This experiment trains a crop model to artificial data to obtain a model that can be used for forecasting.
1. Top Execute R Script takes weather data (AirtTemps.csv) and a crop model and makes synthetic growth curves of crop yields over time for the years 2010-2014 2. Middle Execute R script runs Filzbach parameter inference code to infer the parameters to the crop growth model given the synthetic datasets 3. Bottom Execute R script takes the inferred parameter values and the temperature data for 2015 to predict the crop growth for that year, and overlays them onto observations. 4. I later manually exported the inferred parameter values to use in a prototype web service.