bluuebunny/crossref_metadata_2025 huggingface dataset:
Scenario-based Earthquake Early Warning empowered by NDSHA
Authors: Zhang Yan , Wu Zhongliang , Romanelli Fabio , Vaccari Franco , Jiang Changsheng , Gao Shanghua , Li Jiawei , Kossobokov Vladimir G. , Panza Giuliano F.
Published: March 2022

For the concept of next-generation Early Earthquake Warning (EEW), the core idea is to combine EEW with seismic hazard assessment. In other words, to perform rapidly the computation of seismic hazard after the occurrence of an earthquake is detected and then to issue accurate warning, including lead time and potential seismic hazard level, to different end-users, e.g., railway system, working nuclear power plants and precision surgery in progress. We propose a scenario-based EEW by using the physics- and scenario-based hazard assessment, well known as Neo-deterministic Seismic Hazard Assessment (NDSHA). NDSHA can reliably compute the physically possible maximum ground motion response, including Maximum Credible Earthquakes (MCEs). In the framework of NDSHA, the general unit of processing time ranges from minutes to seconds, depending on the size of the study area and on the amount of computations. When the structural spectral information is available, the processing time significantly drops to a few seconds. Accordingly, a NDSHA scenario-based EEW relies on a hazard database, made by a collection of Modified Mercalli Intensity (MMI) maps, prepared and stored in advance. The establishment of such a hazard database is to consider all possible earthquake scenarios around target source zones based on now-available geophysical knowledge. Taking Xianshuihe (XSH) fault as an example, the six steps of the procedure to build the necessary hazard database could be the following: (1) definition of seismogenic zone; (2) definition of the first scenario source; (3) determination of source parameters; (4) determination of structural models; (5) computation of synthetic seismograms from the first source; (6) repeat (1) ~ (5), to travel all sources. Steps 1 to 6 allows us to obtain final (3264 in our case) results, i.e., the MMI maps for the adopted earthquake scenarios, which should be well representative of the potential earthquakes related to XSH.

As a first-order approximation in the construction of the hazard database, we assigned a characteristic focal mechanism for each cellular scenario earthquake. Once the hazard database is available, effective warning can be quickly issued to different end-users by selecting the suitable MMI map in the hazard database.
Geodetic inference: a selection of some challenging topics
Authors: Teunissen Peter
Published: March 2022

In this presentation a kaleidoscopic overview of some geodetic inferential challenges and opportunities will be given. The topics addressed are (1) Interferometric inference; (2) Distributive computing; and (3) Predictive quality. They represent samples of fertile grounds for the typical researcher (PhD student and Postdoc alike) interested in geodetic data processing and modelling, and eager to take up a difficult challenge and/or looking for research opportunities that can make a difference.

Interferometric inference: Although considerable advances have been made in this field, particularly through the very successful global research in interferometric-GNSS, important challenges posed by our mixed-integer models remain. These challenges will be discussed, with a particular reference to distributional multimodality and integer-estimability of FDMA and LTE based carrier-phase systems.

Distributed computing: With data growth numerically straining conventional centralized approaches, complementary cooperative inferential capabilities are asked for. The opportunities of such principles are discussed and examples will be given of dividing estimation problems into easier-to-solve nodal problems which are then coordinated towards an improved, ideally optimal, solution by means of iterative schemes.

Predictive quality: As parameter estimation and statistical testing are typically combined in any geodetic inference, their interactions are to be taken into account when describing the quality of one’s model predictions. The challenges and intricacies that this brings are highlighted, whereby it is suggested that several of the existing validation and representation procedures need revisiting to ensure suitability of their quality descriptions.
A novel approach to systematically analyze the error structure of precipitation datasets using decision trees
Authors: Sui Xinxin , Li Zhi , Tang Guoqiang , Yang Zong-Liang , Niyogi Dev
Published: March 2022

Multiple environmental factors influence the error structure of precipitation datasets. The conventional precipitation evaluation method over-simply analyzes how the statistical indicators vary with one or two factors via dimensionality reduction. As a result, the compound influences of multiple factors are superposed rather than disassembled. To overcome this deficiency, this study presents a novel approach to systematically and objectively analyze the error structure within precipitation products using decision trees. This data-driven method can analyze multiple factors simultaneously and extract the compound effects of various influencers. By interpreting the decision tree structures, the error characteristics of precipitation products are investigated. Three types of precipitation products (two satellite-based: ‘top-down’ IMERG and ‘bottom-up’ SM2RAIN-ASCAT, and one reanalysis: ERA5-Land) are evaluated across CONUS. The study period is from 2010 to 2019, and the ground-based Stage IV precipitation dataset is used as the ground truth. By data mining 60 binary decision trees, the spatiotemporal pattern of errors and the land surface influences are analyzed.

