NP3.2

How to cite: Thompson, D. W. and Li, J.: Widespread changes in surface temperature persistence under climate change, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1326, https://doi.org/10.5194/egusphere-egu22-1326, 2022.

Himalayan mountain region lying in the northern part of Indian sub-continent is among those zones which bears the most ecologically sensitive environments and is also a repository of biodiversity, fresh water storage and ecosystem services. Over the last three decades, land transformation related to exploitative land uses is among the main drivers of changing snow cover, vegetation cover and productivity in western Himalayas region. In a region where field-based research is challenging due to heterogenous relief and high altitude, quantifying the changes in temperature pattern using Remote Sensing Techniques can provide essential information regarding variating trends in different elements relating to temperature. This paper studies the trend analysis of changing temperature patterns using SWAT data (1979–2014) over Uttarakhand Himalayas and its association with altitudinal gradient. This paper investigates the trends in maximum (T_max), minimum (T_min) & mean (T_mean) temperatures in the annual, seasonal and monthly time-scales for 55 stations in the 5 regions of Uttarakhand’s Western Himalayan region which are categorized on the basis of elevation, from year 1979-2014. Statistical approaches are used to examine the effect of change in pattern of temperature upon the phenology of vegetation in the region under study, fresh water ecosystems, agricultural productivity, decreasing snow line & increasing tree line, change in duration of the seasons etc.

How to cite: Palni, S., Parashar, D., and Pandey, A.: Trend analysis of Changing Temperature over the Time Period of 1979 to 2014 in Uttarakhand, Western Himalaya, India, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1585, https://doi.org/10.5194/egusphere-egu22-1585, 2022.

Understanding the interaction between ocean circulation and ice sheet dynamics is fundamental to study the rapid Quaternary climate changes that punctuate major glacial-interglacial periods. Compared to the surface and deep compartments of the Atlantic Meridional Overturning Circulation (AMOC), intermediate water depths during key time periods, such as Heinrich Stadials (HSs), remain poorly documented, especially in the Northeast Atlantic.

In this study, we use benthic foraminiferal assemblage data from an upper slope sediment core from the Northern Bay of Biscay to reconstruct paleoenvironmental and paleohydrological changes at ~1000m water depth, from ~35 to 14 kyr cal BP. Our results show a strong response of benthic communities to hydrodynamic changes (related to AMOC) and to instabilities of the European Ice Sheet during the last three HSs. Benthic foraminifera provide species-specific responses to the induced physico-chemical changes, in coherence with the various geochemical and sedimentological proxies documented in the area. The three HSs are characterized by the low abundance of species indicative of high-energy environments (Cibicides lobatulus and Trifarina angulosa) and the simultaneous presence of Cibicidoides pachyderma (meso-oligotrophic species) and Globobulimina spp. (anoxia-tolerant species).   This species composition suggests a slowing of the intermediate circulation during the three HSs. Nevertheless, HS1 is very distinct from HS2 and HS3 by the high presence of high-organic flux indicator species (Cassidulina carinata and Bolivina spp.) during its early phase (Early HS1). This result confirms that EIS meltwaters were much less charged in organic material derived from the continent during HS2 and HS3 than during HS1 due to the scarcer vegetation cover and partially frozen soils. Finally, benthic foraminifera depict clearly the rapid "re-ventilation" during Mid-HS2, corresponding to a response to regional glacial instabilities.

How to cite: Depuydt, P., Mojtahid, M., Barras, C., Bouhdayad, F., and Toucanne, S.: Links between intermediate ocean circulation and cryosphere dynamics during Heinrich Stadials in the NE Atlantic: a foraminiferal perspective, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1792, https://doi.org/10.5194/egusphere-egu22-1792, 2022.

Extratropical cyclones are a major source of natural hazards in the mid latitudes as wind and precipitation extremes are associated to this weather phenomenon. Still the response of extratropical cyclones and their characteristics to strong external forcing changes is not yet fully understood. In particular, the impact of the orbital forcing as well as variations of the major ice sheets during glacial times on extratropical cyclones have not been investigated so far.  

