(1) Calibration of AIRS SRFs (2) AIRS Forward Model...

AIRS: February 2000 STM

(1) Calibration of AIRS SRFs

(2) AIRS Forward Model Schedule & Validation

L. Larrabee Strow

Scott E. Hannon

Sergio De Souza-Machado

Howard E. Motteler

U M B C

UN

IVE

RSI

TY

OF

MARYLAND BALTIM

OR

E C

OU

NTY

1 9 6 6

Department of Physics

University of Maryland Baltimore County (UMBC)

Baltimore, MD 21250

L. Strow, UMBC 1


Overview

• SRF Calibration Review and Status

• Forward Model Schedule, pre-launch

• Forward Model Schedule, post-launch

• Validation Requirements

L. Strow, UMBC 2


Overview: SRF Calibration

• Grating Model Fits and Fringe Removal

• Sensitivity of Centroids (Y-offset), Focal Length, Widths to

Temperature

• Model Fits to SRF Shapes: Wings, Center Region

• Absolute Calibration with CO Trace Gas, Air Gap Spectra

L. Strow, UMBC 3


Grating Model Fits and Temperature Sensitivity

• Fringe removal using summed SRFs very successful

• SRF Centroids all move together nicely with temperature

• Focal length, widths insensitive to temperature

• Slight quadratic error in grating model fits to centroids (1% of

width level)

L. Strow, UMBC 4


Example Grating Model Fits (Red=Raw Data, Blue=Fringes Removed)

−1

−0.5

0

0.5

1

% o

bs−

calc

cen

ters

Test:1621, Module: M4d, Gain:Opt, Good Chans:93%

1210 1220 1230 1240 1250 1260 1270 1280−15

−10

−5

0

% o

bs−

calc

wid

ths

Wavenumber (cm−1)

−2

−1

0

1

2

% o

bs−

calc

cen

ters

Test:1621, Module: M5, Gain:Opt, Good Chans:93%

1040 1060 1080 1100 1120 1140−15

−10

−5

0

% o

bs−

calc

wid

ths

Wavenumber (cm−1)

L. Strow, UMBC 5


GM Fit Errors if Channels 82/83, 118/119 Removed

−2

−1

0

1

2%

obs

−ca

lc c

ente

rs

Test:1621, Module: M12, Gain:Opt, Good Chans:95%

645 650 655 660 665 670 675 680 685−20

−15

−10

−5

% o

bs−

calc

wid

ths

Wavenumber (cm−1)

L. Strow, UMBC 6


Variation of Focal Length with Temperature

148 150 152 154 156 158 160 162−30

−20

−10

0

10

20

30

40

Grating Temperature (K)

Foc

al L

engt

h (m

icro

ns) Green line: M12

Red line: M5

L. Strow, UMBC 7


Sensitivity of Centroids to Focal Length

500 1000 1500 2000 2500−5

−4

−3

−2

−1

0

1

2

3

4

5

Wavenumber (cm−1)

Cen

troi

d E

rror

in %

of W

idth

50 µm error20 µm error10 µm error

L. Strow, UMBC 8


Variation of SRF Width with Temperature – I

148 150 152 154 156 158 160 162−0.6

−0.4

−0.2

0

0.2

0.4

0.6

0.8

1

Grating Temperature (K)

Wid

th V

aria

tion

in %

Green line: M12Red line: M8

L. Strow, UMBC 9


Variation of SRF Width with Temperature – II

1000 1500 2000 2500

−1.5

−1

−0.5

0

0.5

1

1.5

2

Wavenumber (cm−1)

Wid

th V

aria

tion

in %

T149 vs T155T155 vs T161T149 vs T161

L. Strow, UMBC 10


Fitting SRFs to an Analytic Model

• Eventually fit wings and center portions separately (maybe 3 wings will

be used for short/mid/long-wave).

• Data shown here are fits to wing and center together, with good starting

estimates for the wing. Actually fit: 20% of log of SRF plus 80% linear SRF.

• Primarily interested in quality of analytical model fits to center region.

• Using H. Aumann’s hybrid Gaussian/Lorentz model

• Main conclusions:

– Slight wavenumber dependence on wing level (scattering?)