 

Results indicate that IMERG and ERA5-Land perform better than SM2RAIN-ASCAT with higher accuracy and more stable interannual patterns for the ten years of data analyzed. The conventional bias evaluation finds that ERA5-Land and SM2RAIN-ASCAT underestimate in summer and winter, respectively. The decision tree method cross-assesses three spatiotemporal factors and finds that underestimation of ERA5-Land occurs in the eastern part of the rocky mountains, and SM2RAIN-ASCAT underestimates precipitation over high latitudes, especially in winter. Additionally, the decision tree method ascribes system errors to nine physical variables, of which the distance to the coast, soil type, and DEM are the three dominant features. On the other hand, the land cover classification and the topography position index are two relatively weak factors.
Soils with seasonal climates have highest potential to stabilize carbon by minerals in sub-Saharan Africa
Authors: von Fromm Sophie F. , Doetterl Sebastian , Butler Benjamin , Trumbore Susan , Six Johan , Aynekulu Ermias , Berhe Asmeret Asefaw , Haefele Stephan , McGrath Steve , Shepherd Keith , Winowiecki Leigh , Hoyt Alison
Published: March 2022

With climate and land use changes, it is becoming increasingly important to understand not only how much carbon is and will be stored in soils, but also how long this C will remain in soils. Estimates of C age can provide useful information about the timescales on which C will respond to such changes. It is generally accepted that the interaction of climate and soil mineralogy have a strong influence on C age. However, our current understanding is primarily based on findings from temperate regions and from small-scale studies. Large knowledge gaps persist in (sub-)tropical regions where soil processes are often understudied.

Here, we use a systematic continental-scale approach to better understand the processes controlling C age on a larger scale in these understudied soils. In total, 510 samples were analyzed for radiocarbon (Δ14C), consisting of topsoils (0–20 cm) and subsoils (20–50 cm) collected from 30 sites across 14 countries. The sampled soils are part of a comprehensive soil survey (AfSIS) for sub-Saharan Africa, for which soil mineralogy (based on X-ray powder diffraction) and soil chemistry were determined.

Soils with the youngest C ages are generally highly weathered, and are characterized by humid climates, high gross primary productivity (GPP), and a dominance of 1:1 clay minerals. In contrast, older C ages are either found in arid regions characterized by low C inputs and low mineral stabilization, or in seasonal climates, where GPP is high but a portion of the C is stabilized by 2:1 clay minerals and poorly crystalline minerals. Cultivation and erosion appear to play a secondary role at this large scale, but widen the range of C ages.

Our data suggest that soils from seasonal climate zones have the most favorable climatic and pedogenic conditions to stabilize and store C. Yet, they are also the most vulnerable climate zones according to future projections for sub-Saharan Africa. Understanding how the stabilizing minerals will react to climate change is key to understanding short and long-term changes in C storage and stabilization.
Water reuse and examples from the case of California
Authors: Tortajada Cecilia
Published: March 2022

Water resources are essential for every development activity, not only in terms of available quantity but also in terms of quality. Water scarcity, due to physical lack or pollution, has become one of the most pressing issues globally, a matter of human, economic and environmental insecurity. Wastewater, whose value had not been appreciated until recently, is increasingly recognised as a potential ‘new’ source of clean water for potable and non-potable uses, resulting in social, environmental and economic beneﬁts. This presentation will discuss the potential of reclaimed water (also known as reused water) to become a signiﬁcant source of safe water for drinking purposes and improved sanitation in support of the Sustainable Development Goals, with the example of California.
Public perception of droughts and water shortages and metropolitan willingness to pay for water saving measures to improve water security
Authors: Sone Jullian , Gesualdo Gabriela , Schwamback Dimaghi , Wendland Edson , Brouwer Roy
Published: March 2022

The increase in water demand and droughts have exacerbated water inequalities and weakened the economy worldwide. Nonetheless, droughts alone do not justify the severity of water scarcity events, leading to public water rationing and restrictions. It is of paramount importance to obtain a better understanding of how public perceptions of and attitudes towards drought adaptation strategies influence the severity and extent of impacts on water consumption. Furthermore, studies on the general public’s willingness to pay for mitigation and adaptation measures are key for the design and implementation of efficient and effective water management policies. This study aims to inform policy and decision-making by investigating people’s experiences, perceptions, and assessments of past water scarcity events to understand how these past events may have changed their attitudes and behaviour towards water availability and saving. Data were collected by surveying a sample of 800 residents in the Metropolitan Area of São Paulo (MASP) in South-eastern Brazil, and in Campo Grande in Midwestern Brazil. The MASP faced a severe drought from 2014 until and including 2015 due to a decrease in rainfall and human factors, including water resource mismanagement. This vulnerability frame is also observed in Campo Grande, where residents faced serious water rationing in 2016 and 2019. Our results show that more than 80% of the respondents think the frequency of drought periods increased over the last 10 years and will continue to increase in the next 10 years, and 95% of the respondents believe climate change is real. These results also corroborate the fact that 80% of the sample have faced water restrictions or rationing in the past, of which most lasted more than one day. The study provides policy and decision-makers with important information about the future design of payments for watershed services (PWS) to improve water security. However, one in every fifth respondent does not believe that a possible payment for water saving measures in the surrounding watersheds supplying the cities with drinking water would be invested by the responsible authorities to reduce future water restrictions and rationing and, therefore, improve water security. This reveals a considerable mistrust in the local, regional, and state governments responsible for water supply. Our findings provide important insights into relevant feedbacks between hydrological events such as droughts and societal vulnerability and response inserted into the present-day Brazilian cultural, socioeconomic, and political context, and the effectiveness of economic policy instruments like PWS.
Iceberg meltwater intrusions observed in Sermilik Fjord, Southeast Greenland
Authors: Lindeman Margaret , Straneo Fiamma , Singh Hanumant , Cenedese Claudia , Sutherland David , Schild Kristin , Duncan Dan
Published: March 2022

