bluuebunny/crossref_metadata_2025 huggingface dataset:
Combining the deep Earth and lithospheric gravity field to study the density structure of the upper mantle
Authors: Root Bart , Fullea Javier , Ebbing Jörg , Martinec Zdenek
Published: March 2021

Global gravity field data obtained by dedicated satellite missions is used to study the density distribution of the lithosphere. Different multi-data joint inversions are using this dataset together with other geophysical data to determine the physical characteristics of the lithosphere. The gravitational signal from the deep Earth is usually removed by high-pass filtering of the model and data, or by appropriately selecting insensitive gravity components in the inversion. However, this will remove any long-wavelength signal inherent to lithosphere. A clear choice on the best-suited approach to remove the sub-lithospheric gravity signal is missing. 

Another alternative is to forward model the gravitational signal of these deep situated mass anomalies and subtract it from the observed data, before the inversion. Global tomography provides shear-wave velocity distribution of the mantle, which can be transformed into density anomalies. There are difficulties in constructing a density model from this data. Tomography relies on regularisation which smoothens the image of the mantle anomalies. Also, the shear-wave anomalies need to be converted to density anomalies, with uncertain conversion factors related to temperature and composition. Understanding the sensitivity of these effects could help determining the interaction of the deep Earth and the lithosphere.

In our study the density anomalies of the mantle, as well as the effect of CMB undulations, are forward modelled into their gravitational potential field, such that they can be subtracted from gravity observations. The reduction in magnitude of the density anomalies due to the regularisation of the global tomography models is taken into account. The long-wavelength region of the density estimates is less affected by the regularisation and can be used to fix the mean conversion factor to transform shear wave velocity to density. We present different modelling approaches to add the remaining dynamic topography effect in lithosphere models. This results in new solutions of the density structure of the lithosphere that both explain seismic observations and gravimetric measurements. The introduction of these dynamic forces is a step forward in understanding how to properly use global gravity field data in joint inversions of lithosphere models.
Power-to-Gas-to-Power is a competitive excess energy subsurface storage technology
Authors: Nakaten Natalie , Kempka Thomas , Kühn Michael
Published: March 2021

The underlying study addresses the ambitious German Federal Government’s objectives for the transition to a new energy era by proposing the implementation of a low-carbon energy system, improving the electricity grid as well as solar and wind power initiatives. Hereby, the “Power-to-Gas-to-Power” (PGP) approach combines the storage of excess energy from renewable power sources in the form of synthetic hydrocarbons, and their subsequent utilisation in a closed cycle to produce low-carbon electricity [1]. Based on the availability of two adjacent subsurface storage formations for CO2 and CH4 [2], hydrogen gained from excess solar and/or wind power is transformed into methane by means of CO2 captured on-site. When required, electricity is regained in a combined cycle plant by burning the CH4, with CO2 cycled in a closed loop.

In a show case study for the two German cities of Potsdam and Brandenburg, the PGP process chain was quantified to a total process efficiency of about 26%, exhibiting costs of 20 eurocent/kWh [2]. These previous assessments referring to energy production and storage technologies economics of the year 2012, have shown that PGP is generally economically competitive compared to conventional storage technologies [2]. Further results show that PGP can compete with global cost bandwidths of hydropower and compressed air storage as well as with upper limit COEs for solar thermal power and photovoltaic. However, PGP is not competitive compared to fossil fuel-based as well as onshore/offshore wind-based energy production [3]. However, cost trends related to energy production and storage technologies significantly correlate with fuel and commodity prices, CO2 emission charges as well as technology improvements that have been rapidly changing in the past few years. Thus, the purpose of the present study is to update the previously published PGP costs and elaborate a general overview on the current status of PGP on the global energy market.

[1] Kühn, M. (2013): System and method for ecologically generating and storing electricity. - Patent WO 2013156611 A1:

[2] Streibel, M., Nakaten, N. C., Kempka, T., Kühn, M. (2013): Analysis of an Integrated Carbon Cycle for Storage of renewables. - Energy Procedia, 40, pp. 202-211. DOI:

[3] Kühn, M., Nakaten, N., Kempka, T. (2020): Geological storage capacity for green excess energy readily available in Germany. - Advances in Geosciences, 54, 173-178. DOI:
The socio-ecologic aspects of nature-based solutions for coastal flooding mitigation
Authors: Inácio Miguel , Karnauskaitė Donalda , Mikša Katažyna , Kalinauskas Marius , Gomes Eduardo , Pereira Paulo
Published: March 2021

