I know that there are many scenarios released by IPCC for climate change prediction, but I am not sure whether they are sensitive to climate type (i.e. arid, semi-arid, humid) of the study region or no? Particularly, when we use down scaling tools to increase the spatial resolution.
Climate scenarios derived from models are informed by emission scenarios and also contain expressions of global and regional climate, which can be shared by a wide range of models or are specific to a single model only. For example, most regions of Mediterranean climate become drier in the winter-spring season.
The main physical differences in climate scenarios are due to the selection of climate model, rather than the emission scenario. Because of the common technique of differencing the mean climate signal from the noise of variability, usually higher emission scenarios are recommended and the results scaled back for lower emissions. The signal of regional mean change is generally similar across emission scenarios.
The best approach is to sample across the range of plausible changes provided by a suite of models (e.g., CMIP5) and assess the uncertainty response of the system. Select the type of climate scenario needed according to the decisions that need to be made on the ground. Tailioring scenarios to decision making is far more important than selection of emission scenario. Make the technique used no more complex that it needs to be. Much effort is often made on downscaling, where it might be much better spent on supporting adaptation directly.
Useful technical guidelines can be found in the IPCC Data Distribution Centre
http://www.ipcc-data.org/guidelines/index.html
Hi Ali,
Emission Scenarios used by the IPCC and found in the CMIP archives are not to be used as prediction tools. The emission scenarios (and the RCPs) should be used for climate projections. There is a big difference between the outputs from NWP models and GCMs. The scenarios and the RCPs are not even probabilistic, and represent possible future conditions under certain assumptions of economic growth, greenhouse gases and socioeconomic development. Moreover, when using downscaling tools, as the emission scenario to be analyzed is run globally by the GCM (that provide the predictors of the downscaling model) it is not sensitive to the study region; in contrast the climate region of interest may respond differently to the atmospheric patterns obtained under different emission scenarios.
As already stated, arid/semi-arid regions are affected by climate change scenarios. Selection of a strong emission scenario in comparison to a control run gives you the range within which you can expect the CC signal. Furthermore, selection of 3 or more ensemble members for that particular scenario gives you the range of uncertainty due to internal climate variability.
However, it depends on the region. If you want to investigate a monsoon region, you cannot expect to get the correct answer from GCMs if they don't simulate the monsoon dynamics correctly, etc.
Greetings, Andreas Will
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