As much as half of the freshwater flux from the Greenland Ice Sheet enters the ocean through calving of icebergs into glacial fjords. Remote sensing studies have shown that substantial iceberg melt occurs within fjords, and models indicate that the resulting heat and freshwater fluxes affect fjord circulation and the properties of waters reaching the glacier terminus. Observations are needed to evaluate whether these models accurately represent the distribution of iceberg melt.

Repeat oceanographic surveys around a large iceberg in Sermilik Fjord show anomalously cold, fresh layers consistent with the expected properties of submarine ice melt. We interpret these features as intrusions of iceberg melt and characterize their properties and vertical distribution. We find that iceberg melt drives significant upwelling, with the vertical scale set by the ambient stratification, as predicted by theory and numerical simulations. Our results agree with recent studies suggesting that the typical melt parameterization likely underestimates melt rates in this setting.
A closer look at lithologic and structural features as a factor causing seismic amplification that could elevate landslide susceptibility 
Authors: Fadel Islam , Tanyas Hakan
Published: March 2022

In February 25, 2018 an earthquake of magnitude Mw 7.5 occurred in Papua New Guinea leading to approximately 10,000 landslides. The event was followed by a series of aftershocks and rainfall events that also triggered more than a thousand of landsides. Our analyses show that large landslides are abundant throughout the study area. We show that landslides concentrate, in particular, across the boundaries of specific rock units e.g., Sisa volcanics and Wongop sandstone or at highly stress zones related to the subducted tectonic activities in the region. The complex setup of the rough topography, the different geologic structural features, and the different properties of the lithological units make it interesting to understand the contribution of each parameter individually to the concentration of the landslides at specific unit boundaries or at specific structural features.

In this research, we run a serious of full waveform spectral element simulations using point sources of the earthquake and the aftershocks. We use 3D Earth models which mimic the lithological and structural settings as well as the steep topography of the study area of the Papua New Guinea. As a result, we aim at better understanding possible cause of seismic amplification that could occur along weakness surfaces. Specifically, we test if vertical variation of the geological units with different strength (and/or permeability) over steep hillslopes could lead to amplification of seismic waves. The results can shed the light on the complex nature of the landslides distribution associated with large earthquakes that leads to catastrophic societal and economical losses.
Probabilistic regional envelope curves in Europe
Authors: Bertola Miriam , Castellarin Attilio , Valtancoli Elena , Viglione Alberto , Blöschl Günter
Published: March 2022

Regional envelope curves represent the current level of information about the most extreme flood events observed in a region. In this study, we derive and compare regional envelope curves across European regions, with a multi-scale approach. A large flood database, containing more than 7000 annual maximum discharge series from gauges located all over Europe, is used for the analysis. Multiple spatial scales are adopted to take into account the uneven gauge density in the study domain. In each region, we derive the slope of the regional envelope curve and the envelope flood for a representative catchment of size 1000km2. Based on the framework of probabilistic envelope curves, we also make a probabilistic statement about the regional envelope curves in terms of its return period. Results show that the slope of the regional envelope curves varies substantially across European regions and the correlation between envelope flood and the estimated return period is investigated.
Impacts of the ENSO cycle on climate and coffee production in Colombia
Authors: Sanderson Michael , fox Cathryn , Hodge Katie , Cure José Ricardo , Rodríguez Daniel , Ponti Luigi , Gutierrez Andrew Paul
Published: March 2022

Colombia is the world’s third largest coffee exporter. The high altitude and rich soils of Colombia’s mountains and valleys create ideal conditions for growing coffee plants. The coffee industry in Colombia mostly consists of small, family-owned farms, and provides many hundreds of thousands of jobs in rural areas. Climatic conditions during the growing season strongly influence the quality and overall yields of coffee beans. Links between the ENSO cycle and coffee production will be investigated. Additionally, coffee crops in Colombia face a variety of threats originating from climate change, including loss of quality and increased prevalence of pests (e.g., the coffee berry borer, Hypothenemus hampei) and diseases (e.g., the coffee leaf rust, Hemileia vastatrix). High resolution climate data are needed to assess how the climate of the coffee growing areas could change and assist growers to adapt to these changes. The ability of three regional climate models (RCA4, RegCM4.3 and CRCM5) to reproduce observed teleconnections between the ENSO cycle and climate in coffee-growing areas of Colombia is also assessed. These regional climate model simulations were produced for the Coordinated Regional Dynamical Experiment (CORDEX) for the Central America, Caribbean, and Mexico (CAM) domain. They represent the highest resolution climate data available for Colombia. Projected changes in the ENSO cycle and possible impacts on coffee production will also be investigated. This study is believed to be the first to explicitly use the CAM-CORDEX results for Colombia.
Generalized Structure Function applied to Soil Water Content during surface and subsurface drip irrigation in a loamy soil.
Authors: Rodriguez-Sinobas Leonor , Zubelzu Sergio , Martín-Sotoca Juan Jose , Tarquis Alfonso Ana Maria
Published: March 2022

