Validation Study of the MOPITT Retrieval Algorithm: Carbon Monoxide Retrieval from IMG Observations during WINCE

Jinxue Wang Atmospheric Chemistry Division, National Center for Atmospheric Research, Boulder, Colorado

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John C. Gille Atmospheric Chemistry Division, National Center for Atmospheric Research, Boulder, Colorado

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Henry E. Revercomb Space Science Engineering Center, University of Wisconsin—Madison, Madison, Wisconsin

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Von P. Walden Space Science Engineering Center, University of Wisconsin—Madison, Madison, Wisconsin

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Abstract

The Measurement of Pollution in the Troposphere (MOPITT) instrument is an eight-channel gas correlation radiometer selected for the Earth Observing System (EOS) Terra spacecraft launched in December 1999. Algorithms for the retrieval of tropospheric carbon monoxide (CO) profiles from MOPITT measurements have been developed. In this paper, validation studies of the MOPITT CO retrieval algorithm using observations by the Interferometric Monitor for greenhouse Gases (IMG) during the Winter Clouds Experiment (WINCE) conducted from 23 January to 13 February 1997 are described. Synthetic radiance spectra calculated by a line-by-line radiative transfer model, FASCOD3, using the retrieved CO profile agrees well with IMG-measured radiance spectra. Observations by the Moderate Resolution Imaging Spectrometer (MODIS) Airborne Simulator (MAS) from the NASA ER-2 platform during WINCE were successfully used to assist in the identification of clear and cloudy IMG observations.

Corresponding author address: Dr. Jinxue Wang, NCAR/ACD, P.O. Box 3000, Boulder, CO 80307-3000.

Email: jwang@cos.ucar.edu

Abstract

The Measurement of Pollution in the Troposphere (MOPITT) instrument is an eight-channel gas correlation radiometer selected for the Earth Observing System (EOS) Terra spacecraft launched in December 1999. Algorithms for the retrieval of tropospheric carbon monoxide (CO) profiles from MOPITT measurements have been developed. In this paper, validation studies of the MOPITT CO retrieval algorithm using observations by the Interferometric Monitor for greenhouse Gases (IMG) during the Winter Clouds Experiment (WINCE) conducted from 23 January to 13 February 1997 are described. Synthetic radiance spectra calculated by a line-by-line radiative transfer model, FASCOD3, using the retrieved CO profile agrees well with IMG-measured radiance spectra. Observations by the Moderate Resolution Imaging Spectrometer (MODIS) Airborne Simulator (MAS) from the NASA ER-2 platform during WINCE were successfully used to assist in the identification of clear and cloudy IMG observations.

Corresponding author address: Dr. Jinxue Wang, NCAR/ACD, P.O. Box 3000, Boulder, CO 80307-3000.

Email: jwang@cos.ucar.edu

1. Introduction

There have been increasing worldwide concerns and awareness of possible human impact on the environment and climate. To address these concerns and to gain a better understanding of the connection between increased human activities and global climate change, many countries are in the process of designing, building, and launching sophisticated satelliteborne remote sensors to measure the global distribution of trace gases that are important to the greenhouse effect and global tropospheric chemistry. Some of the important trace gases to be measured by satellite instruments in the next decade include H2O, O3, CO, CH4, etc. A better understanding of the global distributions, trends, variability, sources, and sinks of these gases will advance our knowledge of the connections between human activities and the natural environment. Any significant changes in the processes and rates by which trace gases are oxidized in the atmosphere will have profound impacts on the lifetime of many tropospheric gases and hence the climate (Jacob 1998).

Carbon monoxide is one of the important trace gases in tropospheric chemistry. Its concentration in the troposphere directly affects the concentration of tropospheric hydroxyl which regulates the lifetimes of many tropospheric trace gases (Logan et al. 1981). Carbon monoxide can also be used as a tracer to study the transport of global and regional pollutants from industrial activities and large-scale biomass burning.

Many research groups have been conducting surface and tropospheric CO measurements using ground-based and airborne instruments. There is a global surface CO monitoring network, the Climate Monitoring and Diagnostic Laboratory of the National Oceanic and Atmospheric Administration (NOAA/CMDL) Cooperative Air Sampling Network (Novelli et al. 1992; http://www.cmdl.noaa.gov/ccg/flask/sites.html). It includes four NOAA/CMDL baseline observatories, 40 cooperative sites, four commercial vessels, and two sites located on towers. Gas species measured are CO2, CH4, CO, N2O, SF6, and the carbon and oxygen isotopes of CO2. Surface and boundary layer CO concentrations are measured on a routine basis at these sites. Surface measurements at these sites are useful in the study of CO sources and sinks, but they are clearly not adequate for the study of its transport and its roles in tropospheric chemistry. To our knowledge, there are only two sites around the world where tropospheric CO profiles are measured on a routine basis using airborne sampling techniques. One site is at Carr, Colorado, in the United States. It is operated by NOAA/CMDL in Boulder, Colorado. Tropospheric CO profiles have been measured at this site on a biweekly basis using an automated airborne sampling unit since November 1992 (Novelli et al. 1994). The airborne sampling unit collects samples of air using a small pump and 20 glass flasks. The samples are then returned to the NOAA/CMDL laboratory in Boulder, Colorado, for analysis. The other site is located at Cape Grim in Australia. It is operated by the Commonwealth Scientific and Industrial Research Organisation of Australia. Tropospheric CO profiles have been measured on a routine basis using airborne sampling techniques since May 1992 (Francey et al. 1996; Langenfelds et al. 1996). Additionally, there were two shuttle missions totaling about four weeks in 1994, during which CO total column was measured by a spaceborne instrument called Measurement of Air Pollution from Space (MAPS; Reichle et al. 1986, 1990, 1999).

