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Artículos de revistas sobre el tema "Finescale"

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Publicado: 25 de mayo de 2024
Última modificación: 31 de julio de 2025

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1

Polzin, Kurt L., John M. Toole, and Raymond W. Schmitt. "Finescale Parameterizations of Turbulent Dissipation." Journal of Physical Oceanography 25, no. 3 (1995): 306–28. http://dx.doi.org/10.1175/1520-0485(1995)025<0306:fpotd>2.0.co;2.

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2

Polzin, Kurt L., Alberto C. Naveira Garabato, Tycho N. Huussen, Bernadette M. Sloyan, and Stephanie Waterman. "Finescale parameterizations of turbulent dissipation." Journal of Geophysical Research: Oceans 119, no. 2 (2014): 1383–419. http://dx.doi.org/10.1002/2013jc008979.

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3

De Lannoy, Gabriëlle J. M., Rolf H. Reichle, Paul R. Houser, Kristi R. Arsenault, Niko E. C. Verhoest, and Valentijn R. N. Pauwels. "Satellite-Scale Snow Water Equivalent Assimilation into a High-Resolution Land Surface Model." Journal of Hydrometeorology 11, no. 2 (2010): 352–69. http://dx.doi.org/10.1175/2009jhm1192.1.

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Abstract Four methods based on the ensemble Kalman filter (EnKF) are tested to assimilate coarse-scale (25 km) snow water equivalent (SWE) observations (typical of passive microwave satellite retrievals) into finescale (1 km) land model simulations. Synthetic coarse-scale observations are assimilated directly using an observation operator for mapping between the coarse and fine scales or, alternatively, after disaggregation (regridding) to the finescale model resolution prior to data assimilation. In either case, observations are assimilated either simultaneously or independently for each loca
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4

Fridley, Jason D. "Downscaling Climate over Complex Terrain: High Finescale (<1000 m) Spatial Variation of Near-Ground Temperatures in a Montane Forested Landscape (Great Smoky Mountains)*." Journal of Applied Meteorology and Climatology 48, no. 5 (2009): 1033–49. http://dx.doi.org/10.1175/2008jamc2084.1.

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Abstract Landscape-driven microclimates in mountainous terrain pose significant obstacles to predicting the response of organisms to atmospheric warming, but few if any studies have documented the extent of such finescale variation over large regions. This paper demonstrates that ground-level temperature regimes in Great Smoky Mountains National Park (Tennessee and North Carolina) vary considerably over fine spatial scales and are only partially linked to synoptic weather patterns and environmental lapse rates. A 120-sensor network deployed across two watersheds in 2005–06 exhibited finescale
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5

Whalen, Caitlin B., Jennifer A. MacKinnon, Lynne D. Talley, and Amy F. Waterhouse. "Estimating the Mean Diapycnal Mixing Using a Finescale Strain Parameterization." Journal of Physical Oceanography 45, no. 4 (2015): 1174–88. http://dx.doi.org/10.1175/jpo-d-14-0167.1.

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AbstractFinescale methods are currently being applied to estimate the mean turbulent dissipation rate and diffusivity on regional and global scales. This study evaluates finescale estimates derived from isopycnal strain by comparing them with average microstructure profiles from six diverse environments including the equator, above ridges, near seamounts, and in strong currents. The finescale strain estimates are derived from at least 10 nearby Argo profiles (generally &lt;60 km distant) with no temporal restrictions, including measurements separated by seasons or decades. The absence of tempo
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6

Vali, Gabor, Robert D. Kelly, Jeffrey French, et al. "Finescale Structure and Microphysics of Coastal Stratus." Journal of the Atmospheric Sciences 55, no. 24 (1998): 3540–64. http://dx.doi.org/10.1175/1520-0469(1998)055<3540:fsamoc>2.0.co;2.

