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OZONE columns and profiles from ground based FTIR observations
( ESA-NIVR-KNMI project 2907 "OMI validation by ground based remote sensing: ozone columns and atmospheric profiles", 2005-2008)

A.V. Shavrina, Veles A.A., Pavlenko Ya. V., Sinyavski I., Sheminova V.A., Sosonkin M.G., Ivanov Yu.S., Romanyuk Ya. O., Eremenko N.A. (MAO NANU) and M.Kroon (KNMI Netherlands)

Ground-based FTIR observations were performed within the framework of the ESANIVR-KNMI project 2907 entitled "OMI validation by ground based remote validati by remote sensing: ozone columns and atmospheric profiles" for the purpose of OMI data validation. FTIR observations were carried out during the time frames AugustOctober 2005, June-October 2006 and March-October 2007, mostly under cloud free March cloud and clear sky conditions and in some days from early morning to sunset covering the full range of solar zenith angles possible. Ozone column and ozone profile data were obtained for the year 2005 using spectral modeling of the ozone spectral band profile near 9.6 microns with the MODTRAN3 band model based on the HITRAN-96 molecular absorption database. The total based HITRAN absorption total ozone column values retrieved from FTIR observations are biased low with respect to OMI-DOAS data by 8-10 DU on average, where they have a relatively small standard error of about 2%. FTIR observations for the year 2006 were simulated by of about the by MODTRAN4 modeling. For the retrieval of ozone column estimates and particularly ozone profiles from our FTIR observations, we used the following data sources to as input files to construct a priori information for the model: satellite Aqua-AIRS water fil lli vapor and temperature profiles; Aura-MLS stratospheric ozone profiles (version 1.5), TEMIS (KNMI) climatological ozone profiles and the simultaneously performed surface ozone measurements.

Ozone total columns obtained from our FTIR observations for year 2006 with MODTRAN4 modeling are matching rather well with OMITOMS andOMIli hi d OMI DOAS data where standard errors are 0.68 % and 1.11 %, respectively. The observations performing during March 2007 - October 2007 were reduced ti according to the new approach to retrieve tropospheric ozone column and profiles. For final results we used new version AIRS (level 3,v005) T and H2O data. We have got the total ozone column values retrieved from FTIR observations 2007 which are biased low with respect to OMI-DOAS by 0.33 DU and to OMI-TOMS by 4.33 DU on average, where they have a relatively small to OMI by 33 DU on average they have small standard error of about 1.4 %. AURA-MLS data of version 2.2 which have become available in 2007 allow us data of version have become in us to retrieve tropospheric ozone profiles. For some days Aura-TES tropospheric profiles were also available and were compared with our retrieved profiles for validation. A preliminary analysis of troposphere ozone variability was performed. Observation during the time frame March-October demonstrate daily photochemical variability of tropospheric ozone and reveal mixing processes variability ozone reveal during the night.

INTRODUCTION 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, acts as a pollutant but is also an important greenhouse gas. Ozone is not emitted directly by any natural source. However, tropospheric ozone is formed under high ultraviolet radiation flux conditions from natural and anthropogenic emissions of nitrogen oxides (NOx) and volatile organic compounds (VOCs). Satellite remote sensing is used to understand and quantify key processes in the global ozone budgets. Nowadays satellite observations are readily available for total ozone column and atmospheric ozone profiles. Nevertheless, ground based monitoring is important to validate and to complement space-based measurements and to clarify local/regional specific sources and sinks of this gas. Such ground based data can assist to derive the dynamical behavior of air pollution from space space and ground-based observations and to check compliance to the pollutants transport models. They will also aid to the development of an environmental policy, in particular policies on greenhouse gases, on a local and regional scale. in particular on greenhouse gases local regional