Surface and boundary layer CO measurements at the NOAA/CMDL Cooperative Air Sampling Network, regular airborne CO sampling at Carr and Cape Grim, satellite observations by MAPS, and CO measurements by short-duration campaigns all indicate that CO is highly variable both temporally and spatially. There are strong needs for systematic global observations by sensitive spaceborne sensors. The Measurement of Pollution in the Troposphere (MOPITT) instrument is one of the experiments selected to meet these needs. The Earth Observing System (EOS) Terra spacecraft was launched by the National Atmosphere and Space Administration (NASA) in December 1999.

The primary objectives of the MOPITT experiment are the measurement of tropospheric CO profiles with a vertical resolution of 3–4 km and methane (CH4) total column. The nominal spatial resolution of both CO and CH4 measurements is 22 km by 22 km. With a vertical resolution of 3–4 km, the measurement is capable of resolving the troposphere into the upper, middle, and lower troposphere. The higher vertical resolution offered by MOPITT makes it possible to study the long-range transport of CO from source regions to the global atmosphere. Long-range transport from source regions often leads to enhanced CO levels in the middle and upper troposphere. Results from the NASA Global Troposphere Experiment PEM TROPICS-A experiment show that CO from biomass burning in South America and Africa can be transported to regions as far away as the remote tropical Pacific (Hoell et al. 1999; Talbot et al. 1999; Gregory et al. 1999).

Complex and sophisticated algorithms that convert MOPITT radiance observations into tropospheric CO mixing ratios have been developed (Pan et al. 1998; Wang et al. 1999a). It is important to test and validate these algorithms both before and after the launch of MOPITT. Data from the Interferometric Measurement of greenhouse Gases (IMG) instrument can be used to create MOPITT-like signals to test and validate the MOPITT retrieval algorithm (Wang et al. 1999a). We have also used IMG observations to study the radiative properties of surface and clouds in MOPITT spectral bands.

In this paper, a brief description of the MOPITT instrument and CO retrieval algorithm is presented in section 2. The characteristics of IMG instrument and observations are briefly described in section 3. The analysis of IMG spectral radiance observations and the retrieval of tropospheric CO using the MOPITT retrieval algorithms are presented in section 4. Section 5 gives a summary of this MOPITT retrieval algorithm validation study using IMG observations.

2. Brief description of the MOPITT instrument and CO retrieval algorithm

a. MOPITT instrument characteristics

MOPITT is an eight-channel gas correlation radiometer with both pressure modulation cells (PMCs) and length modulation cells (LMCs; see Table 1). Detailed explanations of the PMCs and LMCs and their characteristics can be found in Drummond and Mand (1996) and Taylor (1993). Thermal channels in the CO 4.7-μm band, solar channels in the CO 2.3-μm band, and CH4 2.2-μm band are used in MOPITT. Solar channels are used to enhance instrument sensitivity to the lower troposphere. MOPITT instrument characteristics and sensitivities to PMCs and LMCs pressures and temperatures errors, atmospheric CO, water vapor (H2O), and temperature profiles have been investigated, and can be found in Wang et al. (1999b).

b. MOPITT CO retrieval algorithm

The MOPITT CO retrieval algorithm is based on the maximum likelihood method (Rodgers 1976). At each iteration, the algorithm minimizes the differences between the MOPITT-observed radiance in each channel and forward model–calculated radiance weighted by instrument noise covariances and the distance between the solution CO profile and a priori profile weighted by the CO profile covariances. Mathematically, the algorithm minimizes J(X) in the following equation at each iteration:
JXYmYXtS−1ɛYmYXXX0tS−1aXX0
where Ym is the measured radiance signal by MOPITT, and Y(X) is the radiance signal calculated by the forward radiative transfer model. Here, Sɛ is the MOPITT instrument noise covariance matrix. In the MOPITT retrieval system, Sɛ is a diagonal matrix with instrument channel noise variances as its diagonal elements. Also, Sa is a matrix of the expected CO variances at each retrieval level and covariances between different retrieval levels calculated using aircraft in situ measurements and calculations by chemistry-transport models (e.g., the MOZART model; Brasseur et al. 1998). Here, X0 is the first-guess vector of the CO profiles.
The solution to Eq. (1) is obtained by an iterative process. The update from Xn to Xn+1 is given by the equation:
Xn+1X0SxKTnKnSXKTnSɛ−1YYnKnX0Xn
where Xn are the retrieval state parameters at iteration n, and Xn+1 are the retrieval state parameters at iteration n + 1. Here, Yn are the forward model–calculated signal using Xn, and Kn is the Frechet derivative or Jacobian given by ∂Y/∂X at Xn, which is calculated using a finite difference method. The superscript T stands for matrix transpose. The iteration process is stopped when the convergence criterion is met, such that Xn+1Xn is acceptably small. At this point, the profile X will be substituted back into the forward model, and the differences YmY(x) should be of the order of the measurement error in all channels. More details of the MOPITT retrieval algorithm and forward radiative transfer models can be found in Pan et al. (1998), Edwards et al. (1999), and Wang et al. (1999a). We want to note here that there have been some changes to the MOPITT algorithm since 1998. For example, we have changed the retrieval state variables from CO layer amounts to level mixing ratios. A more detailed description of the updated MOPITT algorithm will be provided in a future paper.

