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JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 112, D24S45, doi:10.1029/2007JD008787, 2007
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Ozone columns obtained by ground-based remote
sensing in Kiev for Aura Ozone Measuring
Instrument validation
A. V. Shavrina,1 Y. V. Pavlenko,1 A. Veles,1 I. Syniavskyi,1 and M. Kroon2
Received 12 April 2007; revised 16 July 2007; accepted 12 November 2007; published 22 December 2007.
[1] Ground-based observations with a Fourier transform spectrometer in the infrared
region (FTIR) were performed in Kiev (Ukraine) during the time frames August–October
2005 and June–October 2006 within the Ozone Monitoring Instrument (OMI) validation
project 2907 entitled ‘‘OMI validation by ground based remote sensing: ozone columns
and profiles’’ in the frame of the international European Space Agency/Netherlands
Agency for Aerospace Programmes/Royal Dutch Meteorological Institute OMI
Announcement of Opportunity effort. Ozone column data for 2005 were obtained by
modeling the ozone spectral band at 9.6 mm with the radiative transfer code
MODTRAN3.5. Our total ozone column values were found to be lower than OMI
Differential Optical Absorption Spectroscopy (DOAS) total ozone column data by 8–10
Dobson units (DU, 1 DU = 0.001 atm cm) on average, while our observations have a
relatively small standard error of about 2 DU. Improved modeling of the ozone spectral
band, now based on HITRAN-2004 spectral data as calculated by us, moves our
results toward better agreement with the OMI DOAS total ozone column data. The
observations made during 2006 with a modernized FTIR spectrometer and higher
signal-to-noise ratio were simulated by the MODTRAN4 model computations. For ozone
column estimates the Aqua Atmospheric Infrared Sounder satellite water vapor and
temperature profiles were combined with the Aura Microwave Limb Sounder stratospheric
ozone profiles and Tropospheric Emission Monitoring Internet Service-Koninklijk
Nederlands Meteorologisch Instituut climatological profiles to create a priori input files for
spectral modeling. The MODTRAN4 estimates of ozone columns from the 2006
observations compare rather well with the OMI total ozone column data: standard errors
are of 1.11 DU and 0.68 DU, standard deviation are of 8.77 DU and 5.37 DU for OMI
DOAS and OMI Total Ozone Mapping Spectrometer, respectively.
Citation: Shavrina, A. V., Y. V. Pavlenko, A. Veles, I. Syniavskyi, and M. Kroon (2007), Ozone columns obtained by ground-based
remote sensing in Kiev for Aura Ozone Measuring Instrument validation, J. Geophys. Res., 112, D24S45, doi:10.1029/2007JD008787.
1. Introduction
[2] It is common knowledge that the stratospheric ozone
layer is very important for sustaining life on Earth. The
ozone layer protects life on Earth from the harmful and
damaging ultraviolet solar radiation. Ozone in the lower
atmosphere, or troposphere, is also an important greenhouse
gas. Ozone is not emitted directly by any natural source.
However, tropospheric ozone is formed under high ultraviolet flux conditions from natural and anthropogenic emissions of nitrogen oxides (NOx), volatile organic compounds
(VOCs), methane and carbon monoxide. The assessment of
the ozone warming potential is a difficult task since both
temporal and spatial distributions should be taken into
1
Main Astronomical Observatory, National Academy of Sciences of
Ukraine, Kiev, Ukraine.
2
Royal Netherlands Meteorological Institute, De Bilt, Netherlands.
Copyright 2007 by the American Geophysical Union.
0148-0227/07/2007JD008787$09.00
account. Marenco et al. [1994] computed a relative radiative
forcing for ozone at least 1200 times higher than for carbon
dioxide (CO2), much higher than the other greenhouse gases
except for chlorofluorocarbons (CFCs) which range up to
5800 times the radiative forcing of CO2. However, the
emissions of CFCs are expected to decrease to near zero
in the next decades following international agreements on
phase-out measures. In this way, ozone becomes (most
probably after 50 years) the most important contributor in
the greenhouse effect after carbon dioxide and methane.
