NP3.3 | Climate Variability & Complex System Analysis Across Scales
EDI
Climate Variability & Complex System Analysis Across Scales
Co-organized by CL4, co-sponsored by PAGES
Convener: Raphael HébertECSECS | Co-conveners: Ángel García GagoECSECS, Adarsh Sankaran, Thomas Plocoste, Qiong Zhang, Vanessa SkibaECSECS, Shaun Lovejoy
Orals
| Tue, 16 Apr, 10:45–12:25 (CEST), 14:00–15:40 (CEST)
 
Room 0.94/95
Posters on site
| Attendance Mon, 15 Apr, 16:15–18:00 (CEST) | Display Mon, 15 Apr, 14:00–18:00
 
Hall X4
Posters virtual
| Attendance Mon, 15 Apr, 14:00–15:45 (CEST) | Display Mon, 15 Apr, 08:30–18:00
 
vHall X4
Orals |
Tue, 10:45
Mon, 16:15
Mon, 14:00
Geophysical processes are governed by diverse spatial and temporal scales, and often characterized by the complex fluctuations of observations. Modeling and simulation of geophysical processes becomes extremely complex because of such non-linear fluctuations, for which, the scaling characterization is extremely important.

The first part of the session expands the knowledge on scaling characterization of geophysical time series from diverse scientific domains to develop a knowledge base of complementary nature. The geophysical processes become even more complex because of the internal structural properties like intermittency and such an in-depth understanding will improve the accuracy of modeling of complex systems. This session aims to nurture the scientific development of scaling, fractals and related methodologies applicable to the time series observations from wide range of geophysical fields like hydrology, climatology, meteorology, atmospheric science, oceanography and statistical physics for their improved modeling and predictability :
- Scaling, fractal, multifractal characterization and modeling of complex geophysical data and extreme events
- In-depth understanding of the internal dynamics of geophysical data
- Understanding the fractal /scaling correlations between governing variables
- Linking network theoretical approach and scaling to find its applications across different geophysical fields

The second part of the session focuses on characterizing multi-decadal and longer Earth system dynamics, which has significant and direct impact on our society. This requires a combination of paleoclimate data and modeling given the insufficiency of short-term observational data. Our aim is to advance the understanding of climate variability across spatial and temporal scales through research focusing on:
-Characterizing multi-decadal to millennial climate dynamics through the use of proxy data and (conceptual or realistic) model simulations
-Evaluating the impact of Earth’s subsystem - such as the ocean, atmosphere, cryosphere and land-surface - in shaping long-term climate variability, and relevant feedback mechanisms
-Proxy system modeling, calibration and propagation of uncertainty with a focus on multi-decadal and longer timescales to aid reconstructions and model-data comparisons
-The attribution of climate variability to internal and/or forced dynamics

Orals: Tue, 16 Apr | Room 0.94/95

Chairpersons: Adarsh Sankaran, Ángel García Gago, Thomas Plocoste
Complex System Analysis Across Scales
10:45–11:05
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EGU24-7105
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NP3.3
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solicited
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On-site presentation
Bellie Sivakumar

Hydroclimatic systems are complex nonlinear dynamically-evolving systems, often made up of a large number of interconnected components that change both in space and in time. Therefore, any effort towards reliable modeling and forecasting of hydroclimatic systems requires proper selection of scientific concepts and methods. Many different scientific concepts and methods have been proposed in the literature and applied to numerous hydroclimatic systems, processes, and problems around the world. Among such, concepts and methods based on chaos theory, complex networks, and fractal theory have been found to offer unique and useful avenues for studying hydroclimatic systems and, thus, have been finding widespread applications in recent times. The purpose of the present study is to discuss the advances in the applications of these concepts to hydroclimatic systems and to look toward the future. This is done through: (1) presenting some key aspects of chaos theory, complex networks, and fractal theory and their relevance to hydroclimatic systems; (2) reviewing various applications of these concepts to hydroclimatic systems, processes, and problems; (3) addressing important data-related issues in the applications of these concepts to hydroclimatic systems; and (4) offering specific directions to advance these concepts and applications further, especially in the context of future grand challenges associated with hydroclimatic systems.

How to cite: Sivakumar, B.: Complexity, Connectivity, and Scale in Hydroclimatic Systems, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7105, https://doi.org/10.5194/egusphere-egu24-7105, 2024.

11:05–11:15
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EGU24-11058
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NP3.3
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ECS
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On-site presentation
Sumayah Santhoshkhan, Athira Madhu, Muraleekrishnan Bahuleyan, and Susan Mariam Rajesh

This study presents the application of Multifractal detrended fluctuation analysis (MFDFA) for analyzing the multifractal properties of river stage time series of Indian rivers. Initially, the MFDFA method was applied to detect long-range correlations and multifractal behaviour of river stage time series of 81 locations from 11 basins of Peninsular India. The study found that all the Hurst exponent (H) values are found to be more than 0.5 indicating the long-range power law correlations in the stage data of Indian rivers. The different datasets indicated strong multifractal degree and a strong association between H and Holder exponent supported by a strong correlation over 0.98. Most of the multifractal spectra (93 %) indicated a positive asymmetry showing the frequent low fluctuations and localized high fluctuations. Basin wise analysis showed the strongest long-term persistence (LTP) and highest degree of multifractality for the datasets of Cauvery basin. In order to get an insight on the multifractality, MFDFA was applied to the daily data of corresponding period as that of stage observations. The analysis indicated that unlike the case of stage data 68 % of the data showed LTP while rest of the data displayed STP in the analysis. The multifractality of stage series is more than that of stream flow series at all river basins in India. Multifractal cross correlation analysis performed between daily river stage data and discharge data of same period indicated a strong correlation (>0.8) in majority of cases for different scales, despite the absence of a definite pattern in the correlation behavior for the data of different stations. This analysis is proven to be a very essential and useful prerequisite for developing stage-discharge relationships in a multifractal perspective, which may eventually help in proper flood management of Indian basins' changing climate scenario.

Keywords: Persistence, multifractality, Stage, Streamflow, Correlation, Scale

How to cite: Santhoshkhan, S., Madhu, A., Bahuleyan, M., and Rajesh, S. M.: Analysing the multifractality and cross correlations of river stage records using detrended fluctuation principles, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11058, https://doi.org/10.5194/egusphere-egu24-11058, 2024.

11:15–11:25
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EGU24-9251
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NP3.3
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ECS
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Virtual presentation
Akshay Pachore and Renji Remesan

Flash droughts, characterized by a rapid decline in soil moisture, are short-term drying events that can cause significant damage to crops when they occur during the growing season. Understanding the spatial and temporal evolution properties of flash droughts is crucial for the effective mitigation and management of this extreme event. The present study employed the complex network theory to assess the spatio-temporal properties of the flash drought which was quantified using the soil moisture percentile drop (SMPD) based definition during the period from 1981 to 2020 over the entire Indian region. An event synchronization (ES)-based complex network is constructed and the spatial propagation of the flash droughts is analyzed using the unidirectional and directed complex networks-based metrics i.e., strength, direction, and distance. Initial results gave insights into how the flash drought hotspots are connected in space and their temporal evolution pattern. From the result of the distance metrics, it was observed that flash drought propagates for longer distances in the central-eastern and southern peninsular regions as compared to the rest of the regions over India. Inference gained from the present analysis can be useful for building an early warning system for flash drought in terms of onset and spatial propagation along with insights on the spatially connected flash drought vulnerable regions.           

How to cite: Pachore, A. and Remesan, R.: Complex network-based analysis of the spatial evolution of the flash droughts over India, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9251, https://doi.org/10.5194/egusphere-egu24-9251, 2024.

11:25–11:35
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EGU24-16778
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NP3.3
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ECS
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On-site presentation
Caterina Gozzi, Axel Kleidon, and Antonella Buccianti

The chemistry of rivers plays a crucial role in comprehending the evolution of weathering processes, especially in the context of climate change and human activities. As weathering proceeds within river catchments, chemical concentrations tend to move towards saturation, or thermodynamic equilibrium. However, thermodynamic equilibrium is extremely difficult to achieve in an open system where matter and energy are continuously exchanged.

The speed of weathering processes and the associated probability distributions of concentrations values differ among geochemical species. We demonstrate that these differences are characterized by the rate of entropy production associated with the mixing of groundwater enriched with weathering products with the less saturated river water.