3. The interferometric measurement of greenhouse gases (IMG) experiment and spectral radiance data products

The IMG instrument was launched aboard the Japanese Advanced Earth Observing Satellite (ADEOS) in August 1996 (Ogawa et al. 1994). It operated successfully from August 1996 through June 1997. The instrument is a Fourier transform spectrometer that measures upwelling spectral infrared radiance at the top of the atmosphere between 3.3 and 14 μm in three separate spectral bands at very high spectral resolution (∼0.05 cm−1). The spectral radiance data can be used to retrieve the profiles of atmospheric temperature and various trace gases, including H2O, CH4, CO, and O3. IMG spectral bands, spectral resolution, and instrument characteristics are listed in Table 2.

The three IMG spectral bands were sampled simultaneously by three different detectors. The instantaneous field of view (IFOV) is three separate 8 km by 8 km squares with a spacing of 4 km, as shown in Fig. 1. The dwell time on each IFOV is 10 s. The scanning mirror is suspended on magnetic bearings and scans 10 cm within the 10-s observation time. After six consecutive observations of 10 s each, the instrument observes deep space and an onboard blackbody for calibration. It takes 110 s to complete the six atmosphere observations, one deep space view and one blackbody view, which are collectively defined as one observation unit. The observation sequence and duration are illustrated in Fig. 2.

The standard IMG level-1 products are calibrated atmospheric spectral radiance spectra. Level-1 data validation was carried out by comparing the measured spectral radiance and line-by-line radiative transfer model calculations (Kobayashi et al. 1998). IMG level-1 data during the Winter Cloud Experiment (WINCE) were used in the validation of the MOPITT retrieval algorithm.

4. Analysis of IMG spectral radiance observations during WINCE

WINCE was conducted jointly by NASA and the University of Wisconsin—Madison’s Space Science and Engineering Center from 23 January to 13 February 1997. The primary objective of WINCE is to test and improve the cloud detection algorithm for the Moderate Resolution Imaging Spectroradiometer (MODIS; King et al. 1992), which was launched on the EOS Terra spacecraft in 1999. A secondary objective is for IMG calibration and data validation using airborne measurements from the ER-2 aircraft and ground-based measurements. More detailed information about WINCE can be found at the WINCE Web site (http://cimss.ssec.wisc.edu/wince/wince.html).

During WINCE, multispectral radiometric measurements of clouds and the earth were made on NASA’s ER-2 aircraft by the MODIS Airborne Simulator (MAS;King et al. 1996), and the High resolution Interferometer Sounder (HIS; Smith et al. 1983). IMG observations during ADEOS overflights were obtained and archived. We have analyzed the IMG spectral radiance measurements during WINCE as part of the effort to validate the MOPITT CO retrieval algorithm. The results of a case study using IMG observations on 28 January 1997 are presented in this section.

a. IMG spectral radiance observations on 28 January 1997

On 28 January 1997 during WINCE, the NASA ER-2 aircraft conducted a successful underflight of the ADEOS satellite over the Nebraska and South Dakota region. HIS observations were used to investigate the calibration of the IMG instrument and resulted in improvements in the IMG calibration. Some earlier problems in IMG phase error correction were resolved. Flight condition reports indicated that sky conditions during overpass were cirrus at the northern end of the flight track and apparently clear in the southern 3/4 of the overpass. We have carefully examined the six IMG observations around 1745 UTC 28 January 1997 when ADEOS flew over the WINCE site. Figure 3 shows the IMG observation locations and ER-2 flight track overlaid on a GOES-8 visible image. From the GOES image, it seems that the IMG observations IMG1–IMG4 were under cloudy conditions and observation IMG5 seems to be partially cloudy. The only clear pixel is believed to be from observation IMG6. Figure 4 shows the IMG spectral radiance observations for IMG1, IMG3, IMG5, and IMG6 with overplot of the nominal MOPITT thermal-band filter profile. IMG1 shown in Fig. 4a was taken over 45.93°N, 96.75°W at 1744:17 UTC. IMG3 shown in Fig. 4b was taken over 44.41°N, and 97.33°W at 1744: 43 UTC. IMG5 shown in Fig. 4c was taken over 42.89°N, 97.87°W at 1744:56 UTC. IMG6 shown in Fig. 4d was taken over 42.13°N, 98.14°W at 1745:22 UTC. These spectra seem to agree with the assessment from the GOES-8 image that observations IMG1 and IMG3 are cloudy as indicated by the low radiance levels (0.4–0.5 mW m−2 sr−1 cm−1) and small absorption at the centers of strong CO lines. They could be a result of IMG observing the cloud tops with cold temperature and shortened atmospheric absorption paths. Observation IMG5 seems to be partially cloudy as indicated by the increased radiance level compared with IMG1 and IMG3. Observation IMG6 seems to be clear, which will be confirmed later by MAS observations and radiative transfer calculations using radiosonde measurements under clear-sky conditions.

b. Cloud discrimination using MODIS airborne simulator (MAS) data

MODIS is a facility instrument on the EOS Terra spacecraft that was launched in 1999. MODIS provides observations of the land, oceans, and atmosphere at 36 wavelengths from 0.4 to 14.5 μm (King et al. 1992). Sophisticated cloud discrimination algorithms have been developed to detect different types of clouds within a MODIS field of view (FOV) (Ackerman et al. 1998). Since MODIS and MOPITT are on the same spacecraft with excellent observation time and location coincidences, there is a plan to use MODIS cloud mask products for cloud detection in the MOPITT FOV.

