suomi-npp cris radiometric calibration uncertainty

Suomi-NPP CrIS radiometric calibration uncertainty

David Tobin,1 Henry Revercomb,1 Robert Knuteson,1 Joe Taylor,1 Fred Best,1 Lori Borg,1

Dan DeSlover,1 GraemeMartin,1 Henry Buijs,2 Mark Esplin,3 Ronald Glumb,4 Yong Han,5

Daniel Mooney,6 Joe Predina,4 Larrabee Strow,7 Lawrence Suwinski,4 and Likun Wang5

Received 7 June 2013; revised 3 August 2013; accepted 4 September 2013.

[1] The Cross-track Infrared Sounder (CrIS) is the high spectral resolutionspectroradiometer on the Suomi National Polar-Orbiting Partnership (NPP) satellite,providing operational observations of top-of-atmosphere thermal infrared radiance spectrafor weather and climate applications. This paper describes the CrIS radiometric calibrationuncertainty based on prelaunch and on-orbit efforts to estimate calibration parameteruncertainties, and provides example results of recent postlaunch validation efforts to assessthe predicted uncertainty. Prelaunch radiometric uncertainty (RU) estimates computed forthe laboratory test environment are less than ~0.2 K 3 sigma for blackbody scenetemperatures above 250 K, with primary uncertainty contributions from the calibrationblackbody temperature, calibration blackbody reflected radiance terms, and detectornonlinearity. Variability of the prelaunch RU among the longwave band detectors andmidwave band detectors is due to different levels of detector nonlinearity. A methodologyfor on-orbit adjustment of nonlinearity correction parameters to reduce the overallcontribution to RU and to reduce field of view (FOV)-to-FOV variability is described. Theresulting on-orbit RU estimates for Earth view spectra are less than 0.2 K 3 sigma in themidwave and shortwave bands, and less than 0.3 K 3 sigma in the longwave band.Postlaunch validation efforts to assess the radiometric calibration of CrIS are underway;validation results to date indicate that the on-orbit RU estimates are representative. CrISradiance products are expected to reach “Validated” status in early 2014.

Citation: Tobin, D., et al. (2013), Suomi-NPP CrIS radiometric calibration uncertainty, J. Geophys. Res. Atmos., 118,doi:10.1002/jgrd.50809.

1. Introduction

[2] The path from research to operations for high spectralresolution infrared sounding has made a major step forwardwith the flight of the Cross-track Infrared Sounder (CrIS)on Suomi NPP [Glumb and Predina, 2002; Han et al.,2013]. The CrIS is a high spectral resolution FourierTransform Spectrometer that is the operational counterpartto the Atmospheric Infrared Sounder (AIRS) on the NASAEOS Aqua Platform [Pagano et al., 2003; Aumann et al.,

2003]. It has spectral resolution/coverage and spatial sam-pling properties similar to AIRS and the same wide rangeof potential applications. While developed primarily as atemperature and water vapor profiling instrument for weatherforecasting, its high accuracy and extensive informationabout trace gases, clouds, dust, and surface properties makeit a powerful tool for climate applications as well.[3] For applying CrIS data to numerical weather prediction

and climate process studies similar to those explored withAIRS and the Infrared Atmospheric Sounding Interferometer(IASI) [e.g., Chahine et al., 2006; Smith et al., 2009; Hiltonet al., 2012], it is important that its radiometric accuracy berigorously understood. This type of characterization is alsorequired for its proper use in satellite intercalibration efforts[Goldberg et al., 2011; GSICS Traceability Statement for IASIand AIRS, 2011; Chander et al., 2013]. Furthermore, accuratecharacterization is also crucial to the new application of this typeof data for benchmarking the current climate regime of the Earthusing approaches defined for the NASA Climate and AbsoluteRadiance and Refractivity Observatory (CLARREO) DecadalSurvey mission [Wielicki et al., 2013]. While the CLARREOobservations will have more complete coverage of the infraredemission spectrum, including the far-infrared (16–50 μm), andwill provide an accuracy of better than 0.1 K 3 sigma, provenon-orbit using new on-orbit verification and test systemtechnologies [e.g., Taylor et al., 2012; Best et al., 2012], CrIS

1University of Wisconsin-Madison, Madison, Wisconsin, USA.2ABB Analytical Measurement Products, Quebec, Quebec, Canada.3Space Dynamics Laboratory, North Logan, Utah, USA.4Exelis Inc., Fort Wayne, Indiana, USA.5Center for Satellite Applications and Research, National Environmental

Satellite, Data, and Information Service, NOAA, Camp Springs, Maryland,USA.

6Lincoln Laboratory, Massachusetts Institute of Technology, Lexington,Massachusetts, USA.

7University of Maryland, Baltimore County, Catonsville, Maryland, USA.

Corresponding author: D. Tobin, Cooperative Institute for MeteorologicalSatellite Studies, Space Science and Engineering Center, University ofWisconsin-Madison, 1225 W. Dayton St., Madison, WI 53706, USA.([email protected])

©2013. American Geophysical Union. All Rights Reserved.2169-897X/13/10.1002/jgrd.50809

