A thermal infrared instrument onboard a geostationary platform for CO and O<sub>3</sub> measurements in the lowermost troposphere: Observing System Simulation Experiments (OSSE)

Abstract

Abstract. This paper presents observing system simulation experiments (OSSEs) to compare the relative capabilities of two geostationary thermal infrared (TIR) instruments to measure ozone (O 3 ) and carbon monoxide (CO) for monitoring air quality (AQ) over Europe. The primary motivation of this study is to use OSSEs to assess how these infrared instruments can constrain different errors affecting AQ hindcasts and forecasts (emissions, meteorology, initial condition and the 3 parameters together). The first instrument (GEO-TIR) has a configuration optimized to monitor O 3 and CO in the lowermost troposphere (LmT; defined to be the atmosphere between the surface and 3 km), and the second instrument (GEO-TIR2) is designed to monitor temperature and humidity. Both instruments measure radiances in the same spectral TIR band. Results show that GEO-TIR could have a significant impact (GEO-TIR is closer to the reference atmosphere than GEO-TIR2) on the analyses of O 3 and CO LmT column. The information added by the measurements for both instruments is mainly over the Mediterranean Basin and some impact can be found over the Atlantic Ocean and Northern Europe. The impact of GEO-TIR is mainly above 1 km for O 3 and CO but can also improve the surface analCorrespondence to: M. Claeyman (marine.claeyman@aero.obs-mip.fr) yses for CO. The analyses of GEO-TIR2 show low impact for O 3 LmT column but a significant impact (although still lower than for GEO-TIR) for CO above 1 km. The results of this study indicate the beneficial impact from an infrared instrument (GEO-TIR) with a capability for monitoring O 3 and CO concentrations in the LmT, and quantify the value of this information for constraining AQ models.

The added value of a visible channel to a geostationary thermal infrared instrument to monitor ozone for air quality

“…Tech., 7, 2185-2201, 2014 www.atmos-meas-tech.net/7/2185/2014/ the simulated observations and the reference state, and the standard deviation of the simulated observations compared to the reference state. The z test has been used in OSSEs before to test the significance of differences between data sets (see Claeyman et al, 2011a;Lahoz et al, 2005). In order to highlight the differences between the results of the statistical tests comparing GEO TIR and GEO TIR+VIS, we calculate the z test for the 0-1 km ozone column only during daytime (07:00-17:00 UTC) (figure not shown).…”

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

“…In practical implementations of chemical OSSEs, approximated PO simulators are often used, see e.g. Claeyman et al (2011a);Zoogman et al (2011). The idea is to avoid the full RT calculations by a predefinition of typical averaging kernels (AKs) aimed at describing the vertical sensitivity of the observing system.…”

“…We compared our full RT pseudo-observations with two approximations: one based on the use of a single average scene-independent A over the whole region of study (hereafter referred to as approximation 1), and the other based on the use of a limited scene-dependent set of A ( T ), as a function of the thermal contrast ( T ) between the surface and the lowest air layer (hereafter referred to as approximation 2). Approximation 1 and 2 are inspired from the approximations recently used to carry out fast OSSEs aimed at studying the impact on LT ozone monitoring of GEO-CAPE (GEOstationary Coastal and Air Pollution Events) (Zoogman et al, 2011) and MAGEAQ (Claeyman et al, 2011a), respectively. The approximation 1 A was obtained by running our pseudo-observations simulator only once over a hypothetical scene with standard summer mid-latitudes climatological vertical profiles of temperature, pressure and trace gases, and a standard surface temperature.…”

“…Very few examples exist of PO approximations with a limited partial consideration of scene characterisation. For example, Claeyman et al (2011a) carried out a simplified OSSE using a look-up-table of precalculated AKs matrices parameterized as a function of NR thermal contrast between the surface temperature and nearsurface air temperature. The thermal contrast has been considered the most important parameter for the problem under investigation, i.e.…”

“…Historically, OSSEs were first used to evaluate the impact of new observations on numerical weather predictions (Arnold and Clifford, 1986;Lahoz et al, 2005;Tan et al, 2007;Masutani et al, 2010a). Recently, OSSEs have been carried out to analyse the expected added value of future satellite missions on trace gases monitoring (Edwards et al, 2009;Claeyman et al, 2011a;Zoogman et al, 2011). Edwards et al (2009) …”