Seven years of IASI ozone retrievals from FORLI: validation with independent total column and vertical profile measurements

Abstract

Ozone Monitoring Experiment-2 (GOME-2) launched on board MetOp-A and Brewer-Dobson data show that, on average, IASI overestimates the ultraviolet (UV) data by 5-6 % with the largest differences found in the southern high latitudes. The comparison with UV-visible SAOZ (Système d'Analyse par Observation Zénithale) measurements shows a mean bias between IASI and SAOZ TOCs of 2-4 % in the midlatitudes and tropics and 7 % at the polar circle. Part of the discrepancies found at high latitudes can be attributed to the limited information content in the observations due to low brightness temperatures. The comparison with ozonesonde vertical profiles (limited to 30 km) shows that on average IASI with FORLI processing underestimates O 3 by ∼ 5-15 % in the troposphere while it overestimates O 3 by ∼ 10-40 % in the stratosphere, depending on the latitude. The largest relative differences are found in the tropPublished by Copernicus Publications on behalf of the European Geosciences Union. 4328A. Boynard et al.: Seven years of IASI ozone retrievals from FORLI ical tropopause region; this can be explained by the low O 3 amounts leading to large relative errors. In this study, we also evaluate an updated version of FORLI-O3 retrieval software (v20151001), using look-up tables recalculated to cover a larger spectral range using the latest HITRAN spectroscopic database (HITRAN 2012) and implementing numerical corrections. The assessment of the new O 3 product with the same set of observations as that used for the validation exercise shows a correction of ∼ 4 % for the TOC positive bias when compared to the UV ground-based and satellite observations, bringing the overall global comparison to ∼ 1-2 % on average. This improvement is mainly associated with a decrease in the retrieved O 3 concentration in the middle stratosphere (above 30 hPa/25 km) as shown by the comparison with ozonesonde data.

Tropospheric ozone profiles by DIAL at Maïdo Observatory (Reunion Island): system description, instrumental performance and result comparison with ozone external data set

“…We find a D of 11.3 % between data sets (LIO3T higher than IASI). These results are in agreement with the 5-15 % O 3 abundance difference of IASI in the troposphere compared to ECC soundings reported recently by Boynard et al (2016). Note that, due to the sparse comparison points, the Southern Hemisphere biomass burning season is barely visible on this plot.…”

“…As LIO3T usually fires between 19:00:00 and 01:00:00 local times, here we used the IASI night-time overpass measurements. The IASI data used in this study come from the FORLI-O 3 v20151001 scheme (Hurtmans et al, 2012;Boynard et al, 2016).…”

Quality assessment of the Ozone_cci Climate Research Data Package (release 2017): 2. Ground-based validation of nadir ozone profile data products

“…less than 10 % and insignificant stratospheric bias, a 10 to 30 % positive bias in the UTLS, and an order of 10 % negative bias in the troposphere. The latter is in agreement with an initial IASI tropospheric ozone (also retrieved with FORLI v20151001) validation exercise using ozonesonde reference measurements performed by Boynard et al (2016). Possible reasons for the UTLS bias are discussed in Dufour et al (2012).…”

Sensitivity of stomatal conductance to soil moisture: implications for tropospheric ozone

“…In fact, atmospheric gases, including air pollutants, are primarily removed from the troposphere by dry deposition to the Earth's surface (Hardacre et al, 2015;Monks et al, 2015). A major part of dry deposition to vegetation is regulated by stomata opening, which strongly depends on the amount of water available in the soil (Büker et al, 2012). Therefore a proper quantification of soil water content as well as a proper understanding of stomatal response to soil moisture is required for correctly quantifying the concentration of gases in the atmosphere, particularly in waterlimited ecosystems (dry and semidry environments), which cover 41 % of Earth's land surface (Reynolds et al, 2007).…”

“…However, this original formulation of the DO 3 SE model presented a main limitation (Simpson et al, 2007;Tuovinen et al, 2009;Mills et al, 2011): for both forests and crops the model did not take into account the limitation due to soil water content. This approach ensured that stomatal fluxes were maximized, corresponding to conditions expected for irrigated areas (Simpson et al, 2007), but, in semi-arid environments, like the Mediterranean Basin, the amount of atmospheric gases entering the leaves might be compromised by the exclusion of the influence of drought on stomatal conductance (Tuovinen et al, 2009;Mills et al, 2011;Büker et al, 2012;Anav et al, 2016;De Marco et al, 2016). Following this assumption, the role of soil moisture on stomatal O 3 fluxes has been often neglected in risk assessment studies because soil water is very difficult to model accurately in large-scale models, as it depends on parameters (such as soil texture, vegetation characteristics and rooting depth) that are not easily available in the frame of large-scale models (Simpson et al, 2007Büker et al, 2012).…”