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Elucidating the causes of errors in 2.2 km Met Office Unified Model simulations of a convective case over the US Great Plains
Author(s) -
Hanley Kirsty E.,
Lean Humphrey W.
Publication year - 2021
Publication title -
quarterly journal of the royal meteorological society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.744
H-Index - 143
eISSN - 1477-870X
pISSN - 0035-9009
DOI - 10.1002/qj.4049
Subject(s) - parametrization (atmospheric modeling) , convection , ensemble forecasting , convective available potential energy , meteorology , scale (ratio) , environmental science , convective inhibition , general circulation model , atmospheric sciences , climatology , geology , physics , climate change , natural convection , radiative transfer , combined forced and natural convection , quantum mechanics , oceanography
Convective‐scale ensemble simulations with perturbed initial and lateral boundary conditions have been performed to investigate the role of compensating errors in the model representation of a US Great Plains severe convective event. The convective‐scale ensembles were generated by nesting a 2.2 km grid‐length domain within the Met Office global ensemble. Within the ensemble framework, two different science configurations (i.e. parametrization set‐ups) were trialled in the 2.2 km model. The variability due to the use of a different driving global ensemble member was significant with differences in the pre‐convective thermodynamic environment and the initiation time of convection. The science changes also influence initiation time as well as the details in the convective structure. Comparison with observed soundings showed that most of the 2.2 km simulations had too little convective inhibition (CIN). The CIN was found to be independent of the science configuration, implying it is determined by the global model, which was also found to have less CIN than the observed soundings. In both 2.2 km ensembles, the member that produced one of the best simulations of the supercells that developed on this day had more CIN than the other members. However, comparisons with surface station data found that this member had a pre‐convective environment that was too cool and too dry. This suggests there are compensating errors in the factors controlling initiation in these models which comparisons with observations can help elucidate.