MAS was designed to measure reflected solar and emitted thermal radiation in 50 narrowband channels between 0.55 and 14.2 μm. MAS provides multispectral images of outgoing radiation for the development and validation of MODIS data processing algorithms for the remote sensing of cloud, aerosol, water vapor, and surface properties from space (King et al. 1996). At the ER-2 flight altitude of 20 km, MAS scans a swath width of 37.2 km, perpendicular to the ER-2 flight track. MAS has an IFOV of 2.5 mrad, which results in a spatial resolution of 50 m by 50 m for each pixel with a nominal ER-2 flight altitude of 20 km.

We have used MAS observations from ER-2 during WINCE to assist in the classification of clear and cloudy IMG observations. Using MAS data in the MOPITT algorithm validation with IMG observations provides opportunities to investigate the potential applications of MODIS data in MOPITT cloud detection. Clouds can often be identified by their high reflectance in visible and near-infrared spectral regions and lower brightness temperatures in thermal spectral regions (Ackerman et al. 1998). We chose to use MAS band 23, a near-infrared band centered at 2.29 μm, because it overlaps the MOPITT CO and CH4 shortwave bands at 2.2 and 2.3 μm. The apparent reflectance in MAS band 23 is sensitive to the presence of clouds in the MAS FOV. High and relatively uniform apparent reflectance is often associated with the presence of clouds. Figure 5 shows the MAS band 23 apparent reflectance at IMG5 location at latitude of 42.9°N and longitude of 98.0°W. The image covers a MAS observation area of 37.2 km by 37.2 km. The IMG band-2 FOV is marked by an 8 km by 8 km square in the middle-right side of the image. The right panel shows a scatterplot of MAS band-45 brightness temperature as a function of MAS band-2 reflectance. MAS band 45 is a thermal infrared band centered at 11.02 μm, and band 2 is a visible band centered at 0.657 μm. Both the MAS band-23 reflectance map and the scatterplot were generated using software, called SHARP, developed by Dr. Liam Gumley at the University of Wisconsin (http://cimss.ssec.wisc.edu/∼gumley/sharp/sharp.html). The reflectance map clearly shows that there exists a band of cloud running across the middle of the image with a relatively high apparent reflectance of about 0.20. The scatterplot also shows a cluster of points with low band-45 brightness temperature and high band-2 reflectance. As a comparison, Fig. 6 shows the MAS band-23 apparent reflectance at IMG6 location at latitude of 42.2°N and longitude of 98.2°W. Again, the image covers a MAS observation area of 37.2 km by 37.2 km. The IMG band-2 FOV is marked by an 8 km by 8 km square in the middle-right side of the image. The land surface features are clearly visible, and there are no obvious cloud features. The scatterplot for the IMG FOV region shows higher band-45 brightness temperature and lower band-2 reflectance. The above conclusions were also confirmed by examining MAS observations in other bands. Therefore, MAS observations are consistent with the GOES-8 image and the IMG radiance observations.

c. CO retrieval from IMG observations

A tropospheric CO profile was retrieved using the IMG6 observation from 2140 to 2194 cm−1, corresponding to the full-width at half-maximum of the MOPITT 4.7-μm filter (see Table 1 and Fig. 4). The retrieval was done using the MOPITT CO retrieval algorithm and the digital gas correlation (DGC) method. The DGC method makes it possible to use the MOPITT retrieval algorithm to retrieve tropospheric CO from interferometer observations. More details on the DGC method and its applications can be found in Wang et al. (1999a). MOPITT CO measurements contain three pieces of independent information, which lead to a vertical resolution of 3–4 km in the troposphere. More detailed information on the MOPITT weighting functions and averaging kernels can be found in the paper by Pan et al. (1998).

Radiosonde temperature and H2O profiles at the closest radiosonde station at Valley, Nebraska (41.30°N, 96.36°W; used as ancillary data in the retrieval), the first-guess CO profile, and the retrieved CO profile are plotted in Fig. 7. The first-guess CO profile is an average of 152 CO profiles assembled from previous aircraft in situ measurements, primarily from the TROPOZ II experiment (Marenco 1994), the STRATOZ III experiment (Marenco and Prieur 1989), and the TRACE-A experiment (Chatfield et al. 1996; Collins et al. 1996; Thompson et al. 1996). The retrieval results indicate relatively high CO levels in the troposphere at the time and location of IMG6. Since the location of IMG6 is only about 20 km from Omaha, Nebraska, and is downwind of other big cities, urban pollution may have contributed to the high CO levels. Measurements by the Douglas County Health Department of Omaha on 28 January 1997 showed a 24-h average surface CO level of 529 ppbv (T. Baker 1999, private communication). Therefore, a CO level of 200–250 ppbv at IMG6, about 20 km from Omaha, is possible. These CO data are available for download at the AIRSdata Web site (http://www.epa.gov/airsdata) of the United States Environmental Protection Agency.