– sinc2 diffraction evident in SRFs at the 1.5 - 4% level? Quite large for

M11/M12.

– Taking diffraction into account in model may improve computation of

fringe signal!

– Small residual asymmetries remain in SRFs, easy to handle

– Bruker aligned, our Bruker model follows data

L. Strow, UMBC 11


Averaged SRFs, Dotted Line is Standard Deviation over Arrays

−300 −200 −100 0 100 200 300

10−3

10−2

10−1

100

Microns from SRF Center

SR

F M

agni

tude

Longwave Midwave Shortwave

L. Strow, UMBC 12


SRF Model Fit Results: Wings

2598 2600 2602 2604 2606 2608 261010

−4

10−3

10−2

10−1

100

Wavenumber (cm−1)

SR

F V

alue

Data Fit |Obs−Calc|

2356 2358 2360 2362 2364 2366 236810

−4

10−3

10−2

10−1

100

Wavenumber (cm−1)

SR

F V

alue


L. Strow, UMBC 13



875 876 877 878 879 880 881

10−3

10−2

10−1

100

Wavenumber (cm−1)

SR

F V

alue


817 818 819 820 821 82210

−4

10−3

10−2

10−1

100

Wavenumber (cm−1)

SR

F V

alue


L. Strow, UMBC 14



750 752 754 756 758

10−2

10−1

100

Wavenumber (cm−1)

SR

F V

alue

+ 0

.005


702 704 706 708 710 712

10−2

10−1

100

Wavenumber (cm−1)

SR

F V

alue

+ 0

.005


L. Strow, UMBC 15



662 664 666 668 670 672

10−2

10−1

100

Wavenumber (cm−1)

SR

F V

alue

+ 0

.005


L. Strow, UMBC 16


�3% Peak-Peak Oscillations in Center Part of SRFs

• All arrays exhibit these oscillations in their obs-calcs for a

symmetric SRF model.

• These oscillations are coherent between arrays (in

position-units)

• Maximum modulation is about 4%, in M12.

• They are probably due to sinc2 oscillations in SRF due to

diffraction. H. Aumann has modelled this behavior 5+ years

ago, appears consistent.

• Very possible that neglecting these features has hampered

our ability to recover the pure fringe signal from the SRFs

L. Strow, UMBC 17


SRF Model Fit Results: Center Region

0

0.51

Blu

e: S

RF

; R

ed: 1

0 x

(obs

−ca

lc)

0

0.51 0

0.51

−15

0−

100

−50

050

100

150

0

0.51

SR

F P

ositi

on in

Mic

rons

<−−− SRF Magnitude −−−>

M1a

M2a

M1b

M2b

L. Strow, UMBC 18


SRF Model Fit Results: Center Region

−150 −100 −50 0 50 100 150−0.2

0

0.2

0.4

0.6

0.8

1

SRF Position in Microns

SR

F M

agni

tude

SRF 10 x (obs−calcs)

M12

L. Strow, UMBC 19


Short/Mid/Long-wave Obs-Calc Averages

−0.02

0

0.02

−0.01

0

0.01

0.02

−100 −50 0 50 100−0.01

0

0.01

0.02

Microns from SRF Center

<−

−−

SR

F F

it O

bs−

Cal

c −

−−

>

Shortwave

Midwave

Longwave

L. Strow, UMBC 20


SRF Asymmetry

−150 −100 −50 0 50 100 1500

0.2

0.4

0.6

0.8

1

1.2

Y−Offset in Microns

SR

F M

agni

tude

SRF Obs/Calc

M1a

−150 −100 −50 0 50 100 1500

0.2

0.4

0.6

0.8

1

1.2

1.4

Y−Offset in Microns

SR

F M

agni

tude

SRF Obs/Calc

M2a

L. Strow, UMBC 21


Fringe Signal Polluted with Temperature Independent Features?

−0.05

0

0.051

− F

ringe

1290 1300 1310 1320 1330−0.05

0

0.05

Wavenumber (cm−1)

T−

shift

Err

or

Red: 6K InterpBlack: 12K Interp

L. Strow, UMBC 22


Absolute Calibration

• CO trace gas data indicates that we need to subtract 0.09 cm�1 from the

apodization corrected wavenumber scale at 2193 cm�1.

