## Summary table: Initialization

chemistry & transport | meteorology | |
---|---|---|

ADREA | One-dimensional wind speed and temperature profiles are provided to be used as initial and boundary conditions. Models are also available for providing the meteorological input data. These are the code FILMAKER which provides meteorological three-dimensional fields from sparse observations and the code ADREA-diagn, a diagnostic meteorological model which provides mass-conserving three-dimensional wind fields | |

ALADIN/A | DFI | |

ALADIN/PL | DFI | |

ARPS | Interpolation of 3-D gridded fields from a global model or from a previous coarser ARPS run. | |

BOLCHEM | Interpolated fields from global models or 1-way nest | Interpolated fields from ECMWF or GFS or 1-way nest |

CALMET/CALPUFF | ||

CALMET/CAMx | restart from previous concentrations | surface data and radiosoundings. |

CLM | digital filter after Lynch (1997) | |

COSMO-2 | Model analysis, if unavailable: interpolated IFS analysis with digital filter after Lynch (1997) | |

COSMO-7 | Model analysis, if unavailable: interpolated IFS analysis with digital filter after Lynch (1997) | |

COSMO-CLM | digital filter after Lynch (1997) | |

COSMO-MUSCAT | Climatological background profiles (or zero) or global data for outermost-nest model as initialisation and boundary values | Interpolated reanalysis data of global model GME or COSMO-DE (DWD, Offenbach, Germany) as initialisation and boundary values |

ENVIRO-HIRLAM | Variant of digital filtering | |

GEM-AQ | fields from previous runs | |

GESIMA | start from 3D synoptic fields without diastrophy (allow 2-3 hours for adjustment) | |

GME | incrementing digital filter initialisation (IDFI) after Lynch (1997) every 6h with averaging of normal modes in order to remove noise | |

Hirlam | Launching DFI a 2-h forward forecast is filtered with DFI and used as starting point for the forecast. The forecast therefore actually starts at analysis time +1h | |

LAMI | ||

LME | operationally: model analysis also possible: interpolated Globalmodell GME analyses with digital filter after Lynch (1997) | |

LME_MH | none in LME_MH (but LME initialized) (MH spin-up time ~1 hour) | |

M-SYS | initialised with measured profiles, precalculation of first day to initialise 3d fields, second day and later to be evaluated | Dynamic initialisation: calculation of balanced fields with 1D pre-processors based on METRAS, cold run starts with flat terrrain and constant large nudging, which decreases during the initialisation phase, restart uses METRAS results to continue |

MC2-AQ | MC2 model uses a type of dynamic initialization. This is performed by first integrating the model forward intime for a small, O(10), number of timesteps (without physics) and then backward to the starting time to begin the forecast itself. As in other models, the initialization timestep is usually smaller then the one used for the regular intergration. | |

MCCM | Horizontally homogeneous typical values or fields extracted from previous simulation | From global model output (identical to MM5) |

MEMO (UoT-GR) | Initialisation is performed with suitable diagnostic methods: A mass-consistent initial wind field is formulated using an objective analysis model. Scalar fields are initialised using appropriate interpolating techniques. Data needed to apply the diagnostics methods may be derived either from observations or from larger scale simulations. | |

MEMO (UoA-PT) | From meteo and landuse and orography data it creates meteo variable fields that characterize the synoptical state, through interpolation. | |

MERCURE | - from radio sounding - interpolation from large scale model fields - use of an objective analysis pre-processing for field campaign (MINERVE code) | |

METRAS | Dynamic initialisation: calculation of balanced fields with 1D pre-processors based on METRAS, cold run starts with flat terrrain and constant large nudging, which decreases during the initialisation phase, restart uses METRAS results to continue | |

METRAS-PCL | Dynamic initialisation: calculation of balanced fields with internal 1D pre-processors based on METRAS-PCL equations | |

MM5 (UoA-GR) | REGRID pre-processor reads archived gridded meteorological analyses and forecasts on pressure levels and interpolate those analyses from some native grid and map projection to the horizontal grid and map projection as defined by the MM5 preprocessor program TERRAIN. REGRID handles pressure-level and surface analyses. Two-dimensional interpolation is performed on these levels. Other types of levels, such as constant height surfaces, isentropic levels or model sigma or eta levels, are not handled. | |

MM5 (UoA-PT) | REGRID pre-processor reads archived gridded meteorological analyses and forecasts on pressure levels and interpolate those analyses from some native grid and map projection to the horizontal grid and map projection as defined by the MM5 preprocessor program TERRAIN. REGRID handles pressure-level and surface analyses. Two-dimensional interpolation is performed on these levels. Other types of levels, such as constant height surfaces, isentropic levels or model sigma or eta levels, are not handled. | |

MM5 (UoH-UK) | The model first generates a hydrostatic input file on the hydrostatic sigma levels which is based on actual surface pressure, not reference pressure. To initialize the data for the nonhydrostatic model a further small vertical interpolation is needed to move to the nonhydrostatic sigma levels. This involves first calculating the heights of the hydrostatic levels, then doing a linear-in-height interpolation of u, v, T and q to the nonhydrostatic levels. Vertical velocity (w) is simply calculated from the pressure velocity (ω) obtained by integrating horizontal velocity divergence vertically while still on the hydrostatic sigma levels. This ω is then interpolated to the nonhydrostatic levels and converted to w (w=-ω/ρg). Pressure perturbation (p′) is initialized to give a hydrostatic balance. Once virtual temperature is known on the nonhydrostatic model levels, the model’s vertical velocity equation in finite difference form is used with the acceleration and advection terms set to zero. This leaves a relation between Tv(z) and the vertical gradient of p′. Given the sea level pressure, p′ at the lowest sigma level can be estimated, and then given the profile of virtual temperature vertical integration gives p′ at the other levels. This balance ensures that the initial vertical acceleration is zero in each model column. | |

MM5(GKSS-D) | Initial conditions are generated from analysis fields (at GKSS: ERA40) on prescribed sigma levels. Pressure, temperature, wind and humidity are interpolated to the specified grid. Surface data and soil information can also be used. | |

Meso-NH | MOCAGE or MOZART | ECMWF, ARPEGE, ALADIN for real cases Possibility of ideal cases. |

NHHIRLAM | Normal mode initialisation | |

RAMS | Spatial interpolation of Global Gridded analysis. | |

RCG | ||

SAIMM | The SAIMM can be initialized using either static or dynamic initialization. Using the static initialization technique, the model is initialized with objectively analyzed fields of wind and potential temperature. Dynamic initialization makes use of the model's inherent adjustments mechanism to bring the wind and temperature fields into balance prior to the initial simulation time. | |

TAPM | The model is initialised at each grid point with values of u, v, θ,q interpolated from the synoptic analyses. Iso-lines of these variables are oriented to be parallel to mean sea level (i.e. cutting into the terrain). Turbulence levels are set to their minimum values as the model is started at midnight. The Exner pressure function is integrated from mean sea level to the model top to determine the top boundary condition. The Exner pressure and terrain-following vertical velocity are then diagnosed using equations. Surface temperature and moisture are set to the deep soil values specified, with surface temperature adjusted for terrain height using the synoptic lapse rate. | |

UM | 3D-VAR: Nudging of analysis increments, weak balance constraint or digital filter all available. First used most generally. | |

WRF-ARW | 3-dimensional initial conditions for real data | |

WRF/Chem |

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