bluuebunny/crossref_metadata_2025 huggingface dataset:
A stochastic solar wind magnetic field model and probing its meandering nature by Energetic Electrons
Authors: Li Gang , Bian Nicolas , Zhao Lulu
Published: March 2021

Energetic electrons in impulsive events can serve as an ideal probe of solar wind magnetic field. Using a recently developed Fractonal Velocity Dispersion Analysis (FVDA), the release time at the Sun and the path length of interplanetary magnetic field can be obtained with very small uncertainties in many impulsive events. Further knowing the source location, one can examine how much do the field lines deviate from the Parker spiral.  In this work, we present an analytic model for the angular dispersion of magnetic field lines that results from the turbulence in the solar wind and at the solar source surface. The heliospheric magnetic field lines in this  model is derived from a Hamiltonian $H_{\rm m}(\mu, \phi, r)$ in which the pair of canonically conjugated variables the cosine of the heliographic colatitude $\mu$ and the longitude $\phi$. This model naturally incorporates the effect of a random footpoint motion on the source surface since such a motion is due to the zero-frequency component of the solar wind turbulence. Assuming the footpoint motion is also diffusive, it is shown that the angular diffusivity of the stochastic Parker spirals is given by the angular diffusivity of the footpoints divided by the solar wind speed and is controlled by a unique parameter which is the Kubo number. We also present some model calculations of meandering field lines resulting from stochastic footpoint motion and statistical results of the field line path length from observations. Our model and statistical results can shed lights on observations made by Parker Solar Probe and Solar Orbiter.

 

 
Droughts and Floods Captured by Land Water Storage in Chao Phraya River Basin during 2002-2017
Authors: Abhishek Abhishek , Kinouchi Tsuyoshi
Published: March 2021

Frequent droughts and floods in the Chao Phraya river basin, which contributes about 66% to Thailand’s GDP, have cost the country’s socio-economic development in several ways. We quantified the Land Water Storage (LWS) in the basin using the three data products, i.e., two mascons and one spherical harmonic in terms of anomaly time series of equivalent water depth or volume, from the Gravity Recovery and Climate Experiment (GRACE) satellite data from April 2002 to June 2017. Since all three data products were highly correlated (r>0.9), the arithmetic mean was used to avoid bias in any particular product. LWS showed a linear trend of 9.8 mm/yr equivalent to 1.6 km3/yr in the basin. The flood and drought events were also well captured by the LWS dynamics in the basin. The severe floods of 2011, primarily resulting from the heavy rainfall of 1439 mm, which was 143 % of the long-term average in the rainy season, led to a maximum value of 430 mm (68.8 km3) in the LWS anomaly during September 2011. The drought in March 2016 was also evident with a minimum LWS anomaly of -334 mm (-53.44 km3). All the multi-year flood and drought years were recorded in the LWS time series with a lag of up to two months from rainfall. Since the minimum rain during the dry periods (i.e., November to April) was almost consistent, the extreme events were supposed to be triggered mainly by the variable maximum rainfall occurring during the monsoon season. The methodology can be used for efficient water management and policymaking in the data-scarce river basins globally. Future work includes filling the data gap between GRACE and GRACE Follow-On data, followed by the assessment of anthropogenic impacts (i.e., groundwater abstraction and reservoir management) on water storage dynamics in the basin.
Climatic controls on mountain glacier basal thermal regimes dictate spatial patterns of glacial erosion
Authors: Lai Jingtao , Anders Alison
Published: March 2021

The basal thermal regime of glaciers is a first-order control on the spatial patterns of glacial erosion. Polythermal glaciers contain both cold-based portions that protect bedrock from erosion and warm-based portions that actively erode bedrock. Climatic controls on the thermal structures of mountain glaciers and the spatial patterns of glacial erosion has received little study. In this study, we aim to fill this gap by modeling the impact of various climatic conditions on glacier basal thermal regimes and patterns of glacial erosion in mountainous regions. We couple a sliding-dependent glacial erosion model with the Parallel Ice Sheet Model (PISM) to simulate the evolution of the glacier basal thermal regime and glacial erosion in a synthetic landscape. We find that glacial erosion patterns follow the patterns of the basal thermal regime. Cold temperature leads to limited glacial erosion at high elevations due to cold-based conditions. Increasing precipitation could overcome the impact of cold temperature on the basal thermal regime by accumulating thick ice and lowering the melting point of ice at the base of glaciers. High precipitation rates, therefore, tend to cause warm-based conditions at high elevations, resulting in intensive erosion near the peak of the mountain range. Previous studies often assess the impact of climate on the spatial patterns of glacial erosion by integrating climatic conditions into the equilibrium line altitudes (ELAs) of glaciers, and glacial erosion is suggested to be maximal around the ELAs. However, our results show that different climatic conditions could produce glaciers with similar ELAs but different patterns of basal thermal regime and glacial erosion, suggesting that there might not be any direct correlation between ELAs and glacial erosion patterns.
Assessing likelihood of sectoral drought impact occurrence in South Korea
Authors: Seo Jungho , Lee Jaehyeong , Kim Yeonjoo
Published: March 2021