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JOURNAL OF GEOPHYSICAL RESEARCH: ATMOSPHERES, VOL. 118, 1–12, doi:10.1002/jgrd.50809, 2013

data is expected to augment the temporal and spatial coverage ofCLARREO observations. These types of demandingapplications provide motivation for the overview of CrISradiometric accuracy provided in this paper. Also, by under-standing the physical basis of CrIS uncertainties, in the futureit should be possible to transfer the even higher accuracy ofCLARREO-type observations to CrIS. (3 sigma is traditionalterminology for a “not to exceed” uncertainty estimate. In thispaper, 1-sigma and 3 sigma are used to express the 68 andgreater than 99% confidence intervals in the estimated uncer-tainties, and are used interchangeably with the metrologicalcoverage factors, k, of 1 and 3).[4] The primary goal of this paper is to describe the

uncertainty in the radiometric calibration of CrIS based onprelaunch and on-orbit efforts to estimate calibrationparameter uncertainties, as well as to provide a few examplesof postlaunch validation efforts to assess the predicteduncertainty. As described in Han et al. [2013], the InterfaceData Processing Segment (IDPS) CrIS radiance productsare expected to reach Validated status in early 2014.Postlaunch validation studies are underway, and as such,there is the potential for further refinements to calibrationparameters and their associated uncertainties. Results todate, however, show that the CrIS radiometric accuracyis very good and substantially better than programrequirements that were established primarily for weatherapplications. It is clear that the advantages of high spectralresolution IR for weather forecasting and climate demon-strated on-orbit by AIRS and IASI [Siméoni et al., 2004;Blumstein et al., 2007] predecessor observations are beingmatched, and in some regard even exceeded, by CrIS.Many of the successes are due to the knowledge of thespectral response functions inherently provided by highspectral resolution observations [Goody and Haskins,1998; Strow et al., 2013] as well as excellent noise perfor-mance [Zavyalov et al., 2013].[5] We begin by describing the CrIS radiometric uncertainty

(or calibration accuracy) expected for observing blackbodyspectra based on preflight thermal/vacuum testing (section 2),present techniques and results for on-orbit calibration refine-ment analyses (section 3), followed with an assessment ofradiometric uncertainty for Earth spectra (section 4), and finallypresent example results of on-orbit radiance validation by com-parison with calculated spectra and other sensors (section 5).Results are summarized in section 6.

2. Preflight Radiometric Uncertaintyfor Blackbody Spectra

[6] The Radiometric Uncertainty (RU) of CrIS character-izes the accuracy of the observed radiance spectra. RUrepresents an upper limit of the bias with respect to the trueradiance for a large ensemble of observed spectra; it doesnot include effects such as detector noise which vary ran-domly from one spectrum to another. Additionally, theseRU estimates do not include data transfer and quality controlparameter related artifacts [Han et al., 2013, section 5.3],which are unrelated to the inherent accuracy of the CrISobservations and which can be removed with futurereprocessing efforts. This section compares the CrIS RU sen-sor specification to an estimate of the CrIS RU relevant toprelaunch thermal vacuum test conditions. In terms of sensorspecification, the CrIS RU is stated as a percent of 287 Kblackbody radiance with 1-sigma values of 0.45%, 0.58%,and 0.77% for the longwave, midwave, and shortwave bands,respectively. Converting to brightness temperature using thePlanck function for blackbody radiation, 3 sigma RU specifi-cations are shown in Figure 1. The 3 sigma specifications aregreater than 0.5 K in the shortwave band and greater than 1 Kat the longwave end of the longwave band. As shown hereand in section 4, both the prelaunch and on-orbit estimatesof the actual RU are approximately a factor of three timesbetter than specification.[7] Estimates of the prelaunch RU are computed using

a parametric perturbation of the radiometric calibrationalgorithm, using parameter uncertainties determined fromprelaunch characterization tests. RU estimates are compli-mentary to, but should be distinguished from, the majorityof postlaunch calibration/validation efforts that aim to esti-mate product uncertainties through comparison with correl-ative observations or calculations. For the purpose of thispaper, the CrIS radiometric calibration algorithm includestwo primary components: a radiometric nonlinearity correc-tion applied to the complex (uncalibrated) spectra followedby radiometric calibration of the resulting linear complexspectra using a responsivity and radiometric offset deter-mined from two calibration targets. During prelaunch ther-mal vacuum testing, the CrIS Internal Calibration Target(ICT) and an external Space Target (ST) were used to calibrateviews of an External Calibration Target (ECT). Both the ECTand ST are large, well-characterized high emissivity black-bodies designed to support CrIS thermal vacuum testing.Differences between predicted and calibrated ECT viewspectra are used to assess the overall radiometric calibrationof CrIS, and ECT view data collected over a range of ECTtemperatures are also used to determine nonlinearity.Following Revercomb et al. [1988], the equation for thecalibrated ECT view radiance spectra, RECT, is

RECT ¼ RICT � RSTð ÞRe C’ECT–C

’ST

� �= C’

ICT � C’ST

� �� þ RST

(1)

where RICT and RST are predicted radiance spectra for theICT and ST calibration views, and C′

ECT, C′ICT, and C′

ST arenonlinearity corrected versions of the ECT, ICT, and STview complex spectra, respectively. The radiometricnonlinearity occurs in the interferogram domain but for the

600 800 1000 1200 1400 1600 1800 2000 2200 2400 26000

0.2

0.4

0.6

0.8

1

1.2

wavenumber (cm−1)

BT

Dif

(K)

1−sigma3−sigma

Figure 1. The CrIS radiometric uncertainty (RU) specifica-tion, expressed as 1 sigma and 3 sigma brightness tempera-ture differences when viewing a 287 K blackbody scene.

