Harmonie

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HARMONIE is a seamless model framework developed jointly between several European national meteorological services. The model system provides flexibility as it contains a suite of different atmospheric models, each adapted for different horizontal resolutions. 

The framework, which facilitates observation handling, climate generation, lateral boundary coupling, and postprocessing required is referred to as the HIRLAM–ALADIN Research on Mesoscale Operatinal NWP in Euromed (HARMONIE) system.

Model description

In HARMONIE, the nonhydrostatic dynamical core (Bubnova et al. 1995; Benard et al. 2010), developed by ALADIN is used. It solves the fully compressible Euler equations using a two time level, semi-implicit, semi-Lagrangian discretization on an Arakawa A grid. In the vertical, a mass-based hybrid pressure terrain-following coordinate is used (Simmons and Burridge, 1981; Laprise, 1992).

HARMONIE-AROME is specifically developed to be run at convection permitting resolutions resolving deep convection explicitly and is generally applied to a resolution of around 2 km.

HARMONIE-AROME parameterizes radiation using a two-stream approximation in model columns and the effects of surface slopes are accounted for. Shortwave and longwave spectral computations follow Fouquart and Bonnel (1980) and Mlawer et al. (1997), respectively, and cloud optical properties for liquid clouds are derived from Morcrette and Fouquart (1986) and from Ebert and Curry (1992) for ice clouds. HARMONIE-AROME uses a mixed-phase microphysics scheme, the ICE3 scheme (Pinty and Jabouille 1998), wherein cloud water and ice as well as rain, snow, and graupel are prognostic variables. Hail is assumed to behave as large graupel particles. The turbulence parameterization was developed by Cuxart et al. (2000) and is based on a prognostic TKE equation combined with a diagnostic mixing length L.

HARMONIE-ALARO-0 is often used from grid sizes of 4 km and larger and hence use the hydrostatic version of the dynamical core. Differences between HARMONIE-ALARO-0 and HARMONIE-AROME appear primarily in the atmospheric physics. In HARMONIE-ALARO-0, radiation is parameterized using the two-stream scheme developed by Ritter and Geleyn (1992) with optical cloud properties following Masek (2005). Deep convection in HARMONIE-ALARO-0 is not explicitly resolved and uses the 3MT parameterization scheme. In standard parameterizations, separate schemes are used for deep convection and for ‘‘nonconvective’’ (i.e., resolved large scale) clouds, with microphysical conversion to precipitation treated separately in each scheme. However, at ever-higher resolution, the risk of double counting convective processes (both through resolved and parameterized parts) increases, and 3MT handles this by formally separating the two different contributions. The microphysical processes handle five prognostic water phases, where autoconversion and evaporation are computed level by level (Gerard et al. 2009). The turbulence parameterization is a pseudoprognostic turbulent kinetic energy (pTKE) scheme, which is an extension of the Louis-type vertical diffusion scheme (Louis 1979).

The surface parametrisation framework in HARMONIE is SURFEX [Surface externalise (Masson et al., 2013)]. It originates from the ISBA (Interactions Soil-Biosphere-Atmosphere) surface scheme (Noilhan and Planton, 1989) and is an external surface modelling system available off-line as well as coupled to atmospheric models. When coupled to an atmospheric model, SURFEX receives variables such as air temperature, humidity, wind and precipitation for every time step and then uses them to compute momentum and surface energy fluxes. Land surface properties in SURFEX are taken from the ECOCLIMAP database (Champeaux et al., 2005). A more thorough description of SURFEX is found in (Le Moigne, 2012). 