Thus, the aim of this study is to fill this gap and to assess the impact of orbital forcing and northern hemispheric ice sheet height variations on extratropical cyclones and their characteristics during winter and summer. The main research tool is the Community Earth System Model CESM1.2. We performed a set of time slice sensitivity simulations under preindustrial (PI) conditions and for the following different glacial periods: Last Glacial Maximum (LGM), Marine Isotopic stage 4 (MIS4), MIS6, and MIS8. Additionally, we vary the northern hemispheric ice sheet height for all the different glacial periods by 33%, 66%, 100% and 125% of the ice sheet reconstructed for the LGM. For each of the simulations the extratropical cyclones are identified with a Lagrangian cyclone detection and tracking algorithm, which delivers a set of different cyclone characteristics, such as, cyclone frequency maps, cyclone area, central pressure, cyclone depth, precipitation associated to the extratropical cyclones as well as extremes in cyclone depth and extratropical cyclone-related precipitation. These cyclone characteristics are investigated for the winter and the summer season separately.

Preliminary results show that the extratropical cyclone tracks are shifted southwards on the Northern Hemisphere during the winter season. This shift has rather strong implication for the Mediterranean, with an increase of winter precipitation during glacial times over the western Mediterranean. The increase is modulated when changing the ice sheet height as extratropical cyclone tracks shift further south with increasing northern hemispheric ice sheet height. The orbital forcing shows a higher impact during summer, where mean precipitation is further reduced over Europe when comparing MIS4 and MIS8 with LGM. The changes in the cyclone tracks and related precipitation changes in the Mediterranean for the summer season need to be assessed. Additionally, the effect of the orbital forcing on changes in cyclone tracks and associated precipitation changes in the North Pacific must be evaluated for both seasons.

How to cite: Raible, C. C., Messmer, M., Jonathan, B., and Emmanuele, R.: Northern Hemispheric extratropical cyclones during glacial times: impact of orbital forcing and ice sheet height, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4276, https://doi.org/10.5194/egusphere-egu22-4276, 2022.

Holocene reconstructions of winter climate in East-Central Europe (ECE) are scarce, although several studies have brought more seasonal insights through the study of pollen in lake sediments, δ¹⁸O and deuterium excess from an ice cave deposit, as well as speleothem trace elements.

Here we present the δ¹⁸O record of stalagmite PU-2 from Urşilor Cave (W Romania) that could shed further light onto ECE Holocene hydroclimate variability for the past 6000 years. This previously published stalagmite benefits now from a more detailed age-depth model and an increased temporal resolution, to an average of 15 years across the whole record. More importantly, following recent monitoring studies, it was concluded that the δ¹⁸O signal in the cave drip water is representative of winter climate conditions.

In East-Central Europe there is a significant correlation between the winter temperature and the East Atlantic teleconnection pattern (EA), as this region witnesses higher than average temperatures during the positive phase of EA. The North Atlantic Oscillation teleconnection pattern (NAO) is known to modulate winter precipitation in the European realm, and many NAO reconstructions have sought to identify its variability in the past.

To investigate the drivers behind winter climate dynamics in the region surrounding the cave and across Europe, we compare our data with other speleothem winter temperature and rainfall records from Europe and the Levant. Further, we examine their variability on a complex time-evolving relationship with the coupled NAO/EA patterns.

How to cite: Dragusin, V., Ersek, V., Fleitmann, D., Ionita-Scholz, M., and Onac, B. P.: 6000 years of winter climate variability revealed by a speleothem record from East-Central Europe, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4277, https://doi.org/10.5194/egusphere-egu22-4277, 2022.

Large explosive volcanic eruptions can have major impacts on global climate, affecting both radiative balance and inducing interannual-to-decadal dynamical alterations of the atmospheric and oceanic circulation. Despite some discrepancies across studies regarding the response of ENSO to volcanism based on paleoclimate data, the majority of ENSO reconstructions display an El Niño–like warming in the year of eruption, while none display a significant La Niña–like response. Furthermore, there has been an emerging consensus from the numerous coupled General Circulation Model studies investigating the impact of tropical volcanism on ENSO, with the overwhelming majority displaying an El Niño–like warming occurring in the year following the eruption. However, the mechanisms that trigger ENSO anomalies following volcanic eruptions are still debated. The center of the argument is understanding how volcanism affects the trade winds along the equatorial Pacific.

