I am working on evaluation of climate change impacts on two adjacent humid subtropical watersheds . The catchment area of the watersheds are 270 km2 and 153.5 km2. Is it possible to evaluate climate change impacts for the said areas. Which type of climate change models may be used for this study, if anyone know RCPs scenarios and CMIP5 global climate models please share with me
Hello,
A study using a statistical downscaling model (SDM) requires many different steps.
There is no magic recipe. It is a long process that need to be performed very carefully if one wants to get something out of it. Please look at the reference below (from one of our PhD student) for a recent publication illustrating some of required steps (in particular the question of transferability). Assessing uncertainties is also key to this kind of study: uncertainty linked to the climate models you are using is one of them but there are other uncertainties as well (the choice of the predictors in your SDM, the transfer function itself, the training dataset and the used observations and/or reanalyses, etc ...)
https://www.researchgate.net/publication/270598238_Transferability_in_the_future_climate_of_a_statistical_downscaling_method_for_precipitation_in_France
Article Transferability in the future climate of a statistical downs...
Dear Muhammad,
In our article "Climate projections for ecologists" we have a section that describes the 3 more commonly used techniques to down-scale a Global Climate Model (GCM). Table 2 (Advantages and Disadvantages of Different Techniques for Rationalizing Global Climate Model Output) in our article briefly describes these techniques, and statistical down-scaling is one of them.
A key question you may ask when choosing down-scaling techniques is if you need to gain pixel resolution (so the map will 'look' better and match other spatial data you already have), or if in addition of adding the pixels resolution you need climate information (a better climatic presentation at a smaller scale). To give you a quick example, you may have an output from a GCM at 100km pixel, and you may use stats to get a 100m pixel, but you won't be adding any climatic information to it. Then, if you needed detailed climatic information the statistical downscaling may not be appropriate method, if you had access to a dynamically down-scaled model, then,that would be the best choice.
The paper I mentioned earlier also present a table with links to all public repositories: Table 3. Overview of Climate Projections Available for Use in Ecological Studies, Based on Different Regionalizing Techniques. You may find this information useful perhaps.
Regards,
Luciana
Hi Muhammad,
In addition to the previous, very useful, answers, you should consider the spatial resolution of the hydrological model used for the climate impact assessment. When you use a lumped model for the two catchments for discharge simulation, your main aim is to represent the climatic characteristics relevant for the impact assessment (e.g. single/ multiple day extreme rainfall amounts) at the catchment scale. Then, statistically downscaling these variables directly to the catchment scale using carefully selected predictors and training and validation periods would be an appropriate option. Good luck.
@ Martijn J. Booij ·Many thanks for guidance Kindly guide me can we use Climate change models to study a catchment area of 250 km2?
In general, you cannot use output of GCMs (spatial scale of 100-200 km) directly as input to an hydrological model for a catchment (here spatial scale of 15-20 km). When output of Regional Climate Models (RCMs) is not available, I would suggest to use a statistical downscaling method relating coarse scale GCM information (predictors) to catchment scale meteorological information as input for a hydrological model (predictands).
My Dear Muhammad Shahid; Here are few references may be useful to you. Thanks
http://link.springer.com/article/10.1023/B:CLIM.0000013685.99609.9e
http://ppg.sagepub.com/content/21/4/530.short
http://journals.ametsoc.org/doi/abs/10.1175/1520-0442(1993)006%3C1161:DOGCCE%3E2.0.CO;2
Dear Muhammad Shahid
I agree with the others. You know, if you want to use outputs of GCMs, you should downscale them. If you use statistical downscaling you can use different methods or different models such as LARS-WG , ASD or SDSM and many toolbox or R packages that these are available on the web. This way is ok but not very exact and precise, therefore you should use the dynamical methods and models such as WRF or different version of RegCM. This way is very time consuming but it is very precise. You can download many toolkit or helps file from the internet. There are many many guidance and helps on it.
Regards,
Nasrin Salehnia
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