back to Janet Zweig Climate Clocks page
  Roll 1
Ocean
Sea Level Rise
Roll 2
Wooded Canyon
Yearly Maximum Temperature
Roll 3
Reservoir
San Diego County Dry Period
 

 

Change in the projected average highest sea level experienced in a year in San Diego, California. Values are calculated using a “business as usual” scenario with no attempts at reducing greenhouse gas emissions, and are for an average year. Because of winter storms and El Niño events, some years would fall above the line and some below.

Projected average hottest day of the year in San Diego for greenhouse gas emissions in a “business as usual” scenario with no attempts at reducing emissions. Values are for an average year. Because of heat waves and cool spells, some years would fall above the line and some below.

Projected driest three consecutive years (in a thirty-one-year period) if greenhouse gas emissions continue in a “business as usual” scenario. For example, the value shown for year 2025 is the average precipitation projected to be seen for the three driest years from 2010 to 2040. Average values are shown; because of wet or dry spells, some three-year droughts would fall above this line and some below.

 

As the climate warms in coming decades, sea level will rise as well, greatly affecting coastal San Diego. Ocean water expands as it gets warmer, which accounts for part of the sea level rise. Land ice in places such as Greenland and Antarctica will increasingly melt away, releasing water to the ocean that will raise sea level even more.
Both effects can already be seen. People have been measuring the ocean’s temperature for decades using everything from simple disposable temperature sensors tossed off commercial ships to autonomous floats that follow the ocean currents, slowly sinking into the deeps and then rising back to the surface where they radio their temperature measurements to satellites. Millions of measurements collected from different instruments over the better part of a century show that the ocean is warming faster than normal variability can account for, and as expected due to society’s releases of greenhouse gases, which warm the planet.
The amount of ice in Greenland and Antarctica is measured by satellites, which are sensitive to minute changes in gravity as those massive ice sheets melt away. Over the years that the satellites have been collecting data they reveal a clear downward trend in the amount of Antarctic and Greenland ice.

To explore what the future holds, scientists use computer models of the Earth’s climate to estimate how continued release of greenhouse gases such as carbon dioxide and methane will warm the planet. This warming will drive more expansion of the oceans and melting of ice, and therefore additional sea level rise.
Sea level already varies due to the tides, storms, and the occasional climate phenomenon known as El Niño, which develops every few years and raises local sea level by six to eight inches during the winter. Our coast gets damaged when there is a convergence of high tide, stormy conditions, and El Niño.

In the future, sea level rise due to the warming Earth will eat away at our beaches and shorelines, and increase the chance that a winter storm or El Niño will cause flooding and property damage. More aggressive action to reduce our emissions of greenhouse gases could limit the rise to two to three feet over a newborn’s life span. On the other hand, if greenhouse gas emissions continue to increase, there could be a four to five foot rise, or more if the uncertain contribution from Antarctica turns out to be more than we currently expect. Considering the damage that high tides, storms, and El Niño already can do to our coast, these increases would have severe consequences.

The rate at which the roll of paper in the artwork is unspooling is based on an estimated sea level rise of four feet over a life span, a value higher than we might get if greenhouse gas emissions are reduced sharply, but not as high as might be reached if nothing is done and more ice melts in Antarctica than estimated. Although additional sea level rise is inevitable at this point, the more greenhouse gas emissions are cut back, the less sea levels will rise in the future.

--David W. Pierce, Division of Climate, Atmospheric Sciences, and Physical Oceanography, Scripps Institution of Oceanography, La Jolla, CA

Data description for climate data used in Roll 1
Ocean

Sea Level RiseThe value plotted is the multi-model ensemble average maximum annual sea level (at the p=0.5 level) from the 8 GCMs that were used to develop hourly sea level data for the 4th California Climate Change Assessment (Pierce et al. 2018). The 8 GCMs with the requisite sea level data are: ACCESS1-0, CMCC-CMS, CanESM2, GFDL-CM3, HadGEM2-CC, HadGEM2-ES, CNRM-CM5, MIROC5. The station location is La Jolla, CA. The scenario used is RCP 8.5 (high emissions). Units are feet.

 


San Diego is fortunate to have a mild year-round climate due to our proximity to the ocean, which dampens coastal temperature swings. Unfortunately, that does not make our region immune to climate change. As greenhouse gases accumulate in the atmosphere, San Diego will warm along with the rest of the planet.

Greenhouse gases warm the planet due to the “greenhouse effect.” Such gases are transparent to sunlight, so they do nothing to diminish solar energy reaching and heating the Earth’s surface. The sunlight heats the Earth’s surface, which emits infrared (heat) radiation upwards, towards space. Historically, the heat lost back into space balanced the heat coming in from the sun. However, greenhouse gases have the peculiar property that although they are transparent to incoming sunlight, they absorb the outgoing infrared (heat) radiation. Greenhouse gases in the atmosphere then warm up and radiate heat back to the Earth, causing the surface temperature to rise.

As greenhouse gas concentrations rise, this effect becomes stronger and causes the temperature increase called “global warming.” In fact, the atmosphere’s concentration of carbon dioxide, an important greenhouse gas, has increased almost 30% since 1950 due to burning fossil fuels, land use changes, and some industrial processes. The effect of this warming can already be seen in the reduction of mountain snowpack across the western U.S., since warmer temperatures mean that more precipitation falls as rain instead of snow, and what snow there is melts earlier in the spring.

This artwork is driven by projected increases in the hottest day of the year in San Diego. Between 1950 and 2000 the average hottest day of the year in San Diego was about 95 °F, with considerable variability year-to-year. As global warming continues over the rest of this century, the average hottest day of the year could increase to about 107 °F if emissions of greenhouse gases continue increasing at the current rate. This would have a significant impact on electrical load for air conditioning, human health (especially for those who work outside or cannot afford air conditioning), wildfire activity, and local ecosystems that are not adapted to such hot temperatures.

