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Journal articles on the topic 'Mesoscale'

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Author: Grafiati

Published: 4 June 2021

Last updated: 25 May 2024

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1

Canuto, V. M., M. S. Dubovikov, M. Luneva, C. A. Clayson, and A. Leboissetier. "Mixed layer mesoscales: a parameterization for OGCMs." Ocean Science Discussions 7, no. 2 (April 29, 2010): 873–917. http://dx.doi.org/10.5194/osd-7-873-2010.

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Abstract. We derive and assess a parameterization of the mixed layer vertical and horizontal mesoscale fluxes of an arbitrary tracer. The results, which are obtained by solving the mesoscale dynamic equations and contain no adjustable parameters, are expressed in terms of the large scale fields resolved by coarse resolution OGCMs (ocean global circulation models). The new model can be put in the right perspective by considering the following. Thus far, the lack of a mixed layer mesoscale model that naturally satisfies the required boundary condition (the vertical flux must vanish at the surface), was remedied by extending the stream function modeled for the adiabatic deep ocean into the mixed layer using an arbitrary tapering function chosen to enforce the required boundary condition. The present model renders the tapering schemes unnecessary for the vertical flux automatically vanishes at the ocean surface. The expressions we derive for the vertical and horizontal mesoscale fluxes are algebraic and should be used in conjunction with any of the available mesoscale models valid in the adiabatic deep ocean. We also discuss a new feature representing the effect of sub-mesoscales on mesoscales. It is shown that in the case of strong wind, one must add to the mean Eulerian velocity that enters the parameterization of the mesoscale fluxes a new term due to sub-mesoscales whose explicit form we work out. The assessment of the model results is as follows. First, previous eddy resolving results indicated a robust re-stratification effect by mesoscales; we show that the model result for the mesoscale vertical flux leads to re-stratification (its second z-derivative is negative) and that it is of the same order of magnitude but opposite sign of the vertical flux by small scale turbulence, leading to a large cancellation. Second, since mesoscales act as a source of the eddy kinetic energy, we compare the predicted surface values vs. the Topex-Poseidon. Third, we carry out an eddy resolving simulation and assess both z-profile and magnitude of the model vertical flux against the simulation data. The tests yield positive results. A more stratified mixed layer has implication for the oceanic absorption of heat and CO2, a feature whose implications on climate predictions we hope to explore in the future.

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2

Canuto, V. M., Y. Cheng, M. S. Dubovikov, A. M. Howard, and A. Leboissetier. "Parameterization of Mixed Layer and Deep-Ocean Mesoscales including Nonlinearity." Journal of Physical Oceanography 48, no. 3 (March 2018): 555–72. http://dx.doi.org/10.1175/jpo-d-16-0255.1.

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AbstractIn 2011, Chelton et al. carried out a comprehensive census of mesoscales using altimetry data and reached the following conclusions: “essentially all of the observed mesoscale features are nonlinear” and “mesoscales do not move with the mean velocity but with their own drift velocity,” which is “the most germane of all the nonlinear metrics.” Accounting for these results in a mesoscale parameterization presents conceptual and practical challenges since linear analysis is no longer usable and one needs a model of nonlinearity. A mesoscale parameterization is presented that has the following features: 1) it is based on the solutions of the nonlinear mesoscale dynamical equations, 2) it describes arbitrary tracers, 3) it includes adiabatic (A) and diabatic (D) regimes, 4) the eddy-induced velocity is the sum of a Gent and McWilliams (GM) term plus a new term representing the difference between drift and mean velocities, 5) the new term lowers the transfer of mean potential energy to mesoscales, 6) the isopycnal slopes are not as flat as in the GM case, 7) deep-ocean stratification is enhanced compared to previous parameterizations where being more weakly stratified allowed a large heat uptake that is not observed, 8) the strength of the Deacon cell is reduced. The numerical results are from a stand-alone ocean code with Coordinated Ocean-Ice Reference Experiment I (CORE-I) normal-year forcing.

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3

Barkan, Roy, Kraig B. Winters, and James C. McWilliams. "Stimulated Imbalance and the Enhancement of Eddy Kinetic Energy Dissipation by Internal Waves." Journal of Physical Oceanography 47, no. 1 (January 2017): 181–98. http://dx.doi.org/10.1175/jpo-d-16-0117.1.

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AbstractThe effects of internal waves (IWs), externally forced by high-frequency wind, on energy pathways are studied in submesoscale-resolving numerical simulations of an idealized wind-driven channel flow. Two processes are examined: the direct extraction of mesoscale energy by externally forced IWs followed by an IW forward energy cascade to dissipation and stimulated imbalance, a mechanism through which externally forced IWs trigger a forward mesoscale to submesoscale energy cascade to dissipation. This study finds that the frequency and wavenumber spectral slopes are shallower in solutions with high-frequency forcing compared to solutions without and that the volume-averaged interior kinetic energy dissipation rate increases tenfold. The ratio between the enhanced dissipation rate and the added high-frequency wind work is 1.3, demonstrating the significance of the IW-mediated forward cascades. Temporal-scale analysis of energy exchanges among low- (mesoscale), intermediate- (submesoscale), and high-frequency (IW) bands shows a corresponding increase in kinetic energy Ek and available potential energy APE transfers from mesoscales to submesoscales (stimulated imbalance) and mesoscales to IWs (direct extraction). Two direct extraction routes are identified: a mesoscale to IW Ek transfer and a mesoscale to IW APE transfer followed by an IW APE to IW Ek conversion. Spatial-scale analysis of eddy–IW interaction in solutions with high-frequency forcing shows an equivalent increase in forward Ek and APE transfers inside both anticyclones and cyclones.