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7

Straka, Jerry M., Erik N. Rasmussen, and Sherman E. Fredrickson. "A Mobile Mesonet for Finescale Meteorological Observations." Journal of Atmospheric and Oceanic Technology 13, no. 5 (1996): 921–36. http://dx.doi.org/10.1175/1520-0426(1996)013<0921:ammffm>2.0.co;2.

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8

Diekmann, Martin, Cecilia Dupre, and Eddy Maarel. "Finescale species associations in alvar limestone grasslands." Nordic Journal of Botany 23, no. 1 (2003): 115–28. http://dx.doi.org/10.1111/j.1756-1051.2003.tb00373.x.

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9

Girard, Claude, Robert Benoit, and Michel Desgagné. "Finescale Topography and the MC2 Dynamics Kernel." Monthly Weather Review 133, no. 6 (2005): 1463–77. http://dx.doi.org/10.1175/mwr2931.1.

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Abstract The Canadian Mesoscale Compressible Community (MC2) model provided daily forecasts across the Alps at 3-km resolution during the Mesoscale Alpine Programme (MAP) field phase of 1999. Among the results of this endeavor, some have had an immediate impact on MC2 itself as it increasingly became evident that the model was spuriously too sensitive to finescale orographic forcing. The model solves the Euler equations of motion using a semi-implicit semi-Lagrangian scheme in an oblique terrain-following coordinate. To improve model behavior, typical approaches were tried at first. These incl
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10

Dematteis, Giovanni, Kurt Polzin, and Yuri V. Lvov. "On the Origins of the Oceanic Ultraviolet Catastrophe." Journal of Physical Oceanography 52, no. 4 (2022): 597–616. http://dx.doi.org/10.1175/jpo-d-21-0121.1.

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Abstract We provide a first-principles analysis of the energy fluxes in the oceanic internal wave field. The resulting formula is remarkably similar to the renowned phenomenological formula for the turbulent dissipation rate in the ocean, which is known as the finescale parameterization. The prediction is based on the wave turbulence theory of internal gravity waves and on a new methodology devised for the computation of the associated energy fluxes. In the standard spectral representation of the wave energy density, in the two-dimensional vertical wavenumber–frequency (m–ω) domain, the energy
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11

Radko, Timour, and Melvin E. Stern. "Finescale Instabilities of the Double-Diffusive Shear Flow*." Journal of Physical Oceanography 41, no. 3 (2011): 571–85. http://dx.doi.org/10.1175/2010jpo4459.1.

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Abstract This study examines dynamics of finescale instabilities in thermohaline–shear flows. It is shown that the presence of the background diapycnal temperature and salinity fluxes due to double diffusion has a destabilizing effect on the basic current. Using linear stability analysis based on the Floquet theory for the sinusoidal basic velocity profile, the authors demonstrate that the well-known Richardson number criterion (Ri &amp;lt; ¼) cannot be directly applied to doubly diffusive fluids. Rigorous instabilities are predicted to occur for Richardson numbers as high as—or even exceeding
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12

Parsons, David B., Melvyn A. Shapiro, R. Michael Hardesty, Robert J. Zamora, and Janet M. Intrieri. "The Finescale Structure of a West Texas Dryline." Monthly Weather Review 119, no. 5 (1991): 1242–58. http://dx.doi.org/10.1175/1520-0493(1991)119<1242:tfsoaw>2.0.co;2.

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13

Krueger, Steven K., Chwen-Wei Su, and Patrick A. McMurtry. "Modeling Entrainment and Finescale Mixing in Cumulus Clouds." Journal of the Atmospheric Sciences 54, no. 23 (1997): 2697–712. http://dx.doi.org/10.1175/1520-0469(1997)054<2697:meafmi>2.0.co;2.

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14

Polzin, Kurt, Eric Kunze, Jules Hummon, and Eric Firing. "The Finescale Response of Lowered ADCP Velocity Profiles." Journal of Atmospheric and Oceanic Technology 19, no. 2 (2002): 205–24. http://dx.doi.org/10.1175/1520-0426(2002)019<0205:tfrola>2.0.co;2.

