HEATWAVES1985

2013

2050

Heatwaves get longer

Heatwaves get warmer at night

Heatwaves become more frequent

Detailed slides: set 6This set continues our look at heatwaves; the bar plot below shows where we ended up from slide set 5. Sasha mentioned we should have a more “girlish” looking 2013 image so that has been updated but is merely for illustrative purposes here. So the question is – how can we show that heat waves will get more humid?

In a basic sense we know the heat waves are getting more humid because the temperature is warmer at night. At night we see the temperature falling towards the dewpoint temperature. The dewpoint temperature tells us how far we have to cool the air for dew to form. Thus a higher dewpoint temperature means the air is more humid. And if we are warmer at night that means the dewpoint temperature is higher.

When we looked at the changes between 1985 and 2013 we looked at the San Diego Lindbergh record. Since this is an airport site we have hourly data and this data includes dewpoint temperature. So for the days that we outlined (slide set #5) we can look at the dewpoint temperature from those events. For this look I’ve selected the dewpoint temperature at the time of the minimum temperature. The dewpoint temperatures are in oC. If we average the values we get 17.0oC for 1985/86 and 18.8oC for 2012/13. So we see an 11% increase in the minimum temperature dewpoint value from 1985 to 2013.

San Diego Lindbergh

Tmin (night) heat waves Dewpoint temperatures

1985Jul 1-3

Jul 10-12Jul 19-21

11.1, 14.4, 16.718.9, 18.3, 18.918.3, 18.9, 18.9

1986 Aug 18-19 16.7, 15.6

2012Aug 12-14Aug 16-20

Sep 5-8Sep 11-12

18.9, 19.0, 19.418.9, 19.0, 19.4, 18.3, 18.9

18.9, 20.0, 17.2, 17.818.3, 18.9

2013 Aug 30-31Sep 4-6

16.7, 19.418.9, 19.4, 19.4

From the global climate model we don’t have hourly dewpoint temperature but we do have near surface (approximately 2meter) specific humidity. Specific humidity is the mass of water vapor in a unit mass of moist air. It is usually expressed as g/kg (grams of water vapor in a kg of moist air). We can look at this to gauge how the night time heat waves are becoming more humid.

CNRM CM5 Tmin (night) heat waves

Daily near surface specific humidity

1989 Aug 2-6 6.0, 6.8, 8.3, 8.3, 6.5

1990 Aug 13-15 10.4, 16.8, 16.1

2049

Jul 15-17Aug 12-17Aug 20-22

Sep 6-9Sep 14-15

7.3, 7.7, 8.18.2, 8.6, 10.6, 14.2, 16.1, 15.6

16.4, 17.1, 14.08.5, 9.1, 9.6, 10.6

16.8, 14.5

2050Jul 17-21

Aug 17-18Sep 2-3

7.7, 7.8, 8.6, 8.3, 11.36.7, 6.8

9.0, 10.3

When we looked at the changes for 2050 (slide set 5) we looked at the CNRM CM5 global climate model simulations. Again we focus on the inland San Diego grid cell which is representative of an area that is partly inland San Diego to mostly desert. The specific humidity values are in g/kg. If we average the values we get 9.9 for 1989/90 and 10.7 for 2049/50. So we see an 8% increase in the specific humidity value from 1989/90 to 2049/50.

HEATWAVES1985

2013

2050

Heatwaves get longer

Heatwaves get warmer at night

more frequent

Heatwaves become

more humid

The little clouds demonstrate the increase in humidity. The 2013 cloud is 11% larger than the 1985 cloud. The 2050 cloud is 8 percent larger. The cloud may not be the most appropriate symbol to use as we would not want the reader to infer more cloudiness.

These are the 6 “bubble” plots that Kristen made for us to show heat wave activity. Sasha thought it would be interesting to look at one plot which shows activity for the 6 regions combined. I’m in touch with Kristen about making this plot and hopefully we’ll have more on this next week (Oct 28 – Nov 1).

Like the bubble plot we’ll take the same 6 sites (8 are shown here) and average the tmax and tmin. Then we’ll plot the tmax and tmin on the same plot – combining this into one plot. We’ll have more on this next week (Oct 28 – Nov 1).

From the average of the 6 sites (tmax and tmin) we’ll make an average “region” temperature. This will replace the black line on the temperature projections plot. We’ll have more on this next week (Oct 28 – Nov 1).

Dan had me make some changes to the water-energy graphics and thought I would share those for your consideration.

20120

20

40

60

80

100

66

13

12

9

San Diego County water use by sectorSDCWA

AgriculturePublicCommercialDomestic

%

Dan had me make some changes to the water-energy graphics and thought I would share those for your consideration. 4

7%

39%

8%5%1%

San Diego region water-related energy useAnnual total = 1712M kWh SDCWA data 2010

End use

Supply and Conveyance

Wastewater Treatment

Distribution

Water Treatment Landscape53%

Toilets10%

Showers/

Baths10%

Faucets9%

Clothes Washers

8%

Leaks8%Other

2%

Water end use breakdown

20120

100

200

300

400

500

356

74

65

47

San Diego County water use by sectorSDCWA

AgriculturePublicCommercialDomestic

AF *

100

0

Staying with the more “primary color” version of this I’ve changed the y-axis units from percent to thousands of acre feet. One acre foot is the amount of water that it would take to cover an acre one foot deep.

Sasha and I talked about making bar graphs from the line graphs below (from Suraj). He felt it was important to emphasize little change in the annual total precipitation but more variability from year to year. I’ll get the data from Suraj so we can make bar graphs (and you can consider binning the data). However we are still thinking about how to emphasize the year-to-year variability. More on this next week (Oct 28-Nov 1).

2013 2050

I’m working on changing the 2013 data shown here (just Lindbergh) to reflect the same six sites – as those we’re going to use for the temperature looks. We’re also working on a version showing the change in year to year variability. Right now I have a bucket with water at the same level but different numbers of holes and different size holes. More on this next week (Oct 28-Nov 1).