scholarly journals How well do we forecast the aurora?

2019 ◽  
Vol 60 (5) ◽  
pp. 5.22-5.25
Author(s):  
Michaela K Mooney ◽  
Colin Forsyth ◽  
Mike Marsh ◽  
Michael Sharpe ◽  
Teresa Hughes ◽  
...  
Keyword(s):  
Space Weather ◽  
Weather Forecast ◽  
Forecast Model ◽  
Weather Forecasts ◽  
Weather Forecast Model

Abstract Michaela K Mooney and co-authors evaluate a space weather forecast model in the same way that weather forecasts are assessed, work that won the 2019 Rishbeth Prize for best poster.

scholarly journals OpenIFS@home version 1: a citizen science project for ensemble weather and climate forecasting

2020 ◽  
Author(s):  
Sarah Sparrow ◽  
Andrew Bowery ◽  
Glenn D. Carver ◽  
Marcus O. Köhler ◽  
Pirkka Ollinaho ◽  
...  
Keyword(s):  
Citizen Science ◽  
General Circulation ◽  
Weather Forecast ◽  
Forecast Model ◽  
General Circulation Models ◽  
Operational Environment ◽  
Computing Systems ◽  
Weather Forecasts ◽  
Operational Forecasts ◽  
Weather Forecast Model

Abstract. Weather forecasts rely heavily on general circulation models of the atmosphere and other components of the Earth system. National meteorological and hydrological services and intergovernmental organisations, such as the European Centre for Medium-Range Weather Forecasts (ECMWF), provide routine operational forecasts on a range of spatio-temporal scales, by running these models in high resolution on state-of-the-art high-performance computing systems. Such operational forecasts are very demanding in terms of computing resources. To facilitate the use of a weather forecast model for research and training purposes outside the operational environment, ECMWF provides a portable version of its numerical weather forecast model, OpenIFS, for use by universities and other research institutes on their own computing systems. In this paper, we describe a new project (OpenIFS@home) that combines OpenIFS with a citizen science approach to involve the general public in helping conduct scientific experiments. Volunteers from across the world can run OpenIFS@home on their computers at home and the results of these simulations can be combined into large forecast ensembles. The infrastructure of such distributed computing experiments is based on our experience and expertise with the climateprediction.net and weather@home systems. In order to validate this first use of OpenIFS in a volunteer computing framework, we present results from ensembles of forecast simulations of tropical cyclone Karl from September 2016, studied during the NAWDEX field campaign. This cyclone underwent extratropical transition and intensified in mid-latitudes to give rise to an intense jet-streak near Scotland and heavy rainfall over Norway. For the validation we use a two thousand member ensemble of OpenIFS run on the OpenIFS@home volunteer framework and a smaller ensemble of the size of operational forecasts using ECMWF’s forecast model in 2016 run on the ECMWF supercomputer with the same horizontal resolution as OpenIFS@home. We present ensemble statistics that illustrate the reliability and accuracy of the OpenIFS@home forecasts as well as discussing the use of large ensembles in the context of forecasting extreme events.

scholarly journals OpenIFS@home version 1: a citizen science project for ensemble weather and climate forecasting

2021 ◽  
Vol 14 (6) ◽  
pp. 3473-3486
Author(s):  
Sarah Sparrow ◽  
Andrew Bowery ◽  
Glenn D. Carver ◽  
Marcus O. Köhler ◽  
Pirkka Ollinaho ◽  
...  
Keyword(s):  
Citizen Science ◽  
General Circulation ◽  
Weather Forecast ◽  
Forecast Model ◽  
General Circulation Models ◽  
Operational Environment ◽  
Computing Systems ◽  
Weather Forecasts ◽  
Operational Forecasts ◽  
Weather Forecast Model

Abstract. Weather forecasts rely heavily on general circulation models of the atmosphere and other components of the Earth system. National meteorological and hydrological services and intergovernmental organizations, such as the European Centre for Medium-Range Weather Forecasts (ECMWF), provide routine operational forecasts on a range of spatio-temporal scales by running these models at high resolution on state-of-the-art high-performance computing systems. Such operational forecasts are very demanding in terms of computing resources. To facilitate the use of a weather forecast model for research and training purposes outside the operational environment, ECMWF provides a portable version of its numerical weather forecast model, OpenIFS, for use by universities and other research institutes on their own computing systems. In this paper, we describe a new project (OpenIFS@home) that combines OpenIFS with a citizen science approach to involve the general public in helping conduct scientific experiments. Volunteers from across the world can run OpenIFS@home on their computers at home, and the results of these simulations can be combined into large forecast ensembles. The infrastructure of such distributed computing experiments is based on our experience and expertise with the climateprediction.net (https://www.climateprediction.net/, last access: 1 June 2021) and weather@home systems. In order to validate this first use of OpenIFS in a volunteer computing framework, we present results from ensembles of forecast simulations of Tropical Cyclone Karl from September 2016 studied during the NAWDEX field campaign. This cyclone underwent extratropical transition and intensified in mid-latitudes to give rise to an intense jet streak near Scotland and heavy rainfall over Norway. For the validation we use a 2000-member ensemble of OpenIFS run on the OpenIFS@home volunteer framework and a smaller ensemble of the size of operational forecasts using ECMWF's forecast model in 2016 run on the ECMWF supercomputer with the same horizontal resolution as OpenIFS@home. We present ensemble statistics that illustrate the reliability and accuracy of the OpenIFS@home forecasts and discuss the use of large ensembles in the context of forecasting extreme events.

