scholarly journals An online trajectory module (version 1.0) for the non-hydrostatic numerical weather prediction model COSMO

2013 ◽  
Vol 6 (1) ◽  
pp. 1223-1257
Author(s):  
A. K. Miltenberger ◽  
S. Pfahl ◽  
H. Wernli
Keyword(s):  
High Resolution ◽  
Wind Field ◽  
Model Simulation ◽  
Weather Prediction ◽  
Limited Area ◽  
Model Output ◽  
Wind Fields ◽  
Time Step ◽  
Flow Distortion ◽  
Cosmo Model

Abstract. A module to calculate online trajectories has been implemented into the non-hydrostatic limited-area weather prediction and climate model COSMO. Whereas offline trajectories are calculated with wind fields from model output, which is typically available every one to six hours, online trajectories use the simulated wind field at every model time step (typically less than a minute) to solve the trajectory equation. As a consequence, online trajectories much better capture the short-term temporal fluctuations of the wind field, which is particularly important for mesoscale flows near topography and convective clouds, and they do not suffer from temporal interpolation errors between model output times. The numerical implementation of online trajectories in the COSMO model is based upon an established offline trajectory tool and takes full account of the horizontal domain decomposition that is used for parallelization of the COSMO model. Although a perfect workload balance cannot be achieved for the trajectory module (due to the fact that trajectory positions are not necessarily equally distributed over the model domain), the additional computational costs are fairly small for high-resolution simulations. Various options have been implemented to initialize online trajectories at different locations and times during the model simulation. As a first application of the new COSMO module an Alpine North Föhn event in summer 1987 has been simulated with horizontal resolutions of 2.2 km, 7 km, and 14 km. It is shown that low-tropospheric trajectories calculated offline with one- to six-hourly wind fields can significantly deviate from trajectories calculated online. Deviations increase with decreasing model grid spacing and are particularly large in regions of deep convection and strong orographic flow distortion. On average, for this particular case study, horizontal and vertical positions between online and offline trajectories differed by 50–190 km and 150–750 m, respectively, after 24 h. This first application illustrates the potential for Lagrangian studies of mesoscale flows in high-resolution convection-resolving simulations using online trajectories.

scholarly journals An online trajectory module (version 1.0) for the nonhydrostatic numerical weather prediction model COSMO

2013 ◽  
Vol 6 (6) ◽  
pp. 1989-2004 ◽  
Author(s):  
A. K. Miltenberger ◽  
S. Pfahl ◽  
H. Wernli
Keyword(s):  
High Resolution ◽  
Wind Field ◽  
Weather Prediction ◽  
Limited Area ◽  
Model Output ◽  
Wind Fields ◽  
Time Step ◽  
Flow Distortion ◽  
Computational Costs ◽  
Cosmo Model

Abstract. A module to calculate online trajectories has been implemented into the nonhydrostatic limited-area weather prediction and climate model COSMO. Whereas offline trajectories are calculated with wind fields from model output, which is typically available every one to six hours, online trajectories use the simulated resolved wind field at every model time step (typically less than a minute) to solve the trajectory equation. As a consequence, online trajectories much better capture the short-term temporal fluctuations of the wind field, which is particularly important for mesoscale flows near topography and convective clouds, and they do not suffer from temporal interpolation errors between model output times. The numerical implementation of online trajectories in the COSMO-model is based upon an established offline trajectory tool and takes full account of the horizontal domain decomposition that is used for parallelization of the COSMO-model. Although a perfect workload balance cannot be achieved for the trajectory module (due to the fact that trajectory positions are not necessarily equally distributed over the model domain), the additional computational costs are found to be fairly small for the high-resolution simulations described in this paper. The computational costs may, however, vary strongly depending on the number of trajectories and trace variables. Various options have been implemented to initialize online trajectories at different locations and times during the model simulation. As a first application of the new COSMO-model module, an Alpine north foehn event in summer 1987 has been simulated with horizontal resolutions of 2.2, 7 and 14 km. It is shown that low-tropospheric trajectories calculated offline with one- to six-hourly wind fields can significantly deviate from trajectories calculated online. Deviations increase with decreasing model grid spacing and are particularly large in regions of deep convection and strong orographic flow distortion. On average, for this particular case study, horizontal and vertical positions between online and offline trajectories differed by 50–190 km and 150–750 m, respectively, after 24 h. This first application illustrates the potential for Lagrangian studies of mesoscale flows in high-resolution convection-resolving simulations using online trajectories.

scholarly journals Effects of Increasing Horizontal Resolution in a Convection-Permitting Model on Flood Forecasting: The 2011 Dramatic Events in Liguria, Italy

2015 ◽  
Vol 16 (4) ◽  
pp. 1843-1856 ◽  
Author(s):  
Silvio Davolio ◽  
Francesco Silvestro ◽  
Piero Malguzzi
Keyword(s):  
High Resolution ◽  
Weather Prediction ◽  
Flood Forecasting ◽  
Horizontal Resolution ◽  
Precipitation Forecast ◽  
Limited Area ◽  
Flood Prediction ◽  
Meteorological Model ◽  
The Impact ◽  
Atmospheric Simulations

Abstract Coupling meteorological and hydrological models is a common and standard practice in the field of flood forecasting. In this study, a numerical weather prediction (NWP) chain based on the BOLogna Limited Area Model (BOLAM) and the MOdello LOCale in Hybrid coordinates (MOLOCH) was coupled with the operational hydrological forecasting chain of the Ligurian Hydro-Meteorological Functional Centre to simulate two major floods that occurred during autumn 2011 in northern Italy. Different atmospheric simulations were performed by varying the grid spacing (between 1.0 and 3.0 km) of the high-resolution meteorological model and the set of initial/boundary conditions driving the NWP chain. The aim was to investigate the impact of these parameters not only from a meteorological perspective, but also in terms of discharge predictions for the two flood events. The operational flood forecasting system was thus used as a tool to validate in a more pragmatic sense the quantitative precipitation forecast obtained from different configurations of the NWP system. The results showed an improvement in flood prediction when a high-resolution grid was employed for atmospheric simulations. In turn, a better description of the evolution of the precipitating convective systems was beneficial for the hydrological prediction. Although the simulations underestimated the severity of both floods, the higher-resolution model chain would have provided useful information to the decision-makers in charge of protecting citizens.

scholarly journals A Feasibility Study of Simulating the Micro-Scale Wind Field for Wind Energy Applications by NWP/CFD Model with Improved Coupling Method and Data Assimilation

Energies ◽  
2019 ◽  
Vol 12 (13) ◽  
pp. 2549
Author(s):  
Shaohui Li ◽  
Xuejin Sun ◽  
Riwei Zhang ◽  
Chuanliang Zhang
Keyword(s):  
Data Assimilation ◽  
Wind Energy ◽  
Wind Field ◽  
Weather Prediction ◽  
Model Performance ◽  
Coupling Method ◽  
Cfd Model ◽  
Wind Fields ◽  
Micro Scale ◽  
Cfd Models

Understanding the details of micro-scale wind fields is important in the development of wind energy. Research has proven that coupling Numerical Weather Prediction (NWP) and Computational Fluid Dynamics (CFD) models is a better approach for micro-scale wind field simulation. The main purpose of this work is to improve the NWP/CFD model performance in two parts: (i) developing a new coupling method that is more suitable for complex terrain between the NWP and CFD models, and (ii) applying a data assimilation system in the CFD model. Regarding part (i), in order to solve the problem of great topographical difference at the domain boundaries between the two models, Cressman interpolation is utilized to impose the NWP model wind on the CFD model boundaries. In part (ii), an assimilation method, nudging, to apply assimilation of observations into the CFD model is explored. Based on the Cressman interpolation coupling method, a preliminary implementation of data assimilation is performed. The results show that the NWP/CFD model with the improved coupling method may capture the details of micro-scale wind fields more accurately. Using data assimilation, the NWP/CFD model performance may be further improved by cooperating observation data.

scholarly journals Temporal and Spatial Interpolation Errors of High-Resolution Modeled Atmospheric Fields

2016 ◽  
Vol 33 (2) ◽  
pp. 303-311 ◽  
Author(s):  
N. C. Privé ◽  
R. M. Errico
Keyword(s):  
High Resolution ◽  
Spatial Resolution ◽  
General Circulation ◽  
Temporal Frequency ◽  
General Circulation Models ◽  
Specific Humidity ◽  
Tropospheric Temperature ◽  
Model Output ◽  
Time Step ◽  
Optimal Output

AbstractGeneral circulation models can now be run at very high spatial resolutions to capture finescale features, but saving the full-spatial-resolution output at every model time step is usually not practical because of storage limitations. To reduce storage requirements, the model output may be produced at reduced temporal and/or spatial resolutions. When this reduced-resolution output is then used in situations where spatiotemporal interpolation is required, such as the generation of synthetic observations for observing system simulation experiments, interpolation errors can significantly affect the quality and usefulness of the reduced-resolution model output. Although it is common in practice to record model output at the highest possible spatial resolution with relatively infrequent temporal output, this may not be the best option to minimize interpolation errors. In this study, two examples using a high-resolution global run of the Goddard Earth Observing System Model, version 5 (GEOS-5), are presented to illustrate cases in which the optimal output dataset configurations for interpolation have high temporal frequency but reduced spatial resolutions. Interpolation errors of tropospheric temperature, specific humidity, and wind fields are investigated. The relationship between spatial and temporal output resolutions and interpolation errors is also characterized for the example model.

Development of Customized Variable-Resolution CPAS for Meteorological Simulation

2020 ◽  
Author(s):  
Louis Kwan Shu Tse ◽  
Ka Ki Ng ◽  
Yuk Sing Lui ◽  
Chi Chiu Cheung ◽  
Wai Nang Leung ◽  
...  
Keyword(s):  
High Resolution ◽  
Southern China ◽  
Global Analysis ◽  
Weather Prediction ◽  
Model Performance ◽  
Time Step ◽  
Variable Resolution ◽  
Area Of Interest ◽  
Run Time ◽  
Regional Forecast

<div> <p>    The model performance and run-time are two major concerns in numerical weather prediction. Both are substantially dependent on the grid specification, in particular, the number of grids, resolution and coverage of the refinement regions. In the Model for Prediction Across Scales - Atmosphere (MPAS-A), unstructured Voronoi mesh is used and the infrastructure, particularly the dynamic core, is implemented to support this flexible topology. However, only several standard meshes are available for download while customization is not supported. Moreover, the use of a globally-constant time-step (determined by the smallest grid) poses challenges on high resolution forecast using meshes with large resolution variation due to impractically long-running time. A Customizable Unstructured Mesh Generation (CUMG) and Hierarchical Time-Stepping (HTS) was developed in the ClusterTech Platform for Atmospheric Simulation (CPAS), offering a potential path for high-resolution local/regional forecast in MPAS-A’s framework. The CUMG algorithm enables local mesh refinement in arbitrary shape using user-defined horizontal resolution at any desired locations. Meshes with large resolution variation, for example, ranging from 128 km to 1 km can be generated. The resulting meshes are 100% well-staggered, and zero obtuse Delaunay triangle is guaranteed. The CPAS provides a web-based graphical user interface and no coding is needed for specifying the refinements. In real simulations, grids are integrated in time with heterogenous time-step according to their cell spacings using HTS. It reduces the model run-time tremendously, particularly for meshes with large resolution variation. </p> </div><div> <p>    In this study, a comparison on the mesh quality, efficiency and performance of a CPAS customized 128-to-1 km mesh to the MPAS-A standard 60-to-3 km mesh with and without HTS was performed. Three historical weather conditions over southern China in 2018 were selected to evaluate their performance: (i) passage of a cold front (ii) heavy rainfall and (iii) passage of a tropical cyclone. In general, the CPAS 128-to-1 km mesh was found to have better quality over the MPAS-A 60-to-3 km mesh, namely cell quality, angle-based triangle quality, and triangle quality. Moreover, using HTS, the benchmarked saving of the total run-time for the CPAS 128-to-1 km mesh and MPAS-A 60-to-3 km mesh are 56.8% (2.33x speedup) and 16.5% (1.20x speedup), respectively. Furthermore, the model results were validated through comparison with the National Centers for Environmental Prediction (NCEP) Final (FNL) Operational Global Analysis. The 5-day simulation results of various forecast variables within the area of interest (a lat-long box covering 3 km refinement region of the MPAS-A 60-to-3 km mesh) with and without HTS for both meshes show comparable performance in all cases. The promising model performance along with remarkable speedup indicates the validity and feasibility of high resolution local/regional forecast using customized global variable-resolution meshes in an operational manner. </p> </div>

scholarly journals Experimental Tropical Cyclone Forecasts Using a Variable-Resolution Global Model

2015 ◽  
Vol 143 (10) ◽  
pp. 4012-4037 ◽  
Author(s):  
Colin M. Zarzycki ◽  
Christiane Jablonowski
Keyword(s):  
High Resolution ◽  
Tropical Cyclone ◽  
Initial Conditions ◽  
Weather Prediction ◽  
Horizontal Resolution ◽  
Hurricane Sandy ◽  
Track Forecast ◽  
Time Step ◽  
Variable Resolution ◽  
The Impact

Abstract Tropical cyclone (TC) forecasts at 14-km horizontal resolution (0.125°) are completed using variable-resolution (V-R) grids within the Community Atmosphere Model (CAM). Forecasts are integrated twice daily from 1 August to 31 October for both 2012 and 2013, with a high-resolution nest centered over the North Atlantic and eastern Pacific Ocean basins. Using the CAM version 5 (CAM5) physical parameterization package, regional refinement is shown to significantly increase TC track forecast skill relative to unrefined grids (55 km, 0.5°). For typical TC forecast integration periods (approximately 1 week), V-R forecasts are able to nearly identically reproduce the flow field of a globally uniform high-resolution forecast. Simulated intensity is generally too strong for forecasts beyond 72 h. This intensity bias is robust regardless of whether the forecast is forced with observed or climatological sea surface temperatures and is not significantly mitigated in a suite of sensitivity simulations aimed at investigating the impact of model time step and CAM’s deep convection parameterization. Replacing components of the default physics with Cloud Layers Unified by Binormals (CLUBB) produces a statistically significant improvement in forecast intensity at longer lead times, although significant structural differences in forecasted TCs exist. CAM forecasts the recurvature of Hurricane Sandy into the northeastern United States 60 h earlier than the Global Forecast System (GFS) model using identical initial conditions, demonstrating the sensitivity of TC forecasts to model configuration. Computational costs associated with V-R simulations are dramatically decreased relative to globally uniform high-resolution simulations, demonstrating that variable-resolution techniques are a promising tool for future numerical weather prediction applications.

Probabilistic Forecasts of (Severe) Thunderstorms for the Purpose of Issuing a Weather Alarm in the Netherlands

2008 ◽  
Vol 23 (6) ◽  
pp. 1253-1267 ◽  
Author(s):  
Maurice J. Schmeits ◽  
Kees J. Kok ◽  
Daan H. P. Vogelezang ◽  
Rudolf M. van Westrhenen
Keyword(s):  
The Netherlands ◽  
Weather Prediction ◽  
Limited Area ◽  
Regression Equations ◽  
Model Output ◽  
Forecast System ◽  
Severe Thunderstorms ◽  
Skill Scores ◽  
Probabilistic Forecasts ◽  
Total Lightning

Abstract The development and verification of a new model output statistics (MOS) system is described; this system is intended to help forecasters decide whether a weather alarm for severe thunderstorms, based on high total lightning intensity, should be issued in the Netherlands. The system consists of logistic regression equations for both the probability of thunderstorms and the conditional probability of severe thunderstorms in the warm half-year (from mid-April to mid-October). These equations have been derived for 12 regions of about 90 km × 80 km each and for projections out to 12 h in advance (with 6-h periods). As a source for the predictands, reprocessed total lightning data from the Surveillance et d’Alerte Foudre par Interférométrie Radioélectrique (SAFIR) network have been used. The potential predictor dataset not only consisted of the combined postprocessed output from two numerical weather prediction (NWP) models, as in previous work by the first three authors, but it also contained an ensemble of advected radar and lightning data for the 0–6-h projections. The NWP model output dataset contained 17 traditional thunderstorm indices, computed from a reforecasting experiment with the High-Resolution Limited-Area Model (HIRLAM) and postprocessed output from the European Centre for Medium-Range Weather Forecasts (ECMWF) model. Brier skill scores and attributes diagrams show that the skill of the MOS thunderstorm forecast system is good and that the severe thunderstorm forecast system generally is also skillful, compared to the 2000–04 climatology, and therefore, the preoperational system was made operational at the Royal Netherlands Meteorological Institute (KNMI) in 2008.

scholarly journals A new module for the tracking of radar-derived precipitation with model-derived winds

2007 ◽  
Vol 10 ◽  
pp. 77-83 ◽  
Author(s):  
T. Winterrath ◽  
W. Rosenow
Keyword(s):  
Wind Field ◽  
Lead Time ◽  
Weather Prediction ◽  
Dynamical Evolution ◽  
Linear Displacement ◽  
Wind Data ◽  
Horizontal Wind ◽  
Time Range ◽  
Wind Fields ◽  
Precipitation Field

Abstract. A new approach for the nowcasting of precipitation has been developed at the German Weather Service combining extrapolation techniques and Numerical Weather Prediction (NWP) for a lead time range of several hours. Radar-derived precipitation fields serve as input data for a tracking algorithm using model-derived wind data. The composite precipitation field is derived from the precipitation scans which are performed every five minutes at the 16 German radar stations. The data are corrected from clutter and shading effects. The tracking of this radar-derived precipitation field is performed using the temporally and spatially resolved horizontal wind fields at different pressure levels provided by the Local Model Europe (LME). The optimal wind field is derived from minimization of the least-squares difference between a linear combination of model wind data from different pressure levels and the linear displacement vectors calculated via pattern recognition from previous radar measurements. An area-preserving displacement of the precipitation fields is realized by eliminating the wind field divergence and by omitting the dynamical evolution of the precipitation fields. Advection is performed using the fourth-order Bott scheme. Forecasted data comprise precipitation rates for every five minutes lead time as well as hourly sums of precipitation. The verification of a case study's results against radar precipitation measurements lead to a mean Equitable Threat Score (ETS) of 70%, 46%, and 38% for the first, second, and third forecast hour, respectively.

scholarly journals Sensitivity of ensemble Lagrangian reconstructions to assimilated wind time step resolution

2009 ◽  
Vol 9 (2) ◽  
pp. 8619-8633
Author(s):  
I. Pisso ◽  
V. Marécal ◽  
B. Legras ◽  
G. Berthet
Keyword(s):  
High Resolution ◽  
Spatial Resolution ◽  
Time Resolution ◽  
Wind Fields ◽  
Time Step ◽  
Coarse Resolution ◽  
Temporal And Spatial ◽  
Atmospheric Tracers

Abstract. The aim of this study is to define the optimal temporal and spatial resolution required for accurate offline diffusive Lagrangian reconstructions of high resolution in-situ tracers measurements based on meteorological wind fields and on coarse resolution 3-D tracer distributions. Increasing the time resolution of the advecting winds from three to one hour intervals has a modest impact on diffusive reconstructions in the case studied. This result is discussed in terms of the effect on the geometry of transported clouds of points in order to set out a method to assess the effect of meteorological flow on the transport of atmospheric tracers.

The Sydney Australia Wildfires of January 1994 - Meteorological Conditions and High Resolution Numerical Modeling Experiments

1996 ◽  
Vol 6 (3) ◽  
pp. 145 ◽  
Author(s):  
MS Speer ◽  
LM Leslie ◽  
JR Colquhoun ◽  
E Mitchell
Keyword(s):  
High Resolution ◽  
Weather Prediction ◽  
Weather Conditions ◽  
Detailed Examination ◽  
Meteorological Conditions ◽  
Limited Area ◽  
Research Activity ◽  
Southeastern Australia ◽  
South Wales ◽  
Resolution Model

Southeastern Australia is particularly vulnerable to wildfires during the spring and summer months, and the threat of devastation is present most years. In January 1994, the most populous city in Australia, Sydney, was ringed by wildfires, some of which penetrated well into suburban areas and there were many other serious fires in coastal areas of New South Wales (NSW). In recent years much research activity in Australia has focussed on the development of high resolution limited area models, for eventual operational prediction of meteorological conditions associated with high levels of wildfire risk. In this study, the period January 7-8, 1994 was chosen for detailed examination, as it was the most critical period during late December 1993/early January 1994 for the greater Sydney area. Routine forecast guidance from the Australian Bureau of Meteorology's operational numerical weather prediction (NWP) models was very useful in that both the medium and short range models predicted synoptic patterns suggesting extreme fire weather conditions up to several days in advance. However, vital information of a detailed nature was lacking. A new high resolution model was run at the operational resolution of 150 km and the much higher resolutions of 25 km and 5 km. The new model showed statistically significant greater skill in predicting details of wind, relative humidity and temperature patterns both near the surface and above the boundary layer. It also produced skilful predictions of the Forest Fire Danger Index.

Sign in / Sign up

Export Citation Format

Share Document