OMI SATELLITE OBSERVATIONS The Dutch-Finnish Ozone Monitoring Instrument (OMI) aboard the NASA Earth Observing System (EOS) Aura satellite is a compact nadir viewing, wide swath, OS) i ultraviolet-visible (270-500 nm) hyperspectral imaging spectrometer that provides daily global coverage with high spatial and spectral resolution. The Aura orbit is sun-synchronous at 705 km altitude with a 98 degrees inclination and ascending node equator-crossing time roughly at 13:45. OMI measures backscattered solar radiance in the dayside portion of each orbit and solar irradiance near the northern hemisphere terminator once per day. The OMI satellite data products are derived from the ratio of Earth radiance and solar irradiance. The OMI TOMS and OMI DOAS total ozone column estimates are publicly TOMS OMI bli available from the NASA DISC systems. The OMI-TOMS algorithm is based on the TOMS V8 algorithm that has been used to process data from a series of four TOMS instruments flown since November 1978. This lgorithm uses measurements at 4 discrete 1 nm wide wavelength bands centered at 313, 318, 331 and 360 nm. The OMI-DOAS algorithm [14] takes advantage of the hyper-spectral feature of OMI. It is based on the principle of Differential Optical Absorption Spectroscopy (DOAS) [9]. The lgorithm uses ~25 OMI measurements in the wavelength range 331.1 nm to 336.6 nm, as described in 14]. nm to nm, in

The key difference between the two algorithms is that the DOAS key between two is that the algorithm removes the effects of aerosols, clouds, volcanic sulfur dioxide, and surface effects by spectral fitting while the OMS algorithm applies an empirical correction to remove these effects. In addition, the TOMS algorithm uses a cloud height climatology that was derived using infrared satellite data, while the DOAS algorithm uses cloud information derived from OMI measurements in the 470 nm O2-O2 absorption band. The two two algorithms also respond to instrumental errors very differently. Validation is key to quantify and understand these differences as a function of measurement geometry, season and geolocation.

GROUND BASED FTIR OBSERVATIONS Ground based FTIR observations are performed with a Fourier Transform Infra-Red (FTIR) spectrometer, model ``Infralum FT 801'', which was modernized for the task of monitoring the atmosphere by direct sun observations. 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 microns (800-5000 cm1) with the highest possible spectral resolution of about 1.0 cm-1. spectral resolution of about cm Following the modernization in 2006 of our spectrometer and upadating 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 (Egevskaya et al.2001) to avoid a degradation of the averaged spectrum due to the recording of atmospheric instabilities at longer exposure times. Our averaged spectra have signalto-noise ratios S/N of 150-200. We registered 3-4 averaged spectra during 2-3 minutes of recording time. Prior to further treatment of the observed spectra we Prior treatment spectra checked the repeatability of these 3-4 spectra and choose the spectrum with the best signal-to-noise ratio S/N to be fitted with the model spectra .

MODTRAN SPECTRA MODELING AND ANALYSIS. The column amounts of ozone (O3) molecules are recovered by using the radiation transfer codes MODTRAN3 and MODTRAN4, a moderate resolution model of transmission [1]. These codes are widely applied to the interpretation of ground based, airborne and spaceborne (satellite) observations of spectra of the Earth's atmosphere. The codes calculate atmospheric transmission and reflection of electromagnetic radiation with frequencies from 0 up to 50000 cm-1. The model uses a spherical source function for the light originating from the Sun and scattered from the Moon, and the the and the standard model atmospheres and user specified atmospheric profiles of gases, aerosols, clouds, fogs and even rain. It uses a two-parameter (temperature and pressure) model of molecular absorption bands, which is calculated on the basis of a large array of previously accumulated data of spectral lines stored in the HITRAN database. MODTRAN uses absorption crosssection data for 12 light molecules (H2O, CO2, O3, CO, CH4, O2, NO, SO2, NO2, N2O, NH4 and HNO3), for heavy molecules - CFC (9 molecules) and for CLONO2, HNO4, CCl4 and N2O5. The calculations are carried out only in an local and i n an thermal equilibrium (LTE) approximation for the moderate spectral resolution (2 cm-1) which just corresponds to our observed Fourier spectra. The Band Model parameters were re-calculated by us on the base of HITRAN-2004 according to the paper of (Shavrina et al. JGR, 2007).

