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Resolution dependence of deep convections in a global simulation from over 10-kilometer to sub-kilometer grid spacing

Resolution dependence of deep convections in a global simulation from over 10-kilometer to sub-kilometer grid spacing

It is impossible for a conventional GCM to represent the hierarchy of cloud organization from elemental con- vective clouds. Thus, comprehensive understanding, in- cluding the impact of organized clouds on general circulation, was not realistic. The new Nonhydrostatic Icosahedral Atmospheric Model (NICAM) (Tomita and Satoh 2004; Satoh et al. 2008; Satoh et al. 2014) is de- signed to conduct global simulation without cumulus parameterization. Previous studies have shown the useful- ness of the global nonhydrostatic model without cumulus parameterization for large-scale organized convective systems and disturbances, such as tropical cyclones (Fudeyasu et al. 2008; Yamaura et al. 2013; Miyamoto et al. 2014; Nakano et al. 2015), the Madden-Julian oscilla- tion (MJO) (Miura et al. 2007; Miyakawa et al. 2014), and monsoon onset (Kajikawa et al. 2015). However, in the early 2010s, the horizontal grid spacing with 3.5 km was limited. Although this resolution was the best possible in those days for qualitatively acceptable results for the cloud disturbance expression, the impact of higher resolution on model results was expected for the interaction between different spatiotemporal scale phenomena.
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Dealing with uncertainty: turbulent parameterizations and grid-spacing effects in numerical modelling of deep moist convective processes

Dealing with uncertainty: turbulent parameterizations and grid-spacing effects in numerical modelling of deep moist convective processes

A deep moist convective scenario, a supercell, in a simpli- fied atmospheric setting is studied by mean of high resolution numerical simulations with COSMO-Model. Different tur- bulent closures are used and their impacts on the space-time properties of convective fields are discussed. The convective- resolving solutions adopting Large Eddy Simulation (LES) turbulent closure converge with respect to the overall flow field structure when grid spacing is properly reduced. By comparing the rainfall fields produced by the model on larger scales with those at the convergence scales it’s possible to size up the uncertainty introduced by the modelling itself on the predicted ground effects in such simplified scenario.
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Analysis of the streamflow extremes and long term water balance  in the Liguria region of Italy using a cloud permitting grid  spacing reanalysis dataset

Analysis of the streamflow extremes and long term water balance in the Liguria region of Italy using a cloud permitting grid spacing reanalysis dataset

The main differences in the case of BC configuration are that observations lay always inside the confidence intervals and there is a better matching between simulated and ob- served sample curves. This is a significant finding; in fact the regional curve is an important ingredient to deal with quan- tile estimation in ungauged basins. It is important to highlight that the regional approach allows us to reduce the errors that can be found for single basins (Boni et al., 2007) and which are shown in Sect. 3.2; on the one hand, the normalization of each ADM series with its average reduces the effects of bias (due for example to a bad hydrological model calibration and other sources of error), but, on the other hand, the ADM time series of each outlet section (or grid point) is only a small subsample of the entire sample used to build the regional curve. It is in any case important to highlight that good re- sults in terms of the growth curve could be also partially due to the effect of error compensation.
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Observations and fine scale model simulations of gravity waves over Davis, East Antarctica (69°S, 78°E)

Observations and fine scale model simulations of gravity waves over Davis, East Antarctica (69°S, 78°E)

Winds associated with cyclones centered over the ocean interact with the coastal topography and katabatic winds which results in orographic wave production along the East Antarctic coast [Turner et al., 2009; Orr et al., 2014]. Smaller cyclones are particularly prominent around East Antarctica [Irving et al., 2010] but are poorly resolved by coarse-resolution global climate models, which have grid spacing of the order 100–200 km [Ohfuchi et al., 2004; Condron and Renfrew, 2013]. The coarse resolution of these models additionally results in an underrepresentation of local topographic variations, such as along the coastal margins, resulting in a generally poor representation of katabatic winds in this region [Bintanja et al., 2014]. Yet the interaction of the katabatic wind with winds from offshore cyclones drives orographic gravity wave production. The pres- ence and passage of Southern Ocean cyclones is a common occurrence throughout the year, although the seasonal cycle of their horizontal and vertical velocity variances in the lower troposphere indicates a peak in winter [Alexander and Murphy, 2015]. Orographic-related cloud forcing by these cyclones along coastal East Antarctica is not limited to this one case study examined here. Although not discussed in their text, these wave clouds are also clearly visible in satellite and simulation results of a wintertime cyclone passing north of Syowa station [Tomikawa et al., 2015].
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Steady non-ideal detonations in cylindrical sticks of expolsives

