Simulated meteorological input for agricultural models

• Published in: Agricultural and forest meteorology 1997-12, Vol.88 (1), p.241-258
• Main Authors: Wallis, Trevor W.R., Griffiths, John F.
• Format: Article
• Language: English
• Subjects: Agricultural models; Climatic zones; Simulated weather; Weather
• ISSN: 0168-1923; 1873-2240
• DOI: 10.1016/S0168-1923(97)00035-X

Many agricultural models need an input of daily weather, and a common way of accommodating this is by simulation. Long daily records are rare for agricultural sites, but it is usually possible to obtain climatic parameters to use as input for a s stochastic model. An additional advantage to simulated weather is that many likely sequences can be generated, whereas observation furnishes only a single realization. The objective of this study was to develop a model to simulate weather records, that places emphasis on realistic variability, sequences, extremes and cross-correlation, as well as mean conditions. The model was designated Simulated Meteorological Input for Agricultural Models (SIMIAM), and relies on selection of air mass as the first stochastic step. All required variables are then generated using air mass statistics. The day's wet or dry character is ascertained by first-order Markov chain and, if wet, precipitation amount simulated in a two-parameter gamma distribution. A weakly-stationary generating system, that incorporates matrices of cross and auto-correlation coefficients, is used to simulate all other variables, including winds. Amarillo, Texas records were used to demonstrate model feasibility. Significantly different air masses were shown to be identifiable by gradient level wind directions, and their sequence was adequately modeled with a first-order Markovian process. SIMIAM was tested for Amorillo, Oklahoma City, and New Orleans, using 15 years of record to compute input (1961–1975), and comparing simulations against an independent 15 years of observations (1976–1990). Results indicated that the study objectives were mostly satisfied for the two inland cities. As input was compiled from discontinuous, multiple, area sources, these tests were robust. They were also considered to demonstrate model applicability, not only to point locations, but to areas of the south central United States. Test results for New Orleans were less acceptable, and further study is clearly necessary to achieve model transportability to different climatic zones.