With its current concentrations, ozone would contribute
22% of the global warming in the Northern Hemisphere
and 13% in the Southern Hemisphere.
[3] Remote sensing is used to quantify and understand
key processes in the global ozone budgets. At the presentday, satellite remote sensing observations are widely available for total ozone column and ozone atmospheric profiles.
Nevertheless, ground-based monitoring is needed to validate and complement space-based measurements and to
clarify local/regional specific sources and sinks of this
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important gas. Space and ground-based observations in
synergy enable studies of the dynamical behavior of atmospheric trace gases and air pollution and to check compliance to the pollution transport models. These observations
will also serve the development of environmental policies,
with greenhouse gas regulation policies in particular, on a
local and regional scale. Our first attempts to retrieve total
ozone columns from the observations by our Fourier transform spectrometer in the infrared region (FTIR) instrument
from the Main Astronomical Observatory of the National
Academy of Sciences of Ukraine was successful [Shavrina
and Veles, 2004]. This success allowed to us to submit our
proposal 2907 entitled ‘‘OMI validation by ground based
remote sensing ozone columns and profiles’’ in response to
the International Ozone Monitoring Instrument (OMI) Announcement of Opportunity call, where it was accepted.
2. FTIR Spectrometer for Atmospheric
Monitoring
[4] Our work is performed with a Fourier transform
infrared (FTIR) spectrometer, model ‘‘Inralum FT 801,’’
which was modernized for the task of monitoring the
atmosphere by direct sun observations. The ‘‘double cat
eye’’ interferometer scheme [Egevskaya et al., 2001] is
shown in Figure 1. The main advantage of this device is
its small size and small sensitivity of the optical arrangement
to vibrations. The working spectral range of the FTIR
spectrometer is 2 – 12 mm (800– 5000 cm1) with the highest
possible spectral resolution of about 1.0 cm1. The accuracy
of the wavelength calibration in the FTIR spectra is determined by the stability of the wavelengths of a helium-neon
laser used as the reference source of light in the reference
channel. The corresponding accuracy is 0.001 cm1. The
exposure time needed to obtain one experimental spectrum
is roughly 3 s. When obtaining the 2005 data set, we
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averaged 6 – 8 spectra obtained within 1.5– 2 min to improve signal-to-noise ratio (S/N) to exceed 100. Following
the modernization in 2006 of our Fourier spectrometer and
the software for the initial treatment of the registered
spectra, the system now allows us to average 2 – 99 individual spectra during the observation period. We averaged
4 single spectra as was recommended by the developers of
the spectrometer device to avoid a degradation of the
averaged spectrum due to the recording of atmospheric
instabilities at longer exposure times. Our averaged spectra
have S/N of 150 –200. We registered 3 – 4 averaged spectra
during 2 –3 min of recording time. Prior to further treatment
of observed spectra we checked the repeatability of these
3– 4 spectra and choose the spectrum with the best S/N to
be fitted with the model spectra ([Egevskaya et al., 2001]).
[5] Direct sun observations of solar radiation transmitted
through the Earth’s atmosphere were performed with the
FTIR spectrometer during the time periods August – October
2005 and June– November 2006 at the Main Astronomical
Observatory (MAO), National Academy of Sciences of
Ukraine (NASU). The geographical coordinates of the
Observatory are 50°21050.9000N and 30°29051.3400E, located
at 186 m above sea level.
[6] In 2005, the spectral resolution of the setup was 4.0
cm1. Following a major system update, the FTIR spectrometer was operated with an improved spectral resolution
of 2.0 cm1 and a higher S/N ratio of 130– 200 during the
observational period of June –November 2006. On sunny
days with clear skies, observations were made during
daylight over a wide range of solar zenith angles (from
26° up to 84°). Starting from July 2006, the Ozone Analyzer
Thermo Environmental, Model 49 UV, for performing
‘‘surface’’ ozone measurements was operating at the same
location as the FTIR spectrometer, namely, on the roof of
the observatory building. An example of the observed
spectra on 27 June 2006, when measurements were per-
Figure 1. Structural and optical scheme of the FTIR spectrometer: 1, fast lens; 2, 4, ellipsoids for shift
of image; 3, interferometer; 5, detector; 6, electronics block.
