bluuebunny/crossref_metadata_2025 huggingface dataset:
Understanding landscape mass-wasting in response to geophysical forcings to constrain long-term erosional budgets
Authors: Marc Odin
Published: March 2022

Landsliding is the dominant process of sediment production in active mountain range. Various geophysical forcing are triggering widespread landsliding over different timescales.

Though less continuous than climatic forcing, shallow earthquakes are an important trigger of mass wasting. PGA not only controls the spatial density of landslides (Meunier 2007) but also their size (Valagussa 2019) and their location in the landscape (Milledge 2019), with implications still to be explored. Combining simple seismological scalings with landscape characterization allows to relate EQ sequences to landslide flux, over various timescales (Marc et al., 2015, 2016, 2017).

Intense rainfall is another recurrent trigger. Landslide catalogue associated with rainfall events are multiplying and showing specific relations with rainfall and topography (Marc et al 2018), in particular, landslide scar appear unrelated to saturation index (Emberson et al., 2021), and in well constrained cases they seem to relate better to rainfall anomaly (ie relative to local extreme rainfall) than to total event rainfall (Marc et al 2019a, in Review).

These triggers can be combined for a given mountain range, such as the Nepalese Himalayas (Marc et al., 2019b). Here we combined a fine characterization of the landslide frequency size distribution for EQ and monsoon rainfall to derive a long-term erosional flux. Accounting for a distribution of EQ properties and the frequency of giant paleolandslides we obtain an erosion rate consistent with the thermochronometric exhumation rate. Recent work has shown that the monsoon strength variations could also modulate the landslide response and that landsliding caused by extreme daily rainfall could also be isolated (Jones 2021), which could allow to refine and better understand how this budget has changed in the past.

Last, we remind that, large, deep seated landslides remain an important and understudied challenge. Indeed, they are poorly correlated to rainfall properties (either the monsoon (Marc et al 2019b, Jones 2021) or the rainfall anomaly from large typhoons (Marc et al., 2019a). However, they may be a dominant contributor to erosion and sediment volumes, and their control, likely related to mechanical strength degradation, should be investigated urgently.
South Atlantic Convergence Zone as Rossby Wave Source During Strong El Niño
Authors: Braga Hugo , Ambrizzi Tercio
Published: March 2022

The South Atlantic Convergence Zone (SACZ), which extends from the Amazon to the southwestern South Atlantic, is one of the major precipitation systems in South America and has an important socioeconomic impact for Brazil. This study suggests the possibility of SACZ to act as a Rossby wave source using numerical simulations from a simple baroclinic model under strong El Niño basic state. Sixteen days after the perturbation, it is possible to observe wave propagation inside the subtropical latitudes of the northern hemisphere. The simulation is performed during the strong El Niño in 2015/16 austral summer, which has a intense westerly zonal flow and stationary wavenumbers 6-10 in the equatorial Atlantic region. The Rossby wave starts in the southeast Brazil, crosses the Atlantic Ocean and, embedded in the subtropical jet of the north hemisphere, extends to the subtropical latitudes over the African and Asian continents. According to the present analyses, SACZ may sometimes act as interhemispheric Rossby wave source, enabling a connection between South America and subtropical latitudes in north hemisphere over 16 days, providing there is westerly flow that allows wave propagation over the equatorial Atlantic Ocean.
The importance of baseline methods for the consistent estimation of regional and global emissions from inverse modeling
Authors: Vojta Martin , Thompson Rona , Plach Andreas , Stohl Andreas
Published: March 2022

Inverse modeling provides a powerful statistical tool to verify national greenhouse gas (GHG) emission inventories by making use of in-situ atmospheric observations. Regional inversions are often based on atmospheric transport simulations with Lagrangian Particle Dispersion Models (LPDMs), where a large number of virtual particles are released from observation sites and traced backward for a limited amount of time to establish a relationship between atmospheric concentrations and emission sources within the simulated period. In order to account for all emissions prior to this simulation period, which also contribute to the corresponding observations, a baseline needs to be defined. This baseline definition is a crucial task, bearing a lot of uncertainties. Most studies investigating halocarbons use statistical methods to calculate the baseline by selecting low concentration observations at individual stations. In this study we show that statistical baseline methods have large systematic problems, that accumulate with increasing backward simulation periods and lead to a non-negligible underestimation of emissions that systematically increases with the length of the backward simulation time. As an alternative, we present a global distribution based (GDB) approach, where baseline concentrations are determined directly from global concentration fields at the termination points of the backward trajectories. These global fields are simulated with the FLEXible PARTicle dispersion chemical transport model (FLEXPART CTM) using a nudging routine to push modeled concentrations towards observed concentrations. We illustrate that this method is fully consistent with the length of the backward simulation, has the ability to account for meteorological variability, and leads to inversion results, that agree well with global emissions calculated with a simple box model.
Reconstructing Cordilleran Ice Sheet stability in western Canada during the Last Deglaciation
Authors: Darvill Christopher , Menounos Brian , Goehring Brent , Lesnek Alia
Published: March 2022