Drought is the most complex natural hazard that can cause a wide range of impacts affecting the environment, the society, and the economy. Drought is often quantified with one or a set of drought indices, yet these drought indices are limited in capturing such various impacts. This study aimed to understand quantitative relationship between drought impact and drought occurrence in South Korea. We there constructed drought impact inventory by collecting data not only from the existing datasets but also by using a web-crawling method. The collected drought impact data were classified into categories such as agriculture and livestock farming, public water supply, wildfire, and water quality. Also, to quantify the drought occurrence, the standardized precipitation and evapotranspiration index (SPEI) was used as a drought index. We derive the likelihood of drought impact occurrence as a function of the drought index with using the log-logistic regression as well as the random forest algorithmas well as the random forest algorithm. Note that the logistic regression is appropriate with binary data such as drought impact occurrence and Note that the logistic regression is appropriate with binary data such as drought impact occurrence and the random forest algorithm is powerful algorithm to develop a predictive model based on classification and regression trees. As a result, the sector-specific likelihood of drought impact occurrence over the regions are identified. We show the highest likelihood of drought impact occurrence in public water supply for Jeonnam area, wildfire for Gangwon area and water quality for Gyeongnam. This study suggests that such drought impact information can support the decision-making for drought risk reduction.

 

Acknowledgement

This work was supported by a grant from the National Research Foundation of Korea funded by the Ministry of Science, ICT & Future Planning (2020R1A2C2007670).
Interaction of the Indian craton with the Reunion plume
Authors: Paul Jyotirmoy , Ghosh Attreyee
Published: March 2021

One of the fundamental characteristics of cratons is the presence of thick lithosphere of more than 200 km, whereas any standard non-cratonic lithosphere thickness is about 100 km thick. The thickness of Indian craton has remained quite controversial. Under the Indian plate, most seismic studies fail to recognise a thick lithosphere; however, a few studies using other geophysical methods (e.g., magnetotellurics) argue for a thick Indian craton. In the last 30 years, more than ten research articles estimated the thickness of the Indian craton that varied from less than 100 km to 260 km. Such controversy arose primarily because of the Reunion plume and Indian craton interaction at ~65 Ma. Some studies suggested that due to the Reunion plume's eruption underneath the Indian craton, the thick lithosphere of the Indian craton was thinned down. This thin lithosphere is attributed as one of the primary reasons for the acceleration of the Indian plate since 65 Ma. On the other hand, several studies advocated that the Reunion plume did not affect the thickness of the Indian craton. Still now, no study has actually investigated the nature of plume-craton interaction under the Indian plate and how the craton was deformed in the presence of a plume. In this study, we develop time-dependent global mantle convection models using CitcomS to understand the evolution of Indian craton for the last 100 Ma. The models are initiated at 100 Ma and are driven forward  up to the present day using reconstructed plate velocities at every 1 Myr interval. Our results show that it is possible to thin down the thicker cratonic lithosphere due to the eruption of the Reunion plume. We also observe that the plume could get bifurcated due to the craton, and eruptions could occur on both the eastern and western parts of the Indian continental lithosphere.
The MLT distribution and detailed structure of ring current:  MMS observations
Authors: Tan Xin , Dunlop Malcolm , Dong Xiangcheng , Yang Yanyan , Russell Christopher
Published: March 2021

The ring current is an important part of the large-scale magnetosphere-ionosphere current system; mainly concentrated in the equatorial plane, between 2-7 RE, and strongly ordered between ± 30 ° latitude. The morphology of ring current directly affects the geomagnetic field at low to middle latitudes. Rapid changes in ring current densities can occur during magnetic storms/sub-storms. Traditionally, the Dst index is used to characterize the intensity of magnetic storms and to reflect the variation of ring current intensity, but this index does not reflect the MLT distribution of ring current. In fact, the ring current has significant variations with MLT, depending on geomagnetic activity, due to the influence of multiple factors; such as, the partial ring current, region 1/region 2 field-aligned currents, the magnetopause current and sub-storm cycle (magnetotail current). The form of the ring current has been inferred from the three-dimensional distribution of ion differential fluxes from neutral atom imaging; however, this technique can not directly obtain the current density distribution (as can be obtained using multi-spacecraft in situ data). Previous in situ estimates of current density have used: Cluster, THEMIS and other spacecraft groups to study the distribution of the ring current for limited ranges of either radial profile, or MLT and MLAT variations. Here, we report on an extension to these studies using FGM data from MMS obtained during the period September 1, 2015 to December 31, 2016, when the MMS orbit and configuration provided good coverage. We employ the curlometer method to calculate the current density, statistically, to analysis the MLT distribution according to different geomagnetic conditions. Our results show the clear asymmetry of the ring current and its different characteristics under different geomagnetic conditions.
Unsupervised classification of ozone profiles from UKESM1 
Authors: Fahrin Fouzia , Jones Dan , Wu Yan , Archibald Alex
Published: March 2021