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15

Wurman, Joshua, and Karen Kosiba. "Finescale Radar Observations of Tornado and Mesocyclone Structures." Weather and Forecasting 28, no. 5 (2013): 1157–74. http://dx.doi.org/10.1175/waf-d-12-00127.1.

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Abstract A variety of vortex configurations observed at finescale with Doppler On Wheels (DOW) radars in and near the hook echoes of supercell thunderstorms are described. These include marginal/weak tornadoes, often with no documented condensation funnels, debris rings, or low-reflectivity eyes; multiple-vortex mesocyclones; multiple simultaneous tornadoes; satellite tornadoes; cyclonic–anticyclonic tornado pairs; multiple vortices within other multiple vortices; tornadoes with quasi-concentric multiple wind field maxima; lines of vortices outside tornadoes; and horizontal vortices. The kinem
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16

Yang, Muqun, Robert M. Rauber, and Mohan K. Ramamurthy. "Origin, Evolution, and Finescale Structure of the St. Valentine’s Day Mesoscale Gravity Wave Observed during STORM-FEST. Part II: Finescale Structure." Monthly Weather Review 129, no. 2 (2001): 218–36. http://dx.doi.org/10.1175/1520-0493(2001)129<0218:oeafso>2.0.co;2.

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17

Fine, Elizabeth C., Matthew H. Alford, Jennifer A. MacKinnon, and John B. Mickett. "Microstructure Mixing Observations and Finescale Parameterizations in the Beaufort Sea." Journal of Physical Oceanography 51, no. 1 (2021): 19–35. http://dx.doi.org/10.1175/jpo-d-19-0233.1.

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AbstractIn the Beaufort Sea in September of 2015, concurrent mooring and microstructure observations were used to assess dissipation rates in the vicinity of 72°35′N, 145°1′W. Microstructure measurements from a free-falling profiler survey showed very low [(10−10) W kg−1] turbulent kinetic energy dissipation rates ε. A finescale parameterization based on both shear and strain measurements was applied to estimate the ratio of shear to strain Rω and ε at the mooring location, and a strain-based parameterization was applied to the microstructure survey (which occurred approximately 100 km away fr
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18

Hohreiter, Vincent. "Finescale Structure and Dynamics of an Atmospheric Temperature Interface." Journal of the Atmospheric Sciences 65, no. 5 (2008): 1701–10. http://dx.doi.org/10.1175/2007jas2576.1.

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Abstract Near-ground observations of an atmospheric temperature interface in the stable nocturnal boundary layer are reported. The thermal effect of the interface passage was a 5-K decrease in temperature during a 5-min period in which changes in wind speed and wind direction were also observed. The interface is of unknown origin and horizontal and vertical scale. A 32-Hz time series of temperature measured with a sonic anemometer–thermometer at 1.5 m above ground level revealed a sharp, nonintermittent decrease in temperature (∼1 K s−1) nested within a more gradual, intermittent decrease (∼1
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19

Lewellen, D. C., Baiyun Gong, and W. S. Lewellen. "Effects of Finescale Debris on Near-Surface Tornado Dynamics." Journal of the Atmospheric Sciences 65, no. 10 (2008): 3247–62. http://dx.doi.org/10.1175/2008jas2686.1.

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Debris clouds provide an important visual signature of tornadoes and can potentially significantly affect the wind structure, damage potential, and Doppler radar measurements of tornado wind speeds. To study such issues, the dynamics of finescale debris have been added to an existing high-resolution large-eddy simulation model of tornado dynamics. A so-called “two-fluid” or “Eulerian–Eulerian” approach is employed, together with a surface layer model for lofting and depositing debris. In this paper the debris implementation is described, three critical dimensionless parameters governing tornad
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20

Ronda, R. J., G. J. Steeneveld, B. G. Heusinkveld, J. J. Attema, and A. A. M. Holtslag. "Urban Finescale Forecasting Reveals Weather Conditions with Unprecedented Detail." Bulletin of the American Meteorological Society 98, no. 12 (2017): 2675–88. http://dx.doi.org/10.1175/bams-d-16-0297.1.

