Generative weather imaging for climate prediction

A system comprising:

• one or more processors configured to perform operations comprising:
• obtaining first real-time observational data of a specified location, the first real-time observational data comprising one or more surface observations of the specified location;
• generating, using an artificial intelligence (AI) radar image generation model, and based on the first real-time observational data, a virtual weather surveillance radar (WSR) image of the specified location, wherein the AI radar image generation model is trained to generate the virtual WSR image using a historical WSR image dataset comprising historical WSR images from one or more pre-selected weather event search results, wherein training the AI radar image generation model includes:
• for each of the one or more pre-selected weather event search results, retrieving a sequence of WSR objects from a historical WSR database, wherein the sequence of WSR objects are associated with a nearest WSR by distance, are located within a specified distance of one or more corresponding pairs of location values, and are captured within a specified time frame;
• extracting from each of the WSR objects, a base reflectivity radar image, a composite reflectivity radar image, and a radial velocity radar image;
• and
• identifying at least one suitable training image sequence from the extracted radar images;
• generating one or more climate profiles for the specified location based on the virtual WSR image, the first real-time observational data, and one or more contemporaneous satellite images of the specified location;
• and
• presenting the one or more climate profiles to a user interface of a user to permit the user to interact with the one or more climate profiles.

One or more non-transitory computer-readable media storing instructions that, when executed by one or more processors, cause a system to perform operations, the operations comprising:

• obtaining first real-time observational data of a specified location, the first real-time observational data comprising one or more first surface observations of the specified location;
• generating, using an artificial intelligence (AI) radar image generation model, and based on the first real-time observational data, a virtual weather surveillance radar (WSR) image of the specified location, wherein the AI radar image generation model is trained to generate the virtual WSR image using a historical WSR image dataset comprising historical WSR images from one or more pre-selected weather event search results, wherein training the AI radar image generation model includes:
• for each of the one or more pre-selected weather event search results, retrieving a sequence of WSR objects from a historical WSR database, wherein the sequence of WSR objects are associated with a nearest WSR by distance, are located within a specified distance of one or more corresponding pairs of location values, and are captured within a specified time frame;
• extracting from each of the WSR objects, a base reflectivity radar image, a composite reflectivity radar image, and a radial velocity radar image;
• and
• identifying at least one suitable training image sequence from the extracted radar images;
• generating one or more first climate profiles for the specified location based on the virtual WSR image, the first real-time observational data, and one or more contemporaneous satellite images of the specified location;
• and
• presenting the one or more climate profiles to a user interface of a user to permit the user to interact with the one or more climate profiles.