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Impact of optimized mixing heights on simulated regional atmospheric transport of CO2

Kretschmer, R. ; Gerbig, C. ; Karstens, Ute LU orcid ; Biavati, Gionata ; Vermeulen, Alex LU orcid ; Vogel, F. ; Hammer, S. and Totsche, K. U. (2014) In Atmospheric Chemistry and Physics 14(14). p.7149-7172
Abstract
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.... (More)
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 similar to 10-20% during day and similar to 40-60% during night. Optimized MHs reduced this bias to similar 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. (Less)
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author
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publishing date
type
Contribution to journal
publication status
published
subject
in
Atmospheric Chemistry and Physics
volume
14
issue
14
pages
23 pages
publisher
Copernicus GmbH
external identifiers
  • wos:000339934900004
  • scopus:84904430213
ISSN
1680-7324
DOI
10.5194/acp-14-7149-2014
language
English
LU publication?
no
id
0870659c-23f8-4aa2-ae7c-d177eefabab8 (old id 4623673)
date added to LUP
2016-04-01 10:54:16
date last changed
2022-01-26 03:34:41
@article{0870659c-23f8-4aa2-ae7c-d177eefabab8,
  abstract     = {{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 similar to 10-20% during day and similar to 40-60% during night. Optimized MHs reduced this bias to similar 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.}},
  author       = {{Kretschmer, R. and Gerbig, C. and Karstens, Ute and Biavati, Gionata and Vermeulen, Alex and Vogel, F. and Hammer, S. and Totsche, K. U.}},
  issn         = {{1680-7324}},
  language     = {{eng}},
  month        = {{07}},
  number       = {{14}},
  pages        = {{7149--7172}},
  publisher    = {{Copernicus GmbH}},
  series       = {{Atmospheric Chemistry and Physics}},
  title        = {{Impact of optimized mixing heights on simulated regional atmospheric transport of CO2}},
  url          = {{http://dx.doi.org/10.5194/acp-14-7149-2014}},
  doi          = {{10.5194/acp-14-7149-2014}},
  volume       = {{14}},
  year         = {{2014}},
}