TOBIN ET AL.: CRIS RADIOMETRIC CALIBRATION UNCERTAINTY

2

CrIS optical bandpasses and quadratic nature of thenonlinearity, the nonlinearity correction simplifies to:

C’ ¼ C 1þ 2 a2VDCð Þ (2)

where C is the measured (nonlinear) complex spectrum, a2 isthe detector/Field-Of-View (FOV) dependent quadraticnonlinearity coefficient, and VDC is the photon-induced DClevel voltage at the first stage of the detector preamplifierwhich varies for each interferogram [Knuteson et al., 2013].It should be noted that equations (1) and (2) are simplifiedversions of the calibration dealing only with the radiometriccontributions to the CrIS RU; spectral contributions areaddressed in Strow et al. [2013].[8] To verify the radiometric calibration of CrIS, ECT view

data were calibrated and assessed for a range of ECT set pointtemperatures: 200 K, 233 K, 260 K, 287 K, 299 K, and 310 K.The RU is also estimated for each of the calibrated ECT viewspectra. Table 1 lists the various calibration parameters andtheir uncertainties used to compute RU. These include the tem-peratures and emissivities of the ICT and ST used to computeRICT and RST and the a2 values used to perform thenonlinearity corrections. Each of the terms is discussed furtherbelow. Other potential contributions, such as stray light andpolarization effects are less significant due to the sensor design[Stumpf and Overbeck, 2002], and are not included here.[9] CrIS utilizes an ambient temperature sensor design

with the optical bench, interferometer, ICT, and the majorityof optical components at similar ambient temperatures. In theCrIS calibration algorithm, the predicted radiance whenviewing the ICT is computed using the ICT “environmentalmodel” [JPSS Configuration Management Office, 2012],which includes an emissive term as well as several reflectedterms due to the nonunit emissivity of the ICT.Furthermore, there are optical components of the reflectedterms that have representative temperature sensors and thosewhich require thermal modeling (the baffle of the SceneSelection Module, SSM), leading to a simplified yet repre-sentative expression for the ICT predicted radiance:

RICT ¼ εICT B T ICTð Þ þ 1� εICTð Þ ½ 0:5 B T ICT;Refl;Measured

� �

þ0:5 B T ICT;Refl;Modeled

� ��(3)

where B is the Planck function, εICT is the effective cavityemissivity of the ICT, TICT is the effective temperature ofthe ICT, and TICT, Refl, Measured and TICT, Refl, Modeled are theeffective temperatures of the reflected optical componentswhich have temperature sensors and those whose

temperatures require a thermal model. The 3 sigma uncer-tainty of TICT is 112.5 mK. This value was determined fromengineering estimates and characterization tests of the effec-tive temperature of the ICT taking into account the inherentuncertainties in the temperature sensors, and thermal andaging effects. The ICT emissivity, shown in Figure 2, wasmeasured using a special thermal vacuum test that providedincreased sensitivity to the ICT reflected components andfrom an independent test of the emissivity for one wave-length region in the shortwave band. The ICT emissivityhas values ranging from as low as 0.974 in the shortwaveband and at the shortwave end of the midwave band, to ashigh as 0.996 in the longwave window region. The 3 sigmauncertainty in the knowledge of εICT is 3%, or ~0.03 in effec-tive emissivity. Due to the ambient design of the CrIS sensor(e.g., that TICT, Refl is similar to TICT), this relatively highuncertainty in the ICT emissivity does not result in largeuncertainties in the calibrated spectra. The optical componentsthat have active temperature monitors included in the ICTreflected term include the frame, Optical MechanicalAssembly (OMA), interferometer beam-splitter, and ICT baffle.The 3 sigma uncertainty in TICT,Refl,Measured is conservativelyestimated as 1.5 K. The SSM baffle accounts for roughly halfof the solid angle of the ICT. Its temperature is not measured;a thermal model is used to predict the SSM baffle temperaturebased on its measured mount temperature, and this has anorbital variation with range of approximately 6 K. As a veryconservative estimate, the prelaunch 3 sigma uncertainty inTICT,Relf,Modeled is taken to be this full range, 6 K.[10] The predicted radiance for the ST involves the ST

effective temperature, emissivity, and reflected temperatures:

RST ¼ εSTB TSTð Þ þ 1� εSTð Þ B TST;Refl

� �(4)

where εST is the ST effective emissivity, TST is the effectiveST temperature, and TST,Refl is the temperature of opticaland structural components in view of the ST. The ST is alarge 5-bounce blackbody with effective emissivity of0.9995, with a 3 sigma uncertainty of 0.0009. The ST iscooled to ~105 K to serve as the cold calibration target duringprelaunch testing, and TST has a conservative 3 sigma uncer-tainty estimate of 6 K. Because the CrIS sensor is at ambienttemperature and views the ST, the reflected term contributesthe largest uncertainty to RST. The nominal value of TST,Refl istherefore taken to be the nominal, ambient temperature ofCrIS (e.g., 280 K) with a conservative 3 sigma uncertaintyof 9 K.[11] The detector nonlinearity corrections (equation (2))

require knowledge of the characterization parameters a2

Table 1. Prelaunch Calibration Parameters andUncertainty Estimates

ParameterNominalValues

1-sigmaUncertainty

3 sigmaUncertainty

TICT 280 K 37.5 mK 112.5 mKεICT 0.974–0.996 0.01 0.03TICT, Refl, measured 280 K 0.5 K 1.5 KTICT, Refl, modeled 280 K 2 K 6 KTST 105 K 2 K 6 KεST 0.9995 0.0003 0.0009TST, Reflected 280 K 3 K 9 Ka2, Longwave FOVs 0.01 to 0.02 V�1 9.6% 29%a2, Midwave FOVs 0.00 to 0.05 V�1 15.5% 47%

600 800 1000 1200 1400 1600 1800 2000 2200 2400 26000.95

0.96

0.97

0.98

0.99

1

wavenumber (cm−1)

emis

sivi

ty (

)

Figure 2. The ICT cavity emissivity.


