Abstract

Abstract. A new, highly flexible model system for the seamless dynamical down-scaling of meteorological and chemical processes from the global to the meso-γ scale is presented. A global model and a cascade of an arbitrary number of limited-area model instances run concurrently in the same parallel environment, in which the coarser grained instances provide the boundary data for the finer grained instances. Thus, disk-space intensive and time consuming intermediate and pre-processing steps are entirely avoided and the time interpolation errors of common off-line nesting approaches are minimised. More specifically, the regional model COSMO of the German Weather Service (DWD) is nested on-line into the atmospheric general circulation model ECHAM5 within the Modular Earth Submodel System (MESSy) framework. ECHAM5 and COSMO have previously been equipped with the MESSy infrastructure, implying that the same process formulations (MESSy submodels) are available for both models. This guarantees the highest degree of achievable consistency, between both, the meteorological and chemical conditions at the domain boundaries of the nested limited-area model, and between the process formulations on all scales. The on-line nesting of the different models is established by a client-server approach with the newly developed Multi-Model-Driver (MMD), an additional component of the MESSy infrastructure. With MMD an arbitrary number of model instances can be run concurrently within the same message passing interface (MPI) environment, the respective coarser model (either global or regional) is the server for the nested finer (regional) client model, i.e. it provides the data required to calculate the initial and boundary fields to the client model. On-line nesting means that the coupled (client-server) models exchange their data via the computer memory, in contrast to the data exchange via files on disk in common off-line nesting approaches. MMD consists of a library (Fortran95 and some parts in C) which is based on the MPI standard and two new MESSy submodels, MMDSERV and MMDCLNT (both Fortran95) for the server and client models, respectively. MMDCLNT contains a further sub-submodel, INT2COSMO, for the interpolation of the coarse grid data provided by the server models (either ECHAM5/MESSy or COSMO/MESSy) to the grid of the respective client model (COSMO/MESSy). INT2COSMO is based on the off-line pre-processing tool INT2LM provided by the DWD. The new achievements allow the setup of model cascades for zooming (down-scaling) from the global scale to the lower edge of the meso-γ scale (≈1 km) with a very high degree of consistency between the different models and between the chemical and meteorological boundary conditions.

Highlights

  • The quality of the results of a regional atmospheric model are highly influenced by the conditions prescribed at the model domain boundaries.For the meteorological/dynamical state of limited-area models, these boundary conditions are usually prescribed from analysis, reanalysis or forecast data from global or regional numerical weather prediction models or from global climate models, the so-called driving models1

  • To carry out the on-line coupling, we extended Modular Earth Submodel System (MESSy) by the Multi-Model-Driver (MMD) library and two MESSy submodels (MMDSERV and MMDCLNT)

  • The MMD library manages the data exchange between the individual tasks of the different model executables very efficiently, as the field exchange during the time integration is implemented as point-to-point, single-sided, non-blocking message passing interface (MPI) communication

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Summary

Introduction

The quality of the results of a regional (or limited-area) atmospheric model are highly influenced by the conditions prescribed at the model domain boundaries.For the meteorological/dynamical state of limited-area models, these boundary conditions are usually prescribed from analysis, reanalysis or forecast data from global or regional numerical weather prediction models or from global climate models, the so-called driving models.

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