IASI Spectral Radiance Performance Validation

Atmos. Chem. Phys. Discuss., 9, 10193–10234, 2009 Atmospheric www.atmos-chem-phys-discuss.net/9/10193/2009/ Chemistry ACPD © Author(s) 2009. This work is distributed under and Physics 9, 10193–10234, 2009 the Creative Commons Attribution 3.0 License. Discussions

This discussion paper is/has been under review for the journal Atmospheric Chemistry IASI spectral and Physics (ACP). Please refer to the corresponding ﬁnal paper in ACP if available. radiance performance validation IASI spectral radiance performance A. M. Larar et al. validation: case study assessment from Title Page the JAIVEx ﬁeld campaign Abstract Introduction

A. M. Larar1, W. L. Smith2,3, D. K. Zhou1, X. Liu1, H. Revercomb3, J. P. Taylor4, Conclusions References 4 5 S. M. Newman , and P. Schlussel¨ Tables Figures 1NASA Langley Research Center, Hampton, VA, USA 2Hampton University, Hampton, VA, USA J I 3University of Wisconsin-Madison, Madison, WI, USA J I 4Met Oﬃce, Exeter, Devon, UK 5 EUMETSAT, Darmstadt, Germany Back Close

Received: 26 February 2009 – Accepted: 7 April 2009 – Published: 23 April 2009 Full Screen / Esc Correspondence to: A. M. Larar ([email protected]) Published by Copernicus Publications on behalf of the European Geosciences Union. Printer-friendly Version

Interactive Discussion

10193 Abstract ACPD Advanced satellite sensors are tasked with improving global-scale measurements of the Earth’s atmosphere, clouds, and surface to enable enhancements in weather pre- 9, 10193–10234, 2009 diction, climate monitoring, and environmental change detection. Measurement sys- 5 tem validation is crucial to achieving this goal and maximizing research and operational IASI spectral utility of resultant data. Field campaigns employing satellite under-ﬂights with well- radiance calibrated Fourier Transform Spectrometer (FTS) sensors aboard high-altitude aircraft performance are an essential part of this validation task. The National Polar-orbiting Operational validation Environmental Satellite System (NPOESS) Airborne Sounder Testbed-Interferometer 10 (NAST-I) has been a fundamental contributor in this area by providing coincident high A. M. Larar et al. spectral and spatial resolution observations of infrared spectral radiances along with independently-retrieved geophysical products for comparison with like products from satellite sensors being validated. This manuscript focuses on validating infrared spec- Title Page

tral radiance from the Infrared Atmospheric Sounding Interferometer (IASI) through a Abstract Introduction 15 case study analysis using data obtained during the recent Joint Airborne IASI Validation Experiment (JAIVEx) ﬁeld campaign. Emphasis is placed upon the beneﬁts achievable Conclusions References from employing airborne interferometers such as the NAST-I since, in addition to IASI Tables Figures radiance calibration performance assessments, cross-validation with other advanced sounders such as the AQUA Atmospheric InfraRed Sounder (AIRS) is enabled. J I

J I 20 1 Introduction Back Close The performance of post-launch validation activities is crucial to verify the quality of satellite measurement systems. It is essential to address all components of the mea- Full Screen / Esc surement system, i.e., sensors, algorithms, along with direct and derived data products, and continue such activities throughout program life to enable long-term monitoring of Printer-friendly Version 25 system performance for ensuring maximum research and operational utility of resultant data. Field experiment campaigns employing satellite under-flights with well-calibrated Interactive Discussion 10194 Fourier Transform Spectrometer (FTS) sensors aboard high-altitude aircraft are an essential part of this validation task. Specifically, airborne FTS systems can enable an ACPD independent, International System of Units (SI) traceable measurement system vali- 9, 10193–10234, 2009 dation by directly measuring the same level-1 parameters spatially and temporally co- 5 incident with the satellite sensor of interest. Continuation of aircraft under-flights for multiple satellites during multiple field campaigns enables long-term monitoring of sys- IASI spectral tem performance and inter-satellite cross-validation. Data from campaign under-flights radiance with airborne FTS systems, such as the National Polar-orbiting Operational Environ- performance mental Satellite System (NPOESS) Airborne Sounder Testbed- Interferometer (NAST- validation 10 I) (Cousins et al., 1997; Smith et al., 1999), have proven to be very useful in earlier Atmospheric InfraRed Sounder (AIRS) (Aumann et al., 2003; Pagano et al., 2003) and A. M. Larar et al. Infrared Atmospheric Sounding Interferometer (IASI) (Blumstein et al., 2004) validation studies (Larar et al., 2003, 2005, 2008a, 2008b; Newman et al., 2009; Tobin et Title Page al., 2006; Zhou et al., 2007a). NAST-I, maintained and deployed internationally by 15 NASA Langley Research Center (LaRC), serves as an ideal validation sensor since it Abstract Introduction measures the same level-1 quantity as many sensors it helps to validate (i.e. infrared spectral radiance), and does so at higher spectral and spatial resolutions. LaRC analy- Conclusions References

sis is further benefited from implementing an independent set of algorithms associated Tables Figures with, e.g., fast radiative transfer modeling and geophysical product retrievals to en- 20 able an independent, concurrent validation of derived level-2 products (Liu et al., 2007; J I Zhou et al., 2007a). Field campaign data from coincident measurement assets (i.e., ground, balloon, aircraft, and satellite) are then available for not only the implemen- J I tation and improvement of validation methodologies but, also, to implement, validate, Back Close and improve radiative transfer and retrieval algorithms and future measurement sys- 25 tem specifications (e.g., Carissimo et al., 2006; Grieco et al., 2007; Strow et al., 2006, Full Screen / Esc 2008; Liu et al., 2009; Serio et al., 2009; Taylor et al., 2008; Zhou et al., 2009). This manuscript focuses on validating infrared spectral radiance from the IASI instrument Printer-friendly Version through a case study analysis using data obtained during the recent Joint Airborne IASI Validation Experiment (JAIVEx) field campaign. Emphasis is placed upon the Interactive Discussion

10195 benefits achievable from employing airborne interferometers such as the NAST-I for not only IASI radiance calibration performance assessment but, also, cross-validation ACPD with other advanced sounders such as the AQUA AIRS. Cross-validation is important 9, 10193–10234, 2009 for referencing new observations to earlier-validated and accepted measurement as- 5 sets to ensure high-quality dataset time series continuity. An overview of the JAIVEx field campaign, case study day, and instrument systems utilized for this analysis is first IASI spectral given. The validation methodology implemented and approach followed for assessing radiance and inter-comparing infrared spectral radiance are then discussed. Results are then performance presented, followed by a summary and conclusions section. Separate papers within validation 10 this IASI Special Issue publication address details of validation for derived geophysical products along with retrieval and radiative transfer models (Zhou et al., 2009; Liu et al., A. M. Larar et al. 2009).