Measurements of surface ozone concentrations by the collocated ozonometer together with satellite remote sensing data from the data the Atmospheric Infrared Sounder Instrument (AIRS http://disc.gsfc.nasa.gov/AIRS/) aboard the NASA EOS-Aqua platform and the Microwave Limb Sounder (MLS), http://avdc.gsfc.nasa.gov/Data/Aura/) aboard the NASA EOS-Aura platform were usedfor the construction of atmospheric ozone, l df temperature and water vapor input profiles for the MODTRAN4.3 code. For the analysis of the 2006 FTIR observations we used MLS version 1.5 data, which then had a preliminary character. We modified the then had character We shape of the MLS stratospheric ozone profile to obtain a better fit to the MODTRAN4.3 model output and to our FTIR spectra of the ozone band around 9.6 microns.

Fortunately, in 2007 the all new and more precise version v2.2 of MLS data became available , that allows us to develop a new approachto the analysis: we now modified the input tropospheric h t th difi dth ozone profile and we only scaled the stratospheric ozone profiles of Aura-MLS v2.2 data within 2-5 % (declared precision of these data) v2 data within data) without any modification to its shape. The tropospheric part of the input (a priori) ozone profile was tropospheric part of the ozone constructed from surface ozone measurement and the TEMIS climatological (monthly averaged) ozone atmospheric profiles, which were downloaded from the TEMIS-KNMI website. In this way we tried to obtain the best possible fit of the model computed spectra to the FTIR observed spectral band on 9.6 microns. AuraFTIR TES data available from the AVDC website were also used if they were available for observational days. for days

To modify the tropospheric ozone profiles we used a smooth function determined between the J1 and J2 points of altitude in the model atmosphere. For any J point of the model we then adopt:
x=(J - J1) /(J 2- J1) , then PJ= P0J * (1 + B * (sin(x))a),

determines the shape of the correction function, a and B determine the amplitude shape correction function the of changes of input tropospheric ozone profile, where B > -1 and a > 0. Using the MODTRAN4 code we compute a grid of the theoretical spectra. To the theoretical determine the best fit parameters, we compare the observed and computed spectra following a two-step optimization procedure: Firstly, we determined the best fit to observed water vapor lines in the spectral region 800 - 1240 cm-1, i.e., fi li i here we exclude the ozone band from the analysis. Secondly, we fit the observed spectrum around the 9.6 micron ozone band with the grid of calculated ozone bands including the previously determined best atmospheric water profile. Hence we determine tropospheric ozone profiles, total and tropospheric ozone column from the best fit of the modeled and observed ozone band spectra, where we th fit th included the unaltered Aura-MLS stratospheric profiles.

Figure 4a: Time series of OMI total ozone (OMI-TOMS and OMI-DOAS) and ground based FTIR total ozone data for 2005. 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 45 DU 19 DU OMI OMI TOMS ith 10.50 DU and 13.41 DU standard deviation (1.98 DU and 2.53 DU standard errors).

Figure 1: Time series of the OMI total ozone column and the ground based FTIR total ozone data of 2006 for the ground site of Kiev (MAO). 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).

Figure 2: The observed FTIR spectra of the 9.6 micron ozone band for the 29th of September 2007 (29.09.07) (left) and the comparison of the observed FTIR spectra and modeled MODTRAN 4 spectra following the procedure for best fitting for the observation at 13h 01m ll local time on this day.

The total ozone column values retrieved from FTIR observations 2007 are biased low with respect to OMI-DOAS by 0.33 DU and to OMI-TOMS by 4.33 DU on average, where they have a relatively small standard error of about 1.4 %.

