87 research outputs found

    Nitrogen compounds and ozone in the stratosphere: comparison of MIPAS satellite data with the chemistry climate model ECHAM5/MESSy1

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    The chemistry climate model ECHAM5/MESSy1 (E5/M1) in a setup extending from the surface to 80 km with a vertical resolution of about 600m near the tropopause with nudged tropospheric meteorology allows a direct comparison with satellite data of chemical species at the same time and location. Here we present results out of a transient 10 years simulation for the period of the Antarctic vortex split in September 2002, where data of MIPAS on the ENVISATsatellite are available. For the first time this satellite instrument opens the opportunity, to evaluate all stratospheric nitrogen containing species simultaneously with a good global coverage, including the source gas N2O and ozone which allows an estimate for NOx-production in the stratosphere. We show correlations between simulated and observed species in the altitude region between 10 and 50 hpa for different latitude belts, together with the Probability Density Functions (PDFs) of model results and observations. This is supplemented by global maps on pressure levels showing the comparison between the satellite and the simulated data sampled at the same time and location. We demonstrate that the model in most cases captures the partitioning in the nitrogen family, the diurnal cycles and the spatial distribution within experimental uncertainty. This includes even variations due to tropospheric clouds. There appears to be, however, a problem to reproduce the observed nighttime partitioning between N2O5 and NO2 in the middle stratosphere using the recommended set of reaction coefficients and photolysis data

    Methane and nitrous oxide from ground-based FTIR at Addis Ababa: Observations, error analysis, and comparison with satellite data

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    A ground-based, high-spectral-resolution Fourier transform infrared (FTIR) spectrometer has been operational in Addis Ababa, Ethiopia (9.01∘ N latitude, 38.76∘ E longitude; 2443 m altitude above sea level), since May 2009 to obtain information on column abundances and profiles of various constituents in the atmosphere. Vertical profile and column abundances of methane and nitrous oxide are derived from solar absorption measurements taken by FTIR for a period that covers May 2009 to March 2013 using the retrieval code PROFFIT (V9.5). A detailed error analysis of CH4_{4} and N2_{2}O retrieval are performed. Averaging kernels of the target gases shows that the major contribution to the retrieved information comes from the measurement. Thus, average degrees of freedom for signals are found to be 2.1 and 3.4, from the retrieval of CH4_{4} and N2_{2}O for the total observed FTIR spectra. Methane and nitrous oxide volume mixing ratio (VMR) profiles and column amounts retrieved from FTIR spectra are compared with data from the reduced spectral resolution Institute of Meteorology and Climate Research/Instituto de Astrofísica de Andalucía (IMK/IAA) MIPAS (Version V5R_CH4_224 and V5R_N2O_224), the Microwave Limb Sounder (MLS) (MLS v3.3 of N2_{2}O and CH4_{4} derived from MLS v3.3 products of CO, N2_{2}O, and H2_{2}O), and the Atmospheric Infrared Sounder (AIRS) sensors on board satellites. The averaged mean relative difference between FTIR methane and the three correlative instruments MIPAS, MLS, and AIRS are 4.2 %, 5.8 %, and 5.3 % in the altitude ranges of 20 to 27 km, respectively. However, the biases below 20 km are negative, which indicates the profile of CH4 from FTIR is less than the profiles derived from correlative instruments by −4.9 %, −1.8 %, and −2.8 %. The averaged positive bias between FTIR nitrous oxide and correlative instrument, MIPAS, in the altitude range of 20 to 27 km is 7.8 %, and a negative bias of −4 % at altitudes below 20 km. An averaged positive bias of 9.3 % in the altitude range of 17 to 27 km is obtained for FTIR N2O with MLS. In all the comparisons of CH4_{4} from FTIR with data from MIPAS, MLS, and AIRS, sensors on board satellites indicate a negative bias below 20 km and a positive bias above 20 km. The mean error between partial-column amounts of methane from MIPAS and the ground-based FTIR is −5.5 %, with a standard deviation of 5 % that shows very good agreement as exhibited by relative differences between vertical profiles. Thus, the retrieved CH4_{4} and N2_{2}O VMR and column amounts from Addis Ababa, tropical site, is found to exhibit very good agreement with all coincident satellite observations. Therefore, the bias obtained from the comparison is comparable to the precision of FTIR measurement, which allows the use of data in further scientific studies as it represents a unique environment of tropical Africa, a region poorly investigated in the past