Coastal flooding has been historically mitigated through engineered artificial (grey) infrastructures such as breakwaters, dikes, and sea walls. However, these structures have a pervasive long-term impact on coastal ecosystems (e.g. sediment transport disruption), and require constant maintenance, and have little resilience to climate change (e.g. hurricanes, sea-level rise) related events.  Grey infrastructures failed to mitigate the effects of coastal floods, and the damages were significantly less in areas where healthy coastal ecosystems were present. This highlighted the role and contribution of coastal habitats to mitigate coastal floods and adapt to new conditions. The inefficiency of grey infrastructure to mitigate the impact of extreme events and following ecosystem-based management led to the development of the Nature-Based Solutions (NBS) concept. In the context of coastal flooding mitigation, to reduce the effects of storm surges, wave action, and erosion, NSB can be designed using (1) natural solutions (e.g., the creation of marine protected areas), (2) soft engineering and ecological restoration practices (e.g., mangrove plantation), and (3) hybrid solutions, which integrates natural and grey infrastructures (e.g. artificial reefs). NBS integrate multiple international environmental agendas, for their capacity to provide multiple co-benefits (e.g. recreation, fisheries). NBS are also key for supporting other agendas and global objectives: the Sustainable Development Goals (e.g. SDG14), Green/Blue economy, coastal resilient and climate-adapted coastal communities, biodiversity targets of the Convention for Biological Diversity and Circular Economy.

 

“Lithuanian National Ecosystem Services Assessment and Mapping (LINESAM)” No. 09.3.3-LMT-K-712-01-0104 is funded by the European Social Fund according to the activity “Improvement of researchers’ qualification by implementing world-class R&D projects” of Measure No. 09.3.3-LMT-K-712.
Using minimal spanning tree based ICA optimization for volcanic unrest determination
Authors: Ghosh Binayak , Motagh Mahdi , Haghshenas Haghshenas Mahmud , Walter Thomas
Published: March 2021

Over the years, various satellites like ERS-1, ERS-2 and Envisat has been in use for the interferometric capability for a wide range of geophysical and environmental applications. With the launches of Sentinel-1A and 1B satellites in 2014 and 2016 respectively, the availability of SAR data from every part of the world has been increased many folds. With short revisit times of 1-6 days, the Sentinel-1 and the planned Tandem-Land NISAR missions provide an unprecedented wealth of topography and surface change data using InSAR technique. Utilizing these Synthetic Aperture Radar (SAR) acquisitions, repeated approximately from the same point in space at different times, it is possible to produce measurements of ground deformations at some of the world’s active volcanoes and can be used to detect signs of volcanic unrest. Most of the existing traditional algorithms like Permanent Scatterer (PS) analysis and Small Baseline Subset (SBAS) technique are computationally extensive and cannot be applied in near real time to detect  precursory deformation and transient deformations. To overcome this problem, we have adapted a minimum spanning tree (MST) based spatial independent component analysis (ICA) method to automatically detect deformation signals of volcanic unrest. We utilize the algorithm’s capability to isolate signals of geophysical interest from atmospheric artifacts, topography and other noise signals, before monitoring the evolution of these signals through time in order to detect the onset of a period of volcanic unrest, in near real time. We demonstrate our approach on synthetic datasets having different signal strengths, varying temporally. We also present the results of our approach on the volcanic unrest of Mt. Thorbjörn in Iceland on 2020 and also the volcanic unrest of a volcano in Mexico from 2017 to 2019.
Day-to-day variations in paddy-residue burning and residential heating emissions control aerosol pollution peaks in rural north-west India
Authors: Pawar Harshita , Sinha Baerbel
Published: March 2021

November onwards, the poor air quality over north-west India is blamed on the large-scale paddy residue burning in Punjab and Haryana. However, the emission strength of this source remains poorly constrained due to the lack of ground-based measurements within the rural source regions. In this study, we report the particulate matter (PM) levels at Nadampur, a rural site in the Sangrur district of Punjab that witnesses rampant paddy residue burning, using the Airveda low-cost PM sensors from October to December 2019. The raw PM measurements from the sensor were corrected using the Random Forest machine learning algorithm. The daily average PM10 and PM2.5 mass concentration at Nadampur correlated well  (r > 0.7) with the daily sum of VIIRS fire counts. Agricultural activities, including paddy residue burning and harvesting operations, contributed less than 40% to the overall PM loading, even in the peak burning period at Nadampur. We show that the increased residential heating emissions in the winter season have a profound and currently neglected impact on ambient air quality. A dip in the daily average temperature by 1 ºC increased the daily emission of PM10 by 6.3 tonnes and that of PM2.5 by 5.8 tonnes. Overall, paddy harvest, local and regional paddy residue burning, residential heating emissions, ventilation, and wet scavenging could explain 79% of the variations in PM10 and 85% of the variations in PM2.5. Day to day variations in PM emissions from residential heating in response to the ambient temperature must be incorporated into emission inventories and models for accurate air quality forecasts.
Comparison of wind-induced air pressure fluctuations at sites with different land use
Authors: Mohr Manuel , Laemmel Thomas , Maier Martin , Kolbe Sven , Jung Christopher , Zeeman Matthias , Longdoz Bernard , Knohl Alexander , Thomas Christoph , Schindler Dirk
Published: March 2021

Previous studies showed at a forest site, that small air pressure fluctuations that are generated during periods of high wind speed significantly enhance topsoil gas transport, which is called pressure-pumping. The strength of these air pressure fluctuations can be described by the pressure pumping coefficient (PPC) which is defined as the mean absolute slope between two measurements (0.5 s) per 30 min interval. It was shown that at this site a quadratic relationship exists between the PPC and above canopy wind speed.