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formed from 0847 LT up to 1905 LT (z = 30.26 –72.80°,
resolution of 2.0 cm1) is shown in Figure 2.
3. MODTRAN Spectral Modeling
[7] The vertical column amounts of ozone molecules
were retrieved with the help of the radiative transfer code
MODTRAN3.5 [Abreu and Anderson, 1996] from the
observations of 2005. MODTRAN4.3 (MODTRAN4 Version 3 Revision 1 [Berk et al., 1999]) was provided to us in
the autumn 2006 and was used for modeling of the
observations of 2006. Both codes use a moderate spectral
resolution model of optical transmission, described by
Abreu and Anderson [1996] and Bernstein et al. [1996].
MODTRAN4.3 has new options for modeling atmospheric
radiation transport and other improvements [Berk et al.,
1999]. MODTRAN3.5 band model was based on HITRAN96 molecular data [Rothman et al., 1998]; MODTRAN4.3
uses HITRAN-2001 (http://www.vs.afrl.af.mil/ProductLines/IR-Clutter/modtran4.aspx). The codes are widely applied to the interpretation of ground based, airborne and
space-borne remote observations of the Earth’s atmospheric
spectra. These programs calculate the atmospheric transmission and irradiation at electromagnetic radiation frequencies
from 0 up to 50,000 cm1. The modeling program uses the
spherical source function for solar and moon light scattering
and the standard and user defined model atmospheres. The
users specify the a priori atmospheric profiles of trace gases,
aerosols, clouds, fog and even rain. To model the shape of
molecular absorption bands, both MODTRAN programs
use the so-called ‘‘smeared lines’’ approximation, namely
the band model approximation [Abreu and Anderson, 1996;
Bernstein et al., 1996], instead of line-by-line calculations.
The band model is calculated once as molecular absorption
in 1 cm1 spectral bins for six temperatures and standard
pressure. The computed table is further applied to calculate
the shape of molecular bands in model spectra using
temperature interpolation and pressure correction. The calculation of the band model is based on a large array of
Figure 3. Comparison of MODTRAN (band model) and
FASCODE (line-by-line) spectral radiance calculation for
ozone 9.6 mm band [from Bernstein et al., 1996]. We estimate
the value of the sample variance of these two spectra fit in the
range of 981– 1078 cm1 as 6.9 104. Please, consult the
text of section 3 for further explanation.
previously accumulated data of spectral lines in the
HITRAN database for 12 molecules (H2O, CO2, O3, N2O,
CO, CH4, O2, NO, SO2, NO2, NH4, and HNO3). In
addition, the programs account for optical spectral absorption by heavy molecules: CFC (9 molecules) and ClONO2,
HNO4, CCl4, and N2O5). The calculations are performed in
local thermodynamic equilibrium (LTE) approximation for
the moderate spectral resolution (2.0 cm1) which fortunately corresponds to the resolution of our observed FTIR
spectra.
[8] For the new set of spectral data recorded during 2006,
the model spectra were calculated with MODTRAN4 code
[Berk et al., 1999] and new band model input file which was
prepared by us based on the HITRAN-2004 database of
Rothman et al. [2005], the most recent and more complete
molecular line database. The band model parameters, namely,
average absorption coefficient S/d and line density parameter
1/d were calculated as defined by Bernstein et al. [1996]
S=d ¼ SSj =Dw;
2
1=d ¼ SSj0:5 =SSj =Dw;
Figure 2. A selection of FTIR spectra recorded on the
27 June 2006. Observations started at 0847 LT and ended at
1905 LT (z = 30.26 – 72.80°, resolution R = 2.0 cm1). Each
spectrum takes roughly 3 s to record. The ozone band is
located at 9.6 mm or 1042 cm1.
where Sj is the temperature-dependent line strength, Dw is
the width of the spectral interval (Dw = 1 cm1 in this
study), and the summation includes only lines within the
interval.
