nedjeljka žagar
  • Contact: Jadranska 19, office 115

Nedjeljka Žagar

professor of meteorology

Research fields Nedjeljka's group has been applying the modal decomposition to atmospheric general circulation models, global data assimilation systems and ensemble forecasting systems.
A real-time representation of atmospheric energy spectra and unbalanced circulation is available on dedicated MODES pages.


Recent publications

N. Žagar, D. Jelic, M. Blaauw and P. Bechtold, 2017:
Energy spectra and inertia-gravity waves in global analyses,
J. Atmos. Sci., 74 (8), 2447-2466.

N. Žagar, M. Horvat, Ž. Zaplotnik and L. Magnusson, 2017:
Scale-dependent estimates of the growth of forecast uncertainties in a global prediction system,
Tellus A, 69, 1287492. Martin's Python tool for fitting the error data

N. Žagar, 2017:
A global perspective of the limits of prediction skill of NWP models,
Tellus A, 69, 1317573.

N. Žagar, J. Bojarova, N. Gustafsson, T. Janjic, G-J. Marseille, M. Rennie, A. Stoffelen and M. Savli, 2017:
Summary of Ljubljana workshop on “Mesoscale data assimilation and the role of winds in limited-area models for NWP in Europe”,
ALADIN-HIRLAM Newsletter, 8, 119-123. Also http://www.umr-cnrm.fr/aladin/meshtml/NL8-final.pdf

Recently submitted

Zaplotnik, Ž., N. Žagar and N. Gustafsson: An intermediate-complexity model for the four-dimensional variational data assimilation including moist processes. To QJRMS

Šavli, M., N. Žagar and J.L. Anderson: Assimilation of the horizontal line-of-sight winds with a mesoscale EnKF data assimilation system. To QJRMS

Blaauw, M. and N. Žagar: Multivariate analysis of Kelvin wave seasonal variability in ECMWF L91 analyses. To ACP

Žagar, N., K. Kosovelj and E. Manzini: Estimating scale-dependent temporal variability and bias in global models. To Clim. Dyn.