Validation of ozone data from the Superconducting Submillimeter‐Wave Limb‐Emission Sounder (SMILES)

Abstract

[1] The Superconducting Submillimeter-Wave Limb-Emission Sounder (SMILES) onboard the International Space Station provided global measurements of ozone profiles in the middle atmosphere from 12 October 2009 to 21 April 2010. We present validation studies of the SMILES version 2.1 ozone product based on coincidence statistics with satellite observations and outputs of chemistry and transport models (CTMs). Comparisons of the stratospheric ozone with correlative data show agreements that are generally within 10%. In the mesosphere, the agreement is also good and better than 30% even at a high altitude of 73 km, and the SMILES measurements with their local time coverage also capture the diurnal variability very well. The recommended altitude range for scientific use is from 16 to 73 km. We note that the SMILES ozone values for altitude above 26 km are smaller than some of the correlative satellite datasets; conversely the SMILES values in the lower stratosphere tend to be larger than correlative data, particularly in the tropics, with less than 8% difference below~24 km. The larger values in the lower stratosphere are probably due to departure of retrieval results between two detection bands at altitudes below 28 km; it is~3% at 24 km and is increasing rapidly down below.

Diurnal variations of stratospheric ozone measured by ground-based microwave remote sensing at the Mauna Loa NDACC site: measurement validation and GEOSCCM model comparison

“…We excluded from the average difference profiles described below individual profiles in which the daytime measurement was made with the instrument set up in Band A while the nighttime measurement was made in Band B or vice versa; this was done to eliminate potential systematic effects that could otherwise appear. Validation of SMILES ozone data is described in Imai et al (2013). The native units of the SMILES L2 version 2.1 data are mixing ratio vs. altitude.…”

Diurnal ozone variations in the stratosphere revealed in observations from the Superconducting Submillimeter‐Wave Limb‐Emission Sounder (SMILES) on board the International Space Station (ISS)

“…Imai et al [2012b] compared the ozone distributions obtained from the SMILES with those obtained from the following five satellite measurements: the Microwave Limb Sounder (MLS) on the Earth Observing System (EOS) Aura satellite, the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) on the Envisat satellite, the Submillimeter Radiometer (SMR) on the Odin satellite, the SABER on the TIMED satellite, and the Atmospheric Chemistry Experiment-Fourier Transform Spectrometer (ACE-FTS) on the SCISAT-1 satellite. They revealed that the agreement with these satellite measurements was generally within 10% in the stratosphere.…”

“…[2012a] compared ozone profiles measured by the SMILES with those obtained from worldwide ozonesonde stations and found good agreement at middle to high latitudes of within 6% to 8% between 20 and 30 km, but at low latitudes, the difference increased to around 7% to 20%; however, part of this increase (~up to 7%) may result from bias in the ozonesonde measurements due to the response time issue. Imai et al [2012b] compared the ozone distributions obtained from the SMILES with those obtained from the following five satellite measurements: the Microwave Limb Sounder (MLS) on the Earth Observing System (EOS) Aura satellite, the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) on the Envisat satellite, the Submillimeter Radiometer (SMR) on the Odin satellite, the SABER on the TIMED satellite, and the Atmospheric Chemistry Experiment-Fourier Transform Spectrometer (ACE-FTS) on the SCISAT-1 satellite. They revealed that the agreement with these satellite measurements was generally within 10% in the stratosphere.…”

Description and Evaluation of the specified-dynamics experiment in the Chemistry-Climate Model Initiative

“…Studies have long shown that transport computations using analyzed winds are very sensitive to how the large-scale flow is specified (e.g., Schoeberl et al, 2003;Meijer et al, 2004;Pawson et al, 2007). However, for historical reasons these sensitivities have been most rigorously explored in the context of offline chemical transport models (CTMs) and Lagrangian trajectory models, with several studies demonstrating the sensitivity of stratospheric transport to both the temporal sampling and averaging of the prescribed fields (e.g., Waugh et al, 1997;Bregman et al, 2006;Legras et al, 2005;Pawson et al, 2007;Monge-Sanz et al, 2007, 2013. By comparison, relatively less attention has been paid to assessing the credibility of large-scale transport in simulations using general circulation models constrained with reanalysis products either using so-called "nudging", wherein the simulated meteorological fields are relaxed towards analysis fields (Kunz et al, 2012), or using approaches derived from data assimilation (e.g., Orbe et al, 2017b).…”