As a further check on the retrieved CO amount, we have calculated the synthetic radiance spectrum using FASCOD3 (Clough et al. 1992; Wang et al. 1996) with the retrieved CO profile and temperature and H2O profiles measured at the closest radiosonde station at Valley, Nebraska (41.30°N, 96.36°W). The FASCOD3 monochromatic radiance spectrum was convolved with the IMG instrument function. Figure 8 shows the direct comparison and residuals between IMG observed spectrum and FASCOD3 calculated spectrum from 2140.0 to 2194.0 cm−1. The top panel shows the direct comparison of the spectral radiance. The bottom panel shows the residuals. Figure 9 presents a closeup look at the CO line centered at 2165.6 cm−1. Both Figs. 8 and 9 show that the residuals are comparable to instrument noise, especially for the CO lines. The residuals are somewhat larger for the H2O lines. This could be caused by the fact that the radiosonde H2O measurement at Valley, Nebraska, is not the same as the H2O profile at the IMG6 location because tropospheric H2O are highly variable. H2O profile and other ancillary data errors also contribute to CO retrieval errors as described in Wang et al. (1999b). Therefore, H2O profile errors also contribute to the residuals for the CO lines. The calculated surface radiance level also agrees with the measurement to the instrument noise level, which is consistent with clear (or nearly clear) sky conditions for IMG observation at IMG6.

5. Summary and comments

We have analyzed the IMG spectral radiance measurements during WINCE as a case study to demonstrate the application of IMG measurements for tropospheric CO retrieval and MOPITT retrieval algorithm validation. Urban pollution at Omaha, Nebraska, may explain the high CO levels. Synthetic radiance spectrum using retrieved CO amount agrees well with the IMG radiance spectrum with residuals generally comparable to instrument noise.

MAS observations were used successfully to assist in cloud detection and classification. This was a useful test for future application of MODIS observations in MOPITT cloud detection and clearing. Since both MOPITT and MODIS were launched on the same EOS Terra spacecraft in 1999, there will be good spatial and temporal coincidence of MOPITT and MODIS observations. MODIS observations and cloud products will be carefully evaluated for use in MOPITT operational data processing.

Acknowledgments

We want to thank the IMG team, in particular Drs. Hirokazu Kobayashi and Hidemichi, for making the WINCE IMG data available to us for this study. We want to thank Mr. Tom Baker of the Douglas County Health Department of Omaha, Nebraska, for providing information on CO measurements at Omaha on 28 January 1997. The NCAR MOPITT project is supported by the National Aeronautics and Space Administration (NASA) Earth Observing System (EOS) Program. The National Center for Atmospheric Research (NCAR) is sponsored by the National Science Foundation.

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  • Smith, W. L., H. E. Revercomb, H. B. Howell, and H. M. Woolf, 1983: HIS—A satellite instrument to observe temperature and moisture profiles with high vertical resolution. Preprints, Fifth Conf. on Atmospheric Radiation, Baltimore, MD, Amer. Meteor. Soc., 1–9.

  • Talbot, R. W., and Coauthors, 1999: Influence of biomass combustion emissions on the distribution of acidic trace gases over the southern Pacific basin during austral springtime. J. Geophys. Res.,104 (D5), 5623–5634.

    • Crossref
    • Export Citation
  • Taylor, F. W., 1993: Pressure modulator radiometry. Spectroscopic Techniques. G. A. Vanasse, Ed., Vol. 3, Academic Press, 137–197.

    • Crossref
    • Export Citation
  • Thompson, A. M., and Coauthors, 1996: Where did tropospheric ozone over southern Africa and the tropical Atlantic come from in October 1992? Insights from ROMS, GTE TRACE A, and SAFARI 1992. J. Geophys. Res.,101 (D19), 24 251–24 278.

    • Crossref
    • Export Citation
  • Wang, J., G. P. Anderson, H. E. Revercomb, and R. O. Knuteson, 1996: Validation of FASCOD3 and MODTRAN3: Comparison of model calculations with ground-based and airborne interferometer observations under clear-sky conditions. Appl. Opt.,35, 6028–6040.

    • Crossref
    • Export Citation
  • ——, J. C. Gille, P. L. Bailey, L. Pan, D. Edwards, and J. R. Drummond, 1999a: Retrieval of tropospheric carbon monoxide profiles from high-resolution interferometer observations: A new digital gas correlation (DGC) method and applications. J. Atmos. Sci.,56, 219–232.

    • Crossref
    • Export Citation
  • ——, ——, ——, J. R. Drummond, and L. Pan, 1999b: Instrument sensitivity and error analysis for the remote sensing of tropospheric carbon monoxide by MOPITT. J. Atmos. Oceanic Technol.,16, 465–474.

    • Crossref
    • Export Citation

Fig. 1.
Fig. 1.

Illustration of IMG IFOV. The IFOV consists of three separate 8 km × 8 km squares with 4-km spacing. The numbers (1–13) are IFOV geolocation points used by the IMG data processing system

Citation: Journal of Atmospheric and Oceanic Technology 17, 10; 10.1175/1520-0426(2000)017<1285:VSOTMR>2.0.CO;2

Fig. 2.
Fig. 2.

Illustration of IMG observation and calibration sequence and duration. Each cycle (six atmosphere, one deep space, and one blackbody observation) takes 110 s

Citation: Journal of Atmospheric and Oceanic Technology 17, 10; 10.1175/1520-0426(2000)017<1285:VSOTMR>2.0.CO;2

Fig. 3.
Fig. 3.

