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F16 SSMIS CalibrationValidation Executive Summary

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Title: F16 SSMIS CalibrationValidation Executive Summary


1
F16 SSMIS Calibration/Validation Executive Summary
  • Presented to Col. Wagner, Ms. Smith
  • 4 May 2005

Cal/Val Team The Aerospace Corporation/NRL
2
Executive Summary Outline
  • Important historical perspective
  • Atmosphere/Ocean Overview
  • What the users will do with SSMIS data
  • EDR performance quick-look
  • SSMIS instrument basics
  • Role and importance of Calibration/Validation
    (Cal/Val)
  • Cal/Val approach
  • Team organization
  • Instrument and algorithm issues
  • The way ahead

Part 1
Part 2
3
Important Historical Perspective
  • SSMIS EDR requirements were generated in late
    1989
  • Users at that time required products such as
    vertical temperature and water vapor profiles,
    ocean surface wind speeds, the EDRs
  • The SSM/T-1 was flying, along with the SSM/I, and
    performance for these instruments were proven
  • The SSM/T-2 had yet to fly, so the government had
    no experience with how this water vapor profiler
    would perform, let alone the SSMIS with nearly
    identical frequencies
  • The SSM/T-2 Cal/Val concluded that there was
    insufficient accuracy in the balloon measurements
    to validate the products, hence Aerospace built
    our ground-based LIDAR which the team has used
    very successfully for SSMIS
  • Current users will soon require SDRs which are
    the calibrated and earth located SSMIS brightness
    temperatures, and are less interested in EDR
    products

4
Atmosphere/Ocean Overview
  • A quick look at the atmospheric temperature and
    water vapor structure
  • A quick look at the ocean parameters
  • A summary of who the users are, and how they will
    use SSMIS data

5
Atmospheric TemperatureClassical Regimes and
SSMIS Sampling
6
Atmospheric Water Vapor A Typical Sounding over
Boulder CO
7
Typical Ocean EDRs Derived from the SSMIS (SSM/I
Example Data)
8
How Do The Users Use SSMIS Data?
  • AFWA/FNMOC (and tactical world) use SSMIS data
    products (EDRs) to be merged with other data
    such as balloon measurements to generate a global
    specification of the atmosphere. This is the EDR
    user.
  • Numerical Weather Prediction users will require
    highly accurate SDRs (lets look at a simulation
    we did on hurricane Jeanne, last year)
  • The SSMIS Cal/Val team has faced many SDR
    challenges along the way, which will be discussed
    later in the briefing
  • Now, you want to know about how the EDRs perform?

9
EDR Performance Quick-look
  • Green means we meet the PIDS specification
  • Yellow means we currently do not meet
    specification, but with addition work, we will
    meet the specification
  • E.g. Team is working on backing out results from
    warm load sun glint and main reflector emissivity
    to improve performance
  • Red means we are not, and will not meet
    specification

10
EDR Performance Quick-look Imaging EDRs
(heritage SSM/I)
11
SSMIS EDR Performance Quick-look Soundings
(Heritage SSM/T-1 SSM/T-2)
Temperature
Water Vapor
Three types of truth data have Been used, each
with its own Strengths. The best measurement We
have are the LIDAR, but it Represents only a
single location Thus a very small sample size
12
SSMIS EDR Products Are Ready For Operational
Users
  • Release a large subset of the EDRs to the users
    (recommend SPD formally release SSMIS data via a
    letter to the users)
  • Clearly articulate the Cal/Val teams caveats,
    that is, those EDRs within a class that are
    yellow and show the path to make them green
  • Release the SDRs with a document that helps
    non-DOD users deal with the data

13
SSMIS Instrument Basics
  • Instrument characteristics
  • Instrument specifications
  • Lets get a feel for how this all works on the
    spacecraft, launching DGS

14
SSMIS Key Instrument Characteristics
  • 24 Channels (19-183 GHz)
  • Conical Scan Geometry
  • Mesospheric Sounding
  • Improved Sounding HCS
  • Swath Width 1700 km
  • Scan Rate 31.6 rpm
  • Calibration Accuracy
  • Better than 1K
  • Warm and Cold Targets each Scan

15
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16
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17
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18
Visualize SSMIS with DMSP Graphics System (DGS)
  • DGS was built to support Cal/Val
  • Invaluable analysis tool which uncovered and
    characterized the warm load anomaly
  • Here we go…