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4

Garabato, Alberto C. Naveira, Xiaolong Yu, Jörn Callies, Roy Barkan, Kurt L. Polzin, Eleanor E. Frajka-Williams, Christian E. Buckingham, and Stephen M. Griffies. "Kinetic Energy Transfers between Mesoscale and Submesoscale Motions in the Open Ocean’s Upper Layers." Journal of Physical Oceanography 52, no. 1 (January 2022): 75–97. http://dx.doi.org/10.1175/jpo-d-21-0099.1.

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Abstract Mesoscale eddies contain the bulk of the ocean’s kinetic energy (KE), but fundamental questions remain on the cross-scale KE transfers linking eddy generation and dissipation. The role of submesoscale flows represents the key point of discussion, with contrasting views of submesoscales as either a source or a sink of mesoscale KE. Here, the first observational assessment of the annual cycle of the KE transfer between mesoscale and submesoscale motions is performed in the upper layers of a typical open-ocean region. Although these diagnostics have marginal statistical significance and should be regarded cautiously, they are physically plausible and can provide a valuable benchmark for model evaluation. The cross-scale KE transfer exhibits two distinct stages, whereby submesoscales energize mesoscales in winter and drain mesoscales in spring. Despite this seasonal reversal, an inverse KE cascade operates throughout the year across much of the mesoscale range. Our results are not incompatible with recent modeling investigations that place the headwaters of the inverse KE cascade at the submesoscale, and that rationalize the seasonality of mesoscale KE as an inverse cascade-mediated response to the generation of submesoscales in winter. However, our findings may challenge those investigations by suggesting that, in spring, a downscale KE transfer could dampen the inverse KE cascade. An exploratory appraisal of the dynamics governing mesoscale–submesoscale KE exchanges suggests that the upscale KE transfer in winter is underpinned by mixed layer baroclinic instabilities, and that the downscale KE transfer in spring is associated with frontogenesis. Current submesoscale-permitting ocean models may substantially understate this downscale KE transfer, due to the models’ muted representation of frontogenesis.

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5

Schubert, René, Jonathan Gula, Richard J. Greatbatch, Burkard Baschek, and Arne Biastoch. "The Submesoscale Kinetic Energy Cascade: Mesoscale Absorption of Submesoscale Mixed Layer Eddies and Frontal Downscale Fluxes." Journal of Physical Oceanography 50, no. 9 (September 1, 2020): 2573–89. http://dx.doi.org/10.1175/jpo-d-19-0311.1.

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AbstractMesoscale eddies can be strengthened by the absorption of submesoscale eddies resulting from mixed layer baroclinic instabilities. This is shown for mesoscale eddies in the Agulhas Current system by investigating the kinetic energy cascade with a spectral and a coarse-graining approach in two model simulations of the Agulhas region. One simulation resolves mixed layer baroclinic instabilities and one does not. When mixed layer baroclinic instabilities are included, the largest submesoscale near-surface fluxes occur in wintertime in regions of strong mesoscale activity for upscale as well as downscale directions. The forward cascade at the smallest resolved scales occurs mainly in frontogenetic regions in the upper 30 m of the water column. In the Agulhas ring path, the forward cascade changes to an inverse cascade at a typical scale of mixed layer eddies (15 km). At the same scale, the largest sources of the upscale flux occur. After the winter, the maximum of the upscale flux shifts to larger scales. Depending on the region, the kinetic energy reaches the mesoscales in spring or early summer aligned with the maximum of mesoscale kinetic energy. This indicates the importance of submesoscale flows for the mesoscale seasonal cycle. A case study shows that the underlying process is the mesoscale absorption of mixed layer eddies. When mixed layer baroclinic instabilities are not included in the simulation, the open-ocean upscale cascade in the Agulhas ring path is almost absent. This contributes to a 20% reduction of surface kinetic energy at mesoscales larger than 100 km when submesoscale dynamics are not resolved by the model.

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6

Gasset, Nicolas, Robert Benoit, and Christian Masson. "Implementing Large-Eddy Simulation Capability in a Compressible Mesoscale Model." Monthly Weather Review 142, no. 8 (August 1, 2014): 2733–50. http://dx.doi.org/10.1175/mwr-d-13-00257.1.

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Abstract The large size of modern wind turbines and wind farms triggers processes above the surface layer, which extend to the junction between microscales and mesoscales, and pushes the limits of existing approaches to predict the wind. The main objectives of this study are thus to introduce and evaluate an approach that will better account for physical processes within the atmospheric boundary layer (ABL), and allow for both microscale and mesoscale modeling. The proposed method, in which mathematical model and main numerical aspects are presented, combines a mesoscale approach with a large-eddy simulation (LES) model based on the Compressible Community Mesoscale Model (MC2). It is evaluated relying on a shear-driven ABL case allowing the authors to assess the model behavior at very high resolution as well as more specific numerical aspects such as the vertical discretization and time and space splitting of turbulence-related terms. The proposed LES-capable mesoscale model is shown to perform on par with other similar reference LES models, while being slightly more dissipative. A new vertical discretization of the turbulent processes eliminates a spurious numerical mode in the solution. Finally, the splitting of horizontal and vertical turbulence-related terms is shown to have no impact on the results of the test cases. It is thus demonstrated that the revised MC2 is suitable at both microscales and mesoscales, thus setting a strong foundation for future work.

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7

Dalaq, Ahmed S., and Shivakumar I. Ranganathan. "Invariants of mesoscale thermal conductivity and resistivity tensors in random checkerboards." Engineering Computations 32, no. 6 (August 3, 2015): 1601–18. http://dx.doi.org/10.1108/ec-08-2014-0162.

