scholarly journals A New Theoretical Framework for Understanding Multiscale Atmospheric Predictability

2020 ◽  
Vol 77 (7) ◽  
pp. 2297-2309
Author(s):  
Y. Qiang Sun ◽  
Fuqing Zhang
Keyword(s):  
Energy Spectrum ◽  
Numerical Models ◽  
Weather Prediction ◽  
Three Dimensional ◽  
Theoretical Framework ◽  
Growth Behavior ◽  
Small Scale ◽  
Growth Equation ◽  
Error Growth ◽  
Atmospheric Predictability

AbstractHere we present a new theoretical framework that connects the error growth behavior in numerical weather prediction (NWP) with the atmospheric kinetic energy spectrum. Building on previous studies, our newly proposed framework applies to the canonical observed atmospheric spectrum that has a −3 slope at synoptic scales and a −5/3 slope at smaller scales. Based on this realistic hybrid energy spectrum, our new experiment using hybrid numerical models provides reasonable estimations for the finite predictable ranges at different scales. We further derive an analytical equation that helps understand the error growth behavior. Despite its simplicity, this new analytical error growth equation is capable of capturing the results of previous comprehensive theoretical and observational studies of atmospheric predictability. The success of this new theoretical framework highlights the combined effects of quasi-two-dimensional dynamics at synoptic scales (−3 slope) and three-dimensional turbulence-like small-scale chaotic flows (−5/3 slope) in dictating the error growth. It is proposed that this new framework could serve as a guide for understanding and estimating the predictability limit in the real world.

scholarly journals Star Formation from Turbulent Fragmentation

2003 ◽  
Vol 208 ◽  
pp. 61-70
Author(s):  
Ralf S. Klessen
Keyword(s):  
Mass Spectrum ◽  
Star Formation ◽  
Numerical Models ◽  
Three Dimensional ◽  
Dynamical Evolution ◽  
Small Scale ◽  
Solar Mass ◽  
Low Efficiency ◽  
Three Dimensional Models ◽  
Log Normal

Star formation is intimately linked to the dynamical evolution of molecular clouds. Turbulent fragmentation determines where and when protostellar cores form, and how they contract and grow in mass via accretion from the surrounding cloud material. Using numerical models of self-gravitating supersonic turbulence, efficiency, spatial distribution and timescale of star formation in turbulent interstellar clouds are estimated. Turbulence that is not continuously replenished or that is driven on large scales leads to a rapid formation of stars in a clustered mode, whereas interstellar turbulence that carries most energy on small scales results in isolated star formation with low efficiency. The clump mass spectrum for models of pure hydrodynamic turbulence is steeper than the observed one, but gets close to it when gravity is included. The mass spectrum of dense cores is log-normal for decaying and large-wavelength turbulence, similar to the IMF, but is too flat in the case of small-scale turbulence. The three-dimensional models of molecular cloud fragmentation can be combined with dynamical pre-main sequence stellar evolution calculations to obtain a consistent description of all phases of the star formation process. First results are reported for a one solar mass protostar.

scholarly journals Mechanical Characterization of Timber-to-Timber Composite (TTC) Joints with Self-Tapping Screws in a Standard Push-Out Setup

2020 ◽  
Vol 10 (18) ◽  
pp. 6534
Author(s):  
Chiara Bedon ◽  
Martina Sciomenta ◽  
Massimo Fragiacomo
Keyword(s):  
Mechanical Characterization ◽  
Numerical Models ◽  
Three Dimensional ◽  
Analytical Models ◽  
Small Scale ◽  
Load Bearing ◽  
Timber Constructions ◽  
Technical Interest ◽  
Push Out

Self-tapping screws (STSs) can be efficiently used in various fastening solutions for timber constructions and are notoriously able to offer high stiffness and load-carrying capacity, compared to other timber-to-timber composite (TTC) joint typologies. The geometrical and mechanical characterization of TTC joints, however, is often hard and uncertain, due to a combination of various influencing parameters and mechanical aspects. Among others, the effects of friction phenomena between the system components and their reciprocal interaction under the imposed design loads can remarkably influence the final estimates on structural capacity, in the same way of possible variations in the boundary conditions. The use of Finite Element (FE) numerical models is well-known to represent a robust tool and a valid alternative to costly and time consuming experiments and allows one to further explore the selected load-bearing components at a more refined level. Based on previous research efforts, this paper presents an extended FE investigation based on full three-dimensional (3D) brick models and surface-based cohesive zone modelling (CZM) techniques. The attention is focused on the mechanical characterization of small-scale TTC specimens with inclined STSs having variable configurations, under a standard push-out (PO) setup. Based on experimental data and analytical models of literature, an extended parametric investigation is presented and correlation formulae are proposed for the analysis of maximum resistance and stiffness variations. The attention is then focused on the load-bearing role of the steel screws, as an active component of TTC joints, based on the analysis of sustained resultant force contributions. The sensitivity of PO numerical estimates to few key input parameters of technical interest, including boundaries, friction and basic damage parameters, is thus discussed in the paper.

Numerical modelling of chain-link steel wire nets with discrete elements

2019 ◽  
Vol 56 (3) ◽  
pp. 398-419 ◽  
Author(s):  
Albrecht von Boetticher ◽  
Axel Volkwein
Keyword(s):  
Numerical Models ◽  
Steel Wire ◽  
Three Dimensional ◽  
Element Model ◽  
Nonlinear Material ◽  
Opening Angle ◽  
Small Scale ◽  
Discrete Elements ◽  
Anisotropic Behaviour ◽  
Chain Link

Chain-link mesh is one of several net types used as protection against rockfall, shallow landslides, and debris flows. The dynamic impact and the corresponding nonlinear barrier response require numerical models. Chain-link meshes show a nonlinear anisotropic behaviour caused by the geometry of the wire. Resolving this geometry and its deformation results in a bottleneck of numerical costs. We present a discrete element model that covers the nonlinear and anisotropic behaviour of the chain-link mesh, using results from either small-scale, quasi-static tension tests or from a detailed mechanical model as material-law input. The mesh stiffness, resistance, and failure depend on the inner mesh opening angle and thus on the direction of deformation. This information enters the model through the transformation of the nonlinear, three-dimensional deformation processes into a nonlinear material law, with an interpolated dependency on the inner mesh angle. The model maps the resistance of the mesh against impacting masses and covers the energy absorption and it is capable of predicting the dynamic behaviour of different protection barriers with high accuracy, optimized calculation time, and minimized calibration efforts. This is illustrated by high impact energy tests that follow the ETAG027 standard, and also with a rockfall attenuating system.

scholarly journals Observation Operator for Visible and Near-Infrared Satellite Reflectances

2014 ◽  
Vol 31 (6) ◽  
pp. 1216-1233 ◽  
Author(s):  
Philipp M. Kostka ◽  
Martin Weissmann ◽  
Robert Buras ◽  
Bernhard Mayer ◽  
Olaf Stiller
Keyword(s):  
Water Content ◽  
Near Infrared ◽  
Weather Prediction ◽  
Three Dimensional ◽  
Liquid Water Content ◽  
Relative Difference ◽  
Cloud Microphysics ◽  
Small Scale ◽  
Limited Area ◽  
Central Wavelength

Abstract Operational numerical weather prediction systems currently only assimilate infrared and microwave satellite observations, whereas visible and near-infrared reflectances that comprise information on atmospheric clouds are not exploited. One of the reasons for that is the absence of computationally efficient observation operators. To remedy this issue in anticipation of the future regional Kilometer-Scale Ensemble Data Assimilation (KENDA) system of Deutscher Wetterdienst, we have developed a version that is fast enough for investigating the assimilation of cloudy reflectances in a case study approach. The operator solves the radiative transfer equation to simulate visible and near-infrared channels of satellite instruments based on the one-dimensional (1D) discrete ordinate method. As input, model output of the operational limited-area Consortium for Small-Scale Modeling (COSMO) model of Deutscher Wetterdienst is used. Assumptions concerning subgrid-scale processes, calculation of in-cloud values of liquid water content, ice water content, and cloud microphysics are summarized, and the accuracy of the 1D simulation is estimated through comparison with three-dimensional (3D) Monte Carlo solver results. In addition, the effects of a parallax correction and horizontal smoothing are quantified. The relative difference between the 1D simulation in “independent column approximation” and the 3D calculation is typically less than 9% between 0600 and 1500 UTC, computed from four scenes during one day (with local noon at 1115 UTC). The parallax-corrected version reduces the deviation to less than 6% for reflectance observations with a central wavelength of 810 nm. Horizontal averaging can further reduce the error of the 1D simulation. In all cases, the bias is less than 1% for the model domain.

Water vapor transport in the turbulent planetary boundary layer (PBL) measured over heterogeneous terrain using multiple LiDAR systems.

