Ph.D, Department of Earth and Planetary Sciences, Weizmann Institute of Science (2017) , M.Sc, Physics, Weizmann Institute of Science (2013), B.Sc, Physics, Tel Aviv University (2010)
Most of my research during my PhD focused on improving our understanding of the large scale circulation in the atmosphere, focusing on storm tracks. More recently, I am interested in integrating machine learning and causal inference methods into climate science. One such example that I find particularly interesting, is using machine learning to improve convection parametrization schemes. A machine learning convection scheme has the potential to reduce precipitation and temperature uncertainties in a global warming scenario.
The relation between the Pacific jet spatial structure and the storm track: a clustering analysis perspective
Janni Yuval and Yohai Kaspi, Journal of Climate, Submitted.
The Relation Between the Seasonal Changes in Jet Characteristics and the Pacific Midwinter Minimum in Eddy Activity 2018
Janni Yuval, Hilla Afargan and Yohai Kaspi, Geophysical Research Letters - https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2018GL078678
Eddy Response to Changes in Jet Characteristics (2018)
Janni Yuval and Yohai Kaspi, Journal of the Atmospheric Science - https://journals.ametsoc.org/doi/abs/10.1175/JAS-D-17-0139.1
The Effect of Vertical Baroclinicity Concentration on Atmospheric Macroturbulence Scaling Relations (2017)
Janni Yuval and Yohai Kaspi, Journal of the Atmospheric Science - http://journals.ametsoc.org/doi/pdf/10.1175/JAS-D-16-0277.1
Eddy Activity Sensitivity to Changes in the Vertical Structure of Baroclinicity (2016)
Janni Yuval and Yohai Kaspi, Journal of the Atmospheric Science - http://journals.ametsoc.org/doi/abs/10.1175/JAS-D-15-0128.1
Dynamics of Elastic Interactions in Soft and Biological Matter (2013)
Janni Yuval and Samuel Safran,
Physical Review E - http://journals.aps.org/pre/abstract/10.1103/PhysRevE.87.042703