Access the toolkit (BETA)
The beta version of the impact indicator toolkit can be accessed via the link below and will open full screen.
By means of the toolkit, the user can access climate changeclimate change
Climate change refers to a change in the state of the climate that can be identified (e.g., by using statistical tests) by changes in the mean and/or the variability of its properties, and that persists for an extended period, typically decades or longer. Climate change may be due to natural internal processes or external forcings such as modulations of the solar cycles, volcanic eruptions and persistent anthropogenic changes in the composition of the atmosphere or in land use. Note that the United Nations Framework Convention on Climate Change (UNFCCC), in its Article 1, defines climate change as: 'a change of climate which is attributed directly or indirectly to human activity that alters the composition of the global atmosphere and which is in addition to natural climate variability observed over comparable time periods'. The UNFCCC thus makes a distinction between climate change attributable to human activities altering the atmospheric composition, and climate variability attributa (impact) indicators calculated for different climate change and socio-economic scenarios. Furthermore, the toolkit presents tools allowing the user to explore available data and to switch between different indicators and different climate change and socio-economic scenarios.
Available impact indicators can be selected through the overarching themes CLIPC focusses on; urban, water and rural, available at the top of the toolkit. The left side of the toolkit allows the user to zoom in and out, select layers, add additional layers, open a help function, go back to the homepage, download and save the selection and share the selection.
Please access the indicator toolkit, keeping in mind it is a first version and new climate impactclimate impact
See Impact Assessment indicators, more metadatametadata
Information about meteorological and climatological data concerning how and when they were measured, their quality, known problems and other characteristics., uncertaintyuncertainty
Lack of precision or unpredictability of the exact value at a given moment in time. It does not usually imply lack of knowledge. Often, the future state of a process may not be predictable, such as a roll with dice, but the probability of finding it in a certain state may be well known (the probability of rolling a six is 1/6, and flipping tails with a coin is 1/2). In climate science, the dice may be loaded, and we may refer to uncertainties even with perfect knowledge of the odds. Uncertainties can be modelled statistically in terms of pdfs, extreme value theory and stochastic time series models. information and toolkit functions will be released in next months. If you have feedback, do not hesitate to contact us.