The distribution of ozone in the atmosphere is relevant for air pollution and radiative forcing. This distribution features complex spatial and temporal variability, set by balances between chemical production, loss processes, and advection. At present, the way in which ozone comparison regions are defined relies on somewhat arbitrarily drawn boundaries. In an effort to develop a more general, data-derived method for defining coherent regimes of ozone structure, we apply an unsupervised classification technique called Gaussian Mixture Modelling (GMM). We apply GMM to the output from the UKESM1 coupled climate model, including the historical run and two of the future climate projections. GMM identifies different ozone profile classes without using any latitude or longitude information, thereby highlighting coherent ozone structure regimes. We determine each of the model data set contains 9 groups of unique vertical classes. The classes depend on latitude, even though GMM was not given any latitude information. Polar and subpolar classes show low tropopause and low tropospheric ozone, and the tropical classes have high tropopause. Northern hemisphere high latitude classes have higher stratospheric ozone than southern hemisphere high latitude classes. We analyze how the spatial extent of the classes changes under different scenarios by comparing classes in SSP126 and SSP585 with a historical simulation. This work suggests that GMM may be a useful method for identifying coherent ozone regimes for comparing different model results and observational data.
Validation of Satellite-Retrieved CCN based on a Cruise Campaign over the polluted Northwestern Pacific Ocean 
Authors: Wang Yichuan , Zhu Yannian , Wang Minghuai , Rosenfeld Daniel , Gao Yang , Yao Xiaohong , Sheng Lifang , Efraim Avichay , Wang Juntao
Published: March 2021

In this study, a methodology for satellite retrieval of cloud condensation nuclei (CCN) in shallow marine boundary layer clouds is presented and validated. This methodology is based on retrieving cloud base drop concentration (Nd) and updrafts (Wb), which are used for calculating supersaturation (S). The Nd is the activated CCN concentration in clouds at a given S. The accuracy of the satellite retrieval is validated against the surface-measured CCN of a cruise campaign over the heavily polluted northwest Pacific Ocean. Clouds which are coupled with the sea surface have good agreement between satellite retrieved Nd and surface-measured CCN after performing corrections for temperature and adiabatic fraction. This study broadens the applicability of the methodology from aerosol-limited to contaminated regions. The validation shows ±30% accuracy in retrieving CCN of both clean and polluted regions. The results further demonstrate the strong dependence of marine shallow cloud Nd on CCN number concentrations and updraft, which allows us to further apply this methodology to quantify the relationships between CCN and cloud microphysical properties and reduce the uncertainty of radiation forcing caused by aerosol cloud interaction (ACI).
Statistical analysis of the accelerated H2O ions above 1 keV: the comet 67P/Churyumov–Gerasimenko observed by the Rosetta spacecraft.
Authors: Kotani Tsubasa , Yamauchi Masatoshi , Nilsson Hans , Stenberg-Wieser Gabriella , Wieser Martin , Bergman Sofia , Taguchi Satoshi , Götz Charlotte
Published: March 2021

The ESA/Rosetta spacecraft has studied the comet 67P/Churyumov-Gerasimenko for two years. Rosetta Plasma Consortium's Ion Composition Analyser (RPC/ICA) detected comet-origin water ions that are accelerated to > 100 eV.  Majority of them are interpreted as ordinary pick-up acceleration  by the solar wind electric field perpendicular to the magnetic field during low comet activity [1,2]. As the comet approaches the sun, a comet magnetosphere is formed, where solar winds cannot intrude.

However,  some water ions are accelerated to > 1 keV even in the magnetosphere [3]. Using RPC/ICA data during two years [4], we investigate the acceleration events > 1 keV where solar winds are not observed, and classify dispersion events with respect to the directions of the sun, the comet, and the magnetic field.  Majority of these water ions show reversed energy-angle dispersion. Results of the investigation also show that these ions are flowing along the (enhanced) magnetic field, indicating that the parallel acceleration occurs in the magnetosphere.

In this meeting, we show a statistical analysis and discuss a possible acceleration mechanism.

References

[1] H. Nilsson et al., MNRAS 469, 252 (2017), doi:10.1093/mnras/stx1491

[2] G. Nicolau et al., MNRAS 469, 339 (2017), doi:10.1093/mnras/stx1621

[3] T. Kotani et al., EPSC, EPSC2020-576 (2020), https://doi.org/10.5194/epsc2020-576

[4] H. Nilsson et al., Space Sci. Rev., 128, 671 (2007), DOI: 10.1007/s11214-006-9031-z 
Detection of slow-moving landslides in large area using InSAR phase-gradients stacking and YOLOv3
Authors: Fu Lv , Wang Teng
Published: March 2021

Landslide is one of the major geohazards that endangers the human society and threatens the safety of life and properties. In recent years, attentions have been paid to the Synthetic Aperture Radar interferometry (InSAR) for landslide monitoring with many successful applications. However, it is still difficult to effectively and automatically identify slow-moving landslides distributed in a large area because of phase unwrapping errors, troposphere turbulence and vegetation cover. Here we propose a method combining phase-gradient stacking and the widely-used neural network for tiny object detection: You Only Look Once (YOLOv3) to detect slow-moving landslides from large-scale interferograms. Using the time-series Sentinel-1 SAR images acquired since 2016, we develop a burst-based, phase-gradient stacking algorithm to sum up phase gradients along the azimuth and range directions of short-temporal-baseline interferograms. The stacked phase gradients clearly present the characteristics of localized surface deformation, mainly caused by slow-moving landslides, avoiding the errors result of multiple phase unwrapping in time-series analysis and atmospheric effects. We then train the YOLOv3 network with the stacked phase-gradient maps of known landslides to achieve the quick and automatic landslide detection. We apply our method in the middle section of the Yalong River in mountainous area of western China, with an area of 180,000 km2. In addition to the slides that have been published in the inventory, we identify many more slow-moving landslides that cannot be detected by traditional time-series InSAR analysis methods. Our results demonstrate the potential usage of the proposed methods for slow-moving landslide detection in large area, which can be applied before the time-consuming time-series InSAR analysis.
Persistent residential burning-related primary organic particles during wintertime hazes in North China: insights into their aging and optical changes
Authors: Liu Lei , Zhang Jian , Li Weijun
Published: March 2021

