Modern meteorology deals not only with the study of the physics and
nonlinear dynamics of the atmosphere, but also with the efficient
statistical analysis of the huge amounts of information resulting from
the numerical simulations performed both in operational and hindcast
(retrospective) modes. Although meteorology was originally concerned
with short-range prediction (1-3 days), this discipline has greatly
evolved and nowadays the forecast horizons expand to seasonal time
scales (predicting climate anomalies months in advance) and climate
change scenarios (decades); in this case, the atmospheric models are
coupled with oceanic ones, with slower dynamics, including also the
effects of the cryosphere, biosphere (mainly land use), etc.
Our
research is focused both in theoretical and applied topics of this
discipline, with special emphasis in those aspects involved in seasonal
forecasting and climate change scenarios. Our interests include the
study of simplified atmospheric models (Lorenz-like models, barotropic
vorticity model, etc.) to analyze theoretical aspects of predictability
and ensemble forecasting in nonlinear spatiotemporal systems, and the
numerical simulation of weather and climate at regional scale, using
regional atmospheric models such as the open-source WRF model (Weather
Research and Forecasting, www.wrf-model.org). We are also involved in
the statistical analysis and postprocessing of the operational
prediction systems, including studies of predictability/skill assessment
and downscaling (local prediction). These activities include the
development of efficient data mining techniques and their implementation
in web portals as applications and services, so they can be used to
provide callibrated/local observations and predictions to different
users from impact sectors (agriculture, hydrology, energy, etc.).
http://www.meteo.unican.es
Group Projects
Group Members
Group Publications
| http://dx.doi.org/10.1175/JCLI-D-16-0366.1 | Reassessing model uncertainty for regional projections of precipitation with an ensemble of statistical downscaling methods | 2017-01-01T00:00:00.0000000Z | Journal of Climate | San-Martín D. | | |
| http://dx.doi.org/10.1002/2016JD025724 | Bias correction and downscaling of future RCM precipitation projections using a MOS-Analog technique | 2017-01-01T00:00:00.0000000Z | Journal of Geophysical Research: Atmospheres | Turco M. | | |
| http://dx.doi.org/10.1175/2016BAMSStateoftheClimate.1 | State of the climate in 2015 | 2016-08-01T00:00:00.0000000Z | Bulletin of the American Meteorological Society | Aaron-Morrison A. | | |