To investigate the variability of small air pressure fluctuations, high-frequency airflow and air pressure measurements were carried out at ten European and American sites with different land use (grassland, crop, forest, urban). The air pressure fluctuations were generally measured above the soil surface and airflow above the site-specific canopy (above trees in forests, on the top of a high building in the city). The measurements took place between 2016 and 2020 and commonly lasted at least one month per site.

Results show that the site-specific PPC increases in a quadratic relationship with above-canopy wind speed at all sites. The data was very close to a quadratic relationship at sites with rather uniform forests and level topography (R² > 0.92), while more complex sites revealed a larger scattering of this correlation (R² > 0.65).

At some sites, the PPC is also highly dependent on the prevailing wind direction. It is shown that the local surface roughness of the plant canopy can be excluded as a main driver of the PPC. Moreover, analysis of surface roughness parameters suggests that the topographic exposure around the measurement sites is responsible for the variability in the PPC.

However, due to the limited data availability and the complexity of the sites (topography, canopy, buildings), it cannot yet be ruled out that other effects have an influence on the PPC. In any case, from the results it can be inferred that wind-induced air pressure fluctuations responsible for pressure-pumping are detectable over a variety of natural and artificial surfaces. It must, therefore, be assumed that they have the potential to increase the diffusion-limited transport rate of trace gases in the soil as well as the soil-atmosphere exchange of trace gases over a large number of surfaces during periods of high wind speed.
Spatial prediction of soil thickness with Gaussian Process Regression using pedological knowledge described by partial differential equations
Authors: Rau Kerstin , Gläßle Thomas , Rentschler Tobias , Hennig Philipp , Scholten Thomas
Published: March 2021

Recently, there is a growing interest for the soil variable soil thickness in the soil science, geoscience and ecology communities. More and more scientists assume that soil thickness summarizes many different characteristics of the site that are important for plant growth, soil biodiversity and climate change. As such soil thickness can be an indicator of properties like water holding capacity, nutrient cycling, carbon storage, habitat for soil fauna and overall soil quality and productivity. At the same time, it takes a lot of effort to measure soil thickness, especially for larger and heterogeneous areas like mountain regions, which would require dense sampling. For these reasons, it is becoming increasingly important to spatially predict soil thickness as accurately as possible using models.
The typical difficulty in predicting variables in environmental sciences is the small number of samples in the field and resulting from this a small number of usable data points to train models in the spatial domain. One possibility to create valid models with sparse spatially distributed soil data is the combination of point measurements with domain knowledge. For soils and their properties such knowledge can be archived from related environmental data, for example, parent material and climate, and their spatial distribution neighboring the sample points. Frequently used machine learning methods for environmental modelling, especially in the geosciences, are the Gaussian Process Regression Models (GPRs), because a spatial correlation can already be implemented via the covariance kernel. One of the great advantages of using GPRs is the possibility to inform this algorithm directly with soil science knowledge. We can claim this knowledge in different ways.
In this paper we apply a new approach of implementing geographical knowledge into the Gaussian Processes by means of partial differential equations (PDEs), each describing a pedological process. These PDEs include information on how independent environmental variables influence the searched dependent variable. At first, we calculate for simple correlations between soil thickness and these variables, which we then convert into a PDE. As independent variables we initially use exclusively topographical variables derived from Digital Elevation Models (DEM) such as slope, different curvatures, aspect or the topographic wetness index. In this way, expert knowledge can adapt the GPR model in addition to the already existing assumption of spatial dependency given by prior covariance, where near things are more related than distant.
The algorithm will be applied to a data set from Andalusia, Spain, developed by Tobias Rentschler. Among land use information gained from remote sensing, it contains our target variable soil thickness.
A protocol for the evaluation of climate change impact models
Authors: Wagener Thorsten , Pianosi Francesca
Published: March 2021

Understanding the implications of climate change for our environment and subsequent services and disservices for nature and society is a key science challenge of our days. Simulation model chains that link the causality of climate-meteorology-hydrology-impact in some way or another are rapidly being developed and increasingly applied to understand the implications of future climate change projections. We discuss in our contribution the urgent need to simultaneously develop protocols to evaluate such models and their adequacy to ensure that scientific rigour is upheld in such analyses. We believe that such an evaluation protocol should consist of at least 3 evaluation stages to ensure a model is justified and its limitations are understood. These are: [1] Establishing an impact model as an adequate representation of our current understanding of the underlying system. [2] Establishing an impact model as an adequate model for the task at hand. [3] Establishing that dominant processes are adequately depicted to enable the assessment of intervention strategies. We argue that it is important to distinguish these stages because achieving stage 1 does not guarantee stage 2, while both stages 1 and 2 can potentially be achieved without ensuring stage 3. Different approaches to implement each of these stages exist and they range in rigour from simple (possibly simplistic) to complex (and therefore demanding). In our contribution we will use different impact modelling examples to discuss the current state of impact model evaluation, the limitations of current strategies and methods, and define additional development needs to obtain the scientific rigour we believe is needed for credible and robust impact assessment.
Observation of gliding tremors from the Gulf of Guinea might help solve over 50 year old mystery
Authors: Bruland Charlotte , Mader Sarah , Hadziioannou Céline
Published: March 2021

In the 1960's a peak in the seismic amplitude spectra around 26 s was discovered and detected on stations worldwide. The source was located in the Gulf of Guinea, with approximate coordinates (0,0), and was believed to be generated continuously. A source with similar spectral characteristics was discovered near the Vanuatu Islands, at nearly the antipodal location of the Gulf of Guinea source. Since it was located close to the volcanoes in Vanuatu, this source is commonly attributed to magmatic processes. The physical cause of the 26 s microseism, however, remains unclear.

