Estimating rainfall adjustment values

A computer-implemented method comprising:

• using rainfall calculation instructions in a server computer system, receiving one or more agricultural data records that represent observed agricultural data points for specific geo-locations at a specific time, wherein the observed agricultural data points include observed radar data from a radar source and observed rain-gauge data from one or more rain gauges that comprise a plurality of precipitation data values;
• using the rainfall calculation instructions, aggregating the one or more agricultural data records into one or more agricultural data sets, where each agricultural data set from the one or more agricultural data sets represents a single type of observed agricultural data;
• using the rainfall calculation instructions, transforming the one or more agricultural data sets into one or more agricultural distribution sets, where the one or more agricultural distribution sets represent a normalized distribution of the one or more agricultural data sets;
• using covariate matrix generation instructions in the server computer system, generating a covariate matrix from the one or more agricultural distribution sets and storing the covariate matrix in digital memory, by deriving at least some values within the covariate matrix from the one or more agricultural distribution sets;
• using the covariate matrix generation instructions, determining the at least some values within the covariate matrix as an average difference between the observed rain-gauge data and the observed radar data;
• using rainfall estimation instructions in the server computer system, estimating a set of rainfall values for a set of geo-locations that correspond to the at least some values within the covariate matrix using defined regression parameters from a digital rainfall regression model and previously stored rainfall adjustment data sets;
• and
• using rainfall overlay instructions, generating a digital image of the set of rainfall values, where the digital image corresponds to a digital image of the set of geo-locations with the set of rainfall values overlaid onto the digital image of the set of geo-locations.

A data processing system comprising:

• a memory;
• one or more processors coupled to the memory;
• rainfall calculation instructions stored in memory, executed by the one or more processors, and configured to cause the one or more processors to receive one or more agricultural data records that represent observed agricultural data points for specific geo-locations at a specific time, wherein the observed agricultural data points include observed radar data from a radar source and observed rain-gauge data from one or more rain gauges that comprise a plurality of precipitation data values;
• the rainfall calculation instructions stored in memory, executed by the one or more processors, and configured to cause the one or more processors to aggregate the one or more agricultural data records into one or more agricultural data sets, where each agricultural data set from the one or more agricultural data sets represents a single type of observed agricultural data;
• the rainfall calculation instructions stored in memory, executed by the one or more processors, and configured to cause the one or more processors to transform the one or more agricultural data sets into one or more agricultural distribution sets, where the one or more agricultural distribution sets represent a normalized distribution of the one or more agricultural data sets;
• covariate matrix generation instructions stored in memory, executed by the one or more processors, and configured to cause the one or more processors to generate a covariate matrix from the one or more agricultural distribution sets and storing the covariate matrix in digital memory, by deriving at least some values within the covariate matrix from the one or more agricultural distribution sets and to cause the one or more processors to determine values within the covariate matrix as an average difference between the observed rain-gauge data and the observed radar data for the specific geo-locations;
• and
• parameter estimation instructions stored in memory, executed by the one or more processors, and configured to cause the one or more processors to estimate regression parameters for a digital rainfall regression model using the covariate matrix as a set of covariate values and using the one or more agricultural distribution sets as rainfall observations.

A data processing system comprising:

• a memory;
• one or more processors coupled to the memory;
• rainfall calculation instructions stored in memory, executed by the one or more processors, and configured to cause the one or more processors to receive one or more agricultural data records that represent observed agricultural data points for specific geo-locations at a specific time, wherein the observed agricultural data points include observed radar data from a radar source and observed rain-gauge data from one or more rain gauges that comprise a plurality of precipitation data values;
• the rainfall calculation instructions stored in memory, executed by the one or more processors, and configured to cause the one or more processors to aggregate the one or more agricultural data records into one or more agricultural data sets, where each agricultural data set from the one or more agricultural data sets represents a single type of observed agricultural data;
• the rainfall calculation instructions stored in memory, executed by the one or more processors, and configured to cause the one or more processors to transform the one or more agricultural data sets into one or more agricultural distribution sets, where the one or more agricultural distribution sets represent a normalized distribution of the one or more agricultural data sets;
• covariate matrix generation instructions stored in memory, executed by the one or more processors, and configured to cause the one or more processors to generate a covariate matrix from the one or more agricultural distribution sets and storing the covariate matrix in digital memory, by deriving at least some values within the covariate matrix from the one or more agricultural distribution sets and configured to cause the one or more processors to determine the at least some values within the covariate matrix as an average difference between the observed rain-gauge data and the observed radar data for specific geo-locations;
• rainfall estimation instructions stored in memory, executed by the one or more processors, and configured to cause the one or more processors to estimate a set of rainfall values for a set of geo-locations that correspond to the at least some values within the covariate matrix using defined regression parameters from a digital rainfall regression model and previously stored rainfall adjustment data sets;
• and
• rainfall overlay instructions stored in memory, executed by the one or more processors, and configured to cause the one or more processors to generate a digital image of the set of rainfall values, where the digital image corresponds to a digital image of the set of geo-locations with the set of rainfall values overlaid onto the digital image of the set of geo-locations.