The Cordilleran Ice Sheet in western North America was of comparable size and topographic setting to the modern Greenland Ice Sheet and exhibited similar dynamics. Ice streams channelled rapid flow and the western ice margin terminated in both marine and terrestrial environments. Reconstructing Cordilleran Ice Sheet retreat can therefore provide a helpful analogue for how the Greenland Ice Sheet may respond to changing climate and underlying topography in the future. Moreover, deglaciation in this region controlled routes available for early human migration into the Americas. Here, we present cosmogenic 10Be nuclide exposure ages from glacial erratics and bedrock on the west coast of British Columbia (53.4°N, 129.8°W) that add to existing chronologies along ~600 km of coastal North America. Collectively, these data show deglaciation back to the present coastline by ca. 18–16 ka. Retreat then slowed and ice seemingly stabilised close to the present coastline for several thousand years until ca. 14–13 ka. Ice may still have been lost during this period of relative stability, but through vertical thinning rather than lateral retreat. We attribute initial retreat to destabilisation and grounding line retreat resulting from rising sea level and/or ocean warming in the northern Pacific. Subsequent stability at the present coast was likely due to the transition from marine to terrestrial margins despite increasing temperatures that may have driven ice sheet thinning. Hence, we show the importance of understanding both climatic and non-climatic drivers of ice sheet change through time. We also show that hundreds of kilometres of coastline were free of ice prior to an important period of early human migration into the Americas.
Magnetic complexity changes within interplanetary coronal mass ejections: insights from a statistical study based on radially-aligned spacecraft observations
Authors: Scolini Camilla , Winslow Réka M. , Lugaz Noé , Salman Tarik M. , Davies Emma E. , Galvin Antoinette B.
Published: March 2022

We present the first statistical analysis of complexity changes affecting the magnetic structure of interplanetary coronal mass ejections (ICMEs), with the aim of answering the following questions: how frequently do ICMEs undergo magnetic complexity changes during propagation? What are the causes of such changes? Do the in situ properties of ICMEs differ depending on whether they exhibit complexity changes? 

We consider multi-spacecraft observations of 31 ICMEs carried out by MESSENGER, Venus Express, ACE, and STEREO between 2008 and 2014 during periods of radial alignment. By analyzing their magnetic properties at the inner and outer observing spacecraft, we identify complexity changes which manifest as fundamental alterations in the ICME magnetic topology, or as significant re-orientations of the ICME magnetic structure. Plasma and suprathermal electron data at 1 au, as well as simulations of the ambient solar wind enable us to reconstruct the propagation scenario for each event, and to identify critical factors controlling their evolution. 

Results show that 65% of ICMEs change their complexity between Mercury and 1 au, and that the interaction with multiple large-scale solar wind structures is the main driver of these changes. Furthermore, 71% of ICMEs observed at large radial (>0.4 au) but small longitudinal (<15 degrees) separations exhibit complexity changes, indicating that the propagation over large distances strongly affects ICMEs. Results also suggest ICMEs may be magnetically coherent over angular scales of at least 15 degrees, supporting earlier theoretical and observational estimates. This work provides statistical evidence that magnetic complexity changes are consequences of ICME interactions with large-scale solar wind structures, rather than intrinsic to ICME evolution, and that such changes are only partly identifiable from in situ measurements at 1 au.
Extreme daily precipitation trends in the Mediterranean region under a business-as-usual pathway 
Authors: Zitttis George , Bruggeman Adriana , Lelieveld Jos
Published: March 2022

Global warming is anticipated to intensify the hydrological cycle. However, this is neither expected to be globally uniform nor is the relationship between temperature increase and rainfall intensities expected to be linear. The objective of this study is to assess changes in annual rainfall extremes, total annual precipitation, and their relationship in the larger Mediterranean region. We use an ensemble of 33 regional climate simulations from the EURO-CORDEX initiative at a spatial resolution of 0.11°. We analyse the significance of trends for two periods (1951–2000 and 2001–2100) under a ‘business-as-usual’ pathway (RCP8.5). Our future projections indicate a strong north/south gradient, with significant, decreasing trends in the magnitude of daily precipitation extremes in the south and the Maghreb region (up to − 10 mm/decade) and less profound, increasing trends in the north parts of the Mediterranean. Despite the contrasting future trends, the 50-year daily precipitation extremes are projected to strongly increase throughout the region. The 100-year extremes, derived with traditional extreme value approaches from the 1951–2000 simulations, underestimate the magnitude of these extreme events in the 2001–2100 projections by 30% for the drier areas of the Mediterranean (200–500 mm average annual rainfall) and by up to 20–30% for the wetter parts of the region. These 100-year extremes can occur at any time in any Mediterranean location. The contribution of the wettest day per year to the annual total precipitation is expected to increase (5–30%) throughout the region. The projected increase in extremes and the strong reductions in mean annual precipitation in the drier, southern and eastern Mediterranean will amplify the challenges for water resource management. These results have been published in Zittis et al. (2021).

