Hi Emily – This is set 5 of our detailed slides. Looking at heatwaves – recall Kristen defined a 95 th percentile for the months of May to October. Being a bit more restrictive here we’ve looked at July-October (123 days) for 30 years ( ) to find what is the 95 th percentile tmax at our 26 sites. A very warm day near the coast will be in the low 80s. Inland this reaches into the upper 80s and low 90s. For the desert regions this will be in the upper 100s to low 110s. For San Diego Lindbergh the value is 85 o F.

Looking at what a warm night means for our 26 sites – it is a bit warmer at the coast compared to some of our inland/mountain sites. Remains quite warm in the desert (80s). For San Diego Lindbergh the value is 71 o F.

For 1985 and 2013 what kind of heatwave events did we see? We’ve defined the temperature “breaks” from which we define a heatwave at the 95 th percentile of the Jul-Oct period. A heatwave lasts at least two days. The total number of days include heatwave days/nights and individually hot days/nights. San Diego Lindbergh 95 th percentile tmax is o F (29.4 o C) and 95 th percentile tmin is o F (21.7 o C). We see quite a bit of variability from year to year in heat waves so we’ll look at two years near our 1985 and 2013 targets. San Diego Lindbergh Tmax (daytime) heat waves Tmin (night) heat waves Tmax total # of days (daytime) Tmin total # of days (night) 1985 Jun 30-Jul 3 Jul 9-10 Aug Jul 1-3 Jul Jul Aug Aug Sep Aug Aug Sep 5-8 Sep Aug Oct 5-6 Aug Sep Looking at these two pairs of years (generally one warmer and one cooler in each pair) we see a total 1985/86 warm day/night periods of 12/14. In 2012/13 the total warm day/night periods is 15/22. The total number of day/night for 1985/86 is 26 and for 2012/13 is 37. Total (day/night) warm periods increase from 1985/86 to 2012/13 by 42%. Total increase in day periods is 25% and in night periods is 57%. For 2 day events we go from day/night totals of 8 to 10 (25 % increase).

To look at the projected temperature data we stayed with the CNRM CM5 model and used the RCP8.5 scenario. Recall for the precipitation we considered data that had been interpolated to a common 2x2 grid (Suraj). This is reasonable with the global climate model precipitation as rainfall is not severely influenced by the land/sea boundary in our region. However with temperature we see a strong influence of the ocean water (which won’t see the day/night variation we see over land). Thus interpolating the data really mixes the land/sea boundary more than is reasonable to consider questions of heatwaves. In a few weeks we hope to replace both the precipitation and temperature data from the global climate models (directly; as used here) with data from these models that has been statistically downscaled. The statistical downscaling will remove model bias (if a model tends to be warmer or wetter than observations) and will represent a more geographically realistic interpretation of the global climate model simulations.

Since we know the ocean “grid” cells won’t see as much day/night variation we select carefully which cell we look at from the CNRM CM5 model. We’ve selected a grid cell centered at N (San Diego Lindbergh is at 32.7N). San Diego Lindbergh is at longitude 117.2W. From the global climate model grid (CNRM CM5) there is a grid cell centered at W. This cell is only 11.2% land so this will have too much ocean influence. The grid cell to the east is centered at W and is 94.9% land. So the numbers below will reflect information for this (large) grid cell region. For the model we have a different “region” so we need to define the 95 th percentile values. The models provide a “historical” simulation from which the models “see” just atmospheric concentrations of greenhouse gases as observed; the models are “fed” no other knowledge of observations. Thus for the historical simulations we do not expect any kind of match to real-world data (1982/83 may have been a very wet winter but if the models showed a wet winter in 1982/83 that would not be related to observations). Over a long-term period (say 30 years) we do expect the models to provide a reasonable match to observed data. For example, the 30-year average July maximum temperature will be close between the model and observations (considering the region covered by the model and possible model bias). In general we don’t look directly at the model values but rather at changes from historical. By that I mean if the model gives us a temperature of 110 o F on July 10 th, 2050, we would not look at the full value but rather at the difference between July 10 th, 2050, and an average of July 10 th values from the historical simulation (say ). If that average July 10 th value was 98 o F then we would save it is 12 o F warmer in 2050 as compared to the historical simulation.

With all the caveats in mind we will “cheat” and look at the actual model values for our grid cell (perhaps best representative of the part-inland San Diego to mostly-desert San Diego region). From the historical simulation July-October period we have a 95 th percentile tmax of o F and a 95 th percentile tmin of 69.0 o F. For comparison the grid cell to the west (our mostly ocean grid cell) has a 95 th percentile tmax of 86.2 o F and a 95 th percentile tmin of 77.1 o F. CNRM CM5 Tmax (daytime) heat waves Tmin (night) heat waves Tmax total # of days (daytime) Tmin total # of days (night) 1989 Aug 1-8 Aug Sep 8-9 Aug Aug 3-6Aug Jul Jul 31-Aug 2 Aug 5-7 Aug Sep 5-6 Jul Aug Aug Sep 6-9 Sep Jul Jul Aug Jul Aug Sep Looking at these two pairs of years (generally one warmer and one cooler in each pair) we see a total 1989/90 warm day/night periods of 19/10. In 2049/50 the total warm day/night periods is 30/34. The total number of day/night for 1989/90 is 29 and for 2049/50 is 64. Total (day/night) warm periods increase from 1989/90 to 2049/50 by 121%. Total increase in day periods is 58% and in night periods is 240%. For number of 2-day events (day and night) we go from 6 to 16 – an increase of 167%.

Heatwaves get longer Heatwaves get warmer at night Below the bar length represents the increase in hot days. We use the observed San Diego Lindbergh data for changes from 1985 to We use the CNRM CM5 data for changes from 1985 to If we take the general number of increase at 42% then we have a bar length of 1.0 for 1985 and 1.42 for For 2050 we see the general increase at 121% so the bar length is Using the night 2013 increase in days we see a 57% increase so the bar height goes from 0.2 to The 2050 night increase is 240% so the bar height goes from 0.2 to The intensity of the shading represents the increase in the number of 2-day events. An increase of 25% for 2013 and an increase of 167% for The red color is 80% transparent for % less transparent for 2013 (transparent at 60%). And for 2050 there is zero transparency. Heatwaves become more frequent