[9] In Figure 3 we show the spectra of the ozone band at
9.6 mm calculated with MODTRAN3 and FASCODE (lineby-line modeling) from Bernstein et al. [1996]. (The code
FASCODE is not available for us, our own line-by-line code
is now under development.) We estimate the value of the
sample variance S of these two spectra fit in the range of
981– 1078 cm1 as S = S(Fobs Fcomp)2/N = 6.9 104,
where Fobs, Fcomp are the observed and computed residual
intensities, N is the number of considered wavelengths. In
the following, we use this value of S as our coincidence
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Figure 4. (top) Time series of OMI total ozone (OMI TOMS and OMI DOAS) and ground-based FTIR
total ozone data for 2005. (bottom) Time series of difference between satellite and ground-based ozone
columns. Average difference of satellite minus ground-based amounts to 8.45 DU and 3.19 DU for OMI
DOAS and OMI TOMS respectively, with a 10.50 DU and 13.41 DU standard deviation (1.98 DU and
2.53 DU standard errors).
criterion to choose the best fits of our model spectra to the
observed ozone bands in the minimization procedure.
4. Input Profiles for Modeling
[10] Measurements of surface ozone concentrations by
the collocated ozonometer together with data from the
Atmospheric Infrared Sounder instrument aboard NASA
EOS-Aqua (AIRS, http://disc.gsfc.nasa.gov/AIRS/) and the
Microwave Limb Sounder (MLS) aboard EOS Aura (http://
avdc.gsfc.nasa.gov/Data/Aura/) were used for construction
of atmospheric ozone, temperature and water vapor input
profiles for the MODTRAN4.3 code. We used the level 3
daily data products of AIRS to obtain water vapor profiles,
temperature profiles and geopotential height estimates at 24
standard pressure levels over the location of MAO in Kiev.
The level 3 files contain geophysical parameters averaged
and binned into 1° 1° grid cells. Grid maps correspond to
180.0° to +180.0° of longitude starting from zero meridional (Greenwich) to the west and the east correspondingly
and are separated into the ascending (A) and descending (D)
portion of the satellite orbit, where ‘‘ascending or descending’’ refers to the directions of the subsatellite points on the
satellite tracks at the equatorial crossing. The level 3 daily
files are provided in the Hierarchical Data Format (HDF)EOS format. To extract data from the HDF files for the
location of MAO in Kiev (latitude 50°210900N, longitude
30°300E), the software package MathLab 6.5 was used.
[11] AIRS vertical profiles of water vapor at 12 atmospheric layers, labeled H2OVapMMRA and H2OVapMMRD
(ascending and descending, respectively) are reported as
water vapor mass mixing ratio (gm/kg dry air). Temperature
profiles are reported in Kelvin at 24 standard pressure
levels, labeled temperatureA and temperatureD. Geopotential
heights are reported in meters at 24 standard pressure levels,
labeled GPHeightA and GPHeightD. These data were used to
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construct the MODTRAN temperature and water vapor
input profiles for each observing day. MLS data over the
location of the MAO observatory in Kiev were downloaded
as ASCII files from the ‘‘station overpass’’ section from the
Aura Validation Data Center (AVDC) (http://avdc.gsfc.
nasa.gov/Data/Aura/). Station overpass data files contain
satellite data observations spatially collocated with the
ground station coordinates ±5° in latitude and ±8° in
longitude. The downloaded MLS data product was ozone
profiles (MLS-L2GP-03) of version V1.5. The data for Kiev
are of 6 – 8 profiles typically per day and were averaged for
each day of the observations. Prior to using MLS data we
downloaded the ‘‘Version 1.5 level 2 data quality and
description document’’ (v1-5-report-29jul05b.pdf) from
the MLS Web site. The MSL ozone profiles were used over
the range 215– 0.46 hPa were the L2gpPrecision field was
taken into account as a weighing factor. We also interpolated these data for the exact coordinates of the point of
observation (MAO NASU). These profiles differ from
averaged very little. We preferred the averaged ozone
profiles due to the rather low precision of MLS v1.5 data.