Primary organic aerosol (POA) is a major component of PM2.5 in winter polluted air in the North China Plain (NCP), but our understanding on the atmospheric aging process of POA particles and the resulting influences on their optical properties is limited. As part of the Atmospheric Pollution and Human Health in a Chinese Megacity (APHH-Beijing) programme, we collected airborne particles at an urban site (Beijing) and an upwind rural site (Gucheng, Hebei province) in the NCP during 13–27 Nov. 2016 for microscopic analyses. We confirmed that large amounts of light-absorbing spherical POA (i.e., tarball) and irregular POA particles with high viscosity were emitted from the domestic coal and biomass burning at the rural site and were further transported to the urban site during regional wintertime hazes. During the heavily polluted period (PM2.5 > 200 μg m−3), more than 60% of these burning-related POA particles were thickly coated with secondary inorganic aerosols (named as core–shell POA–SIA particle) through the aging process, suggesting that POA particles can provide surfaces for the heterogeneous reactions of SO2 and NOx. As a result, their average particle-to-core diameter ratios at the rural and urban sites in the heavily polluted period increased to 1.60 and 1.67, respectively. Interestingly, we found that the aging process did not change the morphology and sizes of POA cores, indicating that these POA particles are quite inert in the atmosphere and can be transported long distances. Using Mie theory we estimated that the absorption capacity of POA particles was enhanced by ~1.39 times in the heavily polluted period at the rural and urban sites due to the “lensing effect” of secondary inorganic coatings. We highlight that the “lensing effect” on burning-related POA particles should be considered in radiative forcing models and the governments should continue to promote clean energy in rural areas to effectively reduce primary emissions.
Morphological effects of a hydraulic lifting dam on the middle Fenhe River, China
Authors: Ni Yufang , Cao Zhixian , Qi Wenjun , Chai Xiangbin , Zhao Aili
Published: March 2021

Hydraulic lifting dams become increasingly popular in China for water storage, river landscaping and environmental restoration. Inevitably, dams influence riverine morphology. Unfortunately, current understanding of this topic has remained rather limited. Here, the morphological effects of a hydraulic lifting dam on the middle Fenhe River, China are investigated. This reach features a compound channel and floodplains, and the riverbed is mainly composed of silt that can be easily eroded, indicating potential significant bed deformation. A computationally efficient depth-averaged two-dimensional shallow water hydro-sediment-morphodynamic model is employed. Unstructured meshes are refined around dam structures to accurately present topography. The numerical predictions show discrepancies of morphological responses of the main channel and floodplains to different operation schemes of the hydraulic lifting dam. This work helps to support decisions on the management of hydraulic lifting dams on the middle Fenhe River and reveals a general pattern for the morphological impact of hydraulic lifting dam.
A means-corrected estimate for the Arctic sea-ice volume in 1990–2019
Authors: Uotila Petteri , Siponen Joula , Rinne Eero , Tietsche Steffen
Published: March 2021

Decadal changes in sea-ice thickness are one of the most visible signs of climate variability and change. To gain a comprehensive understanding of mechanisms involved, long time series, preferably with good uncertainty estimates, are needed. Importantly, the development of accurate predictions of sea ice in the Arctic requires good observational products. To assist this, a new sea-ice thickness product by ESA Climate Change Initiative (CCI) is compared to a set of five ocean reanalysis (ECCO-V4r4, GLORYS12V1, ORAS5 and PIOMAS).

The CCI product is based on two satellite altimetry missions, CryoSat-2 and ENVISAT, which are combined to the longest continuous satellite altimetry time series of Arctic-wide sea-ice thickness, 2002–2017. The CCI product performs well in the validation of the reanalyses: overall root-mean-square difference (RMSD) between monthly sea-ice thickness from CCI and the reanalyses ranges from 0.4–1.2 m. The differences are a sum of reanalysis biases, such as incorrect physics or forcing, as well as uncertainties in satellite altimetry, such as the snow climatology used in the thickness retrieval.