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Purpose – The purpose of this paper is to study the statistics of thermal conductivity and resistivity tensors in two-phase random checkerboard microstructures at finite mesoscales. Design/methodology/approach – Microstructures at finite scales are generated by randomly sampling an infinite checkerboard at 50 percent nominal fraction. Boundary conditions that stem from the Hill-Mandel homogenization condition are then applied as thermal loadings on these microstructures. Findings – It is observed that the thermal response of the sampled microstructures is in general anisotropic at finite mesoscales. Based on 1,728 boundary value problems, the statistics of the tensor invariants (trace and determinant) are obtained as a function of material contrast, mesoscale and applied boundary conditions. The histograms as well as the moments (mean, variance, skewness and kurtosis) of the invariants are computed and discussed. A simple analytical form for the variance of the trace of mesoscale conductivity tensor is proposed as a function of individual phase conductivities and the mesoscale. Originality/value – A rigorous methodology to determine the evolution of the invariants of thermal conductivity (and resistivity) tensors across a variety of length scales (microscale to macroscale) is presented. The objective is to enable setting up of constitutive equations applicable to heat conduction that are valid across all length scales.

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8

Lindborg, Erik. "Two Comments on the Surface Quasigeostrophic Model for the Atmospheric Energy Spectrum." Journal of the Atmospheric Sciences 66, no. 4 (April 1, 2009): 1069–72. http://dx.doi.org/10.1175/2008jas2972.1.

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Abstract The horizontal wavenumber spectra of wind and temperature in the upper troposphere and lower stratosphere display a narrow k−3 range at scales on the order of 1000 km and a broad k−5/3 range at mesoscales on the order of 1 to 500 km. Recently, Tulloch and Smith suggested that a surface quasigeostrophic (SQG) turbulence model can explain the observed spectra. Here, it is first argued that the mesoscale spectra are not likely to be explained by any quasigeostrophic model because the Rossby number corresponding to the mesoscale dynamics is on the order of unity or larger. Then it is argued that the SQG model in particular cannot explain the observations because its mesoscale spectrum displays a k−5/3 dependence only in a very thin layer just below the tropopause. The thickness of this layer can be estimated to be of the order of 10 m, whereas aircraft measurements are typically performed several hundred meters away from the tropopause.

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9

Wang, Jin, Brandon J. Bethel, Changming Dong, Chunhui Li, and Yuhan Cao. "Numerical Simulation and Observational Data Analysis of Mesoscale Eddy Effects on Surface Waves in the South China Sea." Remote Sensing 14, no. 6 (March 18, 2022): 1463. http://dx.doi.org/10.3390/rs14061463.

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Surface current velocities of mesoscale eddies have a unique annular structure, which can inevitably influence surface wave properties and energy distribution. Sensitivity experiments of ideal mesoscale eddies on waves were carried out by the Simulating WAves Nearshore (SWAN) wave model to investigate these influences. In addition, China–France Oceanography SATellite Surface Wave Investigation and Monitoring (CFOSAT-SWIM) observational data of a large warm-cored eddy in the South China Sea (SCS) during the period of October–November 2019 were used to validate the influence of mesoscale eddies on waves. The results illustrated that mesoscale eddies can alter wave properties (wave height, period, and steepness) by 20–30%. Moreover, wave direction could also be modified by 30°–40°. The current effect on waves (CEW) was more noticeable with strong currents and weak winds, and was governed by wave age and the ratio of wave group velocity to current velocity. Wave spectra clearly indicated that current-induced variability in wave energy distribution happens on a spatial scale of 5–90 km (i.e., the sub- and mesoscales). Through comparing the difference of wave energy on both sides of an eddy perpendicular to the wave propagation direction in an eddy, a simple way to trace the footprints of waves on eddies was devised.

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10

Delman, Andrew, and Tong Lee. "A new method to assess mesoscale contributions to meridional heat transport in the North Atlantic Ocean." Ocean Science 16, no. 4 (August 27, 2020): 979–95. http://dx.doi.org/10.5194/os-16-979-2020.

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Abstract. The meridional heat transport (MHT) in the North Atlantic is critically important to climate variability and the global overturning circulation. A wide range of ocean processes contribute to North Atlantic MHT, ranging from basin-scale overturning and gyre motions to mesoscale instabilities (such as eddies). However, previous analyses of “eddy” MHT in the region have mostly focused on the contributions of time-variable velocity and temperature, rather than considering the association of MHT with distinct spatial scales within the basin. In this study, a zonal spatial-scale decomposition separates large-scale from mesoscale velocity and temperature contributions to MHT, in order to characterize the physical processes driving MHT. Using this approach, we found that the mesoscale contributions to the time-mean and interannual/decadal (ID) variability of MHT in the latitude range 39–45∘ N are larger than large-scale horizontal contributions, though smaller than the overturning contributions. Considering the 40∘ N transect as a case study, large-scale ID variability is mostly generated close to the western boundary. In contrast, most ID MHT variability associated with mesoscales originates in two distinct regions: a western boundary region (70–60∘ W) associated with 1- to 4-year interannual variations and an interior region (50–35∘ W) associated with decadal variations. Surface eddy kinetic energy is not a reliable indicator of high MHT episodes, but the large-scale meridional temperature gradient is an important factor, by influencing the local temperature variance as well as the local correlation of velocity and temperature. Most of the mesoscale contribution to MHT at 40∘ N is associated with transient and propagating processes, but stationary mesoscale structures explain most of the mesoscale MHT south of the Gulf Stream separation, highlighting the differences between the temporal and spatial decomposition of meridional temperature fluxes.