Title Page 2 JAIVEx ﬁeld campaign and case study day Abstract Introduction

The JAIVEx was a United States/European collaboration focusing on validation Conclusions References 15 of radiance and geophysical products from the MetOp-A (IASI/AMSU) and AQUA (AIRS/AMSU) sensors. Although all measurements on the MetOp-A and A-train satel- Tables Figures lites were of interest, the focus of JAIVEx (Smith et al., 2008) was on the validation of radiance and geophysical products from the IASI, including inter-comparisons with sim- J I ilar products from the AIRS. IASI, launched 19 October, 2006 on MetOp-A, is the first J I 20 of the advanced ultra-spectral resolution temperature, humidity, and trace gas sounding instruments to be flown on the Joint Polar System (JPS) of NPOESS and MetOp Back Close operational satellites for the purpose of improved weather, climate, and air quality observation and forecasting (Chalon, 2001). The field phase of JAIVEx was conducted Full Screen / Esc out of the NASA Johnson Space Center Ellington Field (EFD) in Houston, TX, between Printer-friendly Version 25 14 April–4 May, 2007. The NASA WB-57 high-altitude aircraft and UK Facility for Air- borne Atmospheric Measurements (FAAM) BAe146-301 aircraft (Taylor et al., 2008), Interactive Discussion well-instrumented with remote and in-situ sensors, flew coordinated sorties over the 10196 Department of Energy (DOE) Atmospheric Radiation Measurements (ARM) Cloud And Radiation Testbed (CART) site and Gulf of Mexico region during MetOp-A and A-train ACPD overpasses. 9, 10193–10234, 2009 2.1 Case study flight day IASI spectral 5 Data from the 29 April 2007 JAIVEx flight day will be utilized for all analysis presented radiance within this manuscript. The flight mission objective that day was to coordinate the performance WB-57 and BAe-146 aircraft for under-flight of the MetOp (15:50 GMT) and AQUA validation (19:19 GMT) satellites over the northern Gulf of Mexico. Figure 1 illustrates this flight sortie with the GOES imager scenes shown for (a) infrared, (b) visible, and (c) wa- A. M. Larar et al. 10 ter vapor band extended scenes as observed by GOES (16:02 GMT), and (d) depicts the flight profile executed by the WB-57. The WB-57 flew a north-south-oriented oval racetrack pattern (at 17 km) in between satellite overpass events, while the BAe-146 Title Page characterized the atmosphere and surface, from a range of altitudes below the WB- Abstract Introduction 57. The WB-57 arrived on-station 20 min prior to MetOp, and remained until 10 s after 15 AQUA (for a 3 h and 50 min on-station duration). Conditions ranged from very clear on Conclusions References the northern part of the race track, to low, puffy cumulus sparsely populating the south- ern extent of the flight profile, with a north-south water vapor gradient, as is shown in Tables Figures the GOES images of Fig. 1a–c. Figure 2 shows the sub-satellite tracks for Metop (IASI) and AQUA (AIRS) in (a) and (b), while the NAST-I nadir track is shown within the IASI J I 20 imager and MODIS scenes in (c) and (d), respectively. J I

2.2 Instrument systems utilized in case study analysis Back Close

Data from several different remote sensors were incorporated into this analysis; most Full Screen / Esc importantly, the high spectral resolution infrared systems under direct comparison include the airborne NAST-I and Scanning High-resolution Interferometer Sounder (S- Printer-friendly Version 25 HIS) FTS systems, along with the satellite-based AIRS discrete-channel grating spectrometer, and the IASI FTS. The NAST-Interferometer, NAST-I (Cousins et al., 1997; Interactive Discussion 10197 Gazarik et al., 1998; Prutzer et al., 1998), high spectral resolution (0.25 cm−1) data are collected over the 3.7–15.5 micron spectral range, using a step and stare scan- ACPD ◦ ning mirror to obtain ±48.4 cross-range coverage with thirteen atmospheric scene 9, 10193–10234, 2009 views. The instrument’s instantaneous field of view (IFOV) translates into a 0.13 km 5 ground footprint at nadir for each 1.0 km of aircraft altitude (i.e. 2.2 km footprint from a 17 km WB-57 altitude). The S-HIS, developed and implemented by the University IASI spectral of Wisconsin-Madison Space Science Engineering Center (SSEC), measures emit- radiance ted thermal radiation at high spectral resolution between 3.3 and 18 microns, with performance 1.5 km resolution (at nadir) across a 30 km ground swath from a nominal flight alti- validation 10 tude of 15 km (Revercomb et al., 1998, 2003). AIRS (Aumann et al., 2003; Pagano A. M. Larar et al. et al., 2003) is a high spectral resolution grating spectrometer with 2378 bands in the thermal infrared between 3.7–15.4 µm that is operational aboard the NASA EOS

AQUA satellite (Chahine et al., 2006). In the cross-track direction, a ±49.5 degree Title Page swath centered on the nadir is scanned. Each scan line contains 90 IR footprints, 15 with a resolution of 13.5 km at nadir and 41 km×21.4 km at the scan extremes from Abstract Introduction the nominal 705.3 km orbit. IASI is a Fourier Transform Spectrometer (Blumstein et Conclusions References al., 2004; Simeoni, 2007) observing the 3.7–15.5 µm spectral range with a spec- −1 tral sampling interval of 0.25 cm , while its scan mirror provides a spatial swath of Tables Figures ±48.3 degrees perpendicular to the satellite track. For each scan position, the instru-

20 ment views about 3.3 degrees×3.3 degrees, or 50 km×50 km at nadir, with a 2×2 ar- J I ray of detectors to yield a 12 km nadir footprint per IFOV pixel. Broadband comparisons are also included using imager data from the MODIS sensor on AQUA and the J I

IASI infrared imager on Metop-A. The Moderate Resolution Imaging Spectroradiome- Back Close ter (MODIS) is a broadband imaging sensor that provides high radiometric sensitivity 25 in 36 spectral bands ranging in wavelength from 0.4 µm to 14.4 µm, with a nominal Full Screen / Esc band-dependent nadir resolution less than or equal to 1 km (Xiong and Barnes, 2006; http://modis.gsfc.nasa.gov/about/design.php). The IASI instrument includes a built-in Printer-friendly Version imager, the IASI infrared imager, to enable accurate collocation between IASI and other Metop sensors as well as to provide sub-IASI-pixel cloud information. The imager cov- Interactive Discussion 10198 ers the IASI ﬁeld-of-view with 64×64 pixels providing sub-kilometer spatial resolution at nadir and has a single channel in the infrared over the 10.3 to 12.5 micron region ACPD (Blumstein et al., 2004; http://smsc.cnes.fr/IASI/GP instrument.htm). 9, 10193–10234, 2009

3 Validation methodology and assessment approach IASI spectral radiance 5 The airborne-field-campaign-centric calibration/validation (Cal/Val) strategy employed performance by the LaRC NAST-I team is illustrated in Fig. 3. While focused about high-resolution validation infrared FTS measurements (i.e., NAST-I), the strategy infuses other remote and in- situ sensors on same and different aircraft, data from other sensors on same and A. M. Larar et al. different spacecraft, data from ground-sites (e.g., DOE ARM CART), and geophysi- 10 cal model fields (e.g., Numerical Weather Prediction, NWP). NAST-I is typically flown jointly with the S-HIS. This provides redundancy for the critical infrared spectral radi- Title Page ance measurement, helps characterize intra-platform uncertainties amongst the airborne interferometers, and enables a better linkage to reference calibration standards; Abstract Introduction