Date

Time H, min

ZSA, grad

TOC, DU

OMITOMS, DU

OMIDOAS, DU

Tr.OC, DU our , TES

Surface O3, ppb

Htrop, km

28.03 2007

85 10 13 14 16 17 18

4 47 12 46 51 51 21

70.434 58.459 47.469 52.131 67.169 76.192 80.375 57.622 43.200 42.879 50.375

364.24 363.57 361.39 363.94 363.54 359.91 366.27 411.01 410.30 410.27 409.54

344.2 353.2

356.0 363.2

47.15 36.06 44.13 46.72 46.33 43.54 44.93 48.06 47.34 47.30 46.57

27.3 40.2 48.8 65.9 64.0 56.5 57.3 18.7 32.8 44.1 46.5

12.0

23.04 2007

922 11 15 14 35 15 40

12.5

412.0" 414.7

414.5 417.6

9.06.07

639 844 11 56 16 08 17 53

75.28 55.66 29.93 45.92 62.42

348.37 341.53 346.05 352.76 349.56

347.6

349.6

38.40 31.70 35.47 36.38 39.56

20 22 42.8 51 57

12.0

14.06. 2007

65 70 90 12 17

2 5 5 06 45

73.20 71.21 52.25 28.96 60.75

355.54 351.04 352.81 348.72 357.36

347.6

349.6

42.9 44.75 39.81 42.86 44.76

14 13 15 46 50

12.0

References: " 22.04.07 OMI total column value = 448 DU;

18.07. 2007

13 14 16 17 18 19

35 52 10 20 15 27

29.93 36.16 46.62 58.23 66.19 77.39

287.12 294.07 290.91 294.39 292.85 296.60

291.5

289.6

44.32 51.27 49.37 51.60 50.09 53.80 53.55*

72 85 95 67 58 46

12.6

29.09. 2007

10 13 15 16 17

35 01 14 37 47

57.722 52.756 61.211 71.676 82.059

269.21 260.34 260.38 261.44 266.62

261.2 260.2

263.9 260.9

29.96 32.64 32.31 33.73 38.92

13.0 29.0 39.0 40.0 35.0

13.0

1.10.07

80 94 13 16 17

8 9 22 21 41

79.704 65.672 53.971 70.201 81.844

271.75 261.95 264.68 271.41 277.23

261.7

264.9

30.31 28.09 30.69 37.42 43.24

8.0 18.0 40.0 45.0 39.0

12.5

2.10.07

831 9 43 12 58 15 20

76.545 66.709 53.897 63.019

279.16 276.51 271.42 274.80

270.9

269.1

40.43 37.78 34.93 36.08 39.19*

8.0 12.0 43.0 47.0

12.5

References: * TESL3 tropospheric ozone column;

Figure 3: The retrieved ozone atmospheric profiles for the 28th of March 2007 , 8h54m and 10h47m (upper figures) local time, and 13h12m and 18h21m (lower figures) local time. From these figures one observes the low ozone concentrations in the boundary layer for the morning observation at 8h54m LT. Here most probably ozone titration by NO as emitted from cars during the morning traffic is taking place. From the 10h47m LT observation we see the abatement of tropospheric ozone, most clearly over the vertical range 211km. The enhancements of ozone due to the photochemical processes in the atmosphere are seen in the lower two figures. Our simultaneously performed surface ozone measurements reflect this dynamics also two simultaneously with the supportive values 27.3 ppb, 40.2 ppb, 48.8 ppb, and 57.3 ppb recorded for exactly these moments in time. For the comparison, we also show the Aura-TES ozone vertical profile for the 28th of March 2007, which can be considered as the valid satellite profile in the troposphere only.

Figure 3: The retrieved ozone atmospheric profiles for the 23rd of April 2007, 09h22m and 11h15m (upper figures) local time, and 14h35m and 15h40m (lower figures) local time. On this day the values of both total ozone columns (411.0 DU by FTIR) and tropospheric ozone columns are very high. Possibly we are here observing a stratospheric intrusion event as the highest OMI value of total ozone column in 2007 was 448 DU for the 22nd of April 2007.