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Abstract Urban landscapes impact the lives of urban dwellers by influencing local weather conditions. However, weather forecasting down to the street and neighborhood scale has been beyond the capabilities of numerical weather prediction (NWP) despite the fact that observational systems are now able to monitor urban climate at these scales. In this study, weather forecasts at intra-urban scales were achieved by exploiting recent advances in topographic element mapping and aerial photography as well as looking at detailed mappings of soil characteristics and urban morphological properties, whic
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21

Toole, John M. "Temporal Characteristics of Abyssal Finescale Motions above Rough Bathymetry." Journal of Physical Oceanography 37, no. 3 (2007): 409–27. http://dx.doi.org/10.1175/jpo2988.1.

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Abstract Current-meter data from a two-year mooring within a fracture zone on the western flank of the Mid-Atlantic Ridge in the South Atlantic Ocean are reported. The mooring, deployed in conjunction with the Brazil Basin Tracer Release Experiment, was placed in the general area where enhanced diapycnal mixing had previously been inferred. The current-meter data characterize the velocity, temperature, shear, and temperature gradient variability as a function of frequency. Energetic velocities and shears were observed at the mooring at a variety of frequencies. In addition to semidiurnal flows
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22

Charba, Jerome P., Frederick G. Samplatsky, Andrew J. Kochenash, Phillip E. Shafer, Judy E. Ghirardelli, and Chenjie Huang. "LAMP Upgraded Convection and Total Lightning Probability and “Potential” Guidance for the Conterminous United States." Weather and Forecasting 34, no. 5 (2019): 1519–45. http://dx.doi.org/10.1175/waf-d-19-0015.1.

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Abstract Localized Aviation MOS Program (LAMP) convection and lightning probability and “potential” guidance forecasts for the conterminous United States, developed by the Meteorological Development Laboratory (MDL), have been produced operationally and made available to aviation and other users through the National Digital Guidance Database (NDGD) since April 2014. In response to user requests for improved skill and resolution of these forecasts, MDL has recently made extensive upgrades, and a switch to the new LAMP guidance was made in January 2018. Upgrades include improved spatial and temp
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23

Lawrence, Dale A., and Ben B. Balsley. "High-Resolution Atmospheric Sensing of Multiple Atmospheric Variables Using the DataHawk Small Airborne Measurement System." Journal of Atmospheric and Oceanic Technology 30, no. 10 (2013): 2352–66. http://dx.doi.org/10.1175/jtech-d-12-00089.1.

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Abstract The DataHawk small airborne measurement system provides in situ atmospheric measurement capabilities for documenting scales as small as 1 m and can access reasonably large volumes in and above the atmospheric boundary layer at low cost. The design of the DataHawk system is described, beginning with the atmospheric measurement requirements, and articulating five key challenges that any practical measurement system must overcome. The resulting characteristics of the airborne and ground support components of the DataHawk system are outlined, along with its deployment, operating, and reco
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24

Chao, Yi, Zhijin Li, John D. Farrara, and Peter Hung. "Blending Sea Surface Temperatures from Multiple Satellites and In Situ Observations for Coastal Oceans." Journal of Atmospheric and Oceanic Technology 26, no. 7 (2009): 1415–26. http://dx.doi.org/10.1175/2009jtecho592.1.

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Abstract A two-dimensional variational data assimilation (2DVAR) method for blending sea surface temperature (SST) data from multiple observing platforms is presented. This method produces continuous fields and has the capability of blending multiple satellite and in situ observations. In addition, it allows specification of inhomogeneous and anisotropic background correlations, which are common features of coastal ocean flows. High-resolution (6 km in space and 6 h in time) blended SST fields for August 2003 are produced for a region off the California coast to demonstrate and evaluate the me
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25

Liu, Lei, and Fei Hu. "Finescale Clusterization Intermittency of Turbulence in the Atmospheric Boundary Layer." Journal of the Atmospheric Sciences 77, no. 7 (2020): 2375–92. http://dx.doi.org/10.1175/jas-d-19-0270.1.