19
Role and Importance of Cal/Val
Calibration
Validation
  • Absolute Accuracy
  • Polarization Purity
  • Geo-location Accuracy
  • Instrument Stability
  • Doppler Correction
  • Antenna Pattern Correction
  • Ocean Wind Speed
  • Water Vapor
  • Cloud Water
  • Rain Rate
  • Sea Ice
  • Soil Moisture
  • Snow water
  • Land Temp
  • Lower-Air Profiles
  • Upper-Air Profiles

Users
Mission Success
  • Meet Specification
  • Operational production of synoptic maps and
    profiles of critical atmospheric, oceanographic,
    sea ice and land parameters
  • Quality Control
  • NWP
  • Real-time tactical
  • Non-tactical
  • JTWC
  • NHC
  • NIC
  • Others

Ensures
20
Importance of Cal/Val
First SSM/I F8 in 1987
21
Cal/Val Approach
22
Team Organization/Schedule
  • NRL SDR validation and ocean parameter EDR
    validation, upper-air sounder partner, designer
    of aircraft under-flight experiments, radiative
    transfer modeling
  • Aerospace processing and re-processing of data
    for the entire team via Omaha/El Segundo labs,
    SDR validation partner, LIDAR campaigns, balloon
    campaigns, sounder validation, DGS simulator
    provider, radiative transfer modeling
  • NG Azusa hardware/software leads, partner in all
    activities
  • NASA ER-2 aircraft under-flight team

23
Team Organization
24
Milestones/Schedule
(Healthy Sensor Stable Ground Processing
Software)
L6 M
L
L12 D
L 12M
L2.5 M
L5 D
L 18M
L20M
27 April 2005 ON SCHEDULE
25
Instrument and Algorithm Issues
  • Instrument issues the Team has worked
  • Spin-up anomaly resolved
  • Channels 1-5 polarization resolved with hardware
    change
  • Warm load sun glint mitigated with fence and
    software modeling
  • Emissivity of the primary reflector mitigation
    path defined, work underway
  • Algorithm issues the Team has worked
  • Earth location routines refined
  • Calibration routines refined
  • New EDR algorithms were designed in an attempt to
    mitigate the polarization issue, this was only
    partially successful
  • New algorithms have been designed to model-out
    the sun glint as best we can

26
SSMIS Instrument Issue SDR Bias
  • Variable Bias Traced to High Main Reflector
    Emissivity
  • Anomalous Gain Excursions Traced to Solar
    Impingement on Warm Load

27
SSMIS Instrument Issue SDR Bias
Bias Radiative Transfer Versus SSMIS Average,
Barking Sands Lidar, Nov 2003-Jan 2004
Derived Requirement
28
SSMIS Instrument Issue SDR Bias, Moisture
Channels Barking Sands Lidar Truth
November 2003-January 2004
Derived Requirement
29
SSMIS Instrument Issue SDR Bias
Bias Radiative Transfer Versus SSMIS Ch 3 ECMWF
SSMIS, 17 Mar 2004
30
The Way Ahead
  • Change hardware to H pol for Channels 1-5
  • Tune SDRs to remove bias
  • Tune temperature and water vapor retrievals by
    running the SSMIS off-line code
  • Implement algorithm to mitigate warm load solar
    bias
  • Add solar fence to protect the warm load
  • Correct for bias caused by main reflector
    emissivity
  • Characterize reflector and develop a thermal
    model
  • Move the thermistor to center of main reflector
    to back out emissivity bias
  • Anticipate a major new software release in the
    near future containing Cal/Val upgrades

31
Summary
  • F16 SSMIS Cal/Val very successfully completed on
    schedule
  • Resulting in numerous instrument modifications
    and algorithm updates
  • The team is ready to support an aggressive
    cross-calibration activity with F16 vs F17 SSMIS
  • The team will continue to work the upper air
    sounder EDRs
  • A full technical briefing will be scheduled for
    end of May
  • Scientific publications will follow by team
    members
  • Finally, all team members thank the DMSP SPO for
    their support, and look forward to the future of
    SSMIS

32
SSMIS Calibration and Validation Status
  • Backups

33
F16 SSMIS Calibration/Validation Data Analysis
  • Presented to Col. Wagner, Ms. Smith
  • 4 May 2005

Cal/Val Team The Aerospace Corporation/NRL
34
Calibration of F-16 SSMIS
  • Instrument Performance
  • Radiometer Sensitivity (NEDT)
  • Receiver Gain Stability
  • Calibration Target Stability
  • Temperature Stability
  • Antenna Polarization Purity
  • Doppler Compensation Stability
  • Geo-location (6 Horns)
  • Antenna Beam/Spin Axis Alignment
  • Time Offsets
  • Earth Incidence Angles