the UW SSEC has done extensive calibration testing of both NAST-I and S-HIS with Conclusions References 15 blackbody sources having SI traceability to the National Institute of Standards and Technology (NIST) (Best et al., 2003; Revercomb et al., 2006). Analysis is further Tables Figures benefited from the independent set of algorithms employed by LaRC associated with, e.g., fast radiative transfer modeling and geophysical product retrievals, to enable an J I independent assessment of derived level-2 products. This approach enables indepen- J I 20 dent (SI-traceable) measurement system validation, and enables long-term monitoring and inter-satellite cross-validation of measurement systems by underflight of multiple Back Close satellites during multiple field campaigns. Spectral radiance validation, i.e. Cal/Val of sensor and level-1 algorithms, is a fun- Full Screen / Esc damental first-step prior to assessing derived geophysical parameter quality. Space Printer-friendly Version 25 and time co-location is critical for this task when the scenes being inter-compared contain significant non-uniformities. Radiosondes are frequently used for point reference Interactive Discussion comparisons and to provide statistics from the usage of large sample sizes. How- 10199 ever, besides of radiosonde dry-bias issues at upper altitudes, they cannot provide a “coincident” measurement due to the ascent time (1–2 h) and associated horizontal dis- ACPD placement (which can be >50 km). Lidar observations are much improved for accuracy 9, 10193–10234, 2009 and instant-time sampling, but these can only provide point measurements and still 5 introduce forward modeling errors when producing “upwelling radiance”. Airborne assets provide the only means for directly comparing radiance, providing the best match IASI spectral to spacecraft data, and can be implemented anywhere unlike fixed ground sites. radiance The objective of the analysis herein is to infuse multiple spatially- and temporally- performance coincident data sources from several independent sensors and simulations for enabling validation 10 inter-comparison and assessment of high-resolution infrared spectral radiance measurements from IASI and the other coincident sensors. Simulated observations are A. M. Larar et al. based upon line-by-line (LBL)-based radiative transfer model (LBLRTM) (Clough et al., 2005) calculations using the best available estimate of surface and atmospheric state. Title Page Airborne FTS sensors, such as the NAST-I, serve as ideal validation sensors due to 15 their higher spatial and spectral resolution (same-scene) measurements which can Abstract Introduction then be degraded to best emulate that observed by the coincident satellite sensors. Conclusions References 3.1 Analysis approach Tables Figures The goal of this case study is to assess IASI spectral radiances standalone and relative to AIRS. Methods employed herein to address this include comparisons of measured J I 20 IASI radiances with simulations and other measurements. Simulations presented J I use the best available estimate for atmospheric state (from, e.g., NWP model fields, radiosondes, or independent retrievals). Other measurements used in the compar- Back Close isons fit within two basic categories: those on the same platform (i.e., intra-platform) Full Screen / Esc and comparison of measurements from different platforms (i.e., inter-platform). Since 25 the airborne interferometer measurements provide the best characterization of scene evolution (as will be shown in the Inter-comparison Results section of this manuscript) Printer-friendly Version these data will also be used as a calibration reference standard to remove scene Interactive Discussion evolution for a more-representative IASI versus AIRS comparison. This approach can 10200 be summarized as follows: ACPD 1. Comparisons with simulations. Spectral radiances from select IASI IFOVs 9, 10193–10234, 2009 are first compared with line-by-line radiative transfer model simulations using esti- 5 mates of atmospheric state derived from NWP model fields (i.e. European Center for Medium-range Weather Forecasting, ECMWF, Gibson et al., 1997), local radiosonde IASI spectral observations, and independently-derived retrievals (Zhou et al., 2002, 2005, 2007b). radiance performance 2. Intra-platform comparisons. Radiance measurements from each available validation 10 platform are compared with consistent measurements from the same platform. This consists of comparing the following spectrally- and spatially-consistent observations: A. M. Larar et al. IASI versus IASI imager (on MetOP-A), AIRS versus MODIS (on AQUA), and NAST-I versus S-HIS (on WB-57). This enables a platform self-consistency verification Title Page while having large sample size comparisons with negligible collocation and viewing 15 geometry errors (i.e., temporal, spatial, angular, and platform altitude). Abstract Introduction

3. Inter-platform comparisons. High spectral resolution radiance measurements Conclusions References

are compared with like observations from a diﬀerent platform. This enables comparing Tables Figures new sensors, such as IASI, to known, previously-validated assets (such as NAST-I, 20 S-HIS, and AIRS). For scene observations that are not temporally-coincident, a ref- J I erence calibration standard is desirable to account for scene evolution. The following inter-platform comparisons are included: J I

a) Direct IASI vs. AIRS comparisons. As a ﬁrst-order comparison, spatially- Back Close coincident latitudinal cross-sections from IASI are compared with similar obser- Full Screen / Esc 25 vations from AIRS.

b) Aircraft vs. spacecraft. NAST-I spectral radiances are compared with spatially- Printer-friendly Version and temporally-coincident observations from both IASI and AIRS. Interactive Discussion c) Indirect IASI vs. AIRS comparisons. Since NAST-I observes the scene evolution 10201 between the Metop-A and AQUA overpasses during the case study JAIVEx ﬂight day, these observations are used as a calibration reference standard to remove ACPD scene evolution and enable indirect cross-validation comparisons between IASI 9, 10193–10234, 2009 and AIRS.

IASI spectral 5 4 Inter-comparison results radiance performance Spectral radiance inter-comparison is a fundamental ﬁrst-step prior to assessing validation derived geophysical parameter quality. As detailed in the last section, the goal of this case study is to assess IASI spectral radiances standalone and relative to A. M. Larar et al. AIRS through comparisons of measured IASI radiances with simulations and other 10 measurements selected from the JAIVEx case study day. The ﬁgures shown in this section illustrate some example infrared spectral radiance validation results. Title Page The inter-comparison results are presented as outlined in the comparison approach detailed within the last section of this manuscript. Abstract Introduction

Conclusions References 15 1. Comparisons with simulations. Figure 4 shows example simulations for an IASI measured spectrum of a select IFOV within the case study day Metop-A over- Tables Figures pass. Figure 4a illustrates the selected IFOV relative to the sub-satellite track, which is an arbitrarily-selected radiosonde location (i.e., FFC, near Atlanta, GA). Figure 4b J I shows the IASI measured spectrum along with four simulation results using different J I 20 estimates to represent the atmospheric state. Specifically, in order of increasing ability to match this specific IASI measurement, simulations utilize the 1976 Standard Back Close Atmosphere (Krueger and Minzner, 1976) (−12 K), ECMWF (−3.6 K), radiosonde (0.99 K), and an independent IASI retrieval (0.21 K); the parenthetical values represent Full Screen / Esc the mean (IASI-simulation) differences across the 1540–1610 cm−1 spectral region Printer-friendly Version 25 shown. The relative goodness of these simulations is in the expected order, i.e. they get better as one goes from models to measurements of closer space and time Interactive Discussion coincidence. It is interesting to point out that while the retrieved atmospheric state 10202 was produced from this specific IASI spectrum, it does not yield perfect results in this comparison since an independent atmospheric stratification and radiative transfer ACPD model have been implemented; this example is included to illustrate the point that even 9, 10193–10234, 2009 assuming a perfectly-known atmospheric state, the forward model errors can still be 5 on the order of a couple tenths of a degree K. This figure serves to demonstrate that results from simulations are not close enough for advanced sounder validation since IASI spectral they are limited by knowledge of atmospheric state and forward modeling differences. radiance performance 2. Intra-platform comparisons. Intra-platform comparisons for IASI and AIRS validation 10 are limited to comparisons with broadband imagers having lower requirements for radiometric and spectral resolutions and calibration. While this limits their ability to A. M. Larar et al. validate spectral radiance stand-alone, they are certainly very important components to and of value for validation. Figure 5 illustrates a comparison of IASI versus the IASI Title Page imager for the JAIVEx flight region scene. Figure 5a shows the imager data degraded 15 to IASI spatial resolution over the IASI scene region while Fig. 5b has IASI spectrally Abstract Introduction degraded through application of the IASI imager spectral response function, making the comparison of Fig. 5a to b spatially- and spectrally-consistent. Figure 5c uses a Conclusions References

histogram to depict the differences between the scenes in Fig. 5a–b. The mode of Tables Figures this distribution is 0.23 K, which is quite close considering the uncertainties involved 20 in this comparison. The outliers in this distribution are mainly due to heterogeneous J I regions of the scene (e.g. clouds) which are most sensitive to spatial errors in the IFOV matchups between IASI and the IASI imager. Figure 6 shows the same type of J I comparison as in Fig. 5 but represents AIRS versus MODIS band 31 (MB31, 11 micron Back Close window region) for the JAIVEx flight region scene. Figure 6a shows the MODIS data 25 degraded to AIRS spatial resolution over the AIRS scene region while Fig. 6b has Full Screen / Esc AIRS spectrally degraded through application of the MB31 spectral response function, making the comparison of Fig. 6a to b spatially- and spectrally-consistent. Figure 6c Printer-friendly Version uses a histogram to depict the differences between the scenes in Fig. 6a–b. The mode of this distribution is −0.12 K which, as in the last example, is quite close considering Interactive Discussion

