Influence of high-resolution surface databases on the modeling of local atmospheric circulation systems

L M S Paiva,L C G Pimentel,G C R Bodstein

doi:10.5194/gmd-7-1641-2014

Abstract

Abstract. Large-eddy simulations are performed using the Advanced Regional Prediction System (ARPS) code at horizontal grid resolutions as fine as 300 m to assess the influence of detailed and updated surface databases on the modeling of local atmospheric circulation systems of urban areas with complex terrain. Applications to air pollution and wind energy are sought. These databases are comprised of 3 arc-sec topographic data from the Shuttle Radar Topography Mission, 10 arc-sec vegetation-type data from the European Space Agency (ESA) GlobCover project, and 30 arc-sec leaf area index and fraction of absorbed photosynthetically active radiation data from the ESA GlobCarbon project. Simulations are carried out for the metropolitan area of Rio de Janeiro using six one-way nested-grid domains that allow the choice of distinct parametric models and vertical resolutions associated to each grid. ARPS is initialized using the Global Forecasting System with 0.5°-resolution data from the National Center of Environmental Prediction, which is also used every 3 h as lateral boundary condition. Topographic shading is turned on and two soil layers are used to compute the soil temperature and moisture budgets in all runs. Results for two simulated runs covering three periods of time are compared to surface and upper-air observational data to explore the dependence of the simulations on initial and boundary conditions, grid resolution, topographic and land-use databases. Our comparisons show overall good agreement between simulated and observational data, mainly for the potential temperature and the wind speed fields, and clearly indicate that the use of high-resolution databases improves significantly our ability to predict the local atmospheric circulation.

Highlights

Numerical modeling of unsteady three-dimensional turbulent atmospheric flow is a natural approach to describe mean properties of various physical processes that are not often captured by field measurements collected at a few scattered points in space
Numerical simulations of the atmospheric boundary layer (ABL) flow are strongly influenced by several factors; namely, the parametric models adopted in the boundary value problem that represents the physical situation, the numerical methods applied to solve the conservation equations, the numerical-grid scheme, and the boundary conditions related to the synoptic forcing and surface databases
In order to reduce the influence of these factors, we incorporate into Advanced Regional Prediction System (ARPS) the 3 arc-sec Shuttle Radar Topography Mission (SRTM) topographic database, the 10 arc-sec European Space Agency (ESA) vegetation-type database and the 30 arc-sec ESA leaf area index (LAI) and FAPAR databases, which are preprocessed by subroutines we developed for the ARPS architecture

Summary

Introduction

Numerical modeling of unsteady three-dimensional turbulent atmospheric flow is a natural approach to describe mean properties of various physical processes that are not often captured by field measurements collected at a few scattered points in space. One of the most robust, versatile and modular mesoscale models designed to resolve atmospheric flows in many scales is the Advanced Regional Prediction System (ARPS; Xue et al, 1995, 2000, 2001). The ARPS code solves a set of partial differential equations (PDEs) written for the three-dimensional, compressible time-dependent atmospheric flow, under dry, moist and nonhydrostatic conditions. ARPS is a typical mesoscale model that can be run at fine space and time resolutions in order to be able to represent highly complex terrain based on the high-resolution surface databases that are available nowadays. ARPS incorporates heterogeneous land-surface conditions and time-dependent synoptic boundary forcing, but they are typically limited by outdated coarse resolution. As other current mesoscale models – such as Weather Research and Forecasting (WRF; Skamarock et al, 2001, 2005), Fifth-Generation National Center for Atmospheric Research (NCAR)/Penn State Mesoscale Model (MM5; Grell et al, 1993; Dudhia et al, 2005), Regional Atmospheric Modeling System (RAMS; Walko et al, 1995), Meso-Eta Model (Black, 1994), Mesoscale Non-Hydrostatic Model (MesoNH; Lafore et al, 1998), and Aire Limitee Adaptation Dynamique Developement International (ALADIN; Bubnová et al, 1993; Radnóti et al, 1995; Horányi et al, 1996) –

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