HCLIM38: a flexible regional climate model applicable for different climate zones from coarse to convection-permitting scales
Danijel Belušić, Hylke de Vries, Andreas Dobler, Oskar Landgren, Petter Lind, David Lindstedt, Rasmus A. Pedersen, Juan Carlos Sánchez-Perrino, Erika Toivonen, Bert van Ulft, Fuxing Wang, Ulf Andrae, Yurii Batrak, Erik Kjellström, Geert Lenderink, Grigory Nikulin, Joni‐Pekka Pietikäinen, Ernesto Rodríguez Camino, Patrick Samuelsson, Erik van Meijgaard, Minchao Wu
Abstract
Abstract. This paper presents a new version of HCLIM, a regional climate modelling system based on the ALADIN–HIRLAM numerical weather prediction (NWP) system. HCLIM uses atmospheric physics packages from three NWP model configurations, HARMONIE–AROME, ALARO and ALADIN, which are designed for use at different horizontal resolutions. The main focus of HCLIM is convection-permitting climate modelling, i.e. developing the climate version of HARMONIE–AROME. In HCLIM, the ALADIN and ALARO configurations are used for coarser resolutions at which convection needs to be parameterized. Here we describe the structure and development of the current recommended HCLIM version, cycle 38. We also present some aspects of the model performance. HCLIM38 is a new system for regional climate modelling, and it is being used in a number of national and international projects over different domains and climates ranging from equatorial to polar regions. Our initial evaluation indicates that HCLIM38 is applicable in different conditions and provides satisfactory results without additional region-specific tuning. HCLIM is developed by a consortium of national meteorological institutes in close collaboration with the ALADIN–HIRLAM NWP model development. While the current HCLIM cycle has considerable differences in model setup compared to the NWP version (primarily in the description of the surface), it is planned for the next cycle release that the two versions will use a very similar setup. This will ensure a feasible and timely climate model development as well as updates in the future and provide an evaluation of long-term model biases to both NWP and climate model developers.