Steady non-ideal detonations in cylindrical sticks of expolsives

∆ is the numerical grid spacing in the reaction zone, points/lDDZ is the number of grid points between the shock and sonic loci along the charge axis, D is the detonation speed in the ax[r]

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Synoptic-scale conditions and convection-resolving hindcast experiments of a cold-season derecho on 3 January 2014 in western Europe

Synoptic-scale conditions and convection-resolving hindcast experiments of a cold-season derecho on 3 January 2014 in western Europe

Moreover, we showed that very high horizontal and verti- cal resolutions were necessary to reproduce the derecho in- tensity of the simulated convection. This is partially in con- trast to the case modelled by Ludwig et al. (2015), which could represent the strong convection embedded in the cold front from storm Kyrill with a coarser grid spacing of 2.8 km. However, a higher model resolution might not always be nec- essary for a good representation of DMCSs due to the strong case to case variability (Gatzen, 2018), but it might be needed for systems in some cases. Overall, the 3 January 2014 dere- cho event revealed the difficulty of forecasting cold-season convective windstorms when they are not associated with a well-defined synoptic-scale cold front, where upward motion is generally given per se. Therefore, convection-resolving en- semble prediction systems might be considered to improve the predictability of such low-probability, high-impact events in the future. Such systems are already employed by the DWD and MeteoSwiss. Future work will focus on a detailed analysis and high-resolution modelling of other DMCSs af- fecting western Europe based on the database established by Gatzen (2018) and on tests for the sensitivity to the ingredi- ents, particularly in terms of the physical mechanisms lead- ing to the large-scale ascent needed to initiate the event.
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Towards European-scale convection-resolving climate simulations with GPUs: a study with COSMO 4.19

Towards European-scale convection-resolving climate simulations with GPUs: a study with COSMO 4.19

While the convection-resolving approach shows very promising results, turbulent and convective motions are still under-resolved (Wyngaard, 2004). Grid spacings of O(1 km) are comparable to the size of the particularly energetic con- vective eddies in the planetary boundary layer (Zhou et al., 2014). At this resolution, shallow clouds still need to be pa- rameterized, and deep-convective clouds tend to be too large, too laminar, too vicious and too widely spaced apart (Clark et al., 2016). Using numerical simulations of an idealized squall line, Bryan et al. (2003) showed that a horizontal grid spacing of 250 m and below is needed to accurately predict the details of deep convection. Associated with this limita- tion is a high sensitivity of condensation processes with re- spect to grid spacing (Bryan and Morrison, 2012). However, Langhans et al. (2012) found that large-scale bulk properties of atmospheric convection, such as moisture and temperature tendencies, converge at a grid spacing of about 2–4 km. Their findings indicate that for real-case simulations, kilometer- scale resolution is often sufficient, provided the focus is on bulk properties and feedbacks rather than the structure of the convective clouds. While this type of convergence addresses the precipitation process within convective systems, Lang- hans et al. (2012) did not address issues related to radiative cloud feedbacks.
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Optimal Design of Unequal Conductor Spacing In Grounding Grid by Modern Computational Intelligent Techniques

Optimal Design of Unequal Conductor Spacing In Grounding Grid by Modern Computational Intelligent Techniques

In this paper optimal design of unequal grid spacing by modern computational intelligent techniques such as PSO and BAT algorithms are presented. These techniques are implemented to achieve one optimal unequal grid configuration among many feasible configurations. It has been found that depending on the grid mesh number grid has its own optimal compression ratio. Touch and step voltages are calculated for different compression ratio generated by the MATLAB program. Developed MATLAB software programs are extremely adoptable to find optimal compression ratio for given area of the grid and number of grid conductor.
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Climate Warming Impacts on Precipitation in Strongly and Weakly-Forced Composite-Based Simulations in the Southern United States.