Based on river chemistry and discharge data observations in the Arno River basin in central Italy, we distinguish two groups of chemical variables, reflecting different levels of dissipative behavior. We show that Calcium (Ca2+) and Bicarbonate (HCO3-) concentrations are close to saturation along most of the downstream length of the Arno River, with decreasing dissipation rates and a (log)normal distribution, while Sodium (Na+) and Chlorine (Cl) concentrations increase substantially downstream, showing increased dissipation rates and being power-law distributed. This supports our hypothesis that power law distributions appear to be indicative of dissipative systems far from thermodynamic equilibrium, while (log)normal distributions indicate weakly dissipative systems close to equilibrium. This suggests that the frequency distributions of environmental variables are intricately connected to their thermodynamic state, and the degree of disequilibrium constrains the range over which power-law scaling can be observed. These results should contribute to a more comprehensive understanding of the characteristics and underlying mechanisms that lead to these types of distributions, allowing to better classify variability in systems based on how dissipative they are.

How to cite: Gozzi, C., Kleidon, A., and Buccianti, A.: Probability distributions as indicators of dissipative dynamics in river chemistry, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16778, https://doi.org/10.5194/egusphere-egu24-16778, 2024.

11:35–11:45
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EGU24-11382
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NP3.3
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On-site presentation
Auguste Gires, Jerry Jose, Angel Garcia-Gago, Ioulia Tchiguirinskaia, and Daniel Schertzer

Rainfall and wind exhibit extreme variability over wide range of space-time scales. Such features are naturally transferred to wind turbine torque and ultimately to wind energy production. Improving our understanding of wind power production requires better accounting for the impact of these small scale fluctuations. This is much needed in order to achieve UN’s (United Nations) Sustainable Development Goal 7 (affordable and clean energy for all) and in a context of increasing global transition towards renewable and carbon neutral energy.

The project RW-Turb (https://hmco.enpc.fr/portfolio-archive/rw-turb/; supported by the French National Research Agency, ANR-19-CE05-0022) was developed to address this challenge and to understand better the correlation across scales between rainfall and wind fields and its impact on wind power production. A high resolution measurement campaign was set up between 12/2020 and 07/2023 with two 3D sonic anemometers (manufactured by Thies), two mini meteorological stations (manufactured by Thies), and two disdrometers (Parsivel2, manufactured by OTT) installed on a meteorological mast at 75 and 45 m respectively in the wind farm of Pays d’Othe (110 km south-east of Paris, France; operated by Boralex). The framework of Universal Multifractals (UM) is used to carry out this analysis. It is a physically based and mathematically robust framework that enables to characterize and simulate the extreme variability of geophysical fields across scales. It is furthermore parsimonious since it relies on the use of only three parameters.

In a first step multifractal analysis of the available fields (wind velocity, power available at the wind farm, power produced by wind turbines, air density, and rainfall) is implemented. Event based analysis enabled to observe differences in UM parameters depending on whether it is raining or not. In general, a slightly stronger variability is found when it rains. In a second step, a joint multifractal analysis is implemented to further quantify correlation across scales between the studied fields. An increase in correlation exponent of the various fields with increase in rain rate is found.

Numerical simulations are then used as a complement to data analysis. More precisely, 3D space plus time vector fields which realistically reproduce observed spatial and temporal variability of wind fields are generated with multifractal tools. Then, they are used as input into three modeling chains of increasing complexity to simulate wind turbine torque. The simplest model uses average wind field over swept area, while a more realistic one computes the torque as an integral over the blades of the turbine enabling to account for the space-time variability of wind. Finally, OpenFAST, which is widely used by researchers and practitioners is implemented. UM analysis on the simulated torque time series were performed to quantify the impact of small scale fluctuations on wind power production, as well as the ability of the various models to account for it.

How to cite: Gires, A., Jose, J., Garcia-Gago, A., Tchiguirinskaia, I., and Schertzer, D.: Multifractal correlation of rainfall and wind fields and consequences on wind power production, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11382, https://doi.org/10.5194/egusphere-egu24-11382, 2024.

11:45–11:55
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EGU24-17984
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NP3.3
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ECS
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On-site presentation
Ching-Chun Chou, Auguste Gires, Li-Pen Wang, Ioulia Tchiguirinskaia, and Daniel Schertzer

Rainfall is extremely variable in both space and time, which makes its analysis complex. A widely used framework to properly handle these features is Universal Multifractals (UM), which is a physically based and mathematically robust framework. It relies on three parameters, meaning it is parsimonious. Two types of multifractal phase transitions can affect the analysis of a series: (i) the divergence of moments, which is related to the singular limit of the underlying cascade process at small scales and notably explains the power law fall-off observed on numerous geophysical fields, (ii) sampling limitations, which is related to the fact that great moments cannot be observed on finite series.
 
This study employs UM to analyse the time series of rainfall intensities observed by the Parsival2 disdrometer at the 10-second resolution from three distinct typhoons over the period of July to October 2022, revealing differences and limitations in their statistical characteristics. It enables us to illustrate the  two previously mentioned concepts of divergence of moments and sampling limitations and their impact on the analysis of rainfall data.

The analysis of typhoon Hinnamnor exhibited limitations due to the sampling dimension, indicating that the current data length was insufficient to capture the multifractal nature of the rainfall events for large moments, reducing the robustness of the analysis for moments greater than 5.43. It reflects sampling limitations, leading to a constrained understanding of extreme events.

For typhoon Nalgae, our analysis highlighted the occurrence of divergence of moments, i.e. a limitation associated with a critical moment. As higher-order moments were calculated, we observed statistical values tending towards infinity, suggesting that extreme rainfall events significantly influenced this typhoon and pointing out the inadequacy of traditional statistical methods in such scenarios. Such multifractal phase transition is seldom observed on individual series, highlighting the interest of studying this typhoon series. 

Finally, the analysis of the typhoon Nesat presented a behavior affected by both multifractal phase transitions resulting in a more complex interpretation. 

Our findings provide new insights into the multifractal analysis of typhoon rainfall intensities, emphasising the importance of considering multifractal theory and its associated phase transitions when dealing with natural phenomenon data. These discoveries lay a crucial methodological foundation for more accurate prediction and response to extreme weather events. In case of rainfall, it then has some hydrological consequences notably in terms of stormwater management or optimization of dams for hydraulic production.

How to cite: Chou, C.-C., Gires, A., Wang, L.-P., Tchiguirinskaia, I., and Schertzer, D.: Observation of different multifractal phase transitions over three typhoon events, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17984, https://doi.org/10.5194/egusphere-egu24-17984, 2024.

11:55–12:05
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EGU24-13680
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NP3.3
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On-site presentation
Rudy Calif and Maïna Andre

Solar energy is an intricate phenomenon, especially within tropical insular locations, where this energy source demonstrates significant fluctuations across various short-term timeframes and spatial dimensions. Research on the stochastic characteristics of solar energy is gaining momentum in the scientific literature, revealing signs of scaling properties despite its inherent complexity. This paper sequentially delves into the examination of temporal fluctuations scaling and multifractal properties of irradiance for tropical insular sites (Guadeloupe, Réunion, Hawaï). By analogy with Taylor law performed on several complex process, an analysis of temporal fluctuations irradiance scaling properties is proposed. The results showed that the process of intradaily variability obeys Taylor’s power law for every short time scales and several insolation conditions. This approach elucidates the relationship between the variance of fluctuations and the mean with exponent between 1 and 2. This could confirm the relevance of Tweedie Convergence Theorem in a manner related to the central limit theorem; a mathematical basis for Taylor’s power law, 1/f noise and multifractality according to Kendal and Jørgensen [1].
Through various multifractal analysis techniques, including MFDFA, wavelet leader, structure functions, and arbitrary order Hilbert spectral analysis, on global solar radiation sequences, the intermittent and multifractal properties inherent in global solar radiation data have been brought to light across  scales ranging from one second to few hours and all intensities.
The understanding the dynamics of irradiance fluctuations is essential in various fields, including atmospheric science, remote sensing, and renewable energy. The results of these properties can help improve the modeling and prediction, which is crucial to optimally integrate PV onto electrical grids.

