CLARREO IIP and Study Discussion

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CLARREOIIP and Study Discussion

• T. Pagano
• Jet Propulsion Laboratory
• October 24, 2007

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JPL IIP SupportTropospheric Emission
Spectrometer
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TES Flight System Has Several Modules
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TES Uses Double Pass Corner Cube Interferometer
EPD 50 mm f/ 2.0 EFL 100 mm FOV 12 mr x
7.5 mr IFOV 0.75 mr x 7.5 mr Scan OPD 33.8
cm Pointing 45 deg Cone Pixel Size 0.75 mm x
0.075 mm
Tscan 4 s (nadir)
1A 3.3 5.3 mm 1B 8.7 12.2 mm 2A 5.1
9.1 mm 2B 11.1 15.4 mm
Nd YAG 1.06 microns
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TES Team Available at JPL

• Tom Glavich TES PM
• Reinhard Beer TES PI
• Mary White Optics PEM
• Eric Hochberg Optics Fab
• Dave Rider Instrument Scientist
• Jose Rodrigues Thermal Design
• Kevin Bowman Algorithms
• Helen Warden Algorithms
• FPAs Teledyne (Formerly Rockwell)
• Dewar Space Dynamice Lab
• Pulse Tube Cooler NGST (Formerly TRW)

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TES, AIRS, CrIS Comparison
Tropospheric Emission Spectrometer Spectral
Range 3.3-15.4 mm Spectral Resolution 0.015
0.06 cm-1 Spatial Resolution 0.5 x 5 km,
nadir 385 kg, 334 W, 1.8 m3, 4.5 Mbps Cost 180M
Atmospheric Infrared Sounder Spectral Range
3.7-15.4 mm Spectral Resolution 0.5 2.5
cm-1 Spatial Resolution 14 km, 49.5 177 kg,
236 W, 0.9 m3, 1.3 Mbps Cost 196M
Crosstrack Infrared Sounder Spectral Range
3.9-15.4 mm Spectral Resolution 0.5 2.5
cm-1 Spatial Resolution 14 km, 48.3 165 kg,
135 W, 0.5 m3, 1.5 Mbps Cost 250M (2 Flight
Units)
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JPL Far IR Detectors
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Herschel, SOFIA and ground based platforms are
are limited by emission from warm
telescopes.Ultimate limitation is photon noise
from the astrophysical backgrounds.Source
confusion is not a problem for R1000
spectroscopy.SPICA leads the way to SAFIR and
beyond temperature is more important than
aperture.Cold space telescope allows
high-redshift spectroscopy throughout the far-IR
Far-IR spectroscopy with cold telescope is a new
frontier.
Crosses show redshifted fine structure lines in
ULRGs Effect of finite detector NEP in yellow
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Spider-Web Bolometers for Herschel Planck

• HERSCHEL
• 3.5 m telescope (80 K)
• L2 halo orbit
• 4.5 year lifetime
• 2008 launch
• Three instruments
• SPIRE (bolometers)
• photometer at 250, 350, 500 um
• FT spectrometer 200 350, 350 670 um
• PACS (photoconductors bolometers)
• imaging at 70/100, 170 um
• grating spectroscopy 60 210 um
• HIFI (heterodyne)
• high-resolution spectroscopy 610 270 um
• PLANCK

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Quantum Well IntraSubband Photodetector
(QWISP)for Far Infrared Radiation Detection

• New far-IR detector concept addresses the need
  for 100 300 mm large format focal plane array
  (FPA)
• Closely related to the well-established Quantum
  Well Infrared Photodetector (QWIP)
• Extensive 3D quantum device simulation predicts
  superior far-IR performance than the QWIP (see
  below)
• Based on mature GaAs technology
• Can leverage JPLs world-class large-format QWIP
  FPA expertise
• Can be developed rapidly and inexpensively

POC David.Z.Ting_at_jpl.nasa.gov
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CLARREO Performance
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Expect Pyroelectric D of 2 x 108
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CLARREO Design Parameters to Meet NEdT of 0.1K