The CCI and reanalysis basin-scale sea-ice volumes have a good match in terms of year-to-year variability and long-term trends but rather different monthly mean climatologies. These findings provide a rationale to construct a multi-decadal sea-ice volume time series for the Arctic Ocean and its sub-basins from 1990–2019 by adjusting the ocean reanalyses ensemble toward CCI observations. Such a time series, including its uncertainty estimate, provides new insights to the evolution of the Arctic sea-ice volume during the past 30 years.
Assessing the relation of tree ring width with climate variables in South Korea through multi-gridded dataset
Authors: Salehnia Nasrin , Ahn Jinho
Published: March 2021

The Tree Ring Width (TRW) records are one of the main paleoclimate proxies that estimate the past climate variability. TRW measurements pave the way for scientists to produce sequences from various kinds of trees and reconstruct climate variables over the past years. Understanding the relation between TRW and climate variables in the past would help us analyze climate change events. This study has applied multi-gridded datasets to find the relations and model TRW data with different climate variables in South Korea's northeast. We utilized TRW data related to our case study that is available on the NOAA website; furthermore, we have checked three primary gauges, namely Agmerra (The Modern-Era Retrospective Analysis for Research and Applications), CRU TS4.03 (Climatic Research Unit Time-Series version 4.03), and APHRODITE's (Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation) for climate variables. In the first step, we have checked the relation between the gauges' precipitation data and observation TRW. According to the obtained efficiency criteria, CRU performed the best consequences. In the second step, we have tried to model observation TRW as a dependent variable and four climate variables of CRU (precipitation, minimum temperature, potential evapotranspiration, and diurnal temperature range) as independent ones over 1969-1998. We have created a linear regression model and determined the accurate coefficients for each climate variable. Besides, we have examined the observation TRW and modeled TRW data. The results showed that with R2  ≈ 0.40 and a p-value of 0.0323, the regression line was linearly significant at the 95 percent significance level. It represents that our model is acceptable. We will extend our model with Artificial Intelligence methods and try to apply other TRW stations in the future step. In this way, we may produce highly accurate models and fill the gaps for future researches.
Two-dimensional phase unwrapping integrating deep learning and minimal cost flow
Authors: Wu Zhipeng , Wang Teng , Wang Yingjie , Ge Daqing
Published: March 2021

InSAR can measure surface deformation in all-weather conditions and has been widely used to study landslides, land subsidence, and many geophysical processes. Since the phase of radar echo is measured in 2π rad modulo (wrapped), phase unwrapping is an indispensable step for InSAR, and its reliability directly determines the feasibility of deformation monitoring. However, temporal and spatial decorrelation often leads to severe noises, localized deformation or strong atmospheric turbulence may result in dense fringes, both making traditional unwrapping methods fail in acquiring continual unwrapped phases. Here, we present a deep convolutional neural network (DENet) to identify the probability of phase discontinuities between every two adjacent pixels in the interferogram and apply the probability as cost in the widely-used minimal cost flow solver to achieve phase unwrapping. To train the network effectively, we design a simulation strategy to generate sufficient training samples: the terrain-related phases are used as the background phases, and the deformation phases, atmospheric turbulence phases, and noises are superimposed to build the training samples. Unlike classical methods such as GAMMA and SNAPHU that use the coherence map as the quality index, we use the probability of phase discontinuities estimated by the DENet as the arc-cost of the minimum cost flow problem. We apply the proposed method to unwrap simulated and real interferograms and compare the results with 8 existing methods (including traditional and deep learning-based ones).  On the simulated data set, the root-mean-square error (RMSE) of the proposed method is lower than all the 8 existing methods. We also test different methods to unwrap the real Sentinel-1 interferograms and verified the reliability using ALOS-2 data with a nearly identical acquisition period. Our results show strong robustness and stability when unwrapping very large interferograms with complicated phase patterns. The proposed method takes advantages of both deep learning and traditional minimal cost flow solver, which can effectively unwrap interferograms with low coherence and/or dense fringes, providing strong potential for large-scale SAR interferometry applications.
The Late Cretaceous Asteroussia event as recorded in the Cyclades: a potential key to Western Tethys tectonic evolution
Authors: Yeung Sonia , Forster Marnie , Skourtsos Emmanuel , Lister Gordon
Published: March 2021

The Cretaceous arc system formed during closure of West Tethys closure has long been a research focus for crustal geometry and associated ore deposits. Understanding the Africa-Europe motion across time is the key to its resolution. Evidence as to the time that Tethys subduction initiated is preserved in subduction accreted tectonic slices such as in the Gondwanan basement terranes on Ios, Cyclades, Greece. 40Ar/39Ar geochronology in its granitoid basement and the structurally overlying garnet-mica schist tectonic slice identified a Late Cretaceous high pressure, medium temperature (HP–MP) metamorphic event. The timing and metamorphic conditions are comparable with geochronology and metamorphic conditions reported from other Cycladic islands. We suggest the northward extension of the Asteroussia crystalline terrane on Crete should therefore include the Ios basement tectonic slices, thus revising the regional geometry of the terrane stack. The northern part of the Hellenic terrane stack is overlain by individual Cycladic Eclogite-Blueschist terrane slices (e.g., on Ios) and the southern part is underplated by the tectonic units of the external Hellenides (Crete). To make such an architecture possible, we propose a 250-300 km southward jump of the subduction megathrust when the Ios basement terranes were accreted to the European terrane stack. Such a significant leap of the subduction megathrust supports a tectonic mode switch in which crust above the subduction zone was first subjected to shortening followed by a stretching event.  Accretion of the Asteroussia slices to the terrane stack likely commenced at or about ~38 Ma. During accretion, the already stretched and exhumed terranes of the Cycladic Eclogite-Blueschist Unit begun to thrust over the newly accreted Ios basement. The subduction jump had likely been accomplished by ~35 Ma, with rollback recommencing after a period of flat slab subduction followed by slab break off in the new subduction zone. This would allow explanation of the extreme extension that exhumed the Ios basement terrane, with the Asteroussia slices defining the core of the Ios metamorphic core complex, followed by the onset of Oligo-Miocene extension and accompanying magmatism in the Cyclades.
Predicting Groundwater Flow and Solute Transport in the Heterogeneous Aquifer Sandbox Using Different Parameter Estimation Methods
Authors: Jiang Liqun , Sun Ronglin , Liang Xing
Published: March 2021

