Yiguo Wang

Yiguo Wang

To improve climate predictions by optimising the model’s use of observations, through data assimilation.

What are you most excited about with this project?
This project enhances the collaborations between UiB, NERSC, NORCE and IMR through climate prediction research activities and is valuable for national and international climate prediction communities.

What do you see as your biggest challenge for now?
My main challenge is how to define a new non-isotropic, multivariate and spatially varying localisation method. In data assimilation, localisation is used to limit the influence of observations within a given radius of influence. It is common to weight the observations with a smooth distance-dependent (typically quasi-Gaussian) localisation function. A new localisation method will be more consistent with climate state, which will lead to more accurate climate state estimations.

Related projects and committees
BCCR Centre for Climate Dynamics funded strategic project: AOIP: Atmosphere-Ocean-Ice interactions in Polar and subpolar regions
NFR funded research project SFE: Seasonal Forecasting Engine
Nordforsk funded Nordic Centre of Excellence ARCPATH
EU H2020 funded research project INTAROS Integrated Arctic observation system
EU H2020 funded research project Blue-Action Arctic Impact on Weather and Climate
NFR funded Young Research Talent project: CoRea. (Coordinator)