Articles | Volume 24, issue 3
https://doi.org/10.5194/npg-24-569-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/npg-24-569-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Quantifying the changes of soil surface microroughness due to rainfall impact on a smooth surface
Benjamin K. B. Abban
CORRESPONDING AUTHOR
Hydraulics and Sedimentation Lab, Department of Civil & Environmental Engineering, University of Tennessee – Knoxville, Knoxville, TN 37996, USA
A. N. (Thanos) Papanicolaou
Hydraulics and Sedimentation Lab, Department of Civil & Environmental Engineering, University of Tennessee – Knoxville, Knoxville, TN 37996, USA
Tennessee Water Resources Center, Knoxville, TN 37996, USA
Christos P. Giannopoulos
Hydraulics and Sedimentation Lab, Department of Civil & Environmental Engineering, University of Tennessee – Knoxville, Knoxville, TN 37996, USA
Dimitrios C. Dermisis
College of Engineering, Department of Chemical, Civil & Mechanical Engineering, McNeese State University, Lake Charles, LA 70605, USA
Kenneth M. Wacha
USDA-ARS – National Laboratory for Agriculture and the Environment, Ames, IA 50011, USA
Christopher G. Wilson
Hydraulics and Sedimentation Lab, Department of Civil & Environmental Engineering, University of Tennessee – Knoxville, Knoxville, TN 37996, USA
Mohamed Elhakeem
Abu Dhabi University, Abu Dhabi, P.O. Box 59911, Abu Dhabi, United Arab Emirates
Related subject area
Subject: Scaling, multifractals, turbulence, complex systems, self-organized criticality | Topic: Climate, atmosphere, ocean, hydrology, cryosphere, biosphere
Clustering of settling microswimmers in turbulence
A global analysis of the fractal properties of clouds revealing anisotropy of turbulence across scales
Phytoplankton retention mechanisms in estuaries: a case study of the Elbe estuary
On dissipation time scales of the basic second-order moments: the effect on the Energy and Flux-Budget (EFB) turbulence closure for stably stratified turbulence
Stieltjes functions and spectral analysis in the physics of sea ice
Review article: Scaling, dynamical regimes, and stratification. How long does weather last? How big is a cloud?
Brief communication: Climate science as a social process – history, climatic determinism, Mertonian norms and post-normality
Characteristics of intrinsic non-stationarity and its effect on eddy-covariance measurements of CO2 fluxes
Fractional relaxation noises, motions and the fractional energy balance equation
How many modes are needed to predict climate bifurcations? Lessons from an experiment
Non-linear hydrologic organization
Comparing estimation techniques for temporal scaling in palaeoclimate time series
The impact of entrained air on ocean waves
Ordering of trajectories reveals hierarchical finite-time coherent sets in Lagrangian particle data: detecting Agulhas rings in the South Atlantic Ocean
Approximate multifractal correlation and products of universal multifractal fields, with application to rainfall data
Stratified Kelvin–Helmholtz turbulence of compressible shear flows
Influence of atmospheric stratification on the integral scale and fractal dimension of turbulent flows
Fractal behavior of soil water storage at multiple depths
Multifractal behaviour of the soil water content of a vineyard in northwest Spain during two growing seasons
Horton laws for hydraulic–geometric variables and their scaling exponents in self-similar Tokunaga river networks
Jingran Qiu, Zhiwen Cui, Eric Climent, and Lihao Zhao
Nonlin. Processes Geophys., 31, 229–236, https://doi.org/10.5194/npg-31-229-2024, https://doi.org/10.5194/npg-31-229-2024, 2024
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The swimming of settling microswimmers in a fluid flow is found to induce a gyrotactic torque, causing them to swim against gravity. A Lagrangian model of the swimmer under this effect is used in the analysis of small-scale clustering in turbulence. The intensity and location of clustering under this swimming-induced gyrotactic torque are found to depend on not only the swimming velocity but also the settling speed, indicating the importance of the settling effect on gyrotaxis.
Karlie N. Rees, Timothy J. Garrett, Thomas D. DeWitt, Corey Bois, Steven K. Krueger, and Jérôme C. Riedi
EGUsphere, https://doi.org/10.5194/egusphere-2024-552, https://doi.org/10.5194/egusphere-2024-552, 2024
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The shapes of clouds viewed from space reflect both vertical and horizontal motions in the atmosphere. The turbulence that shapes clouds is similarly described and related theoretically to the measured complexity of cloud perimeters from various satellites and a numerical model. We find agreement between theory and observations, and, remarkably, that the theory applies globally using only basic planetary physical parameters from the smallest scales of turbulence to the planetary scale.
Laurin Steidle and Ross Vennell
Nonlin. Processes Geophys., 31, 151–164, https://doi.org/10.5194/npg-31-151-2024, https://doi.org/10.5194/npg-31-151-2024, 2024
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Phytoplankton are key in estuaries, as they form the ecosystem's base. Despite being washed out by river flow and facing a large range of different salinities, they persist. Our Lagrangian simulation of the Elbe estuary shows that buoyancy helps them to be retained. Riverbanks and tidal flats offer refuges from strong currents. Our findings emphasize the need for careful ecosystem management in estuaries.