 

Reference

W. S. Kendal and B. Jorgensen, Tweedie convergence: A mathematical basis for Taylor's power law, 1/f noise, and multifractality. Phys. Rev. E 84, 066120, 2011. DOI. https://doi.org/10.1103/PhysRevE.84.066120.

 

How to cite: Calif, R. and Andre, M.: Temporal fluctuations scaling, multifractality and Tweedie distributions of solar energy in insular context, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13680, https://doi.org/10.5194/egusphere-egu24-13680, 2024.

12:05–12:15
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EGU24-4818
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NP3.3
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Virtual presentation
Wei Zhao

Momentum-scalar coupling turbulence, such as buoyancy-driven turbulence and electrohydrodynamic (EHD) turbulence, involves the transportation of multicomponent scalars under the strong interplay of multiphysics. For instance, in the atmosphere, the temperature gradient can induce buoyancy, driving the flow to form thermal convection. At the same time, electric body force can be generated on droplets, dust, and moisture gradients through spatial electric fields, resulting in air flow into EHD turbulence. Additionally, charged species move and create electric current, leading to Lorentz force due to the magnetic field of the earth, which may induce magnetohydrodynamic (MHD) turbulence. These physical mechanisms generate the diverse phenomena on our beautiful planet. This study theoretically explores how multiphysical mechanisms interplay, governing the cascades of turbulent kinetic energy and multicomponent scalars. Some new scaling properties, which differ from those predicted in buoyancy-driven turbulence, EHD, and MHD, emerge when two mechanisms and scalar components exist simultaneously. The quad-cascade processes of such turbulent systems are again validated. Unfortunately, when three or more mechanisms are taken into account at the same time, the problem becomes unattainable to close. This research endeavors to shed light on the diverse observation in momentum-scalar coupling turbulence across various scenarios.

How to cite: Zhao, W.: Emergence of scaling properties in momentum-scalar coupling turbulence: Exploring interplay of multiphysics mechanisms, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4818, https://doi.org/10.5194/egusphere-egu24-4818, 2024.

12:15–12:25
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EGU24-8588
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NP3.3
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ECS
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Virtual presentation
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Konstantinos Gkoutis, Ilias Papakonstantis, Panagiotis Papanicolaou, and Panayiotis Dimitriadis

In total, 11 experiments of turbulent buoyant jets were carried out in an experimental apparatus, which includes a tank with dimensions 1.00 m x 0.80 m x 0.70 m. Specifically, in a stationary homogeneous ambient fluid, six (6) experiments were performed, with a temperature at the outlet significantly higher than the ambient water, and five (5) experiments with the same temperature but in an ambient saltwater environment of initial density difference between 18.4 and 19.2 kg/m3. The nozzle diameter was equal to 1.5 cm in all experiments, the densimetric Froude number was ranging between 1.72 and 3.73, and the Reynolds number ranging between 1222 and 3136. The experiments included flow visualization and concentration measurements based on the Laser Induced Fluorescence (LIF) technique using Rhodamine 6G as fluorescent tracer. A planar laser sheet was created and the experiments were recorded using a suitable video camera. The energy-spectra of the concentration were estimated using Fast Fourier Transformation and were compared to theoretical arguments, such as the K41 model.

How to cite: Gkoutis, K., Papakonstantis, I., Papanicolaou, P., and Dimitriadis, P.:  Power-spectra of turbulent buoyant jets from laboratory measurements, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8588, https://doi.org/10.5194/egusphere-egu24-8588, 2024.

Lunch break
Chairpersons: Raphael Hébert, Qiong Zhang, Vanessa Skiba
Climate Variability Across Scales
14:00–14:20
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EGU24-10986
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NP3.3
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solicited
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Virtual presentation
Zhengyu Liu, Yuntao Bao, Lonnie Thompson, Ellen Mosley-Thompson, Clay Tabor, Guang Zhang, Mi Yan, Marcus Lofverstrom, Isabel Montanez, and Jessica Oster

 Tropical mountain ice core : A Goldilocks indicator for global temperature change   Zhengyu Liu1,2,3, , Yuntao Bao1, Lonnie G. Thompson3,4, Ellen Mosley-Thompson1,3,  Tabor Clay5, Guang J. Zhang6, Mi Yan2, Marcus Lofverstrom7, Isabel Montanez8,  Jessica Oster9  1.      Department of Geography, The Ohio State University, Columbus, OH 2.      School of Geography Science, Nanjing Normal University, Nanjing, China. 3.      Byrd Polar and Climate Research Center, The Ohio State University, Columbus, OH 4.      School of Earth Sciences, The Ohio State University, Columbus, OH 5.      Department of Earth Sciences, University of Connecticut, Storrs, CT 6.      Scripps Institute of Oceanography, University of California San Diego, San Diego, CA

  • Department of Geosciences, University of Arizona, Tucson, AZ
  • Department of Earth and Planetary Sciences, University of California–Davis, Davis, CA
  • Department of Earth and Environmental Sciences, Vanderbilt University, Nashville, TN

 

Very high tropical alpine ice coresprovide a distinct paleoclimate record for climate changes in the middle and upper troposphere. However, the climatic interpretation of a key proxy, the stable water oxygen isotopic ratio in ice cores (), remains an outstanding problem. Here, combining proxy records with climate models, modern satellite measurements and radiative-convective equilibrium theory, we show that the tropical  is an indicator of the temperature of the middle and upper troposphere, with a glacial cooling of -7.35+-1.1oC (66% CI). Moreover, it severs as a “Goldilocks-type” indicator of global mean surface temperature change, providing the first estimate of glacial stage cooling that is independent of marine proxies as -5.9+-1.2oC. Combined with all estimations available gives the maximum likelihood estimate of glacial cooling as -5.85+10.51oC .

 

 

How to cite: Liu, Z., Bao, Y., Thompson, L., Mosley-Thompson, E., Tabor, C., Zhang, G., Yan, M., Lofverstrom, M., Montanez, I., and Oster, J.: Tropical mountain ice core  : A Goldilocks indicator for global temperature change, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10986, https://doi.org/10.5194/egusphere-egu24-10986, 2024.

14:20–14:30
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EGU24-4605
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NP3.3
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On-site presentation
Ning Cao, Qiong Zhang, and Katherine Power

Multi-centennial climate variability, evident in paleoclimate proxy records and observed in both forced transient and unforced control simulations with numerous fully coupled climate models, presents a significant yet elusive phenomenon in climate dynamics. This study, utilizing a coupled climate model EC-Earth3-LR, identifies and analyzes a prominent multi-centennial climate variability with a distinct 200-year cycle in a pre-industrial (PI, with atmospheric CO2 concentration of 280 ppmv) control simulation. This oscillation originates predominately from the North Atlantic and displays a strong association with the Atlantic Meridional Overturning Circulation (AMOC). 

We pinpoint the crucial interplay between salinity advection feedback and vertical mixing in the subpolar North Atlantic as key roles in providing the continuous internal energy source to maintain this multi-centennial oscillation. The perturbation flow of mean subtropical-subpolar salinity gradients serves as positive feedback that sustain the AMOC anomaly, while the mean advection of salinity anomalies and the vertical mixing acts as negative feedback, constraining the amplitude of AMOC anomaly.
 
In warmer climate conditions, with atmospheric CO2 concentrations elevated to 400 ppmv and 560 ppmv, we observe an expected stabilization of the water column in the North Atlantic deep-water formation regions, potentially leading to a reduction in the AMOC. These conditions are simulated to assess the evolution of unforced internal multi-centennial variability under higher CO2 levels. Results show that while multi-centennial climate variability persists in these warmer climate states, oscillation amplitudes are diminished. Despite the reduced intensity, the most pronounced effects remains in the North Atlantic and the Arctic, hypothesized to be driven by AMOC fluctuations. In contrast to the PI simulation, where the Arctic and subtropical fluxes exhibit aligned power spectra peaks, the warmer climate scenarios reveal longer timescales and reduced amplitudes in multi-centennial climate variability, suggesting a climate state dependence in the subtropical mechanism. Notably, while the subtropical salinity feedback is coupled with the Arctic mechanism in the PI state, it evolves into a weaker, slower, and self-sustaining mechanism in warmer climates.

How to cite: Cao, N., Zhang, Q., and Power, K.: Multi-centennial variability of the Atlantic Meridional Overturning Circulation: underlying mechanisms and its response to elevated CO2 levels , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4605, https://doi.org/10.5194/egusphere-egu24-4605, 2024.