scholarly journals Sensitivity of a long-range numerical weather forecast model to small changes of model parameters

2011 ◽  
Vol 6 (1) ◽  
pp. 13-18 ◽  
Author(s):  
M. B. Gavrilov ◽  
G. R. Jovanović ◽  
Z. Janjić
Keyword(s):  
Initial Conditions ◽  
Weather Forecast ◽  
Forecast Model ◽  
Model Parameters ◽  
Weather Forecasts ◽  
Numerical Weather ◽  
First Case ◽  
Weather Forecast Model ◽  
Model Setup ◽  
Numerical Weather Forecast

Abstract. Sensitivity of extended-range numerical weather forecasts to small changes of model parameters is studied for two cases. In the first case the Earth radius was perturbed. In the other case changes of the gravity were introduced. The results for the 500 hPa geopotential fields are presented on hemispheric maps and intercompared visually and using RMS differences of the perturbed and reference forecasts. During about the first 10 days of integration the results indicate modest sensitivity of the forecasts to the parameter variation. After this period the forecasts diverge rapidly and start to differ significantly. Repeated integrations on the same computer using the same model setup and the same initial conditions yield identical results.

DeepPE: Emulating Parameterization in Numerical Weather Forecast Model Through Bidirectional Network

2021 ◽  
pp. 87-101
Author(s):  
Fengyang Xu ◽  
Wencheng Shi ◽  
Yunfei Du ◽  
Zhiguang Chen ◽  
Yutong Lu
Keyword(s):  
Weather Forecast ◽  
Forecast Model ◽  
Numerical Weather ◽  
Weather Forecast Model ◽  
Numerical Weather Forecast

scholarly journals Operational Implementation of the ISBA Land Surface Scheme in the Canadian Regional Weather Forecast Model. Part II: Cold Season Results

2003 ◽  
Vol 4 (2) ◽  
pp. 371-386 ◽  
Author(s):  
Stéphane Bélair ◽  
Ross Brown ◽  
Jocelyn Mailhot ◽  
Bernard Bilodeau ◽  
Louis-Philippe Crevier
Keyword(s):  
Land Surface ◽  
Weather Forecast ◽  
Forecast Model ◽  
Cold Season ◽  
Land Surface Scheme ◽  
Weather Forecast Model ◽  
Surface Scheme

scholarly journals Some Experimental Lessons on Digital Filtering in the ALADIN-France 3DVAR Based on Near-Ground Examination

2011 ◽  
Vol 139 (3) ◽  
pp. 774-785 ◽  
Author(s):  
Claude Fischer ◽  
Ludovic Auger
Keyword(s):  
Data Assimilation ◽  
Digital Filter ◽  
Three Dimensional ◽  
Weather Forecast ◽  
Forecast Model ◽  
Horizontal Wind ◽  
Screen Level ◽  
Incremental Formulation ◽  
Weather Forecast Model ◽  
Observation Impact

Abstract This paper deals with the characteristics and effects of digital filter initialization, as implemented in the operational three-dimensional variational data assimilation (3DVAR) system of the Aire Limitée Adaptation Dynamique Développement International (ALADIN)-France regional weather forecast model. First, a series of findings on the properties of the initialization of the model are discussed. Examples of initial spinup linked with inertia–gravity wave occurrence are shown, and the major sources for their generation are listed. These experimental results are compared with past and present experiences concerning the use and need for digital filter initialization. Furthermore, the impacts of switching to an incremental formulation of the filter in data assimilation mode are demonstrated. Second, the effects of the filter formulation on the results of an observation impact study are illustrated. The latter consists of implementing screen-level, 10-m horizontal wind information into the ALADIN 3DVAR analysis. There can, indeed, be some delicate interference between observation impact evaluation and the effects of filtering, at least on short-term forecasts. The paper is concluded with some general considerations on the experimental evaluation of spinup and the link between the assimilation system design and model state filtering.

scholarly journals A Multi-purpose Weather Forecast Model for the Mondsee Catchment

GI_Forum ◽  
2015 ◽  
Vol 1 ◽  
pp. 600-609 ◽  
Author(s):  
Hermann Klug ◽  
Liviu Oana
Keyword(s):  
Weather Forecast ◽  
Forecast Model ◽  
Weather Forecast Model
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