We investigate the source location and evolution of the 26 s microseim using data from permanent broadband stations in Germany, France and Algeria and temporary arrays in Morocco, Cameroon and Botswana for spectral analysis and 3-C beamforming to get closer to resolving the source mechanism responsible for this enigmatic signal. We find that the signal modulates over time and is not always detectable, but occasionally it becomes so energetic it can be observed on stations worldwide. Such a burst can last for hours or days. The signal is visible on stations globally approximately 30 percent of the time. Our beamforming analysis confirms that the source is located in the Gulf of Guinea, as shown in previous studies, and that the location is temporally stable. Whenever the signal is detectable, both Love and Rayleigh waves are generated. We discover a spectral glide effect associated with the bursts, that so far has not been reported in the literature. 

The spectral glides last for about two days and are observed on stations globally. Although at higher frequencies, very long period tremors and gliding tremors are also observed on volcanoes as Redoubt in Alaska and Arenal in Costa Rica, suggesting that the origin of the 26 s tremor is also volcanic. However, there is no reported volcanic activity in the area where the source appears to be located.

 
Anisotropic permeability and fluid dispersion in pervasively fractured lavas, Rotokawa Geothermal System, New Zealand.
Authors: Kissling Warwick , Massiot Cecile
Published: March 2021

Geothermal provides nearly 20% of New Zealand’s electricity as well as increasing opportunities for direct use. In New Zealand’s ~20 high temperature geothermal systems, fluids flow dominantly through fractured rocks with low matrix permeability. It is important to understand the nature of these fracture systems, and how fluids flow through them, so that the geothermal systems may be more efficiently and sustainably used. Here we present fluid flow calculations in several distinct discrete fracture models, each of which is broadly consistent with the fracture density and high dip magnitude angle distributions directly observed in borehole image logs at the Rotokawa Geothermal Field (>300°C, 175 MWe installed capacity). This reservoir is hosted in fractured andesites. In general, fractures are steeply dipping, and the reservoir is known to be compartmentalized.

Our new code describes fluid flow through large numbers (e.g., thousands) of stochastic fracture networks to provide statistical distributions of permeability, permeability anisotropy and fluid dispersion at reservoir scale (e.g., 1 km2). Calculations can be based on both the cubic flow law for smooth-walled fractures and the Forchheimer flow model, which includes an additional term to describe the nonlinear drag (i.e. friction) in real fractures caused by surface roughness of the fracture walls.

Models with fracture density consistent with borehole observations show pervasive connectivity at reservoir scales, with fluid flow (hence permeability) and tracer transport predominantly along the mean fracture orientation. As the fracture density is varied, we find a linear relationship between permeability which holds above a well-defined percolation threshold. Permeability anisotropy is in general high (~10 to 15), because of the steeply dipping fractures. As fracture density decreases, mean anisotropy decreases while its variability increases. Significant dispersion of fluid occurs as it is transported through the reservoir. These fracture models will inform more traditional continuum models of fractured geothermal reservoirs hosted in volcanic rocks, to provide a better description of fluid flow within reservoirs and aid the responsible and sustainable use of that resource in the future.
Critical transitions in Earth system dynamics
Authors: Boers Niklas
Published: March 2021

It has been argued that several components of the Earth system may destabilise in response to gradually changing forcing such as rising atmospheric greenhouse gas concentrations and temperatures. Key examples of potentially unstable parts of the Earth system include the polar ice sheets and sea ice cover, the Atlantic Meridional Overturning Circulation, as well as tropical rainforests and monsoon systems. There are reasons to believe that the leading dynamical modes of these subsystems may essentially mimic bifurcations in low-order random dynamical systems. The stability loss on the way to critical transitions associated with such bifurcations typically leaves characteristic imprints in the statistics of time series encoding the dynamics of the system in question, which can hence serve as a proxy to assess the stability of the system. Here, we present recent advances in detecting stability loss along these lines and investigate proxy reconstructions and observations of several of the Earth system components that have been proposed to be at risk of destabilisation. We discuss the control parameters relevant for the different Earth system components and report on the posterior distributions of the critical thresholds, beyond which stability would be lost. 
Modelling carbon fluxes from New Zealand’s pastoral agriculture
Authors: Keller Elizabeth , Graham Scott , Hunt John , Wall Aaron , Schipper Louis , McMillan Andrew , Hidy Dora , Barcza Zoltán , Bukosa Beata , Mikaloff-Fletcher Sara
Published: March 2021

