Method


The beginning of this method is the same as any other scenario generation procedure.


Choose a study area.


As with future scenario generation you will need to specify a date and the GCM pattern and RCP and climate sensitivity.



As this is a scenario based on change from baseline you cannot use 1995 (the baseline year) in your analysis.


Click on Future and choose and future data for analysis.


The next choice is for the GCMs to apply. We suggest a complete ensemble but you may have specific reasons for choosing one or more GCMs for your particular analysis.


By clicking on the yellow star to the right of the selection boxes you can save the ensemble of choice for future use:



You can add a favourite or manage the ensembles you had saved previously.


By clicking Add favourite a dialogue box will appear where you can name the ensemble and it will display the GCM/RCMs you have previously selected to form your ensemble. Click OK to save.



By clicking on Manage you will open a dialogue box displaying previously saved ensembles and you can open them for application or delete them if they are no longer required:



Back to making an ensemble for your analysis . . .



When you click on more than two or more GCMS the following dialogue box appears:



This functionality represents the option of choosing the percentile of a certain result from the ensemble chosen and can be used to reflect the level of risk that you may wish to test for.


You can leave this dialogue box blank and the resulting scenario will portray the ensemble mean.


Or you can chose , for example, the 5th (low) and 95th (high) scenario. This will result in the generation of three maps. One will still be the ensemble mean. percentile (or a centile) is a measure used in statistics indicating the value below which a given percentage of observations in a group of observations fall. There is a point known as the 5th percentile, because 5% of the GCM values (or 1 value in 20) is less than all values (best case in terms of change from baseline assuming that a change from baseline is not desirable)). The same high point is known as the 95th percentile, where only 1 value in 20 is higher than all values (worse case from baseline assuming that a change from baseline is not desirable).


Chose the months/season for analysis and climate sensitivity as seen below.


Sensitivity (from SimCLIM FAQ document) : In 2007, the IPCC considered the projections from models, paleo-climate information, and expert judgement and stated that the best estimate of how much the average temperature of the Earth’s atmosphere would increase with a CO2 doubling is 3°C (about 5.4°F). Because climate models yield different results and historical and paleo-climate analyses yield different estimates of temperature associated with CO2 doubling, scientists have defined a range of climate sensitivities


The IPCC said that there is a two-thirds chance that the true sensitivity is between 2°C (3.6°F) and 4.x°C (8.1°F). If there is a two-thirds chance that climate sensitivity is between 2°C and 4.x°C, then there is a one-third chance it is outside this range. The IPCC concluded that there is only approximately a one in 20 chance that climate sensitivity is below 1.5°C (2.7°F). Wigley et al. (2009) found that there is only a one in 20 chance that climate sensitivity is greater than 6°C (10.8°F). Thus, scientists have concluded that there is a nine in 10 chance that the true sensitivity is between 1.5°C and 6.0°C. This range represents a factor of 4. Therefore the medium sensitivity is centered on 3 C and low on 2 C and high on 4.5 C.



After making your selections click on Generate.


Three images will be displayed.



Activity: changes from baseline using tools


The usual tools are available for working with such images.


By scrolling over the figure the result for that site is displayed with the latitude and longitude on the top left of the screen.


You can use the image display function on your images.


Generate a series of ‘change from baseline’ images and creatively (think about what you wish to display to your audience) apply the image display function on them.



The image that follows was reclassified for all the values that represented a decrease in rainfall from baseline of between 30 and 10 percent by 2100. It was also reclassified to only five categories.



NOTE: YOU DO NOT NEED TO ACCEPT THE DEFAULT NUMERIC VALUES WHEN RECLASSIFYING. YOU CAN CHOOSE YOUR OWN. TRY IT!