Figure 4: The retrieved ozone atmospheric profiles for the 18th of July 2007, 13h35m and 16h10m (upper figures) local time, and 17h20m and 19h27m (lower figures) local time. The very high tropospheric ozone columns and surface ozone concentrations (see Table2 for the exact numbers) and their daily dynamics are characteristic for episodes of strongly enhanced surface and tropospheric ozone due to tropospheric photochemistry. Please note that on this day the total ozone column is rather low (291.5 DU)

Figure 6: The retrieved atmospheric ozone profiles for the 1st of October 2007, 08h08m and 9h49m (upper figures) local time and 16h21m and 17h41m (lower figures) local time. Please note that on this day the FTIR total ozone column is rather low, only 262 DU. Nevertheless, we can see the daily dynamics of tropospheric ozone: in the morning ozone titration by NO and rather high ozone concentrations later in the afternoon due to photochemistry.. Unfortunately, for this day Aura-TES data are absent and hence the tropospheric part of the input ozone profile for the MODTRAN modeling process was constructed on the basis of the TEMIS monthly averaged data.

CONCLUSION We have obtained a long track record of ground based FTIR total ozone column observations over the years 2005- 2007. Our estimates of the total ozone columns the estimates total agree well with OMI satellite remote sensing data. Differences are in the percentile range. We note some significant differences under insufficiently clear sky conditions, which are indicative of the influence of clouds on FTIR observations. di hi di fl FTIR
AURA-MLS data of version 2.2 become available in 2007. We have got the total ozone column values retrieved from FTIR observations 2007 which are biased low with respect to OMI-DOAS by 0.33 DU and to OMI-TOMS by 4.33 DU on average (as mean value and 0.05 and 2.98 respectively as median one), where they have a relatively small standard error of about 1.4 %. AURA-MLS data of version 2.2 allow us to retrieve tropospheric ozone profiles. For some days AURA-TES tropospheric profiles were also available and were compared with our profiles were also available and retrieved profiles for validation. A preliminary analysis of troposphere ozone variability was performed. Observations during March-October demonstrate daily photochemical variability of tropospheric ozone and reveal mixing processes during the night. ozone reveal processes the

The work presented here is the first step towards ozone profile retrievals on a regular basis. For this we need to further develop our retrieval procedures and we need to perform testing of our model calculations through line-by-line radiation transfer model calculations alike FASCODE. Since we do not have this code available we need to develop such coding in the near future ourselves. The procedure of quantitative comparison of our retrieved profile and other available data must be developed. Line by line approach *No additional suggestions for opacity computations; *Direct computations of every line core and wings; core and *Voigt function is adopted for the line profile; *We compute blending lines using the detailed abundances information + isotopes! *Spectra are smoothed AFTER the radiative transfer solution.

· ACKNOWLEDGEMENTS · The authors are grateful to the AVDC, AURA-MLS and AIRS website administrations for providing the necessary satellite remote sensing data. The work of the authors from MAO NASU was partly supported by the grant of STCU (20052007) and by Space Agency of Ukraine (2007).

1. Morozhenko O.V., Sosonkin M.G.,Shavrina A.V., Ivanov Yu.S. Problem in the Remote Monitiring of Global Variations in the Earth Atmosphere. - Kosm. nauka i tekhnologija, Vol 1, N 2-6,. 1995, - P.3-17. 2. Morozhenko O.V., Sosonkin M.G.,Shavrina A.V., Ivanov Yu.S. Device and Program Complex for Remote Spectrophotometric Monitoring of Pr for Earth Atmosphere Gas Composition. - 23rd European Meeting on Atmospheric Studies by Optical Method, 1996,Sept 2-6, Kiev, Ukraine. Proceeding of SPIE, Vol. 3237, 1996 - P.136-143. 3. Shavrina A.V., Veles A. A., Morozhenko A.V. The express method of the atmosphere chemical composition monitoring data treatment. Proc."The Sixteenth Coll. on High Resolution Molecular Spectroscopy", The Sixteenth Dijon, 1999, P.7-p 4. M.G. Sosonkin, A.A. Veles, A.V. Morozhenko, A.V. Shavrina. Remote Air Pollution Monitoring for Kiev City. Ai ll K i Ci EUROTRAC-2 Saturn Annual Report 2000, p.114 5. Veles A.A.,Morozhenko A., Sosonkin M., Shavrina A., Kesselman L. Veles A.A.,Mor Sosonkin M., A., A hardware-software complex of the infrared fourier spectrometer for air pollution monitoring. KFNT Suppl., 2000, N3, pp. 305-306