14:30–14:40
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EGU24-4158
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NP3.3
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ECS
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On-site presentation
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Fernanda DI Alzira Oliveira Matos, Christian Stepanek, Gerrit Lohmann, Qiong Zhang, Katherine Elizabeth Power, Jan Streffing, and Tido Semmler

Quantifying the Earth's climate system response to changes in atmospheric carbon dioxide (CO2) concentrations is crucial for understanding the impact of greenhouse gases on the Earth's past, present, and future climate. The sensitivity of the Earth's climate to increasing CO2 levels will largely determine the environmental conditions faced by human societies, fauna, and flora in the years to come. Projected future climate conditions depend on the sensitivity of the numerical models employed. Therefore, a comprehensive understanding of model sensitivity to radiative forcing across various temporal and spatial scales is essential. Towards this goal, we employ the newly developed AWI-CM3 model, which will be used for future climate projections in CMIP7, to examine Equilibrium Climate Sensitivity (ECS) across different time scales. 

Our quasi-equilibrium simulations span 2,000 model years, subjected to atmospheric CO2 concentrations of 280, 400, 560, and 1120 ppmv. The highest concentration simulation is inspired by the CMIP6 abrupt4xCO2 protocol, designed to assess climate response to an abrupt change in radiative forcing. Notably, our simulations run much longer than the CMIP6 suggested 150-year duration. The lower concentration simulation represents the pre-industrial period (PI), while the remaining were designed to investigate the climate with CO2 concentrations similar to the current climate and with a doubling of PI levels, respectively.

The ECS derived from AWI-CM3 stands at 3.95ºC, ranking it as medium-range sensitivity compared to the CMIP6 ensemble. A key finding is that ECS increases by up to 1.5ºC when simulations are extended beyond the CMIP6 minimum runtime requirement. This change in ECS correlates to alternations in deep water formation in both the North Atlantic and Southern Oceans. Throughout the simulations, we note adjustment processes in the overall climate and multi-centennial variability in the strength of the Atlantic Meridional Overturning Circulation (AMOC) due to changes in North Atlantic Deep Water (NADW) and Antarctic Bottom Water (AABW) formation. 

The simulations also reveal a progressive weakening and shallowing of the AMOC and a strengthening of the AABW as CO2 concentrations increase. Beyond 200 years, under adjusted radiative forcing, the AMOC recovers, but the resultant circulation pattern features persistently shallower NADW and a weaker, more northward-extending AABW in the Atlantic and Pacific Oceans. Our results highlight the intricate relationship between deep water formation and Earth's equilibrium climate sensitivity. Furthermore, our findings suggest a need to reevaluate the current framework for deriving ECS in the standard CMIP6 methodology. Prolonged simulations not only enhance our understanding of the underlying mechanisms driving climate sensitivity to changing radiative forcing but also provide valuable insights into the time required for the Earth's climate to adjust to these changes.

How to cite: Oliveira Matos, F. D. A., Stepanek, C., Lohmann, G., Zhang, Q., Power, K. E., Streffing, J., and Semmler, T.: Changes in deep-water formation amplify the Earth's Equilibrium Climate Sensitivity on multi-centennial time scales, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4158, https://doi.org/10.5194/egusphere-egu24-4158, 2024.

14:40–14:50
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EGU24-2344
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NP3.3
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ECS
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On-site presentation
Kunpeng Yang, Haijun Yang, and Mengyu Liu

A multicentennial oscillation (MCO) of the Atlantic meridional overturning circulation (AMOC) is exhibited in a CESM1 control simulation. It primarily arises from internal oceanic processes in the North Atlantic, potentially representing a North Atlantic Ocean-originated mode of AMOC multicentennial variability (MCV) in reality. Specifically, this AMOC MCO is mainly driven by salinity variation in the subpolar upper North Atlantic, which dominates local density variation. Salinity anomaly in the subpolar upper ocean is enhanced by the well-known positive salinity advection feedback that is realized through anomalous advection in the subtropical-subpolar upper ocean. Meanwhile, mean advection moves salinity anomaly in the subtropical intermediate ocean northward, weakening the subpolar upper salinity anomaly and leading to its phase change. This mechanism aligns with a theoretical model we proposed earlier. In this theoretical model, artificially deactivating either the anomalous or mean advection in the AMOC upper branch prevents it from exhibiting AMOC MCO, underscoring the indispensability of both the anomalous and mean advections in this North Atlantic Ocean-originated AMOC MCO. In our coupled model simulation, the South Atlantic and Southern Ocean do not exhibit variabilities synchronous with the AMOC MCO; the Arctic Ocean’s contribution to the subpolar upper salinity anomaly is much weaker than the North Atlantic. Hence, this North Atlantic Ocean-originated AMOC MCO is distinct from the previously proposed Southern Ocean-originated and Arctic Ocean-originated AMOC MCOs. 

How to cite: Yang, K., Yang, H., and Liu, M.: A North Atlantic Ocean-originated mode of the AMOC multicentennial variability, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2344, https://doi.org/10.5194/egusphere-egu24-2344, 2024.

14:50–15:00
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EGU24-6829
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NP3.3
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ECS
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On-site presentation
Benjamin H. Tiger, David McGee, and Caroline Ummenhofer

Across all future IPCC Shared Socioeconomic Pathways, the strength of the Atlantic Meridional Overturning Circulation (AMOC) is projected to decline. However, there is much less certainty about the impacts of AMOC decline further afield. Evidence from paleoclimate archives and simulations suggests eastern African monsoons weakened under periods of high meltwater forcing in the North Atlantic, particularly during the most recent deglaciation. To explore the dynamics of this high- to low-latitude teleconnection, we use a compilation of ~30 sea surface temperature (SST) records from the tropical Indian Ocean spanning the last 30 ka. The zonal Indian Ocean SST gradient calculated from this compilation shows a remarkable similarity with North Atlantic 231Pa/230Th records of AMOC strength, particularly during intervals of variable meltwater forcing such as the Younger Dryas, Bølling-Allerød, and Heinrich stadials. A weaker AMOC is associated with cooler western Indian Ocean and a warmer eastern Indian Ocean, suggesting a tight linkage between AMOC strength and zonal Indian Ocean variability. To better understand this teleconnection, we analyzed a meltwater single-forcing scenario from a transient simulation of the Last Glacial Maximum to present (TraCE, 22ka-0ka). Under simulated meltwater forcing events, the tropical zonal Indian Ocean SST gradient intensifies (i.e., relative cooling in the west and warming in the east), in agreement with SST paleorecords. This response stems from an intensification of the subtropical high over Southern Europe which drives northerly surface wind anomalies across Arabia and the Horn of Africa, with cooler Northern Hemisphere anomalies extending as far south as Madagascar. This cools the surface western Indian Ocean, particularly in the Arabian Sea, enhancing the Bjerknes feedback and strengthening the Walker circulation across the basin. This effect is strongest in austral summer (DJF) when the Somali Jet reverses and northerly winds advect cool northern air into the deep tropics. Anomalous northerly winds and western Indian Ocean cooling were also found to be common feature of eight hosing experiments under preindustrial boundary conditions from the North Atlantic Hosing Model Intercomparison Project (NAHosMIP). Overall, we hypothesize an atmospheric mechanism connecting the high-latitude North Atlantic and tropical Indian Ocean under meltwater forcing, with the western Indian Ocean playing an outsized role in steepening the zonal SST gradient across the basin which weakens monsoon systems in eastern Africa.

How to cite: Tiger, B. H., McGee, D., and Ummenhofer, C.: Tropical-polar teleconnections: Impacts of North Atlantic meltwater forcing on the Indian Ocean, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6829, https://doi.org/10.5194/egusphere-egu24-6829, 2024.