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AbstractThe intermittency of atmospheric turbulence plays an important role in the understanding of particle dispersal in the atmospheric boundary layer and in the statistical simulation of high-frequency wind speed in various applications. There are two kinds of intermittency, namely, the magnitude intermittency (MI) related to non-Gaussianity and the less studied clusterization intermittency (CI) related to long-term correlation. In this paper, we use a 20 Hz ultrasonic dataset lasting for 1 month to study CI of turbulent velocity fluctuations at different scales. Basing on the analysis of r
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26

Pietrycha, Albert E., and Erik N. Rasmussen. "Finescale Surface Observations of the Dryline: A Mobile Mesonet Perspective." Weather and Forecasting 19, no. 6 (2004): 1075–88. http://dx.doi.org/10.1175/819.1.

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Abstract Mobile mesonet line normal, time-to-space converted data analysis on three meridional drylines that occurred in west Texas on 10 June 1999 and 5 May 2000 are presented herein; two occurred in a quiescent environment on 5 May 2000. Based on the data, the mixing zone across the dryline was composed of a series of large horizontal moisture differentials that were highly variable in width, ranging from 5 km down to several hundred meters. The largest dewpoint differential sampled was 10.0°C over 185 m. Concurrent with a deceleration of dryline movement to nearly stationary, and while mois
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27

Stow, C. David, Stuart G. Bradley, Keith E. Farrington, Kim N. Dirks, and Warren R. Gray. "A Rain Gauge for the Measurement of Finescale Temporal Variations." Journal of Atmospheric and Oceanic Technology 15, no. 1 (1998): 127–35. http://dx.doi.org/10.1175/1520-0426(1998)015<0127:argftm>2.0.co;2.

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28

Kral, Stephan T., Joachim Reuder, Timo Vihma, et al. "The Arctic Stable Boundary Layer: ISOBAR’s Finescale Observing and Modeling." Bulletin of the American Meteorological Society 103, no. 5 (2022): 350–56. http://dx.doi.org/10.1175/bams-d-19-0212.a.

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29

Jameson, A. R., M. L. Larsen, and A. B. Kostinski. "Disdrometer Network Observations of Finescale Spatial–Temporal Clustering in Rain." Journal of the Atmospheric Sciences 72, no. 4 (2015): 1648–66. http://dx.doi.org/10.1175/jas-d-14-0136.1.

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Abstract The spatial clustering of drops is a defining characteristic of rain on all scales from centimeters to kilometers. It is the physical basis for much of the observed variability in rain. The authors report here on the temporal–spatial 1-min counts using a network of 21 optical disdrometers over a small area near Charleston, South Carolina. These observations reveal significant differences between spatial and temporal structures (i.e., clustering) for different sizes of drops, which suggest that temporal observations of clustering cannot be used to infer spatial clustering simply using
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30

Pinkel, Robert, and Steven Anderson. "Toward a Statistical Description of Finescale Strain in the Thermocline." Journal of Physical Oceanography 22, no. 7 (1992): 773–95. http://dx.doi.org/10.1175/1520-0485(1992)022<0773:tasdof>2.0.co;2.

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31

Chunchuzov, Igor. "Nonlinear Formation of the Three-Dimensional Spectrum of Mesoscale Wind Velocity and Temperature Fluctuations in a Stably Stratified Atmosphere." Journal of the Atmospheric Sciences 75, no. 10 (2018): 3447–67. http://dx.doi.org/10.1175/jas-d-17-0398.1.

