Schematic representation of the processes included in ICONīesides horizontal and vertical transport processes (so-called adiabatic processes) in the atmosphere, diabatic processes like radiation, turbulence, formation of clouds, and precipitation play a major role for NWP. For ice-covered parts of the oceans, the sea ice fraction is analyzed once per day from observations, whereas the ice thickness and the ice surface temperature are predicted with a simple sea-ice model. The sea surface temperature over ice-free ocean surfaces is analyzed once per day from observations and is kept constant during the ICON forecast. If a snow cover is present, snow water equivalent and snow density are predicted in addition. Over land, additional prognostic equations are solved for soil temperature and soil water content for 7 soil levels. These variables are calculated for all grid cells on 90 terrain-following model levels extending from the surface to a height of 75 km, yielding a total of about 265 million grid points. The most important prognostic variables of ICON are air density and virtual potential temperature (which allows diagnosing the pressure), horizontal and vertical wind speed, humidity, cloud water, cloud ice, rain, and snow. Therefore, DWD operates in addition the high-resolution limited-area model COSMO -DE with a mesh size of 2.8 km. predicting the channeling of the low-level airflow in the Rhine Valley. However, resolving such features can be important for some aspects, e.g. While large mountain ranges can be represented reasonably well at a mesh size of 13 km, capturing individual mountain ranges or valleys requires even finer meshes. This also pertains to the external parameters like the orography (see figure orography of Europa). ICON orography at a mesh size of 13 km for the western part of Europe.Ĭorresponding to the mean area of the triangular grid cells of 173 km², all model variables like density, temperature, wind, humidity, cloud water, cloud ice, rain and snow have to be considered as averages over the cell area of 173 km². temperature, density, moisture quantities) are located in the circumcenter of the triangles, whereas the edge-normal wind components are located in the edge midpoints. All scalar prognostic model variables (e.g. In the current operational version, the global ICON grid has 2,949,120 triangles, corresponding to an average area of 173 km² and thus to an effective mesh size of about 13 km. The effective mesh size of our model grid is defined as the square root of the mean area of the spherical triangles. bisection, trisection) of the triangle edges then yields a model grid with the desired spatial resolution. Connecting the 12 vertices of the icosahedron with geodesic lines yields 20 equilateral spherical triangles with a edge length of about 7054 km. The grid generation starts with an icosahedron inscribed in the sphere. This avoids the so-called pole problem related to the convergence of meridians in lat-lon grids, which poses severe challenges to a computationally efficient implementation. Compared to traditional approaches such as the latitude-longitude grid, icosahedral grids provide a nearly homogeneous coverage of the globe. This basic grid structure was retained for ICON. The predecessor of ICON named GME, which started operational production in December 1999, was the first operational NWP model in the world using an icosahedral grid. Such models depend on lateral boundary conditions provided by a global model throughout their forecast range. All other weather services operating an own forecast model currently restrict themselves to limited-area models focusing on their specific area of interest. Right: Example of an ICON grid with refinement area over EuropeĭWD is one of only fourteen weather services in the world running a global numerical weather prediction (NWP) model. Left: Schematic depiction of the icosahedral grid structure of ICON
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |