Quantitative Evaluation of a Mesoscale Numerical Model Simulation Using Four-Dimensional Data Assimilation of Complex Airflow over the Kanto Region in Japan

1996 ◽  
pp. 569-581
Author(s):  
Itsushi Uno
Keyword(s):  
Numerical Model ◽  
Data Assimilation ◽  
Quantitative Evaluation ◽  
Model Simulation ◽  
Kanto Region ◽  
Four Dimensional Data Assimilation

scholarly journals Evaluation of Operational Monsoon Moisture Surveillance and Severe Weather Prediction Utilizing COSMIC-2/FORMOSAT-7 Radio Occultation Observations

2021 ◽  
Vol 13 (15) ◽  
pp. 2979
Author(s):  
Yu-Chun Chen ◽  
Chih-Chien Tsai ◽  
Yi-Chao Wu ◽  
An-Hsiang Wang ◽  
Chieh-Ju Wang ◽  
...  
Keyword(s):  
Numerical Model ◽  
Data Assimilation ◽  
Water Resource Management ◽  
Radio Occultation ◽  
Positive Impact ◽  
Weather Prediction ◽  
Severe Weather ◽  
Model Experiments ◽  
Typhoon Structure ◽  
Numerical Model Experiments

Operational monsoon moisture surveillance and severe weather prediction is essential for timely water resource management and disaster risk reduction. For these purposes, this study suggests a moisture indicator using the COSMIC-2/FORMOSAT-7 radio occultation (RO) observations and evaluates numerical model experiments with RO data assimilation. The RO data quality is validated by a comparison between sampled RO profiles and nearby radiosonde profiles around Taiwan prior to the experiments. The suggested moisture indicator accurately monitors daily moisture variations in the South China Sea and the Bay of Bengal throughout the 2020 monsoon rainy season. For the numerical model experiments, the statistics of 152 moisture and rainfall forecasts for the 2020 Meiyu season in Taiwan show a neutral to slightly positive impact brought by RO data assimilation. A forecast sample with the most significant improvement reveals that both thermodynamic and dynamic fields are appropriately adjusted by model integration posterior to data assimilation. The statistics of 17 track forecasts for typhoon Hagupit (2020) also show the positive effect of RO data assimilation. A forecast sample reveals that the member with RO data assimilation simulates better typhoon structure and intensity than the member without, and the effect can be larger and faster via multi-cycle RO data assimilation.

Data assimilation with the ensemble Kalman filter in a numerical model of the North Sea

2016 ◽  
Vol 66 (8) ◽  
pp. 955-971 ◽  
Author(s):  
Stéphanie Ponsar ◽  
Patrick Luyten ◽  
Valérie Dulière
Keyword(s):  
Kalman Filter ◽  
Numerical Model ◽  
Data Assimilation ◽  
North Sea ◽  
Ensemble Kalman Filter ◽  
The North ◽  
The North Sea

On four-dimensional data-assimilation

Tellus ◽  
1973 ◽  
Vol 25 (6) ◽  
pp. 595-595
Author(s):  
INGEMAR HOLMSTRÖM
Keyword(s):  
Data Assimilation ◽  
Four Dimensional Data Assimilation

Fractality of Simulated Fracture

2009 ◽  
Vol 409 ◽  
pp. 154-160 ◽  
Author(s):  
Petr Frantík ◽  
Zbyněk Keršner ◽  
Václav Veselý ◽  
Ladislav Řoutil
Keyword(s):  
Numerical Model ◽  
Elastic Plate ◽  
Model Simulation ◽  
Element Model ◽  
The Other ◽  
Particle Model ◽  
Discrete Element Model ◽  
Fractal Nature ◽  
Discrete Elements ◽  
The Impact

The paper is focussed on numerical simulations of the fracture of a quasi-brittle specimen due to its impact onto a fixed rigid elastic plate. The failure of the specimen after the impact is modelled in two ways based on the physical discretization of continuum: via physical discrete elements and pseudo-particles. Advantages and drawbacks of both used methods are discussed. The size distribution of the fragments of the broken specimen resulting from physical discrete element model simulation follows a power law, which indicates the ability of the numerical model to identify the fractal nature of the fracture. The pseudo-particle model, on the other side, can successfully predict the kinematics of the fragments of the specimen under impact failure.

On the Origin of Rotation Derived from Super Rapid Scan Satellite Imagery at the Cloud-Tops of Severe Deep Convection

2021 ◽  
Author(s):  
Jason M. Apke ◽  
John R. Mecikalski
Keyword(s):  
Quality Control ◽  
Numerical Model ◽  
Flow Field ◽  
Optical Flow ◽  
Case Studies ◽  
Model Simulation ◽  
Deep Convection ◽  
Vertical Wind Shear ◽  
Future Research ◽  
Severe Thunderstorms

AbstractSevere thunderstorms routinely exhibit adjacent maxima and minima in cloud-top vertical vorticity (CTV) downstream of overshooting tops within flow fields retrieved using sequences of fine-temporal resolution (1-min) geostationary operational environmental satellite (GOES)-R series imagery. Little is known about the origin of this so-called “CTV couplet” signature, and whether the signature is the result of flow field derivational artifacts. Thus, the CTV signature’s relevance to research and operations is currently ambiguous. Within this study, we explore the origin of near-cloud-top rotation using an idealized supercell numerical model simulation. Employing an advanced dense optical flow algorithm, image stereoscopy, and numerical model background wind approximations, the artifacts common with cloud-top flow field derivation are removed from two supercell case studies sampled by GOES-R imagers. It is demonstrated that the CTV couplet originates from tilted and converged horizontal vorticity that is baroclinically generated in the upper levels (above 10 km) immediately downstream of the overshooting top. This baroclinic generation would not be possible without a strong and sustained updraft, implying an indirect relationship to rotationally-maintained supercells. Furthermore, it is demonstrated that CTV couplets derived with optical flow algorithms originate from actual rotation within the storm anvils in the case studies explored here, though supercells with opaque above anvil cirrus plumes and strong anvil-level negative vertical wind shear may produce rotation signals as an artifact without quality control. Artifact identification and quality control is discussed further here for future research and operations use.

Four-dimensional data assimilation with a wide range of scales

1995 ◽  
Vol 47 (5) ◽  
pp. 974-997 ◽  
Author(s):  
Monique Tanguay ◽  
Peter Bartello ◽  
Pierre Gauthier
Keyword(s):  
Data Assimilation ◽  
Wide Range ◽  
Four Dimensional Data Assimilation
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