6. Shavrina, A. V.; Veles, A. A., Remote sensing of some greenhouse gases by Fourier- spectrometry in Kiev, 2004, JQSRT, 2004, 88, 345 350 7. Shavrina A.V., Pavlenko Ya. V., Veles A., Syniavskyi I and M. Kroon Ozone columns obtained by ground-based remote sensing in Kiev remote sensing for Aura Ozone Measuring Instrument validation // J. of Geophys. Res. , 112, D24S45, doi:10.1029/2007JD008787. 8. A.V. Shavrina, Ya.V. Pavlenko, A. A. Veles, V. A. Sheminova, I. I. Synyavski, M. G. Sosonkin, Ya. O. Romanyuk, N. A. Eremenko, Yu. S. Ivanov, O. A. Monsar and M. Kroon Tropospheric ozone columns and ozone profiles for Kiev in 2007(submitted in Kosmichna Nauka I Tekhnologiya, NKAU, NANY) 9. A.V. Shavrina, Ya.V. Pavlenko, A. A. Veles, V. A. Sheminova, I. I. Synyavski, M. G. Sosonkin, Ya. O. Romanyuk, N. A. Eremenko, Yu. S. Ivanov, O. A. Monsar and M. Kroon. Atmosphere ozone columns and ozone profiles over Kiev in 2007 (submitted in sbornik NKAU and NANU "Kosmichni doslidzhennya v Ukraine", 10. A.V. SHAVRINA , M.G. SOSONKIN, A.A. VELES, V.I. NOCHVAY INTEGRATED MODELLING OF SURFACE AND TROPOSPHERIC OZONE FOR KIEV CITY(SUBMITTED TO PUBL. NATO CONF., 2007) TO

11. OMI AO PROGRESS REPORT NO 1, RP-OMIE-KNMI-823_AOPR2005, ISSUE1 (HTTP://HIRLAM.KNMI.NL/OMI/RESEARCH/VALIDATION/AO/DOCUMENTS.HTML) 12. Progress Report no 2, RP-OMIE-KNMI-823_AOPR2006, Issue2 (http://hirlam.knmi.nl/omi/research/validation/ao/documents.html) 13. OMI AO Progress Report no 3, RP-OMIE-KNMI-823_AOPR2006, Issue3 (http://hirlam.knmi.nl/omi/research/validation/ao/documents.html) nl/omi/research/validation/ao/documents html) 14. OMI AO Progress Report no 4, RP-OMIE-KNMI-823_AOPR2006, Issue4 (http://hirlam.knmi.nl/omi/research/validation/ao/documents.html)

An investigation of ozone and planetary boundary layer dynamics over the complex topography of Grenoble combining measurements and modeling
O. Couach et al., 2003 (Atmos.Chem.Phys. 3, 549-562)

MODTRAN4

MODTRAN3.7 MODTRAN3.7 includes a number of upgrades to the aerosol models. The built-in aerosol models are no longer confined to fixed regions, but can be independently moved to any region and can be stretched, compressed, overlapped and scaled. The user-supplied spectral parameter pp input schemes for aerosols have also been improved. In addition, extensive modifications now allow MODTRAN to incorporate NOVAM, the Navy Oceanic Vertical Aerosol Model (Gathman and Davidson, 1993). Here, NOVAM is used as a stand-alone code, which is first executed to produce an output file consisting of spectraland altitude-dependent aerosol extinction, absorption, and asymmetry parameters.