From these data together with the Tropospheric Emission
Monitoring Internet Service (TEMIS) climatological ozone
profiles (http://www.temis.nl/data/fortuin.html), the ozone
input files for the MODTRAN modeling were constructed.
AIRS water vapor (H20) data are given for the range 1100 –
150 hPa, and AIRS temperature (T) data are given for the
range 1100 –1.5 hPa. These data sets were expanded by
MODTRAN standard summer water vapor and temperature
profile data for the midlatitude standard model atmosphere.
5. Software Developments
[12] We developed in-house a sophisticated procedure to
analyze the observed ozone spectral band at 9.6 mm. To
obtain the best fit to the observed spectral band, we adhered
to the following procedure:
[13] 1. We use the standard summer or the averaged
summer-winter MODTRAN model atmosphere as a reference model to compute a grid of Earth model atmospheres
with different atmospheric columns and profiles of ozone.
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The construction of ozone input profiles, AIRS water vapor
and CO2 profiles are iterated in the case of a poor fit of model
spectra to the observed spectrum (at the end of the process)
by a procedure in which these profiles are determined by two
parameters: scaling (or fitting) factor and location (altitude)
of the maximum of the molecular densities. Additionally, for
ozone we adopt two parameters determining the curvatures
of upper and lower parts of the profile corresponding to
upper and lower atmosphere layers near the ozone density
maximum.
[14] 2. Using the MODTRAN4 code, we compute a grid
of the theoretical spectra associated with the grid of the
model atmospheres.
[15] 3. To determine the best fit parameters, we compare
the observed and computed spectra with a two-step optimization procedure. First, we determined the best fit to
observed water vapor and CO2 lines in the region 800–
1240 cm1; that is, we exclude the ozone spectral band
from the analysis. Second, we fit the observed spectrum
with the grid of calculated ozone spectral band profiles
using water vapor and CO2 atmospheric profiles selected on
the previous step. We choose the best fit in accordance with
a minimal value of the sample variance.
6. Ozone Column Data Analysis
[16] Ozone columns for various dates in 2005 were
obtained using MODTRAN3.5 [Abreu and Anderson,
1996] modeling of the ozone spectral band shape at
9.6 mm with the original band model based on the
HITRAN-96 database [Rothman et al., 1998]. As mentioned
above, MODTRAN4.3 version was available to us in autumn 2006 only, band model based on HITRAN-2004 was
prepared by us nearly to the same time. We compared our
ozone columns with spatially and temporally collocated
Aura OMI total ozone column data downloaded from the
Aura Validation Data Center, OMDOAO3 level 2 data and
OMTO3 data. The OMDOAO3 data product contains total
ozone and ancillary information produced by the OMI
Differential Optical Absorption Spectroscopy (DOAS) algorithm. The OMI DOAS algorithm is described in the OMI
Table 1. Descriptive Statistics and Regressive Analysis of the Ground-Based FTIR Total Ozone Column Versus the OMI DOAS and
OMI TOMS Total Ozone Column Data for 2005 and 2006
Descriptive Statistics
Mean
Standard Error
Median
Standard Deviation
Sample Variance
Range
Minimum
Maximum
Sum
Count
2005 DOAS FTIR/TOMS FTIR
2006 DOAS FTIR/TOMS FTIR
8.45/3.19
1.98/2.53
10.70/1.45
10.50/13.41
110.19/179.84
38.40/56.60
9.40/18.00
29.00/38.60
236.60/89.40
28/28
0.37/-0.25
1.11/0.68
0.16/0.115
8.77/5.37
76.96/28.89
50.42/27.38
15.98/12.28
34.44/15.1
23.12/15.33
62/62
Regressive Analysis
Slope
Intercept
Correlation
R-squared
FTIR versus DOAS/FTIR versus TOMS
FTIR versus DOAS/FTIR versus TOMS
0.9394/0.6836
10.0179/89.4564
0.7580/0.6007
0.5745/0.3609
