The HARMONIE–AROME Model Configuration in the ALADIN–HIRLAM NWP System

The aim of this article is to describe the reference configuration of the convection-permitting numerical weather prediction (NWP) model HARMONIE-AROME, which is used for operational short-range weather forecasts in Denmark, Estonia, Finland, Iceland, Ireland, Lithuania, the Netherlands, Norway, Spa...

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Bibliographic Details
Published in:Monthly Weather Review
Main Authors: Bengtsson, Lisa, Andrae, Ulf, Aspelien, Trygve, Batrak, Yurii, Calvo Sánchez, Francisco Javier, Rooy, Wim de, Gleeson, Emily, Hansen Sass, Bent, Homileid, Mariken, Hortal Reymundo, Mariano, Ivarsson, Karl-Ivan, Lenderink, Geert, Niemelä, Sami, Nielsen, Kristian Pagh, Onvlee, Jeanette, Rontu, Laura, Samuelsson, Patrick, Santos Muñoz, Daniel, Subías Díaz-Blanco, Álvaro, Tijm, Aleksander, Toll, Velle, Yang, Xiaohua, Ødegaard KØlgzow, Morten
Format: Article in Journal/Newspaper
Language:English
Published: American Meteorological Society 2017
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Online Access:https://hdl.handle.net/20.500.11765/7320
Description
Summary:The aim of this article is to describe the reference configuration of the convection-permitting numerical weather prediction (NWP) model HARMONIE-AROME, which is used for operational short-range weather forecasts in Denmark, Estonia, Finland, Iceland, Ireland, Lithuania, the Netherlands, Norway, Spain, and Sweden. It is developed, maintained, and validated as part of the shared ALADIN–HIRLAM system by a collaboration of 26 countries in Europe and northern Africa on short-range mesoscale NWP. HARMONIE–AROME is based on the model AROME developed within the ALADIN consortium. Along with the joint modeling framework, AROME was implemented and utilized in both northern and southern European conditions by the above listed countries, and this activity has led to extensive updates to themodel’s physical parameterizations. In this paper the authors present the differences inmodel dynamics and physical parameterizations compared with AROME, as well as important configuration choices of the reference, such as lateral boundary conditions, model levels, horizontal resolution, model time step, as well as topography, physiography, and aerosol databases used. Separate documentation will be provided for the atmospheric and surface data-assimilation algorithms and observation types used, as well as a separate description of the ensemble prediction system based on HARMONIE–AROME, which is called HarmonEPS.