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Discussion papers | Copyright
https://doi.org/10.5194/npg-2018-44
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 11 Oct 2018

Research article | 11 Oct 2018

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Nonlinear Processes in Geophysics (NPG).

Characterising regime behaviour in the stably stratified nocturnal boundary layer on the basis of stationary Markov chains

Carsten Abraham and Adam H. Monahan Carsten Abraham and Adam H. Monahan
  • University of Victoria, School of Earth and Ocean Sciences, P.O. Box 3065 STN CSC, Victoria, BC V8P 5C2, Canada

Abstract. Recent research has demonstrated that hidden Markov model (HMM) analysis is an effective tool to classify regimes of the stratified nocturnal boundary layer (SBL) at different tower sites. Here we analyse if SBL regime statistics (the occurrence of regime transitions, subsequent transitions after the first, and very persistent nights) in observations match theoretical calculations obtained from a stationary Markov chain with the goal of developing the foundations of novel Markov-chain-based boundary layer schemes which capture the effects of SBL regime dynamics. The regime statistics of a stationary Markov chain using the best estimate transition probabilities from the HMM analyses generally overestimate occurrence probabilities of regime transitions, resulting in an underestimation of persistent nights. Across the locations considered, sensitivity analyses of transition probability matrices in the HMM and the stationary Markov chain reveal that regimes are generally required to be more persistent in the stationary Markov chain in order to simulate observations accurately. A range of transition probability matrices allowing for a relatively accurate description of the occurrence of at least one transition within a night, multiple transitions, and the mean event durations is identified. The occurrence of very persistent nights (nights without regime transitions) is found to depend highly on the season. Therefore, for better representations of very persistent nights a nonstationary Markov chain linked to external drivers is likely appropriate. The observed transition probability maximum between one and two hours after a previous transition cannot be accounted for by two-state Markov processes (stationary or not). The use of these results in the development of SBL turbulence parameterisations is discussed.

Carsten Abraham and Adam H. Monahan
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Status: open (until 06 Dec 2018)
Status: open (until 06 Dec 2018)
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Carsten Abraham and Adam H. Monahan
Carsten Abraham and Adam H. Monahan
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Latest update: 15 Oct 2018
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