• S 100 Spatial Resolution (km)
• H 705.3 Orbit Altitude (km)
• vg 6.76 km/s
• D 5 Aperture Diameter (cm)
• fno 2 Focal Ratio
• d 14.0 Detector Size (mm)
• Trans 0.2 System Transmission
• Tstare14.8 Stare Time (s)
• Dstar 2E8 Detectivity at 200Hz (cm
  root-hz / W)
• vn_min 200 Minimum Wavenumber (cm-1)
• vn_max 2000 Maximum Wavenumber (cm-1)
• OPD 0.5 Optical Path Difference (cm)
• dvn 1.0 System Spectral Resolution
  (cm-1)
• Tscene 250 Average Scene Temperature
  (K)
• Tinst 280 Instrument Temperature (K)

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D-Star of 2x108 Not affected by Background
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SNR and NEdTLimited at Higher Wavenumbers
Preliminary Best Case
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Self Apodization broadens lineshape at lower
frequencies
Shift of Peak Frequency With Off-Axis Response
Uncorrected Response 5 cm-1
OPD 0.5 cm n 2000 cm-1 l 5 mm Dn 1 cm-1
Unapodized Ideal Response FOV 0 to 4
4 x 4 Array with Bias Correction 1.5 cm-1

• CLARREO 100 km Footprint Broadens Lineshape
• Increases Impact of Non-homogenous Fields
• Correct using N x N Array at Higher Spatial
  Resolution
• Offset Spectral Response by Nominal Value at
  Center of Array
• Need to Analyze Effects of Residual Errors
• Effect seen in IASI data in cloudy scenes.

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CLARREO Grating Concept
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JPL Has Expertise in Far IR Grating Spectrometers
Need Wide Field CLARREO Optical Design
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CLARREO Grating Concept

• Preliminary
• Approach
• Solid State Grating Spectrometer
• 3mm Aperture Telescope with 0.1X Magnification
• 3cm Aperture Grating Spectrometer
• Single Grating operated in 6 Orders
• Use 640 x 480 Microbolometer Array
• 6 Segments (800 um x 1) x (27 um x N)
• TBD Optimize optics for 17 micron pixels
• Wide Field Grating Spectrometer
• Performance
• 5-50 um, Dn 1cm-1 to 2cm-1
• Close, but not quite there
• Requires higher spectral resolution in SW
• Need ambient operation
• Need to Redo NEdT Calculation for Latest
  Microbolometer Performance

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System Parameters
14.6 s Dwell
3 mm Aperture
0.1 Magnification
804 um Detector
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Absorption for a Simple Bolometer Stack Not
Optimized
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Spectrometer Parameters
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Spectral Resolution and Grating Efficiency
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Dispersion Angles
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Cross-Calibration Lessons Learned and
Expectations for CLARREO
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Instrument Stability and Accuracy Essential for
Climate Studies
AIRS Hyperspectral CoverageClimate Data Record
(CDR)over 5 Billion Spectra
AIRS Radiometric Performance Stable to lt8mK/Y
H. Aumann (JPL)
2378 channels
Scanning HIS Validates Rad Accy to 0.2K H.
Revercomb (UW)
AIRS Frequencies Stable Knowledge to lt 1 PPM -
L. Strow (UMBC)
Reference JGR, VOL. 111, April 2006
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Validation Requires Good Spatial Resolution and
Coverage

• Validation Essential
• All instruments must be validated using in-situ
  observations
• Radiometric Buoys, Aircraft, ARM Sites
• Spectral Atmospheric Lines
• Validation Requirements
• Moderate Spatial Resolution (lt15 km)
• Allows direct comparison with aircraft
• Allows sufficient number of clear samples
• Wide Swath (gt 45)
• Allows more opportunity for cross-comparison and
  simultaneous in-situ observations
• Good NEdT (lt 0.2K)
• For least number of samples per comparison