Climate Warming Impacts on Precipitation in Strongly and Weakly-Forced Composite-Based Simulations in the Southern United States.

Figure 3.27 Precipitation (mm) difference using 12km grid spacing between the F72 (1200UTC Day 4) total weakly-forced event future simulation precipitation minus the F72 (1200UTC Day [r]

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Particle clustering and subclustering as a proxy for  mixing in geophysical flows

Particle clustering and subclustering as a proxy for mixing in geophysical flows

Figure 3 shows the different cumulative clusters, found at time 50–58 in the simulation, in different colors. By this time the double jet has undergone instability, and coherent vor- tices, as well as vorticity filaments, are formed (Fig. 1). As explained earlier, cumulative clusters are formed by particle– particle interactions that occur up to a particular time. The threshold separation for interaction between two particles is 40 % of the grid spacing in this case. We can see in this figure how different clusters merge during their evolutions. An example for this is the transition from time 52 to 54 in Fig. 3, where the green and magenta clusters merge into one magenta cluster. Two clusters merge into one when a particle from one cluster interacts with a particle from another clus- ter. A question that follows is the following: can new clusters take the place of old clusters when they merge? The answer is yes; we can easily show the formation of new clusters hav- ing size of the same order. We create another figure, Fig. 4, which is identical to Fig. 3, except for the threshold inter- action distance set to equal 20 % of the initial spatial grid spacing now. Comparing Figs. 3 and 4, we see that the clus- ters in the latter are smaller than those in the first. This is obvious because fewer particles interact with a threshold dis- tance equal to 20 % of the grid spacing. In particular, par- ticles in the clusters shown in Fig. 4 interact more strongly
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Impact of model improvements on 80 m wind speeds during the second Wind Forecast Improvement Project (WFIP2)

Impact of model improvements on 80 m wind speeds during the second Wind Forecast Improvement Project (WFIP2)

The biases of the 80 m wind speed also exhibit a diurnal cycle (Fig. 2). Again, Fig. 2a shows averages of the four reforecast periods and panels b–e display the four refore- cast periods separately. The diurnal trend of the bias in the HRRR CNT is evident in the red curves, with positive bi- ases at nighttime (stable atmospheric conditions), averaging 0.7 m s −1 , and negative values during daytime (unstable at- mospheric conditions), down to −0.4 m s −1 (panel a). The diurnal trend for the HRRR CNT is also clear for the four reforecast periods separately (panels b–e). The HRRR EXP reforecast runs (blue curves) tend to eliminate the diurnal trend in all reforecast periods, because of the differences in the treatment of boundary-layer turbulence in unstable and stable conditions, but lower the bias significantly, leading to a negative average value of ∼ − 0.6 m s −1 (panel a). A pos- sible reason for such behavior in the HRRR EXP runs can be found in the representation of drag due to SGS orogra- phy (Steeneveld et al., 2008; Tsiringakis et al., 2017) added to the HRRR physics suite. This new representation is only active in the HRRR but not in the HRRRNEST due to its finer grid spacing (Olson et al., 2019a). While the expected benefit of such improved representation of the drag is to de- crease the high wind speed bias in stable conditions often found in the HRRR, the detriment in this case seems to be too large a decrease in wind speed. The addition of wind turbine drag from the wind farm parameterization also contributed to the low wind speed bias but to a lesser degree. Due to the results found in this study and in other WFIP2 related studies, ways to revisit the treatment of the drag due to sub- grid-scale orography are under consideration. Finally, the di- urnal trends in the MAE and biases are smaller in the winter than in other seasons. This result could also be due to differ- ences in the treatment of boundary-layer turbulence in unsta- ble and stable conditions. Similar results were found by Berg et al. (2019) in their study of the sensitivity of winds simu- lated using the Mellor–Yamada–Nakanishi–Niino (MYNN) planetary boundary-layer parameterization in the Weather Research and Forecasting model.
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The relative importance of macrophysical and cloud albedo changes for aerosol-induced radiative effects in closed-cell stratocumulus: insight from the modelling of a case study

