Articles | Volume 18, issue 2
https://doi.org/10.5194/os-18-307-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/os-18-307-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Passive tracer advection in the equatorial Pacific region: statistics, correlations and a model of fractional Brownian motion
Imre M. Jánosi
CORRESPONDING AUTHOR
Max Planck Institute for the Physics of Complex Systems, Nöthnitzer Str. 38, 01187 Dresden, Germany
Department of Water and Environmental Policy, Faculty of Water Sciences, University of Public Service, Ludovika tér 2, 1083 Budapest, Hungary
Amin Padash
Max Planck Institute for the Physics of Complex Systems, Nöthnitzer Str. 38, 01187 Dresden, Germany
Jason A. C. Gallas
Max Planck Institute for the Physics of Complex Systems, Nöthnitzer Str. 38, 01187 Dresden, Germany
Instituto de Altos Estudos da Paraíba, Rua Silvino Lopes 419-2502, 58039-190 João Pessoa, Brazil
Holger Kantz
Max Planck Institute for the Physics of Complex Systems, Nöthnitzer Str. 38, 01187 Dresden, Germany
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Surface flow fields of the global oceans are dominated by so-called mesoscale (50–300 km) eddies. They usually drift westward at a few kilometers per day, transporting mass, temperature, chlorophyll, and debris. There are several methods to identify and track eddies based on satellite measurements, some of them very computationally demanding. Here we extend a recently proposed simple procedure to the global scale, which gives quick coarse-grained statistics on mesoscale vortex properties.
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Mesoscale eddies are ubiquitous swirling flow patterns in the open ocean with diameters of around 100 km. They transport a huge amount of heat and material and are therefore key elements of the “weather” of the ocean. Using satellite-based ocean surface elevation, we found that the combined global effect of all mesoscale eddies can be treated as a single strong “super-vortex”. This finding can be helpful to estimate the energy budget of ocean regions where only sparse field data are available.
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The remotely sensed drought severity index (DSI) records compiled by Mu et al. (2013) exhibit significant local trends in several geographic areas. Since the interpretation of DSI values and trends depend on several local factors, standard field significance tests cannot provide more reliable results than the presented local trend survey. The observed continent-wide trends might be related to a slow (decadal) mode of climate variability, a link to global climate change cannot be established.
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The forecast error growth of atmospheric phenomena is caused by initial and model errors. When studying the initial error growth, it may turn out that small-scale phenomena, which contribute little to the forecast product, significantly affect the ability to predict this product. With a negative result, we investigate in the extended Lorenz (2005) system whether omitting these phenomena will improve predictability. A theory explaining and describing this behavior is developed.
Imre M. Jánosi, Holger Kantz, Jason A. C. Gallas, and Miklós Vincze
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Surface flow fields of the global oceans are dominated by so-called mesoscale (50–300 km) eddies. They usually drift westward at a few kilometers per day, transporting mass, temperature, chlorophyll, and debris. There are several methods to identify and track eddies based on satellite measurements, some of them very computationally demanding. Here we extend a recently proposed simple procedure to the global scale, which gives quick coarse-grained statistics on mesoscale vortex properties.
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The Madden–Julian Oscillation (MJO) has important socioeconomic impacts due to its influence on both tropical and extratropical weather extremes. In this study, we use machine learning (ML) to correct the predictions of the weather model holding the best performance, developed by the European Centre for Medium-Range Weather Forecasts (ECMWF). We show that the ML post-processing leads to an improved prediction of the MJO geographical location and intensity.
Hynek Bednář and Holger Kantz
Geosci. Model Dev., 15, 4147–4161, https://doi.org/10.5194/gmd-15-4147-2022, https://doi.org/10.5194/gmd-15-4147-2022, 2022
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A scale-dependent error growth described by a power law or by a quadratic hypothesis is studied in Lorenz’s system with three spatiotemporal levels. The validity of power law is extended by including a saturation effect. The quadratic hypothesis can only serve as a first guess. In addition, we study the initial error growth for the ECMWF forecast system. Fitting the parameters, we conclude that there is an intrinsic limit of predictability after 22 days.
Karim Medjdoub, Imre M. Jánosi, and Miklós Vincze
Ocean Sci., 17, 997–1009, https://doi.org/10.5194/os-17-997-2021, https://doi.org/10.5194/os-17-997-2021, 2021
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In our laboratory experiments we addressed the question of how surface standing waves in a closed stratified basin are damped by the interaction of the flow in the bulk with a sill-like bottom obstacle reaching up to a density interface between the more saline deep layer and the freshwater layer at the top. We quantify the decay rates of the surface waves and explore what types of internal waves can be excited in this process along the internal density interface.
Meagan Carney and Holger Kantz
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Extremes in weather can have lasting effects on human health and resource consumption. Studying the recurrence of these events on a regional scale can improve response times and provide insight into a changing climate. We introduce a set of clustering tools that allow for regional clustering of weather recordings from stations across Germany. We use these clusters to form regional models of summer temperature extremes and find an increase in the mean from 1960 to 2018.
Imre M. Jánosi, Miklós Vincze, Gábor Tóth, and Jason A. C. Gallas
Ocean Sci., 15, 941–949, https://doi.org/10.5194/os-15-941-2019, https://doi.org/10.5194/os-15-941-2019, 2019
Short summary
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Mesoscale eddies are ubiquitous swirling flow patterns in the open ocean with diameters of around 100 km. They transport a huge amount of heat and material and are therefore key elements of the “weather” of the ocean. Using satellite-based ocean surface elevation, we found that the combined global effect of all mesoscale eddies can be treated as a single strong “super-vortex”. This finding can be helpful to estimate the energy budget of ocean regions where only sparse field data are available.
P. I. Orvos, V. Homonnai, A. Várai, Z. Bozóki, and I. M. Jánosi
Geosci. Instrum. Method. Data Syst., 4, 189–196, https://doi.org/10.5194/gi-4-189-2015, https://doi.org/10.5194/gi-4-189-2015, 2015
Short summary
Short summary
The remotely sensed drought severity index (DSI) records compiled by Mu et al. (2013) exhibit significant local trends in several geographic areas. Since the interpretation of DSI values and trends depend on several local factors, standard field significance tests cannot provide more reliable results than the presented local trend survey. The observed continent-wide trends might be related to a slow (decadal) mode of climate variability, a link to global climate change cannot be established.
R. C. Batac and H. Kantz
Nonlin. Processes Geophys., 21, 735–744, https://doi.org/10.5194/npg-21-735-2014, https://doi.org/10.5194/npg-21-735-2014, 2014
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Spectacular climatic phenomena such as El Nino—La Nina oscillations are connected with large-scale rearrangements of oceanic surface flow patterns. In order to get a better insight into the dynamics of such changes, we performed numerical experiments on the advection of 6600 water parcels in the focal area. Surface flow fields were taken from the AVISO data bank. A simple stochastic model (fractional Brownian motion) with only two parameters nicely reproduced the statistics of advection.
Spectacular climatic phenomena such as El Nino—La Nina oscillations are connected with...