1J. Krijger et. al, The effect of sensor
resolution on the number of cloud-free
observations from space, Atmos. Chem. Phys.
Discuss., 6, 4465-4499, 2006, www.atmos-chem-phys-
discuss.net/6/4465/2006
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Cross-Calibration and Comparison Successful with
Sounders / Imagers
Cross- Calibration
AIRS-MODIS/HIRS Trend in Radiometric
Calibration Dome Concordia
Shift in MODIS Calibration Algorithm V4 to V5
MODIS Bias 1K
Cross- Comparison
IASI-AIRS Accurate to 0.008K 0.18K
HIRS Stable
S. Broberg, Evaluation of AIRS, MODIS, and HIRS
11 micron brightness temperature difference
changes from 2002 through 2006, SPIE 6296-22,
August 2006

• Samples
• Uniform Scene at Dome C

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Nonuniform Scene Adds Noise to Cross-Calibration
Spatial Response Function Must be well
known Channel 774, FP 70
AIRS-MODIS Non-uniform Scene
Uncorrected 4.2K
Simple Correction 2.26K
Corrected 0.57K
Noise in non-uniform scene leads to need for
clear-uniformor significantly more samples
D. Eliott, et. al, The Impact Of the AIRS
Spatial Response On Channel-To-Channel and
Multi-Instrument Data Analyses, Proc. SPIE,
6296-01 (2006)
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Limited Overlaps if 100 km Nadir Only
Satellite 1 833 km alt, Sunsynch orbit,
footprint 1500 km wide x 45 km highSatellite 2
750 km alt, Polar orbit, footprint 100 km wide x
100 km high.
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Zonal and Temporal Dependence of Orbits will
Complicate Cross-Calibration
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Insufficient Samples to Cross-CalibrateRequire
Pointing and Higher Resolution

• Number of Samples if Clear for Cross-Cal 1000
• Non-Uniform Scene Noise Amplification x 25
• Number of Overpasses / Satellite in 5 Mo 5 /
  1300
• Number of Satellites / 3
• Total Number of Months to Calibrate 32
• Time is Too Long to avoid systematic errors
• Thermal/Temporal Drift of Instrument
• Secular Climatology Change of Atmosphere
• Regional Biases in Sampling Set
• Solution
• 1. Point Instrument Line of Sight 50
• 2. Higher Spatial Resolution lt15 km

Study activity will compare AIRS MODIS Cross-Cal
vs AIRS Resolution and Pointing. Redo Orbit
Analysis.
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Sounder Climate Science
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Sounder Constellation in Place Continuously from
2002 onward
IASI
AIRS
CrIS
Actual AIRS Spectra
AIRS on Aqua 130 PM Orbit 14 km GSD 49.5
Swath 0.1-0.2K Absolute 10mK/year Stability
CrIS on NPOESS 130 PM Orbit 14 km GSD 48.3
Swath C1 2013 C3 2020
IASI on MetOp 1030 AM Orbit 12 km GSD 49 Swath
NPOESS 530 AM C2 2016 CrIS De-Manifested
NPP
C3
C1
C2
TES on Aura 130 PM Orbit
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AIRS/CrIS and IASI Provide 4 Points in Diurnal
Cycle
Diurnal Cycle of SST
AIRS Aqua 1330, 130TES Aura 1330,
130 CrIS NPOESS C1 and C3 1330, 130 IASI
MetOp, 930, 2130 CrIS NPOESS C2
(Cancelled) 530, 1730
A
C
A
C
C
I
I
C
I
C
A
C
CrIS on C2 Would Improve Characterizationof
Diurnal Cycle
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Sounder Data Products and Spectra are used for
Climate Model Validation

• Method 1 Data Products (L3)
• The models are drier than AIRS observations by
  10-25 in the tropics below 800 hPa.
• The models are more moist by 25-100 between 300
  and 600 hPa, especially in the extra-tropics.
• David W. Pierce, Tim P. Barnett, Eric J.
  Fetzer, Peter J. Gleckler, Three-dimensional
  tropospheric water vapor in coupled climate
  models compared with observations from the AIRS
  satellite system, GRL, VOL. 33, L21701,
  doi10.1029/2006GL027060, 2006
• Method 2. Radiances (L1b)
• OLR Agrees with Models
• Compensating Errors
• Models dry in lower troposphere compensated by
  higher surface flux
• Huang et al. 2007.

