Meteorology and Atmospheric Physics

, Volume 75, Issue 3, pp 161–193

The Advanced Regional Prediction System (ARPS) – A multi-scale nonhydrostatic atmospheric simulation and prediction model. Part I: Model dynamics and verification


  • M. Xue
    •  Center for Analysis and Prediction of Storms, University of Oklahoma, Norman OK 73019
  • K. K. Droegemeier
    •  Center for Analysis and Prediction of Storms, University of Oklahoma, Norman OK 73019
  • V. Wong
    •  Center for Analysis and Prediction of Storms, University of Oklahoma, Norman OK 73019

DOI: 10.1007/s007030070003

Cite this article as:
Xue, M., Droegemeier, K. & Wong, V. Meteorol Atmos Phys (2000) 75: 161. doi:10.1007/s007030070003


 A completely new nonhydrostatic model system known as the Advanced Regional Prediction System (ARPS) has been developed in recent years at the Center for Analysis and Prediction of Storms (CAPS) at the University of Oklahoma. The ARPS is designed from the beginning to serve as an effective tool for basic and applied research and as a system suitable for explicit prediction of convective storms as well as weather systems at other scales. The ARPS includes its own data ingest, quality control and objective analysis packages, a data assimilation system which includes single-Doppler velocity and thermodynamic retrieval algorithms, the forward prediction component, and a self-contained post-processing, diagnostic and verification package.

The forward prediction component of the ARPS is a three-dimensional, nonhydrostatic compressible model formulated in generalized terrain-following coordinates. Minimum approximations are made to the original governing equations. The split-explicit scheme is used to integrate the sound-wave containing equations, which allows the horizontal domain-decomposition strategy to be efficiently implemented for distributed-memory massively parallel computers. The model performs equally well on conventional shared-memory scalar and vector processors. The model employs advanced numerical techniques, including monotonic advection schemes for scalar transport and variance-conserving fourth-order advection for other variables. The model also includes state-of-the-art physics parameterization schemes that are important for explicit prediction of convective storms as well as the prediction of flows at larger scales.

Unique to this system are the consistent code styling maintained for the entire model system and thorough internal documentation. Modern software engineering practices are employed to ensure that the system is modular, extensible and easy to use.

The system has been undergoing real-time prediction tests at the synoptic through storm scales in the past several years over the continental United States as well as in part of Asia, some of which included retrieved Doppler radar data and hydrometeor types in the initial condition.

As the first of a two-part paper series, we describe herein the dynamic and numerical framework of the model, together with the subgrid-scale turbulence and the PBL parameterization. The model dynamic and numerical framework is then verified using idealized and realistic mountain flow cases and an idealized density current. Other physics parameterization schemes will be described in Part II, which is followed by verification against observational data of the coupled soil-vegetation model, surface layer fluxes and the PBL parameterization. Applications of the model to the simulation of an observed supercell storm and to the prediction of a real case are also found in Part II. In the latter case, a long-lasting squall line developed and propagated across the eastern part of the United States following a historical number of tornado outbreak in the state of Arkansas.

Copyright information

© Springer-Verlag Wien 2000