Comparing atmospheric transport models for future regional inversions over Europe. Part 1: Mapping the CO<sub>2</sub> atmospheric signals

Abstract

Abstract. The CO2 source and sink distribution across Europe can be estimated in principle through inverse methods by combining CO2 observations and atmospheric transport models. Uncertainties of such estimates are mainly due to insufficient spatiotemporal coverage of CO2 observations and biases of the models. In order to assess the biases related to the use of different models the CO2 concentration field over Europe has been simulated with five different Eulerian atmospheric transport models as part of the EU-funded AEROCARB project, which has the main goal to estimate the carbon balance of Europe. In contrast to previous comparisons, here both global coarse-resolution and regional higher-resolution models are included. Continuous CO2 observations from continental, coastal and mountain in-situ atmospheric stations as well as flask samples sampled on aircrafts are used to evaluate the models' ability to capture the spatiotemporal variability and distribution of lower troposphere CO2 across Europe. 14CO2 is used in addition to evaluate separately fossil fuel signal predictions. The simulated concentrations show a large range of variation, with up to ~10 ppm higher surface concentrations over Western and Central Europe in the regional models with highest (mesoscale) spatial resolution. The simulation – data comparison reveals that generally high-resolution models are more successful than coarse models in capturing the amplitude and phasing of the observed short-term variability. At high-altitude stations the magnitude of the differences between observations and models and in between models is less pronounced, but the timing of the diurnal cycle is not well captured by the models. The data comparisons show also that the timing of the observed variability on hourly to daily time scales at low-altitude stations is generally well captured by all models. However, the amplitude of the variability tends to be underestimated. While daytime values are quite well predicted, nighttime values are generally underpredicted. This is a reflection of the different mixing regimes during day and night combined with different vertical resolution between models. In line with this finding, the agreement among models is increased when sampling in the afternoon hours only and when sampling the mixed portion of the PBL, which amounts to sampling at a few hundred meters above ground. Main recommendations resulting from the study for constraining land carbon sources and sinks using high-resolution concentration data and state-of-the art transport models are therefore: 1) low altitude stations are preferable over high altitude stations as these locations are difficult to represent in state-of-the art models, 2) at low altitude stations only afternoon values can be represented sufficiently well to be used to constrain large-scale sources and sinks in combination with transport models, 3) even when using only afternoon values it is clear that data sampled several hundred meters above ground can be represented substantially more robust in models than surface station records, and finally 4) traditional large scale transport models seem not sufficient to resolve CO2 distributions over regions of the size of for example Spain and thus seem too coarse for interpretation of continental data.

What can we learn from European continuous atmospheric CO<sub>2</sub> measurements to quantify regional fluxes – Part 2: Sensitivity of flux accuracy to inverse setup

“…This is illustrated in Geels et al (2007), with a twofold increase in the spread of model results between marine and continental stations. This implies a model error twice larger at continental stations than at marine sites.…”

“…Following Peylin et al, 2005, daily errors are calculated as the standard deviation of actual hourly (or half-hourly) CO 2 measurements, each day between 11:00 and 16:00. The underlying assumption to link this error calculation to the random part of error in transport modeling is that atmospheric transport models tend to be less reliable for sites and days with larger hourly variability (Geels et al, 2007). The resulting annual mean daily error varies between 0.56 ppm at Pallas, up to 2.84 ppm at Cabauw.…”

“…For inverting the fluxes, the modeled CO 2 pseudo-data are selected for daytime only, between 11:00 and 16:00 local time, and their influence functions calculated accordingly. This daytime selection strategy is currently applied by modelers simulating continuous CO 2 data (Geels et al, 2007;Peters et al, 2007;Law et al, 2008), and by experimentalists taking flask samples. This selection recognizes the difficulties of large-scale models simulating nocturnal CO 2 trapping near the ground during the growing season.…”

Comparing high resolution WRF-VPRM simulations and two global CO<sub>2</sub> transport models with coastal tower measurements of CO<sub>2</sub>

“…The intercomparison study revealed the remarkable improvement of the CO 2 concentration simulation by regional models with horizontal resolutions down to 50 km compared to the coarser global models. The conclusions made by Geels et al (2007) impose severe limitations on the usability of continental CO 2 concentration data from short towers and mountain stations in inversions. Moreover one may also add coastal stations to the "difficult sites" list (Riley et al, 2005).…”

“…The transport deficiencies become especially critical when trying to invert high space/time resolution of fluxes as compared to monthly fluxes on large regions for which data limitation is probably larger (Gurney et al, 2002). A comprehensive validation of different global (TM3, LMDZ) and regional (HANK, DEHM, REMO) offline transport models were done by (Geels et al, 2007) for several European tall towers and mountain stations. The intercomparison study revealed the remarkable improvement of the CO 2 concentration simulation by regional models with horizontal resolutions down to 50 km compared to the coarser global models.…”