Tanya L. Spero1, Megan S. Mallard1, Stephany M

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Examining Changes to Extreme Temperatures and Precipitation Across the U.S. Through 2100 Tanya L. Spero1, Megan S. Mallard1, Stephany M. Taylor1,2, and Christopher G. Nolte1 1U.S. EPA Office of Research and Development, Research Triangle Park, NC 2ORISE Presented to: 15th Annual CMAS Conference Chapel Hill, NC 26 October 2016

Responding to a Changing Climate EPA needs better tools to: understand how climate change can affect air pollutants regulated by NAAQS prepare for future extreme weather events at regional and local levels EPA/ORD modeling techniques improve simulated regional climate: Atmospheric circulation Summertime precipitation Effects of lakes Extreme events Small ensemble of regional climate and air quality data dynamically downscaled from global models that contributed to the IPCC Fifth Assessment Report. Future regional climate used with CMAQ to examine projected changes to human health and ecosystems. Parched river bed in California. (LA Times) Figure courtesy NOAA and Climate Central

Developing Downscaling Methodology for Environmental Applications Global climate model creates coarse gridded future climate with world-wide coverage. Use historical data sets to develop downscaling methodology Apply downscaling methodology to future climate simulations Examine air quality- climate change interactions, as well as impacts on human exposure, energy demands, ecosystems, etc. GCM RCM Regional climate model generates gridded higher-resolution climate predictions over focal area.

Downscaling Configuration Global climate: NCAR/DOE Community Earth System Model (CESM) Approximately 1° × 1° resolution 6-h atmospheric data Monthly surface data Data from CMIP5 (most current public archive) Regional climate: Weather Research and Forecasting (WRF) Model 36-km North American domain, 34 layers, hourly output Continuous simulations (no reinitialization) Downscaling options (e.g., Spero et al., J. Climate, 2016) Spectral nudging, YSU PBL, NOAH LSM, USGS LU Study periods “Historical” period: 1995 – 2005 Future periods: 2025 – 2100 following RCP4.5 and RCP8.5

Representative Concentration Pathways RCPs are radiative forcing in W m-2 at 2100 relative to pre-industrial levels. They include socio-economic and emissions drivers from existing literature. RCPs were used in CMIP5 global models for the IPCC 5th Assessment Report. van Vuuren et al., Climatic Change, 2011

2-m Temperature Bias CESM-WRF (1995–2005) vs. NARR Reanalysis **GCM “historical” data do not correspond directly to observed conditions.** DJF MAM JJA SON Tmax DJF MAM JJA SON Tmin CESM (downscaled by WRF) is biased for the “historical” period. Biases are not systematic in Tmax and Tmin either spatially or by season. Biases are less pronounced in US than in Canada Mexico.

Regional Analysis using NCEI U.S. Climate Regions www.ncdc.noaa.gov

Annual Mean Temperature

Temperature Maximum Temperature Minimum Changes in Tmax & Tmin (K): Summer (JJA) 2035 2050 2065 2080 2095 RCP4.5 Temperature Maximum RCP8.5 RCP4.5 Temperature Minimum RCP8.5

Temperature Maximum Temperature Minimum Changes in Tmax & Tmin (K): Winter (DJF) 2035 2050 2065 2080 2095 RCP4.5 Temperature Maximum RCP8.5 RCP4.5 Temperature Minimum RCP8.5

Change in Annual Precip (mm) RCP 4.5 2035 2065 2095 RCP 8.5 2035 2065 2095

Change in Days with Precip > 0.5 in RCP 4.5 2035 2065 2095 RCP 8.5 2035 2065 2095

Change in Summer Days (Tmax > 25°C) RCP 4.5 2035 2065 2095 RCP 8.5 2035 2065 2095

Change in Tropical Nights (Tmin > 20°C) RCP 4.5 2035 2065 2095 RCP 8.5 2035 2065 2095

Change in Frost Days (Tmin < 0°C) RCP 4.5 2035 2065 2095 RCP 8.5 2035 2065 2095

Jan and Apr: Regional Changes in Diurnal 2-m Temperature (K) Southwest Upper Midwest Southeast 5 4 3 2 1 5 4 3 2 1 5 4 3 2 1 January 5 4 3 2 1 5 4 3 2 1 5 4 3 2 1 April

Jul and Oct: Regional Changes in Diurnal 2-m Temperature (K) Southwest Upper Midwest Southeast 5 4 3 2 1 5 4 3 2 1 5 4 3 2 1 July 5 4 3 2 1 5 4 3 2 1 5 4 3 2 1 October

As Climate is Changing, Extremes are Becoming More Pronounced. Temperature in downscaled CESM (using WRF) follows theory for RCPs. More intense changes in extremes with RCP8.5 compared with RCP4.5. Changes in temperature and precipitation threshold values are locally accentuated. Gradients in terrain and near coastlines for temperature and precipitation. Changes are non-uniform spatially, seasonally, and diurnally. Value of using high-resolution downscaled data. Downscaled future climate and air quality from CMAQ used in EPA’s CIRA2.0 and 4th National Climate Assessment.