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11

Gao, Yu, Igor Kamenkovich, Natalie Perlin, and Benjamin Kirtman. "Oceanic Advection Controls Mesoscale Mixed Layer Heat Budget and Air–Sea Heat Exchange in the Southern Ocean." Journal of Physical Oceanography 52, no. 4 (April 2022): 537–55. http://dx.doi.org/10.1175/jpo-d-21-0063.1.

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Abstract We analyze the role of mesoscale heat advection in a mixed layer (ML) heat budget, using a regional high-resolution coupled model with realistic atmospheric forcing and an idealized ocean component. The model represents two regions in the Southern Ocean, one with strong ocean currents and the other with weak ocean currents. We conclude that heat advection by oceanic currents creates mesoscale anomalies in sea surface temperature (SST), while the atmospheric turbulent heat fluxes dampen these SST anomalies. This relationship depends on the spatial scale, the strength of the currents, and the mixed layer depth (MLD). At the oceanic mesoscale, there is a positive correlation between the advection and SST anomalies, especially when the currents are strong overall. For large-scale zonal anomalies, the ML-integrated advection determines the heating/cooling of the ML, while the SST anomalies tend to be larger in size than the advection and the spatial correlation between these two fields is weak. The effects of atmospheric forcing on the ocean are modulated by the MLD variability. The significance of Ekman advection and diabatic heating is secondary to geostrophic advection except in summer when the MLD is shallow. This study links heat advection, SST anomalies, and air–sea heat fluxes at ocean mesoscales, and emphasizes the overall dominance of intrinsic oceanic variability in mesoscale air–sea heat exchange in the Southern Ocean.

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12

Callies, Jörn, Oliver Bühler, and Raffaele Ferrari. "The Dynamics of Mesoscale Winds in the Upper Troposphere and Lower Stratosphere." Journal of the Atmospheric Sciences 73, no. 12 (November 23, 2016): 4853–72. http://dx.doi.org/10.1175/jas-d-16-0108.1.

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Abstract Spectral analysis is applied to infer the dynamics of mesoscale winds from aircraft observations in the upper troposphere and lower stratosphere. Two datasets are analyzed: one collected aboard commercial aircraft and one collected using a dedicated research aircraft. A recently developed wave–vortex decomposition is used to test the observations’ consistency with linear inertia–gravity wave dynamics. The decomposition method is shown to be robust in the vicinity of the tropopause if flight tracks vary sufficiently in altitude. For the lower stratosphere, the decompositions of both datasets confirm a recent result that mesoscale winds are consistent with the polarization and dispersion relations of inertia–gravity waves. For the upper troposphere, however, the two datasets disagree: only the research aircraft data indicate consistency with linear wave dynamics at mesoscales. The source of the inconsistency is a difference in mesoscale variance of the measured along-track wind component. To further test the observed flow’s consistency with linear wave dynamics, the ratio between tropospheric and stratospheric mesoscale energy levels is compared to a simple model of upward-propagating waves that are partially reflected at the tropopause. For both datasets, the observed energy ratio is roughly consistent with the simple wave model, but wave frequencies diagnosed from the data draw into question the applicability of the monochromatic theory at wavelengths smaller than 10 km.

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13

Hanrath, Tobias. "Mesoscale metamorphosis." Nature Materials 19, no. 1 (October 14, 2019): 2–3. http://dx.doi.org/10.1038/s41563-019-0515-0.

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14

AOYAGI, Takeshi, and Masao DOI. "Mesoscale Simulation." Kobunshi 48, no. 5 (1999): 316–19. http://dx.doi.org/10.1295/kobunshi.48.316.

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15

Orlanski, Isidro. "Mesoscale Dynamics." Eos, Transactions American Geophysical Union 89, no. 42 (2008): 408. http://dx.doi.org/10.1029/2008eo420004.

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16

Yap, May Lin, Xiaowei Wang, Geoffrey A. Pietersz, and Karlheinz Peter. "Mesoscale Nanoparticles." Hypertension 71, no. 1 (January 2018): 61–63. http://dx.doi.org/10.1161/hypertensionaha.117.09944.

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17

Zeng, Hongkui. "Mesoscale connectomics." Current Opinion in Neurobiology 50 (June 2018): 154–62. http://dx.doi.org/10.1016/j.conb.2018.03.003.

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18

Hoffmann, Axel, and Helmut Schultheiß. "Mesoscale magnetism." Current Opinion in Solid State and Materials Science 19, no. 4 (August 2015): 253–63. http://dx.doi.org/10.1016/j.cossms.2014.11.004.

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19

Jacobs, G. A., C. N. Barron, and R. C. Rhodes. "Mesoscale characteristics." Journal of Geophysical Research: Oceans 106, no. C9 (September 15, 2001): 19581–95. http://dx.doi.org/10.1029/2000jc000669.

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20

Nicolaides, David. "Mesoscale Modelling." Molecular Simulation 26, no. 1 (January 2001): 51–72. http://dx.doi.org/10.1080/08927020108024200.

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21

Canuto, V. M., and M. S. Dubovikov. "Derivation and assessment of a mixed layer sub-mesoscale model." Ocean Science Discussions 6, no. 3 (September 17, 2009): 2157–92. http://dx.doi.org/10.5194/osd-6-2157-2009.