2020 ◽  
Author(s):  
Johannes Speidel ◽  
Hannes Vogelmann ◽  
Matthias Mauder ◽  
Matthias Perfahl ◽  
Timothy J. Wagner ◽  
...  
Keyword(s):  
Water Vapor ◽  
Numerical Models ◽  
Weather Prediction ◽  
Measurement Techniques ◽  
Vapor Transport ◽  
Water Vapor Transport ◽  
Small Scale ◽  
Special Focus ◽  
Heterogeneous Terrain ◽  
Essential Question

<p>Water vapor plays a crucial role for several processes on almost every scale of Earth's atmosphere. However, its turbulent transport throughout the PBL is at the same time particularly important and not very well understood. With the increasing resolution of numerical models arises the need for improved representations of the small-scale and nonlinear turbulent processes inside the PBL. Recent papers have shown that these refinements, predominantly on water vapor transport, are urgently needed as they are a limiting factor in the process of lifting numerical weather prediction to the next level.<br> The CHEESEHEAD campaign, carried out in summer 2019, especially addresses the complex, turbulent land-atmosphere interactions over heterogeneous terrain and aims to close the energy balance. Therefore, a dense network of sensors has been installed measuring throughout the scales of the PBL with a multiple set of different measurement techniques.<br> Within this proposed contribution, first results from the CHEESEHEAD measurements with a water vapor DIAL in combination with several Doppler wind LiDARs will be presented. The synergy of a virtual tower scanning geometry of the Doppler LiDARs right next to the water vapor DIAL delivers highly resolved data throughout the entire PBL. Therefore, special focus of this work lies on turbulent fluctuations inside vertical water vapor columns during the measuring time, spanning the entire PBL. This gives the additional opportunity to observe important entrainment processes at the very top of the PBL. Furthermore, this work deals with the calculation of vertical fluxes of latent heat. Therefore, the essential question whether this data is suitable for these calculations, which are highly sensitive towards temporal resolution, will be addressed. As a further step, aerosol and temperature data that have been measured with the same LiDAR system shall be integrated as well - aiming towards a comprehensive insight on relevant processes throughout the entire PBL. </p>

scholarly journals Crossing Multiple Gray Zones in the Transition from Mesoscale to Microscale Simulation over Complex Terrain

Atmosphere ◽  
2019 ◽  
Vol 10 (5) ◽  
pp. 274 ◽  
Author(s):  
Fotini Chow ◽  
Christoph Schär ◽  
Nikolina Ban ◽  
Katherine Lundquist ◽  
Linda Schlemmer ◽  
...  
Keyword(s):  
Complex Terrain ◽  
Large Scale ◽  
Climate Modeling ◽  
Numerical Models ◽  
Weather Prediction ◽  
Regional Climate ◽  
Regional Climate Modeling ◽  
Small Scale ◽  
Gray Zone ◽  
Definition Of

This review paper explores the field of mesoscale to microscale modeling over complex terrain as it traverses multiple so-called gray zones. In an attempt to bridge the gap between previous large-scale and small-scale modeling efforts, atmospheric simulations are being run at an unprecedented range of resolutions. The gray zone is the range of grid resolutions where particular features are neither subgrid nor fully resolved, but rather are partially resolved. The definition of a gray zone depends strongly on the feature being represented and its relationship to the model resolution. This paper explores three gray zones relevant to simulations over complex terrain: turbulence, convection, and topography. Taken together, these may be referred to as the gray continuum. The focus is on horizontal grid resolutions from ∼10 km to ∼10 m. In each case, the challenges are presented together with recent progress in the literature. A common theme is to address cross-scale interaction and scale-awareness in parameterization schemes. How numerical models are designed to cross these gray zones is critical to complex terrain applications in numerical weather prediction, wind resource forecasting, and regional climate modeling, among others.

scholarly journals Numerical simulations of Hall MHD small-scale dynamos

2009 ◽  
Vol 5 (H15) ◽  
pp. 436-437
Author(s):  
Daniel O. Gómez ◽  
Pablo D. Mininni ◽  
Pablo Dmitruk
Keyword(s):  
Numerical Simulations ◽  
Hall Effect ◽  
Three Dimensional ◽  
Theoretical Framework ◽  
Mhd Equations ◽  
Small Scale ◽  
Hall Parameter ◽  
Hall Mhd ◽  
Three Dimensional Simulations

AbstractMuch of the progress in our understanding of dynamo mechanisms, has been made within the theoretical framework of magnetohydrodynamics (MHD). However, for sufficiently diffuse media, the Hall effect eventually becomes non-negligible. We present results from three dimensional simulations of the Hall-MHD equations subjected to random non-helical forcing. We study the role of the Hall effect in the dynamo efficiency for different values of the Hall parameter, using a pseudospectral code to achieve exponentially fast convergence.

scholarly journals Impact of the Mesoscale Range on Error Growth and the Limits to Atmospheric Predictability

2020 ◽  
Vol 77 (11) ◽  
pp. 3769-3779
Author(s):  
Tsz Yan Leung ◽  
Martin Leutbecher ◽  
Sebastian Reich ◽  
Theodore G. Shepherd
Keyword(s):  
Weather Prediction ◽  
Growth Characteristic ◽  
Growth Behavior ◽  
Original Model ◽  
Two Dimensional ◽  
Error Growth ◽  
Synoptic Scale ◽  
Perfect Model ◽  
Per Se ◽  
Model Context

