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| Titel |
Impact of optimized mixing heights on simulated regional atmospheric transport of CO2 |
| VerfasserIn |
R. Kretschmer, C. Gerbig, U. Karstens, G. Biavati, A. Vermeulen, F. Vogel, S. Hammer, K. U. Totsche |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1680-7316
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Chemistry and Physics ; 14, no. 14 ; Nr. 14, no. 14 (2014-07-16), S.7149-7172 |
| Datensatznummer |
250118886
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| Publikation (Nr.) |
 copernicus.org/acp-14-7149-2014.pdf |
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| Zusammenfassung |
| 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 improve tracer transport by minimizing errors of simulated MHs.
In this paper we evaluate a method to constrain the Lagrangian
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
Forecasting (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 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 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 the context
of CO2 inversions at regional scales. |
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