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Abstract. Present studies of mixed layer sub-mesoscales rely primarily on high resolution numerical simulations. Only few of these studies have attempted to parameterize the ensuing buoyancy submesoscale fluxes in terms of the resolved fields so that they can be used in OGCMs (ocean circulation models) that do not resolve sub-mesoscales. In reality, OGCMs used in climate studies include a carbon-cycle which also requires the flux of a passive tracer. The goal of this work is to derive and assess a parameterization of the submesoscale vertical flux of an arbitrary tracer in terms of the resolved fields. The parameterization is obtained by first solving the dynamic equations governing the velocity and tracer fields that describe sub-mesoscales and then constructing second-order moments such as the tracer fluxes. A key ingredient of the present approach is the modeling of the non-linear terms that enter the dynamic equations of the velocity and tracer fields, a problem that we discuss in two Appendices. The derivation of the sub-mesoscale tracer vertical flux is analytical and can be followed in detail since no additional information is required. The external forcing includes both baroclinic instabilities and wind stresses. We compare the model results with data from sub-mesoscale resolving simulations available in the literature which are of two kinds, one with no wind (baroclinic instabilities only) and the other with both baroclinic instabilities and wind. In both cases, the model results reproduce the simulation data satisfactorily.

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22

Sun, Y. Qiang, Richard Rotunno, and Fuqing Zhang. "Contributions of Moist Convection and Internal Gravity Waves to Building the Atmospheric −5/3 Kinetic Energy Spectra." Journal of the Atmospheric Sciences 74, no. 1 (January 1, 2017): 185–201. http://dx.doi.org/10.1175/jas-d-16-0097.1.

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Abstract With high-resolution mesoscale model simulations, the authors have confirmed a recent study demonstrating that convective systems, triggered in a horizontally homogeneous environment, are able to generate a background mesoscale kinetic energy spectrum with a slope close to −5/3, which is the observed value for the kinetic energy spectrum at mesoscales. This shallow slope can be identified at almost all height levels from the lower troposphere to the lower stratosphere in the simulations, implying a strong connection between different vertical levels. The present study also computes the spectral kinetic energy budget for these simulations to further analyze the processes associated with the creation of the spectrum. The buoyancy production generated by moist convection, while mainly injecting energy in the upper troposphere at small scales, could also contribute at larger scales, possibly as a result of the organization of convective cells into mesoscale convective systems. This latter injected energy is then transported by energy fluxes (due to gravity waves and/or convection) both upward and downward. Nonlinear interactions, associated with the velocity advection term, finally help build the approximate −5/3 slope through upscale and/or downscale propagation at all levels.

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23

Michelson, Daniel B., Valentin I. Foltescu, Lars Häggmark, and Bo Lindgren. "MESAN Mesoscale analysis of precipitation." Meteorologische Zeitschrift 9, no. 2 (July 14, 2000): 85–96. http://dx.doi.org/10.1127/metz/9/2000/85.

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24

Yi, Daling Li, and Peng Wang. "Global Wavenumber Spectra of Sea Surface Salinity in the Mesoscale Range Using Satellite Observations." Remote Sensing 16, no. 10 (May 15, 2024): 1753. http://dx.doi.org/10.3390/rs16101753.

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Sea surface salinity (SSS) variability at mesoscales has become an important research topic in recent decades, thanks to satellite missions enabling observations of SSS with global capacity and mesoscale resolution. Here, we analyze the near-global data of the Aquarius/SAC-D along-track SSS, focusing on the slopes of SSS variance spectra in the mesoscale range from 180 to 430 km. In the vast extratropics, the spectral slope is close to −2, indicating a dynamical regime for the inverse cascade of depth-integrated energy identified by the surface quasi-geostrophic theory. However, the spectral slopes in regions near the mouths of the largest rivers are steeper than −2, reaching −3, possibly due to the large river freshwater flux. In addition, data from high-resolution thermosalinograph are used to validate satellite measurements and show good consistency in terms of SSS variance spectral slopes.

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25

Avsarkisov, Victor, Erich Becker, and Toralf Renkwitz. "Turbulent Parameters in the Middle Atmosphere: Theoretical Estimates Deduced from a Gravity Wave–Resolving General Circulation Model." Journal of the Atmospheric Sciences 79, no. 4 (April 2022): 933–52. http://dx.doi.org/10.1175/jas-d-21-0005.1.

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Abstract We present a scaling analysis for the stratified turbulent and small-scale turbulent regimes of atmospheric flow with emphasis on the mesosphere. We distinguish rotating-stratified macroturbulence turbulence (SMT), stratified turbulence (ST), and small-scale isotropic Kolmogorov turbulence (KT), and we specify the length and time scales and the characteristic velocities for these regimes. It is shown that the buoyancy scale (Lb) and the Ozmidov scale (Lo) are the main parameters that describe the transition from SMT to KT. We employ the buoyancy Reynolds number and horizontal Froude number to characterize ST and KT in the mesosphere. This theory is applied to simulation results from a high-resolution general circulation model with a Smagorinsky-type turbulent diffusion scheme for the subgrid-scale parameterization. The model allows us to derive the turbulent root-mean-square (rms) velocity in the KT regime. It is found that the turbulent RMS velocity has a single maximum in summer and a double maximum in winter months. The secondary maximum in the winter MLT we associate with a secondary gravity wave–breaking phenomenon. The turbulent rms velocity results from the model agree well with full correlation analyses based on MF-radar measurements. A new scaling for the mesoscale horizontal velocity based on the idea of direct energy cascade in mesoscales is proposed. The latter findings for mesoscale and small-scale characteristic velocities support the idea proposed in this research that mesoscale and small-scale dynamics in the mesosphere are governed by SMT, ST, and KT in the statistical average. Significance Statement Mesoscale dynamics in the middle atmosphere, which consists of atmospheric turbulence and gravity waves, remains a complex problem for atmospheric physics and climate studies. Due to its high nonlinearity, the mesoscale dynamics together with the small-scale turbulence is the primary source of uncertainties and biases in high-altitude general circulation models (GCM) in the middle atmosphere. We use the stratified turbulence theory and the gravity wave–resolving GCM to characterize different scaling regimes and to define various length, time, and velocity scales, that are relevant for the mesoscale and small-scale dynamical regimes. Our results highlight the importance of stratified turbulence in the mesosphere and lower-thermosphere region.

