Tim Hewson
European Centre for Medium-Range Weather Forecasts
Network
Latest external collaboration on country level. Dive into details by clicking on the dots.
Publication
Featured researches published by Tim Hewson.
Bulletin of the American Meteorological Society | 2013
Urs Neu; M. G. Akperov; Nina Bellenbaum; Rasmu S. Benestad; Richard Blender; Rodrigo Caballero; Angela Cocozza; Helen F. Dacre; Yang Feng; Klaus Fraedrich; Jens Grieger; Sergey K. Gulev; John Hanley; Tim Hewson; Masaru Inatsu; Kevin Keay; Sarah F. Kew; Ina Kindem; Gregor C. Leckebusch; Margarida L. R. Liberato; Piero Lionello; I. I. Mokhov; Joaquim G. Pinto; Christoph C. Raible; Marco Reale; Irina Rudeva; Mareike Schuster; Ian Simmonds; Mark R. Sinclair; Michael Sprenger
The variability of results from different automated methods of detection and tracking of extratropical cyclones is assessed in order to identify uncertainties related to the choice of method. Fifteen international teams applied their own algorithms to the same dataset—the period 1989–2009 of interim European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERAInterim) data. This experiment is part of the community project Intercomparison of Mid Latitude Storm Diagnostics (IMILAST; see www.proclim.ch/imilast/index.html). The spread of results for cyclone frequency, intensity, life cycle, and track location is presented to illustrate the impact of using different methods. Globally, methods agree well for geographical distribution in large oceanic regions, interannual variability of cyclone numbers, geographical patterns of strong trends, and distribution shape for many life cycle characteristics. In contrast, the largest disparities exist for the total numbers of cyclones, the detection of wea...
Bulletin of the American Meteorological Society | 2013
Urs Neu; M. G. Akperov; Nina Bellenbaum; Rasmus Benestad; Richard Blender; Rodrigo Caballero; Angela Cocozza; Helen F. Dacre; Yang Feng; Klaus Fraedrich; Jens Grieger; Sergey K. Gulev; John Hanley; Tim Hewson; Masaru Inatsu; Kevin Keay; Sarah F. Kew; Ina Kindem; Gregor C. Leckebusch; Margarida L. R. Liberato; Piero Lionello; I. I. Mokhov; Joaquim G. Pinto; Christoph C. Raible; Marco Reale; Irina Rudeva; Mareike Schuster; Ian Simmonds; Mark R. Sinclair; Michael Sprenger
The variability of results from different automated methods of detection and tracking of extratropical cyclones is assessed in order to identify uncertainties related to the choice of method. Fifteen international teams applied their own algorithms to the same dataset—the period 1989–2009 of interim European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERAInterim) data. This experiment is part of the community project Intercomparison of Mid Latitude Storm Diagnostics (IMILAST; see www.proclim.ch/imilast/index.html). The spread of results for cyclone frequency, intensity, life cycle, and track location is presented to illustrate the impact of using different methods. Globally, methods agree well for geographical distribution in large oceanic regions, interannual variability of cyclone numbers, geographical patterns of strong trends, and distribution shape for many life cycle characteristics. In contrast, the largest disparities exist for the total numbers of cyclones, the detection of wea...
Bulletin of the American Meteorological Society | 2016
R. Swinbank; Masayuki Kyouda; Piers Buchanan; Lizzie Froude; Thomas M. Hamill; Tim Hewson; Julia H. Keller; Mio Matsueda; John Methven; Florian Pappenberger; Michael Scheuerer; Helen A. Titley; Laurence J. Wilson; Munehiko Yamaguchi
AbstractThe International Grand Global Ensemble (TIGGE) was a major component of The Observing System Research and Predictability Experiment (THORPEX) research program, whose aim is to accelerate improvements in forecasting high-impact weather. By providing ensemble prediction data from leading operational forecast centers, TIGGE has enhanced collaboration between the research and operational meteorological communities and enabled research studies on a wide range of topics.The paper covers the objective evaluation of the TIGGE data. For a range of forecast parameters, it is shown to be beneficial to combine ensembles from several data providers in a multimodel grand ensemble. Alternative methods to correct systematic errors, including the use of reforecast data, are also discussed.TIGGE data have been used for a range of research studies on predictability and dynamical processes. Tropical cyclones are the most destructive weather systems in the world and are a focus of multimodel ensemble research. Their ...
