The effect of using limited scene-dependent averaging kernels approximations for the implementation of fast observing system simulation experiments targeted on lower tropospheric ozone

Abstract

Practical implementations of chemical OSSEs (Observing System Simulation Experiments) usually rely on approximations of the pseudo-observations by means of a predefined parametrization of the averaging kernels, which describe the sensitivity of the observing system to the target atmospheric species. This is intended to avoid the use of a computationally expensive pseudo-observations simulator, that relies on full radiative transfer calculations. Here we present an investigation on how no, or limited, scene dependent averaging kernels parametrizations may misrepresent the sensitivity of an observing system. We carried out the full radiative transfer calculation for a three-days period over Europe, to produce reference pseudo-observations of lower tropospheric ozone, as they would be observed by a concept geostationary observing system called MAGEAQ (Monitoring the Atmosphere from Geostationary orbit for European Air Quality). The selected spatio-temporal interval is characterised by an ozone pollution event. We then compared our reference with approximated pseudo-observations, following existing simulation exercises made for both the MAGEAQ and GEOstationary Coastal and Air Pollution Events (GEO-CAPE) missions. We found that approximated averaging kernels may fail to replicate the variability of the full radiative transfer calculations. In addition, we found that the approximations substantially overestimate the capability of MAGEAQ to follow the spatio-temporal variations of the lower tropospheric ozone in selected areas, during the mentioned pollution event. We conclude that such approximations may lead to false conclusions if used in an OSSE. Thus, we recommend to use comprehensive scene-dependent approximations of the averaging kernels, in cases where the full radiative transfer is computationally too costly for the OSSE being investigated

Data assimilation: making sense of Earth Observation

“…Several OSSEs have been performed to assess the benefit of additions to the GOS to monitor air quality at the surface and lower troposphere (between the surface and ∼6 km), notably from GEO platforms. These OSSEs have tended to focus on measurements of ozone and CO (Edwards et al, 2009;Claeyman et al, 2011;Sellitto et al, 2013;Yumimoto, 2013;Hache et al, 2014;Zoogman et al, 2014); ozone is considered because it is a key lower tropospheric pollutant, and CO because it provides information on sources of pollution and transport processes in the lower troposphere. Other OSSEs for air quality have considered measurements of PM, another key tropospheric pollutant (Timmermans et al, 2009a,b).…”

Potential of multispectral synergism for observing ozone pollution by combining IASI-NG and UVNS measurements from EPS-SG satellite

“…For a practical consideration of computation, OSSEs typically approximate the pseudo-observations by means of a predefined parametrization of the averaging kernels (AVKs) that describe the retrieval method sensitivity to true vertical profiles of atmospheric species. If this procedure avoids full radiative transfer calculations and costly computational time, approximated averaging kernels with no (or limited) scenedependence may fail to replicate the variability of the full radiative transfer calculations (Sellitto et al, 2013); complex scene-dependent parametrizations of AVK may represent a more useful cost-benefits compromise in the case of multispectral/multi-instrument observing systems. In order to avoid these approximations, we perform full and accurate forward and inverse radiative transfer calculations, but for a limited time period of 4 days.…”