We performed a series of sensitivity experiments using the Norwegian Earth System Model (NorESM1-M) designed to shed light on the processes that govern the ENSO response to volcanic eruptions as a function of the regional distribution of the aerosol forcing. Specifically, a uniform stratospheric volcanic aerosol loading was imposed over different parts of the tropics and extra-tropics to test the four main mechanisms invoked to explain the ENSO response to volcanic eruptions: 1) the ocean dynamical thermostat (ODT) mechanism; 2) the cooling of the Maritime Continent (MC) mechanism; 3) the cooling of tropical northern Africa (NAFR) mechanism; and 4) the Intertropical Convergence Zone shift mechanism. In this contribution, we will present results for NorESM1-M, illustrate their implications for understanding of forced ENSO dynamics and discuss how our approach can give benefit to multi-model assessments of ENSO response to volcanic forcing.

How to cite: Pausata, F. S. R. and the et al.: Disentangling the mechanisms of ENSO response to volcanic eruptions, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6233, https://doi.org/10.5194/egusphere-egu22-6233, 2022.

Variability in the Aleutian Low is a known contributor to North Pacific sea surface temperature (SST) variability, but its role in forcing the basin-wide SST anomalies that characterise Pacific Decadal Variability (PDV) is unclear owing to the difficulty of disentangling coupled atmosphere-ocean processes. Here we perform a large ensemble experiment with an intermediate complexity GCM where the winter-time Aleutian Low is nudged to an anomalously strong state during successive winters. This ensemble is compared to a free-running simulation to isolate the impacts of the anomalous Aleutian Low. The nudged experiment produces a basin-scale SST response that closely resembles PDV in the free running simulation, confirming that the Aleutian Low can force PDV-like variability. Tropical Pacific sea surface temperatures (SSTs) are significantly warmer in response to the strong Aleutian Low, demonstrating that extratropical atmospheric forcing can impart a signature in tropical SSTs. The largest tropical Pacific warming is manifest in the season following nudging (boreal spring), though anomalies persist year-round. We use the Bjerknes Stability Index to attribute the drivers of the tropical Pacific SST response and find that the thermocline feedback is key, which itself is most dominant in summer. The results lend new understanding to the potential for extratropical atmospheric forcing of tropical ocean variability.

How to cite: Dow, W., Maycock, A., McKenna, C., Trascasa Castro, P., Joshi, M., Smith, D., and Blaker, A.: The role of the Aleutian Low in driving Pacific Decadal Variability, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8635, https://doi.org/10.5194/egusphere-egu22-8635, 2022.

IODP Site U1389 recovered a thick contouritic drift sequence deposited on the main branch of the Mediterranean Overflow Water in the gulf of Cadiz. That allows high resolution core recoveries for Quaternary period. In this study a high-resolution SST record was obtained by modern analogues method, using planktic foraminifer assemblages and Artificial Neural Networks. Seawater oxygen isotope composition was inferred by using the Globigerina bulloides δ¹⁸O record and the new SST data.

During MIS-3 the average amplitude of the SST change between Greenland stadials and interstadials is in the order of 2 to 4 °C. Foraminifer taxa that best reflects these minor changes is Globigeririnita glutinata. Heinrich stadial periods are represented by abrupt SST drops of about 8 °C compared to Interstadial values, and high abundance of polar and subpolar species Neogloboquadrina pachyderma sin and Turborotalita quinqueloba. During MIS-2 and MIS-4, SST is higher than expected for glacial maxima, with some subtropical species occurrence except in Heinrich events. Seawater δ¹⁸O also shows millennial variability, with higher values during Greenland Interstadials and the most pronounced drops or freshening in Heinrich stadial events. During glacial maxima stadials δ¹⁸O reaches its highest values, that reflects together with the high SST potential subtropical influence.

SST and seawater δ¹⁸O changes along the record precisely reflect the impact of the Greenland stadial-interstadial events and Heinrich events on sea surface conditions. Minor event Heinrich 2.2 (2b) has been identified by SST drop but not by water freshening. Otherwise, Greenland stadial 15, which corresponds to C-14 IRD event in North Atlantic shows Heinrich-like behavior according to both sea surface proxies.

How to cite: Perez-Tarruella, J., Sierro, F. J., and Béjard, T. M.: High resolution Sea Surface Temperature and seawater oxygen isotope records in IODP Site U1389 during MISs 2 to 4, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9290, https://doi.org/10.5194/egusphere-egu22-9290, 2022.

How to cite: Wainer, I., Gorenstein, I., F. Prado, L., R. Bianchini, P., L Griffiths, M., SR Pausata, F., and Yokoyama, E.: South American climate reconstruction during the mid-Holocene from an updated paleodata compilation, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10080, https://doi.org/10.5194/egusphere-egu22-10080, 2022.