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Dosta, Maksym, Kolja Jarolin, and Pavel Gurikov. "Modelling of Mechanical Behavior of Biopolymer Alginate Aerogels Using the Bonded-Particle Model." Molecules 24, no. 14 (July 12, 2019): 2543. http://dx.doi.org/10.3390/molecules24142543.

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A novel mesoscale modelling approach for the investigation of mechanical properties of alginate aerogels is proposed. This method is based on the discrete element method and bonded-particle model. The nanostructure of aerogel is not directly considered, instead the highly porous structure of aerogels is represented on the mesoscale as a set of solid particles connected by solid bonds. To describe the rheological material behavior, a new elastic-plastic functional model for the solids bonds has been developed. This model has been derived based on the self-similarity principle for the material behavior on the macro and mesoscales. To analyze the effectiveness of the proposed method, the behavior of alginate aerogels with different crosslinking degrees (calcium content) was analyzed. The comparison between experimental and numerical results has shown that the proposed approach can be effectively used to predict the mechanical behavior of aerogels on the macroscale.

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27

Ubelmann, Clément, Loren Carrere, Chloé Durand, Gérald Dibarboure, Yannice Faugère, Maxime Ballarotta, Frédéric Briol, and Florent Lyard. "Simultaneous estimation of ocean mesoscale and coherent internal tide sea surface height signatures from the global altimetry record." Ocean Science 18, no. 2 (April 8, 2022): 469–81. http://dx.doi.org/10.5194/os-18-469-2022.

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Abstract. This study proposes an approach to estimate the ocean sea surface height signature of coherent internal tides from a 25-year along-track altimetry record, with a single inversion over time, resolving both internal tide contributions and mesoscale eddy variability. The inversion is performed on a reduced-order basis of topography and practically achieved with a conjugate gradient. The particularity of this approach is to mitigate the potential aliasing effects between mesoscales and internal tide estimation from the uneven altimetry sampling (observing the sum of these components) by accounting for their statistics simultaneously, while other methods generally use a prior mesoscale. The four major tidal components are considered (M2, K1, S2, O1) over the period 1992–2017 on a global configuration. From the solution, we use altimetry data after 2017 for independent validation in order to evaluate the performance of the simultaneous inversion and compare it with an existing model.

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28

Fritsch, J. Michael. "Modification of Mesoscale Convective Weather Systems." Meteorological Monographs 43 (December 1, 1986): 77–86. http://dx.doi.org/10.1175/0065-9401-21.43.77.

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Abstract Modification of mesoscale convective weather systems through ice-phase seeding is briefly reviewed. a simple mathematical framework for estimating the likely mesoscale response to convective cloud modification is presented, and previous mesoscale modification hypotheses are discussed in the context of this mathematical framework. Some basic differences between cloud-scale and mesoscale modification hypotheses are also discussed. Numerical model experiments to test the mesoscale sensitivity of convective weather systems are reviewed, and several focal points for identifying mesoscale modification potential are presented.

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29

Raney, Jordan R., and Jennifer A. Lewis. "Printing mesoscale architectures." MRS Bulletin 40, no. 11 (November 2015): 943–50. http://dx.doi.org/10.1557/mrs.2015.235.

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30

Rundquist, Bradley, John Harrington, and Douglas Goodin. "Mesoscale Satellite Bioclimatology." Professional Geographer 52, no. 2 (May 2000): 331–44. http://dx.doi.org/10.1111/0033-0124.00229.

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31

Horn, Diane P. "Mesoscale beach processes." Progress in Physical Geography: Earth and Environment 26, no. 2 (June 2002): 271–89. http://dx.doi.org/10.1191/0309133302pp336pr.

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32

Szuromi, P. D. "CHEMISTRY: Mesoscale Metallocycles." Science 304, no. 5678 (June 18, 2004): 1721a. http://dx.doi.org/10.1126/science.304.5678.1721a.

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33

Chelton, Dudley. "Mesoscale eddy effects." Nature Geoscience 6, no. 8 (July 30, 2013): 594–95. http://dx.doi.org/10.1038/ngeo1906.

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34

Steenson, Molly Wright. "Microworld and mesoscale." Interactions 22, no. 4 (June 25, 2015): 58–60. http://dx.doi.org/10.1145/2786024.

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35

Jacobi, Anthony. "A Mesoscale World." HVAC&R Research 8, no. 2 (April 1, 2002): 133–34. http://dx.doi.org/10.1080/10789669.2002.10391432.

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36

Fritsch, J. M., and G. S. Forbes. "Mesoscale Convective Systems." Meteorological Monographs 50 (November 1, 2001): 323–58. http://dx.doi.org/10.1175/0065-9401-28.50.323.

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37

Li, Ruoning, and Yongfeng Wang. "Mesoscale coordination constructs." Nature Chemistry 12, no. 5 (April 28, 2020): 431–32. http://dx.doi.org/10.1038/s41557-020-0461-0.

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38

Canuto, V. M., and M. S. Dubovikov. "Modeling mesoscale eddies." Ocean Modelling 8, no. 1-2 (January 2005): 1–30. http://dx.doi.org/10.1016/j.ocemod.2003.11.003.

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39

PZ. "Mesoscale meteorological modeling." Environmental Software 1, no. 1 (June 1986): 60. http://dx.doi.org/10.1016/0266-9838(86)90039-0.

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40

Warner, Thomas T. "Mesoscale atmospheric modeling." Earth-Science Reviews 26, no. 1-3 (January 1989): 221–51. http://dx.doi.org/10.1016/0012-8252(89)90023-8.

