Metodija (Meto) Shapkalijevski
Ph.D., Researcher.
Fields of work
Theoretical and computational meteorology; development of numerical weather prediction systems with focus on atmospheric boundary-layer processes and surface-atmosphere continuum.
Research interests
- Atmospheric boundary-layer turbulence, clouds, and chemistry
- Surface-vegetation-atmosphere exchange processes (momentum, energy, reactive chemical compounds)
- Transport interaction in multiscale atmospheric processes (from meso to micro)
Special competences
- Using a set of models: conceptual models, large-eddy simulations, numerical weather prediction systems
- Retrieval and analysis of meteorological data from point and remote sensing instruments
- Using and developing data-driven stochastic parameterizations
Latest publications
Numerical Weather Prediction Model Coupling-Strategies, Challenges, and Outlook
Josh Kousal, Charles Pelletier, Jasper M. C. Denissen, Luise Schulte, Sarah Keeley, Peter Dueben, Stephen G. Penny, Rae-Seol Park, Diego G. Miralles, Metodija Shapkalijevski, Arianna Valmassoi, Ian Renfrew, Lorenzo Zampieri, Rajesh Kumar, Melissa Ruiz-Vasquez, Jan-Peter Schulz, Lichuan Wu, Xabier Pedruzo Bagazgoitia
In: Bulletin of The American Meteorological Society - (BAMS), Vol. 107, No. 1
2026
Increasing complexity in Aerodynamic Gradient flux calculations inside the roughness sublayer applied on a two-year dataset
E. A. Melman, S. Rutledge-Jonker, M. Braam, K. F. A. Frumau, A. F. Moene, Metodija Shapkalijevski, J. Vila-Guerau de Arellano, M. C. van Zanten
Perspectives toward Stochastic and Learned-by-Data Turbulence in Numerical Weather Prediction
Metodija Shapkalijevski