Calibration of DMSP SSM/IS for Weather and Climate Applications Fuzhong Weng Sensor Physics Branch Satellite Meteorology and Climatology Division NOAA/NESDIS/ORA and Banghua Yan, Ninghai Sun and Mark Liu Joint Center for Satellite Data Assimilation 2006 JCSDA Workshop, Greenbelt, MD May 31 – June 1, 2006

SSMIS Instrument Characteristics The Defense Meteorological Satellite Program (DMSP) successfully launched the first of five Special Sensor Microwave Imager/Sounder (SSMIS) on 18 October 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 vs. AMSU-A Weighting Functions Oxygen Band Channels SSMIS13 Channels Sfc – 80 km AMSU-A 13 Channels Sfc - 40 km SSMIS vs. AMSU Sounding

F DMSP LTANs F F F F NOAA LTANs N N N N N As of August 2005 N15 F14 F15 N17 N18 F16 N16 DMSP and NOAA Constellation

The First SSM/I Monthly Products Generated from NOAA/NESDIS

SSMIS Antenna System and Calibration Main-reflector conically scans the earth scene Sub-reflector views cold space to provide one of two-point calibration measurements Warm loads are directly viewed by feedhorn to provide other measurements in two-point calibration system The SSMIS main reflector emits radiation from its coating material –SiOx VDA (coated vapor-deposited aluminum) –SiOx and Al VDA Mixture –Graphite Epoxy Warm load calibration is contaminated by solar and stray Lights –Reflection Off of the Canister Top into Warm Load –Direct Illumination of the Warm Load Tines Lunar contamination on space view

Microwave Instrument Calibration Components Energy sources entering feed for a reflector configuration 1.Earth scene Component, 2.Reflector emission 3.Sensor emission viewed through reflector, 4.Sensor reflection viewed through reflector, 5.Spacecraft emission viewed through reflector, 6.Spacecraft reflection viewed through reflector, 7.Spillover directly from space, 8.Spillover emission from sensor, 9.Spillover reflected off sensor from spacecraft, 10.Spillover reflected off sensor from space, 11.Spillover emission from spacecraft

SSMIS Antenna/Calibration Subsystem

NESDIS/STAR Integrated Cal/Val System Current Capabilities: Noise quantification (NEDT), Linear and non-linear calibration algorithms, Correction of sudden jumps and contamination associated with warm load and space view calibration counts, Monitoring instrument noise, gain, telemetry and PRT uniformity, Mitigation of radio frequency interference, Global bias analysis from forward calculations using NWP models, Time series of SNO/SCO matched data from a pair of operational satellites, Time series of updated calibration coefficients with digital access, Reference areas/site for vicarious calibration, Monitoring of key MW products sensitive to calibration Future Capabilities: Validation of EDRs

SSMIS Anomaly Distribution Shown is the difference between simulated and observed SSMIS 54.4 GHz. The SSMIS is the first conical microwave sounding instrument, precursor of NPOESS CMIS. The calibration of this instrument remains unresolved after 2 years of the lunch of DMSP F16. The outstanding anomalies have been identified from three processes: 1) antenna emission after satellite out of the earth eclipse which contaminates the measurements in ascending node and small part in descending node, 2) solar heating to the warm calibration target and 3) solar reflection from canister tip, both of which affect most of parts of descending node.

SSMIS Anomalies and Their Mitigation Algorithms 1.Antenna is not a pure reflector. It emits radiation with a very small emissivity and its own temperature. This additional radiation is called as an antenna emission anomaly 2.Warm load is heated by intruded solar radiation. The energy received through feedhorn does not match with the warm load physical temperature measured by the platinum résistance thermisters (PRT). This is referred as a warm load anomaly 3.The radiance from space view by the sub- reflector does not correspond to the sum of cosmic background temperature (2.73K) and pre-calculated correction values for each channel due to antenna side-lobe effort. 1.Use the emissivity from NRL antenna model and the temperature measured from the thermister mounted on antenna arm as approximation 2.Analyze the time series of warm load counts together with PRT and define the anomaly locations in terms of the FFT harmonics 3.Analyze the time series of cold space view count and define the anomaly locations in terms of the FFT harmonics and cosmic temperature plus antenna correction Anomaly CausesAnomaly Mitigation Process