15:00–15:10
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EGU24-5384
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NP3.3
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On-site presentation
|
Eric Hillebrand, Mikkel Bennedsen, Kathrine Larsen, and Siem Jan Koopman

Time series analysis of delta-O-18 and delta-C-13 measurements from benthic foraminifera for purposes of paleoclimatology is challenging. The time series reach back tens of millions of years, they are relatively sparse in the early record and relatively dense in the later, the time stamps of the observations are not evenly spaced, and there are instances of multiple different observations at the same time stamp (Westerhold et al., 2020, Science 369 p. 1383). The time series appear non-stationary over most of the historical record with clearly visible temporary trends of varying directions. In this paper, we propose a continuous-time state-space framework to analyze the time series prepared in Westerhold et al. (2020). State space models are uniquely suited for this purpose, since they can accommodate all the challenging features mentioned above. We specify univariate models and joint bivariate models for the two time series of delta-O-18 and delta-C-13. The models are estimated using maximum likelihood by way of the Kalman filter recursions. The suite of models we consider has an interpretation as an application of the Butterworth filter (Gomez 2001 [JBES 19 p. 365], Harvey & Trimbur 2003 [REStat 85 p. 244]). We propose model specifications that take the origin of the data from different studies into account and that allow for a partition of the total period into sub-periods following Westerhold et al. 2020, which we have been able to confirm with a statistical method (Larsen et al. 2024: Estimating Breakpoints between Climate States in Paleoclimate Data, abstract submitted to EGU General Assembly Session CL3.2.3). The models can be used, for example, to generate evenly time-stamped data by way of Kalman filtering. They can also be used, in future work, to analyze the relation to proxies for CO2 concentrations.

How to cite: Hillebrand, E., Bennedsen, M., Larsen, K., and Koopman, S. J.: Continuous-time state-space time series models for delta-O-18 and delta-C-13, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5384, https://doi.org/10.5194/egusphere-egu24-5384, 2024.

15:10–15:20
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EGU24-11718
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NP3.3
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Highlight
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On-site presentation
Brian Durham and Christian Pfrang

Last year we posed the question:  Given Earth’s ocean-atmosphere gas equilibrium, why do measured atmospheric carbon dioxide (CO2) curves rise more steeply against solvent temperature than predicted by Henry’s Law? (https://presentations.copernicus.org/EGU23/EGU23-6069_presentation.pdf). We here develop our experimental procedure to simulate more closely the ocean-atmosphere gas exchange in the lab, seeking to better understand the relationship between atmospheric COand average sea surface temperatures, with implcations for past and future climate variability in the Earth System. 

To this end, we previously reported provisional trends when water and natural seawater samples are equilibrated with an atmospheric ratio of CO2 in air. We also outlined a narrower interest in the published offset in annual CO2 cycles between marine and terrestrial stations which record atmospheric CO2 levels (Ye Yaun et al 2019).

Provisional results were compared with published values from seawater that had been `killed’ and acidified (Li and Tsui 1971 and Weiss (1974). Working at atmospheric partial pressures of CO2 however, a definitive value for the respective Henry constant was complicated by the difficulty of predicting an equilibrium asymptote in either water or seawater determinations.

We therefore listed a number of modifications to be adopted in future campaigns to address this issue. One proposed modification was to investigate alternative catalysts. Sodium dodecyl sulphate (SDS) is therefore replaced with a natural enzyme complex, generically carbonic anhydrase (CA), described as efficient in the reversible hydration of CO2 to bicarbonate.  CA is seen as an enzyme family with several independent evolutions across the phylogenetic tree, abundant in plants, diatoms, eubacteria and archaea (Supuran, 2016). The metallo-proteins are described as including a reaction space that combines one half hydrophilic and the opposing half hydrophobic, `allowing these enzymes to act as some of the most effective catalysts known in nature’.

In Phase 2 we therefore compare water samples with and without dosing with an infusion of terrestrial soil biota, while for seawater, being a living medium, we use a freshly-unfrozen sample of UK Atlantic coast water for each determination.

How to cite: Durham, B. and Pfrang, C.: An ocean-atmosphere paradox, Phase 2, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11718, https://doi.org/10.5194/egusphere-egu24-11718, 2024.

15:20–15:30
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EGU24-10640
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NP3.3
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On-site presentation
Frank Stefani, Gerrit Horstmann, Martins Klevs, George Mamatsashvili, and Tom Weier

We examine a remarkable consistency of the power spectrum of paleoclimatic varved sediment data from Lake Lisan [1] with that of a novel solar dynamo model that is doubly synchronized by tidal effects and the revolution of the Sun around the barycenter of the solar system [2,3]. We support and specify the latter model by quantifying the tidal excitation of magneto-Rossby waves [4] at the solar tachocline and by estimating the effects of spin-orbit coupling. Typical time series resulting from this dynamo model are then utilized in a double regression of solar and anthropogenic influences on the global temperature of the past 170 years in order to quantify various climate sensitivities [5].
 

[1] S. Prasad et al., Geology 32 (2004), 581
[2] F. Stefani et al., Solar Phys. 296 (2021), 88
[3] F. Stefani et al., arXiv:2309.00666
[4] G. Horstmann et al., Astrophys. J. 944 (2023), 48 
[5] F. Stefani, Climate 9 (2021), 163

How to cite: Stefani, F., Horstmann, G., Klevs, M., Mamatsashvili, G., and Weier, T.: A synchronized solar dynamo model and its consistency with climate data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10640, https://doi.org/10.5194/egusphere-egu24-10640, 2024.

15:30–15:40
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EGU24-19127
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NP3.3
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ECS
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Highlight
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On-site presentation
Gregor Mathes

Biodiversity is critically endangered by anthropogenic climate change. One of the core goals of ecological research and conservation science is therefore to enhance the mechanistic understanding of the processes that cause species to go extinct, particularly in light of anthropogenic climate change. However, the presence of non-linearities, multiple equilibria, thresholds, and internal feedbacks within ecological and climatic systems often impedes a mechanistic comprehension. One fundamental issue for extinction studies using contemporary data is that this data is always dependent on past conditions. Within ecology, the dependence of contemporary biodiversity dynamics on past climate is generally termed “climate legacy”. Climate legacies can arise from a multitude of ecological processes, such as time lags, niche conservatism, physiological thresholds, or cascading effects. Further, climate legacies can be assumed to be present in all ecological systems as a consequence of the dynamic nature of ecological patterns and processes. If not accounted for, climate legacies can hinder or even prevent the detection of true ecological responses to climate change. However, few studies on the relationship between extinction dynamics and climate include these climate legacies. Even less studies reach beyond merely discussing potential impacts of climate legacies and include them in their empirical framework. Those studies where climate legacies were included and quantified found a large impact of these legacy effects on extinction dynamics. Here I introduce a methodical framework for the quantification of effects arising from climate legacies in biotic systems of any temporal scale. I first introduce the concept of climate interactions, which describe and quantify the potential dependence of extinction risk on the long-term climatic context. Climate interactions might create a characteristic pattern in extinction dynamics and can arise from climate legacies acting over days to millions of years. They therefore provide a unifying framework for studying the consequences of climate legacies in ecosystems. The expected characteristic pattern consists of higher extinction risk, or related measures, when climatic changes add to previous trends in the same direction (such as a short-term warming adding to a long-term warming trend). It is hypothesized that these synergistic climate interactions first lead to environmental conditions increasingly different from initial adaptations of taxa, which then result in a higher extinction risk for these taxa. An antagonistic climate interaction, where a short-term climate change reverses a previous long-term trend (such as short-term cooling adding to a long-term warming trend), might result in a generally lower extinction risk through climatic conditions being more similar to initial adaptations of taxa. The emergence of expected patterns are then tested in  a variety of ecosystems, both marine and terrestrial, taking advantage of the fossil record with its rich information of past responses of organisms to climatic changes. 

How to cite: Mathes, G.: Climate legacies in macroevolutionary dynamics, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19127, https://doi.org/10.5194/egusphere-egu24-19127, 2024.

Posters on site: Mon, 15 Apr, 16:15–18:00 | Hall X4

Display time: Mon, 15 Apr 14:00–Mon, 15 Apr 18:00
Chairpersons: Shaun Lovejoy, Adarsh Sankaran, Raphael Hébert
Climate Variability Across Scales
X4.125
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EGU24-4074
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NP3.3
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ECS
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Qin Tao, Jesper Sjolte, and Raimund Muscheler

North Atlantic climate variability is to a large extent governed by the recurring modes of atmospheric circulation, also exhibiting impacts of volcanic and solar activities. These factors emphasize the importance of evaluating the leading variability modes and their responses to natural forcing in climate models for assessing the North Atlantic-European climate predictions. The recent availability of spatial field reconstructions of atmospheric circulation over the last millennium offers a unique opportunity for the paleo-evaluation of CMIP-PMIP models for these purposes across annual to centennial timescales. Particularly, with the possibility of comparing the spatial structure of variability.