The spatial variability of soil water content (SWC) and its temporal evolution are two essential factors to optimize the irrigation efficiency. This work presents an application of the Generalized Structure Function (GSF) to analyse the SWC evolution during two types of drip irrigation: surface and subsurface. In this way, we will compare both types of irrigation.

The GSF has been normally applied on time series. In our context we have used is on transect series of SWC measured at two different soil depth and at different times. From this type of analysis, two parameters are calculated: Hurst Index (HI) and Multifractality (DH). A set of experimental runs were performed in two irrigated plots with either surface or subsurface drip irrigation. SWC was estimated through the cumulative temperature (Tcum) from a Distributed Temperature Sensor (DTS) recordings aided by the Active Heated Fiber Optic (AHFO) technique. The fiber optic cable was deployed at 5 and 25 cm underneath the soil in both plots. Soil was a loamy sand textures (77% sand, 16% loam and 7% clay), 982 kg·m-1 bulk density, 3.67 mm·min-1 saturated hydraulic conductivity and 62% porosity.

The SWC evolution during the experiments in subsurface irrigation presented an HI around 0.50 (random) and more constant than in surface irrigation. The spatial and temporal variability of data revealed a HI>0.50 (persistent character) at the upper layer of the surface irrigated plot caused by the unequal distribution of ponded water around certain emitters and a subsequent anti-persistent character (HI<0.50) at the bottom because of the heterogeneous infiltration. The DH values estimated from surface irrigated plot with wider variation range that those from subsurface irrigated and greater similarity between both depths in the subsurface irrigated plot.

The results are discussed from an agronomic point of view providing an insight into the required adaptation of both irrigation water depths and frequency to avoid water loss in either surface or subsurface irrigation systems.
Paleoproterozoic Cordilleran-Type Tectonics in central West Greenland
Authors: Guarnieri Pierpaolo , Rosa Diogo , Thrane Kristine , Kokfelt Thomas F. , Sørensen Erik V. , Baker Nigel
Published: March 2022

A new tectonic model is presented to explain the tectonostratigraphic evolution of the Paleoproterozoic Karrat Group in central West Greenland and the polyphase deformation, magmatism and metamorphism in the Rinkian orogen recorded in Paleoproterozoic rocks and Archaean complexes. The Karrat Group (from c. 71°00’ to 73°00’ N) formed in an intra-cratonic sag basin after c. 2000 Ma with basal quartzites of the Qaarsukassak and Mârmorilik formations unconformably overlaying Archaean gneisses of the Rae Craton. From 1950 to 1900 Ma a carbonate platform represented by the Mârmorilik Formation developed toward the south, while rift related alkaline volcanic rocks represented by the alkaline member of the Kangilleq Formation and syn-rift siliciclastic and volcaniclastic sediments of the Nûkavsak Formation were deposited to the north. The rifting was succeeded by a back-arc system, represented by the transitional member of the Kangilleq Formation. Concomitantly with development of the back-arc system, arc-related granitoids of the Prøven Intrusive Complex (PIC) intruded into and along the basal contact of the Karrat Group around 1900 Ma with major pulses at c. 1870 and c. 1850 Ma. The Karrat Group and the magmatic arc rocks underwent HT-metamorphism at c. 1830–1800 Ma during the collisional phase of the Rinkian orogen. The metamorphic grade increases from greenschist facies in the south, to granulite facies in the north, where the metamorphism is associated with migmatization and emplacement of the S-type Qinngua leucogranites. Extensive thrust emplacement and folding characterize the Rinkian orogen south of the PIC and the eastern boundary of the magmatic arc is reworked along a top to ESE shear zone post-dating the HT-metamorphism. The ESE-ward emplacement of allochthonous thrust sheets during an early stage of thin-skinned tectonics is followed by NE-ward emplacement of basement nappes and finally by a NW-SE compression stage resulting in tectonic inversion of basin normal faults.  The back-arc extension and Cordilleran-type magmatism were driven by eastward subduction of oceanic crust during the Trans-Hudson Orogeny resulting from the convergence of the Superior, Meta Incognita and Rae Archean cratons between 1870–1800 Ma. The Karrat Group north of the PIC together with the time-correlative Piling Group of Baffin Island (Canada) probably represented the passive margin succession of the Rae craton that evolved into a forearc setting during the Trans-Hudson Orogeny. The Rinkian orogen is an example of Cordilleran-type tectonics resulting from the deformation of the Rae continental margin intruded by magmatic arc granites during subduction, followed by HT-metamorphism in the upper plate and the structuring of a back-arc fold and thrust system antithetic to the subducting plate.
Advancing the U.S. global chemical weather forecasting capabilities with next-generation,UFS-based fully coupled prediction systems
Authors: Montuoro Raffaele , Clune Thomas L. , Silva Arlindo M. da , Baker Barry , Zhang Li , Pan Li , Bhattacharjee Partha S. , Wang Siyuan , He Jian , Heinzeller Dom , Ahmadov Ravan , Chawla Arun , Stajner Ivanka , Frost Gregory J. , Grell Georg A. , McQueen Jeff , Kondragunta Shobha
Published: March 2022

