1. Past trends in public health relevant characteristics of U.S. extreme heat events Evan M. Oswald, Richard B. Rood

2. Motivation 1.Past changes in extreme heat event (EHE) risk 2.Assist in future forecasting of EHE risk 3.United States Historical Climate Network (USHCN) monthly dataset version 2-based trends Hypotheses 1.Continental average trends exist 2.Regional-scale spatial structure exists in those trends 3.Extreme heat event trends are a function of which daily metric(s) used 4.Strong relationships with summer average temperature trends

3. Dataset 1.USHCN monthly dataset version 2 2.USHCN daily dataset version 1 3.Day-to-day variability transferred onto monthly values 4.Station selection criteria Study details 1.EHE def: 92.5 th percentile, 2 dates, running mean > 92.5 th percentile 2.Types: Tmin, Tmax, “Tmnx” 3.EHE Characteristics: 1.All encompassing metrics: No. EHE days per summer, sum intensity 2.Specific EHE characteristics: mean duration, mean intensity, No. EHEs per summer 3.Special interest metrics: No. of EHE days before July 1st

4. Continental averages EHE characteristics EHE type

5. Spatial Maps (1970-2010) Tmin type Tmnx type Tmax type

6. Spatial Maps (1930-2010) Tmin type Tmnx type Tmax type Longer trends = bigger decrease, smaller increase

7. Relationship with summer mean trends

8. Relationship with early season events

9. Conclusions 1.Continental averages a)Increasing trends: 1970-2010 b)Small trends: 1930-2010 2.Spatial structure a)Upper midwest / Eastern Central US feature. 3.Relationships a)Characteristics b)Different daily extremes c)Seasonal averages d)Early season

10. Things to think about 1.Climatologists a)Mapping data of different temporal resolutions b)Warming hole, extreme temperatures c)Trend sensitivity (distribution, season) 2.End-users a)EHE definition: daily extreme sensitivity b)Trend sensitivity c)Summer average vs summertime EHE trends d)Early season vs summertime EHE trends