Performance of Land Surface Schemes in the WRF Model for Climate Simulations over the MENA-CORDEX Domain
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ORIGINAL ARTICLE
Performance of Land Surface Schemes in the WRF Model for Climate Simulations over the MENA‑CORDEX Domain Katiana Constantinidou1 · Panos Hadjinicolaou1 · George Zittis1 · Jos Lelieveld1,2 Received: 29 July 2020 / Accepted: 6 November 2020 © The Author(s) 2020
Abstract Land–atmosphere interactions need to be optimally represented in climate models for the realistic representation of past and future climate. In this work, six different versions of land surface schemes (LSS) are used to simulate the climate over the Middle East–North Africa (MENA) region for the period 2000–2010 with a horizontal resolution of 0.44 ◦ , using the Weather Research and Forecasting (WRF) model. The monthly time series output is evaluated against observations for several surface climate variables using statistical metrics (climatology, 5th and 95th percentiles, standard deviation, linear trend) and Taylor diagrams. The resulting biases are presented for the whole MENA domain as well as 7 sub-domains. A ranking procedure objectively retrieves a performance spectrum among the schemes. The LSS that is closest to observations and is, therefore, considered as the best performing is Noah, followed by its augmented version (NoahMP). For these simulations at the relatively coarse horizontal resolution of 50 km, the more elaborate LSSs are not performing very well. These results are useful for the choice of LSS in climate change modelling of the MENA-CORDEX as a whole, as well as its sub-regions. Keywords Land surface schemes · WRF · Regional climate model · Evaluation · Ranking · MENA
1 Introduction Information about key near-surface meteorological variables at regional and/or local levels can be obtained by regional climate models (RCMs), which simulate climate over limited areas of the globe by applying the dynamical downscaling technique (Giorgi and Gutowski 2015). The common simulation framework of the Coordinated Regional Climate Downscaling Experiment (CORDEX) can provide projections of different working groups over specific domains that are useful for regional climate change assessments (Zittis et al. 2019). A number of studies have dealt with the evaluation of the CORDEX RCM output against observations, revealing biases of the modelled temperature and precipitation climatology (Kotlarski et al. 2014; Gbobaniyi et al. 2014; Fotso-Nguemo et al. 2017) and extremes (Vautard et al. * Katiana Constantinidou [email protected] 1
Climate and Atmosphere Research Centre (CARE‑C), The Cyprus Institute, 2121 Nicosia, Cyprus
Department of Atmospheric Chemistry, Max Plank Institute for Chemistry, 55020 Mainz, Germany
2
2013; Diallo et al. 2016; Klutse et al. 2016) influenced by the choice of physics parameterizations. For example, a EURO-CORDEX domain study indicated systematic temperature and precipitation biases for the Weather Research and Forecasting (WRF) model, linked to different physical mechanisms related to convection, radiation and land surface (Katragkou et al. 2015). Davin et al. (2016) also highlighte
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