Browsing by Author "Karstens, U"

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    Assessment of regional atmospheric transport model performance using 222Radon observations
    (European Geosciences Union (EGU), 2020-05-04) Karstens, U; Levin, I; Ramonet, M; Gerbig, C; Arnold, S; Conil, S; Della Coletta, J; Frumau, A; Gheusi, F; Kazan V; Kubistin, D; Lindauer, M; Lopez, M; Maurer, L; Mihalopoulos, N; Pichon, JM; Spain, G
    The rather short life time of 222Radon of 5.5 days makes this radioactive noble gas an almost ideal tracer of atmospheric transport processes. 222Radon, the gaseous progeny of 226Radium, which is a trace constituent of all soils, can escape the soil grains and make its way from the unsaturated soil zone into the atmosphere. The exhalation rate of 222Radon from continental surfaces depends on soil type and permeability, but is orders of magnitude larger than that from ocean surfaces. Therefore, the atmospheric 222Radon activity concentration can be used as a measure of the residence time of air over continental surfaces or to distinguish continental from marine air masses. At continental sites, the short-term variability of 222Radon is mainly determined by diurnal or synoptic-scale boundary layer mixing processes. If its continental exhalation rate is known, 222Radon can even be applied as a quantitative tracer for evaluating regional scale transport model performance. In the present study we use 222Radon activity concentration measurements from the ICOS atmospheric station network and STILT transport model results to assess the ability of this routinely used model to correctly simulate the (diurnal) variation of boundary layer transport. This uncertainty assessment is an important step towards reliable estimates of the contribution of transport model error in GHGs inversion studies that aim at providing accurate fluxes from inversion of atmospheric GHGs observations in ICOS. © Author(s) 2020. This work is distributed under the Creative Commons Attribution 4.0 License.
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    Atmospheric transport and chemistry of trace gases in LMDz5B
    (Copernicus Publications, 2015-02-03) Locatelli, R; Bousquet, P; Hourdin, F; Saunois, M; Cozic, A; Couvreux, F; Grandpeix, JY; Lefebvre, MP; Rio, C; Bergamaschi, P; Chambers, SD; Karstens, U; Kazan, V; van der Laan, S; Meijer, HAJ; Moncrieff, J; Ramonet, M; Scheeren, HA; Schlosser, C; Schmidt, M; Vermeulen, AT; Williams, AG
    Representation of atmospheric transport is a major source of error in the estimation of greenhouse gas sources and sinks by inverse modelling. Here we assess the impact on trace gas mole fractions of the new physical parameterizations recently implemented in the atmospheric global climate model LMDz to improve vertical diffusion, mesoscale mixing by thermal plumes in the planetary boundary layer (PBL), and deep convection in the troposphere. At the same time, the horizontal and vertical resolution of the model used in the inverse system has been increased. The aim of this paper is to evaluate the impact of these developments on the representation of trace gas transport and chemistry, and to anticipate the implications for inversions of greenhouse gas emissions using such an updated model. © Author(s, 2015.
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    Evaluation of the boundary layer dynamics of the TM5 model over Europe
    (Copernicus Publications, 2016-09-14) Koffi, EN; Bergamaschi, P; Karstens, U; Krol, M; Segers, A; Schmidt, M; Levin, I; Vermeulen, AT; Fisher, RE; Kazan, V; Klein Baltink, H; Lowry, D; Manca, G; Meijer, HAJ; Moncrieff, J; Pal, S; Ramonet, M; Scheeren, HA; Williams, AG
    We evaluate the capability of the global atmospheric transport model TM5 to simulate the boundary layer dynamics and associated variability of trace gases close to the surface, using radon (222Rn). Focusing on the European scale, we compare the boundary layer height (BLH) in the TM5 model with observations from the National Oceanic and Atmospheric Admnistration (NOAA) Integrated Global Radiosonde Archive (IGRA) and also with ceilometer and lidar (light detection and ranging) BLH retrievals at two stations. Furthermore, we compare TM5 simulations of 222Rn activity concentrations, using a novel, process-based 222Rn flux map over Europe (Karstens et al., 2015), with harmonised 222Rn measurements at 10 stations. The TM5 model reproduces relatively well the daytime BLH (within 10–20 % for most of the stations), except for coastal sites, for which differences are usually larger due to model representation errors. During night, however, TM5 overestimates the shallow nocturnal BLHs, especially for the very low observed BLHs (< 100 m) during summer. The 222Rn activity concentration simulations based on the new 222Rn flux map show significant improvements especially regarding the average seasonal variability, compared to simulations using constant 222Rn fluxes. Nevertheless, the (relative) differences between simulated and observed daytime minimum 222Rn activity concentrations are larger for several stations (on the order of 50 %) than the (relative) differences between simulated and observed BLH at noon. Although the nocturnal BLH is often higher in the model than observed, simulated 222Rn nighttime maxima are actually larger at several continental stations. This counterintuitive behaviour points to potential deficiencies of TM5 to correctly simulate the vertical gradients within the nocturnal boundary layer, limitations of the 222Rn flux map, or issues related to the definition of the nocturnal BLH. At several stations the simulated decrease of 222Rn activity concentrations in the morning is faster than observed. In addition, simulated vertical 222Rn activity concentration gradients at Cabauw decrease faster than observations during the morning transition period, and are in general lower than observed gradients during daytime. Although these effects may be partially due to the slow response time of the radon detectors, they clearly point to too fast vertical mixing in the TM5 boundary layer during daytime. Furthermore, the capability of the TM5 model to simulate the diurnal BLH cycle is limited by the current coarse temporal resolution (3 h/6 h) of the TM5 input meteorology. © Author(s) 2016.