Long-term assessment of potential regional and local climate impacts is critical to enable municipalities, businesses and regional economies to prepare for potentially damaging and costly impacts of climate change — from prolonged droughts to more frequent and intense extreme events such as major storms and heat waves.
Unfortunately, the tools commonly used to project future climate impacts, Earth System Models (ESM), are not up to the task. ESMs are too computationally intensive and too expensive to operate at sufficient resolution to provide the necessary local and regional detail.
To this end, a new Study under MIT in the magazine Earth and Space Science uses a regional climate model of the northeastern United States to downscale mid- and late-century climate projections of an ESM under a high-impact emissions scenario at 3-km horizontal resolution. Through downscaling, the output from the ESM was used to drive the regional model to a higher spatial resolution, allowing it to simulate local conditions in greater detail. The resulting high-resolution climate projections consist of more than 200 climate variables at an hourly frequency.
Among other things, the study predicts that between now and the end of the century, the region will experience significantly more days per year on which average and maximum temperatures exceed 86 degrees Fahrenheit and fewer days per year on which the minimum temperature falls below freezing. . At that time in Bostonthe annual number of days where the average temperature exceeds 86 F increases from three to 22, and the number of days when the daily maximum temperature exceeds 86 F increases from 49 to 78.
“Our approach allows the analysis of changes in temperature, precipitation and other climate variables within a single 24-hour period,” he says. Muge Komurcu, the study's lead author and a researcher with the MIT Joint Program on Global Change Science and Policy and the Department of Earth, Atmospheric, and Planetary Sciences (EAPS). “The goal of these projections is to support further climate change impact assessments and sustainability studies in the region.”
Downscaling of climate projections provides climate variables in the analysis needed to assess the impacts of climate change at regional and local scales. As a result, the variables produced in the study can be used as input in other models and analyzes to assess the potential future impact of climate change on extreme rainfall and heat events, regional ecosystems, agriculture, the spread of infectious diseases (e.g. Lyme disease), hydrology, economics and other concerns.
To generate the study's climate variables, the researchers used a high-resolution regional climate model, Weather Research and Forecasting (WRF) model, to downscale mid- and end-of-century climate projections of the Community Earth System Model (CESM) in a high GHG scenario at 3 km horizontal resolution for the northeastern US
To ensure their method is reliable, Komurcu and her co-authors — MIT EAPS professor of atmospheric science Kerry Emanuel and Purdue University professor Matthew Huber and doctoral student Rene Paul Acosta — simulated the process using historical climate observations. They showed that their technique reproduced observed historical average and extreme climate events over a 10-year period.
The study's 200-plus km resolution climate variables span 55 years, covering mid- and late-century time periods.
“To our knowledge, this is the first and only study that has downscaled global model forecasts to such a high resolution over a long period of time for this region,” says Komurcu.
To aid regional climate change impact assessments and sustainability studies in the northeastern US, the researchers plan to release all model input and output files from this study through the University of New Hampshire. Data Distribution Center. The study was supported by the National Science Foundation through the New Hampshire Established Program to Stimulate Competitive Research.