References

  • Lind, Petter, David Lindstedt, Erik Kjellström and Colin Jones. 2016. Spatial and Temporal Characteristics of Summer Precipitation over Central Europe in a Suite of High-Resolution Climate Models. Journal of Climate. DOI: 10.1175/JCLI-D-15-0463.1
  • Lindstedt, David, Petter Lind, Colin Jones and Erik Kjellström. 2015. A new regional climate model operating at the meso-gamma scale; performance over Europe. Tellus A, 67, 24138. DOI: 10.3402/tellusa.v67.24138
  • Bénard, P., Vivoda, J., Mašek, J., Smolíková, P., Yessad, K. and co-authors. 2010. Dynamical kernel of the Aladin-NH spectral limited-area model: revised formulation and sensitivity experiments. Q. J. Roy. Meteorol. Soc. 136(646), 155#169. DOI:10.1002/qj.522.
  • Bubnová, R., Hello, G., Beńard, P. and Geleyn, J. 1995. Integration of the fully elastic equations cast in the hydrostatic pressure terrain-following coordinate in the framework of the ARPEGE/Aladin NWP system. Mon. Weather Rev. 123(2), 515#535.
  • Simmons, A. and Burridge, D. 1981. An energy and angular momentum conserving vertical finite-difference scheme and hybrid vertical coordinates. Mon. Weather Rev. 109, 758#766.
  • Laprise, R. 1992. The Euler equations of motion with hydrostatic pressure as an independent variable. Mon. Weather Rev. 120, 197#207.
  • Ritter, B. and Geleyn, J. 1992. A comprehensive radiation scheme for numerical weather prediction models with potential applications in climate simulations. Mon. Weather Rev. 120, 303#325.
  • Masson, V., Le Moigne, P., Martin, E., Faroux, S., Alias, A. and co-authors. 2013. The SURFEXv7.2 land and ocean surface platform for coupled or offline simulation of earth surface variables and fluxes. Geosci. Model Dev. 6(4), 929#960. DOI:10.5194/gmd-6-929 2013.
  • Mašek, J. 2005. New parameterization of cloud optical properties proposed for model ALARO-0. Report. Download the report.
  • Gerard, L., Piriou, J.-M., Brožková, R., Geleyn, J.-F. and Banciu, D. 2009. Cloud and precipitation parameterization in a Meso-Gamma-Scale operational weather prediction model. Mon. Weather Rev . 137(11), 3960#3977. DOI: 10.1175/2009MWR2750.1.
  • Louis, J. 1979. A parametric model of vertical eddy fluxes in the atmosphere. Bound Layer Meteorol. 7, 187#202.
  • Le Moigne, P. 2012. Surfex Scientific Documentation. Technical Report. Météo-France. Download the technical report.
  • Champeaux, J. L., Masson, V. and Chauvin, F. 2005. ECOCLIMAP: a global database of land surface parameters at 1 km resolution. Meteorol. Appl. 12(1), 29#32. DOI: 10.1017/S1350482705001519
  • Fouquart, Y., and B. Bonnel, 1980: Computations of solar heating of the earth’s atmosphere: A new parameterization. Beitr. Phys. Atmos., 53, 35–62.
  • Mlawer, E. J., S. J. Taubman, P. D. Brown, M. J. Iacono, and S. A. Clough, 1997: Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave. J. Geophys. Res., 102, 16 663–16 682, doi:10.1029/97JD00237.
  • Morcrette, J.-J., and Y. Fouquart, 1986: The overlapping of cloud layers in shortwave radiation parameterizations. J. Atmos. Sci., 43, 321–328, doi:10.1175/15200469(1986)043,0321:TOOCLI.2.0.CO;2.
  • Ebert, E. E., and J. A. Curry, 1992: A parameterization of ice cloud optical properties for climate models. J. Geophys. Res.,97, 3831, doi:10.1029/91JD02472.
  • Pinty, J.-P., and P. Jabouille, 1998: Mixed-phase cloud parameterization for use in a mesoscale non-hydrostatic model: Simulations of a squall line and of orographic precipitation. Proc. Conf. on Cloud Physics, Everett, WA, Amer. Meteor. Soc., 217–220.
  • Cuxart, J., P. Bougeault, and J.-L. Redelsperger, 2000: A turbulence scheme allowing for mesoscale and large eddy simulations. Quart. J. Roy. Meteor. Soc., 126, 1-30, doi:10.1002/qj.49712656202

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