Analysis of errors introduced by geographic coordinate systems on weather numeric prediction modeling

Yanni Cao, Guido Cervone, Zachary Barkley, Thomas Lauvaux, Aijun Deng, Alan Taylor

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Most atmospheric models, including the Weather Research and Forecasting (WRF) model, use a spherical geographic coordinate system to internally represent input data and perform computations. However, most geographic information system (GIS) input data used by the models are based on a spheroid datum because it better represents the actual geometry of the earth. WRF and other atmospheric models use these GIS input layers as if they were in a spherical coordinate system without accounting for the difference in datum.

When GIS layers are not properly reprojected, latitudinal errors of up to 21 km in the midlatitudes are introduced. Recent studies have suggested that for very high-resolution applications, the difference in datum in the GIS input data (e.g., terrain land use, orography) should be taken into account. However, the magnitude of errors introduced by the difference in coordinate systems remains unclear. This research quantifies the effect of using a spherical vs. a spheroid datum for the input GIS layers used by WRF to study greenhouse gas transport and dispersion in northeast Pennsylvania.

Original languageEnglish (US)
Pages (from-to)3425-3440
Number of pages16
JournalGeoscientific Model Development
Volume10
Issue number9
DOIs
StatePublished - Sep 19 2017

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Numerics
Weather
Geographic information systems
Geographic Information Systems
weather
Prediction
prediction
Modeling
modeling
Forecasting
gas transport
orography
Greenhouse gases
Land use
Spherical coordinates
Greenhouse Gases
greenhouse gas
Land Use
Earth (planet)
co-ordinate system

All Science Journal Classification (ASJC) codes

  • Modeling and Simulation
  • Earth and Planetary Sciences(all)

Cite this

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Analysis of errors introduced by geographic coordinate systems on weather numeric prediction modeling. / Cao, Yanni; Cervone, Guido; Barkley, Zachary; Lauvaux, Thomas; Deng, Aijun; Taylor, Alan.

In: Geoscientific Model Development, Vol. 10, No. 9, 19.09.2017, p. 3425-3440.

Research output: Contribution to journalArticle

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