 

References

Zittis, G., Bruggeman, A., Lelieveld, J., 2021. Revisiting future extreme precipitation trends in the Mediterranean. Weather and Climate Extremes. 34, 100380. https://doi.org/10.1016/j.wace.2021.100380
The French monumental heritage in the face of global climate change: state of the art and research perspectives
Authors: Lefèvre Roger-Alexandre , Brimblecombe Peter , Verney-Carron Aurélie
Published: March 2022

France's monumental heritage has been the subject of little theoretical research in the face of global climate change, although many applied studies have concerned its adaptation and resilience, especially at the local level. Furthermore, this heritage includes more than 44,000 monuments and classified sites, 48 of which being inscribed on the UNESCO List and therefore deserves to be taken into account in the context of the current climate unbalance.

The complexity lies in the diversity of materials making up the monuments (stones, glass, metals, wood...) and of phenomena that affect them (as well as other constructions). In order to assess the impact of these increasing slow or extreme events already at work, the tools and methodologies range from the description and inventory of the effects, their measurement, mapping and projection into the future using models such as dose-response functions (DRF) with input data from climate models and scenarios. Ancient data can also be used to complement the correlation between climate and heritage, such as dendroclimatology studies of the wood in monuments.

Results from research carried out in France will be presented concerning stone facades, ancient stained glass windows, metals, degradation of walls by salts and dendroclimatology. Further research should focus on the consequences on the monumental heritage of rising marine waters, river and urban flood and low waters, freeze-thaw, the stability of monuments on clay soils and the indoor climate of monuments and their carbon footprint.

In conclusion, much remains to be done in France: (1) complete the inventory and description of the phenomena, their impacts and their location at the national, regional, urban and monumental scales, (2) quantify these impacts in the future via empirical or geochemical models based on climate models outputs.
Experimental radial profiles of early time (< 4 μs) neutral and ion spectroscopic signatures in lightning-like discharges
Authors: Passas-Varo María , Gordillo-Vázquez Francisco J , Sánchez del Río Justo , Kieu Thi Ny
Published: March 2022

The GrAnada Lightning Ultrafast Spectrograph (GALIUS) is a portable, ground-based slit spectrograph designed and developed at the Instituto de Astrofísica de Andalucía, in Granada, Spain. It is able to record spectra of natural and triggered lightning or lightning-like plasmas with submicrosecond time resolution in a spectral range from 380 nm to 854 nm. Our work shows GALIUS radial-resolved slit spectroscopy of 20 laboratory produced lightning-like discharges of 30 mm length and 8 ± 2 mm mean width, generated with an automated Wimshurst machine, being their mean peak voltage and current 32.70 kV and 149.58 A, respectively. We analyze the visible (645.0 - 663.0 nm) region operated at 900 kfps with 0.79 µs exposure time, spectral resolution better than 0.38 nm and spectral dispersion of 0.58 mm/px, that allows us to experimentally quantify the profiles of electron density and electron/gas temperature along the radial dimension of the lightning-like plasma channels and their temporal dynamics. To do so, we analyze the rows of the 2D spatial-spectral images of the heated channel of every lightning-like discharge, to follow the radial and temporal variation of neutral (atoms and molecules) and ion spectroscopic signatures. From these measurements we also estimate the evolution of the radial profiles of electrical conductivity, overpressure and populations of key chemical species(N2, NO, O2, OH, H2, N2O, NO2, HO2, O3 and H2O) produced along the radius of the plasma channel.
Non-contact, Low-cost Sensor Network for River Stage Monitoring and Dynamic Discharge Estimation 
Authors: Sah Neeraj , Buytaert Wouter , D. Paul Jonathan , De Stercke Simon , Paschalis Athanasios
Published: March 2022

Long series of river discharge data are essential for developing improved river and water management strategies and for coping with water-related hazards such as floods. However, continuous direct measurement of river discharge is practically infeasible. Recently developed electromagnetic and ultrasonic methods can be used for automated (or direct) river discharge measurements; however, they are not widely used because they are expensive and are prone to damage during high flows.