In this study, we perform a model-data comparison of the North Atlantic climate focusing on the leading variability modes (North Atlantic Oscillation, NAO; East Atlantic Pattern, EA; Scandinavian Pattern, SCA) and the imprints of major natural forcing over the last millennium. We first develop an updated version of climate field reconstructions covering the past 700 years by assimilating proxy records into isotope-enabled simulations. This new version shows improved skills in reproducing the leading variability modes to serve as a reference for the comparisons with the past1000 runs. We then evaluate the multidecadal spatial variability in winter modes from the last millennium to the end of the 21st century. The models generally have a good representation of the average spatial structures of the NAO, EA and SCA patterns, but with persistent biases in their spatial variability. Particularly, the underestimated spatial shift in the NAO centres of action is directly related to the biases in regional temperature and precipitation changes. Furthermore, we examine the volcanic and solar imprints over the last millennium. Although not all the models can reproduce the significant NAO responses to volcanic eruptions as shown in the reconstructions, they do capture some NAO-like signals mixed with the EA and SCA patterns. Overall, our model-data comparison presents some potential uncertainties in climate projections over the North Atlantic sector, which remain challenging for the reliability of future projections. Also, this model-data comparison framework presents a pathway for future studies aiming to select the better-performing models for regional climate studies.

How to cite: Tao, Q., Sjolte, J., and Muscheler, R.: A model-data comparison of North Atlantic climate variability and its responses to natural forcing over the last millennium , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4074, https://doi.org/10.5194/egusphere-egu24-4074, 2024.

X4.126
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EGU24-14135
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NP3.3
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ECS
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Rebecca Cleveland Stout, Cristian Proistosescu, and Gerard Roe

Constraining forced and unforced climate variability impacts interpretations of past climate variations and predictions of future warming. However, comparing general circulation models (GCMs) and Holocene hydroclimate proxies reveals significant mismatches between simulated and reconstructed low-frequency variability on multi-decadal to multi-centennial timescales. Using a combination of GCMs and energy balance models, we have previously identified robust differences in the spatial pattern and magnitude of forced and unforced temperature variability on these long timescales. Our work suggests that not only is it important to understand variance, but also the spatial correlation between temperature at different sites. In principle, the spatial correlation at low frequencies is strongly related to the nature of variability. Now, we apply this dynamical understanding to the proxy record—specifically, across 49 globally-distributed Holocene sediment core sites with Mg/Ca and Uk37-based temperature reconstructions. We identify spatiotemporal statistics of forced and unforced variability using GCMs, and then use proxy-system models to assess how variability and spatial correlation are filtered by Mg/Ca and Uk37. Understanding these spatial correlations provides extra targets for interpreting these cores. Ultimately, we seek to characterize the forced and unforced components of slow modes of climate adjustment across the Holocene. 

How to cite: Cleveland Stout, R., Proistosescu, C., and Roe, G.: Spatial coherence as a key metric for interpreting marine records of Holocene temperature variability, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14135, https://doi.org/10.5194/egusphere-egu24-14135, 2024.

X4.127
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EGU24-19055
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NP3.3
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ECS
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Yuta Kuniyoshi, Ayako Abe-Ouchi, Sam Sherriff-Tadano, and Wing-Le Chan

Unlike the interglacial stable climate, glacial climate was dominated by millennial-scale variability, which is strongly associated with changes in the Atlantic meridional overturning circulation (AMOC). The development of the North American ice sheet has been shown to have a significant impact on the strength of the AMOC through surface cooling and enhanced surface winds. However, the impact of mid-glacial ice sheet involved in millennial-scale variability of the AMOC are still elusive. Here, using a coupled atmosphere-ocean model MIROC4m, we perform several climate simulations under mid-glacial ice sheet configurations. We use Marine Isotope Stage (MIS)-5a and MIS-3 ice sheet configurations as boundary conditions, which are derived from the simulation of an ice sheet model, IcIES-MIROC. These volumes are the 40 m sea level equivalent for MIS5a (approximately 33% of the LGM) and the 96 m sea level equivalent for MIS3 (approximately 80% of the LGM). To account for uncertainty in the altitude of the ice sheet, we also conduct experiments under topographic conditions in which only the altitude was changed, but not the extent, for each ice sheet configuration. As a result, self-sustained oscillations of millennial-scale periodicity in the climate and AMOC are simulated for both ice sheet cases. The result suggests that the millennial-scale climate variability could occur as long as the North American ice sheet exists, even if the ice sheet is small. The expansion of the North American ice sheet from MIS5a to MIS3 have an influence of shortening the weak AMOC period (stadial) and lengthening of the strong AMOC period (interstadial), because the stronger surface winds over North Atlantic enhance retreat of sea-ice during the stadial and increase salt transport via wind-driven ocean circulation during the interstadial. Meanwhile, one of the other simulations under the ice sheet condition with MIS3-equivalent extent but altitudes as low as 50% results in a persistent stadial state, which is due to the large cooling effect. Our results show that the relative strength of surface wind and surface cooling effects depends on the ice sheet configuration, which could modify the length of stadial and interstadial.

How to cite: Kuniyoshi, Y., Abe-Ouchi, A., Sherriff-Tadano, S., and Chan, W.-L.: Role of size and height of ice sheet on millennial-scale climate variability, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19055, https://doi.org/10.5194/egusphere-egu24-19055, 2024.

X4.128
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EGU24-16097
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NP3.3
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ECS
|
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Christina Brodowsky, Simon Barker, Michael Sigl, and Kirstin Krüger

Explosive volcanic eruptions have disrupted the climate system dramatically in the past. Recent volcanological fieldwork suggests that at least four VEI 8 events took place in the past 100’000 years, depositing large amounts of volcanic volatiles onto polar ice sheets, each one with potentially significant impacts on human life on Earth. Previous studies on this research topic and time period tend to focus either on tropical eruptions or only consider changes in radiative forcing due to orbital parameters, solar variability, or changes in atmospheric CO2. Here, we seek to evaluate the climatic and environmental impacts of the ~25.5 ka Oruanui eruption (Taupō caldera, 38°S, 175°E, New Zealand). We thereby refine our understanding of the volcanic forcing based on volcanological and ice core data to provide a basis for long-term climate simulations. We use existing emission details for an idealized Oruanui-like eruption scenario. We run an ensemble of CESM2/WACCM simulations with 1850 pre-industrial conditions and instantaneously emit 260 Tg SO2, and the corresponding halogen load derived from petrological estimates into the stratosphere. We then analyze the climatic effects in the decades following the eruption compared with available paleo proxies. Our overarching goal is to provide comprehensive insights into the climatic and environmental repercussions of an Oruanui-like eruption, with a specific emphasis on the differences to tropical events of comparable magnitude. By comparing these two distinct types of eruptions, we aim to contribute to a refined understanding of volcanic impacts on Earth's climate and human life.

How to cite: Brodowsky, C., Barker, S., Sigl, M., and Krüger, K.: Climatic and environmental impacts of an Oruanui-like supereruption in the Southern Hemisphere extratropics, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16097, https://doi.org/10.5194/egusphere-egu24-16097, 2024.

X4.129
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EGU24-7152
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NP3.3
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ECS
Fengli An, Mingjun Tong, and Haijun Yang

Long-term proxy data have shown that there is significant multi-centennial variability in Earth's climate system. However, the causes and mechanisms of this variability are still a major scientific problem for climate scientists and archaeologists. From the middle of the Holocene until the Industrial Revolution, there was little change in the Earth's external forcing, so it is important to study the long-term natural oscillations of our climate system during this period. In our research, we designed a series of experiments using CESM1.0 to explore the sources of multi-centennial variability of climate system. In some experiments, the thermohaline circulation was turned off to see if its presence would affect the oscillation of climate system. We finally conclude that thermohaline circulation is likely to determine the multi-centennial variability of Earth's climate system.

How to cite: An, F., Tong, M., and Yang, H.: Thermohaline Circulation Determines the Multi-centennial Variability of Earth's Climate System, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7152, https://doi.org/10.5194/egusphere-egu24-7152, 2024.

