CO-MICC – Supporting risk assessment and adaptation at multiple spatial scales: CO-development of Methods to utilize uncertain multi-model-based Information on freshwater-related hazards of Climate Change

CO-MICC is an online knowledge and data portal for freshwater-related climate change risk assessment and adaptation at multiple spatial scales.

Our Mission and Motivation

Climate change (CC) is one of the main drivers influencing freshwater availability across the Earth. The influence of this global phenomenon on continental surface water and groundwater manifests itself in very diverse and complex forms. While some regions experience a general decrease in their freshwater resources over a certain time period, e.g. in the form of retreating glaciers or decreasing lake and groundwater levels, the opposite is observed in other regions. While some regions experience an increasing frequency of drought events, other regions are confronted with a higher frequency of flood events.

With this in mind, CC risk assessments and adaptation plans have been gradually integrated into the policy-making sphere to ensure future freshwater availability for human activities and ecosystems. It is state-of-the-art that multi-model ensembles (MMEs) of future freshwater-related hazards of CC (e.g. derived by driving a number of global hydrological models by the output of a number of climate models) are optimal for informing CC risk management. However, there is a general lack of knowledge on how to best utilize the information provided by MMEs in CC risk management, in particular for the identification of adaptation measures.

Our Goals

The CO-MICC portal was developed with the purpose of providing boundary organizations and stakeholders acting on different spatial scales (global, transboundary region, river basin) with:

  • State-of-the-art MME data on CC freshwater-related hazards in an interactive online portal with a focus on uncertainty representation
  • Methods co-developed together with stakeholders for providing and utilizing these MME data for CC risk and adaptation assessments