Grasslands cover half of New Zealand’s land area, with much of it consisting of pastoral agriculture systems of varying intensity. Carbon fluxes from grazed pasture are thus a crucial part of the national carbon budget. We have used Biome-BGCMuSo v6 to model national CO2 fluxes from grasslands, calibrated with eddy covariance measurements at grazed farms at various sites around the country. We discuss the challenges of scaling up site measurements to the national level and modelling the diversity of New Zealand's pastoral sector. Model outputs will subsequently be used as a prior estimate of CO2 fluxes in an atmospheric inversion to obtain a total carbon budget for New Zealand as part of the CarbonWatch-NZ project.
Extraction of Absolute Water Level in the Florida Everglades Using TanDEM-X Bistatic Science Phase Observations with a Large Perpendicular Baseline
Authors: Hong Sang-Hoon , Wdowinski Shimon , Kim Sang-Wan
Published: March 2021

High spatial resolution maps of relative water level changes in wetlands environment have been successfully generated using spaceborne interferometric synthetic aperture radar (InSAR) techniques. However, the wetland InSAR application has limited hydrological monitoring application, because it estimates water level changes not absolute water levels, which are used by hydrologists. TanDEM-X bistatic observations provide simultaneous phase measurements of water surfaces with a two-satellite constellation without temporal decorrelation. In this study, the TanDEM-X bistatic science phase observations with very large baseline (> 1.3 km) geometric configuration were evaluated to extract absolute water levels of the Everglades wetland in south Florida, U.S.A. Thanks to the large perpendicular baseline, spatial variation of water level surfaces with extremely low slope were estimated. We processed two datasets of TanDEM-X bistatic observations acquired on August 26 and 31, 2015. The perpendicular baselines are 1.43 km and 1.36 km and the ambiguity heights were calculated as 3.61 m and 3.90 m in each interferometric pair. The estimated absolute water level maps with 3.6 m and 7.4 m pixel spacing in range and azimuth directions (multilook factor of 4), respectively, show vast detailed variation of the water surfaces for each acquisition date. Hourly water level measurements obtained by stage stations, which are provided by the Everglades Depth Estimation Network (EDEN), were used for verifying the estimated absolute water levels. Some of stage stations, which are located in low interferometric coherence areas, such as dense vegetated and tree areas, were considered as outliers and were excluded from the comparison. The verification results show very good agreements (code of determination > 0.95) between the TanDEM-X derived absolute water levels and the stage station measurements. The root mean square error (RMSE) between the TanDEM-X results and stage records for the two datasets were 0.77 m and 0.66  m. Although, TanDEM-X bistatic observations have no temporal baseline, there are severe volume decorrelations over various tree types due to the very large perpendicular baseline. The TanDEM-L mission with longer wavelength of radar signal will enable us to generate more coherent interferometric phase observations over wetlands and, consequently, generate improved absolute water level maps.
Synoptic climatology of southern Indian Ocean and paleoclimate proxy interpretation
Authors: Udy Danielle , Vance Tessa , Kiem Anthony , Holbrook Neil , Curran Mark
Published: March 2021

Weather systems in the southern Indian Ocean drive synoptic-scale precipitation, temperature and wind variability in East Antarctica, sub-Antarctic islands and southern Australia.  Over seasonal to decadal timescales, the mean condition associated with combinations of these synoptic weather patterns (e.g., extratropical cyclones, fronts and regions of high pressure) is often referred to as variability in the westerly wind belt or the Southern Annular Mode (SAM). The westerly wind belt is generally considered to be zonally symmetric around Antarctica however, on a daily timescale this is not the case. To capture the daily variability of regional weather systems, we used synoptic typing (Self-Organising Maps) to group weather patterns based on similar features, which are often lost when using monthly or seasonal mean fields. We identified nine key regional weather types based on anomaly pattern and strength. These include four meridional nodes, three mixed nodes, one zonal node and one transitional node. The meridional nodes are favourable for transporting warm, moist air masses to the subantarctic and Antarctic region, and are associated with increased precipitation and temperature where the systems interact with the Antarctic coastline.  These nodes have limited association with the SAM, especially during austral spring.  In contrast, the zonal and mixed nodes were strongly correlated with the SAM however, the regional synoptic representation of SAM positive conditions is not zonally symmetric and is represented by three separate nodes.  These different types of SAM positive conditions mean that the commonly used hemispheric Marshall index often fails to capture the regional variability in surface weather conditions in the southern Indian Ocean. Our results show the importance of considering different synoptic set ups of SAM conditions, particularly SAM positive, and identify conditions that are potentially missed by SAM variability (e.g., extreme precipitation events). Our results are particularly important to consider when interpreting SAM or westerly wind belt reconstructions in the study region (from ice cores, tree rings, or lake sediments).  Here we present a case study using the synoptic typing results to enhance our understanding of the Law Dome (East Antarctica) ice core record, focussing on links to large scale modes of climate variability and Australian hydroclimate.  These results enhance the usefulness of ice core proxies in coastal East Antarctica and assist with determining where and how it is appropriate to use coastal East Antarctic ice core records for reconstructions of large scale modes of climate variability (e.g. SAM and ENSO) and remote hydroclimate conditions.
Relationship of EIT Waves Phenomena with Other Solar Phenomena
Authors: Verma Virendra
Published: March 2021