10203 the uncertainties involved in this type of comparison. Intra-platform comparison among the WB-57 airborne sensors enables compar- ACPD ison of the high spectral resolution interferometer instruments NAST-I and S-HIS. 9, 10193–10234, 2009 Figure 7 shows a comparison of NAST-I versus S-HIS for average spectra from 5 collocated scenes during the 29 April 2007 JAIVEx flight mission for the (a) longwave window (880–980 cm−1), (b) midwave (1250–1450 cm−1), and (c) shortwave window IASI spectral (2385–2530 cm−1) spectral regions. Mean differences of these spectra are shown radiance to be −0.03 K, −0.02 K, and 0.04 K for these spectral regions, respectively. The performance higher-resolution NAST-I data have been reduced to the S-HIS spectral resolution for validation 10 a spectrally-consistent comparison. Figure 8 shows a scatter plot of NAST-I versus S-HIS for the average spectra shown in Fig. 7. A 10 cm−1 boxcar smoothing has first A. M. Larar et al. been applied to the spectra to better facilitate radiometric calibration inter-comparison. As indicated in the figure, the 800–1010 cm−1, 1215–1615 cm−1, and 2385–2600 cm−1 Title Page spectral regions have been included and show mean differences on the order of 15 hundredths of a degree K; this provides a consistency check of NAST-I relative to Abstract Introduction S-HIS for larger spectral extents than are used in later examples comparing NAST-I to IASI and AIRS. Conclusions References

Tables Figures 3. Inter-platform comparisons. 20 a) Direct IASI vs. AIRS comparisons. Figure 9 shows nadir and common cross-section J I lines extracted in the next example for a ﬁrst-order direct comparison of IASI and AIRS, and extend ±5 degrees in latitude from the sub-satellite intersection point J I of the satellite ground tracks for a) IASI and b) AIRS. Tracks are shown on top of Back Close platform imager scenes, i.e., IASI imager and MODIS (MB31), respectively. Figure 10 −1 25 shows water vapor band (1540–1610 cm ) latitudinal cross-sections (deviation from Full Screen / Esc brightness temperature mean, K) along the sub-satellite nadir for a) IASI, b) AIRS, and along a common cross-section for c) IASI and d) AIRS. The nadir cross-sections have Printer-friendly Version a point-in-space coincidence, and the common cross-sections have a line-in-space coincidence; however, temporal coincidence is shown to be more important since Interactive Discussion

10204 the different cross-sections from each sensor seem to more resemble each other than the corresponding cross-sections from the other sensor (that are not temporally ACPD coincident). The importance of time coincidence in comparisons involving an evolving 9, 10193–10234, 2009 geophysical field is also illustrated in the next example. Figure 11 shows another direct 5 comparison of IASI and AIRS coincident IFOVs within the JAIVEx 29 April 2007 flight domain. Select MODIS spectral response functions have been applied to illustrate IASI spectral scene evolution (between satellite overpasses) from a broadband perspective. Long- radiance wave window (MB31) and midwave water vapor (MB27) regions are shown in the top performance and bottom plots, respectively. The goal was to find IFOVs with a minimum of scene validation 10 evolution since any direct comparison of instruments will include both instrument differences and scene changes. In this example, out of the 374 IFOVs that overlap A. M. Larar et al. spatially in the JAIVEx “study region” only 2 can be found to satisfy a close match; i.e. ∼0.5% of the scenes produce a difference of ∼0.75 K, band averaged, which is Title Page still larger than desired for validation. The last two examples illustrate that, unlike 15 the simultaneous nadir observation (SNO) comparisons possible in polar regions Abstract Introduction (see, e.g., Cao et al., 2005), such direct satellite-to-satellite comparisons in lower latitude regions (where significant time can exist between overpasses) can contain Conclusions References

significant scene evolution differences making them difficult to utilize for detecting Tables Figures small instrument differences in Cal/Val.

20 J I b) Aircraft vs. spacecraft. Space and time collocation is critical for the validation task when the scenes being inter-compared contain signiﬁcant non-uniformity in J I the spatial and temporal domains, respectively. Airborne FTS assets, such as the Back Close NAST-I and S-HIS, are uniquely able to provide such collocation and enable the 25 best overall direct radiance inter-comparisons. The comparisons shown in this Full Screen / Esc section are all for single spacecraft sensor IFOVs relative to combined near-nadir NAST-I observations coincident in space and time. Since NAST-I is of higher spectral Printer-friendly Version resolution than the spacecraft sensors, an additional curve (in blue) is added in the plots to enable same-spectral resolution comparisons. Figure 12 shows example Interactive Discussion

10205 infrared spectral radiance inter-comparisons for a longwave window (880–980 cm−1) spectral interval between select space and time coincident NAST-I observations ACPD relative to a) IASI and b) AIRS measurements. Mean differences over this spectral 9, 10193–10234, 2009 interval are shown to be 0.13 K and 0.11 K for (NAST-I – IASI) and (NAST-I – AIRS), −1 5 respectively. A similar comparison for a midwave (1540–1610 cm ) spectral interval is shown in Fig. 13. This example uses different IFOVs to show comparisons to IASI spectral such levels are not outlier occurrences and, as with the last example, space and radiance time coincident NAST-I observations are shown relative to a) IASI and b) AIRS performance measurements. Mean differences over this spectral interval are shown to be 0.08 K validation 10 and 0.11 K for (NAST-I – IASI) and (NAST-I – AIRS), respectively. The shortwave A. M. Larar et al. window region is also included with a comparison of the 2390–2490 cm−1 spectral interval shown in Fig. 14. Once again, different space and time coincident IFOVs

have been selected to compare NAST-I observations relative to a) IASI and b) AIRS Title Page measurements. Mean diﬀerences over this spectral interval are shown to be 0.10 K 15 and 0.05 K for (NAST-I – IASI) and (NAST-I – AIRS), respectively. The airborne FTS Abstract Introduction versus spacecraft sensor comparisons included in this section show IASI and AIRS Conclusions References spectral radiances both matching coincident NAST-I observations to within ∼0.1 K (band-averaged). Such inter-comparisons yield the closest levels of direct radiance Tables Figures comparisons and veriﬁcation to these levels is hard to achieve using other approaches.

20 J I c) Indirect IASI vs. AIRS comparisons. The remaining ﬁgures in this section are focused on enabling an indirect radiometric comparison of IASI and AIRS utilizing J I

NAST-I observations, covering the time in between Metop-A (IASI) and AQUA (AIRS) Back Close overpasses, to remove differences due to scene evolution. Figure 15 illustrates the 25 sampling logistics for the next example, showing select NAST-I nadir tracks relative Full Screen / Esc to sub-satellite tracks for a) IASI and b) AIRS which are used for data cross-section −1 extraction. Figure 16 shows water vapor band (1540–1610 cm ) spectral radiance Printer-friendly Version latitudinal cross-sections for a) NAST-I at the IASI over pass time, b) IASI, c) NAST-I at the AIRS overpass time, and d) AIRS. Note that the NAST-I observations are Interactive Discussion 10206 degraded both spectrally and spatially to more-appropriately compare with IASI and AIRS in this example. As can be seen in this figure, space and time coincident NAST-I ACPD provides a better match to IASI observations than space-only coincident AIRS (i.e., 9, 10193–10234, 2009 a best matches b), and to AIRS observations than space-only coincident IASI (i.e., c 5 best matches d) , further demonstrating the potential for inter-satellite cross-validation using such airborne sensors. IASI spectral The next figure summarizes the sampling logistics to be used for comparing IASI radiance versus AIRS via NAST-I. Specifically, Fig. 17 illustrates the nadir tracks of IASI, AIRS, performance and NAST-I superimposed over the IASI imager scene of the JAIVEx case study day validation 10 flight region. Figure 18 shows the latitudinal variability of the geophysical field scene as will be observed in the aircraft/spacecraft measurement comparison. In this figure, A. M. Larar et al. sub-AIRS-pixel MODIS data (MB31) are used to represent scene characteristics within AIRS IFOV positions and for estimating view- and sampling-induced differences rela- Title Page tive to subsequent comparisons with NAST-I. Time varying NAST-I spatial positions are 15 used to achieve spatial coincidence with the AIRS/MODIS scene, albeit at the fixed-in- Abstract Introduction time AQUA overpass. A similar spatial character in field variability is also inferred using the IASI/imager scene from the Metop overpass, implying a consistent message that Conclusions References