SDRs and EDRs must be Climate Quality
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Hyperspectral IR Spectra DirectlyUsed for
Climate Studies

• Trending
• The four year anomaly of AMSU and AIRS
  temperatures at 400 mb shows a pronounced
  quasi-bi-annual fluctuation of about 0.4 K
  peak-to-peak.
• This fluctuation severely limits the ability to
  interpret trends on a four year time scale in
  terms of climate relevance.
• It also makes it difficult to compare the mean of
  four years from today with similar data taken 20
  years ago or 20 years from now, even if they were
  intrinsically accurate at the 100 mK 3 sigma
  level.
• Aumann (2007)
• Principal Component Analysis
• Difference in EOF1 suggest there is a problem in
  the boundary layer humidity.
• Huang, X., and Y. L. Yung. (2005). Spatial and
  spectral variability of the outgoing thermal IR
  spectra from AIRS A case study of July 2003. J.
  Geophys. Res. 110 D12102/2004JD005530.
• See Yung/Waliser Poster

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Derived Products Valuable for Climate Validation
and Process Studies

• Coupled Climate Model Validation
• The models are drier than AIRS observations by
  10-25 in the tropics below 800 hPa.
• The models are more moist by 25-100 between 300
  and 600 hPa, especially in the extra-tropics.
• David W. Pierce, Tim P. Barnett, Eric J.
  Fetzer, Peter J. Gleckler, Three-dimensional
  tropospheric water vapor in coupled climate
  models compared with observations from the AIRS
  satellite system, GRL, VOL. 33, L21701,
  doi10.1029/2006GL027060, 2006
• Water Vapor Parameterization
• Supersaturation affects amount of water vapor in
  upper stratosphere which in turns affect amount
  of clouds
• Changes Cloud Forcing
• LWIR D -7 W/m2, SWIR D 8 W/m2, NET D
  -0.60.3 W/m2
• A. Gettelman and D. E. Kinnison, The global
  impact of supersaturation in a coupled
  chemistry-climate model, Atmos. Chem. Phys., 7,
  16291643, 2007 www.atmos-chem-phys.net/7/1629/200
  7/
• Water Vapor Transport Studies
• Simple trajectory model with fixed RH limit does
  a good job of reproducing AIRS annual average
  water vapor
• Dessler, A. E., and K. Minschwaner (2007), An
  analysis of the regulation of tropical
  tropospheric water vapor, J. Geophys. Res., 112,
  D10120, doi10.1029/2006JD007683, 2007

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Small CO2 Signal Trends Only Possible with
Sufficient Stability and Coverage
AIRS CO2 Product (Chahine)
CO2 Trending using Spectra (Strow)
Observed
AIRS vs JAL
AIRS Zonal Trends (Strow)
Model
Demonstrates lt10mK/year Stability
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Sounder Limitations over Land, Clouds and
Boundary Layer
Emissivity
Climate Scientists need better products in
PBL Clouds and Emissivity Limit Sounder Accuracy
AIRS 50x50 km ? 1095 cm-1
Temperature Profile Error
MODIS 5x5 km ? 1205 cm-1
Can CLARREO Improve PBL Water Vapor and Surface
Emissivity?
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Temperature and Water Vapor Obs only require one
band
HyTWP
Mike Gunson (JPL)
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SIRAS IIP can reduce cost of MW/LW sensor
The Spaceborne Infrared Atmospheric Sounder
(SIRAS) Spectrometer Developed under
NASAInstrument Incubator Program in 2001 No
Moving or Active Parts Mass 2kg Size 10 x 10 x
14 cm Field of view X-Track 16.2 Pushbroom
Operation Spectral Resolution gt900 (l/Dl) Number
of Channels 512 Each 4 Required for Full
Spectral Range Spectral Range 12-15.4 µm PI
Hartmut Aumann (AIRS IR Proj. Sci.)
PRELIMINARY BALL AEROSPACE DESIGN
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Compact MW/LW Spectrometer Concepts Exist
Size 0.4 x 0.3 x 0.2 m Mass 50 kg (est.) Power
50 W (est.) Data Rate 2 Mbps
Thermally Isolated Controlled Optical Bench
Electronics
Calibration Point Mirror
Active Cryo- Cooler
Grating Spectrometer
Passive Radiator
Telescope
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Panel on Climate Variability and Change (Chapter
9) Define Science Questions

