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New cloud and microphysics parameterisation for use in high‐resolution dynamical downscaling: application for summer extreme temperature over Belgium
Author(s) -
Hamdi R.,
Van de Vyver H.,
Termonia P.
Publication year - 2011
Publication title -
international journal of climatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.58
H-Index - 166
eISSN - 1097-0088
pISSN - 0899-8418
DOI - 10.1002/joc.2409
Subject(s) - downscaling , noon , environmental science , cloud cover , climatology , diurnal cycle , climate model , atmospheric sciences , spatial distribution , meteorology , geology , physics , climate change , precipitation , cloud computing , remote sensing , oceanography , computer science , operating system
We explore the use of high‐resolution dynamical downscaling as a means to simulate extreme values of summer maximum surface air temperature over Belgium ( T MAX ). We use the limited area version of the ARPEGE‐IFS model, ALADIN. Our approach involves a sequence of daily integrations driven by perfect boundary conditions at the lateral boundaries provided by the ERA40 reanalysis. In this study, three different recent past (1961–1990) simulations are evaluated against different station datasets: (1) 40 km spatial resolution (ALD40), (2) 10 km spatial resolution (ALD10), and (3) 4 km spatial resolution (ALR04) using a new parameterisation of deep convection, and microphysics allowing the use of ALADIN at resolutions ranging from a few tens of kilometers down to less than 4 km. The validation of ALD40 reveals a positive summer bias (2.2 °C), even though the considerable spatial resolution enhancement by a factor of 4, ALD10 reduces slightly the warm biases (1.7 °C). This warm bias on T MAX is strongly correlated with cloud cover representation. Result shows an overestimate of clear‐sky occurrences by ALD10 and a developing solar radiation overestimate through the diurnal cycle, with 116 W m −2 maximum overestimate at noon. ALR04 reduces considerably the warm biases (−0.2 °C) which suggests of its ability to simulate weakly forced convective cloud in the summer over Belgium. In addition, the Generalized Pareto Distribution (GPD) of the extreme high temperatures produced by the different simulations has been compared to observations of the same period. ALD40 and ALD10 gave a GPD distribution that did not replicate the observed distribution well and, thus, overestimated the extremes. This study shows that the consistent treatment of deep convection and cloud–radiation interaction when increasing the horizontal resolution is very important when studying extremely high temperatures events. Copyright © 2011 Royal Meteorological Society