IMG observation points during WINCE overflight and ER-2 flight track overlaid on GOES-8 visible image (courtesy of K. Strabala from the University of Wisconsin)

Citation: Journal of Atmospheric and Oceanic Technology 17, 10; 10.1175/1520-0426(2000)017<1285:VSOTMR>2.0.CO;2

Fig. 4.
Fig. 4.

IMG spectral radiance measurements for observations IMG1, IMG3, IMG5, and IMG6 with the MOPITT thermal band-filter profile overlaid on the plots. Observations 1 and 3 are believed to be under cloudy conditions, as indicated by the low radiance level and shallow CO absorption. Observation 6 (at IMG6) is believed to be under clear-sky conditions, as indicated by the high radiance level and deeper CO absorption. This has also been confirmed with MAS observations from the ER-2 platform underflying the ADEOS satellite

Citation: Journal of Atmospheric and Oceanic Technology 17, 10; 10.1175/1520-0426(2000)017<1285:VSOTMR>2.0.CO;2

Fig. 5.
Fig. 5.

Apparent reflectance map of MAS band 23 (2.29 μm) over IMG5 location at 42.9°N, 98.0°W. The image covers a MAS observation area of 37.2 km by 37.2 km. The IMG band-2 FOV is marked by a 8 km by 8 km square on the middle-right side of the image. The right panel shows a scatterplot of MAS band-45 brightness temperature as a function of MAS band-2 reflectance. The reflectance map clearly shows that a band of cloud exists across the middle of the image with a relatively high apparent reflectance of about 0.20

Citation: Journal of Atmospheric and Oceanic Technology 17, 10; 10.1175/1520-0426(2000)017<1285:VSOTMR>2.0.CO;2

Fig. 6.
Fig. 6.

Apparent reflectance map of MAS band 23 (2.29 μm) over IMG6 location at 42.2°N, 98.2°W. Again, the image covers a MAS observation area of 37.2 km by 37.2 km. The IMG band-2 FOV is marked by a 8 km by 8 km square on the middle-right side of the image. The land surface features are clearly visible, and there are no obvious cloud features. The scatterplot for the IMG FOV region shows higher band-45 brightness temperature and lower band-2 reflectance

Citation: Journal of Atmospheric and Oceanic Technology 17, 10; 10.1175/1520-0426(2000)017<1285:VSOTMR>2.0.CO;2

Fig. 7.
Fig. 7.

Plots of radiosonde temperature and water vapor profiles at Valley, NE (41.30°N, 96.36°W) on 28 Jan 1997, first-guess CO profile, and retrieved CO profile using IMG observation at IMG6, as shown in Fig. 3. The first-guess profile is the average of 152 profiles assembled from aircraft in situ measurements

Citation: Journal of Atmospheric and Oceanic Technology 17, 10; 10.1175/1520-0426(2000)017<1285:VSOTMR>2.0.CO;2

Fig. 8.
Fig. 8.

Comparison between IMG-observed spectral radiance spectrum and FASCOD3-calculated spectral radiance spectrum from 2140.0 to 2194.0 cm−1. Top panel shows the direct comparison of the spectral radiance. The bottom panel shows the residuals. The retrieved CO, temperature, and water vapor profiles measured by the closest radiosonde station at Valley, NE (41.30°N, 96.36°W), are used in the calculation by FASCOD3. For other gases, U.S. Standard Atmosphere, 1976 data are used

Citation: Journal of Atmospheric and Oceanic Technology 17, 10; 10.1175/1520-0426(2000)017<1285:VSOTMR>2.0.CO;2

Fig. 9.
Fig. 9.

A closeup look of the comparison between the IMG-observed spectral radiance and FASCOD3-calculated spectral radiance for CO line at 2165.6 cm−1. Top panel shows the direct comparison of the spectral radiance. The bottom panel shows the residuals. The residuals are generally comparable with instrument noise

Citation: Journal of Atmospheric and Oceanic Technology 17, 10; 10.1175/1520-0426(2000)017<1285:VSOTMR>2.0.CO;2

Table 1.

Characteristics of MOPITT CO and CH4 channels. There are four CO thermal channels, two CO solar channels, and two CH4 solar channels. The nominal PMC and LMC cell pressure, temperature, and length are also listed. Numbers in parenthesis are full-width at half-maximum (FWHM) of the bandpass filters

Table 1.
Table 2.

IMG instrument characteristics. Spectral range from 714 to 3030 cm−1 covered by the three IMG bands. Band 2 overlaps the MOPITT CO thermal band from 2140 to 2194 cm−1 (FWHM). OPD is the optical path difference

Table 2.
Save
  • Ackerman, S. A., K. L. Strabala, W. P. Menzel, R. A. Frey, C. C. Moeller, and L. E. Gumley, 1998: Discriminating clear sky from clouds with MODIS. J. Geophys. Res.,103 (D24) 32 141–32 157.

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  • Brasseur, G. P., D. A. Hauglustaine, S. Walters, P. J. Rasch, J.-F. Muller, C. Granier, and X. X. Tie, 1998: MOZART, a global chemical transport model for ozone and related chemical tracers. 1: Model description. J. Geophys. Res.,103 (D21), 28 265–28 289.