35
Calibration of F-16 SSMIS (cont.)
  • Scan Uniformity
  • Field-of-View Intrusions at Start and End of Scan
  • A/B Integrator Calibration
  • Image Striping of Upper Air Channels
  • Absolute Calibration
  • APMIR Underflights (Channels 12-16)
  • COSMIR Underflights (Channels 1-3, 8-11, 17-18)
  • Cross-Calibration with F-14 SSM/I (Channels
    12-18)
  • Radiative Transfer Modeling with LIDAR, NWP,
    Raobs (Sounding Channels)

36
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37
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38
Nov
Oct
Dec
Jan
Feb
Mar
Apr
May
39
SSMIS Geo-location Task
  • OBJECTIVES
  • Determine Geo-location Accuracy
  • Derive Corrections to bring errors within
    specification ( 6km)
  • Time Offset
  • 1/2 Cone Angle Offsets
  • Pitch, Roll, Yaw Offsets
  • Beam Azimuth / Elevation Offsets
  • Azimuth Offset
  • Determine Earth Incidence Angle of Antenna Beam
  • APPROACH
  • Overlay Global Coastline Map with Imagery and
    Derived Coastline
  • Used Successfully for SSM/I and WINDSAT

40
SSMIS Geo-location Results
  • All Channels have Yaw -1.0 Deg. Correction
  • All channels have Delta Time -1.899 Sec.
    Correction
  • Channels 12-14 have 0.4 Deg. Beam Elevation
    Correction
  • Channels 17-18 8-11 have -0.2 Deg. Beam
    Elevation Correction
  • Channels 12-14 have -0.3 Deg. Azimuth Correction
  • EIA Impact Channels 12-14, 8-11, 17-18
  • Geo-location Error
  • Independent Review by Bill Purdy Confirms Results
  • (NRL consultant for WINDSAT)

41
SSMIS Geo-location Before and After Correction
Ch. 18 (Spain/N.Africa)
42
SSMIS Geo-location Before and After Correction
Ch. 18 (Somalia/Yemen)
43
SSMIS Geo-location Before and After Correction
Ch. 12 (Spain/N.Africa)
44
SSMIS Geo-location Before and After Correction
Ch. 15 (Gulf Of Mexico/Yucatan)
45
SSMIS Scan Non-Uniformity
  • Observations
  • Chs. 12-14 Large Increase at Start of Scene
    Sector
  • 3-5 K change over 12 pixels
  • Chs. 15-16 Large Decrease at End of Scene
    Sector
  • 4-7 K change over 12 pixels
  • Chs. 8-11,17-18 Saw-tooth Behavior
  • Chs. 1-7,24 Small Saw-tooth Behavior and Small
  • Chs. 19-23 Scan Behavior Not Repeatable or
    Understood
  • Causes 1) Field-of-View Intrusion of Chs. 12-14
    by Cold Space Reflector at Start of Scene Sector
    2) Near-field Interaction by S/C with Chs. 15-16
    3) A/B Integrator Calibration Error (Only Odd
    Sampled Pixels)4) Upper-air Channels Dominated
    by Zeeman Effects
  • Solution Implement Pixel Dependent Scan Bias
    Correction in GDPS SDRP Module.
  • Result Entire 1700 km Swath Available for SDR
    and EDR Products

46
SSMIS Scan Non-Uniformity Channels 12-14 and 15-16
47
SSMIS Scan Non-Uniformity Channels 8-11, 17-18
and 1-7, 24
48
Receiver LO Compensation Removes Doppler Shift
of Upper Air Channels
49
Average Larger Set of Calibration Data Removes
Striping in Upper Air Channels
50
APMIR (Airborne Polarimetric Microwave
Imaging Radiometer)
  • Justin Bobak
  • Naval Research Laboratory
  • Washington DC

Troy vonRentzell Norman McGlothlin Steven Quinn
David Dowgiallo Louis Rose Brian Hicks
51
APMIR
52
SSMIS Underflight 3/23/04 19V
53
Time Series Plot 37H FWD and 19H AFT
54
Conclusions for March 23 data
  • Excellent agreement between all SSMIS and APMIR
    channels
  • Small bias exists on 22V
  • Data trends in APMIR data match those in SSMIS
    data
  • Over 60 of 19V and 37H data comparisons are
    within 1 K
  • No major calibration errors are present