    An observation-based climatology of middle atmospheric meridional circulation

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    Measurements of long-lived trace gases (SF₆, CFC-11, CFC-12, HCFC-12, CCl₄, N₂O, CH₄, H₂O, and CO) performed with the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) have been used to infer the stratospheric and mesospheric meridional circulation. The MIPAS data set covers the time period from July 2002 to April 2012. The method used for this purpose was the direct inversion of the two-dimensional continuity equation. Monthly climatologies of circulation fields are presented along with their variabilities. Stratospheric circulation is found to be highly variable over the year, with a quite robust annual cycle. The new method allows to track the evolution of various circulation patterns over the year in more detail than before.The deep branch of the Brewer-Dobson circulation and the mesospheric overturning pole-to-pole circulation are not separate but intertwined phenomena. The latitude of stratospheric uplift in the middle and upper stratosphere is found to be quite variable and is not always found at equatorial latitudes. The usual schematic of stratospheric circulation with the deep and the shallow branch of the Brewer-Dobson circulation and the mesospheric overturning circulation is an idealization which best describes the observed atmosphere around Equinox. Sudden stratospheric warmings cause increased year-to year variability

    Correction of stratospheric age-of-air derived from SF 6 for the effect of chemical sinks

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    Observational monitoring of the stratospheric transport circulation, the Brewer-Dobson-Circulation (BDC), is crucial to estimate any decadal to long-term changes therein, a prerequisite to interpret trends in stratospheric composition and to constrain the consequential impacts on climate. The transport time along the BDC (i.e., the mean age of stratospheric air, AoA) can best be deduced from trace gas measurements of tracers which increase linearly in time and are chemically passive. The gas SF6 is often used to deduce AoA, because it has been increasing monotonically since the ~1950s, and previously its chemical sinks in the mesosphere have been assumed to be negligible for AoA estimates. However, recent studies have shown that the chemical sinks of SF6 are stronger than assumed, and become increasingly relevant with rising SF6 concentrations. To adjust biases in AoA that result from the chemical SF6 sinks, we here propose a simple correction scheme for SF6-based AoA estimates accounting for the time-dependent effects of chemical sinks. The correction scheme is based on theoretical considerations with idealized assumptions, resulting in a relation between ideal AoA and apparent AoA which is a function of the tropospheric reference time-series of SF6 and of the AoA-dependent effective lifetime of SF6. The correction method is thoroughly tested within a self-consistent data set from a climate model that includes explicit calculation of chemical SF6 sinks. It is shown within the model that the correction successfully reduces biases in SF6-based AoA to less than 5 % for mean ages below 5 years. Tests with using only sub-sampled data for deriving the fit coefficients show that applying the correction scheme even with imperfect knowledge of the sink is far superior to not applying a sink correction. Further, we show that based on currently available measurements, we are not able to constrain the fit parameters of the correction scheme based on observational data alone. However, the model-based correction curve lies within the observational uncertainty, and we thus recommend to use the model-derived fit coefficients until more high-quality measurements will be able to further constrain the correction scheme. The application of the correction scheme to AoA from satellites and in-situ data suggests that it is highly beneficial to reconcile different observational estimates of mean AoA