1.0727/1.033
22.3545/10.3535
0.95905/0.9846
0.9198/0.9695
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Algorithm Theoretical Basis Document (http://avdc.gsfc.nasa.gov/Data/Aura/OMI/OMDOAO3/ieee-ozonedoas_20050427.pdf). OMTO3 contains total ozone, aerosol
index, and ancillary information produced from the Total
Ozone Mapping Spectrometer (TOMS) Version 8 (V8) algorithm applied to OMI global mode measurements. (http://
avdc.gsfc.nasa.gov/Data/Aura/OMI/OMTO3/OMTO3ReleaseDetails.html). In Table 1 we present the statistical
results of our comparisons. Our total ozone values are found
to be somewhat lower than the OMI-DOAS data by 8 – 10
Dobson units (DU, 1 DU = 0.001 atm cm) on average with a
standard deviation of 10.5 DU (about 3.5%) (see Table 1 and
Figure 4). Our total ozone values have a relatively small
standard error 2 DU. Incorporating our new band model
based on the HITRAN-2004 database [Rothman et al., 2005]
as calculated by us improves the agreement of our ozone
column data with OMI DOAS data to near zero difference on
average with a similar standard deviation. Our total ozone
values are lower than the OMI TOMS data by 3 DU on
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average with a standard deviation of 13.4 DU (about 4%)
and standard error 2.5 DU.
[17] FTIR observations during the time frame July 2006 to
October 2006 with the modernized FTIR spectrometer
provided observations with a much better signal-to-noise
ratio. The recorded spectra were simulated using MODTRAN4.3 and our new band model based on the HITRAN2004. The AIRS’s water vapor and temperature profiles,
Aura MLS stratospheric ozone profiles and TEMIS climatological ozone profiles [Fortuin and Kelder, 1998] were used
for the creation of the a priori input files. The MODTRAN4.3
ozone columns in 2006 fit rather well with OMI TOMS
and OMI DOAS data, see Table 1 and Figure 5. As coincidence criteria we consider the values of standard errors
and standard deviation (Table 1). The standard errors are of
1.11 DU and 0.68 DU with a standard deviation of 8.77 DU
(2.7%) and 5.37 DU (1.8%), for OMI DOAS and OMI
TOMS, respectively. The number of collocated observations
of FTIR and satellite was 28 and 62 in 2005 and 2006,
Figure 5. (top) Time series of the OMI total ozone and the ground based FTIR total ozone data of 2006
for Kiev (MAO). (bottom) Time series of difference of satellite minus ground-based ozone columns.
Average difference of satellite minus ground-based amounts to 0.37 DU and 0.25 DU for OMI DOAS
and OMI TOMS, respectively, with a 8.77 DU and 5.37 DU standard deviation (1.11 DU and 0.68 DU
standard errors).
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respectively. We only found significant differences between
ground-based and satellite observations under conditions of
insufficiently clear skies (clouds).
[18] The total ozone column estimates were in general
obtained from the FTIR spectra observed at lower zenith
angles of the Sun, 1100 to 1400 LT. Their values are mainly
determined by stratospheric ozone profiles, namely by their
maximum heights and widths near the concentration maximum. Their dependence on tropospheric ozone variations
is rather weak.
7. Conclusion
[19] In this paper we have presented our extensive data
record of FTIR direct sun observations and the ozone
columns retrieved from these spectra, covering two periods
in the time frame 2005 – 2006. Our estimates of the total
ozone columns in the 2006 time frame obtained with the
MODTRAN4 modeling agree well with the OMI total
ozone column data. We noted some significant differences
for the data reordered under the insufficiently clear skies
(clouds) which exemplifies the care one must to take to
perform accurate FTIR measurements of the total ozone
column.