Evgeny Kadantsev, Evgeny Mortikov, Andrey Glazunov, Nathan Kleeorin, and Igor Rogachevskii
EGUsphere, https://doi.org/10.5194/egusphere-2023-3164, https://doi.org/10.5194/egusphere-2023-3164, 2024
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Our study investigates how turbulence behaves in stable conditions using direct numerical simulations. We found that rethinking how energy dissipates in these situations is crucial. By revising existing models, we uncovered limitations in understanding how temperature is transported vertically in very stable conditions. We focused on how turbulence works in extreme stability offering new insights that could improve our understanding of natural phenomena affected by stable atmospheric conditions.
Kenneth M. Golden, N. Benjamin Murphy, Daniel Hallman, and Elena Cherkaev
Nonlin. Processes Geophys., 30, 527–552, https://doi.org/10.5194/npg-30-527-2023, https://doi.org/10.5194/npg-30-527-2023, 2023
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Our paper tours powerful methods of finding the effective behavior of complex systems, which can be applied well beyond the initial setting of sea ice. Applications include transport properties of porous and polycrystalline media, such as rocks and glacial ice, and advection diffusion processes that arise throughout geophysics. Connections to random matrix theory establish unexpected parallels of these geophysical problems with semiconductor physics and Anderson localization phenomena.
Shaun Lovejoy
Nonlin. Processes Geophys., 30, 311–374, https://doi.org/10.5194/npg-30-311-2023, https://doi.org/10.5194/npg-30-311-2023, 2023
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How big is a cloud?and
How long does the weather last?require scaling to answer. We review the advances in scaling that have occurred over the last 4 decades: (a) intermittency (multifractality) and (b) stratified and rotating scaling notions (generalized scale invariance). Although scaling theory and the data are now voluminous, atmospheric phenomena are too often viewed through an outdated scalebound lens, and turbulence remains confined to isotropic theories of little relevance.
Hans von Storch
Nonlin. Processes Geophys., 30, 31–36, https://doi.org/10.5194/npg-30-31-2023, https://doi.org/10.5194/npg-30-31-2023, 2023
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Climate science is, as all sciences, a social process and as such conditioned by the zeitgeist of the time. It has an old history and has attained different political significances. Today, it is the challenge of anthropogenic climate change – and societies want answers about how to deal with it. In earlier times, it was mostly the ideology of climate determinism which led people to construct superiority and eventually colonialism.
Lei Liu, Yu Shi, and Fei Hu
Nonlin. Processes Geophys., 29, 123–131, https://doi.org/10.5194/npg-29-123-2022, https://doi.org/10.5194/npg-29-123-2022, 2022
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We find a new kind of non-stationarity. This new kind of non-stationarity is caused by the intrinsic randomness. Results show that the new kind of non-stationarity is widespread in small-scale variations of CO2 turbulent fluxes. This finding reminds us that we need to handle the short-term averaged turbulent fluxes carefully, and we also need to re-screen the existing non-stationarity diagnosis methods because they could make a wrong diagnosis due to this new kind of non-stationarity.
Shaun Lovejoy
Nonlin. Processes Geophys., 29, 93–121, https://doi.org/10.5194/npg-29-93-2022, https://doi.org/10.5194/npg-29-93-2022, 2022
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The difference between the energy that the Earth receives from the Sun and the energy it emits as black-body radiation is stored in a scaling hierarchy of structures in the ocean, soil and hydrosphere. The simplest scaling storage model leads to the fractional energy balance equation (FEBE). We examine the statistical properties of FEBE when it is driven by random fluctuations. In this paper, we explore the statistical properties of this mathematically simple yet neglected equation.
Bérengère Dubrulle, François Daviaud, Davide Faranda, Louis Marié, and Brice Saint-Michel
Nonlin. Processes Geophys., 29, 17–35, https://doi.org/10.5194/npg-29-17-2022, https://doi.org/10.5194/npg-29-17-2022, 2022
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Present climate models discuss climate change but show no sign of bifurcation in the future. Is this because there is none or because they are in essence too simplified to be able to capture them? To get elements of an answer, we ran a laboratory experiment and discovered that the answer is not so simple.
Allen Hunt, Boris Faybishenko, and Behzad Ghanbarian
Nonlin. Processes Geophys., 28, 599–614, https://doi.org/10.5194/npg-28-599-2021, https://doi.org/10.5194/npg-28-599-2021, 2021
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The same power law we previously used to quantify growth of tree roots in time describes equally the assemblage of river networks in time. Even the basic length scale of both networks is the same. The one difference is that the basic time scale is ca. 10 times shorter for drainage networks than for tree roots, since the relevant flow rate is 10 times faster. This result overturns the understanding of drainage networks and forms a basis to organize thoughts about surface and subsurface hydrology.
Raphaël Hébert, Kira Rehfeld, and Thomas Laepple
Nonlin. Processes Geophys., 28, 311–328, https://doi.org/10.5194/npg-28-311-2021, https://doi.org/10.5194/npg-28-311-2021, 2021
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Paleoclimate proxy data are essential for broadening our understanding of climate variability. There remain, however, challenges for traditional methods of variability analysis to be applied to such data, which are usually irregular. We perform a comparative analysis of different methods of scaling analysis, which provide variability estimates as a function of timescales, applied to irregular paleoclimate proxy data.
