A flexible, integrated system for generating meteorological surfaces derived from point sources across multiple geographic scales

The generation of meteorological surfaces from point-source data is a difficult but necessary step required for modeling ecological and hydrological processes across landscapes. To date, procedures to acquire, transform, and display meteorological information geographically have been specifically ta...

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Bibliographic Details
Published in:Environmental modelling & software : with environment data news 2005-07, Vol.20 (7), p.873-882
Main Authors: Jolly, William M., Graham, Jonathan M., Michaelis, Andrew, Nemani, Ramakrishna, Running, Steven W.
Format: Article
Language:English
Subjects:
Interpolation
Inverse distance weighting
Ordinary kriging
SOGS
Truncated Gaussian filter
Weather
Online Access:Get full text
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Summary:The generation of meteorological surfaces from point-source data is a difficult but necessary step required for modeling ecological and hydrological processes across landscapes. To date, procedures to acquire, transform, and display meteorological information geographically have been specifically tailored to individual studies. Here we offer a flexible, integrated system that employs a relational database to store point information, a modular system incorporating a choice of weather data interpolation methods, and a matrix inversion method that speeds computer calculations to display information on grids of any specified size, all with minimal user intervention. We demonstrate the power of this integrated approach by cross-validating projected daily meteorological surfaces derived from ∼1200 weather stations distributed across the continental United States for a year. We performed cross-validations for five meteorological variables (solar radiation, minimum and maximum temperatures, humidity, and precipitation) with a truncated Gaussian filter, ordinary kriging and inverse distance weighting and achieved comparable success among all interpolation methods. Cross-validation computation time for ordinary kriging was reduced from 1 h to 3 min when we incorporated the matrix inversion method. We demonstrated the system's flexibility by displaying results at 8-km resolution for the continental USA and at one-degree resolution for the globe.
ISSN:1364-8152
1873-6726
DOI:10.1016/j.envsoft.2004.05.003