X4.130
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EGU24-3084
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NP3.3
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ECS
Vanessa Skiba, Andrew Dolman, Raphaël Hébert, Mara McPartland, and Thomas Laepple

Knowledge on natural climate variability is pivotal for making future climate projections. Previous studies demonstrated that centennial to millennial temperature variability is lacking in climate model simulations and that this bias is spatially heterogeneous. Various mechanisms have been proposed that might be important to modulate this low-frequency variability such as the ocean circulation, the meridional temperature gradient or external forcing and climate sensitivity to that forcing, but the evidence to identify the main driver(s) is still debated. Here, we provide preliminary insights on the respective importance of those mechanisms in driving long-term climate variability by investigating spatial patterns of low-frequency climate variability.

Low-frequency variability beyond multi-decadal timescales cannot be studied using only instrumental data due to data limitations and the confounding impact of anthropogenic forcing. Consequently, noisy and biased palaeoclimate proxy observations have to be utilised in order to investigate spatio-temporal patterns of climate change. Using a multi-archive and -proxy approach, we characterise the first-order spatial pattern of low-frequency climate variability of interglacial periods. By combining information on the spatio-temporal fingerprint derived from various archives and proxies with different characteristics, we aim to identify the common climate variability signal and assess the ability of climate models to explain the proxy-based spatial pattern of low-frequency variability.

How to cite: Skiba, V., Dolman, A., Hébert, R., McPartland, M., and Laepple, T.: Spatio-temporal climate fingerprint in palaeoclimate data vs models, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3084, https://doi.org/10.5194/egusphere-egu24-3084, 2024.

Complex Systems Analysis Across Scales
X4.131
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EGU24-3157
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NP3.3
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ECS
Hynek Bednar and Holger Kantz

Inspired by the Lorenz (2005) system, we mimic an atmospheric variable in one dimension, which can be decomposed into three spatiotemporal scales. This is motivated by and consistent with scale phenomena in the atmosphere. When studying the initial error growth in this system, it turns out that small scale phenomena, which contribute little to the forecast product, significantly affect the ability to predict this product. In other words, a more precise knowledge of the initial condition does not translate into a longer closeness of the forecast to the truth. Lorenz gave a sketch of such error growth. After a fast growth of the small scale errors with saturation at these very same small scales, the large scale errors continue to grow at a slower rate until even these saturate. We will present that scale dependent error growth can be translated into power law error growth. We will explain how parameter values of the power law are related to the error growth properties of the individual scales. We apply the results to the initial error growth of numerical weather prediction systems and show that the validity of the power law would imply a finite prediction horizon.

How to cite: Bednar, H. and Kantz, H.: Power law error growth in a more realistic atmospheric Lorenz system with three spatiotemporal scales, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3157, https://doi.org/10.5194/egusphere-egu24-3157, 2024.

X4.132
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EGU24-8571
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NP3.3
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ECS
|
|
Bo Li, Ciprian Panaitescu, Paul Glover, Kejian Wu, Piroska Lorinczi, and Bingsong Yu

Characterising the complexity of spatial patterns and their underlying physics using a nonlinear approach is growing in many fields. Many features in geomaterials, such as pore and fracture systems, exhibit scaling behaviour, allowing their properties to be characterised using fractal theory.

The widely used fractal dimension is a ratio that compares how the level of detail in a structure varies with its size, measuring its space-filling ability. Lacunarity, derived from the Latin word "lacuna," meaning "gap," quantifies the “voidness” of a texture. Nevertheless, neither fractal dimension nor lacunarity can characterise the percolating properties of a fractal. Mandelbrot coined the concept of succolarity. Given that "percolare" in Latin translates to "to flow through," the term "succolare" (sub-colare) aptly conveys the concept of "to nearly flow through" in neo-Latin. A succolating fractal is characterised by almost containing the connecting paths that permit percolation, i.e., one below the percolation threshold. However, it remains a less known notion than the other two fractal counterparts. In the last ten years, succolarity has evolved from an idea to a computable parameter. It has characterised many patterns in different scales and fields, such as medical objects, material surfaces, and networks from nano-micropores to rivers.

In this contribution, we aim (i) to understand the physical meaning of succolarity and how it relates to pore networks and other petrophysical properties across different scales, and (ii) to provide new approaches to succolarity calculation. We implemented the succolarity algorithm using the gliding box-counting method. We then re-examined the published datasets for validation and comparison. The succolarity for 2/3D images of rock samples and synthetic models with various porous structures was also calculated for deeper understanding. Finally, we correlated the succolarity results with porosity, permeability, and other petrophysical parameters.

Our findings reveal that (i) succolarity contains information about a structure's anisotropy, phase fraction (e.g., porosity in the case of pore space), and percolation information. (ii) It is susceptible to connectedness. As we cut out smaller pores of a structure, succolarity decreases linearly until a pore size (porosity) threshold is reached; it drops significantly and follows a power law. (iii) Succolarity (Su) and permeability are fitted to an exponential relation: k = aebSu. The computation of succolarity excludes isolated pores for a given flooding direction, allowing it to reflect the flow properties better than porosity alone. (iv) Moreover, it is worth noting that using pressure or velocity field in the succolarity calculation algorithm would endow it with a clearer physical meaning than being a proxy for porosity.

How to cite: Li, B., Panaitescu, C., Glover, P., Wu, K., Lorinczi, P., and Yu, B.: Unravelling succolarity to quantify multiscale petrophysical properties beyond porosity, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8571, https://doi.org/10.5194/egusphere-egu24-8571, 2024.

X4.133
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EGU24-13694
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NP3.3
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ECS
Sitian Zhu, Auguste Gires, Cedo Maksimovic, Ioulia Tchiguirinskaia, and Daniel Schertzer

The cooling efficacy of green roofs in mitigating the urban heat island (UHI) effect within dense cities is largely attributed to evapotranspiration (ET) processes. Hence, accurate understanding and quantification of ET are pivotal for optimizing this cooling effect. ET estimation can be achieved either directly (weighing lysimeters) or indirectly (e.g., Penman-Monteith equation). Micro-meteorological approaches have been developed in recent years. Among which scintillometer can evaluate ET by its measurement parameter   which corresponds to the fluctuations of air refractive index  ) in combination with surface energy balance and Monin-Obukhov similarity theory. Hence, improvement in  data as well as understanding of its variability across wide range of space-time scale would result in better ET estimation and ultimately optimization. Yet it is often overlooked, and little research has focused on it and notably its variability.

This study explores the ET estimation on a wavy and vegetated green roof covering an area of 1 ha, known as the Blue Green Wave, which is located in Ecole des Ponts Paristech campus. Data from a large aperture scintillometer with 10-minute timestep during December 2019 and January 2020 is adopted.   data variability across scales was analysed with the help of structure function and Universal Multifractal model (UM). The UM framework, widely employed for characterizing and simulating geophysical fields extremely variable across wide range of space-time scales, relies on two parameters with physical interpretation: the mean intermittency codimension  and multifractality index  (, indicates monofractal; , indicates log-normal model.) An additional one, which is needed for non-conservative fields such as ET is the non-conservativeness parameter H.

Both structure function and UM approaches reveal good scaling behaviour on scales ranging from 10 min to 2h, confirming the relevance of the framework and demonstrating the potential for upscaling and downscaling. UM analysis conducted through Trace Moment and Double Trace Moment methods, provided similar values for UM parameters around   H is approximately 0.44 in our case, which deviates from traditional scaling laws due to the intricate composition of the fluxes and requires further investigations. Indeed  is influenced by temperature, humidity, air pressure and wind speed. To interpret properly structure function analysis from UM analysis, it is necessary to introduce a parameter denoted a. It corresponds to the power to which the assumed conservative underlying field should be raised before fractional integration to account for non-conservativeness to retrieve the studied field.  Here, we observed that a is around 0.76 to ensure the highest consistency of the outcome from both the structure function and UM analyses. A better understanding of the underlying complexity and variability of Cn2 is achieved by our analysis. This, in turn, improves our understanding of the underlying physical processes generating variability and temporal-spatial dynamics in ET, which paves the way for future applications.

 

How to cite: Zhu, S., Gires, A., Maksimovic, C., Tchiguirinskaia, I., and Schertzer, D.: Multifractal analysis of Cn2  scintillometer data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13694, https://doi.org/10.5194/egusphere-egu24-13694, 2024.