55
Results of CoSMIR Under-Flights of the SSMIS
  • J. R. Wang, P. Racette, and J. Piepmeier
  • NASA Goddard Space FlightCenter
  • Greenbelt, Maryland
  • June 29-30, 2004

92
50
150
183
56
CoSMIR Flight Track
57
CoSMIR Comparison with SSMIS (03/17/2004)
58
Conclusions
  • Based on laboratory test data and the in-flight
    data the lakes, the accuracy of the calibrated
    CoSMIR brightness temperatures (Tb) is very good.
    Thus, the data sets acquired from the
    under-flights are adequate for calibration/validat
    ion of the SSMIS.
  • March 04 Comparison of the SSMIS and CoSMIR Tb
    values suggests that the 50 GHz channels of the
    SSMIS are vertically polarized. For the other
    channels between 91-183 GHz, the SSMIS
    measurements are generally higher.
  • The positive biases of the SSMIS 50-183 GHz
    channels appear to depend slightly on the times
    of the overpasses.
  • Modifications to CoSMIR were undertaken to allow
    a selectable polarization of either V or H to
    match SSMIS.
  • Recent A/C underflights confirm that SSMIS Chs.
    1-5 have V polarization and that the anomalous
    increase in SSMIS Tb observed during exit from
    eclipse does NOT occur with CoSMIR measurements.
    The latter result provides further confirmation
    of the relatively large reflector emissivity of
    SSMIS.

59
Cross-Calibrate SSMIS SDRs with F-14 SSM/I
  • Very High Spatial/Temporal Coincidence
  • Satellite Sub-tracks Overlay and
  • Within 10 minutes 6-7 November 03
  • 20 minutes 14-15 January 04
  • 30 minutes 23-24 March 04
  • Pixel to Pixel Distances within 2-5km
  • Scene Viewing Geometry/Propagation Paths Nearly
    Same
  • Many Matchups of all Surface Types/Atmospheres
  • (Typically over 500,000 for Ocean 300,000 for
    land, and 120,000 for Sea Ice)

60
Cross-Calibrate SSMIS SDRs with F-14 SSM/I (cont.)
  • Channel Frequencies/Polarizations
  • SSM/I SSMIS
  • 19.35 V/H 19.35 V/H
  • 22.235 V 22.235 V
  • 37.0 V/H 37.0 V/H
  • 85.5 V/H 91.65 V/H
  • Known Pre-launch Feedhorn Misalignment of
    Polarizations of 19/22/37 with Earth Basis
  • Map SSMIS TDR to F-14 SSM/I SDR with New Antenna
    Pattern Correction (APC) in GDPS
  • Use 6-7 November 03 Matchups for Development Set
  • Use 14-15 January 04 and 23-24 March 04 for Test
    Set
  • Daily Global Comparison for Additional Tests

61
New SSMIS APC Based on regression of Matchups
with F-14 SSM/I
62
Comparison of SSMIS SDR (New APC) with F-14
SSM/I (Descending Passes 06 November 2003)
63
SDR Differences of SSMIS (New APC) with F-14
SSM/I (Ascending / Descending Passes 06 November
2003)
64
Cross-Validate SSMIS Environmental EDRs with F-14
SSM/I
  • SSMIS EDRs Employ SDRs that have a New APC
    Derived from Cross-Calibration with F-14
    SSM/I
  • EDR Comparisons
  • Ocean Surface Wind Speed, Water Vapor, Cloud
    Liquid Water, Rain Flag and
    Rainfall Rate
  • Land Surface Surface Type, Surface Temperature,
    Soil Moisture, Snow Water Equivalent,
    Snow Edge, Rain Flag, Rainfall Rate
  • Sea Ice Concentration, Age, Edge
  • Coast/Near Coast Rain Flag, Rainfall Rate
  • Heritage SSM/I EDR Algorithms are Employed for
    SSMIS Providing Continuity of Transition from
    SSM/I

65
SSMIS SSM/I Ocean Surface Wind Speed EDR
Comparison (06 November 2003)
66
SSMIS SSM/I Ocean Surface Water Vapor EDR
Comparison (06 November 2003)
67
SSMIS-SSMI Land Surface Type EDR (06 November
2003)
68
SSMIS SSM/I Land Surface Temperatures (06
November 2003)
69
SSMIS _ SSM/I Sea Ice Concentration (Northern
Hemisphere (06 November 2003)
70
SSMIS _ SSM/I Sea Ice Concentration Southern
Hemisphere (06 November 2003)
71
SSMIS SSM/I Ocean, Land and Sea Ice EDR
Comparison
72
Cal/Val Infrastructure Pyramid
People
Analysis Tools
Analysis Products
Data Quality
Database
Metadata
Process
Data Sets
Hardware
Software Tools
73
Infrastructure Pyramid (Foundation)
Process
Data Sets
Hardware
Software Environment
  • Developed Calibration and Validation Plans
  • Analyzed Calibration and Validation Plans to
    design process flow required to fulfill Cal/Val
    plan execution
  • Used process flow diagrams to identify key
    milestones, assess readiness and identify tasks
    and infrastructure needs.

