Abstract. Chlorine monoxide (ClO) is the key species for anthropogenic ozone losses in the middle atmosphere. We observed ClO diurnal variations using the Superconducting Submillimeter-Wave Limb-Emission Sounder (SMILES) on the International Space Station, which has a non-sunsynchronous orbit. This includes the first global observations of the ClO diurnal variation from the stratosphere up to the mesosphere. The observation of mesospheric ClO was possible due to 10-20 times better signal-to-noise (S/N) ratio of the spectra than those of past or ongoing microwave/submillimeter-wave limb-emission sounders. We performed a quantitative error analysis for the strato-and mesospheric ClO from the Level-2 research (L2r) product version 2.1.5 taking into account all possible contributions of errors, i.e. errors due to spectrum noise, smoothing, and uncertainties in radiative transfer model and instrument functions. The SMILES L2r v2.1.5 ClO data are useful over the range from 0.01 and 100 hPa with a total error estimate of 10-30 pptv (about 10 %) with averaging 100 profiles. The SMILES ClO vertical resolution is 3-5 km and 5-8 km for the stratosphere and mesosphere, respectively. The SMILES observations reproduced the diurnal variation of stratospheric ClO, with peak values at mid-
We observed ozone (O3) in the vertical region between 250 and 0.0005 hPa (~ 12–96 km) using the Superconducting Submillimeter-Wave Limb-Emission Sounder (SMILES) on the Japanese Experiment Module (JEM) of the International Space Station (ISS) between 12 October 2009 and 21 April 2010. The new 4 K superconducting heterodyne receiver technology of SMILES allowed us to obtain a one order of magnitude better signal-to-noise ratio for the O3 line observation compared to past spaceborne microwave instruments. The non-sun-synchronous orbit of the ISS allowed us to observe O3 at various local times. We assessed the quality of the vertical profiles of O3 in the 100–0.001 hPa (~ 16–90 km) region for the SMILES NICT Level 2 product version 2.1.5. The evaluation is based on four components: error analysis; internal comparisons of observations targeting three different instrumental setups for the same O3 625.371 GHz transition; internal comparisons of two different retrieval algorithms; and external comparisons for various local times with ozonesonde, satellite and balloon observations (ENVISAT/MIPAS, SCISAT/ACE-FTS, Odin/OSIRIS, Odin/SMR, Aura/MLS, TELIS). SMILES O3 data have an estimated absolute accuracy of better than 0.3 ppmv (3%) with a vertical resolution of 3–4 km over the 60 to 8 hPa range. The random error for a single measurement is better than the estimated systematic error, being less than 1, 2, and 7%, in the 40–1, 80–0.1, and 100–0.004 hPa pressure regions, respectively. SMILES O3 abundance was 10–20% lower than all other satellite measurements at 8–0.1 hPa due to an error arising from uncertainties of the tangent point information and the gain calibration for the intensity of the spectrum. SMILES O3 from observation frequency Band-B had better accuracy than that from Band-A. A two month period is required to accumulate measurements covering 24 h in local time of O3 profile. However such a dataset can also contain variation due to dynamical, seasonal, and latitudinal effects
We observed the diurnal variation of ozone (O3) in the vertical region between 250 and 0.0005 hPa (~12–96 km) using the Superconducting Submillimeter-Wave Limb-Emission Sounder (SMILES) on the Japanese Experiment Module (JEM) of the International Space Station (ISS) between 12 October 2009 and 21 April 2010. The new 4 K superconducting heterodyne receiver technology of SMILES allowed us to obtain a one order of magnitude better signal-to-noise ratio for the O3 line observation compared to past spaceborne microwave instruments. We assessed the quality of the vertical profiles of O3 in the 100–0.001 hP (~16–90 km) region for the SMILES NICT Level 2 product version 2.1.5. The evaluation is based on four components; error analysis; internal comparisons of observations targeting three different instrumental setups for the same O3 625.371 GHz transition; internal comparisons of two different retrieval algorithms; and external comparisons for various local times with ozonesonde, satellite and balloon observations (ENVISAT/MIPAS, SCISAT/ACE-FTS, Odin/OSIRIS, Odin/SMR, Aura/MLS, TELIS). SMILES O3 data have an estimated absolute accuracy of better than 0.3 ppmv (3%) with a vertical resolution of 3–4 km over the 60 to 8 hPa range. The random error for a single measurement is better than the estimated systematic error, being less than 1, 2, and 7%, in the 40–1, 80–0.1, and 100–0.004 hPa pressure region, respectively. SMILES O3 abundance was 10–20% lower than all other satellite measurements at 8–0.1 hPa due to an error arising from uncertainties of the tangent point information and the calibration problem for the intensity of the spectrum. The non sun-synchronous orbit of the ISS allowed us to observe O3 at various local times. A two month period is required to accumulate measurements covering 24 h in local time. However such a dataset can also contain variation due to dynamical, seasonal, and latitudinal effects