What is the spatial scale of natural climate fluctuations, and how does it depend on timescale? To answer this question, we characterize the spatio-temporal correlation structure of global surface temperature fields by estimating frequency spectra of the effective spatial degrees of freedom (ESDOF), which can be interpreted as the effective number of independent spatial samples on the globe at each frequency. ESDOF spectra are estimated from the HadCRUT4 global gridded, monthly mean temperature anomaly dataset, based exclusively on instrumental measurements, covering the period 1850 to near-present. Because this dataset includes gaps (due to a lack of observations in certain months and regions on the globe), we employ a newly developed method that allows for bias-free spectral estimation from gappy data without interpolation across gaps. To correct for the anthropogenic warming trend, the data is detrended prior to the analysis, by subtracting the linear response to the anthropogenic global mean log(CO2-equivalent) forcing time series. The resulting ESDOF spectra reveal a reduction of the ESDOF value by a factor of 10, from about 130 (±15%) at sub-annual timescales to about 13 (±50%) at multi-decadal time scales. Uncertainties are estimated by applying the same analysis to a CMIP6 climate model ensemble, with HadCRUT4 data gaps imposed. To test for the possible impact of the data gaps, the ESDOF analysis is applied to global temperature fields with and without gaps, taken from both the climate model ensemble and from the NOAA 20th Century Reanalysis dataset. Results suggest slightly higher ESDOF values for complete fields, with the increase being negligible at sub-annual timescales and of the order of 15-20% at multi-decadal timescales. Overall, the results indicate that natural temperature variability at multi-decadal timescales is characterised by an ESDOF value between 10 and 20. Since it is unlikely, due to physical constraints, that the ESDOF value increases towards timescales longer than those resolved by the instrumental record, the above multi-decadal ESDOF estimate can be taken as an upper limit for centennial and longer timescales. This may have important implications in the context of paleo-climate reconstructions and their comparison with model simulations.

How to cite: Kunz, T. and Laepple, T.: How does the spatial scale of natural climate fluctuations vary across timescales?, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10537, https://doi.org/10.5194/egusphere-egu22-10537, 2022.

The spatial scale of climate fluctuations, or effective spatial degrees of freedom (ESDOF), depends on the timescale and the forcing: while local scale variability between far away locations may be independent on short timescales, they may become coherent over sufficiently long timescales, or if they are driven by a common forcing. While ESDOF have been estimated from instrumental data over the historical period and climate model simulations, it remains difficult to perform such analysis on paleoclimate data given the time uncertainty and proxy-specific bias. We take advantage of a database of absolutely dated annual proxies comprising tree ring, corals and varved sediments in order to provide the first estimate of ESDOF for longer than multi-decadal timescales based on proxy-data.

How to cite: Hébert, R., Kunz, T., and Laepple, T.: Using proxy data to characterize the spatio-temporal structure of climate variablity, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10736, https://doi.org/10.5194/egusphere-egu22-10736, 2022.

Climate variability, resulting from natural radiative forcing and interactions within the climate system, is a major source of uncertainty for regional climate projections. Constraining the amplitude of these natural variations is fundamental to assess the range of plausible future scenarios. As the instrumental record is limited to the last two centuries, information about climate variations on multi-decadal to millennial timescales relies on the analysis of climate proxy records and climate model simulations. However, current results from systematic model-proxy comparisons of natural variability seem contradictory. Several studies suggest that simulated local temperature variability is consistently smaller than proxy-based reconstructions and conclude that climate models might have major deficiencies. Other studies find agreement in global temperature variability across timescales and argue that current models can faithfully simulate climate variability. 

Here, we review the evidence on the strength of natural temperature variability during recent millennia. We identify systematic biases in the reconstructions that may contribute to the model-proxy discrepancy but are likely not sufficient to reach consistency. Instead, we propose that the seemingly contradictory  findings on the (dis)agreement between proxies and simulations can be reconciled assuming that regional climate variations persist on longer time scales than currently simulated by climate models. The combined evidence argues for deficiencies in the simulation of internal variability but a faithful response of climate models to natural radiative forcing. We propose a strategy to test our hypothesis and discuss the implications for future climate projections.