Juan M. Restrepo, Alex Ayet, and Luigi Cavaleri
Nonlin. Processes Geophys., 28, 285–293, https://doi.org/10.5194/npg-28-285-2021, https://doi.org/10.5194/npg-28-285-2021, 2021
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A homogenization of Navier–Stokes to wave scales allows us to determine that air bubbles suspended near the ocean surface modify the momentum equation, specifically enhancing the vorticity in the flow. A model was derived that relates the rain rate to the production of air bubbles near the ocean surface. At wave scales, the air bubbles enhance the wave dissipation for small gravity or capillary waves.
David Wichmann, Christian Kehl, Henk A. Dijkstra, and Erik van Sebille
Nonlin. Processes Geophys., 28, 43–59, https://doi.org/10.5194/npg-28-43-2021, https://doi.org/10.5194/npg-28-43-2021, 2021
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Fluid parcels transported in complicated flows often contain subsets of particles that stay close over finite time intervals. We propose a new method for detecting finite-time coherent sets based on the density-based clustering technique of ordering points to identify the clustering structure (OPTICS). Unlike previous methods, our method has an intrinsic notion of coherent sets at different spatial scales. OPTICS is readily implemented in the SciPy sklearn package, making it easy to use.
Auguste Gires, Ioulia Tchiguirinskaia, and Daniel Schertzer
Nonlin. Processes Geophys., 27, 133–145, https://doi.org/10.5194/npg-27-133-2020, https://doi.org/10.5194/npg-27-133-2020, 2020
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This paper aims to analyse and simulate correlations between two fields in a scale-invariant framework. It starts by theoretically assessing and numerically confirming the behaviour of renormalized multiplicative power law combinations of two fields with known scale-invariant properties. Then a new indicator of correlation is suggested and tested on rainfall data to study the correlation between the common rain rate and drop size distribution features.
Omer San and Romit Maulik
Nonlin. Processes Geophys., 25, 457–476, https://doi.org/10.5194/npg-25-457-2018, https://doi.org/10.5194/npg-25-457-2018, 2018
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We study the scaling laws of stratified shear flows by performing high-resolution numerical simulations of inviscid compressible turbulence induced by Kelvin–Helmholtz instability.
Manuel Tijera, Gregorio Maqueda, and Carlos Yagüe
Nonlin. Processes Geophys., 23, 407–417, https://doi.org/10.5194/npg-23-407-2016, https://doi.org/10.5194/npg-23-407-2016, 2016
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This work investigates the possible correlations between the integral scale of the turbulent stratified flows in the atmospheric boundary layer and parameters characterizing topological features of the wind velocity field, such as fractal dimension and its stability properties, studied through the bulk Richardson number. Fractal dimension and the integral scale of the horizontal (u') and vertical (w') velocity fluctuations have been calculated using the mean wind direction as a framework.
Wenjun Ji, Mi Lin, Asim Biswas, Bing C. Si, Henry W. Chau, and Hamish P. Cresswell
Nonlin. Processes Geophys., 23, 269–284, https://doi.org/10.5194/npg-23-269-2016, https://doi.org/10.5194/npg-23-269-2016, 2016
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We measure soil water at points (point scale) and try to understand how they vary over the landscape. Previous studies identified a statistical relationship between these scales only at the surface and not at depths. This study found that the relationship stands at different depths. The relationship was very similar at different depths in drier season or in late summer and fall. A less similar relationship was observed between surface and subsurface layers in spring or in wetter seasons.
José Manuel Mirás-Avalos, Emiliano Trigo-Córdoba, Rosane da Silva-Dias, Irene Varela-Vila, and Aitor García-Tomillo
Nonlin. Processes Geophys., 23, 205–213, https://doi.org/10.5194/npg-23-205-2016, https://doi.org/10.5194/npg-23-205-2016, 2016
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The current study aimed to describe the dynamics of soil water content at three depths in a vineyard under rain-fed and irrigation conditions and to assess the multifractality of these time data series. Soil water content data series obeyed power laws and tended to behave as multifractals. Our results suggest that singularity spectra were useful for characterising temporal variability of soil water content, distinguishing patterns among series registered under rain-fed and irrigation treatments.
V. K. Gupta and O. J. Mesa
Nonlin. Processes Geophys., 21, 1007–1025, https://doi.org/10.5194/npg-21-1007-2014, https://doi.org/10.5194/npg-21-1007-2014, 2014
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Short summary
We examine rainfall-induced change in soil microroughness of bare soil surfaces in agricultural landscapes with initial microroughness length scales on the order of 2 mm (smooth surfaces). Past studies have focused on scales of 5–50 mm and have reported a decrease in miccroroughness. Findings in this study show a consistent increase in microroughness under rainfall action for initial length scales of 2 mm. Thus, rainfall–surface interactions can be different for smooth and rough surfaces.
We examine rainfall-induced change in soil microroughness of bare soil surfaces in agricultural...