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41

Barber, Dylan M., Alfred J. Crosby, and Todd Emrick. "Mesoscale Block Copolymers." Advanced Materials 30, no. 13 (January 30, 2018): 1706118. http://dx.doi.org/10.1002/adma.201706118.

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42

Bykov, A. V., and A. N. Shikhov. "Mesoscale convective systems forecast using global and mesoscale atmospheric models." Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa 15, no. 2 (2018): 213–24. http://dx.doi.org/10.21046/2070-7401-2018-15-2-213-224.

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43

Browning, K. A. "The mesoscale data base and its use in mesoscale forecasting." Quarterly Journal of the Royal Meteorological Society 115, no. 488 (July 1989): 717–62. http://dx.doi.org/10.1002/qj.49711548802.

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44

Li, Shengwei, Heping Xie, Ru Zhang, Mingzhong Gao, Zetian Zhang, Guo Li, and Jing Xie. "A Multiscale Simulation Method and Its Application to Determine the Mechanical Behavior of Heterogeneous Geomaterials." Advances in Materials Science and Engineering 2017 (2017): 1–12. http://dx.doi.org/10.1155/2017/9529602.

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To study the micro/mesomechanical behaviors of heterogeneous geomaterials, a multiscale simulation method that combines molecular simulation at the microscale, a mesoscale analysis of polished slices, and finite element numerical simulation is proposed. By processing the mesostructure images obtained from analyzing the polished slices of heterogeneous geomaterials and mapping them onto finite element meshes, a numerical model that more accurately reflects the mesostructures of heterogeneous geomaterials was established by combining the results with the microscale mechanical properties of geomaterials obtained from the molecular simulation. This model was then used to analyze the mechanical behaviors of heterogeneous materials. Because kernstone is a typical heterogeneous material that comprises many types of mineral crystals, it was used for the micro/mesoscale mechanical behavior analysis in this paper using the proposed method. The results suggest that the proposed method can be used to accurately and effectively study the mechanical behaviors of heterogeneous geomaterials at the micro/mesoscales.

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45

Jiang, Wuyi, Jiawei Xu, Yongli Cai, and Zhiyong Liu. "Ecological Land Adaptive Planning in Macroscale, Mesoscale, and Microscale of Shanghai." Sustainability 12, no. 5 (March 10, 2020): 2142. http://dx.doi.org/10.3390/su12052142.

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The urban ecosystems in China have been compromised during the process of urbanization. The declining services of ecological lands have hindered the sustainable development of cities and the current ecological land management (regulations, rules, and laws) in China cannot meet the demand of future development. In this paper, a new multiscale systematic adaptive ecological land planning method is proposed. Shanghai, a typical mega-city in China, was chosen as the research area. To scientifically and adaptively manage ecological land, downscale management was used and macroscales (city), mesoscales (town), and microscales (community) were chosen. In different scales, different indicators were chosen as evaluation criteria to evaluate the services of the lands. At the mesoscale, habitat quality, carbon sequestration, water conservation, and soil fertility maintenance were chosen. At the mesoscale, habitat quality, carbon sequestration capacity, water production service and food supply were chosen as the evaluation criteria. These indicators are used to evaluate the importance levels of corresponding areas. Based on the importance levels of macroscales and mesoscales, three different scenarios with different targets of Changtian Community were proposed. All three scenarios were judged by stakeholders (residents and managers) of the community and a final scenario was proposed to meet all the requirements. This research not only provides theoretical reference and technical support for ecological land management in different scales of Shanghai, but also provides a new method of adaptive ecological land planning in megacities.

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46

Sun, Shuangwen, Yue Fang, Yongcan Zu, Baochao Liu, Tana, and Azizan Abu Samah. "Seasonal Characteristics of Mesoscale Coupling between the Sea Surface Temperature and Wind Speed in the South China Sea." Journal of Climate 33, no. 2 (January 15, 2020): 625–38. http://dx.doi.org/10.1175/jcli-d-19-0392.1.

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AbstractThe seasonal characteristics of the mesoscale coupling between sea surface temperature (SST) and wind speed in the South China Sea (SCS) are investigated using satellite observations. The correlation between mesoscale SST and wind speed is highest in winter. The region of high correlation is located in the central SCS in the early stage of the winter monsoon. It then gradually shifts northward in the following months and is located in the northern SCS in the late stage of the winter monsoon. In summer, the region of high correlation is located to the east of the Vietnam coast. Two controlling factors are crucial in mesoscale SST–wind speed coupling: the mesoscale SST gradient and the wind speed steadiness. The mesoscale SST gradient is fundamental in mesoscale coupling, but a steady wind speed also plays an important role. The development of significant coupling depends on the relative contribution of these two factors. For regions where the mesoscale SST gradient is relatively weak, a very steady wind field is required for detectable mesoscale coupling to occur, whereas in regions where the wind speed is less steady, a stronger mesoscale SST gradient must exist for coupling to develop. Variations in wind speed steadiness can well explain the inconsistency between the spatial patterns of the mesoscale SST gradient and the intensity of coupling. The wind speed steadiness is a good factor with which to evaluate the constraining effect of the background wind field variability on the development of mesoscale coupling in the SCS.

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47

Jiang, Bin, Ji Guang Song, Song Tao Wang, Bo Chen, and Xuan Chi Liu. "Model of Intrinsic/Extrinsic about the Safety for High Speed Milling Tools on Mesoscale." Advanced Materials Research 500 (April 2012): 198–204. http://dx.doi.org/10.4028/www.scientific.net/amr.500.198.