X4.134
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EGU24-17721
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NP3.3
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ECS
Jerry Jose, Yelva Roustan, Auguste Gires, Ioulia Tchiguirinskaia, and Daniel Schertzer

Below cloud scavenging by rain is known to be a very efficient sinking mechanism for aerosols in atmosphere. Since this scavenging depends on interaction between aerosol particles as well as the scavening raindrops, and notably their respective size ranges, it is interesting to examine both fields together across various size ranges and across temporal scales. Towards this, a 4 month long data was used from Cherbourg-Octeville, France from 01/11/2010 to 12/03/2011 from the experimental station managed by Institut de Radioprotection et de Sûreté Nucléaire (IRSN). Here, simultaneous and continuous measurement of size resolved particle concentration (14.6 to 478.3 nm and 0.523 to 19.81 µm) range has been done using Scanning Mobility Particle Sizer (SMPS) and Aerodynamic Particle Sizer (APS), and rain measurement using a disdrometer.

Variation of total aerosol concentration in nm and µm range, as well as individual number concentration in small size bins were analyzed according to rain and dry events, using the framework of Universal Multifractals (UM). UM is widely used, as a physically based scale invariant framework, for characterizing and simulating extreme variability and intermittency in geophysical fields. From initial analysis, the total concentration showed scaling properties (1 min to 1 hr), in both rain and dry events, regardless the scavenging efficiency of event. This was further explored in individual concentration ranges and they showed similar scaling properties in different rain types. However, while considering the different stages of rain, say start and end, the values of UM parameters showed some variation. To understand the behavior more clearly, few sizes were selected from nm and µm range, and efforts were made to extract the field which is devoid of scavenging by rain. Understanding the correct transformation required to extract accurate UM values and comparing the scavenging and non scavenging fields will improve understanding of particle concentration variation, and eventually understanding of scavenging coefficient.

How to cite: Jose, J., Roustan, Y., Gires, A., Tchiguirinskaia, I., and Schertzer, D.: Multifractal analysis of aerosol particle concentration during rain and dry conditions in nm and µm range, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17721, https://doi.org/10.5194/egusphere-egu24-17721, 2024.

X4.135
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EGU24-16400
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NP3.3
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Hanno Spreeuw, Johan Hidding, Niklas Hohmann, and Emilia Jarochowska

Rhythmic variations in the properties of sediments are commonly used as archives of paleoclimate changes driven by variation in insolation caused by the changes in the Earth's orbit and the tilt of its axis. But rhythmicity can also arise from diagenetic self-organization. Distinguishing between these two drivers requires simulating self-organization. We started with an attempt to reproduce the main results from a paper by Ivan L'Heureux (2018)¹ - who proposed a mathematical model of a nonlinear dynamical system, in which self-organized oscillations arise from homogenous initial sediment and result in sediment layers with different compositions. The model consists of five stiff differential equations, for the composition of calcite and aragonite, two mineral polymorphs of CaCO3, of which aragonite is metastable, for the concentrations of calcium and carbonate ions in the pore water and for the porosity, as functions of depth and time. The self-organized patterns are in this model the result of two processes happening at different temporal scales: rapid dissolution of aragonite and slow sediment compression in response to increased porosity as aragonite is removed from the solid phase. Reproducing the steady-state distributions along depth required a major effort, mostly with regard to understanding what triggers numerical instabilities, but was finally successful.  
Currently, we have not yet succeeded in reproducing oscillations, that L'Heureux predicted
, without requiring an external force, for high initial and boundary sediment porosity.  It is essential that we are able to determine for which inital and boundary conditions oscillations should occur, beyond the uncertainties introduced by numerical algorithms for solving partial differential equations, e.g. for many sets of parameters the integrations over time can easily "derail". We have formulated two questions that we want to share with the audience in order to seek help. These are our questions: 

1) Do the five differential equations describe the underlying physics adequately?  
2) Our current software implementation of the five differential equations does not yield any oscillations, is that a flaw on our side, or does this agree with mathematical insights?

  • "Diagenetic Self-Organization and Stochastic Resonance in a Model of Limestone-Marl Sequences" by Ivan L'Heureux (2018). https://doi.org/10.1155/2018/4968315

How to cite: Spreeuw, H., Hidding, J., Hohmann, N., and Jarochowska, E.: Uncertainties in modelling diagenetic self-organisation in limestone-marl sequences, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16400, https://doi.org/10.5194/egusphere-egu24-16400, 2024.

X4.136
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EGU24-6672
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NP3.3
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ECS
Rhisiart Davies, Shaun Lovejoy, Raphael Hebert, Fabrice Lambert, and Andrej Spiridonov

With few exceptions, paleodata are irregularly sampled; this poses numerous challenges for the statistical characterization of paleoindicators, this includes the indicators needed to understand the climate and macroevolution.  The key variable is the measurement density - the number of measurements per unit time (r(t)).  Our study used 27 paleoindicators collectively spanning time scales from years to hundreds of millions of years.

Using Haar fluctuation analysis and for all the series, we show that r(t) has two scaling regimes.  At high frequencies, there is a low intermittency (quasi-Gaussian) scaling regime (intermittency parameter C1 ≈ 0).  Over this regime, the fluctuation exponent H is negative implying that the chronologies become more uniform at longer time scales, r(t) is commonly close to a Gaussian white noise (H = -1/2).  In contrast, at low frequencies, r(t) is highly intermittent (large C1), but it also has positive H so that fluctuations tend to grow with scale but in a highly intermittent fashion.  In this this regime, “gaps” at all scales are important. 

The two regimes have simple physical interpretations: the high frequency behaviour can be explained by fairly smooth (but scaling) sedimentation rates, whereas the low frequencies can be explained by scaling erosion processes that introduce gaps over a wide range of scales (in conformity with the Sadler effect). To confirm this interpretation, we introduce a simple multiplicative sedimentation -  erosion model that is close to the data.  Finally, we empirically show that the gaps typically have extreme power law probability tails so that the series are not only scaling in time, but also in probability space.

A key issue for paleontologists is the effect of variable r(t) on the paleoindicator estimates themselves (e.g. on paleotemperatures T(t)).  Using Haar fluctuations we determined the fluctuation - fluctuation correlation R(Δt) = < Δ r(Δt) ΔTt) >.  When R(Δt) is small, the measurements and indicators are statistically independent so that the biases due to r(t) variability on paleoindicator statistics are easy to correct.  However, at large Δt, the correlations are frequently large, and this poses additional difficulties in data interpretation.  Strong correlations were observed in the Quaternary, but not the Holocene or Phanerozoic.

Our study spans more than 8 orders of magnitude in time scale and it shows that it is wrong to theorize paleoseries as being fundamentally regularly sampled but interspersed with occasional data “holes” that can be dealt with using conventional techniques such as interpolation.  While Haar fluctuation analysis is insensitive to the chronology variability - and if needed can easily be statistically corrected for any biases that it introduces -  this is not true of existing spectral estimators that are extremely sensitive to scaling data gaps. 

How to cite: Davies, R., Lovejoy, S., Hebert, R., Lambert, F., and Spiridonov, A.: Unified scaling framework for Holocene, Quaternary and Phanerozoic geochronology variability, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6672, https://doi.org/10.5194/egusphere-egu24-6672, 2024.

Posters virtual: Mon, 15 Apr, 14:00–15:45 | vHall X4

Display time: Mon, 15 Apr 08:30–Mon, 15 Apr 18:00
Chairpersons: Adarsh Sankaran, Ángel García Gago, Thomas Plocoste
vX4.6
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EGU24-7409
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NP3.3
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ECS
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Meenakshi Murugan

The ozone layer acts as the planet's natural sunscreen, protecting people, plants, and animals from harmful UV-B rays. In Antarctica, British scientists discovered the hole in the ozone layer in 1985. The effects of climate change have been experienced by all living hoods through various kinds of natural calamities due to this hole. Many researchers dedicated their time to solving this problem and saving the planet. This article explores Antarctica's post-1985 climate changes.  The authors have to Investigate the time series data for the global temperature, precipitation, and Antarctica ice sheet mass balance through analysis utilizing the fractal analysis tool.  Additionally, the nonlinear dynamical data's chaotic feature is verified.

How to cite: Murugan, M.: Fractal approach in the Analysis of climate change due to the ozone layer hole, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7409, https://doi.org/10.5194/egusphere-egu24-7409, 2024.