Protection and management of groundwater resources demand high-resolution distributions of hydraulic parameters (e.g., hydraulic conductivity (K) and specific storage (Ss)) of aquifers. In the past, these parameters were obtained by traditional analytical solutions (e.g., Theis (1935) or Cooper and Jacob (1946)). However, traditional methods assume the aquifer to be homogeneous and yield the equivalent parameter, which are averages over a large volume and are insufficient for predicting groundwater flow and solute transport process (Butler & Liu, 1993). For obtaining the aquifer heterogeneity, some scholars have used kriging (e.g., Illman et al., 2010) and hydraulic tomography (HT) (e.g., Yeh & Liu, 2000; Zhu & Yeh, 2005) to describe the K distribution.

In this study, the laboratory heterogeneous aquifer sandbox is used to investigate the effect of different hydraulic parameter estimation methods on predicting groundwater flow and solute transport process. Conventional equivalent homogeneous model, kriging and HT are used to characterize the heterogeneity of sandbox aquifer. A number of the steady-state head data are collected from a series of single-hole pumping tests in the lab sandbox, and are then used to estimate the K fields of the sandbox aquifer by the steady-state inverse modeling in HT survey which was conducted using the SimSLE algorithm (Simultaneous SLE, Xiang et al., 2009), a built-in function of the software package of VSAFT2. The 40 K core samples from the sandbox aquifer are collected by the Darcy experiments, and are then used to obtain K fields through kriging which was conducted using the software package of Surfer 13. The role of prior information on improving HT survey is then discussed. The K estimates by different methods are used to predict the process of steady-state groundwater flow and solute transport, and evaluate the merits and demerits of different methods, investigate the effect of aquifer heterogeneity on groundwater flow and solute transport.

According to lab sandbox experiments results, we concluded that compared with kriging, HT can get higher precision to characterize the aquifer heterogeneity and predict the process of groundwater flow and solute transport. The 40 K fields from the K core samples are used as priori information of HT survey can promote the accuracy of K estimates. The conventional equivalent homogeneous model cannot accurately predict the process of groundwater flow and solute transport in heterogeneous aquifer. The enhancement of aquifer heterogeneity will lead to the enhancement of the spatial variability of tracer distribution and migration path, and the dominant channel directly determines the migration path and tracer distribution.
Variability of Temperature Extremes in Northwest Himalayas during Early 21st Century.
Authors: Aziz Farhan , Tariq Nadeem , Rahim Akif , Mahmood Ambreen
Published: March 2021

In recent years, extreme events and their severe damage have become more common around the world. It is widely known that atmospheric greenhouse gases have contributed to global warming.
A set of appropriate indicators describing the extremes of climate change can be used to study the extent of climate change. This study reveals the trends of temperature extreme indices on the spatial scale in the western part of Northwest Himalayas. The study is conducted at 13 climate stations lies at a different altitude of the study area.The Daily maximum and minimum temperature data during 2000--2018 of stations obtained from the Pakistan Meteorological Department (PMD) and Water and Power Development Authority (WAPDA). The 12 extreme temperature indices (FD, SU, TXx , TXn., TNx, TNn, TN10p , TN90p, TX10p , TX90p, CSDI, WSDI) recommended by ETCCDI (Expert Team on Climate Change Detection and Indices) are used to study the variabilities in temperature extremes. These indices are characterized based on amplitude, persistence, and frequency. The analysis is performed by using R package of extremes “RClimDEX”. The analysis shows the frequency of summer days (Su) and warm spells (WSDI) have increasing trends in the Southwest region, whereas the frequency of cold spells and frost days have decreasing trends observed in the Northern region of the study areas. The maximum and minimum values of daily maximum temperature (TXX, TXN) increase in the foothill area of the region and decreasing trends in the high elevation region. The day and night get cool in the Northwest region, whereas the days and nights are showing warmer trends in low elevation regions of the study area. Overall, the study concludes that the Northwestern parts have cool trends while South West and South eastern parts have warm trends during the early 21st century.