[20] The algorithm for automatic modification of the
atmospheric ozone input profiles, particularly tropospheric
profiles requires further development. Our calculations with
the band model of MODTRAN4.3 must be tested through
modeling with the line-by-line radiative transfer code (like
FASCODE). We plan to create such code for the line-by-line
calculations with the HITRAN-2004 molecular line lists and
the available model atmospheres.
[21] Acknowledgments. This work was performed in the framework
of the International ESA/KNMI/NIVR OMI ‘‘Announcement of Opportunity for Calibration and Validation of the Ozone Monitoring Instrument,’’
providing early access to provisional OMI data sets and guidance to public
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OMI data. The Dutch-Finnish built OMI instrument is part of the NASA
EOS Aura satellite payload. The OMI project is managed by NIVR and
KNMI in the Netherlands. Provisional OMI data were obtained from the
NASA Goddard Aura Validation Data Center (AVDC). Public OMI data
were obtained from the NASA Goddard Earth Sciences (GES) Data and
Information Services Center (DISC), home of the GES Distributed Active
Archive Center (DAAC). We thank the AIRS team, the Aura team, the
MLS team, and the TEMIS KNMI team for their data. The work of the
authors from MAO NASU was supported by the grant of STCU.
References
Abreu, L. W., and G. P. Anderson (1996), The MODTRAN 2/3 Report and
LOWTRAN 7 Model, technical report, Ontar Corp., North Andover,
Mass.
Berk, A., G. Anderson, P. Acharya, J. Chetwynd, L. Bernstein, E. Shettle,
M. Matthew, and S. Adler-Golden (1999), MODTRAN4 User’s Manual,
Air Force Res. Lab., Hanscom AFB, Mass.
Bernstein, L. S., A. Berk, P. K. Acharya, D. C. Robertson, G. P. Anderson,
J. H. Chetwynd, and L. M. Kimball (1996), Very narrow band model
calculations of atmospheric fluxes and cooling rates, J. Atmos. Sci., 53,
2887 – 2904.
Egevskaya, T. B., A. M. Vlasov, and A. V. Bublikov (2001), Infrakrasnyj
Fur’e-spectrometr ‘‘infralum FT-801’’, Nauka Proizvodstvu, 12, 38 – 41.
Fortuin, J. P. F., and H. Kelder (1998), An ozone climatology based on
ozonesonde and satellite measurements, J. Geophys. Res., 103(D24),
31,709 – 31,734.
Marenco, A., H. Gouget, P. Nédélec, J.-P. Pagés, and F. Karcher (1994),
Evidence of a long-term increase in tropospheric ozone from Pic du Midi
data series: Consequences: Positive radiative forcing, J. Geophys. Res.,
99(D8), 16,617 – 16,632.
Rothman, L. S., et al. (1998), The HITRAN molecular spectroscopic database and HAWKS (HITRAN Atmospheric Workstation): 1996 edition,
J. Quant. Spectrosc. Radiat. Transfer, 60, 665 – 710.
Rothman, L. S., et al. (2005), The HITRAN 2004 molecular spectroscopic
database, J. Quant. Spectrosc. Radiat. Transfer, 96, 139 – 204.
Shavrina, A. V., and A. A. Veles (2004), Remote sensing of some greenhouse gases by Fourier-spectrometry in Kyiv, J. Quant. Spectrosc. Radiat. Transfer, 88, 345 – 346.
Y. V. Pavlenko, A. V. Shavrina, I. Syniavskyi, and A. Veles, Main
Astronomical Observatory, National Academy of Sciences of Ukraine, 27
Zabolotnoho Street, 03680, Kiev, Ukraine. ([email protected])
M. Kroon, Royal Netherlands Meteorological Institute, P.O. Box 201,
NL-3730 AE De Bilt, Netherlands.
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