At most gauging sites around the world, a rating curve is used to convert the measured stage into discharge. However, using rating curves is fraught with difficulties, including (a) hysteresis effect during unsteady flow, (b) extrapolation error during high flows, (c) need for regular updating due to change in hydraulic resistance and channel geometry. More recently, methods have been developed for dynamic river discharge estimation by solving governing equations of river flow i.e., shallow water equations (SWE). However, these methods (a) solve SWE in its conservative form, (b) are most suitable for prismatic channels with no lateral flow, (c) require one flow value, and (d) assume channel roughness or calibrate it by using observed stage data from two or three gauging locations. Although, stage data from two or three gauging locations are theoretically sufficient to calibrate channel roughness, in practice error margins are still high due to sub-optimal positioning of gauging stations, and coarse temporal resolution of existing measurement networks.

Therefore, motivated by a need to surmount the limitations in existing methods, we have developed a non-contact, robust, and cost-effective approach for dynamic river discharge estimation. We use an array of bespoke sensors to monitor the river stage at high resolutions and use these stage data to estimate river discharge. We present a methodology to calibrate a hydraulic model of a river reach by only using stage data from a network of such sensors. We use freely available HEC-RAS software as the solver for SWE. We have developed python scripts to control and automate HEC-RAS simulations and estimate river discharge dynamically.
Chorus acceleration of ultra-relativistic radiation belt electrons during periods of low plasma density
Authors: Allison Hayley , Shprits Yuri , Wang Dedong , Zhelavskaya Irina , Smirnov Artem
Published: March 2022

Satellite observations show that electrons in the Van Allen radiation belts can have energies in excess of 7 MeV. The Van Allen Probes mission not only provided measurements of ultra-relativistic radiation belt electrons, but also simultaneous observations of plasma waves, allowing for the routine inference of total plasma number density. Based on a year of observations from 2015, we show that the electron plasma density has a controlling effect over local chorus acceleration to ultra-relativistic energies, which occurs only when the plasma number density drops down to very low values (~10 cm-3). Results from a Versatile Electron Radiation Belt (VERB) simulation show that a reduced electron plasma density allows chorus waves to efficiently resonate with electrons up to ultra-relativistic energies, producing enhancements from 100s of keV up to >7 MeV via local diffusive acceleration. We analyse statistically the observed chorus wave power during ultra-relativistic enhancement events, considering the contribution from both upper and lower band chorus waves. The Versatile Electron Radiation Belt (VERB) model is also used to recreate an ultra-relativistic electron acceleration event and simulation results are compared to observations, showing close agreement in the evolution when the reduction in electron plasma density is taken into account. The PINE density model allows for the investigation of global magnetospheric density changes during this event. We therefore analyze the how the global cold plasma density changes during ultra-relativistic enhancement events and compare to in-situ point measurements of the plasma density.
Intercomparison between 2DVD and MRR Datasets
Authors: Blouin Christopher K. , Barber Carson A. , Larson Michael L.
Published: March 2022

Simultaneous measurements of the rain drop size distribution were made by a 2-dimensional video disdrometer (2DVD, Joanneum Research, Graz, Austria) and a MicroRain Radar-Pro (MRR-Pro, Metek, Elmshorn, Germany) deployed near Charleston, South Carolina, USA and horizontally separated by approximately 20 meters. The 2DVD data was post-processed to correct for spurious drop detection and incorrect assignment of effective sensor area, and the MRR-Pro spectral data was corrected to incorporate a height-dependent estimate of the ambient vertical wind. Surface 2DVD drop measurements were utilized to reconstruct an approximation of the drop size distribution aloft at different heights and times to compare to the inferred MRR-Pro drop spectrum and bulk rain parameters. Despite fundamentally different measurement principles and different sets of assumptions associated with the reconstruction of drop size distributions aloft, the agreement between the 2DVD and MRR-Pro data showed promise. The two data sets are further investigated in order to reveal possible features of boundary layer rain vertical variability, estimates of drop-drop collision rates, and near-surface rain microphysical phenomena.
Andean Permafrost in Taluses and Blockslopes in the Agua Negra Catchment, Argentina - Distribution and Hydrological Significance
Authors: Stammler Melanie A. , Ortiz Diana A. , Koehler Tamara , Schrott Lothar
Published: March 2022

Extensive areas in mountain regions are under permafrost conditions with periglacial processes in the arid Andes of Argentina being mostly associated with high mountain permafrost. The most visible expression of creeping mountain permafrost within the periglacial altitudinal belt (between 35º and 27ºS), is the occurrence of rock glaciers. Beside snow and ice melting, active layer thawing and degrading permafrost contribute to river runoff; an essential resource in the arid Andes and their forelands. Halla et al. (2021) calculated for the first time rock glacier ice content using geophysical methods and four-phase modeling. Besides rock glaciers, taluses (including protalus ramparts) and blockslopes are widespread above an altitude of 4000 m a.s.l., with a first quantitative assessment revealing a surface coverage of about 73 %. We hypothesize that beside rock glaciers, taluses and blockslopes present a high potential for ice content, having a comparable or even more significant importance as valuable water reserves. However, taluses and blockslopes have not yet been properly investigated and little research has focused on the permafrost distribution and stratigraphy of these landforms.