Because the amount of global warming that happens in coming years depends on the concentration of greenhouse gases in the atmosphere, how much the average hottest day of the year increases will depend on whether human societies reduce greenhouse gas emissions. If measures are taken to reduce emissions, the rise in the average hottest day of the year could be limited to 102 °F or even less, depending on how sharply such emissions were curtailed.

--David W. Pierce, Division of Climate, Atmospheric Sciences, and Physical Oceanography, Scripps Institution of Oceanography, La Jolla, CA

Data description for climate data used in Roll 2
Wooded Canyon
Yearly Maximum Temperature

The value plotted is the multi-model ensemble average hottest day of each year, taken across the 32 General Circulation Models (GCMs; see Appendix 1) that were downscaled to 1/16th degree spatial resolution as part of the Localized Constructed Analogs statistical downscaling effort for the 4th California Climate Change Assessment (Pierce et al. 2018). The LOCA downscaling method is described in Pierce et al. 2014 and Pierce et al. 2015. The scenario used is Representative Concentration Pathway (RCP) 8.5, which is a “business as usual” (high) emissions scenario. The domain is San Diego county. Units are degrees F.


We live in a semi-arid region, with the San Diego International Airport receiving just over ten inches of rain per year on average. By comparison, San Francisco receives about twice as much, and New York City four times as much. The dry conditions in our region mean that water is a valuable and limited resource.

The amount of precipitation we receive varies widely year-to-year. In fact, the San Diego region has proportionally some of the largest year-to-year variability in total precipitation in the country. Multiple years of low precipitation produce droughts, which have always been a characteristic of our region’s climate. Droughts can affect our daily lives by damaging our county’s agriculture, ecosystems, and some local industries, or even leading to water restrictions in severe events.

As the Earth continues to warm in coming decades, precipitation patterns will change as well. Our dry climate regime is likely to expand northward, reducing the number of wet days San Diego experiences, particularly in the spring and autumn. However, wet days in winter are likely to become wetter, as the Earth’s higher temperatures increase the amount of water vapor in the air (as is sometimes said, “warmer air holds more water”). This combination of effects – fewer wet days, but more precipitation on wet days – will give more year-to-year variability of precipitation. It is like rolling dice; rolling a large number of dice (many wet days in a year) and adding up the total gives a fairly constant value each time, with small fluctuations. Rolling just a few dice (few wet days in a year) gives much more variability in the total each time you roll.

The mechanism in this artwork is driven by how dry the driest three consecutive years in a thirty-one-year period is likely to change in the future. Three-year droughts are important because they are long enough to have significant impacts on ecosystems and society. Historically in San Diego county, three-year droughts have received about 40% less precipitation than the average of 15” per year. In coming decades, climate change could increase this deficit to 49% less than average because of the increasing precipitation variability described above. At the same time, higher temperatures will drive more water loss from plants, exacerbating the effect of the drought on our landscape and wildfire activity.

How regional droughts change in the future partly depends on whether societies continue to emit greenhouse gases at the same rate they are currently. Reducing such emissions would reduce the changes in precipitation and drought. Although our region will always experience dry periods, increased variability and drier extremes would be expensive for people and our local economy to adapt to, and perhaps impossible for some sensitive local ecosystems.

--David W. Pierce, Division of Climate, Atmospheric Sciences, and Physical Oceanography, Scripps Institution of Oceanography, La Jolla, CA

Data description for climate data used in Roll 3
Reservoir
San Diego County Dry Period

The value plotted is the multi-model ensemble average lowest precipitation in a consecutive 3-yr period in a sliding 31-yr window, taken across the 32 General Circulation Models (GCMs; see Appendix 1) that were downscaled to 1/16th degree spatial resolution as part of the Localized Constructed Analogs statistical downscaling effort for the 4th California Climate Change Assessment (Pierce et al. 2018). The scenario used is RCP 8.5. The domain is San Diego county. Units are inches.

Appendix 1

The 32 models downscaled with the LOCA method are:
ACCESS1-0 ACCESS1-3 CCSM4 CESM1-BGC CESM1-CAM5 CMCC-CM CMCC-CMS CNRM-CM5 CSIRO-Mk3-6-0 CanESM2 EC-EARTH FGOALS-g2 GFDL-CM3 GFDL-ESM2G GFDL-ESM2M GISS-E2-H GISS-E2-R HadGEM2-AO HadGEM2-CC HadGEM2-ES IPSL-CM5A-LR IPSL-CM5A-MR MIROC-ESM MIROC-ESM-CHEM MIROC5 MPI-ESM-LR MPI-ESM-MR MRI-CGCM3 NorESM1-M bcc-csm1-1 bcc-csm1-1-m inmcm4

References

Pierce, D. W., D. R. Cayan, and B. L. Thrasher, 2014: Statistical downscaling using localized constructed analogs (LOCA). J. Hydrometeorology, v. 15, p. 2558, doi:10.1175/JFM-D-14-0082.1 
Pierce, D. W., D. R. Cayan, E. P. Maurer, J. T. Abatzoglou, and K. C. Hegewisch, 2015: Improved bias correction techniques for hydrological simulations of climate change. J. Hydrometeorology, v. 16, p. 2421-2442. DOI: http://dx.doi.org/10.1175/JHM-D-14-0236.1
Pierce, D. W., J. F. Kalansky, and D. R. Cayan, 2018: Climate, Drought, and Sea Level Rise scenarios for California’s fourth climate change assessment. California Energy Commission publication CCCA4-CEC-2018-006.