• The panel focused on four fundamental questions
  in its approach to envisioning specific
  space-based and supporting in situ and
  surface-based observations required for studies
  of the Earths climate
• (1) what governs the Earths climate, (2) what
  forces climate change, (3) what feedbacks affect
  climate variability and change, and (4) how is
  the climate changing? In the coming decade, we
  will be challenged to better predict how the
  Earth will respond to the changes in atmospheric
  composition and other forcing. Our observations
  must document the forces on the climate system
  (including solar and volcanic activity,
  greenhouse gases and aerosols, changes in land
  surface and albedo), the characteristics of
  internal variability which can obscure forced
  changes and which may evolve in response to
  climate change, the feedback processes involving
  the atmosphere, land and ocean, biogeochemical
  cycles and the hydrologic cycle, and climate
  change itself.
• Stripped to fundamentals, the climate is first
  affected by the long-term balance between the
  sunlight absorbed and infrared radiation emitted
  by the Earth. Thus, key elements to observe are
  the incident sunlight, the absorbed sunlight and
  the emitted infrared radiation. Achieving an
  understanding of how the system works requires
  the determination of the affecting influences,
  the absorbed sunlight and the emitted radiation.
  These include the composition of the atmosphere
  (such as greenhouse gases and aerosols), the
  state of the surface (whether snow or ice
  covered, whether vegetated or desert), and the
  effects of the various atmospheric components and
  the surface state on radiation loss to space. In
  addition, physical and chemical processes within
  the system feed back to affect the composition of
  the atmosphere and the surface state, such as the
  processes affecting water vapor and clouds. Other
  processes and conditions such as the extent of
  permafrost, subsurface concentrations of
  phytoplankton, and the oceans thermohaline
  circulation are hidden from direct space view.
  Inferences must be drawn not only from records of
  space-based observations, but also from in situ
  as well as remotely sensed observations from
  surface-based, balloon, and suborbital platforms.

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Panel on Climate Variability and Change (Chapter
9) Addresses Process Studies

• Focused Process Studies
• Process studies focus on understanding the
  climate feedback process and are critical to
  improving climate models. They are generally
  intensive, short-duration, repeated campaigns
  with ground-based, airborne, satellite, and
  modeling components. These studies typically
  require frequent, diurnally resolved measurements
  and a wide variety of simultaneous products, a
  need typically at odds with the accuracy and
  stability essential for achieving reliable
  long-term records.
• Current Status of Process Studies
• Many climate system processes and many causes of
  climate variability and change are not fully
  understood or adequately validated with
  observations. The large range in climate model
  estimates of the change in the global surface
  temperature in response to a doubling of CO2
  illustrates how choices in treating these
  processeswhich vary greatly from model to
  modelcan have sizable consequences. Reliable
  climate simulations require improved treatment of
  the processes known to be inadequate (NRC, 2003b
  NRC, 2005b) (1) clouds, aerosols, and convective
  systems (2) biosphere-atmosphere interactions
  (3) sea ice, ocean circulation and ice-melt
  coupling (4) ice sheet dynamics (5) the fluxes
  of heat, momentum, water, and trace species
  across the interfaces of ocean-atmosphere,
  land-atmosphere, ice-atmosphere, boundary layer
  and free troposphere, troposphere-stratosphere,
  and ice-ocean and (6) internal variability such
  as the ENSO.
• Needed Improvements and Products for Process
  Studies
• There must be a more deliberate effort to focus
  resources on the most critical weaknesses in
  predictive models, most specifically the six
  topics listed above.

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Requirements Traceability Matrix
Green Ch 4 Decadal Survey Purple Ch 9 Decadal
Survey
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Measurement and Mission Requirements
Green Ch 4 Decadal Survey Purple Ch 9 Decadal
Survey