AbstractGlobal numerical weather prediction (NWP) models have begun to resolve the mesoscale k−5/3 range of the energy spectrum, which is known to impose an inherently finite range of deterministic predictability per se as errors develop more rapidly on these scales than on the larger scales. However, the dynamics of these errors under the influence of the synoptic-scale k−3 range is little studied. Within a perfect-model context, the present work examines the error growth behavior under such a hybrid spectrum in Lorenz’s original model of 1969, and in a series of identical-twin perturbation experiments using an idealized two-dimensional barotropic turbulence model at a range of resolutions. With the typical resolution of today’s global NWP ensembles, error growth remains largely uniform across scales. The theoretically expected fast error growth characteristic of a k−5/3 spectrum is seen to be largely suppressed in the first decade of the mesoscale range by the synoptic-scale k−3 range. However, it emerges once models become fully able to resolve features on something like a 20-km scale, which corresponds to a grid resolution on the order of a few kilometers.

scholarly journals Using Convection-Allowing Ensembles to Understand the Predictability of an Extreme Rainfall Event

2016 ◽  
Vol 144 (10) ◽  
pp. 3651-3676 ◽  
Author(s):  
Erik R. Nielsen ◽  
Russ S. Schumacher
Keyword(s):  
Large Scale ◽  
Numerical Models ◽  
Regional Scale ◽  
Extreme Rainfall ◽  
Rainfall Event ◽  
Small Scale ◽  
Extreme Rainfall Event ◽  
Error Growth ◽  
Ensemble Spread ◽  
South Central

This research uses convection-allowing ensemble forecasts to address aspects of the predictability of an extreme rainfall event that occurred in south-central Texas on 25 May 2013, which was poorly predicted by operational and experimental numerical models and caused a flash flood in San Antonio that resulted in three fatalities. Most members of the ensemble had large errors in the location and magnitude of the heavy rainfall, but one member approximately reproduced the observed rainfall distribution. On a regional scale a flow-dependent diurnal cycle in ensemble spread growth is observed with large growth associated with afternoon convection, but the growth rate then reduced after convection dissipates the next morning rather than continuing to grow. Experiments that vary the magnitude of the perturbations to the initial and lateral boundary conditions reveal flow dependencies on the scales responsible for the ensemble growth and the degree to which practical (i.e., deficiencies in observing systems and numerical models) and intrinsic predictability limits (i.e., moist convective dynamic error growth) affect a particular convective event. Specifically, it was found that large-scale atmospheric forcing tends to dominate the ensemble spread evolution, but small-scale error growth can be of near-equal importance in certain convective scenarios where interaction across scales is prevalent and essential to the local precipitation processes. In a similar manner, aspects of the “upscale error growth” and “downscale error cascade” conceptual models are seen in the experiments, but neither completely explains the spread characteristics seen in the simulations.

scholarly journals Insights into Atmospheric Predictability through Global Convection-Permitting Model Simulations

2018 ◽  
Vol 75 (5) ◽  
pp. 1477-1497 ◽  
Author(s):  
Falko Judt
Keyword(s):  
Isotropic Turbulence ◽  
Weather Prediction ◽  
Baroclinic Instability ◽  
Complex Problem ◽  
Finite Limit ◽  
Wind Component ◽  
Moist Convection ◽  
Error Growth ◽  
Growth Regime ◽  
Atmospheric Predictability

Global convection-permitting models enable weather prediction from local to planetary scales and are therefore often expected to transform the weather prediction enterprise. This potential, however, depends on the predictability of the atmosphere, which was explored here through identical twin experiments using the Model for Prediction Across Scales. The simulations were produced on a quasi-uniform 4-km mesh, which allowed the illumination of error growth from convective to global scales. During the first two days, errors grew through moist convection and other mesoscale processes, and the character of the error growth resembled the case of [Formula: see text] turbulence. Between 2 and 13 days, errors grew with the background baroclinic instability, and the character of the error growth mirrored the case of [Formula: see text] turbulence. The existence of an error growth regime with properties similar to [Formula: see text] turbulence confirmed the radical idea of E. N. Lorenz that the atmosphere has a finite limit of predictability, no matter how small the initial error. The global-mean predictability limit of the troposphere was estimated here to be around 2–3 weeks, which is in agreement with previous work. However, scale-dependent predictability limits differed between the divergent and rotational wind component and between vertical levels, indicating that atmospheric predictability is a more complex problem than that of homogeneous, isotropic turbulence. The practical value of global cloud-resolving models is discussed in light of the various aspects of atmospheric predictability.

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