    Differences in ozone retrieval in MIPAS channels A and AB: a spectroscopic issue

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    Discrepancies in ozone retrievals in MIPAS channels A (685–970cm−1) and AB (1020–1170cm−1) have been a long-standing problem in MIPAS data analysis, amounting to an interchannel bias (AB–A) of up to 8% between ozone volume mixing ratios in the altitude range 30–40km. We discuss various candidate explanations, among them forward model and retrieval algorithm errors, interchannel calibration inconsistencies and spectroscopic data inconsistencies. We show that forward-modelling errors as well as errors in the retrieval algorithm can be ruled out as an explanation because the bias can be reproduced with an entirely independent retrieval algorithm (GEOFIT), relying on a different forward radiative transfer model. Instrumental and calibration issues can also be refuted as an explanation because ozone retrievals based on balloon-borne measurements with a different instrument (MIPAS-B) and an independent level-1 data processing scheme produce a rather similar interchannel bias. Thus, spectroscopic inconsistencies in the MIPAS database used for ozone retrieval are practically the only reason left. To further investigate this issue, we performed retrievals using additional spectroscopic databases. Various versions of the HITRAN database generally produced rather similar channel AB–A differences. Use of a different database, namely GEISA-2015, led to similar results in channel AB, but to even higher ozone volume mixing ratios for channel A retrievals, i.e. to a reversal of the bias. We show that the differences in MIPAS channel A retrievals result from about 13% lower air-broadening coefficients of the strongest lines in the GEISA-2015 database. Since the errors in line intensity of the major lines used in MIPAS channels A and AB are reported to be considerably lower than the observed bias, we posit that a major part of the channel AB–A differences can be attributed to inconsistent air-broadening coefficients as well. To corroborate this assumption we show some clearly inconsistent air-broadening coefficients in the HITRAN-2008 database. The interchannel bias in retrieved ozone amounts can be reduced by increasing the air-broadening coefficients of the lines in MIPAS channel AB in the HITRAN-2008 database by 6%–8%

    TUNER-compliant error estimation for MIPAS

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    This paper describes the error estimation for temperature and trace gas mixing ratios retrieved from the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) limb emission spectra. The following error sources are taken into account: measurement noise, propagated temperature and pointing noise, uncertainties of the abundances of spectrally interfering species, instrument line shape errors, and spectroscopic data uncertainties in terms of line intensities and broadening coefficients. Furthermore, both the direct impact of volatile as well as persistent gain calibration uncertainties, offset calibration and spectral calibration uncertainties and their impact through propagated calibration-related temperature and pointing uncertainties are considered. An error source specific to the MIPAS upper atmospheric observation mode is the propagation of the smoothing error crosstalk of the combined NO and temperature retrieval. Whenever non-local thermodynamic equilibrium modelling is used inthe retrieval, also related kinetic constants and mixing ratios of species involved in the modelling of populations of excitational states contribute to the error budget. Both generalized Gaussian error propagation and perturbation studies are used to estimate the error components. Error correlations are taken into account. Estimated uncertainties are provided for a multitude of atmospheric conditions. Some error sources were found to contribute both to the random and the systematic component of the total estimated error. The sequential nature of the MIPAS retrievals gives rise to entangled errors. These are caused by error sources that affect the uncertainty of the final data product via multiple pathways, i.e., on the one hand directly, and on the other hand via errors caused in a preceding retrieval step. These errors tend to partly compensate each other. The hard-to-quantify effect of the horizontally non-homogeneous atmosphere and unknown error correlations of spectroscopic data are considered as the major limitations of the MIPAS error estimation

    TUNER-compliant error estimation for MIPAS: methodology

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    This paper describes the error estimation for temperature and trace gas mixing ratios retrieved from the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) limb emission spectra. The following error sources are taken into account: measurement noise, propagated temperature and pointing noise, uncertainties of the abundances of spectrally interfering species, instrument line shape errors, and spectroscopic data uncertainties in terms of line intensities and broadening coefficients. Furthermore, both the direct impact of volatile as well as persistent gain calibration uncertainties, offset calibration and spectral calibration uncertainties and their impact through propagated calibration-related temperature and pointing uncertainties are considered. An error source specific to the MIPAS upper atmospheric observation mode is the propagation of the smoothing error crosstalk of the combined NO and temperature retrieval. Whenever non-local thermodynamic equilibrium modelling is used inthe retrieval, also related kinetic constants and mixing ratios of species involved in the modelling of populations of excitational states contribute to the error budget. Both generalized Gaussian error propagation and perturbation studies are used to estimate the error components. Error correlations are taken into account. Estimated uncertainties are provided for a multitude of atmospheric conditions. Some error sources were found to contribute both to the random and the systematic component of the total estimated error. The sequential nature of the MIPAS retrievals gives rise to entangled errors. These are caused by error sources that affect the uncertainty of the final data product via multiple pathways, i.e., on the one hand directly, and on the other hand via errors caused in a preceding retrieval step. These errors tend to partly compensate each other. The hard-to-quantify effect of the horizontally non-homogeneous atmosphere and unknown error correlations of spectroscopic data are considered as the major limitations of the MIPAS error estimation
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