SimCLIM FOR DESKTOP TRAINING EXERCISE

CLIMATE CHANGE AND CLIMATIC EXTREMES:

EFFECTS ON BOP ENERGY DEMAND

THE PROBLEM

Mercury Energy distributes power for the BOP and part of New Zealand. Climate variability and extremes are very important for power generation, affecting both supply and demand. One of the critical periods for Mercury Energy is during the summer months of January and February when the power demand can spike because of increased demand for space cooling. The use of air conditioners has increased dramatically in the region.

The power industry, as well as state and local governments, haves recently become concerned about the risks of such power crises as they affect projections and policies for future long-term regional growth to the year 2050. For these reasons, the industry requests that you carry out two analyses:

  • to assess how climate change might affect future demand for energy, particularly with regard to spatial thresholds regarding the demand for air conditioning;
  • to assess the risks of power failure due to climate extremes in the region, both under current climate and future climate change.

PART 1:

SPATIAL THRESHOLD ANALYSIS FOR ENERGY DEMAND

Mercury Energy (ME) has planned for some incremental increases in energy demand as a basis of its population projections for its region. However, it did not take account of future changes in climate. How might changes in climate affect the per capita demand for power through increased usage of air conditioning?

ME knows that in regions where the average seasonal (in January and February) maximumtemperature is 24 degrees or higher, the use of air conditioners for domestic and commercial purposes is widespread (both in terms of number and intensity of use). Thus, as an indicator, 24 degrees appears to be the threshold that prompts decisions to purchase air conditioners and to use them intensely.

Using the SimCLIM SCENARIO GENERATOR, examine the spatial change of this indicator threshold of 24 degrees for the Bay of Plenty region. Please answer three questions:

TASKS

(1) Analyse the spatial extent of the 24-degree maximum temperature threshold under current climate.

  • What areas currently do not exceed the threshold value? How do these coincide with population distribution?

(2) Analyse the change in spatial extent of the 24-degree maximum temperature threshold under scenarios of climate change for the years 2030 and 2050.

  • How do the areas change as a result of climate change by the years 2030 and 2050?
  • To what extent do the areas of high power demand now coincide with the region’s areas of high population density and growth?

Steps for carrying out the tasks using SimCLIM:

First select the Bay of Plenty from the drop-down menu (far right-side of screen). Then choose

the SpatialScenario Generator option

and select maximum temperature (OK), the year 1990 (OK), and for the months select January and February (OK). You might have to wait a bit for the image to appear.

You should now have an image of average maximum temperature for January-February for the selected Bay of Plenty region. In order to view the entire area, grab the top-right corner and drag to the left (if you “un-tick” the boundary.vec option you will have a better image).

In order to identify the areas falling below the 24 degree threshold, select the Displayfrom the Tools drop-down menu, which looks like:

For Minimum Value enter 24 and click OK.

On the image the grey areas are “cool” and the areas with colour are “hot” under the baseline climate. The boundary between them is the 24 degree threshold line.

Address the question under Task 1 above.

Under the baseline climate, the areas not affected by the 24 degree threshold are all areas other than those inland from Whakatane and Opotiki, near Kawerau and through parts of the Uruwera National Forest Park. Urbanised areas of population growth including Tauranga and Rotorua are belwo the 24 degree threshold, as is Whakatane, however Whakatane is close to the threshold.

Leave the image on the screen!

Now create a scenario of climate change. Click on the Spatial Scenario Generator icon again. The following model parameters are preferred by government guidelines:

Year: 2030

GCM: Ensemble

Global Projection: RCP4.5 (a mid-range projection)

Climate Sensitivity: Mid (average value for a range of model sensitivities)

Months: select January and February, then Generate

Again, adjust the image and isolate the 24-degree threshold using the Image Display Option, as above.

Leave the image on the screen and repeat steps above for the year 2050 using the same scenario.

Address the questions under Task 2 above.