3

and VDC for each detector. VDC is known well from telemetryobservation, and the primary uncertainty is in the determina-tion of the a2 values. Using prelaunch data, the a2 values aredetermined using two independent methods, and the differ-ences between the resulting a2 values are used to estimatesystematic uncertainties in a2. The first method involvesCrIS viewing the ECT over a range of ECT temperatures,with the a2 value for each detector determined empiricallyto create optimal agreement of calibrated radiance spectraamong the nine CrIS FOVs and with respect to the predictedECT view spectra. These a2 values, derived from groundTVAC characterization using a stepped temperature ECT,are referred to as a2

TVAC-ECT.[12] The effect of a quadratic nonlinearity in the interfero-

gram domain is to produce low-resolution artifacts that peakoutside the optical pass band that are proportional to thenonlinearity magnitude [e.g., Knuteson et al., 2004]. Thesecond method therefore involves the use of CrIS diagnosticmode (DM) interferogram data collections (bypassing thenormal onboard numerical filtering and decimation processwhich limits the band pass of the resulting spectra) and anal-ysis of the out-of-band harmonics to characterize the natureof the nonlinearity and estimate a2 for each detector. Thesevalues are referred to as a2

TVAC-DM. Figure 3 shows both setsof prelaunch a2 values, with the a2

TVAC-DM values derivedfrom DM views of the ST from the TVAC3 MissionNominal data set. There is relatively good agreementbetween the two independent methods of estimating a2.Taking the mean over FOVs, the structural uncertaintyderived from these independent methods leads to 3 sigma un-certainties of 29% for longwave FOV values and 47% formidwave FOV values. Figure 3 also shows that all longwaveFOVs have appreciable yet similar values of nonlinearity

correction (a2), while the midwave band FOVs have a largerrange of correction values ranging from the highly linearFOV 6 and FOV 9 to maximum nonlinearity for FOV 7.CrIS utilizes photovoltaic HgCdTe detectors in all threespectral bands [Masterjohn et al., 2003]. Subsequent investi-gation has identified that the set of nine midwave detectorswere cut from two different wafers. The same nonlinearityanalysis performed for the shortwave band detectors showsthat they are all highly linear. Therefore, the shortwave banda2 values are set to zero and the corresponding nonlinearityuncertainty is zero in this analysis.[13] Using equations (1) through (4) and the uncertainties

listed in Table 1, the prelaunch CrIS RU is shown as 3 sigmabrightness temperature uncertainties in Figures 4 and 5. Foreach calibration parameter, the calibration is perturbed bythe 3 sigma parameter uncertainty. The uncertainties arelargely independent of one another, and the total RU is com-puted as the root sum square (RSS) of the individual terms.Figure 4 shows the individual contributions to the RU budgetand the total RU for FOV 7 for calibrated views of the ECT at287 K. The leading uncertainty terms are the TICT, εICT, TICT,Refl,Modeled, and a2 terms. For blackbody view spectra, the un-certainties are generally smoothly varying with wave num-ber, while the TICT,Refl terms follow the signature of theICT emissivity versus wave number. Figure 5 shows theRU for all nine CrIS FOVs as a function of ECT brightnesstemperature for one representative spectral channel in eachof the three CrIS spectral bands. Two versions of the RUare shown. The top row in Figure 5 shows RU estimatesusing all terms in Table 1, where the ST is used in thermalvacuum test conditions along with the ICT to perform radio-metric calibration. The bottom row does not include the STuncertainty terms and represent the on-orbit case where

1 2 3 4 5 6 7 8 90

0.01

0.02

0.03

FOV #

a 2 (1

/V)

1 2 3 4 5 6 7 8 9

0

0.05

0.1

FOV #

a 2 (1

/V)

Figure 3. Comparison of prelaunch estimates of quadratic nonlinearity correction coefficients determinedfrom minimizing ECT view residuals for the TVAC3 Mission Nominal 260 K, 287 K, 299 K, and 310 Ktemperature plateaus (a2

TVAC-ECT, black bars), from analysis of prelaunch ST out-of-band harmonics indiagnostic mode data (a2

TVAC-DM, white bars), and on-orbit version 33 EP values (grey bars), for the(top) Longwave band FOVs and for the (bottom) Midwave band FOVs.


4

Deep Space (DS) views would be available for calibration.These results show that the ST terms introduce significantadditional uncertainty for the prelaunch test conditions, par-ticularly for cold scene temperatures and shorter wavelengths.However, for warmer scene temperatures, the estimatedprelaunch RU is considerably less than the CrIS specificationvalues shown in Figure 1. The spread in RU among the variousFOVs is due to FOV-dependent nonlinearity magnitudes, withmidwave FOV 7 having the largest magnitude and uncertaintyalong with FOV 9 in the longwave band. The shortwave banddetectors are linear, and the resulting RU estimates areindependent of FOV for that band.[14] Also shown in the top row of Figure 5 are 3 sigma

uncertainties in the ECT view predicted brightness tempera-tures as well as the absolute value of the predicted minuscalibrated brightness temperatures for each ECT temperature

set point and each FOV (“ECT residuals”). These ECTresiduals are used to verify the overall radiometric calibrationof CrIS, and the ECT residuals should therefore be boundedby the uncertainty of the ECT view predicted radiances andthe CrIS RU estimates. The ECT used in TVAC is a largefive-bounce specular blackbody. The ECT radiance uncer-tainty is computed using an ECT temperature uncertainty of89.1 mK 3 sigma, cavity emissivity of 0.9995, emissivity un-certainty of 0.0009 3 sigma, reflected temperature of 290 K,and reflected temperature uncertainty of 5 K 1 sigma. Dueto the contribution of the ECT reflected radiance from a warmexternal environment, the uncertainty in the predicted ECTview radiance becomes larger for the cold ECT temperatureset points and for shorter wavelengths. For all wavelengthsand FOVs, Figure 5 shows that the ECT residuals are smallerthan both the uncertainty of the predicted ECT views and theuncertainty in the CrIS calibrated spectra. In other words, theECT residuals are consistent with the ECT and calibratedCrIS uncertainty estimates.