this type of comparison (on this case study day) will have a periodic/latitudinal oscil- Tables Figures lation superimposed due to the aircraft flight profile and relative sampling differences 20 compared with the spacecraft sensors. J I Figure 19 shows a time series representation of a) NAST-I – IASI and b) NAST-I – −1 AIRS for a longwave spectral interval (880–980 cm ). As with the last figure, space J I coincidence is achieved for each comparison point whereas time coincidence is only Back Close achieved at satellite overpass times. The red symbols indicate, after the filtering of 25 outliers due to gross scene sampling differences, the time series differences of NAST-I Full Screen / Esc – IASI in a) and NAST-I – AIRS in b), the blue lines represent linear fits to the red symbols, and the vertical black lines correspond to satellite overpass times as indicated. Printer-friendly Version We can then calculate a residual difference between IASI and AIRS by performing a double-difference including the NAST-I observations coincident in space and time with Interactive Discussion

10207 each satellites overpass, specifically: ACPD (NAST-I − AIRS)|AOT − (NAST-I − IASI)|IOT ∼ (IASI − AIRS), (1) 9, 10193–10234, 2009 where AOT and IOT are the AIRS and IASI overpass times, respectively. Evaluation of Eq. (1) for this case using data derived from the linear fits (blue lines) yields a difference 5 between these spaceborne sensors of less than 0.05 K for this spectral interval, specif- IASI spectral ically, IASI-AIRS=0.049 K. Other approaches for evaluating this double-difference, e.g. radiance using local means or least-squares fits, have also been tried and yield similar results. performance It should be noted that there is also some justification for using a linear fit based upon validation the relationships observable in Fig. 19, i.e. aside from the sampling-induced cyclic A. M. Larar et al. 10 latitudinal behavior previously discussed, the scene evolution trend is fairly linear for this longwave window spectral interval; a more sophisticated fitting approach may be necessary to adequately represent the character observed in other spectral regions Title Page (e.g. water vapor band), as is currently under investigation for future reporting. This radiometric difference between IASI and AIRS is similar to that inferred by other ap- Abstract Introduction 15 proaches (i.e., which reported agreement between IASI and AIRS to better than 0.1 K) Conclusions References using SNO analysis in polar regions or NWP model fields for removing scene evolution in other regions (Strow et al., 2008), however, this airborne-centric approach is Tables Figures not limited to application in polar regions and does not have the potential for bias by the NWP model field assimilated sensors. These examples demonstrate the utility of J I 20 airborne FTS sensors, such as the NAST-I and S-HIS, to serve as reference calibration standards for enabling inter-satellite cross-validation. J I

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5 Summary and conclusions Full Screen / Esc This manuscript has stressed the importance of post-launch validation activities employing airborne field campaigns to verify the quality of satellite measurement sys- Printer-friendly Version 25 tems. Data from the JAIVEx field campaign have been shown to be very useful for Interactive Discussion IASI and AIRS validation and are serving to further refine methodologies for future 10208 advanced sounder validation associated with, for example, the Cross-track Infrared Sounder (CrIS) to fly on the NPOESS Preparatory Project (NPP) and NPOESS. ACPD It has been demonstrated that high-altitude, airborne FTS systems such as the 9, 10193–10234, 2009 NAST-I and S-HIS play a vital role in assessing radiometric and spectral fidelity of 5 spaceborne observations, since they provide the best means of comparison with spatially- and temporally-coincident SI-traceable measurements. Comparisons with IASI spectral simulations are limited by knowledge of atmospheric state and forward model uncer- radiance tainties, and such forward model error can easily exceed acceptable values for radiance performance comparisons, or that achievable using airborne sensors. Without the benefit of coinci- validation 10 dent airborne assets, attempts to do direct radiance validation through measurement- to-measurement comparisons (i.e., independent of forward radiative transfer model- A. M. Larar et al. ing uncertainties) would be limited to intra- and inter-satellite comparisons. For this case study, direct comparisons of IASI versus AIRS correspond to comparing mea- Title Page surements from overpasses separated by about 3.5 h. Even restricting comparisons 15 to those scenes with minimum evolution, the existing scene evolution is still too large Abstract Introduction and inhibits inferring instrument differences. Intra-platform comparisons are limited to sensors collocated on same platform, so for IASI and AIRS such comparisons are Conclusions References

restricted to those with broadband imagers having lower requirements for radiomet- Tables Figures ric and spectral resolutions and calibration. While this limits their ability to validate 20 spectral radiance stand-alone, they are still certainly very important components to J I and of value for validation by providing platform self-consistency veriﬁcation with large sample size comparisons having negligible collocation and viewing geometry errors. J I Alternatively, airborne FTS versus spacecraft sensor comparisons have shown IASI Back Close and AIRS spectral radiances both matching coincident NAST-I observations to within 25 ∼0.1 K (band-averaged). Such inter-comparisons yield the closest levels of direct ra- Full Screen / Esc diance comparisons and veriﬁcation to these levels is hard to achieve using other approaches. The airborne FTS measurements coincident with multiple satellite platforms Printer-friendly Version have also been shown to have potential for serving as calibration reference standards for enabling cross-validation, as coincident NAST-I observations have demonstrated Interactive Discussion

10209 longwave band differences between IASI and AIRS on the order of less than 0.05 K. Therefore continuation of aircraft under-flights for multiple satellites during multiple field ACPD campaigns can enable long-term monitoring of system performance and inter-satellite 9, 10193–10234, 2009 cross-validation. 5 The case study examined herein can be analyzed in further detail, bringing in more independent measurements from the other in-situ and remote sensors that also partic- IASI spectral ipated in the JAIVEx field campaign. Further examination of data from other flight days radiance not presented herein will also be part of this continued analysis. performance validation Acknowledgements. The authors wish to acknowledge the NASA Langley Research Center, 10 NASA SMD, NPOESS Integrated Program Office, and the various team members and their A. M. Larar et al. respective institutions for their continued, enabling support of the NAST program. The authors greatly appreciate the contributions from members of the NAST instrument and JAIVEx field campaign teams for making JAIVEx and this work possible. The FAAM is jointly funded by Title Page the UK Met Office and the Natural Environment Research Council. IASI has been developed 15 and built under the responsibility of the Centre National dEtudes Spatiales (CNES). It is flown Abstract Introduction onboard the Metop satellites as part of the EUMETSAT Polar System. The IASI L1 data are received through the Unified Meteorological Archival and Retrieval Facility (UMARF) of EU- Conclusions References METSAT. Tables Figures

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20 Aumann, H. H., Chahine, M. T. Gautier, C., Goldberg, M. D., Kalnay, E., McMillin, L. M., J I Revercomb, H., Rosenkranz, P. W., Smith, W. L., Staelin, D. H., Strow, L., and Susskind, J.: AIRS/AMSU/HSB on the AQUA mission: design, science objective, data products, and Back Close processing systems, IEEE T. Geosci. Remote , 41, 253–264, 2003. Best, F. A., Revercomb, H. E., Knuteson, R. O., Tobin, D. C., Dedecker, R. G., Dirkx, T. P., Mulli- Full Screen / Esc 25 gan, M. P., Ciganovich, N. N., and Te, Y.: Traceability of Absolute Radiometric Calibration for the Atmospheric Emitted Radiance Interferometer (AERI), Conference on Characterization Printer-friendly Version and Radiometric Calibration for Remote Sensing, Utah State University Space Dynamics Laboratory, Logan, UT, USA, 2003. Interactive Discussion

