Postprocessing of Medium Range Hydrological Ensemble Forecasts Making Use of Reforecasts

Autor: Joris Van den Bergh, Emmanuel Roulin

Publikováno v: Hydrology, Vol 3, Iss 2, p 21 (2016)

A hydrological ensemble prediction system is running operationally at the Royal Meteorological Institute of Belgium (RMI) for ten catchments in the Meuse basin. It makes use of the conceptual semi-distributed hydrological model SCHEME and the Europea

Externí odkaz: https://doaj.org/article/eb6b0bdc449a4a8d82ef69115662d696

Assimilation of backscatter observations in a hydrological model: a case study in Belgium using ASCAT data

Autor: Pierre Baguis, Alberto Carrassi, Emmanuel Roulin, Stéphane Vannitsem, Joris Van den Bergh, Sara Modanesi, Hans Lievens

We investigate the possibilities to improve hydrological simulations by assimilating active radar backscatter observations from the Advanced Scatterometer (ASCAT) in the hydrological model SCHEME. This effort is motivated by the great need of accurat

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::66e5914fb01b7c57255ad591a653b61f
https://doi.org/10.5194/egusphere-egu22-3514

Leveraging Artificial Intelligence and Fleet Sensor Data towards a Higher Resolution Road Weather Model

Autor: Toon Bogaerts, Sylvain Watelet, Niko De Bruyne, Chris Thoen, Tom Coopman, Joris Van den Bergh, Maarten Reyniers, Dirck Seynaeve, Wim Casteels, Steven Latré, Peter Hellinckx

Publikováno v: Sensors; Volume 22; Issue 7; Pages: 2732
Sensors

Road weather conditions such as ice, snow, or heavy rain can have a significant impact on driver safety. In this paper, we present an approach to continuously monitor the road conditions in real time by equipping a fleet of vehicles with sensors. Bas

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d9787546f64f46cc32f0ae3dc0fce938
https://pubmed.ncbi.nlm.nih.gov/35408346

Statistical postprocessing for weather forecasts review, challenges, and avenues in a big data world

Autor: Jonas Bhend, Stephan Hemri, Zied Ben Bouallègue, Nigel Roberts, Leila Hieta, Bert Van Schaeybroeck, Kirien Whan, Lesley De Cruz, John Bjørnar Bremnes, Jussi Ylhaisi, Aitor Atencia, Jonathan Demaeyer, Markus Dabernig, Jonathan Flowerdew, Lionel Moret, Maurice Schmeits, Iris Odak Plenković, Olivier Mestre, Sebastian Lerch, Joris Van den Bergh, Gavin R. Evans, Maxime Taillardat, Stéphane Vannitsem, Susanne Theis

Publikováno v: Bulletin of the American Meteorological Society
Bulletin of the American Meteorological Society, 2021, 102 (3), pp.E681-E699. ⟨10.1175/BAMS-D-19-0308.1⟩
BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY

Statistical postprocessing techniques are nowadays key components of the forecasting suites in many National Meteorological Services (NMS), with for most of them, the objective of correcting the impact of different types of errors on the forecasts. T

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::22e4387cbadc3565ff2d166301c77478
https://doi.org/10.1175/bams-d-19-0308.1

Towards detection of road weather conditions using large-scale vehicle fleets

Autor: Sylvain Watelet, Wim Casteels, Joris Van den Bergh, Maarten Reyniers, Peter Hellinckx, Siegfried Mercelis, Toon Bogaerts

Publikováno v: 2020 IEEE 91st Vehicular Technology Conference (VTC2020-Spring), 25-28 May, 2020, Antwerp, Belgium
VTC Spring

Bad weather conditions such as heavy rain, black ice and fog can have a significant impact on road safety. Currently vehicle safety technologies such as the electronic stability program work reactive to hazardous situations. In this paper, we propose

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::11be5543773e5a66bbe64a4bf3fbb663
https://hdl.handle.net/10067/1704110151162165141