LIMITED AREA WEATHER PREDICTION MODELS VIEWED AS DYNAMICAL SYSTEMS

1999 ◽  
Vol 09 (05) ◽  
pp. 831-842 ◽  
Author(s):  
F. CHOMÉ ◽  
C. NICOLIS
Keyword(s):  
Prediction Models ◽  
Weather Prediction ◽  
Dynamical Behavior ◽  
Limited Area ◽  
Initial State ◽  
Weather Forecasts ◽  
Fine Mesh ◽  
Area Of Interest ◽  
Variable Mesh ◽  
High Resolution Models

Different strategies for building high-resolution models providing a more detailed description of a limited area of interest as for example, in regional weather forecasts are developed. They are subsequently compared, on the basis of the dynamical behavior generated by the corresponding models. The statistical properties of the relevant fields are analyzed, and predictability experiments are performed on statistical ensembles of close lying trajectories whose mean distance represents the uncertainty in the initial state of the system. The results show that a global, variable-mesh model performs much better than a limited area fine mesh one embedded into a coarser global model.

Forecasting of Tornadoes and Downbursts

2020 ◽  
Author(s):  
Djordje Romanic
Keyword(s):  
Chaos Theory ◽  
Prediction Models ◽  
Weather Prediction ◽  
Small Scale ◽  
Weather Forecasts ◽  
Wind Speeds ◽  
The Past ◽  
Extreme Wind ◽  
Extreme Wind Speeds ◽  
Numerical Weather Prediction Models

Tornadoes and downbursts cause extreme wind speeds that often present a threat to human safety, structures, and the environment. While the accuracy of weather forecasts has increased manifold over the past several decades, the current numerical weather prediction models are still not capable of explicitly resolving tornadoes and small-scale downbursts in their operational applications. This chapter describes some of the physical (e.g., tornadogenesis and downburst formation), mathematical (e.g., chaos theory), and computational (e.g., grid resolution) challenges that meteorologists currently face in tornado and downburst forecasting.

scholarly journals A Transformed Lagged Ensemble Forecasting Technique for Increasing Ensemble Size

2007 ◽  
Vol 135 (4) ◽  
pp. 1424-1438 ◽  
Author(s):  
Andrew R. Lawrence ◽  
James A. Hansen
Keyword(s):  
Prediction Models ◽  
Weather Prediction ◽  
Ensemble Forecast ◽  
Ensemble Forecasting ◽  
Limited Area ◽  
Ensemble Size ◽  
Probabilistic Forecasting ◽  
Ensemble Forecasts ◽  
Chaotic Model ◽  
The Impact

Abstract An ensemble-based data assimilation approach is used to transform old ensemble forecast perturbations with more recent observations for the purpose of inexpensively increasing ensemble size. The impact of the transformations are propagated forward in time over the ensemble’s forecast period without rerunning any models, and these transformed ensemble forecast perturbations can be combined with the most recent ensemble forecast to sensibly increase forecast ensemble sizes. Because the transform takes place in perturbation space, the transformed perturbations must be centered on the ensemble mean from the most recent forecasts. Thus, the benefit of the approach is in terms of improved ensemble statistics rather than improvements in the mean. Larger ensemble forecasts can be used for numerous purposes, including probabilistic forecasting, targeted observations, and to provide boundary conditions to limited-area models. This transformed lagged ensemble forecasting approach is explored and is shown to give positive results in the context of a simple chaotic model. By incorporating a suitable perturbation inflation factor, the technique was found to generate forecast ensembles whose skill were statistically comparable to those produced by adding nonlinear model integrations. Implications for ensemble forecasts generated by numerical weather prediction models are briefly discussed, including multimodel ensemble forecasting.

scholarly journals Two adaptive radiative transfer schemes for numerical weather prediction models

2007 ◽  
Vol 7 (21) ◽  
pp. 5659-5674 ◽  
Author(s):  
V. Venema ◽  
A. Schomburg ◽  
F. Ament ◽  
C. Simmer
Keyword(s):  
Radiative Transfer ◽  
Prediction Models ◽  
Weather Prediction ◽  
Limited Area ◽  
Perturbation Scheme ◽  
Spatial Correlations ◽  
Radiative Fluxes ◽  
Temporal Correlations ◽  
Core Idea ◽  
Computational Resources

