Climate data processing and impact prediction systems

A computer-implemented method, the method comprising:

• receiving, by a computing system comprising a processor and a memory, via at least one network, a user indication of a selected climate change scenario from a remote client device;
• identifying, by the computing system, one or more energy factors from among one or more energy sources;
• retrieving, by the computing system, over the at least one network, historical financial information directed to one or more securities from one or more remote financial data sources;
• predicting, by the computing system, one or more future returns for the one or more securities, by applying the historical financial data and the one or more energy factors to at least one hierarchical linear model (HLM);
• adjusting, by the computing system, the predicted one or more future returns based on a first climate scenario and the selected climate scenario, to form respective first adjusted returns and second adjusted returns;
• generating, by the computing system, a climate transition risk for the one or more securities based on a spread between the first adjusted returns and the second adjusted returns;
• and
• providing, by the computing system, a data set representing the climate transition risk to the remote client device.

A non-transitory computer readable medium having instructions stored thereon, which, when executed by a processor, cause the processor to perform an operation comprising:

• receiving, via at least one network, a user indication of a selected climate change scenario from a remote client device;
• identifying one or more energy factors from among one or more energy sources;
• retrieving, over the at least one network, historical financial information directed to one or more securities from one or more remote financial data sources;
• predicting one or more future returns for the one or more securities, by applying the historical financial data and the one or more energy factors to at least one hierarchical linear model (HLM);
• adjusting the predicted one or more future returns based on a first climate scenario and the selected climate scenario, to form respective first adjusted returns and second adjusted returns;
• generating a climate transition risk for the one or more securities based on a spread between the first adjusted returns and the second adjusted returns;
• and
• providing a data set representing the climate transition risk to the remote client device.