3. Methodology for On-Orbit NonlinearityConfirmation and Refinement

[15] As discussed in the previous section, Figure 5 repre-sents an estimate of the radiometric uncertainty based onthe prelaunch estimates of uncertainties in the calibrationparameters and verification testing performed in a thermalvacuum chamber. If the assumption is made that the relevantcalibration parameter uncertainties have not changedpostlaunch, then the bottom row of Figure 5 (computedassuming a real view of Deep Space) represents the CrISon-orbit radiometric uncertainty for viewing a Planck spectrum.

500 1000 1500 2000 2500

0

0.05

0.1

0.15

0.2

wavenumber (cm−1)

3σ B

T R

U (

K)

Figure 4. Prelaunch RU contributions and total RU for cal-ibrated FOV 7 ECT view spectra, for the ECT temperature of287 K, as a function of wave number.

0

0.1

0.2

0.3

0.4

0.5

3σ B

T R

U (

K),

BT

Diff

(K

)

200 250 3000

0.1

0.2

0.3

0.4

0.5

BT (K)

3σ B

T R

U (

K)

200 250 300

BT (K)

200 250 300

BT (K)

Figure 5. Prelaunch RU (filled circles) as a function of ECT brightness temperature at (left column)900 cm�1, (middle column) 1500 cm�1, and (right column) 2350 cm�1. RU estimates are shown forcalibrations performed in (top row) the prelaunch thermal vacuum test environment using the SpaceTarget and also for (bottom row) the case where a deep space view is assumed to be available. For thethermal vacuum test case (Figure 5, top row), also shown is the 3 sigma uncertainty in the predictedECT view brightness temperatures (black curves) and the absolute value of the calibrated minus predictedECT view brightness temperatures (open squares).


5

This assumption is valid for all of the parameter uncertaintiesexcept for the nonlinearity coefficients. Repeated CrISprelaunch testing cycles demonstrated that the linearity of somedetectors can change upon detector warm-up prelaunch andsubsequent detector cool-down postlaunch. The exact cause ofthis effect is still under investigation, but the implication wasthat the nonlinearity of the longwave and midwave detectorswould have to be reevaluated in orbit.[16] This section describes the methodology used to

determine the on-orbit a2 parameters and estimate theiruncertainties. A remarkable outcome of this approach is theability to reduce the prelaunch RU of the most nonlineardetectors by tying these to reference detectors with smallernonlinearity, particularly for the midwave band FOVs. Atthe same time, because the largest source of radiometricdifferences among FOVs is due to the varying degrees ofnonlinearity, the nonlinearity coefficients have been adjustedto produce optimal radiometric agreement among FOVs.Ensuring radiometric uniformity of the nine CrIS FOVs isimportant for users of the data, e.g., data assimilation.[17] The methodology used to refine the on-orbit nonlinearity

parameters involves two steps. The first step provides an esti-mate of the potential change in nonlinearity from prelaunch toon-orbit, and involves the collection of on-orbit DM data forDS views and subsequent analysis of the out-of-bandharmonics. This is the same process used prelaunch to providethe a2 estimates using DM ST data discussed in section 2. Thefractional change in a2 from prelaunch to on-orbit is thereforeaccurately estimated from the ratio of these DM derivedon-orbit and prelaunch a2 values. The results suggest thatsome detectors, e.g., longwave FOV 9 and midwave FOV7, changed significantly while other detectors stayed closeto their prelaunch estimates. The longwave FOV 5 a2 valueis estimated to have changed approximately 6%, and thesechange estimates have an uncertainty of approximately 5%1 sigma. The on-orbit DM data are very useful because theyhave provided the ability to verify the quadratic nature ofthe nonlinearity while on-orbit, and also to verify that theshortwave band detectors are linear. Also, importantly, theyhave been used to verify that two of the midwave bandFOVs (6 and 9) have negligible nonlinearity on-orbit.[18] The second step for refining the on-orbit nonlinearity

correction involves the selection of a “reference FOV” foreach spectral band, followed by an Earth view FOV-to-FOV analysis in which adjustments to the a2 values of theremaining eight FOVs are made to create optimal agreementwith the reference FOV brightness temperature observations.

For the midwave band, FOV 9 is highly linear and is thereference FOV. In other words, it serves as a linear referencefor the other nonlinear midwave FOVs. Unlike the midwaveband, all longwave FOVs display similar levels ofnonlinearity. FOV 5 has the lowest nonlinearity and ischosen as the longwave reference FOV. The Earth viewFOV-to-FOV analysis approach makes use of the fact that,in a statistical sense, all nine FOVs observe the same Earthscene distributions (ignoring the small angular spread amongthe FOVs within the 3 × 3 array, 1.1 to 1.5°). Brightnesstemperature differences relative to the selected referenceFOV are computed for each FOV for a large set of Earthobservations for spectral regions which have high sensitivityto nonlinearity and also low spatial variability (typically highaltitude peaking channels). The data set is restricted to in-clude only the center four Fields-of-Regard (FORs) nearestthe nadir view to avoid artifacts due to atmospheric opacitydifferences for higher view angles. The data set is alsofiltered to only include FORs with low spatial variability(standard deviation of nine FOVs within the FOR less than1 K). The a2 values are then adjusted to minimize theobserved FOV-to-FOV brightness temperature differences.Resulting on-orbit a2 values are shown in Figure 3. A sampletime series of brightness temperature differences is shown inFigure 6 for spectral means of the 672–682 cm�1 longwaveregion and the 1585–1600 cm�1 midwave region, usingCrIS radiance products generated at IDPS. The abrupttransition in April 2012 is due to the upload of EngineeringPacket version 33 (EP 33) to replace the prelaunchnonlinearity parameters (EP 32) with those determinedpostlaunch in the early checkout period using Earth viewFOV-to-FOV analysis of a relatively small data sample.After upload of EP 33 the FOV-to-FOV agreement is greatlyimproved, yet further refinement of these parameters utilizinga larger data set is expected before CrIS reaches validated sta-tus. The time variations of the longwave band FOV-to-FOVdifferences (amplitude of ~0.015 K) are not yet understoodand under investigation. Note, however, that they are sub-stantially smaller than the overall uncertainty estimated forEarth view spectra at this wavelength region (see section 4).Furthermore, an adjustment to the longwave referenceFOV 5 a2 value is expected prior to reaching validated status.[19] The FOV-to-FOV brightness temperature differences