 In the present paper, we have studied the relationship between the Extreme Ultraviolet Imaging Telescope (EIT) waves phenomena with solar flares, coronal holes, solar winds, and coronal mass ejections (CMEs) events. The EIT/ SOHO instrument recorded 176 EIT events during the above period (March 25, 1997-June 17, 1998) and the EIT waves list was published by Thompson & Myers (2009). After temporal matching of EIT wave events with CMEs phenomena, we find that corresponding to 58 EIT wave events, no CMEs events were recorded and thus we excluded 58 EIT wave events from the present study. Out of 176 EIT wave events, only 106 are accompanied by CMEs phenomena. The correlation study of the speed of EIT wave events and CMEs events of 106  events shows poor correlation r= 0.32, indicate that the EIT waves and CMEs events do not have a common mechanism of origin, and also indicate that some other factor is working in the formation of  CMEs from EIT waves. Further, We have also matched the spatial matching EIT wave sources as indicated by Thomson & Myers (2009) with CHs and flares and found that CMEs appear to be associated with EIT wave phenomena and CHs.  Earlier Verma & Pande (1989), Verma (1998) indicated that the CMEs may have been produced by some mechanism, in which the mass ejected by solar flares or active prominences, gets connected with the open magnetic lines of CHs (source of high-speed solar wind streams) and moves along them to appear as CMEs. Most recently Verma & Mittal (2019)  proposed a  methodology to understand the origin of CMEs through magnetic reconnection of   CHs and solar flares.  In the present paper, we proposed a scenario/ 2-dimensional model, in which the origin of CMEs through reconnection of EIT waves and solar winds coming from the CHs and also found that the calculated CMEs velocity after reconnection of EIT waves and solar winds coming from the CHs are in very close to the observed CMEs linear velocity. We also calculated the value of the correlation coefficient between the observed linear velocity of CME events and the calculated value of CMEs velocity after reconnection and found the value as r=0.884. The value of correlation as r=0.884 is excellent and supports the proposed methodology.  Finally, we have also discussed the relationship of EIT wave phenomena with other solar phenomena, in view of the latest scenario of solar heliophysics phenomena.

 

 

References:

Thompson, B. J. & Myers, D. C. (2009) APJS, 183, 225.
Verma, V. K. & Pande, M. C. (1989) Proc. IAU Colloq. 104 Solar and Stellar Flares (Poster Papers), Stanford University, Stanford, USA, p.239.
Verma, V. K.(1998) Journal of Geophysical Indian Union, 2, 65.
Verma, V. K. & Mittal, N.(2019) Astronomy Letters, 45, 164-
Generation of two-band chorus waves in the Earth's outer radiation belt
Authors: Li Jinxing , Bortnik Jacob , An Xin , Li Wen , Angelopoulos Vassilis , Russell Christopher
Published: March 2021

Naturally occurring chorus emissions are a class of electromagnetic waves found in the space environments of the Earth and other magnetized planets. They play an essential role in accelerating high-energy electrons forming the hazardous radiation belt environment. Chorus typically occurs in two distinct frequency bands separated by a gap. The origin of this two-band structure remains a 50-year old question. Using measurements from NASA’s Van Allen Probes we report that banded chorus waves are commonly accompanied by two separate anisotropic electron components. We demonstrate, using numerical simulations, that the initially excited single-band chorus waves alter the electron distribution immediately via Landau resonance, and suppresses the electron anisotropy at medium energies. This naturally divides the electron anisotropy into a low and a high energy components which excite the upper-band and lower-band chorus waves, respectively. This mechanism may also apply to the generation of chorus waves in other magnetized planetary magnetospheres.
Toward Downscaling Storage-Discharge Dynamics: Training Long Short-Term Memory (LSTM) model for Simulating Nonlinear Storage-Discharge Relations at The Rum River Watershed, MN
Authors: Teng Pai-Feng , Nieber John
Published: March 2021