• Combined apodization correction and offset correction is

�true � �1� 6:944� 10�5 � 0:09=2193�� obs

• Comparison with air gap data shows a difference of 0.03 cm�1 between

what we measure, and what is calculated with the above equation (so far

this includes on 149 and 155K data).

• This comparison assumes that we have correctly computed the

apodization correction (uniform beam, known size, etc.)

• Another way to say this: the Bruker apodization correction is always

about 3x too large.

• This comparison does indicate that our absolute wavenumber scale is

probably sufficient for calibration of the channel spectra.

• CO spectra appear very symmetric! Bruker well-aligned.

L. Strow, UMBC 23


CO Trace Gas Spectrum

2190 2200 2210 2220 2230 2240 22500.3

0.4

0.5

0.6

0.7

0.8

0.9

1

1.1P

seud

o T

rans

mis

sion

Wavenumber (cm−1)

L. Strow, UMBC 24


CO Trace Gas Spectrum – Zoom

2186 2188 2190 2192 21940.4

0.5

0.6

0.7

0.8

0.9

1

1.1P

seud

o T

rans

mis

sion

Wavenumber (cm−1)

L. Strow, UMBC 25


Forward Model Schedule: Pre-Launch

• Proposal is to deliver 10 different AIRS-RTA’s, each offset by 5% of a

width, so the max offset RTA offset at launch will be 2.5% of a width.

These SRFs will be “pure”, no fringing.

• This is a big job! Calibration has taken our attention away from

automating this procedure.

• Optimistic delivery schedule (if get 8 more processors!):

March: Finish SRF analysis for “pure” SRFs

April: Finish new kCARTA spectroscopy

May: Start RTA convolutions (maybe late April)

June: Deliver RTA #1

August: Deliver RTA #2,#3 (now automated production begins)

September: Deliver RTA #4,#5

. . . Deliver 2 RTA’s per month

December: Deliver RTA #10

L. Strow, UMBC 26


Production of AIRS-RTA, Flow Diagram

kCARTA

Layer-to-SpaceTransmittances

Line ShapesContinuum

Profiles

GENLN2

Layers

kCompressedDatabase

SVDCompression

HITRAN 9X

Fast ModelRadiative Transfer

MonochromaticAbs. Coeffs (k)

Fast ModelRegressions

Fast ModelParameters

Radiances

CustomLBL

SRFConvolutions

ConvolvedTransmittances

Retrieval

L. Strow, UMBC 27


AIRS-RTA Production: Automation

• Main steps in putting RTA together after convolutions:

– 7 sets of predictors

– OPTRAN for water

– Variable CO2 correction

– Water continuum (1 shot)

– Solar at top of atmosphere (1 shot)

– Reflected Thermal (1 shot)

• Only 5% speed-up doing the (1 shot) steps only once

• System can be automated, but that is 1-2 months work

L. Strow, UMBC 28


Other Pre-Launch RTA Activities

• Finish SRF shape analysis

– Wings

– Diffraction effects (important for separating out fringes)

– Optimization of SRF shape parameters (connect wing to center region)

• New UMBC-LBL finished, have generated monochromatic transmittancesfor input to kCARTA. These include new Toth H2O and P/R-branch mixingin CO2.

• Compress transmittances for input to kCARTA (starting soon). 1-2months of work to do this.

• Install into kCARTA. Can then start AIRS-RTA convolutions with new SRFs.(Could use old spectroscopy for launch ready software, but would rathernot.)

• We really need to test our forward model against an independentstatistical set of profiles. That has not be done for several years witholder, less accurate?, RTA models.

L. Strow, UMBC 29


Forward Model Schedule: Post-Launch

Launch + 60 days Start comparing radiances to model radiances computed using

kCARTA; need clear flag, over ocean only

Launch + 75 days Spot check AIRS-RTA with kCARTA convolved output, any

obvious large errors?