Abstract. Radiative transfer calculations in atmospheric models are computationally expensive, even if based on simplifications such as the δ-two-stream approximation. In most weather prediction models these parameterisation schemes are therefore called infrequently, accepting additional model error due to the persistence assumption between calls. This paper presents two so-called adaptive parameterisation schemes for radiative transfer in a limited area model: A perturbation scheme that exploits temporal correlations and a local-search scheme that mainly takes advantage of spatial correlations. Utilising these correlations and with similar computational resources, the schemes are able to predict the surface net radiative fluxes more accurately than a scheme based on the persistence assumption. An important property of these adaptive schemes is that their accuracy does not decrease much in case of strong reductions in the number of calls to the δ-two-stream scheme. It is hypothesised that the core idea can also be employed in parameterisation schemes for other processes and in other dynamical models.

scholarly journals Dynamical contribution of mean potential vorticity pseudo-observations derived from MetOp/GOME2 ozone data into short-range weather forecast during high precipitation events

2015 ◽  
Vol 4 (2) ◽  
pp. 206
Author(s):  
Siham Sbii ◽  
Mimoun Zazoui ◽  
Noureddine Semane
Keyword(s):  
Potential Vorticity ◽  
Short Range ◽  
Initial Conditions ◽  
Weather Prediction ◽  
Dynamical Behavior ◽  
Heavy Precipitation ◽  
Limited Area ◽  
Total Column Ozone ◽  
Ozone Data ◽  
Precipitation Events

<p>Satellites are uniquely capable of providing uniform data coverage globally. Motivated by such capability, this study builds on a previously described methodology that generates numerical weather prediction initial conditions from satellite total column ozone data. The methodology is based on two principal steps. Firstly, the studied linear regression between vertical (100hPa-500hPa) Mean Potential Vorticity (MPV) and MetOp/GOME2 total ozone data (O3) generates MPV pseudo-observations. Secondly, the 3D variational (3D-Var) assimilation method is designed to take into account MPV pseudo-observations in addition to conventional observations.</p><p>After a successful assimilation of MPV pseudo-observations using a 3D-Var approach within the Moroccan version of the ALADIN limited-area model, the present study aims to assess the dynamical behavior of the short-range forecast at upper levels during heavy precipitation events (HPEs). It is found that MPV assimilation offers the possibility to internally monitor the model upper-level dynamics in addition to the use of Water Vapor Satellite images.</p>

scholarly journals Limited-area short-range ensemble predictions targeted for heavy rain in Europe

2005 ◽  
Vol 9 (4) ◽  
pp. 300-312 ◽  
Author(s):  
K. Sattler ◽  
H. Feddersen
Keyword(s):  
Short Range ◽  
Weather Prediction ◽  
Heavy Rain ◽  
River Basins ◽  
Ensemble Prediction ◽  
Limited Area ◽  
Target Area ◽  
Extreme Rainfall Events ◽  
Ensemble Prediction System ◽  
Area Of Interest

Abstract. Inherent uncertainties in short-range quantitative precipitation forecasts (QPF) from the high-resolution, limited-area numerical weather prediction model DMI-HIRLAM (LAM) are addressed using two different approaches to creating a small ensemble of LAM simulations, with focus on prediction of extreme rainfall events over European river basins. The first ensemble type is designed to represent uncertainty in the atmospheric state of the initial condition and at the lateral LAM boundaries. The global ensemble prediction system (EPS) from ECMWF serves as host model to the LAM and provides the state perturbations, from which a small set of significant members is selected. The significance is estimated on the basis of accumulated precipitation over a target area of interest, which contains the river basin(s) under consideration. The selected members provide the initial and boundary data for the ensemble integration in the LAM. A second ensemble approach tries to address a portion of the model-inherent uncertainty responsible for errors in the forecasted precipitation field by utilising different parameterisation schemes for condensation and convection in the LAM. Three periods around historical heavy rain events that caused or contributed to disastrous river flooding in Europe are used to study the performance of the LAM ensemble designs. The three cases exhibit different dynamic and synoptic characteristics and provide an indication of the ensemble qualities in different weather situations. Precipitation analyses from the Deutsche Wetterdienst (DWD) are used as the verifying reference and a comparison of daily rainfall amounts is referred to the respective river basins of the historical cases.