Key words:  Temperature Extremes, Northwest Himalayas, Trends, R-Climdex, Climate Change
Evidence for contemporaneous Deccan volcanic aerosol deposition preceding the K-Pg boundary at El Kef, Tunisia
Authors: Sillitoe-Kukas Steffanie , Humayun Munir , Adatte Thierry , Keller Gerta
Published: March 2021

The cause of the Cretaceous-Paleogene extinction remains debated between an asteroid impact and volcanism. Precise geochronology showed that the extinction coincided with a voluminous phase (Poladpur eruption) of Deccan volcanism (Schoene et al., 2019). Paleontological evidence indicates that microfossil diversity declined about 300,000 years before the K-Pg boundary, synchronous with the onset of Deccan volcanism (Keller et al. 2009). High concentrations of Ir in the K-Pg boundary supported the asteroid hypothesis but recent work indicates that siderophile accumulation at the K-Pg in El Kef is secondary (Humayun et al., this conf.). Here, we critically examine existing element data for the K-Pg boundary and examine new results at the El Kef site, Tunisia, for volcanogenic volatile element accumulation associated with the contemporaneous Deccan eruptions. In this study, we analyzed 60 elements by laser ablation ICP-MS in search of these volcanic aerosol enrichments in the K-Pg sediments at El Kef, Tunisia. A study of siderophile element distribution at global K-Pg sites found that the Ru/Ir ratio is sub-chondritic. Mixing of upper continental crust (Ru/Ir> CI) with a chondritic impactor fails to explain this trend. Volcanic aerosol emissions for Ir are well known but there is less data available for Ru. Relative emission rates of Ru were found to be lower than those of Ir for the Kudryavy volcano (Yudovskaya et al., 2008), so a possible explanation of the sub-chondritic Ru/Ir ratio observed in global K-Pg sites involves deposition of volcanic aerosols in sediments. We also modeled the effect of adding volcanic aerosols to sediments approximated compositionally as upper continental crust (UCC) to find that Re, Cd, Os and Ir are the first elements to become enriched in sediments by volcanogenic aerosol deposition. Sediments from El Kef below the K-Pg boundary are enriched in both Re and Cd. On a plot of Cd vs. Re, the K-Pg sediment from El Kef falls on a mixing line between volcanic aerosol (Erta Ale volcano) and UCC. Sediment at 3 cm above the K-Pg boundary has little enrichment of either Cd or Re, interpreted here to indicate that this sediment was deposited in the interlude between the Poladpur and the Ambenali eruption phases of the Deccan. The availability of chemical proxies of volcanogenic aerosol deposition in sediments enables direct correlation between fossil evidence and the contemporaneous intensity of volcanic outgassing, the likely destroyer of life by the Deccan eruptions (Keller et al., 2020).
Bedload export from an Alpine glacier inferred from seismic methods 
Authors: Mancini Davide , Dietze Michael , Jenkin Matthew , Miesen Floreana Marie , Müller Tom , Lane Stuart Nicholas
Published: March 2021

Environmental seismology is the discipline that uses ambient noise to detect and to measure geomorphic processes. The basic principle relies on the unique seismic signal, in terms of excited frequencies and amplitudes, generated by such processes which is then propagated and recorded to sensors (geophones). Recent developments of this technique are interesting for geomorphology because there is evidence that it can be used to study processes that are rare and difficult to measure, such as bedload transport in rivers. This is of particular importance for quantify bedload flux in proglacial streams. This paper focuses on using this method to quantify bedload export from an Alpine valley glacier. At present, there is no time-continuous measurement of bedload export in such settings. This is because objective measurement of bedload flux is a challenge task for both theoretical and practical reasons. Theoretically, the high variability of bedload transport means that measurements need to be continuous to identify when it happens and with which intensity. Practically, in order to know how to sample the signal through time, you need to know its variance a priori, which is commonly unsteady, and therefore needs to be sampled in order to know how to sample it. Direct manual sampling (e.g. with Helley-Smith samplers) have a serious disadvantage in this sense. Existing indirect methods (e.g. hydrophones and plate geophones) allow collection of continuous data but, at the same time, their installation can be difficult and expensive and they need to be carefully calibrated against manual samplings.

In the present study we used seismic data collected by out-of-stream geophones to infer bedload flux along an entire melt season (June - September) at the Glacier d’Otemma proglacial forefield, south-western Swiss Alps. Raw seismic data were inverted into sediment flux following the methodology developed in Dietze et al. (2019), to produce the first continuous dataset of bedload export from an Alpine glacier. The inversion model has been calibrated using statistical (i.e. sensitivity analysis) and direct (i.e. in situ active seismic survey) approaches.
Investigating marine heat waves with a coupled atmosphere-ocean regional climate model
Authors: Pontoppidan Marie , Mooney Priscilla , Tjiputra Jerry
Published: March 2021

Marine heat waves (MHW’s) exert a substantial impact on human life and ecosystems in the ocean. In the western part of the tropical Atlantic basin, coral reefs are impacted by such events, resulting in coral bleaching and subsequently loss of biodiversity. To mitigate future changes in MHW’s it is detrimental to increase our mechanistic understanding of these events, and this must be investigated on a local scale to understand the smaller scale driving processes of the heat waves, e.g. air-sea interactions, and the spatio-temporal extent on environmental drivers essential for the ecosystem processes.