Flooding is one of the most financially devastating natural hazards in the world. Studying storage-discharge relations can have the potential to improve existing flood forecasting systems, which are based on rainfall-runoff models. This presentation will assess the non-linear relation between daily water storage (ΔS) and discharge (Q) simulated by physical-based hydrological models at the Rum River Watershed, a HUC8 watershed in Minnesota, between 1995-2015, by training Long Short-Term Memory (LSTM) networks and other machine learning (ML) algorithms. Currently, linear regression models do not adequately represent the relationship between the simulated total ΔS and total Q at the HUC-8 watershed (R2 = 0.3667). Since ML algorithms have been used for predicting the outputs that represent arbitrary non-linear functions between predictors and predictands, they will be used for improving the accuracy of the non-linear relation of the storage-discharge dynamics. This research will mainly use LSTM networks, the time-series deep learning neural network that has already been used for predicting rainfall-runoff relations. The LSTM network will be trained to evaluate the storage-discharge relationship by comparing two sets of non-linear hydrological variables simulated by the semi-distributed Hydrological Simulated Program-Fortran (HSPF): the relationship between the simulated discharges and input hydrological variables at selected HUC-8 watersheds, including air temperatures, cloud covers, dew points, potential evapotranspiration, precipitations, solar radiations, wind speeds, and total water storage, and the dynamics between simulated discharge and input variables that do not include the total water storage. The result of this research will lay the foundation for assessing the accuracy of downscaled storage-discharge dynamics by applying similar methods to evaluate the storage-discharge dynamics at small-scaled, HUC-12 watersheds. Furthermore, its results have the potentials for us to evaluate whether downscaling of storage-discharge dynamics at the HUC-12 watershed can improve the accuracy of predicting discharge by comparing the result from the HUC-8 and the HUC-12 watersheds.
Understanding the role of different geographical features in the hydrological response of humid mountainous areas through a stepwise clustering scheme
Authors: Yang Yaqian , Liu Jintao
Published: March 2021

In the mountainous basins with less anthropogenic influence, the hydrological function is mainly affected by climate and landscape, which makes it possible to measure hydrological similarity indirectly by geographical features. Due to the mechanisms of runoff generation can vary geographically, in this study, a simple stepwise clustering scheme was proposed to explore the role of geographical features at different spatial hierarchy in indicating hydrological response. Research methods mainly include (1) Stepwise regression was used to quantitatively show the correlation between 35 geographical features and 35 flow features and identify the important explanatory variables for hydrological response; (2) 64 basins were divided by stepwise clustering scheme, and the overall ability of the scheme to capture hydrological similarity was tested by comparing the optimal parameters; (3) The hydrological similarity of basin groups was measured by the leave-one cross validation of hydrological model parameters. The results showed that: (1) Rainfall features, elevation, slope and soil bulk density are the main explanatory variables. (2) The NSE of basin groups based on stepwise clustering is 0.64, reaches 80% of the optimal parameter sets (NSE=0.80). The NSE of 90% basins is greater than 0.5, 80% is greater than 0.6, and 49% is greater than 0.7. (3) In humid areas, the hydrological responses of the basins with more uniform monthly rainfall and more abundant summer rainfall are more similar, e.g., the NSE of Class 4 is 0.77. Under similar rainfall patterns, the hydrological responses of the basins with higher average altitude, greater slope, more convergent of shape and richer vegetation are more similar, e.g., the NSE of Class 3-2 is 0.72 and that of Class 1-2 is 0.70. In the case of similar rainfall patterns and landforms, the hydrological responses of the basins with smaller soil bulk density are more similar, e.g., the NSE of Class 3-2-2 is 0.80. In conclusion, the stepwise clustering enhances the interpretability of basin classification, and the effect of different geographical features on hydrological response can show the applicability of hydrological simulation in ungauged basins.
Timing and rate of exhumation of Central Sredna Gora Zone basement, Bulgaria
Authors: Balkanska Eleonora , Georgiev Stoyan , Kounov Alexandre , Peytcheva Irena , Tagami Takahiro , Sueoka Shigeru
Published: March 2021

Sredna Gora Zone in Bulgaria is confined between the Balkan fold-thrust belt to the north and the Rhodope metamorphic complex to the south. The pre-Mesozoic basement of the central parts of the zone consists of Variscan high-grade metamorphic rocks intruded by Late Carboniferous granitoid plutons. They are transgressively overlaid by Triassic epicontinental, arc-related Upper Cretaceous volcaniclastic and Paleocene continental deposits. The Paleogene-Neogene sediments of the Thrace basin cover unconformably the older rock sequences. The zone experienced several compressional and extensional events during the Alpine time followed by post-orogenic extension in the Cenozoic.

We performed apatite fission-track analysis on rocks from the central, topographically highest parts of the Sredna Gora Zone in order to constrain the cooling history of the Variscan basement. With this aim four granitic samples were collected at different altitude (between 565 and 1604 m) from the tectonically uninterrupted section along the slope of Sredna Gora Mountains. The samples were processed and analyzed in the newly established Low-Temperature Thermochronology Laboratory in Bulgaria using LA-ICP-MS technique.

The samples yield apatite FT ages between 41.6 ± 2.6 (the highermost sample) and 39.4 ± 3.1 (the lowermost sample). The obtained confined mean tracks lengths are between 12.81 and 14.06 µm with standard deviation between 0.99 and 2.11 µm. The Dpar values vary from 1.75 µm to 1.46 µm (with standard deviation of approx. 0.20 µm).

The obtained positive age-altitude correlation suggests indeed that the studied part of the basement has cooled as one single block. The apparent exhumation rate is estimated to 0.46 mm/year. However, the positive Dpar-age correlation implies that the age dispersion could be influenced by apatite kinetic variability and hence relatively different closure temperature for the analysed samples may be suggested. Therefore, we consider the estimated apparent exhumation rate as only the minimum possible rate. The thermal models of the analysed samples (using HeFTy software) also show moderate cooling rates in the period between 45 and 35 Ma. This cooling could be related to the period of post-orogenic denudation and extension during the Eocene, associated with formation of the Thrace basin to the south-southeast. This extensional event, known from the whole Balkan Peninsula, is well documented in the neighbouring Balkan fold-thrust belt and the Rhodope metamorphic complex from where much faster exhumation rates were reported.

