Quantification of internal variability of the arctic summer atmosphere based on HIRHAM5 ensemble simulations

The non-linear behaviour of the atmospheric dynamics is not well understood and makes the evaluation and usage of regional climate models (RCMs) difficult. Due to these non-linearities, chaos and internal variability (IV) within the RCMs are induced, leading to a sensitivity of RCMs to their initial...

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Bibliographic Details
Main Author: Sommerfeld, Anja
Format: Doctoral or Postdoctoral Thesis
Language:English
Published: 2015
Subjects:
Online Access:https://publishup.uni-potsdam.de/frontdoor/index/index/docId/8534
https://nbn-resolving.org/urn:nbn:de:kobv:517-opus4-85347
https://publishup.uni-potsdam.de/files/8534/sommerfeld_diss.pdf
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Summary:The non-linear behaviour of the atmospheric dynamics is not well understood and makes the evaluation and usage of regional climate models (RCMs) difficult. Due to these non-linearities, chaos and internal variability (IV) within the RCMs are induced, leading to a sensitivity of RCMs to their initial conditions (IC). The IV is the ability of RCMs to realise different solutions of simulations that differ in their IC, but have the same lower and lateral boundary conditions (LBC), hence can be defined as the across-member spread between the ensemble members. For the investigation of the IV and the dynamical and diabatic contributions generating the IV four ensembles of RCM simulations are performed with the atmospheric regional model HIRHAM5. The integration area is the Arctic and each ensemble consists of 20 members. The ensembles cover the time period from July to September for the years 2006, 2007, 2009 and 2012. The ensemble members have the same LBC and differ in their IC only. The different IC are arranged by an initialisation time that shifts successively by six hours. Within each ensemble the first simulation starts on 1st July at 00 UTC and the last simulation starts on 5th July at 18 UTC and each simulation runs until 30th September. The analysed time period ranges from 6th July to 30th September, the time period that is covered by all ensemble members. The model runs without any nudging to allow a free development of each simulation to get the full internal variability within the HIRHAM5. As a measure of the model generated IV, the across-member standard deviation and the across-member variance is used and the dynamical and diabatic processes influencing the IV are estimated by applying a diagnostic budget study for the IV tendency of the potential temperature developed by Nikiema and Laprise [2010] and Nikiema and Laprise [2011]. The diagnostic budget study is based on the first law of thermodynamics for potential temperature and the mass-continuity equation. The resulting budget equation reveals seven ...