Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Lionel Moret"'
Autor:
Daniele Nerini, Francesco Zanetta, Mathieu Schaer, Jonas Bhend, Christoph Spirig, Lionel Moret, Mark A. Liniger
Forecasting winds at the local scale can be challenging due to the highly variable and complex nature of wind patterns, particularly in the case of complex terrain. In such cases, the accuracy of numerical weather prediction models (NWPs) is often li
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6241da2dd8da940e92f3019b02d81f47
https://doi.org/10.5194/egusphere-egu23-14973
https://doi.org/10.5194/egusphere-egu23-14973
Automated forecasting provides the basis for everyday forecast products used by a wide range of users. Continued progress in numerical weather prediction allows to produce local forecasts with considerable accuracy. To further reduce systematic error
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7240cbf56a55ebab7750d027fd7c69bb
https://doi.org/10.5194/ems2022-330
https://doi.org/10.5194/ems2022-330
Autor:
Omar Bellprat, Christoph Spirig, Moritz Flubacher, Jacques Grandjean, Yves-Alain Roulet, Lionel Moret, Mathias Bavay, Joel Fiddes, Boris Orlowsky, Shinan Kassam, Hafiz Kalandarov, Safarali Yatimov, Akramkhanov Akmal, Stefan Martin Strohmeier, Ram Sharma, Mira Haddad, Ajit Govind, Kaya Fatih, Dominique Berod
Severe weather and climate change take a high toll on the most vulnerable population of Tajikistan. Every year, droughts, flooding or avalanches and non-optimal management practices cause food insecurity and affect the lives of exposed rural communit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d4c58d983ecd0d0d3b33ad079e7234cb
https://doi.org/10.5194/ems2022-476
https://doi.org/10.5194/ems2022-476
Objective forecast verification provides the basis to motivate changes to the forecast system. At MeteoSwiss, we are introducing statistical ensemble postprocessing into our automated forecast production. These automated forecasts are accessed by the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::850e07b5b4b8701bb0dbeef09422b34d
https://doi.org/10.5194/ems2022-332
https://doi.org/10.5194/ems2022-332
Autor:
Stephan Hemri, Jonas Bhend, Christoph Spirig, Daniele Nerini, Lionel Moret, Reinhard Furrer, Mark A. Liniger
Probabilistic predictions of precipitation call for rather sophisticated postprocessing approaches due to its low predictability, high spatio-temporal variability and highly positive skewness. Moreover, the large number of zeros makes the generation
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3752d7a317c28d7707b188224ccddd4c
https://doi.org/10.5194/ems2022-427
https://doi.org/10.5194/ems2022-427
Lessons learnt from implementing a postprocessing suite for probabilistic seamless weather forecasts
Autor:
Christoph Spirig, Jonas Bhend, Stephan Hemri, Jan Rajczak, Daniele Nerini, Lionel Moret, Mark A. Liniger
MeteoSwiss is currently implementing a new NWP postprocessing suite for providing automated local weather forecasts to the general public. As these forecasts are nowadays mainly accessed via smartphone app, we aimed at global postprocessing approache
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::98a87ba44548c54a2aa0d86617750df1
https://doi.org/10.5194/ems2022-377
https://doi.org/10.5194/ems2022-377
Hourly wind forecasts from numerical weather prediction models suffer from a range of systematic and random errors that are to a great extent related to limitations in the model grid resolution. To correct for such biases, statistical postprocessing
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4010f09318eef29846544f7e7e69379b
https://doi.org/10.5194/ems2021-277
https://doi.org/10.5194/ems2021-277
Autor:
Jonas Bhend, Jean-Christophe Orain, Christoph Spirig, Vera Schönenberger, Lionel Moret, Mark A. Liniger
Verification is a core activity in weather forecasting. Insights from verification are used for monitoring, for reporting, to support and motivate development of the forecasting system, and to allow users to maximize forecast value. Due to the broad
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b223108390689544631411848d4b95e9
https://doi.org/10.5194/ems2021-246
https://doi.org/10.5194/ems2021-246
Machine Learning has a big potential for various tasks along the whole value chain of a national Met-Service. Indeed, many research groups, private and national weather services have started to explore the possibilities and first real-time operationa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d5ee6d109df8bdfa61657f8baad30165
https://doi.org/10.5194/ems2021-181
https://doi.org/10.5194/ems2021-181
Over the last decade statistical postprocessing has become a standard tool to reduce biases and dispersion errors of probabilistic numerical weather prediction (NWP) ensemble forecasts. Most established postprocessing approaches train a statistical m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::61a17817875e1428759d4116dc5574c8
https://doi.org/10.5194/ems2021-129
https://doi.org/10.5194/ems2021-129