SSMIS Calibration Algorithms 1.Use the emissivity from NRL antenna model and the temperature measured from the thermister mounted on antenna arm as an approximation 2.Analyze the time series of warm load counts together with PRT and define the anomaly locations in terms of the FFT harmonics 3.Analyze the time series of cold space view count and define the anomaly locations in terms of the FFT harmonics and cosmic temperature plus antenna correction where T A is the antenna temperature corresponding to the earth scene’s radiance, and  R and T R is the reflector emissivity and Temperature, respectively

Theoretical SSMIS Reflector Surface Parameters (NRL Multilayer Antenna Model) Emissivity (V-pol/20deg) [ ∈ R ] Freq. (GHz)AlGrEpSiOx SiOx/Al

FFT Analyses of Warm Counts (54.4 GHz) Note: (1) C W F = FFT -1 ( FFT(C W ) * Filter(f L ) ) ), where f L is a cutoff frequency of the low pass filter, where T  102 minutes. (2) f 0 is sampling frequency = 1.0/T.

SSMIS Antenna Temperature Bias February 3, 2006 Before anomaly correctionAfter anomaly correction Temperature biases from TDR and SDR space are related through the slope coeff. for spill-over correction, Tb = a*Ta + b

SSMIS 54 GHz (TDR) Obs-CalibObs-Calib (Em) Obs Calib

SSMIS 19V GHz (TDR) Obs Calib Obs-Calib (Em)

SSMIS 150 GHz (TDR) Obs Calib Obs-Calib (Em) More channel examples can be found /nsun/mirs.temp/product/tb.html

SSMIS 54 GHz (TDR) Obs-CalibObs-Calib (Em) Obs Calib

SSMIS 19V GHz (TDR) Obs Calib Obs-Calib (Em)

SSMIS 150 GHz (TDR) Obs Calib Obs-Calib (Em) More channel examples can be found /nsun/mirs.temp/product/tb.html

AMSU vs. SSMIS Matching through Simultaneous Conical Overpass SNO – every pair of POES satellites with different altitudes make orbital intersections within a few seconds regularly in the polar regions (predictable w/ SGP4) Precise coincidental pixel-by-pixel match-up data from radiometer pairs provide reliable long-term monitoring of instrument performance The SNO method (Cao et al., 2005) is used for on-orbit long-term monitoring of imagers and sounders (AVHRR, HIRS, AMSU) and for retrospective intersatellite calibration from 1980 to 2003 to support climate studies The method has been expanded for SSM/I with Simultaneous Conical Overpasses (SCO)

SSMIS Bias Trending

SSMIS Assimilation Trials at ECMWF Graeme Kelly Pre-processed data: 40 % flagged limited coverage tuning ongoing T sounding chs only 0.5K obs errors NO SAT NO SAT + SSMIS NO SAT + N15 AMSU SH AC 500hPa height NH AC 500hPa height

SSMIS Cloudy Radiance Assimilation The warm Core of Katrina is captured very well from SSMIS 54 GHz (Liu and Weng, GRL, 2006) SSMIS sounding channel radiances under all weather conditions are used through GSI in GDAS. Shown is the temp difference between test and control at a sigma level of 0.5

Hurricane Katrina Analysis from AMSU/AMSR-E Above two figures compare GDAS analysis temperature field near 250 hPa with HVAR analysis. The temperature field from analysis shows hurricane warm core is about 2 degree warmer than GDAS analysis. Uses of cloudy radiances under storm conditions dramatically improve warm core structure. At 0600 UTC August 25, 2005, Katrina was at tropical storm intensity, with the minimum central pressure of 1000 hPa.

SSMIS vs. SSM/I Products SSMIS-F16 SSM/I-F15 Cloud Liquid WaterTotal Precipitable Water

SSMIS vs. SSM/I Products Land Surface TemperatureLand Surface Emissivity SSMIS-F16 SSM/I-F15

Microwave Emissivity Model Upgrade in CRTM-V1 ( )

IR Emissivity Estimated from MW ( Dr. Peimeng Dong, CMA visiting scientist)

Summary DMSP SSMIS may soon become another major data source for NWP data assimilation. Currently, resolving its calibration uncertainty from antenna emission and contamination by solar/stray lights is of a highest priority The NESDIS/STAR beta-version calibration algorithm has significantly eliminated most of SSMI radiance anomalies (e.g. antenna emission, warm load anomaly) Impacts of SSMIS radiances on NCEP analysis field are significantly positive. CRTM allows for uses of most of SSMIS radiance data SSMIS EDRS (cloud liquid and water vapor) is of a quality similar to SSM/I’s products The methodology of using MW imagers to derive IR emissivity is promising and allows IR emissivity estimated under all weather conditions