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Data, The 16th International TOVS Study Conference, Angra dos Reis, Brazil, 7–13 May, 2008a. 15 Larar A. M., Zhou, D. K., Liu, X., and Smith, W. L.: Select Methodology for Validating Ad- Title Page vanced Satellite Measurement Systems, Proceedings of the International Radiation Sympo- sium (IRS2008), Foz do Iguaçu, Brazil, 3–8 August, 2008b. Abstract Introduction Liu, X., Zhou, D. K., Larar, A. M., Smith Sr., W. L., and Mango, S. A.: Case-study of a principal- component-based radiative transfer forward model and retrieval algorithm using EAQUATE Conclusions References 20 data, Q. J. Roy. Meteorol. Soc., 133(S3), 243–256, 2007. Liu, X., Zhou, D. K., Larar, A. M., Smith, W. L., Schluessel, P., Newman, S. M., Taylor, J. P., Tables Figures and Wu, W.: Retrieval of atmospheric profiles and cloud properties from IASI spectra using super-channels, Atmos. Chem. Phys. Discuss., 9, 8683–8736, 2009, J I http://www.atmos-chem-phys-discuss.net/9/8683/2009/. 25 Newman, S. M., Knuteson, R. O., Zhou, D. K., Larar, A. M., Smith, W. L., and Taylor, J. P.: J I Radiative transfer validation study from the European Aqua Thermodynamic Experiment, Q. J. Roy. Meteorol. Soc., 135, 277–290, doi:10.1002/qj.382, 2009. Back Close Pagano, T. S., Aumann, H. H., Hagan, D. E., and Overoye, K.: Prelaunch and in-flight radio- Full Screen / Esc metric calibration of the Atmospheric Infrared Sounder (AIRS), IEEE T. Geosci. Remote, 41, 30 265–273, 2003. Prutzer, S., Ryan-Howard, D. P., Garcia, J. G., and Bold, D. R.: NPOESS Airborne Sounder Printer-friendly Version Testbed (NAST) IR Spectrometer Design, Proceedings of the IEEE Aerospace Conference, Snowmass, CA, USA, 1998. Interactive Discussion 10212 Revercomb, H. E., Walden, V. P., Tobin, D. C., Anderson, J., Best, F. A., Ciganovich, N. C., Dedecker, R. G., Dirkx, T., Ellington, S. C., Garcia, R. K., Herbsleb, R., Knuteson, R. O., La- ACPD Porte, D., McRae, D., and Werner, M.: Recent Results From Two New Aircraft-Based Fourier- Transform Interferometers: The Scanning High-resolution Interferometer Sounder and the 9, 10193–10234, 2009 5 NPOESS Atmospheric Sounder Testbed Interferometer, ASSFTS Conference, Toulouse, France, October 1998. Revercomb, H. E., Tobin, D. C., Knuteson, R. O., Best, F. A., Smith, W. L., van Delst, P.,LaPorte, IASI spectral D. D., Ellington, S. D., Werner, M. W., Dedecker, R. G., Garcia, R. K., Ciganovich, N. K., How- radiance ell, H. B., Dutcher, S., and Taylor, J. K.: Validation of Atmospheric InfraRed Sounder (AIRS) performance 10 spectral radiances with the Scanning High-resolution Interferometer Sounder (S-HIS) aircraft validation instrument, International TOVS Study Conference, 13th, Sainte-Adele, Quebec, Canada, 29 October–4 November 2003 (proceedings). A. M. Larar et al. Revercomb, H. E., Anderson, J. G., Best, F. A., Tobin, D. C., Knuteson, R. O., LaPorte, D. D., and Taylor, J. K.: Infrared calibration for climate: A perspective on present and future 15 high spectral resolution instruments, Multispectral, Hyperspectral, and Ultraspectral Remote Title Page Sensing Technology, Techniques, and Applications, Gao, India, 13–16 November 2006. Serio, C., Masiello, G., Grieco, G., Carissimo, A., Di Girolamo, P., Suma, D., Rodriguez, A., Abstract Introduction Stuhlmann, R., and Tjemkes, S.: Potential of the MTG -IRS mission to resolve small scale variability of atmospheric humidity, Proceedings of the International Radiation Symposium, Conclusions References 20 IRS 2008: Current Problems in Atmospheric Radiation (IRS 2008), edited by: Nakajima, T. and Yamasoe, M., American Institute of Physics Conference Proceedings, 331–334, 2009. Tables Figures Simeoni, D.: IASI: A Review of Instrument Performance and Characterizations, The Centre National d’Etudes Spatiales (CNES) and EUMETSAT IASI Conference, Anglet, France, 13– J I 16 November, 2007. 25 Smith, W., Larar, A., Zhou, D., Sisko, C., Li, J., Huang, B., Howell, H., Revercomb, H., Cousins, J I D., Gazarik, M., Mooney, D., and Mango, S.: NAST-I: Results from Revolutionary Aircraft Sounding Spectrometer, Proceedings from the SPIE Optical Spectroscopic Techniques and Back Close Instrumentation for Atmospheric and Space Research III, Conference, Denver, CO, USA, Full Screen / Esc 3756, 1999. 30 Smith, W., Larar, A., Taylor, J., Revercomb, H., Kireev, S., Zhou, D., Liu, X., Tobin, D., Newman, S., Schlussel,¨ P., Clough, A., Mango, S., and St. Germain, K.: Joint Airborne IASI Validation Printer-friendly Version Experiment (JAIVEx) – An overview, Proc. Int. ATOVS Study Conf. XVI, Angra dos Reis, Brazil, CIMSS, University of Wisconsin-Madison, Angra dos Reis, Brazil, 7–13 May, 2008. Interactive Discussion 10213 Strow, L. L., Hannon, S. E., De-Souza Machado, S., Motteler, H. E., and Tobin, D. C.: Validation of the Atmospheric Infrared Sounder radiative transfer algorithm, J. Geophys. Res., 111, ACPD D09S06, doi:10.1029/2005JD006146, 2006. Strow, L. L., Hannon, S., and Tobin, D.: IASI and AIRS validation and intercomparisons with 9, 10193–10234, 2009 5 SARTA, Advanced High Spectral Resolution Infrared Observations Workshop, EUMETSAT, Darmstadt, Germany, 15–17 September, 2008. Taylor, J. P., Smith, W. L., Cuomo, V., Larar, A. M., Zhou, D. K., Serio, C., Maestri, T., Rizzi, IASI spectral R., Newman, S., Antonelli, P., Mango, S., Di Girolamo, P., Esposito, F., Grieco, G., Summa, radiance D., Restieri, R., Masiello, G., Romano, F., Pappalardo, G., Pavese, G., Mona, L., Amodeo, performance 10 A., and Pisani, G.: EAQUATE – An international experiment for hyper-spectral atmospheric validation sounding validation, B. Am. Meteorol. Soc., 89(2), 203–218, 2008. Tobin, D. C., Revercomb, H. E., Knuteson, R. O., Best, F. A., Smith, W. L., Ciganovich, N. A. M. Larar et al. N., Dedecker, R. G., Dutcher, S., Ellington, S. D., Garcia, R. K., Howell, H. B., LaPorte, D. D., Mango, S. A., Pagano, T. S., Taylor, J. K.,van Delst, P., Vinson, K. H., and Werner, M. 15 W.: Radiometric and spectral validation of Atmospheric Inf rared Sounder observations with Title Page the aircraft-based Scanning High-Resolution Interferometer Sounder, J. Geophys. Res., 111, D09S02, doi:10.1029/2005JD006094, 2006. Abstract Introduction Xiong, X. and Barnes, W.: An overview of MODIS radiometric calibration and characterization, Advances in Atmospheric Sciences, 23(1), 69–79, 2006. Conclusions References 20 Zhou, D. K., Smith, W. L., Li, J., Howell, H. B., Cantwell, G. W., Larar, A. M., Knuteson, R. O., Tobin, D. C., Revercomb, H. E., and Mango, S. A.: Thermodynamic product retrieval Tables Figures methodology for NAST-I and validation, Appl. Optics, 41, 6957–6967, 2002. Zhou, D. K., Smith, W. L., Liu, X., Larar, A. M., Huang, H.-L. A., Li, J., McGill, M. J., and Mango, J I S. A.: Thermodynamic and cloud parameters retrieval using infrared spectral data, Geophys. 25 Res. Lett., 32, L15805, doi:10.1029/2005GL023211, 2005. J I Zhou, D. K., Smith, W. L., Cuomo, V., Taylor, J. P.,Barnet, C. D., Di Girolamo, P.,Pappalardo, G., Larar, A. M., Liu, X., Newman, S. M., Lee, C., and Mango, S. A.: Retrieval validation during Back Close the European Aqua Thermodynamic Experiment, Q. J. Roy. Meteorol. Soc., 133, 203–215, Full Screen / Esc 2007a. 30 Zhou, D. K., Smith Sr., W. L., Liu, X., Larar, A. M., Mango, S. A., and Huang, H.- L.: Physically retrieving cloud and thermodynamic parameters from ultraspectr al IR measurements, J. Printer-friendly Version Atmos. Sci., 64, 969–982, 2007b. Zhou, D. K., Smith, W. L., Larar, A. M., Liu, X., Taylor, J. P., Schlussel,¨ P., Strow, L. L., and Interactive Discussion 10214 Mango, S. A.: All weather IASI single field-of-view retrievals: case study – validation with JAIVEx data, Atmos. Chem. Phys., 9, 2241–2255, 2009, ACPD http://www.atmos-chem-phys.net/9/2241/2009/. 9, 10193–10234, 2009

