Estimating crop top microclimates from weather station data

Abstract

A mathematical model (Microsim) was developed to estimate the microclimate at the top of nearby crops using inputs of weather station data and some knowledge about crop characteristics, such as height, albedo, and leaf area index. The model was tested using data measured simultaneously over a weather station and over each of two crops ‐ corn and soybean. Temperatures at the top of unstressed, uniform crops on level terrain within 1600 m of a recording weather station were estimated within 1.0° C 96% of the time for a corn crop and 92% of the time for a soybean crop. Winds at crop top were estimated within 0.4 m s^?1 92% of the time for corn and 100% of the time for soybean. Energy balance flux density estimates for the corn crop resulted in correlation coefficients of r > 0.89 for each of R_n, LE, H and G. microsim worked well under atmospheric conditions that ranged from very stable to unstable.

An enhancement was made to the model to describe wind and temperature profiles based on the complete fetch characteristics of the sites. This resulted in significantly better wind estimates, but had the disadvantage of requiring more information about the crop and weather station surroundings.