Abstract. The Extrapolar SWIFT model is a fast ozone chemistry scheme for interactive calculation of the extrapolar stratospheric ozone layer in coupled general circulation models (GCMs). In contrast to the widely used prescribed ozone, the SWIFT ozone layer interacts with the model dynamics and can respond to atmospheric variability or climatological trends.The Extrapolar SWIFT model employs a repro-modelling approach, in which algebraic functions are used to approximate the numerical output of a full stratospheric chemistry and transport model (ATLAS). The full model solves a coupled chemical differential equation system with 55 initial and boundary conditions (mixing ratio of various chemical species and atmospheric parameters). Hence the rate of change of ozone over 24 h is a function of 55 variables. Using covariances between these variables, we can find linear combinations in order to reduce the parameter space to the following nine basic variables: latitude, pressure altitude, temperature, overhead ozone column and the mixing ratio of ozone and of the ozone-depleting families (Cl y , Br y , NO y and HO y ). We will show that these nine variables are sufficient to characterize the rate of change of ozone. An automated procedure fits a polynomial function of fourth degree to the rate of change of ozone obtained from several simulations with the ATLAS model. One polynomial function is determined per month, which yields the rate of change of ozone over 24 h. A key aspect for the robustness of the Extrapolar SWIFT model is to include a wide range of stratospheric variability in the numerical output of the ATLAS model, also covering atmospheric states that will occur in a future climate (e.g. temperature and meridional circulation changes or reduction of stratospheric chlorine loading).For validation purposes, the Extrapolar SWIFT model has been integrated into the ATLAS model, replacing the full stratospheric chemistry scheme. Simulations with SWIFT in ATLAS have proven that the systematic error is small and does not accumulate during the course of a simulation. In the context of a 10-year simulation, the ozone layer simulated by SWIFT shows a stable annual cycle, with inter-annual variations comparable to the ATLAS model. The application of Extrapolar SWIFT requires the evaluation of polynomial functions with 30-100 terms. Computers can currently calculate such polynomial functions at thousands of model grid points in seconds. SWIFT provides the desired numerical efficiency and computes the ozone layer 10 4 times faster than the chemistry scheme in the ATLAS CTM.
[1] We present a climatology of the diurnal variation of short-lived atmospheric compounds, such as ClO, BrO, HO 2 , and HOCl, as well as longer-lived species: O 3 , the hydrogen chloride isotopes H 35 Cl and H 37 Cl, and HNO 3 . Measurements were taken by the Superconducting Submillimeter-wave Limb-Emission Sounder (SMILES). This spectrally resolving radiometer, with very low observation noise and altitude range from the lower stratosphere to the lower thermosphere (20-100 km), was measuring vertical profiles of absorption spectra along a non-sun-synchronous orbit, thus observing at all local times. We used the retrieved volume mixing ratio profiles to compile climatologies that are a function of pressure, a horizontal coordinate (latitude or equivalent latitude), and a temporal coordinate (solar zenith angle or local solar time). The main product presented are climatologies with a high resolution of the temporal coordinate (diurnal variation climatologies). In addition, we provide climatologies with a high resolution of the horizontal coordinate (zonal climatologies).The diurnal variation climatologies are based on data periods of 2 months and the zonal climatologies on monthly data periods. Consideration of the SMILES time-space sampling patterns with respect to the averaging coordinates is a key issue for climatology creation, especially in case of diurnal variation climatologies. Biases induced by inhomogeneous sampling are minimized by carefully choosing the size of averaging bins. The sampling biases of the diurnal variation climatology of ClO and BrO are investigated in a comparison of homogeneously sampled model data versus SMILES-sampled model data from the stratospheric Lagrangian chemistry and transport model Alfred Wegener Institute Lagrangian Chemisrty/Transport System. In most cases, the relative sampling error is in the range of 0-20%. The strongest impact of sampling biases is found where the species' temporal gradients are strongest (mostly at sunrise and sunset), with a relative error of 60-100%. The SMILES climatology data sets are available via the SMILES data distribution home page.Citation: Kreyling, D., H. Sagawa, I. Wohltmann, R. Lehmann, and Y. Kasai (2013), SMILES zonal and diurnal variation climatology of stratospheric and mesospheric trace gasses: O 3 , HCl, HNO 3 , ClO, BrO, HOCl, HO 2 , and temperature, J. Geophys.
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