This study determines the characteristics and the influence of climatic, topographical, and lithological conditions on the permafrost, using a multi-method approach: Electrical Resistivity Tomography (ERT), Seismic Refraction Tomography (SRT), hydrological monitoring along the course of Agua Negra river (discharge, water sampling), and UAV-, as well as spaceborne remote sensing analysis. While the use of ERT is beneficial due to the contrasting electrical resistivities of lithological media, water and ice, SRT complements the data with detailed p-wave based information on the upper layer. Hydrological monitoring aids in distinguishing different water resources and in estimating their contributions to runoff. In addition, the repeated application of remote sensing techniques allows for an acquisition of high resolution digital elevation models with models of difference providing insight in the magnitude, timing and spatial pattern of vertical and horizontal surface changes.

The possibility of determining with greater precision the distribution of permafrost in the arid Andes will lead to a more accurate estimation of solid-state water reserves stored in periglacial landforms in arid Andean catchments.

Halla, C., Blöthe, J.H., Tapia Baldis, C., Trombotto, D., Hilbich, C., Hauck, C., Schrott, L., 2021. Ice content and interannual water storage changes of an active rock glacier in the dry Andes of Argentina. The Cryosphere, 15, 1187-1213.
Capturing the Influence of Large Wood on Fluvial Bedload Transport with RFID Tracers and Linear Mixed Modelling
Authors: Clark Miles , Bennett Georgina , Ryan Sandra , Sear David , Franco Aldina
Published: March 2022

Bedload transport is a fundamental process by which coarse sediment is transferred through landscapes by river networks and may be well described stochastically by distributions of grain step length and rest time obtained through tracer studies. To date, none of these published tracer studies have specifically investigated the influence of large wood in the river channel on distributions of step length or rest time, limiting the applicability of stochastic sediment transport models in these settings. Large wood is a major component of many forested rivers and is increasing due to anthropogenic ‘Natural Flood Management’ (NFM) practices. This study aims to investigate and model the influence of large wood on grain-scale bedload transport. 

We tagged 957 cobble – pebble sized particles (D50 = 73 mm) and 28 pieces of large wood (> 1 m in length) with RFID tracers in an alpine mountain stream. We monitored the transport distance of tracers annually over three years, building distributions of tracer transport distances. Empirical data was used in linear mixed modelling (LMM) statistical analysis, determining the relative influence proximity to wood had on likelihood of entrainment, deposition, and the transport distances of sediments. 

Tracer sediments accumulated both up and downstream of large wood pieces, with LMM analysis confirming a reduction in the probability of entrainment of tracers closer to wood in all three years. Upon remobilisation, tracers entrained from positions closer to large wood had shorter subsequent transport distances in each year. In 2019, large wood also had a trapping effect, significantly reducing the transport distances of tracer particles entrained from upstream, i.e. forcing premature deposition of tracers. This study demonstrates the role of large wood in influencing bedload transport in alpine stream environments, with implications for both natural and anthropogenic addition of wood debris in fluvial environments.
The glacial geomorphology of the Scărișoara Plateau, Godeanu Mountains, Southern Carpathians, Romania
Authors: Balaban Cristina-Ioana , Roberts David H. , Evans David J.A. , Jamieson Stewart S.R.
Published: March 2022

Reconstructing the extent, style, timing and drivers of past mountain glaciation is crucial in both understanding past atmospheric circulation and predicting future climate change. Unlike in high-elevation mountains situated in maritime and continental climates, less is known of past glaciation in mid-altitude mountains, located in transitional climates, such as the Southern Carpathians of Romania. Despite these mountains harbouring a rich glacial geomorphology, this has never been systematically mapped according to well-established morphological criteria, nor confidently related to former styles of glaciation. Therefore, filling this gap is important for not only accurately identifying glacial extents, but also for establishing past glaciation styles and relating them to past ice dynamics and climate. We aim to understand the extent and timing of past glaciation in the Godeanu Mountains, Southern Carpathians. We present a new geomorphological map of the area, highlighting landforms associated with glaciation of the Scărișoara plateau and surrounding valleys. Using both remote (orthophotographs and Google Earth) and field mapping techniques, we describe and interpret the origins of glacial erosional landforms (ice-moulded bedrock, ice-marginal meltwater channels), and of depositional discrete debris assemblages of likely glacial (moraines), periglacial (pronival ramparts, protalus lobes, rock glaciers) and paraglacial (rock slope failure) origins. We also hypothesize the relationship of these landforms with former styles of glaciation. The field study results aid the interpretation of the geomorphology in the wider mountain range. Once absolute chronological results have been produced, the mapping will be used as a spatial constraint for numerical ice-flow modelling in the Parallel Ice Sheet Model (PISM).
Carbon and Nitrogen storage in Baltic coastal wetlands
Authors: Rodrigues-Morgado Mariana , Villoslada Peciña Miguel , D. Ward Raymond , F. Bergamo Thaísa , Sepp Kalev
Published: March 2022

