The Nabro stratovolcano in Eritrea, northeastern Africa, erupted on 13 June 2011, injecting approximately 1.3 teragrams of sulfur dioxide (SO(2)) to altitudes of 9 to 14 kilometers in the upper troposphere, which resulted in a large aerosol enhancement in the stratosphere. The SO(2) was lofted into the lower stratosphere by deep convection and the circulation associated with the Asian summer monsoon while gradually converting to sulfate aerosol. This demonstrates that to affect climate, volcanic eruptions need not be strong enough to inject sulfur directly to the stratosphere.
Abstract. This paper presents extensive bias determination analyses of ozone observations from the Atmospheric Chemistry Experiment (ACE) satellite instruments: the ACE Fourier Transform Spectrometer (ACE-FTS) and the Measurement of Aerosol Extinction in the Stratosphere and Troposphere Retrieved by Occultation (ACE-MAESTRO) instrument. Here we compare the latest ozone data products from ACE-FTS and ACE-MAESTRO with coincident observations from nearly 20 satellite-borne, airborne, balloonborne and ground-based instruments, by analysing volume mixing ratio profiles and partial column densities. The ACE-FTS version 2.2 Ozone Update product reports more ozone than most correlative measurements from the upper troposphere to the lower mesosphere. At altitude levels from 16 to 44 km, the average values of the mean relative differences are nearly all within +1 to +8%. At higher altitudes (45-60 km), the ACE-FTS ozone amounts are significantly larger than those of the comparison instruments, with mean relative differences of up to +40% (about +20% on average). For the ACE-MAESTRO version 1.2 ozone data product, mean relative differences are within ±10% (average values within ±6%) between 18 and 40 km for both the sunrise and sunset measurements. At higher altitudes (∼35-55 km), systematic biases of opposite sign are found between the ACE-MAESTRO sunrise and sunset observations. While ozone amounts derived from the ACE-MAESTRO sunrise occultation data are often smaller than the coincident observations (with mean relative differences down to −10%), the sunset occultation profiles for ACE-MAESTRO show results that are qualitatively similar to ACE-FTS, indicating a large positive bias (mean relative differences within +10 to +30%) in the 45-55 km altitude range. In contrast, there is no significant systematic difference in bias found for the ACE-FTS sunrise and sunset measurements.
[1] A 7+ year (2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008) data set of stratospheric BrO profiles measured by the Optical Spectrograph and Infra-Red Imager System (OSIRIS) instrument, a UV-visible spectrometer measuring limb-scattered sunlight from the Odin satellite, is presented. Zonal mean radiance spectra are computed for each day and inverted to yield effective daily zonal mean BrO profiles from 16 to 36 km. A detailed description of the retrieval methodology and error analysis is presented. Single-profile precision and effective resolution are found to be about 30% and 3-5 km, respectively, throughout much of the retrieval range. Individual profile and monthly mean comparisons with ground-based, balloon, and satellite instruments are found to agree to about 30%. A BrO climatology is presented, and its morphology and correlation with NO 2 is consistent with our current understanding of bromine chemistry. Monthly mean Br y maps are derived. Two methods of calculating total Br y in the stratosphere are used and suggest (21.0 ± 5.0) pptv with a contribution from very short lived substances of (5.0 ± 5.0) pptv, consistent with other recent estimates.
The possibility of retrieving horizontal atmospheric structure from a series of limb images taken aboard a satellite is discussed and a maximum likelihood expectation maximization algorithm is developed. Examples of the retrieval of horizontal structure with this algorithm, for different S/N (signal-to-noise) ratios and different structures, are presented. It is shown that with this algorithm and even in the presence of substantial observational noise, a S/N equal to 10 for a single observation, it is possible to retrieve both horizontal and vertical atmospheric structure.
Abstract. In this paper, we present a HARMonized dataset of OZone profiles (HARMOZ) based on limb and occultation measurements from Envisat (GOMOS, MIPAS and SCIAMACHY), Odin (OSIRIS, SMR) and SCISAT (ACE-FTS) satellite instruments. These measurements provide high-vertical-resolution ozone profiles covering the altitude range from the upper troposphere up to the mesosphere in years [2001][2002][2003][2004][2005][2006][2007][2008][2009][2010][2011][2012]. HARMOZ has been created in the framework of the European Space Agency Climate Change Initiative project.The harmonized dataset consists of original retrieved ozone profiles from each instrument, which are screened for invalid data by the instrument teams. While the original ozone profiles are presented in different units and on different vertical grids, the harmonized dataset is given on a common pressure grid in netCDF (network common data form)-4 format. The pressure grid corresponds to vertical sampling of ∼ 1 km below 20 km and 2-3 km above 20 km. The vertical range of the ozone profiles is specific for each instrument, thus all information contained in the original data is preserved. Provided altitude and temperature profiles allow the representation of ozone profiles in number density or mixing ratio on a pressure or altitude vertical grid. Geolocation, uncertainty estimates and vertical resolution are provided for each profile. For each instrument, optional parameters, which are related to the data quality, are also included.For convenience of users, tables of biases between each pair of instruments for each month, as well as bias uncertainties, are provided. These tables characterize the data consistency and can be used in various bias and drift analyses, which are needed, for instance, for combining several datasets to obtain a long-term climate dataset.This user-friendly dataset can be interesting and useful for various analyses and applications, such as data merging, data validation, assimilation and scientific research.The dataset is available at
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