This function can be performed on any data in the browser but we have only used it for temperature so far. The example below is for temperature.


Graphing the long term normalised temperature in the baseline against projections for future years is a good way to visualise how the average temperature will change over time.

Figure 12  shows how not only the hottest month is getting hotter, but also how the current average maximum extends to months earlier and later in the year.

            1. Example projected normalised monthly mean temperature

This graph is created by creating a different set of normalised monthly mean data. The baseline and one for every future year of interest.

Create the baseline using the following steps below (instructions on how to use each function are explained in the sub sections earlier in this chapter).

1) Open the data browser and select your BoM site of interest

2) Limit the baseline period

3) Click aggregate data and select “monthly” and “on average/total”. Do not select “no aggregation if a block contains missing data”, Click OK.

1)Click “calculate long term normal”

There should be 12 values corresponding to the 12 months 1 = Jan, 2 = Feb and so on.

2) Copy to clipboard (right click on heading rows of table) and paste in excel – label with location and timestep (in this case, baseline). It is useful to create an extra column and label the months as Jan, Feb etc.

Generate your projected timeseries using the following steps

3) Load data again and DON’T FORGET TO RESET THE VIEWING PERIOD TO that of the original baseline

4) Click scenario (you will see the pop-up window in Figure 13)

            1. Site browser climate scenario popup

1) Select future year

2) Select GCM or ensemble (if using an ensemble you will be returned the ensemble median (50th percentile) as an output. Select and define upper and lower percentiles e.g. 10th and 90th if a range of the result is also required. ****if you haven’t defined any ensembles you will have to do this – see SimCLIM essentials manual vol.1

3) Select emissions scenario (GHG concentration pathway)

4) Click OK  – the dataset with perturb i.e. generate a time-series for the future year selected.

5) Reset your viewing period to be the same as the baseline and repeat steps 3 to 5.

6) Repeat steps 6 to 12 for each future year

7) Rearrange the data in the excel sheet first so the first month is July, this will make the graph smooth with the summer hump in the middle

You should end up with a table in the same format as shown in Figure 3

            1. longterm average monthly temperature data in excel

1) Plot these data in excel using scatter plot – smooth line chart

a) X axis is month

b) Y axis is temperature

2) Format the chart as required and add additional graphics in PowerPoint.