Coastal wetland systems are a priority habitat, according to the EU Habitats Directive (1992). They consist of a range of plant communities and in Europe can include salt marshes, coastal wet grasslands, swamp vegetation on the seaward edge, and scrub vegetation on the landward side. Coastal wetlands provide numerous essential ecosystem services, including supporting high biodiversity, high productivity, flood defense and wave attenuation as well as carbon and nitrogen sequestration and storage. Despite their ecological importance coastal wetlands have been subjected to habitat degradation and loss throughout their distribution as well as decreases in ecosystem service provision, and this is likely to be exacerbated by climate change. There has been increasing interest in the ability of coastal wetlands to store and sequester carbon and nitrogen as a highly important ecosystem service that may help mitigate climate change.

We collected topsoil cores from three Baltic coastal meadows following stratified random sampling for each plant community: Lower Shore (LS), Upper Shore (US), Tall Grass (TG) and Open Pioneer (OP). A total of 10 cores per plant community per site were collected. Sampling cylinders (88.2 ml capacity; 40 mm height; 53 mm internal diameter) were used to collect undisturbed soil material. Organic carbon content (SOC) was determined by the Tjurin (wet combustion) method and total nitrogen (Ntot) content with the Kjeldahl method.

Our results show that organic carbon content and total nitrogen are site and plant community specific. The specificity is likely driven by sedimentary and geomorphic constraints such as rates and duration of inundation and allochthonous organic inputs, which highlights how increasing rates of sea level rise and frequency of extreme flooding events will likely impact carbon and nitrogen storage in coastal wetlands. This also shows that not all sites provide the same level of these ecosystem services and should carbon metrics be applied for conservation purposes in the future, site specific studies and monitoring of carbon sequestration will be required.
Nowcasting Tracks of Severe Convective Storms in West Africa from Observations of Land Surface State
Authors: Taylor Christopher M. , Klein Cornelia , Dione Cheikh , Parker Douglas J. , Marsham John , Abdoulahat Diop Cheikh , Fletcher Jennifer , Saidou Chaibou Abdoul Aziz , Nafissa Dignon Bertin , Semeena Valiyaveetil Shamsudheen , Cole Steven , Anderson Seonaid
Published: March 2022

In tropical convective climates, where numerical weather prediction of rainfall has high uncertainty, nowcasting provides essential alerts of extreme events several hours ahead. In principle, short-term prediction of intense convective storms could benefit from knowledge of the slowly-evolving land surface state in regions where soil moisture controls surface fluxes. Here we explore how near-real time (NRT) satellite observations of the land surface and convective clouds can be combined to aid early warning of severe weather in the Sahel on time scales of up to 12 hours. Using Land Surface Temperature (LST) as a proxy for soil moisture deficit, we characterise the state of the surface energy balance in NRT. We identify the most convectively-active parts of Mesoscale Convective Systems (MCSs) from spatial filtering of cloud-top temperature imagery.

We find that predictive skill provided by LST data is maximised early in the rainy season, when soils are drier and vegetation less developed. Land-based skill in predicting intense convection extends well beyond the afternoon, with strong positive correlations between daytime LST and MCS activity persisting as far as the following morning in more arid conditions. For the Science for Weather Information and Forecasting Techniques (SWIFT) Forecasting Testbed event during September 2021, we developed a simple technique to translate LST data into NRT maps quantifying the likelihood of convection based solely on land state. We used these maps in combination with convective features to nowcast the tracks of existing MCSs, and predict likely new initiation locations. This is the first time to our knowledge that nowcasting tools based principally on land observations have been developed. The strong sensitivity of Sahelian MCSs to soil moisture, in combination with MCS life times of typically 6-18 hours, opens up the opportunity for nowcasting of hazardous weather well beyond what is possible from atmospheric observations alone, and could be applied elsewhere in the semi-arid tropics.
Environmental control of marine phytoplankton C:N stoichiometry in the North Atlantic Ocean today and under climate change
Authors: Sauterey Boris , Ward Ben
Published: March 2022