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The article is about the safety for high speed milling tools between macroscopic and mesoscale, making some analysis about the relationship between damage of cutting tools and its components and mesoscale movement, the damage of cutting tools and its components is known. With the boundary conditions of material force damage, using the material design software named MAPS to do molecular dynamics simulation, the simulation is about mesoscale state in different stress, Make sure the various mesoscale movement on stress response rate, the model of intrinsic/extrinsic about the safety for high speed milling tools on a mesoscale is established. Clear the value of intrinsic/extrinsic parameters and mesoscale movement on stress response rate. The regular pattern between damage of cutting tools and its components and mesoscale movement, which could help us to design tools, choose materials of tools and determine cutting parameters.

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48

Zhang, Fuqing, Andrew M. Odins, and John W. Nielsen-Gammon. "Mesoscale Predictability of an Extreme Warm-Season Precipitation Event." Weather and Forecasting 21, no. 2 (April 1, 2006): 149–66. http://dx.doi.org/10.1175/waf909.1.

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Abstract A mesoscale model is used to investigate the mesoscale predictability of an extreme precipitation event over central Texas on 29 June 2002 that lasted through 7 July 2002. Both the intrinsic and practical aspects of warm-season predictability, especially quantitative precipitation forecasts up to 36 h, were explored through experiments with various grid resolutions, initial and boundary conditions, physics parameterization schemes, and the addition of small-scale, small-amplitude random initial errors. It is found that the high-resolution convective-resolving simulations (with grid spacing down to 3.3 km) do not produce the best simulation or forecast. It was also found that both the realistic initial condition uncertainty and model errors can result in large forecast errors for this warm-season flooding event. Thus, practically, there is room to gain higher forecast accuracy through improving the initial analysis with better data assimilation techniques or enhanced observations, and through improving the forecast model with better-resolved or -parameterized physical processes. However, even if a perfect forecast model is used, small-scale, small-amplitude initial errors, such as those in the form of undetectable random noise, can grow rapidly and subsequently contaminate the short-term deterministic mesoscale forecast within 36 h. This rapid error growth is caused by moist convection. The limited deterministic predictability of such a heavy precipitation event, both practically and intrinsically, illustrates the need for probabilistic forecasts at the mesoscales.

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49

Weaver, Christopher P. "Coupling between Large-Scale Atmospheric Processes and Mesoscale Land–Atmosphere Interactions in the U.S. Southern Great Plains during Summer. Part II: Mean Impacts of the Mesoscale." Journal of Hydrometeorology 5, no. 6 (December 1, 2004): 1247–58. http://dx.doi.org/10.1175/jhm-397.1.

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Abstract This is Part II of a two-part study of mesoscale land–atmosphere interactions in the summertime U.S. Southern Great Plains. Part I focused on case studies drawn from monthlong (July 1995–97), high-resolution Regional Atmospheric Modeling System (RAMS) simulations carried out to investigate these interactions. These case studies were chosen to highlight key features of the lower-tropospheric mesoscale circulations that frequently arise in this region and season due to mesoscale heterogeneity in the surface fluxes. In this paper, Part II, the RAMS-simulated mesoscale dynamical processes described in the Part I case studies are examined from a domain-averaged perspective to assess their importance in the overall regional hydrometeorology. The spatial statistics of key simulated mesoscale variables—for example, vertical velocity and the vertical flux of water vapor—are quantified here. Composite averages of the mesoscale and large-scale-mean variables over different meteorological or dynamical regimes are also calculated. The main finding is that, during dry periods, or similarly, during periods characterized by large-scale-mean subsidence, the characteristic signature of surface-heterogeneity-forced mesoscale circulations, including enhanced vertical motion variability and enhanced mesoscale fluxes in the lowest few kilometers of the atmosphere, consistently emerges. Furthermore, the impact of these mesoscale circulations is nonnegligible compared to the large-scale dynamics at domain-averaged (200 km × 200 km) spatial scales and weekly to monthly time scales. These findings support the hypothesis that the land– atmosphere interactions associated with mesoscale surface heterogeneity can provide pathways whereby diurnal, mesoscale atmospheric processes can scale up to have more general impacts at larger spatial scales and over longer time scales.

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Powers, Jordan G., Andrew J. Monaghan, Arthur M. Cayette, David H. Bromwich, Ying-Hwa Kuo, and Kevin W. Manning. "Real-Time Mesoscale Modeling Over Antarctica: The Antarctic Mesoscale Prediction System*." Bulletin of the American Meteorological Society 84, no. 11 (November 1, 2003): 1533–46. http://dx.doi.org/10.1175/bams-84-11-1533.

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In support of the United States Antarctic Program (USAP), the National Center for Atmospheric Research and the Byrd Polar Research Center of The Ohio State University have created the Antarctic Mesoscale Prediction System (AMPS): an experimental, real-time mesoscale modeling system covering Antarctica. AMPS has been designed to serve flight forecasters at McMurdo Station, to support science and operations around the continent, and to be a vehicle for the development of physical parameterizations suitable for polar regions. Since 2000, AMPS has been producing high-resolution forecasts (grids to 3.3 km) with the “Polar MM5,” a version of the fifth-generation Pennsylvania State University-NCAR Mesoscale Model tuned for the polar atmosphere. Beyond its basic mission of serving the USAP flight forecasters at McMurdo, AMPS has assisted both in emergency operations to save lives and in programs to explore the extreme polar environment. The former have included a medical evacuation from the South Pole and a marine rescue from the continental margin. The latter have included scientific field campaigns and the daily activities of international Antarctic forecasters and researchers. The AMPS program has been a success in terms of advancing polar mesoscale NWP, serving critical logistical operations of the USAP, and, most visibly, assisting in emergency rescue missions to save lives. The history and performance of AMPS are described and the successes of this unique real-time mesoscale modeling system in crisis support are detailed.

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