scholarly journals A Similarity-Based Implementation of the Schaake Shuffle

2016 ◽  
Vol 144 (5) ◽  
pp. 1909-1921 ◽  
Author(s):  
Roman Schefzik
Keyword(s):  
Prediction Models ◽  
Initial Conditions ◽  
Weather Prediction ◽  
Similarity Criterion ◽  
Ensemble Prediction ◽  
Ensemble Forecasts ◽  
Weather Forecasts ◽  
Prediction Horizon ◽  
Prediction Systems ◽  
Specific Implementation

Contemporary weather forecasts are typically based on ensemble prediction systems, which consist of multiple runs of numerical weather prediction models that vary with respect to the initial conditions and/or the parameterization of the atmosphere. Ensemble forecasts are frequently biased and show dispersion errors and thus need to be statistically postprocessed. However, current postprocessing approaches are often univariate and apply to a single weather quantity at a single location and for a single prediction horizon only, thereby failing to account for potentially crucial dependence structures. Nonparametric multivariate postprocessing methods based on empirical copulas, such as ensemble copula coupling or the Schaake shuffle, can address this shortcoming. A specific implementation of the Schaake shuffle, called the SimSchaake approach, is introduced. The SimSchaake method aggregates univariately postprocessed ensemble forecasts using dependence patterns from past observations. Specifically, the observations are taken from historical dates at which the ensemble forecasts resembled the current ensemble prediction with respect to a specific similarity criterion. The SimSchaake ensemble outperforms all reference ensembles in an application to ensemble forecasts for 2-m temperature from the European Centre for Medium-Range Weather Forecasts.

scholarly journals Comparison of Snow Cover from Satellite and Numerical Weather Prediction Models in the Northern Hemisphere and Northern Europe

2009 ◽  
Vol 48 (6) ◽  
pp. 1199-1216 ◽  
Author(s):  
Otto Hyvärinen ◽  
Kalle Eerola ◽  
Niilo Siljamo ◽  
Jarkko Koskinen
Keyword(s):  
Snow Cover ◽  
Prediction Models ◽  
Weather Prediction ◽  
Ground Truth ◽  
In Situ Measurements ◽  
Lower Atmosphere ◽  
Limited Area ◽  
In Situ Observations ◽  
Using Data

Abstract Snow cover has a strong effect on the surface and lower atmosphere in NWP models. Because the progress of in situ observations has stalled, satellite-based snow analyses are becoming increasingly important. Currently, there exist several products that operationally map global or continental snow cover. In this study, satellite-based snow cover analyses from NOAA, NASA, and the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT), and NWP snow analyses from the High-Resolution Limited-Area Model (HIRLAM) and ECMWF, were compared using data from January to June 2006. Because no analyses were independent and since available in situ measurements were already used in the NWP analyses, no independent ground truth was available and only the consistency between analyses could be compared. Snow analyses from NOAA, NASA, and ECMWF were similar, but the analysis from NASA was greatly hampered by clouds. HIRLAM and EUMETSAT deviated most from other analyses. Even though the analysis schemes of HIRLAM and ECMWF were quite similar, the resulting snow analyses were quite dissimilar, because ECMWF used the satellite information of snow cover in the form of NOAA analyses, while HIRLAM used none. The differences are especially prominent in areas around the snow edge where few in situ observations are available. This suggests that NWP snow analyses based only on in situ measurements would greatly benefit from inclusion of satellite-based snow cover information.

scholarly journals The role of urban boundary layer investigated by high resolution models and ground based observations in Rome area: a step for understanding parameterizations potentialities

2013 ◽  
Vol 6 (3) ◽  
pp. 5297-5344
Author(s):  
E. Pichelli ◽  
R. Ferretti ◽  
M. Cacciani ◽  
A. M. Siani ◽  
V. Ciardini ◽  
...  
Keyword(s):  
Boundary Layer ◽  
High Resolution ◽  
Urban Areas ◽  
Prediction Models ◽  
Weather Prediction ◽  
Sonic Anemometer ◽  
Lower Atmosphere ◽  
Area Of Interest ◽  
The Impact