Recent NOAA collaborative efforts supported through the Unified Forecast System Research-to-Operations (UFS-R2O) Project have led to the development of advanced coupled systems to improve aerosol predictions on a global scale. These systems, integrated within the UFS framework, include online-coupled prognostic model components for atmosphere, ocean, sea ice, and waves, and rely upon state-of-the-science interoperable atmospheric physics schemes accessible via the Common Community Physics Package (CCPP) framework. Interoperability has been a key design element for those systems from the start, and thus it has also driven the incorporation of predictive aerosol processes. The approach to aerosol development within the UFS focuses on two primary outcomes: to build the next-generation upgrade to the currently operational Global Ensemble Forecast System (GEFS), and to create a research-oriented platform that allows developing and assessing the latest physical and chemical processes updates. In collaboration with NASA/GMAO, a novel aerosol component (UFS-Aerosols) was developed to succeed GEFS-Aerosols. This UFS component implements NASA’s 2nd generation GOCART model and brings the MAPL infrastructure layer into the UFS framework, enabling tighter collaborations with NASA and ensuring model interoperability across U.S. modeling centers thanks to its NUOPCcompliant interface. It also includes an updated FENGSHA dust scheme along with refinements to surface emissions. Furthermore, a CCPP-compliant implementation of aerosol processes based on GEFS-Aerosols was developed within the UFS framework to support and advance atmospheric chemistry research. This presentation will provide an overview of the architecture of each system as well as results from preliminary evaluations.
Dynamic origin of anomalous subsidence of Jurassic Ordos basin
Authors: Wan Neng , Liu Shaofeng , Liu Guangting , Li Xueyan
Published: March 2022

The Jurassic Ordos basin is generally considered an intracontinental basin characterized by rapid subsidence rate along western margin and slow subsidence rate within basin interior. However, the formation mechanism of Ordos basin was not yet well understood. Flexural backstripping of stratigraphic record spanning from 174-153Ma, along three well sections perpendicular to the western margin of Ordos basin clearly demonstrates that there were long wavelength anomalous subsidence components, termed residual subsidence, in addition to those induced by thrust loads and sediment loads. Flexural components exhibit similar spatial and temporal trends along three sections. Simulations demonstrates that the foredeep is only 80-100 km wide, corresponding to effective thickness of 15-20 km. Contribution by flexural component relative to cumulative subsidence decreases from 50-60% to -15% within foredeep from thrust front towards basin interior, while residual subsidence could account for 40-50% of cumulative subsidence for areas outboard extent of foredeep. From 174-153 Ma, residual subsidence increases from ~150 m to ~330 m, ~200 m to ~390 m, ~180 m to ~480 m in southern, middle and northern section respectively. Our results indicate that thrust loads could act as the dominant driver for subsidence of foredeep while other mechanism needs to be raised to explain the basin-wide anomalous residual subsidence. The general agreement regarding both magnitude and trends along all three sections between dynamic topography predicted by geodynamic models and residual subsidence separated from flexural modeling, indicates that the anomalous subsidence component might be of dynamic origin, related to subduction of paleo-Pacific plate initiated from latest Early Jurassic.
TERRA FORMA: Developing the observation platform of the Anthropocene 
Authors: Longuevergne Laurent , Elger Arnaud , Girard Virginie
Published: March 2022

The Anthropocene, a new geological period when human actions are altering the habitability of the Earth for all forms of life, raises new challenges in terms of knowledge integration that fragmented approaches cannot overtake. Due to complex interactions within geo-eco-socio-systems (GESS), a “whole system” approach is required to answer societal concerns around soil capital, water resources, chemical pressure and biodiversity.

To address these challenges, the TERRA FORMA project will design and test in-situ observation plateform coupling sensor viewpoints on human, biotic and abiotic dynamics. This project builds on pioneering and mature technological advances (optical sensors, 3D printing, IoT, AI) to design and probe a scalable network of smart sensors. We will develop a new generation of smart, connected, low-cost, low-impact and socially appropriated environmental sensors, adapted to field conditions, dedicated to capture the behavior, metabolism and trajectory of GESS emerging from states and fluxes of liquid, gas and solid matter and biota. These new technologies will contribute to shed light on “essential variables” for GESS and evaluate the descriptive and predictive potential of models over a wide range of contexts. TERRA FORMA gathers scientists, in an interdisciplinary effort at the crossroad of Earth, environmental, technological, computer and social sciences.