How to cite: Laepple, T., Bothe, O., Chevalier, M., Ellerhoff, B., Hébert, R., Herbert, A., Martrat, B., Moreno Chamarro, E., Rehfeld, K., Schoch, P., Weitzel, N., and Ziegler, E.: The enigma of multidecadal to centennial global vs. local temperature variability in models and proxies, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10981, https://doi.org/10.5194/egusphere-egu22-10981, 2022.

The North Atlantic Oscillation (NAO) index describes the hemispheric meridional oscillation of atmospheric masses above near Iceland and the subtropical Atlantic regions. In specific, NAO index indicates the differences in atmospheric pressure patterns between the two regions. Strong positive NAO index values relate to significant pressure differences, exposing US East and Northern Europe to warmer weather conditions, and Southern Europe to colder weather conditions. Negative NAO index values indicate weaker pressure differences, exposing US East and Northern Europe to cold weather, and Southern Europe to warm weather. A significant portion of the Atlantic sector climate is associated with NAO index and its variability. Historically, NAO index values were in a positive trend between 1970s and 1980s. Highest positive values were reported in the early 1990s. By that time, it was suggested that NAO index positive trends contributed significantly to the global warming signal. Most recently, research outputs from climate model predictions suggest that NAO index values will be more at the positive phase as a result of strong global warming signal. In a warmer climate the overall number of storms is predicted to decrease but storms will be more intense. However, more research is needed to understand variability trends in NAO index and to what extent they might be attributed to climate change impacts. Hence referred in here as NAO natural and non-natural, or else, climate change related variability trends. This study investigated the NAO variability trends by use of Singular Spectrum Analysis (SSA) and SSA based Entropy index. SSA is a statistical mechanics tool used to study the non-linear behavioral characteristics in complex geophysical, meteorological and climatic systems, monitored by time series data. The main objective of this analysis is to reveal the evolution of the NAO index dynamical system and convey information about the changing dynamics of the system. By use of SSA Entropy based index, the chaotic behavior of NAO index is studied. An SSA entropy based chaotic descriptor might entail information of the non-natural variability trend for NAO index values. Also the same descriptor might prove capable of defining a historical milestone of when this NAO variability trend started changing in an unpredictable- non natural- way owed to climate change forcing factors. NAO Index data are extracted from Climatic Research Unit, University of East Anglia from 1979-2018. SSA Phase space reconstruction by method of delays has been applied first to characterize the statistical and chaotic behavior of NAO patterns, by calculating variability and inconsistency descriptors. Phase space reconstruction allows analyzing time series data within the dynamics systems theory context. Following that, reconstructed attractor from the NAO observed time series allowed to build an approximation of the unknown observed states. Results revealed a highly variable and inconsistent behavior in NAO patterns over time. SSA Entropy based index investigation is currently underway to further understand the nature of inconsistency revealed in NAO patterns. Further research is expected to establish wind and wave storm patterns connections with NAO index patterns, through transfer dynamics concepts.

How to cite: Chatzirodou, A. and Livogiannis, A.: Climate change and North Atlantic Oscillation (NAO) index: Can entropy reveal a non-natural variability trend in NAO index?, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12100, https://doi.org/10.5194/egusphere-egu22-12100, 2022.

Atmospheric fields are known to exhibit extreme variability over wide range of temporal and spatial scales, which makes them complex to characterize. When it comes to wind power production, the power available at atmosphere and power extracted by turbines at multiple scales are affected by corresponding variations in coexisting fields. Understanding their variability and correlations helps in quantifying uncertainties in modeling as well as real data analysis. Here, we aim to characterize the variability and correlations across scales of wind power production, and atmospheric fields including 3D wind, rainfall and air density using simultaneous measurements in a wind farm relying on the framework of Universal Multifractal (UM) analysis. It is a widely used, physically based, scale invariant framework for characterizing and simulating geophysical fields over wide range of scales.

Towards this, high-resolution atmospheric data collected from a meteorological mast located in the wind farm of Pays d’Othe operated by Boralex (110 km south-east of Paris, France) is used. The data is being collected under the project RW-Turb (https://hmco.enpc.fr/portfolio-archive/rw-turb/; supported by the French National Research Agency (ANR-19-CE05-0022). The campaign utilizes multiple 3D sonic anemometers (manufactured by Thies), mini meteorological stations (manufactured by Thies), and disdrometers (Parsivel2, manufactured by OTT) installed at turbine hub height along with turbines in the wind farm. The temporal resolution is 100 Hz for the 3D sonic anemometers, 1 Hz for the meteorological stations and 30 s for the disdrometers. Variability in power production is examined according to different meteorological conditions using the framework of UM and consequences of their correlations are discussed. In the process we also make short commentary on the actual sampling resolution at which fields should be considered for extracting useful statistical information about their variability.