 

Acknowledgements. The study is supported by the grant 04/9 funded by the National Science Fund, Ministry of Education and Science, Bulgaria.
Non-Monotonic Aerosol Effect on Precipitation over the ITCZ
Authors: Liu Huan , Guo Jianping , Koren Ilan , Altaratz Orit , Dagan Guy , Wang Yuan , Jiang Jonathan H. , Zhai Panmao , Yung Yuk L.
Published: March 2021

Aerosol effects on clouds’ microphysics and dynamics are still considered as an important open question that contributes a major uncertainty to climate research and prediction. Using 7 years of observational and reanalysis data, we show a non-monotonic trend in convective cloud properties and rain intensity as a function of aerosol optical depth (AOD). The invigoration effect shifts into weak suppression beyond an optimal AOD ( of ~ 0.3-0.4). Using a cloud model we explain this shift in trend as the result of a competition between two types of microphysical processes: cloud-core-based invigorating processes vs. peripheral suppressive processes. We show that the optimal AOD, for which cloud and rain reach their maximal values, depends on the environmental thermodynamic conditions and it is higher for more unstable or more humid conditions. Our findings improve the understanding of aerosol-cloud interaction and their link to environmental conditions. It can aid in the improvement of parameterizations of clouds in climate models.
A daily burned area mapping method using AVHRR time-series data
Authors: Lou Shuhan , Liao Yuanhong , Liu Yufu , Bai Yuqi
Published: March 2021

The study of complex interactions between fire and atmospheric dynamics of the earth system is drawing increasing attention in recent years, especially when fire seasons are extended due to global warming, where the historical daily burnt area data played a pivotal role in analyzing wildfire regimes change. Existing products could not fully meet the temporal requirements: daily burnt area data in global fire emissions database (GFED4) starts from mid-2000 using MODIS while ESA Fire Climate Change Initiative (FireCCILT10) Dataset from 1982 to 2017 is provided on a monthly grid.

Advanced Very High Resolution Radiometer (AVHRR) series of sensors are widely used to develop pre‐MODIS daily historical records. However, compared to MODIS, the AVHRR sensor has a lower radiometric and geometric quality and is missing Short Wave Infrared (SWIR) band. To address the data quality problem, this research study presents a time-series mapping method for daily burned area using AVHRR composite. Daily fire-sensitive indices are calculated to develop a time-series data composite which is masked by the burnable surface of GLASS_GLC land cover product. Then, Continuous Change Detection and Classification (CCDC) time-series model, which originally implemented on Landsat data monitoring land cover change, is revised to detect an abrupt change in the time-series data composite and remove noise, ensuring temporal consistency. The image of a time-series breakpoint is further classified using a spatial contextual method to distinguish biomass burning from other forest degradation change like a landslide and is used to generate burned area probability map.

The methodology is verified in California, US, where fuel aridity increased during 1984–2015 driven by anthropogenic climate change. The samples are collected based on the National Monitoring Trends in Burn Severity（MTBS）Burned Areas Boundaries Dataset from 1984 – 2018 and California Department of Forestry and Fire Protection's Fire and Resource Assessment Program (FRAP) fire perimeters from since 1950. Primary results show that the proposed method can effectively detect burned area on daily basis with CCDC algorithm reducing the complexity of change detection.
Wind Speed Parameterization and Turbulence Intermittency in the Roughness Sublayers over Urban Areas: a Wind Tunnel Study
Authors: Mo Ziwei , Liu Chun-Ho
Published: March 2021

The flow in inertial sublayer (ISL) is horizontally homogeneous where the Monin–Obukhov similarity theory (MOST) well describes the flux-gradient relationship.  In contrast, roughness sublayer (RSL) flow is highly inhomogeneous. Its dynamics is influenced by the length scale of individual roughness elements. This study presents an analytical solution to the mean wind profile for both ISL and RSL by adding a new function in the flux-gradient relationship to handle the RSL dynamics. The mean wind speeds measured in the wind tunnel experiments over a range of idealized and real urban geometries are well predicted by the new analytical solution. The root-mean-square errors (RMSE) are reduced over an order of magnitude compared with the conventional logarithmic law of the wall (log-law). Its key parameter, the RSL constant converges asymptotically to μ = 1.7 for urban setting which is different from that (μ = 2.6) for vegetation canopy. The RSL turbulence intermittency is revealed by higher-order moments of velocities, probability density function (PDF), quadrant analysis, and conditional sampling. Ejection Q2 (-u’’, +w”) and sweep Q4 (+u’’, -w”) dominate in both RSL and ISL but with different share. Unlike the ISL, Q2 occurs more frequently (but contributes less to momentum flux) than Q4 in the RSL. It is thus suggested that RSL turbulent transport is driven by occasional, fast motions of accelerating downward flow (Q4) and bulk, slow decelerating upward flow (Q2).