In this presentation, we will show how instrumental developments (spectroscopy, lab on a chip, …) and methodological developments (biogeophysics, …) contributes to the construction of the observation plateform.
The Hunga Tonga-Hunga Haʻapai hydration of the stratosphere
Authors: Millán Luis , Froidevaux Lucien , Manney Gloria , Lambert Alyn , Livesey Nathaniel , Pumphrey Hugh , Read William , Santee Michelle , Schwartz Michael , Su Hui , Werner Frank , Wu Longtao
Published: March 2022

Hunga Tonga-Hunga Haʻapai, a submarine volcano in the South Pacific, reached an eruption climax on 15 January 2022. The blast sent a plume of ash well into the stratosphere, triggered tsunami alerts across the world, and caused ionospheric disturbances. A few hours after the violent eruption, the Microwave Limb Sounder (MLS) measured enhanced values of water vapor at altitudes as high as 50 km - near the stratopause.
On the following days, as the plume dispersed, several MLS chemical species, including H2O and SO2, displayed elevated values, far exceeding any previous values in the 18-year record. In this presentation we discuss the validity of these measurements, the stratospheric evolution of the SO2 and H2O plumes, and, lastly, the implications of the large-scale hydration of the stratosphere by the eruption.
Sentinel-5P TROPOMI data application and their comparison with OIAP spectroscopic datasets on CO and NO2 columns
Authors: Rakitin Vadim , Gruzdev Alexander , Skorokhod Andrey , Kirillova Natalia , Fedorova Eugenia , Kazakov Artem
Published: March 2022

This study considers usage of high-resolution data on CO and NO2 of newest orbital spectrometer TROPOMI.
First, using our own software package Level 2 data (15 NetCdf files for every day) were converted to Level 3 (one daily mat-file) while maintaining spatial resolution. Then CO total content (CO TC) and NO2 tropospheric (NO2 TrC) and total content (NO2 TC) OFFL diurnal data were compared with OIAP ground-based measurements in Moscow and at Zvenigorod Scientific station (ZSS, Moscow province, 53 km West from Moscow) as well as with AIRS CO TC observations.
The character of dependence between ground-based and satellite data was chosen as linear:
Ugr = KUstl + A, were Ugr and Ustl are ground-based and satellite contents of an impurity, respectively; A is the constant.
High correlation between TROPOMI CO OFFL and ground-based CO TC measurements was obtained, with R~ 0.79-0.85, K~0.78-0.91, A~2.3-5.0*1017 molec/cm2 in dependence on orbital data resolution.
Correlation parameters depend on viewing azimuth angle VZA (the best correlation was obtained for VZA≤50º) and do not significantly depende on the Earth albedo.
For diurnal NO2 TrC OFFL for ZSS were obtained R~ 0.41-0.48, K~3.3-4.3, A~0.9-1.1*1015 molec/cm2and for NO2 TC OFFL R~0.59-0.61, K~6.7-7.0, A~ (-)0.76-0.86 *1015 molec/cm2.
Additional possibilities to calculate averaged spatial and trend distributions of different atmospheric species based on TROPOMI data using our original software are presented.  
The study was supported by Russian Science Foundation under grant №21-17-00210. NO2 data comparison was supported by the Russian Foundation for Basic Research, grant №20-05-00274.
Infilling Spatial Precipitation Recordings with a Memory-Assisted CNN
Authors: Meuer Johannes , Bouwer Laurens , Plésiat Étienne , Lehmann Roman , Hoffmann Markus , Ludwig Thomas , Karl Wolfgang , Kadow Christopher
Published: March 2022

Missing climate data is a widespread problem in climate science and leads to uncertainty of prediction models that rely on these data resources. So far, existing approaches for infilling missing precipitation data are mostly numerical or statistical techniques that require considerable computational resources and are not suitable for large regions with missing data. Most recently, there have been several approaches to infill missing climate data with machine learning methods such as convolutional neural networks or generative adversarial networks. They have proven to perform well on infilling missing temperature or satellite data. However, these techniques consider only spatial variability in the data whereas precipitation data is much more variable in both space and time. Rainfall extremes with high amplitudes play an important role. We propose a convolutional inpainting network that additionally considers a memory module. One approach investigates the temporal variability in the missing data regions using a long-short term memory. An attention-based module has also been added to the technology to consider further atmospheric variables provided by reanalysis data. The model was trained and evaluated on the RADOLAN data set  which is based on radar precipitation recordings and weather station measurements. With the method we are able to complete gaps in this high quality, highly resolved spatial precipitation data set over Germany. In conclusion, we compare our approach to statistical techniques for infilling precipitation data as well as other state-of-the-art machine learning techniques. This well-combined technology of computer and atmospheric research components will be presented as a dedicated climate service component and data set.
(encore abstract)  Ship drift and Automatic Identification System analysis used to monitor ocean surface currents
Authors: guichoux yann , le goff clement , boussidi brahim , mironov alexey
Published: March 2022