74
Calibration Process Flow
75
Validation Process Flow
76
Algorithm Improvement Process Flow
77
Infrastructure Pyramid (Foundation)
Process
Data Sets
Hardware
Software Environment
  • Identified required truth and sensor data sets
  • Data set availability and ingest requirements
  • Developed data delivery and storage formats
  • Determined sizing and storage requirements
  • Diagrammed entire data flow process through the
    cal/val process

78
Calibration/Validation Data Flow
79
Aerospace Omaha Data Flow
80
Infrastructure Pyramid (Foundation)
Process
Data Sets
Hardware
Software Environment
  • Sized and implemented computer hardware
    infrastructure for Omaha field office and El
    Segundo Lab
  • 35GB data transmittal and storage per day
  • Cluster of Sun Servers, SGI, Cray and Mac OS X
    servers
  • Media Delivery, archive and backup mechanisms
    (DVD, DLT Tape, FTP)

81
Infrastructure Pyramid (Foundation)
Process
Data Sets
Hardware
Software Environment
  • Selection and deployment of software environment
    to be used for data collection, processing, and
    distribution of data sets and analysis products
  • Programming Environment includes unix shell
    scripts, C/C, IDL, Oracle database development
    suite
  • Implemented source code revision control system
    for all software development

82
Infrastructure Pyramid (Data Warehouse)
Data Quality
Database
Metadata
  • Implemented Data Quality tools to apply quality
    flags to data elements
  • Database infrastructure
  • Unix file system, Oracle 9i database, Oracle
    Collaboration Tools, custom programs
  • Metadata information (Data about the data)
  • Spatial, temporal, data source, anomaly
    annotation, etc..
  • Data warehouse level stores, tracks and allows
    for retrieval of all data sets and generated
    analysis products via metadata query

83
Infrastructure Pyramid (Analysis)
Analysis Tools
Analysis Products
  • Interactive analysis tools
  • Custom developed and commercial off the shelf
    (COTS) visualization tools
  • Analysis Products
  • Imagery, plots, reports
  • Automatic generation and distribution of certain
    analysis products

84
Analysis Tools Data Flow
85
Ice Clouds Analysis Product
86
Surface Boundary Analysis Product
87
Infrastructure Pyramid (Apex)
People
  • Talented group of sensor engineers,
    meteorological experts software developers,
    database engineers, network and systems engineers
  • Frequent collaboration for the development and
    improvement of tools and analysis products
  • Conducted very successful dry runs exercising
    data collection and analysis components prior to
    launch

88
Cal/Val Infrastructure Look Ahead
  • Improvement of data warehouse infrastructure
    through continued Oracle Workflow, Collaborative
    Suite and Warehouse builder implementation
  • Increased functionality by implementing IDL
    Dataminer, VisAd, and improvements to custom
    analysis tools
  • Development of NPOESS collaborative database to
    support NPOESS cal/val risk reduction and data
    needs.
  • Recasting of data sets and analysis products into
    HDF5 for use by NPOESS cal/val community
  • Funding secured for NPOESS related improvements
    from NPOESS program office

89
Infrastructure Summary
People
  • Infrastructure is in place and meeting F16
    cal/val requirements
  • Continued improvement to data warehouse and
    analysis tools
  • Will provide for a complete and comprehensive
    database of truth and satellite data
  • Invaluable application to scientific community,
    future DMSP flights, and NPOESS Cal/Val

Analysis Tools
Analysis Products
Data Quality
Database
Metadata
Process
Data Sets
Hardware
Software Tools
90
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91
Hurricane Ivan SSMIS - SSM/I SDR Imagery 15
September 2004
SSMIS Ch. 18 (R04703)
SSM/I 85H (R24597)
92
Hurricane Ivan SSMIS SDR Imagery Chs. 8-11
(R04703) 15 September 2004
Ch.09
Ch.08
Ch.11
Ch.10
93
SSMIS - SSM/I Land EDR Comparisons
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