Impacts of Aerosols on Climate Extremes in the USA Nora Mascioli

Objectives To determine the effect of aerosols on the magnitude, frequency, and duration of extreme weather events relevant to air quality concerns in the historical record. To assess how these extreme events may evolve in the future as a result of changing aerosol and greenhouse gas levels.

Aerosols and Climate Change The most abundant anthropogenic aerosols are sulfate and black carbon. Sulfate aerosols reflect solar radiation back into space, cooling the planet. Black carbon absorbs solar radiation, heating the planet. Aerosol are the dominant source of uncertainty in the net anthropogenic forcing. Source: IPCC AR4 (FAQ 2.1)

Aerosol Indirect Effects Aerosols also affect climate indirectly via their interactions with clouds. Aerosols can act as cloud condensation nuclei (CCN). Clouds form with smaller droplets, making them more reflective (cloud albedo effect) It also theoretically increases the lifetime of the cloud by suppressing precipitation (cloud lifetime effect). Source: IPCC AR4, Ch. 2

Changing Aerosol Emissions Primary anthropogenic sources of aerosols are fossil fuel and biomass burning. Due to air quality regulations, anthropogenic aerosol emissions peaked in the US around Globally, aerosol emissions have not increased significantly since 1970.

Extreme Weather Extreme weather events such as heat waves and dry spells are important for air quality management. How will aerosols effect these events? We will use indices provided by the Expert Team on Climate Change Detection and Indices (ETCCDI) Source: accuweather.com

Extreme Climate Indices For this project, we will use: –Maximum of daily maximum temperature(TXx) –% of days above the 90th percentile daily maximum temperature (TX90) –Warm spell duration (WSDi) –Days with rain above a fixed threshold (R1mm, R10mm, and R20mm) –Consecutive dry days (CDD). Results shown are based on the GFDL-CM3 historical simulations for eastern North America. Source: Giorgi et al, 2000.

Maximum daily maximum temperature (TXx) No clear change between 1860 and the present looking over entire region. However, smaller subregions show changes between the and means that may be statistically significant. TXx from appears cooler than and Difference between and means

Maximum daily maximum temperature (TXx) Left hand plot shows the difference between the and means at each grid cell is the period of peak aerosol emissions in the US shows uniformly higher TXx values, compared with

Warm Days (TX90) PDFs do not show any clear differences between time periods. Can see opposite signed changes in Canada and Eastern U.S. Difference between and means

Warm Spell Duration (WSDi) Similarly, no discernible changes in the pdf between time periods Small changes in WSDi outside of Florida. Although mid-Atlantic and midwest regions saw decreases in TX90 similar to Florida, they do not translate to equal decreases in WSDi. Difference between and means

Number of wet days (R1mm) Large variance and significant deviations on decadal time scales. Over the eastern US, there are general decreases in the number of wet days. Eastern Canada shows an increase in the number of wet days. Difference between and means

Very heavy precipitation days (R20mm) The northeast US shows decreases in the number of extreme precipitation events. Eastern Canada shows a slight increase in the number of extreme precipitation events, although the magnitude of the changes are generally small. Difference between and means

Next Steps Generally, we do not see any significant changes in the distributions of the climate indices examined here. However, results thus far suggest that we may have better luck studying smaller sub-regions. It is also possible that there may be cancellations between the effects of aerosols and greenhouse gases. In order to understand the role of aerosols in affecting these climate indices, we will examine GFDL-CM3’s aerosol only runs, aerosol and ozone only runs, greenhouse gas only runs, and control simulations for the preindustrial and Finally, we will expand our analysis to include other CMIP5 models that have performed aerosol only simulations.

Back up Material

Heavy precipitation days (R10mm) Similar to R1mm and R20mm, we see large decreases in the heavy rain dains over the Northeast, mid-Atlantic, and Midwest US. Heavy rain days increase over Eastern Canada. Difference between and means

Consecutive Dry Days (CDD) Slight decreases in CDD over Canada and southeast US. The magnitude of the anomalies are generally less than a day, so it is unlikely that they are statistically significant. Difference between and means

Global trends in climate extremes Source: Sillman et al, 2013

Global trends in climate extremes Time series of the (a, b) global spatial mean and (c, d) spatial median over all land grid points of consecutive dry days (CDD) from 1948 to 2005 of the ensemble mean (solid) and median (dashed) of 31 CMIP5 (black) and 18 CMIP3 (green) models as well as the reanalysis ERA40 (blue) from 1958 to 2001, ERA interim (cyan) and NCEP2 (orange) from 1979 to 2010, and NCEP1 (red) from 1948 to Source: Sillman et al, 2013