Tuesday, November 14, 2006
141-15
Weather Analogue: A Tool for Simulation of Daily Weather Data.
Mohammad Bannayan, Univ of Georgia, Dept. of BAE,, 1109 Experiment St, Griffin, GA 30223 and Gerrit Hoogenboom, Univ of Georgia, Dept. of BAE,, 1109 Experiment St, Griffin, GA 30223.
Availability of weather predictions with adequate lead time is an essential part of agricultural productivity forecasting. Incorporating the simulated weather data with a crop process based simulation model is considered as an added value to the forecasting of weather data. However, there is always a mismatch between the spatial and temporal scale of the outputs of dynamic climate models and what required as input for crop process based simulation models. A means of predicting future climate data is needed as standalone or as part of a decision support system. Among nonparametric approaches the K-nearest-neighbor (K-NN) approach showed more promising. Applied algorithm in this approach based on similarity of target year and historical year daily weather data, selects a specified number of days similar to characteristics to the day of interest. One of these days is randomly resampled to predict the weather of the next day. The objective of this study was to describe a weather analogue modeling tool for predicting daily weather data based on K-NN approach. We used the original K-NN algorithm, as briefed above, to predict daily weather data along with introducing two more methodologies. In the first methodology, we used the average of selected days weather data instead of re-sampling one day using probability weightings. The second methodology was based on the idea that we have recorded the antecedent weather data up to yesterday, but that the remainder of the weather data has not been recorded yet. Based on this approach the developed application is able to find the best match for the rest of the year based on the observed historical data. Our results showed that the developed application is able to track the observed data for 2005 of two different sites in Georgia.
Handout (.pdf format, 182.0 kb)