How to cite: Jose, J., Gires, A., Schnorenberger, E., Tchiguirinskaia, I., and Schertzer, D.: Combined multifractal analysis of wind power production and atmospheric fields using simultaneous measurement of high-resolution data, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6858, https://doi.org/10.5194/egusphere-egu22-6858, 2022.

In Korea, typhoons are becoming an essential issue as they cause huge damage and their occurrence frequency has increased since 2001. Many types of research and case studies related to the prediction of typhoon intensity and typhoon track are being conducted, especially with the help of numerical models. However, there is a lack of studies investigating the nonlinear behavior of typhoons, especially by using radar data, see however Lee et al. (2020, DOI: 10.1175/JAMC-D-18-0209.1). We perform such a detailed analysis of datasets of wind fields retrieved from radar in a multifractal framework. More precisely, we analyzed the difference of multifractality on each altitude depending on the different typhoon tracks and show that estimates of the multifractal parameters can be used to characterize the typhoon tracks. 

The radar dataset was collected depending on the category of the track of the typhoon. Track category 1: typhoon moving straight north from Jeju island to the Korean peninsula, and track category 2: typhoon making a curve northeastward as the typhoon passes Jeju island. Typhoon Khanun, Bolaven and Sanba (2012) are selected for track category 1. Tembin (2012) and Chaba (2016) are selected for track category 2. Then, the wind field of each typhoon case was calculated by using the dual-Doppler wind retrieval method and the analysis of each field was separately performed on its positive and negative parts. 

This large amount of space-time data was analyzed by calculating fractal dimension, the Trace Moments (TM, Schertzer and Lovejoy, 1987) and Double Trace Moment (DTM, Lavallée et al., 1992). The last two enable to quantify the mean fractality of the process with the help of its fractal co-dimension C1 and its multifractality index α, which measures how fast the intermittency evolves for higher singularities.

It was possible to estimate the category of the tracks of the typhoon by calculating the fractal dimension of wind velocity components U and V  (resp. East-West and South-North) before and after landfalling on Jeju island. Also, it was noted that the location of the typhoon center affects the decreasing trend of fractal dimension of positive V. Also, with the help of TM and DTM analysis, it was possible to verify the movement of the typhoon even with the same category of track moving north. The parameter  C1 quantifies the mean sparseness of the field but the dependence on 𝛼 of positive U showed the possibility of typhoon curving to the east. Also, the track category moving to the northeast, the dependence on 𝛼 of negative U makes the difference of degree of curvature of the track. Moreover, it was possible to identify the location of the typhoon track according to the UM parameters. If the curvature degree at the altitudes of 2-5 km is large, the typhoon center is located more on the east side of the island.

How to cite: Lee, J., Tchiguirinskaia, I., Schertzer, D., and Lee, D.-I.: Characterization of Typhoon Track Using Multifractal Analysis of Wind Fields, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6807, https://doi.org/10.5194/egusphere-egu22-6807, 2022.

Every year, the Caribbean basin is strongly impacted by sand mists from African deserts. The health impact is significant for the population living there. This is the reason why a better understanding of the behavior of particulate matter that have an aerodynamic diameter less than 10 µm diameter (PM10) is crucial to predict their fluctuations. The aim of this study is to characterize the PM10 fluctuations in the fully developed turbulence framework. For that, this analysis is carried out using PM10 datasets sampled at daily basis during six years period for three Caribbean islands (Martinique–Guadeloupe-Puerto Rico). After a multifractal analysis, the results obtained show that the log-Lévy model is suitable, in comparison to the log normal model, to fit the scaling exponent function ζ(q) and the multifractal spectrum f(α). Under this basis, a PM10 fluctuations characterization for each island is proposed using the three universal multifractal parameters [1,2]. Hence, stochastic simulations can be envisaged to mimic the stochastic behavior of PM10 data.

References

[1] Schertzer, D., Lovejoy, S., 1987. Physical modeling and analysis of rain and clouds by anistropic multiplicative processes. J. Geophys. Res. 92 (D8), 9693-9714.

