SUMMARYThe goal of this study is to adapt the multiscale fluid solver EULerian or LAGrangian framewrok (EULAG) to future graphics processing units (GPU) platforms. The EULAG model has the proven record of successful applications, and excellent efficiency and scalability on conventional supercomputer architectures. Currently, the model is being implemented as the new dynamical core of the COSMO weather prediction framework. Within this study, two main modules of EULAG, namely the multidimensional positive definite advection transport algorithm (MPDATA) and the variational generalized conjugate residual, elliptic pressure solver Generalized Conjugate Residual (GCR) are analyzed and optimized. In this paper, a method is proposed, which ensures a comprehensive analysis of the resource consumption including registers, shared, and global memories. This method allows us to identify bottlenecks of the algorithm, including data transfers between host and global memory, global and shared memories, as well as GPU occupancy. We put the emphasis on providing a fixed memory access pattern, padding as well as organizing computation in the MPDATA algorithm. The testing and validation of the new GPU implementation have been carried out based on modeling decaying turbulence of a homogeneous incompressible fluid in a triply-periodic cube. Simulations performed using the standard version of EULAG and its new GPU implementation give similar solutions. Preliminary results show a promising increase in terms of computational efficiency.

A comparison between anelastic and compressible convection-permitting weather forecasts for the Alpine region is presented. This involves mesoscale simulation of a typical westerly flow accompanied by a passage of frontal systems as well as intense airmass convection and orographic convection. The limited-area model employing a 2.2-km horizontal grid length is driven by time-dependent boundary conditions from a coarse-resolution model. The results obtained with the anelastic and the compressible model versions show good agreement. Validations of the 10-m wind, 2-m temperature, 2-m dewpoint temperature, total cloud cover, and surface precipitation against observations for a seven-member forecast ensemble reveal only minor differences between the two configurations. The sensitivity study demonstrates only a small impact of realistic pressure perturbations (about a reference profile) on the solutions. Overall, anelastic approximation proves remarkably accurate in simulating moist mesoscale dynamics. The study has been conducted using a newly developed hybrid limited-area nonhydrostatic version of the Consortium for Small-Scale Modeling (COSMO) model. This version facilitates the use of two alternative dynamical cores: compressible (original) and anelastic (new). The new dynamical core, which is based on the Euler–Lagrangian (EULAG) solver, aims at integrating atmospheric flow equations at resolutions higher than O(1) km for steep orography. A coupler has been developed to merge the EULAG dynamical core with the COSMO numerical weather prediction framework.

The correctness and accuracy of the new implementations are examined based on a standard three-dimensional solid body rotation test case. Additionally, we focus on testing computational efficiency and scalability. In most runs and especially in simulations with larger computational grids the new codes performed better than the traditional implementation.Index Terms-MPDATA, advection solver, parallel computing.

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This paper presents the semi-implicit compressible EULAG as a new dynamical core for convective-scale numerical weather prediction. The core is implemented within the infrastructure of the operational model of the Consortium for Small Scale Modeling (COSMO), forming the NWP COSMO-EULAG model (CE). This regional high-resolution implementation of the dynamical core complements its global implementation in the Finite-Volume Module of ECMWF’s Integrated Forecasting System. The paper documents the first operational-like application of the dynamical core for realistic weather forecasts. After discussing the formulation of the core and its coupling with the host model, the paper considers several high-resolution prognostic experiments over complex Alpine orography. Standard verification experiments examine the sensitivity of the CE forecast to the choice of the advection routine and assess the forecast skills against those of the default COSMO Runge-Kutta dynamical core at 2.2 km grid size showing a general improvement. The skills are also compared using satellite observations for a weak-flow convective Alpine weather case-study, showing favorable results. Additional validation of the new CE framework for partly convection-resolving forecasts using 1.1 km, 0.55 km, 0.22 km, and 0.1 km grids, designed to challenge its numerics and test the dynamics-physics coupling, demonstrates its high robustness in simulating multi-phase flows over complex mountain terrain, with slopes reaching 85 degrees, and the flow’s realistic representation.

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Abstract. Meteorological data concerning the severe convective system from the 21 August 2007 are analyzed in this study. Compiled information allows to understand the reason for the storm development and to identify its fundamental convective mode. Next, the EULAG model is utilized to perform an idealized test that shows a downwind-developing storm growth in an environment comparable to the one that was observed on the 21 August 2007 in the Masurian Lake District. Finally, the COSMO numerical weather prediction model is applied to reconstruct the storm development. The experiment is carried out for various computational grids having the horizontal grid length between 7.0 and 0.55 km. It turns out that the COSMO model is capable in simulating storms of that type. Since the model is used for operational weather forecasting in Poland the evaluation of this skill contributes to the increase of public safety.