are shown to be Gaussian in nature, leading to remarkablysmall estimated uncertainties of 3 mK (3 sigma) in thelongwave band and 6 mK (3 sigma) in the midwave bandwhen using a month of FOV-to-FOV differences. These

Apr Jul Oct Jan Apr Jul

−0.2

−0.1

0

0.1

0.2

BT

Diff

(K

)Apr Jul Oct Jan Apr Jul

Figure 6. Daily mean FOV-to-FOV brightness temperature differences from April 2012 to May 2013 forspectral channels sensitive to detector nonlinearity in (left) the CrIS longwave band (672–682 cm�1) withrespect to reference FOV 5 and in (right) the midwave band (1585–1600 cm�1) with respect to referenceFOV 9.


6

brightness temperature uncertainties are then converted touncertainties in a2 using a2 Jacobians, dR/da2. The uncer-tainties in the final on-orbit a2 values therefore have contribu-tions from the prelaunch determination of a2 for the referenceFOV (in Table 1), the change from prelaunch to on-orbit forthe reference FOV estimated from Diagnostic Mode data(15% 3 sigma), and the FOV-to-FOV adjustments based onEarth view analysis. Since the FOV-to-FOV analysis createsoptimal agreement with the reference FOV, the a2 uncer-tainty contributions are combined in units of a2 rather thanpercent. The on-orbit 3 sigma uncertainties of the quadraticnonlinearity parameter are listed in Table 2 for each detectorin the longwave and midwave focal planes. For both spectralbands, the uncertainty in the Earth view FOV-to-FOV adjust-ments are relatively small and the total uncertainties arelargely dependent on the uncertainty of the reference FOV.For the midwave band, this results in small uncertainties inunits of a2 for all FOVs due to the excellent inherent linearityof reference FOV9, yet large percentage uncertainties forFOVs when the a2 value is small. For the longwave band,all FOVs have similar a2 values and the final uncertaintiesare approximately equal to the FOV 5 uncertainty in termsof both percent and in units of a2.[20] To illustrate the impact of these reduced a2 uncer-

tainties, RU estimates computed for ECT views using theseuncertainties are shown in Figure 7. These are computed as-suming that a DS view is available, and can be compared di-rectly to the RU estimates shown in the bottom row ofFigure 5. The primary impact of the on-orbit a2 adjustmentsis to remove the majority of the FOV dependence of the esti-mated RU. Additionally, the midwave RU is reduced to besimilar to that predicted for the linear shortwave band dueto the high linearity of midwave reference FOV 9, whilethe longwave band RU for all FOVs remains slightly ele-vated with respect to the midwave and shortwave bands.

4. On-Orbit Radiometric Uncertaintyfor Earth Spectra

[21] On-orbit RU estimates for Earth view spectra arecomputed using the same approach as described in section2 for prelaunch conditions. However, as opposed toprelaunch blackbody spectra and prelaunch parameteruncertainties, the on-orbit RU estimates are shown here forrepresentative Earth view spectra using on-orbit parameteruncertainties. The on-orbit calibration uses a DS view with unitemissivity rather than a less perfect ST in TVAC. Thus, the un-certainty of the on-orbit nonlinearity parameters differs from theprelaunch uncertainties, with on-orbit uncertainties described insection 3 and given in Table 2. Additionally, postlaunch valida-tion efforts have verified that the ICT environmental model doesnot introduce significant artifacts (either in terms of the shape ofthe ICT reflectivity or in orbital variations), and the uncertaintyof TICT,Refl,Modeled is reduced to 3 K (3 sigma) for these on-orbitRU estimates. This allows CrIS to produce very low RU fromits ICT even though its emissivity is less than perfect.[22] Given the on-orbit uncertainties contained in Tables 1

and 2, the RU of an Earth scene can be computed. Figures 8and 9 show 3 sigma RU estimates for representative warm(nominally clear sky) and cold (high thick cloud) Earth viewFOV 9 spectra collected on 24 February 2012. Overall, theRU is less than 0.2 K in the midwave and shortwave bands,and less than 0.3 K in the longwave band. In both cases,and as with the prelaunch estimates, the uncertainty in theICT temperature is a leading contributor. For Earth scenes,the nonlinearity corrections and resulting RU contributionsare dependent on the spectrally integrated signal of the com-plex spectra, as well as the spectral shape of the Earth viewspectra, and thus can vary significantly from one spectrumto another. For typical warm scene spectra, the longwaveband nonlinearity corrections and associated uncertainties

Table 2. 3 Sigma Uncertainties in On-Orbit a2 Values, Given in Units of a2 and Percent

FOV1 FOV2 FOV3 FOV4 FOV5 FOV6 FOV7 FOV8 FOV9

LW (V�1) 0.00403 0.00403 0.00403 0.00403 0.00403 0.00403 0.00403 0.00403 0.00403LW (%) 23 30 26 20 32 24 29 32 18MW (V�1) 0.00154 0.00160 0.00157 0.00162 0.00162 0.00168 0.00162 0.00161 0.00128MW (%) 26 11 6 15 13 54 4 6 49

200 250 3000

0.1

0.2

0.3

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0.5

BT (K)

3σ B

T R

U (

K)

200 250 300

BT (K)200 250 300

BT (K)

FOV1FOV2FOV3FOV4FOV5FOV6FOV7FOV8FOV9

Figure 7. RU as a function of ECT brightness temperature at (left) 900 cm�1, (middle) 1500 cm�1, and(right) 2350 cm�1. RU estimates are shown for calibrations performed in the prelaunch thermal vacuum testenvironment, but for the case where a deep space view is assumed to be available and using the on-orbit a2uncertainties in Table 2.