Under the 2030 scenario with a medium range projection of climate change, more parts of Tauranga, Whakatane, Te Puke and inland areas are above the 24 degree threshold, and this intensifies even further under the 2050 scenario with a high range projection for climate change

The changes projected with climate change are expected to affect most parts of Tauranga, Te Puke, Whakatane by 2030 and all areas of these population centres by 2050, for increased power demand, given that they are projected to be above the 24 degree threshold.

PART 2:

EXTREME CLIMATIC EVENTS AND THE RISKS OF POWER CRISES

In addition to the long-term demand and supply projections, Mercury Energy is also trying to come to grips with the effects of climatic extremes. Extreme hot days can exceed Dawning Power’s capacity to supply power. ME acknowledge that a dailymaximum temperature equal to, or exceeding, 33 degrees (in any month) is the threshold that triggers the power crisis, but does not know the probability of such an event occurring.

TASKS:

(1) Analyse the risk of power failure under the “current” climate regime:

  • What are the chances in any given year (or the return period) of power failure due to an extreme hot day (i.e. 33.5 degrees or higher)?
  • What would be the probability of such an event occurring at least once over a time horizon of the next 10 years ((risk) assuming no change in climate?

(2) Analyse the risks of power failure under scenarios of climate change for the years 2030 and 2050:

  • What would be the chances (return period) in any given year of power failure by the year 2030? 2050?
  • The government has advised that a return period of 1-in-20 yearsis the “acceptable risk” for power failure given the regional growth policy. With the scenarios of climate change, at what approximate date will this threshold of “acceptable risk” possibly be exceeded?

Steps for carrying out Task 2 using SimCLIM:

On the Main Menu, choose Bay of Plenty Extract(far right-hand side of screen). Clear the screen of any images. From theTools drop-down menu, select the Extreme Value Analysis:

A map will appear (grab the lower border and drag down to get the full view). Of the choices offered therein, choose:

  • Data type: daily
  • Site: Te Puke - 1645 (click on dot on map or use drop-down menu)
  • Date range for simulation: Month (Select All)
  • Climate variable: select the Maximum Temperature (T Max) tab and enter 1for the number of days (note: this means that you will be examining the daily extreme values which occurred within every year on record)
  • Scenario: leave at 1995 (to assess “current” climate)
  • Leave all other settings at default
  • ClickRun.

To access the graphical results and risk calculator, click anywhere on the table of results.

Extreme Event Value: Enter an extreme value (33.5 degrees) and the Return Period will be calculated (note: a return period of, for example, 1-in-20 years means that there is a 1-in-20 chance of your selected extreme value occurring or being exceeded in any given year).

The return period of power failure due to an extreme hot day (i.e. 33.5 degrees or higher) is 130.95 years, under the current climate.

Risk: This tool gives the probability of the event occurring (or being exceeded) at least once over the time horizon specified. Enter a value for the time horizon (e.g. 10 years) and the probability will be calculated.

The probability of a33.5 degree event occurring for Max Temperature, at least once over a time horizon of the next 10 years (risk), assuming no change in climate is: 0.07

Address the questions under Task 1 (Part 2) above.

Leave your graph on the screen

In order to examine these extreme events under climate change (Task 2), return to the Extreme Event Analysis menu and click on Scenario. Choose:

Year: 2030

GCM:GISS-E2-R-CC

Global Projection: RCP8.5 (a high-range projection of future atmospheric greenhouse gas concentrations)

Climate Sensitivity: High

Then, Generate

You are now back to the extreme event menu. Ensure that the parameter settings are the same as the previous run and then click RUN to re-plot the extremes. Click on table to get the graph. Analyse the return period for the 33.5-degree threshold, as above.

Leave the image on the screen and repeat the process for the year 2050.

Address the questions posed under the Task 2 above.

  • In any given year by the year 2030 and 2050, there will be a return period of 1-in-22.70 and 1-in-7.51 years respectively, of an extreme event of 33.5 degrees Maximum Temperature occurring
  • With the scenarios of climate change the threshold of ‘acceptable risk’ will possibly be exceeded by 2120 approximately (in the 2030 scenario) and by 2053 approximately (in the 2050 scenario).

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