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Titel:
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Impact of optimized mixing heights on simulated regional atmospheric transport of CO2
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Auteur(s):
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Kretschmer, R.; Gerbig, C.; Karstens, U.; Biavati, G.; Vermeulen, A.T.; Vogel, F.; Hammer, S.; Totsche, K.U.
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Gepubliceerd door:
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Publicatie datum:
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ECN
Environment & Energy Engineering
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14-4-2014
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ECN publicatienummer:
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Publicatie type:
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ECN-W--14-012
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Artikel wetenschap tijdschrift
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Aantal pagina's:
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62
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Gepubliceerd in: Atmospheric Chemistry and Physics Discussions (Copernicus Publications), , 2014, Vol.14, p.4627-4685.
Samenvatting:
The mixing height (MH) is a crucial parameter in commonly used transport models
that proportionally affects air concentrations of trace gases with sources/sinks near the
ground and on diurnal scales. Past synthetic data experiments indicated the possibility
to 5 improve tracer transport by minimizing errors of simulated MHs. In this paper
we evaluate a method to constrain the Langrangian particle dispersion model STILT
(Stochastic Time-Inverted Lagrangian Transport) with MH diagnosed from radiosonde
profiles using a bulk Richardson method. The same method was used to obtain hourly
MHs for the period September/October 2009 from the Weather Research and Fore10
casting (WRF) model, which covers the European continent at 10 km horizontal resolution.
Kriging with External Drift (KED) was applied to estimate optimized MHs from
observed and modelled MHs, which were used as input for STILT to assess the impact
on CO2 transport. Special care has been taken to account for uncertainty in MH
retrieval in this estimation process. MHs and CO2 concentrations were compared to
15 vertical profiles from aircraft in-situ data. We put an emphasis on testing the consistency
of estimated MHs to observed vertical mixing of CO2. Modelled CO2 was also
compared with continuous measurements made at Cabauw and Heidelberg stations.
WRF MHs were significantly biased by 10–20% during day and 40–60% during
night. Optimized MHs reduced this bias to 5% with additional slight improvements
20 in random errors. The KED MHs were generally more consistent with observed CO2
mixing. The use of optimized MHs had in general a favourable impact on CO2 transport,
with bias reductions of 5–45% (day) and 60–90% (night). This indicates that a
large part of the found CO2 model-data mismatch was indeed due to MH errors. Other
causes for CO2 mismatch are discussed. Applicability of our method is discussed in
25 the context of CO2 inversions at regional scales.
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