The Climate Corporation

Christopher Goodman

Frederick Anthony Eckel

Gregory Reid Herman

Mark Ehrhardt

Atif Khan

John M McNichols

Sourindu Chatterjee

In an embodiment, a computer-implemented method of generating and displaying a comprehensive depiction of a weather element comprises: based on archived forecast model and observed data, training a machine learning model; calibrating current forecast data by applying the machine learning model to yield a calibrated forecast probability density function; displaying graphical representation of recently observed data and calibrated forecast probability density.

Generating and conveying comprehensive weather insights at fields for optimal agricultural decision making

An agricultural apparatus operable in agricultural fields includes one or more digital electronic weather stations affixed to the apparatus and optionally one or more GPS receivers and/or proximity sensors, each coupled to a mobile computing device such as a cab computer. The weather stations transmit data representing wind speed, temperature and/or other weather parameters, as measured on the apparatus, to the mobile computing device. Under control of program logic, the mobile computing device continuously compares real-time, then-current weather data received from the weather stations to programmed or configured threshold values relating to a current agricultural operation. If the weather data indicates weather conditions that exceed one of the thresholds, a warning message may be generated at the mobile computing device to prompt the operator to confirm whether to continue the operation.

Real-time agricultural recommendations using weather sensing on equipment

Growing community of inventors

St. Louis, MO, United States of America

Christopher Goodman