[2] Schertzer, D., Lovejoy, S., Schmitt, F., Chigirinskaya, Y., Marsan, D., 1997. Multifractal cascade dynamics and turbulent intermittency. Fractals 5 (3), 427-471.

How to cite: Plocoste, T., Calif, R., and Euphrasie-Clotilde, L.: PM10 fluctuation modeling in the Caribbean area using the universal multifractals framework, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10788, https://doi.org/10.5194/egusphere-egu22-10788, 2022.

The systematic study of extreme geological events (e.g., plate collision and subduction, earthquakes, volcanoes, and mineralization) that occurred during the evolution of the earth is essential not only for understanding the "abrupt changes in the evolution of the earth", but also for an in-depth understanding of the co-evolution of material-life-environment of the livable earth. However, due to the temporal and spatial anomalies and complexity of extreme geological events, classical mathematical models cannot be effectively applied to quantitively describe such events. Comparative studies of many types of geological events indicate that such extreme geological events often depict "singular" characteristics (abnormal accumulation of matter or massive release of energy in a small space or time interval). On this basis, the author proposes a unified definition of extreme geological events, a new concept of "fractal density" and a "local singularity analysis” method for quantitative description and modeling of extreme geological events. Applications of these methods to several types of extreme geological events have demonstrated that the singularity theory and methods developed in the current research can be used as general approaches for the characterization, simulation, and prediction of geological events. The case studies to be introduced include anomalous heat flow over the mid-ocean ridges, and major flare up magmatism and marine sediment flux fluctuations over the past 3 Ga history of earth continental crust evolution.

How to cite: Cheng, Q.: Fractal density and local singularity analysis method for modeling extreme geological events, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6850, https://doi.org/10.5194/egusphere-egu22-6850, 2022.

The static characterization and sedimentological/stratigraphic modelling of the Naturally Fractured and Vugular Deposits (YNFV) are carried out based on the multiscale and multi-physical/geological data (Big Geodata). To date, the reference analytical techniques used in the Oil Industry to integrate this information are uncertain. There are several reasons for this, the main one being the different nature and accuracy of the exploration data. Multifractal and p-Adic analyses of the architecture of the field of interest were carried out. It was documented that the trajectories' uncertainty and error in deviation depend on the scale of used information. From the 3D visualization of the YNF and its main structural elements (at scales from mega to micro), the corresponding maps of the heterogeneity and anisotropy of the effective porosity and permeability of the studied YNF were delivered. The main research goal is to develop accurate 2D and 3D maps of the productive horizon (or volume) of interest of the YNF Xikin, with a statistically- and structurally accurate forecast of the hydrocarbons distribution (made from the available seismic cube). The design of wells optimal trajectories and corresponding direction of the shots, based on the pattern of continuity/tortuosity of the corridors or networks of fractures. Muuk´ il Kaab (MIK) software, designed in conjunction with the Ku Maloob Zaap Field Assets and calibrated in several PEMEX fields used to construct the Effective Metric of Connected Fractures in the Xikin from the seismic records, analyze the geometry and topology of clusters detection of anomalous amplitudes/frequencies of seismic waves and to interpret it quantitatively from the point of view of their possible occupation by hydrocarbons and the geometry/topology of networks/fracture corridors. To reduce the bias of the final interpretation of the displayed data, at least ten techniques of nonlinear analysis, including multifractal and p-adic, were used. These techniques, applied to the original seismic records were visualized in the form of Textons (term that comes from Pattern Recognition area), which we will call: Macro- and MicroTexels , depending on the scale of observation and within which synthetic wells with optimal values of the variables selected as Direct Hydrocarbon Indicators (DIHO) were located.

The results of the analysis and visualization of the connected multiscale networks of fractures and according to the direct hydrocarbon indicators selected in this study for Xikin, the following  maps were constructed:
1. A probabilistic map of hydrocarbon concentration zones correlated with Xikin-specific sedimentological/stratigraphic features (with particular attention to the multiscale pattern of fracture);
2. 3D map of the optimal trajectories of the recommended wells, associated with the directional scheme of the shots in the preferential direction of each connected fracture pattern.

How to cite: Oleshko, K., Khrennikov, A., and de Jesús Correa López, M.: Multifractal and p-adic forecasting of distribution and continuity of faults, fracture corridors with a high probability of being associated with hydrocarbons, for the statistically-based design of trajectories of future production wells, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13127, https://doi.org/10.5194/egusphere-egu22-13127, 2022.