7

are small in the longwave window region and larger in themore opaque CO2 absorption region. For the example coldscene RU estimate, the Earth view spectrum is more similarto a blackbody and the resulting RU contribution is relativelyflat versus wave number with ~0.1 K contribution throughoutthe opaque and window regions of the longwave band. Theon-orbit nonlinearity contributions to the RU in the midwave

band are very small. Additionally, due to efforts discussed insection 3, there is little FOV-to-FOV variability in the Earthscene RU estimates. Finally, to capture a larger range ofEarth scene radiances, RU for an orbit of data on 24February 2012 is shown in Figure 10. The distributions in-clude RU for all spectral channels and FOVs. The largestRU values observed in the longwave band correspond to 14

200

220

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300

BT

(K

)

700 800 900 1000

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gma

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)

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RU

(K

)

wavenumber700 800 900 1000

1200 1300 1400 1500 1600 1700

wavenumber

200 220 240 260 280 300BT (K)

wavenumber1300 1400 1500 1600 1700

2200 2300 2400 2500

wavenumber

200 220 240 260 280 300BT (K)

wavenumber2200 2300 2400 2500

Figure 8. On-orbit RU estimates for a typical warm Earth view spectrum collected on 24 February 2013.(top row) The observed spectra in the longwave, midwave, and shortwave bands. (middle row) The variouscontributions to and the total RU for each band. (bottom row) The scene brightness temperature depen-dence of the RU color coded by wave number. The legend for Figure 8 (middle row) is the same as thatfor Figure 3.

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)

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)

wavenumber700 800 900 1000

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wavenumber1300 1400 1500 1600 1700

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wavenumber2200 2300 2400 2500

Figure 9. On-orbit RU estimates for a cold Earth view spectrum collected on 24 February 2013. Sameformat as Figure 7.


8

μm channels for nominally clear sky scenes such as thatshown in Figure 8 but with warmer surface temperatures.

5. Example Postlaunch RadianceValidation Results

[23] RU estimates presented in section 4 based on calibrationparameter uncertainty estimates suggest an overall on-orbit RUof less than 0.2 to 0.3 K 3 sigma. Various postlaunch efforts areunderway to independently assess the radiometric accuracy andstability of CrIS, as well as the spectral calibration, noise perfor-mance, and geolocation accuracy. The radiometric assessmentsinclude a variety of approaches including, for example, compar-isons with other satellite sensors and with clear sky calculatedspectra [e.g., Tremblay et al., 2012; Han et al., 2013] andunderflights by high altitude aircraft [e.g., Larar et al., 2011;Taylor et al., 2013]. While these validation efforts are ongoing,preliminary results are generally consistent with the on-orbit RUestimates, with observed biases on the order of a few tenths ofK, stable with time, and small FOV-to-FOV differences.

Future publications will present the postlaunch validationfindings in greater detail, including differences presented as afunction of scan angle, scene brightness temperature, and orbitalphase, for example. Some example results are presented here.[24] Following the methodology of Strow et al. [2006],

comparisons of clear sky observed and calculated spectraare shown in Figure 11. The ensemble includes tropical(�30 to +30 degree latitude) ocean nighttime spectracollected between April 2012 and April 2013. The determi-nation of clear scenes is also described in Strow et al.[2006, section 3.2], with only a small percent (1%) of thenighttime ocean scenes accepted. The calculations areperformed using SARTA [Strow et al., 2003] developed forCrIS with ECMWF 3 h analysis/forecast fields used forocean surface temperature and atmospheric state profiles.The observed biases are similar to biases computed forIASI and AIRS [e.g., Strow et al., 2006, Figure 9]. This in-cludes the largest observed residual at 2380 cm�1; thesechannels have peak sensitivity to atmospheric temperature

BT (K)

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gma

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(K

)

200 250 3000

0.1

0.2

0.3

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log(count)0 5 10

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200 250 300

Figure 10. Log scale distributions of 3 sigma RU for one orbit of CrIS Earth view data for the (right)longwave, (middle) midwave, and (left) shortwave spectral bands. The distributions include values fromall FOVs and all spectral channels within the band.

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)

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−1

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Obs

−C

alc(

K)

wavenumber (cm−1)

Figure 11. (top) Mean observed brightness temperature spectrum and (bottom) biases with respect toclear sky calculated spectra for tropical (±30° latitude) ocean nighttime spectra. The biases includeHamming spectral apodization.


9

around 25 mbar, but with an unusual bimodel shape with asecondary peak near 4 mbar which gives it unique sensitivityto the ECMWF profile shape. Given the uncertainties in thecalculated spectra, the observed minus calculated residualsare reasonable and not inconsistent with the CrIS RU esti-mates that are under 0.3 K everywhere.

