Insight in Context
LMI complements this industry-leading climate risk data analysis with customer knowledge and deep expertise in relevant policies, processes, and technologies—ensuring recommendations are actionable and easily understood. Results are conveyed in the customer’s terminology with data visualizations—giving leaders the business case to make decisions that promote long-term resilience against current and projected climate-related risks.
The Climanomics™ Platform
The Climanomics™ platform translates data from academic, public, and commercial sources into consistent formats, which is overlaid on coherent spatial and temporal grids. Further statistical processing into probability distribution functions enables hazard data to be coupled with econometric models, producing financial impact curves. The final layer translates data into sectorspecific language and visualizations, ensuring the results are easily understood by the customer. The platform offers the following.
LMI worked with the National Oceanic and Atmospheric Administration’s National Climate Assessment Technical Support Unit to serve the climate scenario needs of key regional and sectoral authors of the Fourth National Climate Assessment. LMI processed and analyzed the latest high-resolution climate-model data for the U.S. based on outputs of 32 climate models to estimate changes in key climate variables as well as indicators and detailed metrics for impacts on people, infrastructure, and elements of the national economy. LMI quantified changes at specific metropolitan areas for approximately 30 different climate variables at daily frequency for 1950–2100 under several scenarios.
Other federal clients include the departments of Defense and Homeland Security, the National Aeronautics and Space Administration, and the General Services Administration
 Government Accountability Office, “Limiting the Federal Government’s Fiscal Exposure by Better Managing Climate Change Risks,” https://www.gao.gov/highrisk/limiting_federal_government_fiscal_exposure/why_did_study, retrieved on 21 October 2019.