The Norwegian Climate Prediction Model – NorCPM
NorCPM is Norway’s very own climate prediction model, developed by the Bjerknes Climate Prediciton Unit.
Around the world, you can find several other weather forecasting and climate prediction models. These are basically computer programs that calculate probable weather tendencies based on an initial state. This is done by using advanced equations based on the fundamental laws of physics, fluid motion, and chemistry, that describe our climate. However, this can be done in different ways.
What makes NorCPM special compared to other models?
NorCPM combines the Norwegian Earth System Model with a method for data assimilation called EnKF – The Ensemble Kalman Filter, a method that was originally developed at NERSC, but which now has a broad user base. When a climate model runs, it divides the Earth into a grid and calculates what is happening in each pixel (of size 100 km) from the top of the atmosphere to the bottom of the ocean. The model thus simulates a weather state, but its calculations inevitably deviate from reality. Data assimilation is thus needed to correct the model’s simulations by synchronizing it with the actual observed climate variations. The EnKF used in NorCPM is an advanced data assimilation method that preserves important climate variables, such as ocean heat, salinity and sea ice volume when assimilating ocean and sea ice observations, which are important because they influence the climate over a long time. This gives a starting point for NorCPM to calculate all variables in each pixel in the future. This initialisation goes hand-in-hand with the ocean model of NorESM, which has a unique mathematical structure and is also meant to carry the ocean heat and salt variations forward intact.
The assimilation of the ocean and sea ice observations is well designed to synchronize the weather and climate from seasons to decades (S2D-seasonal-to-decadal), unlike other models that are meant for about 10 days to seasons (S2S-subseasonal-to-seasonal). Thus, NorCPM will reliably calculate the signals from the slow-varying ocean, while S2S models focus their efforts on atmosphere and land, which are changing faster. Using S2S and S2D models together gives a broader, more comprehensive picture of the possible outcomes of recent variations of the ocean, sea ice, land and atmosphere.
Demonstrating societal relevance
- Although we focus on basic research, our results can be of great benefit to society:
- Climate Futures, a centre for research-based innovation developing climate prediction for handling climate risk, provide regular monthly forecasts to Norwegian stakeholders from their 4 innovation areas: Smart shipping, sustainable food production, renewable energy and resilient societies. Climate Futures use several world-reknown European models to develop these forecasts and have now included NorCPM in their portofolio. Indeed, a team from BCPU found that after including NorCPM, the predictions got better starting conditions and became more reliable 1 year ahead. Looking further out, including NorCPM also improved the forecasts on a 2-5 year time scale and even 6-9 years ahead for Europe, North America and in the oceans (particularly the North Atlantic and the Nordic Seas). More about this study here. NorCPM is already an important tool for Climate Futures, and our partnership will elaborate on it to further improve the forecast accuracy by assimilating data in the atmosphere and land components of NorESM.
- Meanwhile, the Institute for Marine Research is exploring the benefits of downscaling on dynamical forecasts for fisheries related application. [upcoming list of relevant publications and blog posts]
- In addition we contribute to the WMO Lead Centre for Annual-to-Decadal Climate Prediction.
- Furthermore, we now provide NorCPM seasonal forecasts, which are updated on a monthly basis: NorCPM seasonal forecast.