[25] Utilizing simultaneous nadir overpasses (SNOs) andintercomparison techniques described in Tobin et al.[2013], example comparisons of CrIS and METOP-A IASIand CrIS and AIRS are shown in Figures 12 and 13. To as-sess the FOV dependence of the CrIS calibration, IASI minusCrIS spectra for northern hemisphere SNOs are shown for

−0.4

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) FOV 2 FOV 3

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) FOV 5 FOV 6

1000 1500 2000 2500

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IAS

I−C

rIS

(K

)

1000 1500 2000 2500

FOV 8

wavenumber (cm−1)1000 1500 2000 2500

FOV 9

wavenumber (cm−1)

Figure 12. CrIS FOV dependence of IASI-CrIS brightness temperature differences for Northern hemi-sphere SNOs using IDPS CrIS products produced using EP 32 (red, prior to 12 April 2012) and usingEP 33 (black, after 13 April 2012). The green curves are 1 sigma uncertainties in the EP 33 differences.

−0.5

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AIR

S −

CrI

S (

K)

672 − 682 cm−1

−0.051 +/−0.001 K

Apr Jul Oct Jan Apr

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AIR

S−

CrI

S (

K)

830 − 840 cm−1

0.033 +/−0.002 K

1382− 1408 cm−1 −0.095 +/−0.001 K

Apr Jul Oct Jan Apr

1585 − 1600 cm−1

−0.098 +/−0.002 K

2360 − 2370 cm−1 −0.002 +/−0.002 K

Apr Jul Oct Jan Apr

2500 − 2520 cm−1

−0.093 +/−0.003 K

Figure 13. Time series of daily mean AIRS-CrIS brightness temperature differences for representativewave number regions in each of the CrIS spectral bands, from March 2012 to April 2013. The mean andstandard error of the daily mean differences using data after the EP 33 upload in April 2012 are listed foreach wave number region.


10

each CrIS FOV in Figure 12, with the mean IASI-CrISdifference removed. Differences are shown for IDPS CrISproducts using the prelaunch EP 32 and on-orbit EP 33nonlinearity parameters. The results show significantimprovement using the on-orbit adjusted nonlinearity para-meters described in section 3 and are consistent with reducedFOV dependence of the predicted on-orbit RU presented insection 4. EOS Aqua and Suomi-NPP are in similar orbits,resulting in frequent SNOs covering a wide range ofobserved spectra. Figure 13 shows time series of daily meanAIRS minus CrIS brightness temperature differences forspectral regions with sensitivity to various CrIS calibrationparameters. Due to the imprecise methodology for normaliz-ing the spectral response functions of CrIS and AIRS L1Bspectra, the comparisons are shown for ~10 wave numberaverages; this averaging produces a more meaningful assess-ment of the radiometric differences between CrIS and AIRS.The 677, 1395, and 1592 cm�1 regions have sensitivity toCrIS nonlinearity and the discontinuities in April 2012 aredue to the operational processing change from EP 32 to EP33 as discussed in section 3. Otherwise, the differences arewell within the estimated RU of CrIS and stable with time.[26] The current on-orbit RU estimates do not include

several other effects currently under study. These includespectral ringing artifacts for unapodized spectra, potentialcalibration artifacts in opaque regions of the shortwave band,and differences with other on-orbit sensors observed for coldscene temperatures in some spectral regions [Han et al.,2013, section 5.4], as well as a potential adjustment to thelongwave reference FOV 5 a2 value based on reanalysis ofthe thermal vacuum test data. Pending further diagnoses ofthe validation analyses and determination of the root causeof the differences, the on-orbit RU estimates will be assessedand refined as needed.

6. Summary

[27] This paper has described the uncertainty in the radio-metric calibration of CrIS based on prelaunch and on-orbitefforts to estimate calibration parameter uncertainties, andprovided example results of postlaunch validation efforts toassess the predicted uncertainty. RU characterization isimportant for weather, climate, and intercalibration applica-tions of the data. Prelaunch RU estimates computed for thelaboratory test environment utilizing ST and ICT views forcalibration are less than ~0.2 K 3 sigma for blackbody scenetemperatures above 250 K, with primary uncertainty contri-butions from the ICT temperature, ICT reflected radianceterms, and detector nonlinearity correction parameters.Significant FOV-to-FOV variability in the longwave andmidwave band prelaunch RU is due to prelaunch uncertaintyin nonlinearity contributions. A methodology for on-orbitadjustment of detector nonlinearity correction parameters,utilizing Diagnostic Mode data of Deep Space and Earthview data, results in reducing the overall nonlinearity contri-bution to the RU. In addition, this methodology reducesFOV-to-FOV calibration differences better than can beachieved with ground test methods. The resulting CrIS on-orbitRU estimates, shown in section 4 for representative warm andcold scene Earth view spectra, are less than 0.2 K 3 sigma inthe midwave and shortwave bands, and less than 0.3 K 3 sigmain the longwave band. Postlaunch validation efforts to assess the

radiometric calibration of CrIS are underway; validation resultsto date indicate that the on-orbit RU estimates presented here arerepresentative. IDPS CrIS radiance products are expected toreach Validated status in early 2014. Pending additionalfindings from ongoing validation analyses in this time frame,refinements to the CrIS radiometric calibration parameters andassociated RU estimates will be investigated. However, it isalready clear that the high accuracy of CrIS makes it an excep-tional asset for weather applications, and with final refinementsof calibration coefficients and associated data reprocessingefforts, also for climate applications.

[28] Acknowledgments. This research was supported by the NOAAJoint Polar Satellite System Office under grant NA10NES4400013, by theformer Integrated Program Office, and by NASA Suomi-NPP ScienceTeam grant NNX11AK21G. The authors would like to extend their thanksto the NASA Atmospheres Product Evaluation and Analysis ToolsElements and Community Satellite Processing Package teams at theUniversity of Wisconsin-Madison for various data access and data process-ing efforts that contributed to results presented here. IASI L1C data andIDPS generated CrIS data were obtained from NOAA’s ComprehensiveLarge Array-data Stewardship System, and AIRS L1B data were obtainedfrom the Goddard Earth Sciences Data and Information Services Center.

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