The relative importance of macrophysical and cloud albedo changes for aerosol-induced radiative effects in closed-cell stratocumulus: insight from the modelling of a case study

volved in marine stratocumulus. For example, Boutle and Abel (2012, hereafter BA12) showed that a mesoscale model with a 1 km grid spacing could capture closed-cell stratocu- mulus well, but they did not look at open-cell behaviour. Results from WRF-Chem at coarser grid spacings (9 km, Yang et al., 2011; 12 km, Saide et al., 2012; 14 km, George et al., 2013), where the representation of stratocumulus is re- liant on boundary layer parameterizations, have also shown reasonable agreement with observations. Whilst the coarser- resolution models may capture the general features of closed- cell stratocumulus, the simulation of open cells is likely to be more difficult owing to the smaller size of the precipitating and updraft regions and the small scales over which aerosol– cloud interactions occur. It is unclear whether the combina- tion of boundary layer parameterizations and microphysics schemes used in the coarser models will encapsulate the cor- rect response to aerosols.
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3D QSAR MIFs Studies on 3,5 substituted 1,4,2 dioxazoles Derivatives Using Open3DQSAR Tools

3D QSAR MIFs Studies on 3,5 substituted 1,4,2 dioxazoles Derivatives Using Open3DQSAR Tools

The MIFs based PLS calculation resulted in several models and among them, the final model selection is an important issue. To obtain the 3D-QSAR models, PLS analysis was performed using each of the steric and electrostatic MIFs alone and also in combination varying on 3D grid spacing. Seven types of model were produced on varying the grid spacing (see Table 2). All the models comparatively showed good statistical results except the

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Near-global climate simulation at 1 km resolution: establishing a performance baseline on 4888 GPUs with COSMO 5.0

Near-global climate simulation at 1 km resolution: establishing a performance baseline on 4888 GPUs with COSMO 5.0

Abstract. The best hope for reducing long-standing global climate model biases is by increasing resolution to the kilo- meter scale. Here we present results from an ultrahigh- resolution non-hydrostatic climate model for a near-global setup running on the full Piz Daint supercomputer on 4888 GPUs (graphics processing units). The dynamical core of the model has been completely rewritten using a domain- specific language (DSL) for performance portability across different hardware architectures. Physical parameterizations and diagnostics have been ported using compiler directives. To our knowledge this represents the first complete atmo- spheric model being run entirely on accelerators on this scale. At a grid spacing of 930 m (1.9 km), we achieve a simulation throughput of 0.043 (0.23) simulated years per day and an en- ergy consumption of 596 MWh per simulated year. Further- more, we propose a new memory usage efficiency (MUE) metric that considers how efficiently the memory bandwidth – the dominant bottleneck of climate codes – is being used.
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PubMedCentral-PMC5741097.pdf

PubMedCentral-PMC5741097.pdf

When modeling small displacements with finite differences the computational cost can become even more restrictive. Finite difference methods subdivide a grid into a rectangular mesh so the mesh size imposes a discrete limit on scatterer movement, i.e. a scatterer cannot appear in between mesh points. This is unlike many finite element simulations which can use an unstructured and adaptive grid [6]. Therefore, for a direct representation of displacement, the smallest unit of displacement is determined by the spatial grid size. Typical displacements in ultrasound elastography are on the order of microns [7], [8]. For example, to model a 1 micron displacement directly in 2D for a 3×7 cm field of view and a 2MHz emission would require 2.1 × 10 9 grid points. This is an unnecessarily refined grid and unnecessarily large computation because a grid spacing of λ/15, or 51 μm, would be sufficient to model an ultrasound pulse with a 100 dB dynamic range [4]. For this coarser grid spacing the number of points in the simulation is 8.0 × 10 5 , which is almost four orders of magnitude smaller. Thus a displacement method that can be implemented on a coarse grid would provide significant computational benefits.
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Planning spatial sampling of the soil from an uncertain reconnaissance variogram