Abstract. The urban forcing on thermo-dynamical conditions can largely influences local evolution of the atmospheric boundary layer. Urban heat storage can produce noteworthy mesoscale perturbations of the lower atmosphere. The new generations of high-resolution numerical weather prediction models (NWP) is nowadays largely applied also to urban areas. It is therefore critical to reproduce correctly the urban forcing which turns in variations of wind, temperature and water vapor content of the planetary boundary layer (PBL). WRF-ARW, a new model generation, has been used to reproduce the circulation in the urban area of Rome. A sensitivity study is performed using different PBL and surface schemes. The significant role of the surface forcing in the PBL evolution has been verified by comparing model results with observations coming from many instruments (LiDAR, SODAR, sonic anemometer and surface stations). The crucial role of a correct urban representation has been demonstrated by testing the impact of different urban canopy models (UCM) on the forecast. Only one of three meteorological events studied will be presented, chosen as statistically relevant for the area of interest. The WRF-ARW model shows a tendency to overestimate vertical transmission of horizontal momentum from upper levels to low atmosphere, that is partially corrected by local PBL scheme coupled with an advanced UCM. Depending on background meteorological scenario, WRF-ARW shows an opposite behavior in correctly representing canopy layer and upper levels when local and non local PBL are compared. Moreover a tendency of the model in largely underestimating vertical motions has been verified.

scholarly journals Sensitivity of Radiative Fluxes to Aerosols in the ALADIN-HIRLAM Numerical Weather Prediction System

2020 ◽  
Author(s):  
Laura Rontu ◽  
Emily Gleeson ◽  
Daniel Martin Perez ◽  
Kristian Pagh Nielsen ◽  
Velle Toll
Keyword(s):  
Optical Properties ◽  
Numerical Weather Prediction ◽  
Prediction Models ◽  
Weather Prediction ◽  
Limited Area ◽  
Prediction System ◽  
Heating Rates ◽  
Radiative Fluxes ◽  
Numerical Weather ◽  
The Impact

The direct radiative effect of aerosols is taken into account in many limited area numerical weather prediction models using wavelength-dependent aerosol optical depths of a range of aerosol species. We study the impact of aerosol distribution and optical properties on radiative transfer, based on climatological and more realistic near real-time aerosol data. Sensitivity tests were carried out using the single column version of the ALADIN-HIRLAM numerical weather prediction system, set up to use the HLRADIA broadband radiation scheme. The tests were restricted to clear-sky cases to avoid the complication of cloud-radiation-aerosol interactions. The largest differences in radiative fluxes and heating rates were found to be due to different aerosol loads. When the loads are large, the radiative fluxes and heating rates are sensitive to the aerosol inherent optical properties and vertical distribution of the aerosol species. Impacts of aerosols on shortwave radiation dominate longwave impacts. Sensitivity experiments indicated the important effects of highly absorbing black carbon aerosols and strongly scattering desert dust.

De Émeraude/Péridot à Arpège/Aladin

2021 ◽  
pp. 029
Author(s):  
Jean Coiffier ◽  
Régis Juvanon du Vachat ◽  
Jean Pailleux
Keyword(s):  
Numerical Models ◽  
Weather Prediction ◽  
Substantial Improvement ◽  
Limited Area ◽  
Weather Forecasts ◽  
Scientific Innovation ◽  
Local Screen ◽  
New Models ◽  
Modèle Spectral ◽  
Prediction Techniques

À la Météorologie nationale, trois modèles de prévision du projet Améthyste étaient opérationnels en 1980. Des innovations scientifiques, des échanges avec le Centre européen pour les prévisions météorologiques à moyen terme (CEPMMT) et l'arrivée d'un calculateur Cray-1 en 1983 incitèrent à développer de nouveaux modèles. Au début de l'année 1985, le modèle spectral Émeraude et le modèle sur domaine limité Péridot remplacèrent les anciens modèles. L'enthousiasme et la compétence de Jean-François Geleyn, permirent de renouveler en profondeur les paramétrisations physiques. Ces nouveaux modèles améliorèrent les prévisions jusqu'au temps sensible. Enfin de nouvelles techniques de prévision numérique tant pour les modèles de prévision que pour l'assimilation de données allaient ouvrir la voie aux projets Arpège et Aladin. At the Météorologie nationale, at the beginning of the 1980's, there were three operational models. Scientific innovation, fruitful exchanges with scientists at the European Centre for Medium Range Weather Forecasts (ECMWF) and the arrival of a Cray-1 computer in 1983 prompted to develop new models. At the beginning of year 1985 the Émeraude spectral model and the Péridot limited area model replaced the old models. The enthusiasm and the competence of Jean-François Geleyn enabled to deeply renew the physical parameterizations. These new models led to a substantial improvement of the forecasts including local screen level values. Finally new numerical weather prediction techniques both in numerical models and data assimilation were going to open the way for the new Arpège and Aladin projects.

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