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The theory of formation of the space–time spectrum of the mesoscale fluctuations in the horizontal wind velocity and vertical displacements (or relative temperature fluctuations) in a stably stratified atmosphere is developed. The nonlinear mechanism of the formation of the finescale layered inhomogeneities in the internal wave fields associated with the nonresonant wave–wave and wave–vortical mode interactions is described. The 3D spatial spectra of the layered inhomogeneities are obtained from the approximate solutions of Lagrangian motion equations for internal waves and subsequent transiti
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32

Bluestein, Howard B., Zachary B. Wienhoff, David D. Turner, et al. "A Comparison of the Finescale Structures of a Prefrontal Wind-Shift Line and a Strong Cold Front in the Southern Plains of the United States." Monthly Weather Review 145, no. 8 (2017): 3307–30. http://dx.doi.org/10.1175/mwr-d-16-0403.1.

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The objectives of this study are to determine the finescale characteristics of the wind and temperature fields associated with a prefrontal wind-shift line and to contrast them with those associated with a strong cold front. Data from a mobile, polarimetric, X-band, Doppler radar and from a surveillance S-band radar, temperature profiles retrieved from a thermodynamic sounder, and surface observations from the Oklahoma Mesonet are used to analyze a prefrontal wind-shift line in Oklahoma on 11 November 2013. Data from the same mobile radar and the Oklahoma Mesonet are used to identify the fines
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33

Kunze, Eric, and Miles A. Sundermeyer. "The Role of Intermittency in Internal-Wave Shear Dispersion." Journal of Physical Oceanography 45, no. 12 (2015): 2979–90. http://dx.doi.org/10.1175/jpo-d-14-0134.1.

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AbstractThis paper revisits a long-standing discrepancy between (i) 1–5-km isopycnal diffusivities of O(1) m2 s−1 based on dye spreading and (ii) inferences of O(0.1) m2 s−1 from internal-wave shear dispersion Kh ~ 〈Kz〉〈〉/f2 in several studies in the stratified ocean interior, where 〈Kz〉 is the bulk average diapycnal diffusivity, 〈〉 the finescale shear variance, and f the Coriolis frequency. It is shown that, taking into account (i) the intermittency of shear-driven turbulence, (ii) its lognormality, and (iii) its correlation with unstable finescale near-inertial shear, internal-wave shear dis
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34

Tzortzis, Roxane, Andrea M. Doglioli, Monique Messié, et al. "The contrasted phytoplankton dynamics across a frontal system in the southwestern Mediterranean Sea." Biogeosciences 20, no. 16 (2023): 3491–508. http://dx.doi.org/10.5194/bg-20-3491-2023.

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Abstract. Numerical simulations have shown that finescale structures such as fronts are often suitable places for the generation of vertical velocities, transporting subsurface nutrients to the euphotic zone and thus modulating phytoplankton abundance and community structure. In these structures, direct in situ estimations of the phytoplankton growth rates are rare; although difficult to obtain, they provide precious information on the ecosystem functioning. Here, we consider the case of a front separating two water masses characterized by several phytoplankton groups with different abundances
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35

Booher, Evan C. J., and Annika W. Walters. "Identifying Translocation Sites for a Climate Relict Population of Finescale Dace." Transactions of the American Fisheries Society 151, no. 2 (2022): 245–59. http://dx.doi.org/10.1002/tafs.10348.

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36

Glasheen, Katherine, James Pinto, Matthias Steiner, and Eric Frew. "Assessment of Finescale Local Wind Forecasts Using Small Unmanned Aircraft Systems." Journal of Aerospace Information Systems 17, no. 4 (2020): 182–92. http://dx.doi.org/10.2514/1.i010747.

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37

Siebert, Holger, Harald Franke, Katrin Lehmann, et al. "Probing Finescale Dynamics and Microphysics of Clouds with Helicopter-Borne Measurements." Bulletin of the American Meteorological Society 87, no. 12 (2006): 1727–38. http://dx.doi.org/10.1175/bams-87-12-1727.

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38

George, Ron, and John L. Largier. "Description and Performance of Finescale Drifters for Coastal and Estuarine Studies." Journal of Atmospheric and Oceanic Technology 13, no. 6 (1996): 1322–26. http://dx.doi.org/10.1175/1520-0426(1996)013<1322:dapofd>2.0.co;2.