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  • Chatfield, R. B., J. A. Vastano, H. B. Singh, and G. Sachse, 1996: A general model of how fire emissions and chemistry produce African/oceanic plumes (O3, CO, PAN, smoke) in TRACE A. J. Geophys. Res.,101 (D19), 24 279–24 306.

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  • Clough, S. A., M. J. Iacono, and J.-L. Moncet, 1992: Line-by-line calculations of atmospheric fluxes and cooling rates: Application to water vapor. J. Geophys. Res.,97 (D14), 15 761–15 785.

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  • Collins, J. E., B. E. Anderson, G. W. Sachse, J. D. W. Barrick, L. O. Wade, L. G. Burney, and G. F. Hill, 1996: Atmospheric fine structure during GTE TRACE A: Relationships among ozone, carbon monoxide, and water vapor. J. Geophys. Res.,101 (D19), 24 307–24 316.

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  • Drummond, J. R., and G. S. Mand, 1996: The Measurements of Pollution in the Troposphere (MOPITT) instrument: Overall performance and calibration requirements. J. Atmos. Oceanic Technol.,13, 314–320.

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  • Edwards, D. P., C. Halvorson, and J. C. Gille, 1999: Radiative transfer modeling for the EOS Terra Satellite Measurement of Pollution in the Troposphere (MOPITT) instrument. J. Geophys. Res.,104, 16 755–16 775.

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  • Francey, R. J., and Coauthors, 1996: Global Atmospheric Sampling Laboratory (GASLAB): Supporting and extending the Cape Grim trace gas programs. Baseline Atmospheric Program Australia, R. J. Francey, A. L. Dick, and N. Derek, Eds., Bureau of Meteorology and CSIRO Division of Atmospheric Research, 8–29.

  • Gregory, G. L., and Coauthors, 1999: Chemical characteristics of Pacific tropospheric air in the region of the Intertropical Convergence Zone and South Pacific Convergence Zone. J. Geophys. Res.,104 (D5), 5677–5696.

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  • Hoell, J. M., and Coauthors, 1999: Pacific Exploratory Mission in the tropical Pacific: PEM-Tropics A, August–September 1996. J. Geophys. Res.,104 (D5), 5567–5583.

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  • Jacob, D. J., 1998: The oxidizing power of the atmosphere. Handbook of Weather, Climate and Water, T. Potter and B. Colman, Eds., McGraw-Hill, in press.

  • King, M. D., Y. J. Kaufman, W. P. Menzel, and D. Tanre, 1992: Remote sensing of cloud, aerosol, and water vapor properties from MODIS. IEEE Trans. Geosci. Remote Sens.,30, 2–27.

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  • ——, and Coauthors, 1996: Airborne scanning spectrometer for remote sensing of cloud, aerosol, water vapor, and surface properties. J. Atmos. Oceanic Technol.,13, 777–794.

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  • Kobayashi, H., and Coauthors, 1998: IMG, precursor of the high-resolution FTIR on the satellite. Optical Remote Sensing of the Atmosphere and Clouds, J. Wang, B. Wu, T. Ogawa, and Z.-H. Guan, Eds., SPIE Proceedings, Vol. 3501, 23–33.

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  • Langenfelds, R. L., and Coauthors, 1996: Improved vertical sampling of the trace gas composition of the troposphere above Cape Grim since 1991. Baseline Atmospheric Program Australia. 1993 ed., R. J. Francey, A. L. Dick, and N. Derek, Eds., Bureau of Meteorology and CSIRO Division of Atmospheric Research, 46–57.

  • Logan, J. A., M. J. Prather, S. C. Wofsy, and M. B. McElroy, 1981:Tropospheric chemistry: A global perspective. J. Geophys. Res.,86, 7210–7254.

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  • Marenco, A. M., 1994: The airborne programmes Stratoz and Tropoz:A study of atmospheric chemistry on regional and global scale. Int. Symp.: Space, Aeronautics and Atmospheric Environment, Toulouse, France, Météo-France, 193–209.

  • ——, and S. Prieur, 1989: Meridional and vertical CO and CH4 distributions in the background troposphere (70°N–60°S; 0–12 km altitude) from scientific aircraft measurements during the STRATOZ-3 experiment (June 1984). Atmos. Environ.,23, 185–200.

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  • ——, K. A. Masarie, P. P. Tans, and P. M. Lang, 1994: Recent changes in atmospheric carbon monoxide. Science,263, 587–1590.

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  • Ogawa, T., H. Shimoda, M. Hayashi, R. Imasu, A. Ono, S. Nishinomiya, and H. Kobayashi, 1994: IMG, Interferometric measurement of greenhouse gases from space. Adv. Space Res.,14, 25–28.

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  • Pan, L., J. C. Gille, D. P. Edwards, P. L. Bailey, and C. D. Rodgers, 1998: Retrieval of tropospheric carbon monoxide for the MOPITT experiment. J. Geophys. Res.,103, 32 277–32 290.

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  • Reichle, H. G., Jr., and Coauthors, 1986: Middle and upper tropospheric carbon monoxide mixing ratios as measured by a satellite-borne remote sensor during November 1981. J. Geophys. Res.,91, 10 865–10 887.

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  • ——, and Coauthors, 1999: Space shuttle based global CO measurements during April and October 1994, MAPS instrument, data reduction, and data validation. J. Geophys. Res.,104, 21 443–21 454.

  • Rodgers, C. D., 1976: Retrieval of atmospheric temperature and composition from remote measurements of thermal radiation. Rev. Geophys. Space Phys.,14, 609–624.