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d) c) J I Figure 1. JAIVEx flight mission of 29 April 2007. The extended GOES imager scenes are shown for a) infrared, b) visible, and c) water vapor bands, while the WB-57 oval racetrack flight pattern and NAST-I surface scan coverage Back Close Fig. 1. JAIVExwithin the north ﬂight central mission Gulf of Mexico of 29 are April shown 2007.in d). The extended GOES imager scenes are sho wn for (a) infrared, (b) visible, and (c) water vapor bands, while the WB-57 oval racetrack ﬂight Full Screen / Esc pattern and NAST-I surface scan coverage within the north central Gulf of Mexico are shown in (d). Printer-friendly Version

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Figure 2. JAIVEx flight mission of 29 April 2007. The sub-satellite tracks for Metop (IASI) and Aqua (AIRS) are shown in a) and b), while the NAST-I nadir track (pink line) is shown within the IASI imager and Modis scenes in Back Close Fig. 2. c)JAIVEx and d), respectively. ﬂight mission of 29 April 2007. The sub-satellite tracks for Metop (IASI) and Aqua (AIRS) are shown in (a) and (b), while the NAST-I nadir track (pink line) is shown within Full Screen / Esc the IASI imager and Modis scenes in (c) and (d), respectively.

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Figure 4. IASI measured spectra versus simulation for a select IFOV on the 29 April 2007 JAIVEx region overpass Back Close at 1550 GMT. Selected IFOV position shown within the IASI imager scene data in a) along with the sub-satellite track (white-dashed arrow). Fig. 4. IASI measured spectra versus simulation for a select IFOV on the 29 April 2007 JAIVEx Full Screen / Esc region overpass at 15:50 GMT. Selected IFOV position shown within the IASI imager scene data in (a) along with the sub-satellite track (white-dashed arrow). Printer-friendly Version

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Figure 5. IASI versus IASI imager for the Metop-A scene over the 29 April 2007 JAIVEx flight mission: a) Back Close imager degraded to IASI spatial resolution over IASI scene, b) IASI spectrally degraded through application of IASI Fig. 5. imagerIASI spectral versus response IASI function, imager and forc) histogram the Metop-A of scene a) – scene scene b). over the 29 April 2007 JAIVEx ﬂight mission: (a) imager degraded to IASI spatial resolution over IASI scene, (b) IASI spectrally Full Screen / Esc degraded through application of IASI imager spectral response function, and (c) histogram of scene (a) – scene (b). Printer-friendly Version

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Figure 6. AIRS versus Modis Band 31 (MB31) for the Aqua scene over the 29 April 2007 JAIVEx flight mission: a) MB31 degraded to AIRS spatial resolution over AIRS scene, b) AIRS spectrally degraded through application of Back Close Fig. 6. AIRSMB31 spectral versus response Modis function, Band and 31c) histogram (MB31) of scene for thea) – scene Aqua b). scene over the 29 April 2007 JAIVEx ﬂight mission: (a) MB31 degraded to AIRS spatial resolution over AIRS scene, (b) AIRS spec- Full Screen / Esc trally degraded through application of MB31 spectral response function, and (c) histogram of scene (a) – scene (b). Printer-friendly Version

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Figure 8. Scatter plot of NAST-I versus S-HIS for average spectra shown in Figure 7. The higher-resolution J I NAST-I data have been reduced to the S-HIS spectral resolution and spectra have been smoothed over 10 cm-1 to Fig. 8. Scatterbetter facilitate plot radiometric of NAST-I calibration versus inter- S-HIScomparison. for As average indicated in spectra the Figure, shownthe 800 – 1010, in Fig. 1215 7. – 1615, The higher- Back Close resolutionand NAST-I 2385 – 2600 data cm-1 havespectral beenregions are reduced shown. to the S-HIS spectral resolution and spectra have −1 been smoothed over 10 cm to better facilitate radiometric calibration inter-comparison. As Full Screen / Esc indicated in the Figure, the 800–1010, 1215–1615, and 2385–2600 cm−1 spectral regions are shown. Printer-friendly Version

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Title Page

Abstract Introduction

Conclusions References

a) b) Tables Figures Figure 9. Nadir and common cross-section lines extracted for first-order direct comparison of IASI and AIRS, +/- 5 degrees latitude from sub-satellite intersection point of the satellite ground tracks for a) IASI and b) AIRS. Tracks Fig. 9. Nadirare shown and on top common of platform cross-section imager scenes, i.e., IASI lines imager extracted and Modis for B31, ﬁrst-order respectively. direct comparison of IASI and AIRS, ±5 degrees latitude from sub-satellite intersection point of the satellite ground tracks J I for (a) IASI and (b) AIRS. Tracks are shown on top of platform imager scenes, i.e., IASI imager J I and Modis B31, respectively. Back Close

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a) b)

Title Page

Abstract Introduction

Conclusions References

c) d) Tables Figures

Figure 10. Water vapor band (1540 – 1610 cm-1) latitudinal cross-sections (deviation from mean, K) along sub- satellite nadir for a) IASI, b) AIRS, and along a common−1 cross-section for c) IASI and d) AIRS. Nadir cross- J I Fig. 10. sectionsWater have vapor point-in band-space coincidence (1540–1610 while common cm ) cross latitudinal-sections have cross-sections line-in-space coincidence. (deviation from mean, K) along sub-satellite nadir for (a) IASI, (b) AIRS, and along a common cross-section for (c) J I IASI and (d) AIRS. Nadir cross-sections have point-in-space coincidence while common cross- sections have line-in-space coincidence. Back Close