The stoichiometric coupling of carbon to limiting nutrients in marine phytoplankton determines that of the main biogeochemical cycles through the process of biomass production by the phytoplankton. While clear links between phytoplankton stoichiometry and environmental drivers have been identified, the nature and direction of these links, as well as the underlying physiological and ecological mechanisms, remain uncertain. Here we compare the predictions of a well-constrained mechanistic model of plankton ecophysiology to multiple observational data sets to investigate the specific case of the C:N phytoplankton stoichiometry in the North-Atlantic. We show that N availability and temperature emerge as the main drivers of phytoplankton stoichiometry. The biological mechanisms involved however vary depending on the spatiotemporal scale and region considered, leading to opposite predictions regarding the evolution of phytoplankton primary productivity in response to environmental changes. At low to intermediate latitudes phytoplankton stoichiometry is predominantly driven by ecoevolutionary shifts in the functional composition of the phytoplankton communities while phytoplankton stoichiometric plasticity in response to dropping temperatures and increased grazing pressure dominates at higher latitudes. Those results shine a new light on what currently influences the circulation of elements through marine ecosystems but also have great implications regarding the evolution of oceans’ primary productivity and of the main biogeochemical cycles under a regime of climate change.
Quantitative spatial distribution and human vulnerability assessment for site-specific loess landslide
Authors: Zhou Qi , Xu Qiang , Peng Dalei , Zeng Peng , Fan Xuanmei , Ouyang Chaojun , Zhao Kuanyao , Yuan Shuang , Zhu Xing , Li Huajin
Published: March 2022

Landslides are associated with severe losses on the Loess Plateau of China. Providing hazard mitigation decision support for stakeholders and ensuring the safety of personnel play essential roles in risk management for landslides. Although early warning systems and escape guidelines have mitigated the risk to some extent, most methods are qualitative or semi-quantitative in the sitescale. Therefore, we propose a quantitative simulated-based spatial distribution model and scenario‐based human vulnerability probabilistic model for site-specific loess landslide risk assessment. For spatial distribution, coupled with multi-temporal remote sensing images and high-precision UAV cloud point data, a total of 98 loess landslides have occurred since 2004 on the Heifangtai terrace (North-West China) were collected to establish a landslide volume-date and retreating distance database. Eleven loess landslides are selected to construct a numerical model for parameter analysis. The centroid distance and overlapping area can quantitatively evaluate the accuracy of the simulation results. Different volumes and receding distance rates of landslides are fitted to determine the relationship between cracks and potential volume. Different volumes and parameters are combined to simulate the spatial distribution of potential loess landslides. Following the obtained hazard zone, a scenario-based model for evaluating the escape behavior and human vulnerability was proposed using a Python platform. Based on sampling surveys and field investigations, a database that includes detailed information for the hazard zone’s demographic structure and behavioral characteristics were established. The probability of scenario input parameters, such as the escape route and speed, were calculated and quantified by classic probability theory. In the selected slope slide case, farmland near the toe of the slope primarily includes exposed hazards with probabilities greater than 0.7. The registered population over 65 years old accounted for 13.46% of the total, and most residents had no more than a primary school education background. Older adults were inclined to escape a moving landslide by running parallel to the sliding direction, although the public considers this direction to be the most dangerous. The model simulation revealed that cumulative mortality could be significantly reduced by promoting disaster prevention awareness and improving the advance warning time. The developed quantitative hazard and human vulnerability framework provide a useful reference for local disaster reduction and disaster prevention rehearsal guidelines.
Magnetospheric flux throughput in the Dungey cycle: identification of convection state during 2010
Authors: Milan Steve , Carter Jenny , Sangha Harneet , Bower Gemma , Anderson Brian
Published: March 2022

We quantify the contributions of different convection states to the magnetic flux through-put of the magnetosphere during 2010. To do this we provide a continuous classification of convection state for the duration of 2010 based upon observations of the solar wind and interplanetary magnetic field, geomagnetic indices, and field-aligned currents measured by the Active Magnetosphere and Planetary Electrodynamics Response Experiment (AMPERE). Convection states are defined as 1) quiet and 2) weak activity, substorm 3) growth, 4) expansion, and 5) recovery phases, 6) substorm driven phase (when relatively steady magnetospheric convection occurs), 7) recovery bays (when recovery phase is accompanied by a negative excursion of the AL electrojet index), and 8) periods of multiple intensifications (storm-time periods when continuous short-period AL activity occur). The magnetosphere is quiet for 46% of the time, when very little convection takes place. The majority of convection occurs during growth and driven phases (21% and 38%, respectively, of open magnetic flux accumulation by dayside reconnection). We discuss these results in the context of the expanding/contracting polar cap model of convection, and describe a framework within which isolated substorms and disturbances during periods of more continuous solar wind-magnetosphere driving can be understood.
Mapping flooded areas using Sentinel-1 radar satellite imagery series through Machine learning and Deep learning methods
Authors: Toma Andrei , Sandric Ionut
Published: March 2022

