A Decadal Data Set of Global Atmospheric Dust Retrieved From IASI Satellite Measurements

Abstract

Aerosol is an important component of the Earth's atmosphere, affecting weather, climate, and diverse elements of the biosphere. Satellite sounders are an essential tool for measuring the highly variable distributions of atmospheric aerosol. Here we present a new algorithm for estimating atmospheric dust optical depths and associated retrieval uncertainties from spectral radiance measurements of the Infrared Atmospheric Sounding Interferometer (IASI). The retrieval is based on the calculation of a dust index and on a neural network trained with synthetic IASI spectra. It has an inherent high sensitivity to dust and efficiently discriminates dust from other aerosols. In particular, over remote dust‐free areas, the retrieved levels of optical depth have a low bias. Over sea, noise levels are markedly lower than over land. Performance over deserts is comparable to that of other land surfaces. We use ground‐based coarse mode aerosol measurements from the AErosol RObotic NETwork to validate the new product. The overall assessment is favorable, with standard deviations in line with estimated uncertainties, low biases, and high correlation coefficients. However, a systematic relative bias occurs between sites dominated by African and Asian dust sources respectively, likely linked to differences in mineralogy. The retrieval has been performed on over a decade of IASI data, and the resulting data set is now publicly available. We present a global seasonal dust climatology based on this record and compare it with those obtained from independent satellite measurements (Moderate Resolution Imaging Spectroradiometer and a third‐party IASI product) and dust optical depth from the ECMWF model.

Is the recovery of stratospheric O<sub>3</sub> speeding up in the Southern Hemisphere? An evaluation from the first IASI decadal record (2008–2017)

“…The amplitude of the QBO signal is found to be stronger for QBO30 than for QBO10 in the LSt, which is in good agreement with studies from other instruments for the total O 3 (e.g. Baldwin et al, 2001;Steinbrecht et al, 2006;Frossard et al, 2013;Coldewey-Egbers et al, 2014) and from IASI in the troposphere (Wespes et al, 2017). The smaller amplitude of O 3 response to QBO10 in the LSt compared to the MUSt is again in agreement with previous studies that reported changes in the phase of the QBO10 response as a function of altitude with a positive response in the upper stratosphere and destructive interference in the middle-low stratosphere (Chipperfield et al, 1994;Brunner et al, 2006).…”

“…As for the QBO, the strong SF dependence at polar latitudes in the LSt with zonal asymmetry in the O 3 response reflects the influence of the polar vortex strength and of stratospheric warmings and is in good agreement with previous results (e.g. Hood et al, 1997;Zerefos et al, 1997;Labitzke and van Loon, 2000;Steinbrecht et al, 2003;Coldewey-Egbers et al, 2014). It is also worth noting that because only one solar cycle is covered, the QBO and SF effects could not be completely separated because of their strong interaction (e.g.…”

“…In addition to its exceptional spatio-temporal coverage, IASI also provides good spectral resolution and low radiometric noise, which allows the measurement of a series of gas-phase species and aerosols globally (e.g. Clerbaux et al, 2009;Hilton et al, 2012;Clarisse et al, 2019).…”

Spaceborne Measurements of Formic and Acetic Acids: A Global View of the Regional Sources

“…Moreover, the NN computing efficiency permits the processing of the entire IASI/Metop-A and -B observational time series. Other advantages of the ANNI retrieval scheme are specifically discussed by Clarisse et al (2019) and Whitburn et al (2016). Examples of regional CH 3 COOH (and superimposed HCOOH) column distributions from individual days of IASI/Metop-A and -B observations are shown in Figure 1.…”

The Mineral Aerosol Profiling from Infrared Radiances (MAPIR) algorithm: version 4.1 description and validation

“…Further, these sensors allow making observations at nighttime. Currently, global long term data sets of AOD are available from infrared sensors like the Atmospheric InfraRed Sounder (AIRS) and the Infrared Atmospheric Sounding Interferometer (IASI), onboard the polar-orbiting Aqua and MetOp satellites, respectively (DeSouza-Machado et al, 2010;Capelle et al, 2018;Clarisse et al, 2019;Popp et al, 2016). They can additionally provide dust layer mean altitude because infrared channels are sensitive to different levels of the atmosphere.…”