Launch + 90 days Receive standard frequency set, start computing new AIRS-RTA,

“pure” SRFs

Launch + 100 days Receive fringe position data, start computing new AIRS-RTA,

“true” SRFs

Launch + 120 days Deliver new AIRS-RTA with “pure” SRFs. Start providing kCARTA

convolved radiances for subset of co-locations, automated

Launch + 130 days Deliver new AIRS-RTA, “true” SRFs. Start making any obvious

fixes to spectroscopy, fast model in our local software

Launch + 140 days Compute new AIRS-RTA, “true” SRFs, new spectroscopy/fast

model.

Launch + 170 days Could deliver new AIRS-RTA to JPL. Too close to other

activities... When?

L. Strow, UMBC 30


AIRS-RTA Accuracy Before Launch + 13x days

• At launch AIRS-RTA will contain two known errors because;

– Using “pure” SRFs without fringing effects

– Possible wavenumber offset error of up to 2.5% of a width

• See next 3 graphs for error estimates for these two effects.

• At launch + 120 days, AIRS-RTA will be on exact channel centers

• At launch + 130 days, propose? to provide AIRS-RTA with fringing

• We need the “pure” SRF AIRS-RTA to help verify if we put the fringes intothe SRFs correctly.

• Need to decide on how to handle CO2 variability, and spot-check N2Ovariability.

• We need to be careful about the truth. Better agreement withradiosondes does not always mean the AIRS-RTA is better.

• Spectroscopy errors will take longer to fix.

• How will we decide on what channels are tuned, which are not?

L. Strow, UMBC 31


B(T) Errors for a 5 �m Offset in SRF Centers

800 1000 1200 1400 1600−1

−0.5

0

0.5

1

Err

or in

B(T

) in

K

Wavenumber (cm−1)

220

240

260

280B

(T)

in K

L. Strow, UMBC 32


B(T) Errors for a 5 �m Offset in SRF Centers

220

240

260

280B

(T)

in K

2200 2300 2400 2500 2600

−0.2

0

0.2

Err

or in

B(T

) in

K

Wavenumber (cm−1)

L. Strow, UMBC 33


B(T) Errors if Use “Pure” SRFs vs SRF’s with Fringes

220

240

260

280

300

B(T

) in

K

1000 1500 2000 2500

−0.5

0

0.5

Wavenumber (cm−1)

B(T

) E

rror

L. Strow, UMBC 34


Validation Requirements/Suggestions

• At Launch + 60 days we can start comparing AIRS radiances to those

computed with kCARTA using co-located radiosondes. We can determine

wavenumber scale ourselves.

• Spectroscopy and SRF/Fast Model errors take a long time to fix. We need

co-located radiosondes ASAP after launch + 60 days.

• Need CLEAR tags on co-locations.

• Initial work must be done over water so the surface emissivity is known.

• If scene shows proper wavenumber dependence due to sea-surface

emissivity, that is an excellent double-check on CLEAR flag.

• Several individual high-quality radiosonde co-locations over water are far

preferable to 10-100 questionable co-locations over land. Start limited

special radiosonde launches at launch + 60-90 days.

• Suggested Locations: Acension Island, already does ozone sondes. ARM

Pacific Site, too cloudy? Hawaii? Puerto Rico?

L. Strow, UMBC 35


Validation Software

• Prefer “standing order query” for radiosonde co-locations. Put circularqueue of radiosonde reports and Level 1B data in a directory that we canread. Whenever new reports appear we will download them to UMBC andprocess. Old reports will stay in directory for X days, maybe X=5-10.

• We then upload our results to another directory on a daily/weekly basis?Or provide to Science Team via WWW at UMBC?

• We need to pull files from the Data Warehouse in an automated mannerfrom a remote site (UMBC). The “standing order query” can only be usedsparingly, I think.

• For us to design/test software to do automated processing, we needdocuments that describe the architecture of the Validation Warehouseand the details of the software interfaces.

• Lessons from AIRS ground calibration: Tell me how to get the dataremotely, and what you did to it first.

• Sharing of “private” calibration data at Launch + xx days needs to beworked out. We can’t share 30 Mbyte spreadsheets.

L. Strow, UMBC 36

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