MODTRAN4 adds the following features:
· Two Correlated-k (CK) options: the standard option which uses 17 k values (absorption coefficients) per spectral bin and a slower, 33 k value option primarily for upper-altitude bi ti il (>40 km) cooling rate and weighting function calculations; · An option to include azimuth dependencies in the calculation of DISORT solar scattering contributions ; · Upgraded ground surface modeling including parameterized forms for spectral BRDFs (Bidirectional Reflectance Distribution Functions) and an option to define a ground image Reflectance Functions) and to define ground pixel (H2) different from its surrounding surface. · A high-speed option, most appropriate in short-wave and UV spectral regions, that uses 15 cm-1 band model parameters); · Scaling options for water vapor and ozone column amounts; · Improved, higher spectral resolution, cloud parameter database (not aerosols); and hi · More accurate Rayleigh scattering and indices of refraction.

1.2 Radiation Transport Upgrades In addition to adding the above features, many improvements have been made to MODTRAN's MODTRAN' radiation transport algorithms. These include: · Using the new HITRAN96 database (Rothman et al., 1992; Rothman et al., 1998) to the HITRAN Rothman to generate the band model parameters; · Reformulating the absorption coefficient and line spacing band model parameters, and the coefficient spacing parameters and the temperature dependence of the Lorentz half-widths (Bernstein et al., 1995) (MODTRAN3.5); · Lowering the minimum of the band model parameter temperature grid to 180 K for linear interpolation modeling of the Antarctic tropopause (MODTRAN3.5); modeling of the (MODTRAN · Improving the band model line tail treatment by more carefully accounting for the line center locations (MODTRAN3.5) and increasing the line tail calculation resolution to 0.25 cm-1 (MODTRAN3.7); · Applying the "linear-in-tau" method to thermal radiance multiple scattering terms (MODTRAN3.5).

Evaluation of tropospheric and stratospheric ozone trends over Western Europe from ground-based FTIR network observations (C. Vigouroux et al. 2008, Atmos.Chem.Phys. Discuss., 8, 50075060, 2008)

Within Within the European project UFTIR (Time series of Upper Free Troposphere European (Time of Upper Free roposphere observations from an European ground-based FTIR network), six ground-based stations in Western Europe, from 79 N to 28 N, all equipped with Fourier Transform infrared (FTIR) instruments and part of the Network for the Detection of 5 Atmospheric Composition Change (NDACC), have joined their efforts to evaluate the trend of several iti th direct and indirect greenhouse gases over the period 19952004. The retrievals of CO, CH4, C2H6, N2O, CHClF2, and O3 have been optimized. Using the optimal estimation method, some vertical information can be obtained in addition to total column amounts. method, some vertical information can obtained addition total column amounts. The observed total column ozone trends are in agreement with previous studies: 1) no total column ozone trend is seen at the lowest latitude station Izan~a (28 N); 2) slightly positive total column trends are seen at the two mid-latitude stations iti th tit ti Zugspitze and Jungfraujoch (47 N), only one of them being significant; 3) the highest latitude stations Harestua (60 N), Kiruna (68 N) and Ny-A° lesund (79 N) show significant positive total column trends. Following the vertical information ifi th ti contained in the ozone FTIR retrievals, we provide partial columns trends for the layers: ground-10 km, 1018 km, 1827 km, and 2742 km, which helps to distinguish the contributions from dynamical and chemical changes on the total column ozone trends. chemical on the column ozone We obtain no statistically significant trends in the ground10 km layer for five out of the six ground-based stations. We find significant positive trends for the lowermost stratosphere at the two mid-latitude stations, and at Ny-A° lesund. We find smaller, but significant trends for the 1827 km layer at Kiruna, Harestua, Jungfraujoch, and Iza ~na. ifi Ki The results for the upper layer are quite contrasted: we find significant positive trends at Kiruna, Harestua, and Jungfraujoch, and significant negative trends at Zugspitze and Iza~na.