Observations of backscattered near-ultraviolet radiation from the Total Ozone Mapping Spectrometer (TOMS) on board the Nimbus-7 (1979-92) and the Earth Probe (mid-1996 to present) satellites have been used to derive a long-term record of aerosol optical depth over oceans and continents. The retrieval technique applied to the TOMS data makes use of two unique advantages of near-UV remote sensing not available in the visible or near-IR: 1) low reflectivity of all land surface types (including the normally bright deserts in the visible), which makes possible aerosol retrieval over the continents; and 2) large sensitivity to aerosol types that absorb in the UV, allowing the clear separation of carbonaceous and mineral aerosols from purely scattering particles such as sulfate and sea salt aerosols. The near-UV method of aerosol characterization is validated by comparison with Aerosol Robotic Network (AERONET) ground-based observations. TOMS retrievals of aerosol optical depth over land areas (1996-2000) are shown to agree reasonably well with AERONET sun photometer observations for a variety of environments characterized by different aerosol types, such as carbonaceous aerosols from biomass burning, desert dust aerosols, and sulfate aerosols. In most cases the TOMS-derived optical depths of UV-absorbing aerosols are within 30% of the AERONET observations, while nonabsorbing optical depths agree to within 20%. The results presented here constitute the first long-term nearly global climatology of aerosol optical depth over both land and water surfaces, extending the observations of aerosol optical depth to regions and times (1979 to present) not accessible to ground-based observations.

Abstract. Ozone profiles from the surface to about 60 km are retrieved from Ozone Monitoring Instrument (OMI) ultraviolet radiances using the optimal estimation technique. OMI provides daily ozone profiles for the entire sunlit portion of the earth at a horizontal resolution of 13 km×48 km for the nadir position. The retrieved profiles have sufficient accuracy in the troposphere to see ozone perturbations caused by convection, biomass burning and anthropogenic pollution, and to track their spatiotemporal transport. However, to achieve such accuracy it has been necessary to calibrate OMI radiances carefully (using two days of Aura/Microwave Limb Sounder data taken in the tropics). The retrieved profiles contain ∼6-7 degrees of freedom for signal, with 5-7 in the stratosphere and 0-1.5 in the troposphere. Vertical resolution varies from 7-11 km in the stratosphere to 10-14 km in the troposphere. Retrieval precisions range from 1% in the middle stratosphere to 10% in the lower stratosphere and troposphere. Solution errors (i.e., root sum square of precisions and smoothing errors) vary from 1-6% in the middle stratosphere to 6-35% in the troposphere, and are dominated by smoothing errors. Total, stratospheric, and tropospheric ozone columns can be retrieved with solution errors typically in the few Dobson unit range at solar zenith angles less than 80 • .

Abstract. This overview paper highlights the successes of the Ozone Monitoring Instrument (OMI) on board the Aura satellite spanning a period of nearly 14 years. Data from OMI has been used in a wide range of applications and research resulting in many new findings. Due to its unprecedented spatial resolution, in combination with daily global coverage, OMI plays a unique role in measuring trace gases important for the ozone layer, air quality, and climate change. With the operational very fast delivery (VFD; direct readout) and near real-time (NRT) availability of the data, OMI also plays an important role in the development of operational services in the atmospheric chemistry domain.

International audienceOzone profile trends over the period 2000 to 2016 from several merged satellite ozone data sets and from ground-based data by four techniques at stations of the Network for the Detection of Atmospheric Composition Change indicate significant ozone increases in the upper stratosphere, between 35 and 48 km altitude (5 and 1 hPa). Near 2 hPa (42 km), ozone has been increasing by about 1.5 % per decade in the tropics (20° S to 20° N), and by 2 to 2.5 % per decade in the 35° to 60° latitude bands of both hemispheres. At levels below 35 km (5 hPa), 2000 to 2016 ozone trends are smaller and not statistically significant. The observed trend profiles are consistent with expectations from chemistry climate model simulations. Using three to four more years of observations and updated data sets, this study confirms positive trends of upper stratospheric ozone already reported, e.g., in the WMO/UNEP Ozone Assessment 2014, or by Harris et al. (2015). The additional years, and the fact that nearly all individual data sets indicate these increases, give enhanced confidence. Nevertheless, a thorough analysis of possible drifts and differences between various data sources is still required, as is a detailed attribution of the observed increases to declining ozone depleting substances and to stratospheric cooling. Ongoing quality observations from multiple independent platforms are key for verifying that recovery of the ozone layer continues as expected

[1] In this paper we examine differences between cloud pressures retrieved from the Ozone Monitoring Instrument (OMI) using the ultraviolet rotational Raman scattering (RRS) algorithm and those from the thermal infrared (IR) Aqua/MODIS. Several cloud data sets are currently being used in OMI trace gas retrieval algorithms including climatologies based on IR measurements and simultaneous cloud parameters derived from OMI. From a validation perspective, it is important to understand the OMI retrieved cloud parameters and how they differ with those derived from the IR. To this end, we perform radiative transfer calculations to simulate the effects of different geophysical conditions on the OMI RRS cloud pressure retrievals. We also quantify errors related to the use of the Mixed Lambert-Equivalent Reflectivity (MLER) concept as currently implemented of the OMI algorithms. Using properties from the Cloudsat radar and MODIS, we show that radiative transfer calculations support the following: (1) The MLER model is adequate for single-layer optically thick, geometrically thin clouds, but can produce significant errors in estimated cloud pressure for optically thin clouds.(2) In a two-layer cloud, the RRS algorithm may retrieve a cloud pressure that is either between the two cloud decks or even beneath the top of the lower cloud deck because of scattering between the cloud layers; the retrieved pressure depends upon the viewing geometry and the optical depth of the upper cloud deck. (3) Absorbing aerosol in and above a cloud can produce significant errors in the retrieved cloud pressure. (4) The retrieved RRS effective pressure for a deep convective cloud will be significantly higher than the physical cloud top pressure derived with thermal IR.Citation: Vasilkov, A., J. Joiner, R. Spurr, P. K. Bhartia, P. Levelt, and G. Stephens (2008), Evaluation of the OMI cloud pressures derived from rotational Raman scattering by comparisons with other satellite data and radiative transfer simulations,