Here we use a coupled ocean-atmosphere modelling system (COAWST), which includes the atmospheric model WRF and the ocean model ROMS (including the Fennel ecosystem module), to dynamically downscale an area consisting of the Caribbean Sea and the Gulf of Mexico. Our 12 km grid spacing resolves (at least partly) smaller scale phenomena and in combination with the coupling of the ocean and the atmospheric model, it ensures a skilled representation of the air-sea interactions which are important for MHW’s. We will show the results of this decadal climate simulation with regards to generation, evolution and persistence of the MHW’s.
Using machine learning to correct model error in data assimilation and forecast applications
Authors: Farchi Alban , Laloyaux Patrick , Bonavita Massimo , Bocquet Marc
Published: March 2021

Recent developments in machine learning (ML) have demonstrated impressive skills in reproducing complex spatiotemporal processes. However, contrary to data assimilation (DA), the underlying assumption behind ML methods is that the system is fully observed and without noise, which is rarely the case in numerical weather prediction. In order to circumvent this issue, it is possible to embed the ML problem into a DA formalism characterised by a cost function similar to that of the weak-constraint 4D-Var (Bocquet et al., 2019; Bocquet et al., 2020). In practice ML and DA are combined to solve the problem: DA is used to estimate the state of the system while ML is used to estimate the full model. 

In realistic systems, the model dynamics can be very complex and it may not be possible to reconstruct it from scratch. An alternative could be to learn the model error of an already existent model using the same approach combining DA and ML. In this presentation, we test the feasibility of this method using a quasi geostrophic (QG) model. After a brief description of the QG model model, we introduce a realistic model error to be learnt. We then asses the potential of ML methods to reconstruct this model error, first with perfect (full and noiseless) observation and then with sparse and noisy observations. We show in either case to what extent the trained ML models correct the mid-term forecasts. Finally, we show how the trained ML models can be used in a DA system and to what extent they correct the analysis.

Bocquet, M., Brajard, J., Carrassi, A., and Bertino, L.: Data assimilation as a learning tool to infer ordinary differential equation representations of dynamical models, Nonlin. Processes Geophys., 26, 143–162, 2019

Bocquet, M., Brajard, J., Carrassi, A., and Bertino, L.: Bayesian inference of chaotic dynamics by merging data assimilation, machine learning and expectation-maximization, Foundations of Data Science, 2 (1), 55-80, 2020

Farchi, A., Laloyaux, P., Bonavita, M., and Bocquet, M.: Using machine learning to correct model error in data assimilation and forecast applications, arxiv:2010.12605, submitted. 
First experimental estimation of the methane ebullition fraction in water column from the bottom to the surface: application for the East Siberian Arctic Shelf
Authors: Chernykh Denis , Kosmach Denis , Konstantinov Anton , Salomatin Aleksander , Yusupov Vladimir , Shakhova Natalia , Gustafsson Örjan , Gershelis Elena , Dudarev Oleg , Semiletov Igor
Published: March 2021

The key area of the Arctic ocean for atmospheric venting of CH4 is the East Siberian Arctic Shelf (ESAS). The ESAS covers >2 million square kilometers (equal to the areas of Germany, France, Great Britain, Italy, and Japan combined). This vast yet shallow region has recently been shown to be a significant modern source of atmospheric CH4, contributing annually no less than terrestrial Arctic ecosystems; but unlike terrestrial ecosystems, the ESAS emits CH4 year-round due to its partial openness during the winter when terrestrial ecosystems are dormant. Emissions are determined by and dependent on the current thermal state of the subsea permafrost and environmental factors controlling permafrost dynamics. Releases could potentially increase by 3-5 orders of magnitude, considering the sheer amount of CH4 preserved within the shallow ESAS seabed deposits and the documented thawing rates of subsea permafrost reported recently.

The purpose of this work is to determine the methane ebullition fraction in water column: from the bottom to the surface, which is a key to evaluate quantitively methane release from the ESAS bottom through the water column into the atmosphere. A series of 351 experiments was carried out at to determine the quantity of methane (and other greenhouse gases) delivered by bubbles of various sizes through a water column into the atmosphere. It has been shown for depth up to 22 m (about 30% of the ESAS) that pure methane bubbles, depending on their diameter and water salinity, transported to the surface from 60.9% to 85.3% of gaseous methane.

This work was supported in part by grants from Russian Scientific Foundation (№ 18-77-10004 to DCh, DK, AK, № 19-77-00067 to EG), the Ministry of Science and Higher Education of the Russian Federation (grant ID: 075-15-2020-978 to IS). The work was carried out as a part of Federal[ПW1]  assignment № АААА-А17-117030110031-6 to AS.
Jupiter’s Great Red Spot
Authors: Sanchez-Lavega Agustin
Published: March 2021

Jupiter’s Great Red Spot (GRS), is a giant anticyclone, the largest and longest-lived of all the vortices observed in planetary atmospheres. Perhaps observed for the first time in the 17th century, during its history, the length of the GRS has shrunk since 1879 from ~ 40,000 km to 15,000 km in 2020. The GRS is distinguished in the disk of Jupiter as an oval of intense red color, although this coloration changes in time depending on the interactions it undergoes with the meteorological formations and disturbances that flow in its surroundings. The maximum tangential rotation velocity is reached at the periphery of the oval with values from 120 ms-1 in 1979 to 150 ms-1 in 2020, decreasing gradually to the center of the vortex. The GRS, embedded within two jets that oppose in direction, oscillates in longitude with respect to its mean value with a period of 90 days and amplitude of 1°. In this lecture I will review our current knowledge of the GRS, in particular the structure of upper hazes and cloud, its dynamical properties, as well as ideas and models about its nature. Finally, the GRS will be compared with other Jovian vortices, putting into context their relationship with the jet streams pattern of the planet.