Accurate, high-resolution estimate of ocean surface currents is both a challenging issue and a growing end-user requirement. Yet, the global circulation is only indirectly monitored through satellite remote sensing; to benefit the end-user community (science, shipping, fishing, trading, insurance, offshore energy, defence), current information must be accurately constructed and validated from all relevant available resources. eOdyn develops since 2015 a transformative method to derive surface currents from ship motion and Automatic Identification System (AIS) data [1][2]. Currents, derived from AIS data, a complementary in- situ observing system so far under-exploited, have the potential to complete surface current picture with high- frequency part of ocean dynamics in areas with intensive marine traffic activities. The presentation will focus on recent results, using AIS data collected thanks to low earth orbit satellites and ship behaviour analysis to produce relayable high resolution ocean surface current measurements to monitor different currents of interest (off the south African coastline, the Indian ocean and the Mediterranean sea). Comparisons between AIS derived surface currents and independant data sets from altimetry satellites, HF radars and drifters will be presented. The use of this new technology to complement exisiting measurement systems will be demonstrated. [1] Clément Le Goff, Brahim Boussidi, Alexei Mironov, Yann Guichoux, Yicun Zhen, Pierre Tandeo, Simon Gueguen, and Bertrand Chapron. Monitoring the Greater Agulhas Current with AIS Data Information, Published in Journal of Geophysical Research: Oceans, 2021. [2] Guichoux, Y., Lennon, M. and Thomas, N., Sea surface currents calculation using vessel tracking data, Proceedings of theMaritime Knowledge Discovery and Anomaly Detection Workshop. Michele Vespe and Fabio Mazzarella. JRC Conference and Workshop Reports, pp.31-35, 2016.  
Historical analysis of large reservoir storage resilience and vulnerabilities in CONUS
Authors: Steyaert Jen , Condon Laura
Published: March 2022

There are over 2,000 large reservoirs with a storage capacity greater than 1 million cubic meters (MCM) in the contiguous United States (CONUS). While many of these structures are documented in static datasets that include spatial locations and general characteristics (such as maximum storage capacity), there has previously been no comprehensive dataset of historical reservoir operations. To remedy this gap, we have assembled ResOpsUS, the first national dataset of historical reservoir operations. ResOpsUS contains historical time-series of storage, inflow, outflow, elevation, and evaporation data for 679 large reservoirs in CONUS. Here we use the unique ResOpsUS dataset to analyze storage trends over the last 40 years, identify potential causes of regional differences in reservoir variance and evaluate the relationship between meteorological drought and reservoir storage. Our preliminary analysis demonstrates that reservoir storage capacity in CONUS hit a limit in the early 1980s and no longer increased. Additionally, reservoir storage has decreased over the past 20 years with the magnitude of decrease greater in more arid regions.  Finally, correlations between precipitation and reservoir storage depict more direct relationships in wetter climates compared to drier climates where reservoirs are a necessary water supply during dry periods and thus storage in drier years may be higher than in wetter years.
Antarctic ice tongue collapse triggered by loss of stabilizing land-fast sea ice
Authors: Gomez Fell Rodrigo , Rack Wolfgang , Purdie Heather , Marsh Oliver
Published: March 2022

The complete length of Parker Ice Tongue (18 km or 41 km2) calved in March 2020. This event occurred at the same time as repeated full summer break-outs of surrounding land-fast sea ice. Our results showed that periods of continuous ice tongue growth coincided with extended periods of land-fast sea ice coverage for at least the past 60 years. We also found that seasonal variations in the ice tongue dynamics were linked to variations in the local land-fast sea ice extent. A complete Antarctic ice tongue calving right at the grounding line has not been reported before.

Based on the analysis of satellite images and aerial photographs we determined Parker Ice Tongue length variations for the last 65 years. We found that the average growth of Parker Ice Tongue has been ~193 m/y-1. If we assume a constant growth rate, a break-off event of the magnitude observed has not occurred in the last 169 years.

We used a Sentinel-1 SAR image sequence to create a 2017-2020 time series of surface ice velocities. We found a significant inverse correlation between fast ice extent and ice tongue velocities (R= -0.62; R2=0.39). The short summer period, characterized by decreased land-fast sea ice extent, showed around 11% higher velocities compared to winter. This supports the idea that fast-ice extent can influence ice tongue dynamics seasonally.

Here we showcase the vulnerability of Parker Ice Tongue once left exposed to oceanic processes, which poses questions about the fate of other ice tongues if land-fast sea ice decreases more broadly in the future.
How to define the interplay between different instabilities excited within the foot of a supercritical shock : 2D PIC simulations
Authors: Muschietti Laurent , Lembege Bertrand , Decyk Viktor
Published: March 2022

