Skip to content

Latest commit

 

History

History
38 lines (24 loc) · 4.78 KB

README.md

File metadata and controls

38 lines (24 loc) · 4.78 KB
Raw

Content

This repository serves as the central point of ongoing research regarding the usefulness of the large-scale atmospheric variability in the Mediterranean for forecasting extreme precipitation in the domain. This short video presents a short summary of the motivation and followed methodology and this one summarizes how the findings can help various sectors, like agriculture and emergency response units.

At the moment, the repository is structured in accordance with relevant publications on the topic. These publications explain in details the methodology and benefits of using large-scale proxies for providing skillful predictions of extreme precipitation at medium-/extended-range forecasts (some days and weeks in advance).

At a later stage, the intention is to restructure the repository as a standalone toolbox that can be used by users interested in the extended-range forecasts of surface extremes.

Relevant Publications

  • Paper1: Mastrantonas, N.; Herrera-Lormendez, P.; Magnusson, L.; Pappenberger, F.; Matschullat, J., 2021, Extreme precipitation events in the Mediterranean: Spatiotemporal characteristics and connection to large-scale atmospheric flow patterns. International Journal of Climatology. 1–19. https://doi.org/10.1002/joc.6985. The repository version used for the analysis is available at v1.0.0
  • Paper2: Mastrantonas, N.; Furnari, L.; Magnusson, L.; Senatore, A.; Mendicino, G.; Pappenberger, F.; Matschullat, J., 2022. What do large-scale patterns teach us about extreme precipitation over the Mediterranean at medium- and extended-range forecasts? Q. J. R. Meteorol. Soc. 875– 890. https://doi.org/10.1002/qj.4236. The repository version used for the analysis is available at 2.0.0 (relevant short talk available here)
  • Paper3: Mastrantonas, N.; Magnusson, L.; Pappenberger, F.; Matschullat, J., 2021. Forecasting extreme precipitation in the central Mediterranean: Changes in predictors' strength with prediction lead time Meteorological Applications n/a. https://doi.org/10.1002/met.2101. The repository version used for the analysis is available at 3.0.0

Contributing

All code is authored by Nikolaos Mastrantonas, researcher at the European Centre for Medium-Range Weather Forecasts (ECMWF), UK and Ph.D. student at Technische Universität Bergakademie Freiberg (TUBAF), Germany. The code was developed during employment at ECMWF, using ECMWF resources. The main scientific collaborators in this work are: Linus Magnusson (ECMWF), Florian Pappenberger (ECMWF), and Jörg Matschullat (TUBAF)

This work is part of the Climate Advanced Forecasting of sub-seasonal Extremes project (CAFE). The project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 813844.

Comments, suggestions, etc. regarding the scripts and/or the paper are more than welcome!

Contact details:


Licence

Copyright 2021 European Centre for Medium-Range Weather Forecasts (ECMWF)

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

In applying this licence, ECMWF does not waive the privileges and immunities granted to it by virtue of its status as an intergovernmental organisation nor does it submit to any jurisdiction.