Monthly Weather Review | 2012
Thomas Haiden; M. J. Rodwell; David S. Richardson; Akira Okagaki; Tom Robinson; Tim Hewson
AbstractPrecipitation forecasts from five global numerical weather prediction (NWP) models are verified against rain gauge observations using the new stable equitable error in probability space (SEEPS) score. It is based on a 3 × 3 contingency table and measures the ability of a forecast to discriminate between “dry,” “light precipitation,” and “heavy precipitation.” In SEEPS, the threshold defining the boundary between the light and heavy categories varies systematically with precipitation climate. Results obtained for SEEPS are compared to those of more well-known scores, and are broken down with regard to individual contributions from the contingency table. It is found that differences in skill between the models are consistent for different scores, but are small compared to seasonal and geographical variations, which themselves can be largely ascribed to the varying prevalence of deep convection. Differences between the tropics and extratropics are quite pronounced. SEEPS scores at forecast day 1 in t...
Weather and Forecasting | 2018
Estíbaliz Gascón; Tim Hewson; Thomas Haiden
AbstractThe medium-range ensemble (ENS) from the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS) is used to create two new products intended to face the challenges of winter precipitation-type forecasting. The products themselves are a map product that represents which precipitation type is most likely whenever the probability of precipitation is >50% (also including information on lower probability outcomes) and a meteogram product, showing the temporal evolution of the instantaneous precipitation-type probabilities for a specific location, classified into three categories of precipitation rate. A minimum precipitation rate is also used to distinguish dry from precipitating conditions, setting this value according to type, in order to try to enforce a zero frequency bias for all precipitation types. The new products differ from other ECMWF products in three important respects: first, the input variable is discretized, rather than continuous; second, the post...
Quarterly Journal of the Royal Meteorological Society | 1999
Alain Joly; K. A. Browning; P. Bessemoulin; Jean-Pierre Cammas; Guy Caniaux; Jean-Pierre Chalon; S. A. Clough; Richard Dirks; Kerry A. Emanuel; Laurence Eymard; Robert Gall; Tim Hewson; Peter H. Hildebrand; Dave Jorgensen; François Lalaurette; Rolf H. Langland; Yvon Lemaǐtre; Patrick Mascart; James A. Moore; P. Ola G. Persson; Frank Roux; M. A. Shapiro; Chris Snyder; Zoltan Toth; Roger M. Wakimoto
Meteorological Applications | 2010
Tim Hewson; Helen A. Titley
Quarterly Journal of the Royal Meteorological Society | 2010
M. J. Rodwell; David S. Richardson; Tim Hewson; Thomas Haiden
Tellus A | 2015
Tim Hewson; Urs Neu
Bulletin of the American Meteorological Society | 2013
Urs Neu; M. G. Akperov; R. Benestad; Richard Blender; Rodrigo Caballero; Angela Cocozza; Helen F. Dacre; Yang Feng; Jens Grieger; Sergey K. Gulev; John Hanley; Tim Hewson; K. Hodges; Masaru Inatsu; Kevin Keay; Sarah F. Kew; Ina Kindem; Gregor C. Leckebusch; Margarida L. R. Liberato; Piero Lionello; I. I. Mokhov; Joaquim G. Pinto; Christoph C. Raible; Marco Reale; Irina Rudeva; Mareike Schuster; Ian Simmonds; Mark R. Sinclair; Michael Sprenger; Natalia Tilinina