Impact of the additional FASTEX radiosonde observations on the High-Resolution Limited-Area Model (HIRLAM) data-assimilation and forecas- ting system

1999 ◽  
Vol 125 (561) ◽  
pp. 3359-3374
Author(s):  
BJARNE AMSTRUP ◽  
XIANG-YU HUANG
Keyword(s):  
High Resolution ◽  
Data Assimilation ◽  
Limited Area ◽  
Limited Area Model ◽  
Area Model

27 Years of Regional Cooperation for Limited Area Modelling in Central Europe

2018 ◽  
Vol 99 (7) ◽  
pp. 1415-1432 ◽  
Author(s):  
Yong Wang ◽  
Martin Belluš ◽  
Andrea Ehrlich ◽  
Máté Mile ◽  
Neva Pristov ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Central Europe ◽  
Regional Cooperation ◽  
Weather Prediction ◽  
Ensemble Forecasting ◽  
Limited Area ◽  
Member States ◽  
Limited Area Model ◽  
Area Model ◽  
Common System

AbstractThis paper describes 27 years of scientific and operational achievement of Regional Cooperation for Limited Area Modelling in Central Europe (RC LACE), which is supported by the national (hydro-) meteorological services of Austria, Croatia, the Czech Republic, Hungary, Romania, Slovakia, and Slovenia. The principal objectives of RC LACE are to 1) develop and operate the state-of-the-art limited-area model and data assimilation system in the member states and 2) conduct joint scientific and technical research to improve the quality of the forecasts.In the last 27 years, RC LACE has contributed to the limited-area Aire Limitée Adaptation Dynamique Développement International (ALADIN) system in the areas of preprocessing of observations, data assimilation, model dynamics, physical parameterizations, mesoscale and convection-permitting ensemble forecasting, and verification. It has developed strong collaborations with numerical weather prediction (NWP) consortia ALADIN, the High Resolution Limited Area Model (HIRLAM) group, and the European Centre for Medium-Range Weather Forecasts (ECMWF). RC LACE member states exchange their national observations in real time and operate a common system that provides member states with the preprocessed observations for data assimilation and verification. RC LACE runs operationally a common mesoscale ensemble system, ALADIN–Limited Area Ensemble Forecasting (ALADIN-LAEF), over all of Europe for early warning of severe weather.RC LACE has established an extensive regional scientific and technical collaboration in the field of operational NWP for weather research, forecasting, and applications. Its 27 years of experience have demonstrated the value of regional cooperation among small- and medium-sized countries for success in the development of a modern forecasting system, knowledge transfer, and capacity building.

scholarly journals The Soverato flood in Southern Italy: performance of global and limited-area ensemble forecasts

2003 ◽  
Vol 10 (3) ◽  
pp. 261-274 ◽  
Author(s):  
A. Montani ◽  
C. Marsigli ◽  
F. Nerozzi ◽  
T. Paccagnella ◽  
S. Tibaldi ◽  
...  
Keyword(s):  
High Resolution ◽  
Southern Italy ◽  
Ensemble Prediction ◽  
Limited Area ◽  
Prediction System ◽  
Probabilistic Prediction ◽  
Ensemble Forecasts ◽  
Ensemble Prediction System ◽  
Limited Area Model ◽  
Area Model

Abstract. The predictability of the flood event affecting Soverato (Southern Italy) in September 2000 is investigated by considering three different configurations of ECMWF ensemble: the operational Ensemble Prediction System (EPS), the targeted EPS and a high-resolution version of EPS. For each configuration, three successive runs of ECMWF ensemble with the same verification time are grouped together so as to generate a highly-populated "super-ensemble". Then, five members are selected from the super-ensemble and used to provide initial and boundary conditions for the integrations with a limited-area model, whose runs generate a Limited-area Ensemble Prediction System (LEPS). The relative impact of targeting the initial perturbations against increasing the horizontal resolution is assessed for the global ensembles as well as for the properties transferred to LEPS integrations, the attention being focussed on the probabilistic prediction of rainfall over a localised area. At the 108, 84 and 60- hour forecast ranges, the overall performance of the global ensembles is not particularly accurate and the best results are obtained by the high-resolution version of EPS. The LEPS performance is very satisfactory in all configurations and the rainfall maps show probability peaks in the correct regions. LEPS products would have been of great assistance to issue flood risk alerts on the basis of limited-area ensemble forecasts. For the 60-hour forecast range, the sensitivity of the results to the LEPS ensemble size is discussed by comparing a 5-member against a 51-member LEPS, where the limited-area model is nested on all EPS members. Little sensitivity is found as concerns the detection of the regions most likely affected by heavy precipitation, the probability peaks being approximately the same in both configurations.

scholarly journals Regionally Enhanced Global (REG) 4D-Var

2018 ◽  
Vol 146 (12) ◽  
pp. 4015-4038
Author(s):  
Michael A. Herrera ◽  
Istvan Szunyogh ◽  
Adam Brainard ◽  
David D. Kuhl ◽  
Karl Hoppel ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Prediction Models ◽  
Initial Conditions ◽  
Weather Prediction ◽  
Computational Cost ◽  
Limited Area ◽  
Atmospheric Flow ◽  
Forecast Performance ◽  
Limited Area Model ◽  
Area Model

Abstract A regionally enhanced global (REG) data assimilation (DA) method is proposed. The technique blends high-resolution model information from a single or multiple limited-area model domains with global model and observational information to create a regionally enhanced analysis of the global atmospheric state. This single analysis provides initial conditions for both the global and limited-area model forecasts. The potential benefits of the approach for operational data assimilation are (i) reduced development cost, (ii) reduced overall computational cost, (iii) improved limited-area forecast performance from the use of global information about the atmospheric flow, and (iv) improved global forecast performance from the use of more accurate model information in the limited-area domains. The method is tested by an implementation on the U.S. Navy’s four-dimensional variational global data assimilation system and global and limited-area numerical weather prediction models. The results of the monthlong forecast experiments suggest that the REG DA approach has the potential to deliver the desired benefits.

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