In supercritical shocks a substantial fraction of ions is reflected at the steep shock ramp. The beam of reflected ions carries a considerable amount of energy and momentum. As a consequence, different plasma populations can co-exist within the same foot region, which constitutes a source of micro-instabilities excited by the relative drifts between incoming ions, reflected ions, and electrons across the ambient magnetic field Bo . With the help of a spectral periodic 2D PIC code, we investigate the resulting micro-turbulence. Three different waves with different frequency/wave number ranges can be excited simultaneously: Bernstein waves and whistler waves near the lower-hybrid frequency as well as the electron cyclotron frequency. The present work is a 2D extension of a previous analysis (Muschietti et Lembege, Ann. Geophys. 2017) and allows to self-consistently include the mutual interaction between the different instabilities/waves which propagate in different directions with respect to Bo and are at different stages of their respective linear/nonlinear phases. In order to clarify their intricate synergies, a new filtering procedure (low or high pass filter of a given wave number range) has been developed. Taking thus advantage of the spectral nature of the code, we can include/exclude at will the impact of a given instability on the other ones. We have performed several times the simulation with exactly the same initial conditions yet with different filtering ranges. The procedure allows us to illuminate the role played by each instability in the scenario when all are included. Recent results will be presented. 
Groundwater balance estimators using Machine Learning 
Authors: Janardhanan Sreekanth , Pagendam Dan , MacKinlay Dan , Pena-Arancibia Jorge , Mainuddin Mohammed
Published: March 2022

Groundwater use for irrigation, stock and domestic purposes from shallow unconfined aquifers is rarely metered in most parts of the world despite significant increase in the rate of use in the recent decades. Most aquifers systems are poorly characterized and monitored rendering assessment of groundwater balance and informed management decision making difficult.

Advances in automated data collection through remote sensing and other technologies in the recent years, makes available pertinent data sets that can indirectly inform groundwater balance from which groundwater recharge and discharge can be estimated. Assimilating such data sets using traditional means would require simulating the physics across multiple domains including climate, surface water, unsaturated and saturated zones and may be untenable in most decision-making contexts.

Recent advances in Artificial Intelligence and Machine Learning techniques (AI/ML) have created the opportunity to estimate groundwater balance components probabilistically by considering the correlation and causal relationships with other climatic, hydrological and geospatial variables for which data sets are readily available, for example estimates of actual evapotranspiration from remote sensing data. Such machine learning-based models need not necessarily be underpinned by the explicit solutions of governing equations pertaining to the physical processes involved across multiple domains. These ML-based models can be used either independently or in combination with physically based models for retrospective or predictive assessments of groundwater balance components and quantification of recharge and discharge components including historical pumping rates from an aquifer.

This study develops ML-based groundwater balance estimators using machine learning based on suitable supervised learning algorithm for a selected unconfined aquifer system that spans across 16 districts in northwest Bangladesh region. The study uses daily precipitation data, evapotranspiration estimates using Moderate Resolution Imaging Spectroradiometer (MODIS) data, interpolated river stages, and weekly observed water levels from monitoring bores to train, test and validate a Deep Neural Network model implemented using PYTORCH.

Simulated groundwater levels obtained using the trained and tested ML models are used to estimate long-term groundwater storage changes in region and are compared to estimates from a numerical groundwater MODFLOW model developed and history-matched using Flopy and PEST++ frameworks. Both the ML and MODFLOW models are implemented for a rectangular grid with 1500 m × 1500 m cells.  The workflow scripted using PYTORCH and Flopy libraries enabled the ready comparison of ML and numerical models’ outputs and evaluate the applicability of ML models for groundwater balance simulation.

 
Increasing Microbial Biomass is the Key to Sequestering Carbon in Soil. 
Authors: Fitzpatrick Judith
Published: March 2022

Reducing the 20% of CO2 contributed by agricultural practice and increasing carbon sequestration (CSQ), i.e., the storage of soil organic carbon (SOC) in soil, are strategies for remediation of global warming that could have enormous impact. 

The methods proposed for monitoring the success of CSQ have focused on measurement of SOC by dry combustion. SOC is the stably stored bodies of dead microbes and the by-products of microbial digestion, Dry combustion has 2 big drawbacks, high cost and low sensitivity because SOC increases slowly and about 10 years are required to confirm CSQ.  Too bad if you were on the wrong track!

Approximately 90% of farms in the U.S. are conventional, with typically less than 100 ug microbial biomass carbon/g of soil (MBC).  Regenerative farming increases this to at least 200 ug MBC/g soil.  For every 100 ug MBC / g increase, 80 million metric tons of microbial carbon is sequestered, which corresponds to 293 million metric tons of CO2 – 50 times the amount of CO2 emitted per year in the U.S (~5 million metric tons).  Moreover, as SOC is 60-80% the bodies of dead microbes, as long as the increase is maintained or increased, CSQ is increasing and many other MBC benefits such as decreased erosion, increased drought resistance and decreased need for pesticides are being attained.

The microBIOMETER® test enables using MBC as a standard as it replaces expensive MBC testing and includes fungal to bacterial ratio (F:B).  It can be done on site or in labs, correlates 92% with Chloroform Fumigation Extraction (CFE) and costs less than $10.  Data is collected via, smart phone app, analyzed and stored in the cloud. Project management software is also provided. We have demonstrated that the F:B ratio correlates >90% with the inverse of the metabolic quotient (q):  numerous studies confirm that a high F:B ratio and low q are associated with CSQ.

Adoption of MBC as a standard for carbon sequestration progression can improve implementation of regenerative agriculture and CSQ.

 