alexa Dynamical downscaling of temperature variability over T
ISSN : 2332-2594

Journal of Climatology & Weather Forecasting
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Research Article

Dynamical downscaling of temperature variability over Tunisia: evaluation a 21-year-long simulation performed with the WRF model

Bilel Fathalli1*, Benjamin Pohl2, Thierry Castel2 and Mohamed Jomâa Safi1

1Université de Tunis El Manar, Ecole Nationale d’Ingénieurs de Tunis, Tunis, Tunisie

2Centre de Recherches de Climatologie, Biogéosciences, CNRS / université de Bourgogne Franche-Comté, Dijon, France

*Corresponding Author:
Université de Tunis El Manar
Ecole Nationale d’Ingénieurs de Tunis, Tunisie
E-mail: [email protected]

Received date: May 10, 2016; Accepted date: May 18, 2016; Published date: May 26, 2016

Citation: Fathalli B, Pohl B, Castel T, Safi MJ (2016) Dynamical downscaling of temperature variability over Tunisia: evaluation a 21-year-long simulation performed with the WRF model. J Climatol Weather Forecasting 4:166. doi:10.4172/2332-2594.1000166

Copyright: © 2016 Fathalli B, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.



This study evaluates the capabilities of the

Weather Research and Forecasting

(WRF) model to reproduce the space-time variability of near-surface air temperature over Tunisia. Downscaling is based on two nested domains with a first domain covering the Mediterranean Basin and forced by 21 years of ERA-Interim reanalysis (1991-2011), and a second domain (12 km spatial resolution) centered on Tunisia. Analyses and comparisons are focused on daily average (Tavg), minimum (Tmin) and maximum (Tmax) near-surface air temperatures and are carried out at the annual and

seasonal timescales

. WRF results are assessed against various climatological products (ERA-Interim, EOBS and a local network of 18 surface weather stations). The model correctly reproduces the spatial patterns of temperature being significantly superimposed with local topographic features. However, it broadly tends to underestimate temperatures especially in winter. Temporal variability of temperature is also properly reproduced by the model although systematic cold biases mostly concerning Tmax, reproduced throughout the whole simulation period, and prevailing during the winter months. Comparisons also suggest that the WRF errors are not rooted in the driving model but could be probably linked to deficiencies in the model parameterizations of diurnal/nocturnal physical processes that largely impact Tmax / Tmin.


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