    • Crossref
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  • Smith, W. L., H. E. Revercomb, H. B. Howell, and H. M. Woolf, 1983: HIS—A satellite instrument to observe temperature and moisture profiles with high vertical resolution. Preprints, Fifth Conf. on Atmospheric Radiation, Baltimore, MD, Amer. Meteor. Soc., 1–9.

  • Talbot, R. W., and Coauthors, 1999: Influence of biomass combustion emissions on the distribution of acidic trace gases over the southern Pacific basin during austral springtime. J. Geophys. Res.,104 (D5), 5623–5634.

    • Crossref
    • Export Citation
  • Taylor, F. W., 1993: Pressure modulator radiometry. Spectroscopic Techniques. G. A. Vanasse, Ed., Vol. 3, Academic Press, 137–197.

    • Crossref
    • Export Citation
  • Thompson, A. M., and Coauthors, 1996: Where did tropospheric ozone over southern Africa and the tropical Atlantic come from in October 1992? Insights from ROMS, GTE TRACE A, and SAFARI 1992. J. Geophys. Res.,101 (D19), 24 251–24 278.

    • Crossref
    • Export Citation
  • Wang, J., G. P. Anderson, H. E. Revercomb, and R. O. Knuteson, 1996: Validation of FASCOD3 and MODTRAN3: Comparison of model calculations with ground-based and airborne interferometer observations under clear-sky conditions. Appl. Opt.,35, 6028–6040.

    • Crossref
    • Export Citation
  • ——, J. C. Gille, P. L. Bailey, L. Pan, D. Edwards, and J. R. Drummond, 1999a: Retrieval of tropospheric carbon monoxide profiles from high-resolution interferometer observations: A new digital gas correlation (DGC) method and applications. J. Atmos. Sci.,56, 219–232.

    • Crossref
    • Export Citation
  • ——, ——, ——, J. R. Drummond, and L. Pan, 1999b: Instrument sensitivity and error analysis for the remote sensing of tropospheric carbon monoxide by MOPITT. J. Atmos. Oceanic Technol.,16, 465–474.

    • Crossref
    • Export Citation
  • Fig. 1.

    Illustration of IMG IFOV. The IFOV consists of three separate 8 km × 8 km squares with 4-km spacing. The numbers (1–13) are IFOV geolocation points used by the IMG data processing system

  • Fig. 2.

    Illustration of IMG observation and calibration sequence and duration. Each cycle (six atmosphere, one deep space, and one blackbody observation) takes 110 s

  • Fig. 3.

    IMG observation points during WINCE overflight and ER-2 flight track overlaid on GOES-8 visible image (courtesy of K. Strabala from the University of Wisconsin)

  • Fig. 4.

    IMG spectral radiance measurements for observations IMG1, IMG3, IMG5, and IMG6 with the MOPITT thermal band-filter profile overlaid on the plots. Observations 1 and 3 are believed to be under cloudy conditions, as indicated by the low radiance level and shallow CO absorption. Observation 6 (at IMG6) is believed to be under clear-sky conditions, as indicated by the high radiance level and deeper CO absorption. This has also been confirmed with MAS observations from the ER-2 platform underflying the ADEOS satellite

  • Fig. 5.

    Apparent reflectance map of MAS band 23 (2.29 μm) over IMG5 location at 42.9°N, 98.0°W. The image covers a MAS observation area of 37.2 km by 37.2 km. The IMG band-2 FOV is marked by a 8 km by 8 km square on the middle-right side of the image. The right panel shows a scatterplot of MAS band-45 brightness temperature as a function of MAS band-2 reflectance. The reflectance map clearly shows that a band of cloud exists across the middle of the image with a relatively high apparent reflectance of about 0.20

  • Fig. 6.

    Apparent reflectance map of MAS band 23 (2.29 μm) over IMG6 location at 42.2°N, 98.2°W. Again, the image covers a MAS observation area of 37.2 km by 37.2 km. The IMG band-2 FOV is marked by a 8 km by 8 km square on the middle-right side of the image. The land surface features are clearly visible, and there are no obvious cloud features. The scatterplot for the IMG FOV region shows higher band-45 brightness temperature and lower band-2 reflectance

  • Fig. 7.

    Plots of radiosonde temperature and water vapor profiles at Valley, NE (41.30°N, 96.36°W) on 28 Jan 1997, first-guess CO profile, and retrieved CO profile using IMG observation at IMG6, as shown in Fig. 3. The first-guess profile is the average of 152 profiles assembled from aircraft in situ measurements

  • Fig. 8.

    Comparison between IMG-observed spectral radiance spectrum and FASCOD3-calculated spectral radiance spectrum from 2140.0 to 2194.0 cm−1. Top panel shows the direct comparison of the spectral radiance. The bottom panel shows the residuals. The retrieved CO, temperature, and water vapor profiles measured by the closest radiosonde station at Valley, NE (41.30°N, 96.36°W), are used in the calculation by FASCOD3. For other gases, U.S. Standard Atmosphere, 1976 data are used

  • Fig. 9.

    A closeup look of the comparison between the IMG-observed spectral radiance and FASCOD3-calculated spectral radiance for CO line at 2165.6 cm−1. Top panel shows the direct comparison of the spectral radiance. The bottom panel shows the residuals. The residuals are generally comparable with instrument noise

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