                Rapid and accurate mapping of floods offers an excellent advantage for local, regional decision-makers to mitigate the exposure of human and material losses. The current study assessed the performance of several machine learning (ML) and deep learning (DL) models for detecting and mapping floods using Sentinel-1 SAR imagery. Three distinct approaches were used with machine learning and deep learning models: pixel classification, object-based image analysis and object instance segmentation. The ML models are Random Forest (RF) and Support Vector Machine applied for pixel classification and object-based image analysis. The DL models are U-NET, DeepLabV3 and Mask RCNN used for pixel classification and object instance segmentation. The models were implemented using SNAP (Sentinel Application Platform), ESRI ArcGIS Pro, Esri ArcGIS API for Python and Python programming language. To test the model's scalability, five different cases studies were selected. These areas are located in Romania (Prut River sector, Timiș River sector and Râul Negru sector), the United States of America (Missouri River sector) and Australia (Broughton Creek sector). Five Sentinel-1 images were used for each flood, having four collected previous to the flood event and one collected after the flood event. Each Sentinel-1 image was calibrated and ortho-corrected, and filtered using SNAP. The intensity images were stacked and scaled in the range of the intensity thresholds associated with water and non-water so that all the case studies have the same margins for intensity. Further, samples were collected in ArcGIS Pro from the Prut River region using the stack of images created from the previous step. Besides water, other classes, such as forest, agricultural fields and bare soil, were collected and used in the training process. The training for the ML models took place directly on the standardized radar images within ArcGIS Pro. The training of the DL models was done through the use of Jupyter Notebooks and ArcGIS API for Python. The models were trained on samples collected from the Prut River area and then tested on all selected regions to assess their ability to perform in different study areas. The highest accuracy, calculated as Intersect over Union, was obtained by the U-Net model (IoU score of 0.74). Comparable accuracies were obtained by the RF and SVM models implemented with OBIA, with an IoU score of 0.72. Mask R-CNN and DeepLabV3 got IoU scores of 0.70, and the lowest accuracies for floods mapping were obtained by the RF and SVM models implemented as pixel classification (both having IoU scores of 0.53).
Statistical characteristics of wind fluctuations in the troposphere and lower stratosphere over Andøya, Norway (69.30°N, 16.04°E) revealed by MAARSY
Authors: Ghosh Priyanka , He Maosheng , Latteck Ralph , Renkwitz Toralf , Avsarkisov Victor , Zecha Marius , Chau Jorge L.
Published: March 2022

We explore the spectral characteristics of the horizontal and vertical wind fluctuations, in the troposphere and lower stratosphere, using the Middle Atmosphere Alomar Radar System (MAARSY) during the years 2017-2020 over Andøya, Norway (69.30°N, 16.04°E). The power spectral density covers a broad frequency range of 3.5 d-1 > f > 1 h-1. The power spectra are categorized in different ranges: two frequency ranges (lower and higher than (13 h)-1), four altitude ranges (lower troposphere, middle troposphere, tropopause region, and lower stratosphere), and four seasons (spring, summer, autumn, and winter). We investigated the power-law S(f) ∝ fβ through a least-squares regression. Our results demonstrate that (i) the spectra of the horizontal winds follow a power-law with slopes of about β = -5/3 (at high-frequency), and β = -2 (at low-frequency), respectively, and the slope steepens vertically around the tropopause and seasonally during the summer, and (ii) the slope β in the vertical wind is shallow β > -1, which flattens with altitude. The momentum flux and vertical wind variance exhibit seasonal and altitudinal variations, both of which minimize in summer and maximize at the lower troposphere. The probable reason for such variation will be discussed in the presentation.

 

 
Climatic risk, resilience, and adaptation of power systems in small-island states: the case of Jamaica
Authors: Majid Aman , Pant Raghav , Russell Tom , Hall Jim W.
Published: March 2022

Power networks are critical economic infrastructure and are susceptible to natural hazards, such as hurricanes and floods. Disruptions in power systems due to extreme climatic events can cause major detrimental impacts to social systems and large economic losses, and these may worsen due to climate change. Existing methods can be used to spatially map climate risks in energy systems, understand cascading risks, and quantify expected damages in terms of direct and indirect economic losses. Yet, there is a dearth of methods that link operational models of energy networks with climate risk methodologies, making it difficult to assess the impact of system-level operational changes (e.g., increasing renewable energy system (RES) penetration) on climate risk and resilience. In the context of small-island states, such advances are urgently needed as a precursor to producing robust adaptation plans. 

In this work, we introduce a framework to simulate climatic risks in large-scale power networks under uncertain climatic change. We link a highly resolved power system simulation model with a state-of-the-art climate risk analytical framework. We apply our methodology in a national scale case-study from Jamaica. Our results provide the following key insights:

We spatially map climate risks under varying scenarios of climate change to identify the most vulnerable assets in the power network across the island;

We quantify the expected direct and indirect damages, as well as the number of customers affected;

We simulate operational changes in the power system (e.g., increasing RES penetration, adding transmission capacity, changing utility pole materials) and quantify their impact on the risk profiles, and thus informing adaptation.

Our assessment presents a comprehensive assessment of climate risks across Jamaica, which was produced in conjunction with stakeholders from government, industry, and academia from the region.