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39

Atkins, Nolan T., Roger M. Wakimoto, and Conrad L. Ziegler. "Observations of the Finescale Structure of a Dryline during VORTEX 95." Monthly Weather Review 126, no. 3 (1998): 525–50. http://dx.doi.org/10.1175/1520-0493(1998)126<0525:ootfso>2.0.co;2.

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40

Wurman, Joshua, and Swarndeep Gill. "Finescale Radar Observations of the Dimmitt, Texas (2 June 1995), Tornado." Monthly Weather Review 128, no. 7 (2000): 2135–64. http://dx.doi.org/10.1175/1520-0493(2000)128<2135:frootd>2.0.co;2.

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41

Polzin, K. L., E. Kunze, J. M. Toole, and R. W. Schmitt. "The Partition of Finescale Energy into Internal Waves and Subinertial Motions." Journal of Physical Oceanography 33, no. 1 (2003): 234–48. http://dx.doi.org/10.1175/1520-0485(2003)033<0234:tpofei>2.0.co;2.

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42

Sutor, M. M., T. J. Cowles, W. T. Peterson, and S. D. Pierce. "Acoustic observations of finescale zooplankton distributions in the Oregon upwelling region." Deep Sea Research Part II: Topical Studies in Oceanography 52, no. 1-2 (2005): 109–21. http://dx.doi.org/10.1016/j.dsr2.2004.09.029.

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43

Häfliger, Vincent, Eric Martin, Aaron Boone, et al. "Evaluation of Regional-Scale River Depth Simulations Using Various Routing Schemes within a Hydrometeorological Modeling Framework for the Preparation of the SWOT Mission." Journal of Hydrometeorology 16, no. 4 (2015): 1821–42. http://dx.doi.org/10.1175/jhm-d-14-0107.1.

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Abstract The Surface Water and Ocean Topography (SWOT) mission will provide free water surface elevations, slopes, and river widths for rivers wider than 50 m. Models must be prepared to use this new finescale information by explicitly simulating the link between runoff and the river channel hydraulics. This study assesses one regional hydrometeorological model’s ability to simulate river depths. The Garonne catchment in southwestern France (56 000 km2) has been chosen for the availability of operational gauges in the river network and finescale hydraulic models over two reaches of the river.
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44

Liang, Chang-Rong, Xiao-Dong Shang, Yong-Feng Qi, Gui-Ying Chen, and Ling-Hui Yu. "A Modified Finescale Parameterization for Turbulent Mixing in the Western Equatorial Pacific." Journal of Physical Oceanography 51, no. 4 (2021): 1133–43. http://dx.doi.org/10.1175/jpo-d-20-0205.1.

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AbstractFinescale parameterizations are of great importance to explore the turbulent mixing in the open ocean due to the difficulty of microstructure measurements. Studies based on finescale parameterizations have greatly aided our knowledge of the turbulent mixing in the open ocean. In this study, we introduce a modified finescale parameterization (MMG) based on shear/strain variance ratio Rω and compare it with three existing parameterizations, namely, the MacKinnon–Gregg (MG) parameterization, the Gregg–Henyey–Polzin (GHP) parameterization based on shear and strain variances, and the GHP pa
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45

Campbell, Leah S., and W. James Steenburgh. "Finescale Orographic Precipitation Variability and Gap-Filling Radar Potential in Little Cottonwood Canyon, Utah." Weather and Forecasting 29, no. 4 (2014): 912–35. http://dx.doi.org/10.1175/waf-d-13-00129.1.