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38 AIRS - IASI IASI vs AIRS ACPD MB31 9, 10193–10234, 2009

Mode = 0.60 K IASI spectral radiance performance validation

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MB27 Title Page

Mode = Abstract Introduction 2.5 K Conclusions References

Tables Figures

J I

Figure 11. Direct comparison of IASI and AIRS coincident IFOVs within the JAIVEx 29 April 2007 flight Backdomain. Close Fig. 11. DirectSelect comparison Modis spectral of IASIresponse and functions AIRS coincident have been IFOVsapplied within(to the theIASI JAIVEx and AIRS 29 sp Aprilectral radiances) to illustrate 2007 ﬂight domain.scene evolution Select Modis(between spectral satellite response overpass functionses) from a have broadband been applied difference (to perspective the IASI . Longwave windowFull Screen / Esc and AIRS spectral(MB31) radiances) and midwav toe illustrate water vapor scene (MB27) evolution regions (between are shown satellite in the top overpasses) and bottom plots, from respectively. a broadband diﬀerence perspective. Longwave window (MB31) and midwave water vapor (MB27) Printer-friendly Version regions are shown in the top and bottom plots, respectively. Interactive Discussion

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IASI spectral radiance NAST-I sample time = 1525 GMT GMT performance (NAST-I – IASI) = 0.13 K validation IASI

NAST-I A. M. Larar et al. LW window NAST-I * SRF (IASI) (11.4 – 10.2 micron)  a) Title Page

NAST-I sample time = 1856 GMT GMT Abstract Introduction (NAST-I – AIRS) = 0.11 K AIRS Conclusions References NAST-I

NAST-I * SRF LW window (AIRS) Tables Figures (11.4 – 10.2 micron) b) J I Figure 12. Example infrared spectral radiance inter-comparisons for the longwave window 880 – 980 cm-1 spectral region showing space and time coincident NAST-I relative to a) IASI and b) AIRS measurements. Fig. 12. Example infrared spectral radiance inter-comparisons for the longwave window 880– J I 980 cm−1 spectral region showing space and time coincident NAST-I relative to (a) IASI and (b) AIRS measurements. Back Close

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NAST-I sample time = 1555 GMT performance

(NAST-I – IASI) = 0.08 K validation IASI

NAST-I A. M. Larar et al.

H2O band NAST-I * SRF (IASI) (6.5 – 6.2 a) Title Page NAST-I sample time = 1907 GMT (NAST-I – AIRS) = 0.11 K Abstract Introduction

AIRS

NAST-I Conclusions References

H2O band NAST-I * SRF (AIRS) (6.5 – 6.2 ) Tables Figures b)

Figure 13. Example infrared spectral radiance inter-comparisons for the water vapor 1540 – 1610 cm-1 spectral J I region showing space and time coincident NAST-I relative to a) IASI and b) AIRS measurements. Fig. 13. Example infrared spectral radiance inter-comparisons for the water vapor 1540– 1610 cm−1 spectral region showing space and time coincident NAST-I relative to (a) IASI and J I (b) AIRS measurements. Back Close

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IASI spectral NAST-I sample time = 1608 GMT radiance GMT (NAST-I – IASI) = 0.10 K performance

IASI validation SW window NAST-I

(4.2 – 4.0 micron) NAST-I * SRF (IASI) A. M. Larar et al.

a) Title Page NAST-I sample time = 1850 GMT GMT Abstract Introduction (NAST-I – AIRS) = 0.05 K Conclusions References AIRS NAST-I SW window Tables Figures NAST-I * SRF (4.2 – 4.0 micron) (AIRS) b) J I

Figure 14. Example infrared spectral radiance inter-comparisons for the shortwave window 2390 – 2490 cm-1 spectral region showing space and time coincident NAST-I relative to a) IASI and b) AIRS measurements. J I Fig. 14. Example infrared spectral radiance inter-comparisons for the shortwave window 2390– 2490 cm−1 spectral region showing space and time coincident NAST-I relative to (a) IASI and Back Close (b) AIRS measurements. Full Screen / Esc

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Title Page

IASI & AIRS & Abstract Introduction NAST-I NAST-I Conclusions References IFOVs IFOVs a) b Tables Figures ) Figure 15. Select NAST-I nadir tracks relative to sub-satellite tracks for a) IASI and b) AIRS. J I Fig. 15. Select NAST-I nadir tracks relative to sub-satellite tracks for (a) IASI and (b) AIRS. J I

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a) b) Title Page

Abstract Introduction

d) Conclusions References c) Figure 16. Water vapor band (1540 – 1610 cm-1) spectral radiance latitudinal cross-sections for a) NAST-I at the IASI Tables Figures overpass time, b) IASI, c) NAST-I at the AIRS overpass− time,1 and d) AIRS. Fig. 16. Water vapor band (1540–1610 cm ) spectral radiance latitudinal cross-sections for (a) NAST-I at the IASI overpass time, (b) IASI, (c) NAST-I at the AIRS overpass time, and (d) J I AIRS. J I

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44 ACPD 9, 10193–10234, 2009 Nadir tracks: IASI spectral radiance performance validation

A. M. Larar et al.

Title Page

NAST-I Abstract Introduction

Conclusions References

Tables Figures

IASI J I AIRS J I

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Full Screen / Esc Figure 17. Nadir tracks of IASI, AIRS, and NAST-I superimposed over the IASI imager scene of the JAIVEx flight Fig. 17. Nadirregion. tracks of IASI, AIRS, and NAST-I superimposed over the IASI imager scene of the JAIVEx ﬂight region. Printer-friendly Version

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Comparison validation latitude Scene temperature stddev A. M. Larar et al. Scene temperature

IFOV-view-induced temperature difference Title Page

Abstract Introduction

Conclusions References

Tables Figures AIRS overpass (1919 GMT) Figure 18. Latitudinal variability of geophysical field as GMT)observed in aircraft / spacecraft measurement comparison. Sub-pixel Modis data are used to represent scene characteristics within AIRS IFOV positions and for view-induced Fig. 18. differencesLatitudinal relative variability to comparisons of geophysicalwith NAST-I. Latitude, field asscene observed temperature inand aircraft/spacecraft standard deviation, and IFOV measure-- J I ment comparison.view-induced differences Sub-pixel (i.e. between Modis a/c data and s/c are geometries) used to are represent shown for comparison scene characteristics sample positions as a within AIRS IFOVfunction positions of NAST-I andsamplefor time. view-induced differences relative to comparisons with NAST-I. J I Latitude, scene temperature and standard deviation, and IFOV-view-induced differences (i.e. Back Close between a/c and s/c geometries) are shown for comparison sample positions as a function of NAST-I sample time. Full Screen / Esc

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46 ACPD 9, 10193–10234, 2009 Comparison latitude NASTI – IASI (all) IASI spectral NASTI – IASI (filtered) radiance NASTI – IASI (filtered; linear fit) performance validation IOT = IASI overpass time

a) A. M. Larar et al.

IASI overpass (1550 GMT) Title Page

Abstract Introduction Comparison latitude Conclusions References NASTI – AIRS (all)

NASTI – AIRS (filtered) Tables Figures NASTI – AIRS (filtered; linear fit)

AOT = AIRS overpass time J I

J I b) Back Close AIRS overpass (1919 GMT) Figure 19. Time series representation of a) NAST-I – IASI and b) NAST-I – AIRS for a longwave spectral interval (880 – 980 cm-1). Space coincidence is achieved for each comparison point whereas time coincidence is only Full Screen / Esc Fig. 19.achievedTime at series satellite overpass representation times. of (a) NAST-I – IASI and (b) NAST-I – AIRS for a longwave spectral interval (880–980 cm−1).Space coincidence is achieved for each comparison point whereas time coincidence is only achieved at satellite overpass times. Printer-friendly Version Interactive Discussion

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