Generating and conveying comprehensive weather insights at fields for optimal agricultural decision making
AssigneeClimate LLC
InventorsFrederick Anthony Eckel, Gregory Reid Herman, Christopher Goodman
Life of this patent
Estimating the term…
Abstract
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.
Claims19
A computer-implemented method, comprising:
- obtaining, by a processor, an ensemble of weather models for forecasting weather conditions at a field associated with an agricultural operation;
- obtaining, by the processor, output data from executing the ensemble of weather models for a past period of time;
- receiving observed weather data for the past period of time;
- generating, by the processor, calibrating data from the output data and the observed weather data, using machine learning techniques;
- updating the ensemble of weather models to an ensemble of updated weather models based on the calibrating data;
- executing the ensemble of updated weather models for a future time to generate a list of weather forecasts for the field;
- computing a probability distribution function (PDF) based on the list of weather forecasts;
- causing displaying a stacked bar graph based on the PDF.
One or more non-transitory computer-readable media storing instructions which, when executed by one or more processors, cause the one or more processors to perform comprising:
- obtaining an ensemble of weather models for forecasting weather conditions at a field associated with an agricultural operation;
- obtaining output data from executing the ensemble of weather models for a past period of time;
- receiving observed weather data for the past period of time;
- generating, by the processor, calibrating data from the output data and the observed weather data, using machine learning techniques;
- updating the ensemble of weather models to an ensemble of updated weather models based on the calibrating data;
- executing the ensemble of updated weather models for a future time to generate a list of weather forecasts for the field;
- computing a probability distribution function (PDF) based on the list of weather forecasts;
- causing displaying a stacked bar graph based on the PDF.
Dependencies are inferred from the claim text.