Zeeman splitting for SSMIS radiance assimilation • Improve land emissivity model for SSMIS applications • Assess the impacts of SSMIS on NWPs
Instrument Characteristics • The Defense Meteorological Satellite Program (DMSP) successfully launched the first of five Special Sensor Microwave Imager/Sounder (SSMIS) on 18 October 2003. • SSMIS is a joint United States Air Force/Navy multi-channel passive microwave sensor • Combines and extends the current imaging and sounding capabilities of three separate DMSP microwave sensors, SSM/T, SSM/T-2 and SSM/I, with surface imaging, temperature and humidity sounding channels combined. • The SSMIS measures partially polarized radiances in 24 channels covering a wide range of frequencies (19 – 183 GHz) • conical scan geometry at an earth incidence angle of 53 degrees • maintains uniform spatial resolution, polarization purity and common fields of view for all channels across the entire swath of 1700 km.
SSMIS Anomaly Distribution Global Bias (3-20-2005) Global Bias (8-15-2005) Shown are the differences between observed and simulated SSMIS measurements at 54.4 GHz. The SSMIS is the first conical microwave sounding instrument, precursor of NPOESS CMIS. This is the data distributed from DMSP to NWP centers. The biases are caused by 1) antenna emission, 2) direct solar heating to warm load and 3) stray light contamination to its calibration targets
SSMIS Instrument Anomalies • Reflector Emission • SiOx VDA (coated vapor-deposited aluminum) • SiOx and Al VDA Mixture • Graphite Epoxy • Warm Load Intruded by Stray Lights • Reflection Off of the Canister Top into Warm Load • Direct Illumination of the Warm Load Tines From Steve Swadley et al SSMIS Cal/Val
Inputs: TAObs(i), TArm(i), Cw(i), CC(i), TW(i) & Time(i) (i=1,2,.., nscans) for 3-4 orbits Antenna emission correction algorithms using antenna arm temperature and its trend Cw(i), CC(i), TW(i) & Time(i) ■ Calculate the first three Fourier harmonics of warm load counts: CW1, CW2, CW3 ■ Use the slope of Cw and the Fourier harmonics to detect anomalies ■ Calculate CW = CW – CW1 or CW2 or CW3 Algorithm for detecting and quantifying warm load count anomalies TSceneObs(i), Cw(i), Tscan(i), Cw(i), Cc(i), Tw(i) Earth scene algorithm from biases of warm load counts, PRT and space view counts Outputs: Corrected TDR SSMIS Anomaly Correction Algorithms
SSMIS Anomaly Corrected Global Bias (8-15-2005) Global Bias (3-20-2005)
DMSP SSMIS Cal/Val Summary • NESDIS and several NWP centers can now access SSMIS data since March, 2005. We would like to thank JCSDA director for his coordination on this effort • SSMIS antenna (main reflector) emits radiation with an increasing emission after satellite is out of the earth eclipse • Anomaly locations (5 contamination zones in warm load) and magnitudes (20-60 count sudden jump) are quantified through NESDIS developed software • Global corrections of these anomalies are possible with antenna temperature and emissivity information, FFT analysis of warm load counts • SSMIS imager products are demonstrated with NESDIS operational SSM/I algorithms