Articles | Volume 30, issue 4
https://doi.org/10.5194/npg-30-527-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/npg-30-527-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
23 Nov 2023
Research article |
| 23 Nov 2023
| 23 Nov 2023
Stieltjes functions and spectral analysis in the physics of sea ice
Kenneth M. Golden
CORRESPONDING AUTHOR
Department of Mathematics, University of Utah, 155 S 1400 E RM 233, Salt Lake City, UT 84112-0090, USA
N. Benjamin Murphy
Department of Mathematics, University of Utah, 155 S 1400 E RM 233, Salt Lake City, UT 84112-0090, USA
Daniel Hallman
Department of Mathematics, University of Utah, 155 S 1400 E RM 233, Salt Lake City, UT 84112-0090, USA
Elena Cherkaev
Department of Mathematics, University of Utah, 155 S 1400 E RM 233, Salt Lake City, UT 84112-0090, USA
Related subject area
Subject: Scaling, multifractals, turbulence, complex systems, self-organized criticality | Topic: Climate, atmosphere, ocean, hydrology, cryosphere, biosphere | Techniques: Theory
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
How many modes are needed to predict climate bifurcations? Lessons from an experiment
Non-linear hydrologic organization
The impact of entrained air on ocean waves
Approximate multifractal correlation and products of universal multifractal fields, with application to rainfall data
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 Although scaling theory and the data are now voluminous, atmospheric phenomena are too often viewed through an outdated scalebound lens, and turbulence remains confined to isotropic theories of little relevance.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.
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.
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.
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.
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Short summary
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.
Our paper tours powerful methods of finding the effective behavior of complex systems, which can...
