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We are becoming increasingly vulnerable to extreme weather and climate events
Everyone is at risk of being affected by climate risk – be it municipalities, businesses or private individuals.
Not least, it is a matter of being well prepared for climate change, so that it is possible to minimise the risk. Because there is no doubt that the changes in climate will affect us and result in more rain, higher temperatures – overall more episodes of extreme weather that increase the risk of floods, avalanches and landslides.
NORCE develops solutions for predicting and managing climate risk. Feel free to contact us if you would like to work with us.
What do we do?
At NORCE, we conduct groundbreaking climate research and develop completely new solutions for seasonal forecasting. In the Seasonal Forecasting Engine project, we will contribute to strengthening emergency preparedness in the community and securing important infrastructure such as housing, roads and power supply. Our forecasts will provide more secure predictions about the weather up to three months ahead.
If torrential rain is likely for a period, it is important that both municipalities and private companies are prepared. Or if spring comes earlier - and if there is a drought - farmers can be alerted and find solutions that save crops and animals.
In collaboration with other researchers in the Bjerknes Centre, we have a leading national role in the development of and knowledge about the Norwegian Climate Model (NorESM), with expertise in global climate modelling and climate dynamics. This is a very important competence for the work on climate change forecasting and climate risk.
The potential for seasonal forecasting is enormous. Now that the weather forecasting models have improved, we are able to provide better seasonal forecasts than before.
Climate scientist and meteorologist Erik Kolstad at NORCE.
The Seasonal Forecasting Engine is based on five European climate models, including the Bjerknes Centre's own forecasting model NorCPM. Data from satellites, models and observations is input and the "engine" of the project itself is the aforementioned climate models combined with advanced statistical methods. In addition, machine learning is used to train the models to look for systematic errors that can be corrected.
The target group is both the public and private sectors, and we want to contribute to better risk management and planning in Northern Europe and the Arctic.
In Norway, credible forecasts of more than ten days will undoubtedly have a major impact on many industries, including the energy industry, which is dominated by hydropower. More secure predictions of when and how much precipitation falls, how much snow settles in the mountains and on glaciers or when and how powerful the spring floods will be, bring great economic benefits. Seasonal forecasting is also relevant for other sectors such as agriculture, fisheries, transport and tourism. Our goal in climate forecasting is to meet the growing need for advanced, relevant and applied seasonal weather and ocean forecasts.