# Taking Future Climate into Account

The time-averaged weather data contained in an EPW file is inherently flawed because it relies on historical data.  Buildings designed only ten years ago using historical data are already outdated. But climate change forecasting is a complex modeling process that relies on modular sub-models with intricate interdependencies and is fraught with uncertainty. Climate models are also continually changing; for example, the chart below compares changes to the resolution of the climate models used by the Intergovernmental Panel on Climate Change (IPCC) over the past 30 years. Advances in science and technology have allowed for higher resolution models that consider far more factors than possible in the 1990s.

<table><thead><tr><th width="201.85830213511474">Climate Models</th><th width="221.33333333333331">1990</th><th>2021</th></tr></thead><tbody><tr><td><strong>Scale (Resolution)</strong></td><td>Global General Circulation Models (500 km)</td><td>Global Earth System Models (100km) and Regional High-Resolution Models (25-50 km)</td></tr><tr><td><strong>Major Elements</strong></td><td>Circulating Atmosphere &#x26; Ocean Radiative Transfer Land Physics Sea Ice</td><td>Circulating Atmosphere &#x26; Ocean Radiative Transfer Land Physics Sea Ice Atmospheric Chemistry Land Use / Cover Land &#x26; Ocean Biogeochemistry Aerosol &#x26; Cloud Interactions</td></tr></tbody></table>

There are tools you can use to shift weather data given outcomes from global climate models. A simple tool to get started with is available from the University of Maryland Center for Environmental Sciences. They have a web-based [mapping tool](https://fitzlab.shinyapps.io/cityapp/) that allows you to visualize weather “shifts” in the future based on location.


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