Planning spatial sampling of the soil from an uncertain reconnaissance variogram

We can now summarize the practical implications of this analysis for further sampling of the soil to map uranium in this environment or comparable ones. The variogram is un- certain, which is not surprising given the relatively small sample size. Because of this, for any specified sample grid spacing, we cannot be sure about the expected prediction er- ror variance at the centre of a grid cell because this depends on variogram parameters about which we are uncertain. If a decision on sample density were based on the empirical variogram parameters alone, with no attention to their un- certainty, then these results show that the sample effort re- quired to ensure that prediction error variances are below some threshold may be markedly underestimated.
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Numerical Model Parameters for Simulation of Contaminant Transport

Numerical Model Parameters for Simulation of Contaminant Transport

Finite Difference is the most commonly used approach in numerical modelling. For most finite different models, the space and time co-ordinates are divided on a rectangular grid and model parameters (hydraulic conductivity, aquifer thickness) are specified for each model grid cell. Wang and Anderson 1 and Zheng and Bennett 2 provide a description of this method. The flow and transport equations are solved by direct approximation. The grid spacing represents the degree of accuracy of the model in representing lateral or vertical changes in the property values that describe the system. Finite difference methods have the advantage in being relatively simple to use, but have the disadvantage of not accurately representing irregular boundaries and it is also difficult to change the grid spacing to provide greater precision in areas of interest.
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Numerical Model Parameters for Simulation of Contaminant Transport

Numerical Model Parameters for Simulation of Contaminant Transport

Finite Difference is the most commonly used approach in numerical modelling. For most finite different models, the space and time co-ordinates are divided on a rectangular grid and model parameters (hydraulic conductivity, aquifer thickness) are specified for each model grid cell. Wang and Anderson 1 and Zheng and Bennett 2 provide a description of this method. The flow and transport equations are solved by direct approximation. The grid spacing represents the degree of accuracy of the model in representing lateral or vertical changes in the property values that describe the system. Finite difference methods have the advantage in being relatively simple to use, but have the disadvantage of not accurately representing irregular boundaries and it is also difficult to change the grid spacing to provide greater precision in areas of interest.
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An Examination of WRF/Chem: Physical Parameterizations, Nesting Options, and Grid Resolutions

An Examination of WRF/Chem: Physical Parameterizations, Nesting Options, and Grid Resolutions

The accurate representation of meteorological processes in the boundary and surface layers, as well as the interaction between the two, is crucial to the accurate simulation of meteorological variables and chemical species. This work focuses on several facets of simulating atmospheric processes: (1) planetary boundary layer (PBL) parameterizations, (2) land surface models (LSM), (3) horizontal grid spacing, and (4) one- and two-way nesting options. A modeling study utilizing the Weather Research and Forecast model with Chemistry (WRF/Chem) is conducted for a five-day period beginning 12 UTC (7AM CDT) 28 August through 6 UTC (1AM CDT) 2 September 2000. The modeling domain is centered over the Houston-Galveston area in Texas. Sensitivity studies for PBL and LSM options are conducted using a 12-km horizontal grid spacing. For analysis of horizontal grid spacing and nesting options, both 12- and 4-km horizontal grid spacings are used, each utilizing both one- and two-way nesting.
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Numerical Uncertainty in Simulation of Room Ventilation

Numerical Uncertainty in Simulation of Room Ventilation

Interest in improving the accuracy of computational methods, as opposed to determining the uncertainty of the numerical solution, predates the modern digital computer. Prior to the availability of computers, calculations were completed manually using mechanical calculators. This was evident in early work conducted by Richardson, which was first published in 1910 [6]. This century old work is considered to be the first documented iterative CFD solution [7]. The work that Richardson conducted is a method for obtaining a higher-order estimate of the final value to be determined as grid spacing approaches zero, from a lower-order discrete value [8]. This method is termed
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