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Abstract Finescale variations in orographic precipitation pose a major challenge for weather prediction, winter road maintenance, and avalanche forecasting and mitigation in mountainous regions. In this investigation, ground-based X-band radar observations collected during intensive observing period 6 (IOP6) of the Storm Chasing Utah Style Study (SCHUSS) are used to provide an example of these variations during a winter storm in the Wasatch Mountains of northern Utah. Emphasis is placed on precipitation features in and around Little Cottonwood Canyon (LCC), which cuts orthogonally eastward int
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46

Waterman, Stephanie, Kurt L. Polzin, Alberto C. Naveira Garabato, Katy L. Sheen, and Alexander Forryan. "Suppression of Internal Wave Breaking in the Antarctic Circumpolar Current near Topography." Journal of Physical Oceanography 44, no. 5 (2014): 1466–92. http://dx.doi.org/10.1175/jpo-d-12-0154.1.

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Abstract Simultaneous full-depth microstructure measurements of turbulence and finestructure measurements of velocity and density are analyzed to investigate the relationship between turbulence and the internal wave field in the Antarctic Circumpolar Current. These data reveal a systematic near-bottom overprediction of the turbulent kinetic energy dissipation rate by finescale parameterization methods in select locations. Sites of near-bottom overprediction are typically characterized by large near-bottom flow speeds and elevated topographic roughness. Further, lower-than-average shear-to-stra
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47

Hirose, Masafumi, Riko Oki, Shuji Shimizu, Misako Kachi, and Tomohiko Higashiuwatoko. "Finescale Diurnal Rainfall Statistics Refined from Eight Years of TRMM PR Data." Journal of Applied Meteorology and Climatology 47, no. 2 (2008): 544–61. http://dx.doi.org/10.1175/2007jamc1559.1.

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Abstract The adequacy of hourly rainfall sampling was examined in terms of the detection of diurnal variations using 8 yr (1998–2005) of data observed by the precipitation radar on the Tropical Rainfall Measuring Mission (TRMM) satellite. It was found that the monthly and hourly rain samples for each 0.2° grid point over the 8-yr period are composed of multiple precipitation systems. In this study, a “3-h-significant diurnal peak” was defined as the time of maximum rainfall with consecutive positive anomalies for more than 3 h. The fraction of the analyzed area with a 3-h-significant diurnal p
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48

Miao, Qun, and Bart Geerts. "Finescale Vertical Structure and Dynamics of Some Dryline Boundaries Observed in IHOP." Monthly Weather Review 135, no. 12 (2007): 4161–84. http://dx.doi.org/10.1175/2007mwr1982.1.

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Abstract Several radar fine lines, all with a humidity contrast, were sampled in the central Great Plains during the 2002 International H2O Project (IHOP). This study primarily uses aircraft and airborne millimeter-wave radar observations to dynamically interpret the presence and vertical structure of these fine lines as they formed within the well-developed convective boundary layer. In all cases the fine line represents a boundary layer convergence zone. This convergence sustains a sharp contrast in humidity, and usually in potential temperature, across the fine line. The key question addres
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49

Lensky, Itamar M., and Uri Dayan. "Detection of Finescale Climatic Features from Satellites and Implications for Agricultural Planning." Bulletin of the American Meteorological Society 92, no. 9 (2011): 1131–36. http://dx.doi.org/10.1175/2011bams3160.1.

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50

Weiss, Christopher C., Howard B. Bluestein, Andrew L. Pazmany, and Bart Geerts. "Finescale Radar Observations of a Dryline during the International H2O Project (IHOP_2002)." Meteorological Monographs 55 (November 1, 2008): 203–28. http://dx.doi.org/10.1175/0065-9401-33.55.203.

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Abstract A case study of a double dryline on 22 May 2002 is presented. Mobile, 3-mm-wavelength Doppler radars from the University of Massachusetts and the University of Wyoming (Wyoming cloud radar) were used to collect very fine resolution vertical-velocity data in the vicinity of each of the moisture gradients associated with the drylines. Very narrow (50–100 m wide) channels of strong upward vertical velocity (up to 8 m s–1) were measured in the convergence zone of the easternmost dryline, larger in magnitude than reported with previous drylines. Distinct areas of descending motion were evi
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