bluuebunny/crossref_metadata_2025 huggingface dataset:
Soil Microbial Indicators of Alkane Flux around a Natural Gas Seep
Authors: Bott Thomas , Gregory Simon , Shaw George , Palumbo-Roe Barbara
Published: March 2020

The UK has a legacy of onshore oil and gas wells. Aging extraction wells, with deteriorating cap engineering, may act as preferential pathways for gas seepage from the sub-surface. Seeps from hydrocarbon reservoirs are predominately composed of potent greenhouse gases, such as methane and carbon dioxide. Shifts in the soil microbial community are potential indicators of alkane gases rising from the sub-surface. Therefore, soil microbial community change could be used as a tool for monitoring aging, legacy wells, for gas seepage. An increased abundance in bacteria that metabolise methane (methanotrophs), or, C3-C4 alkanes (propanotrophs/butanotrophs) should be correlated with an increased flux of those gases, thereby indicating the presence of a seep.

In the South-East of the Auvergne-Rhône-Alpes region of France, there are several natural-gas analogue macro-seeps where the soil microbial community is potentially interacting with increased alkane fluxes. A well characterised natural gas seepage site was visited, and soil samples were collected for DNA analysis. Surface gas flux measurements and soil-pore gas concentrations (at 1 metre depth) were collected at the same sampling locations by BGRM involved in the ERA-ACT funded Subsurface Evaluation of Carbon capture and storage and Unconventional Risk (SECURe) project. The abundance of alkanotrophs within the bacterial community was explored using quantitative-PCR assays of the key genes used in alkane metabolism. DNA was used in qPCR assays to estimate the proportion of methane monooxygenase and butane/propane oxidising genes within the total bacterial community (using 16S as a proxy). The in-field measurements of gases were contrasted with the relative abundance of methanotrophs and propanotrophs/butanotrophs.

Preliminary results suggest an increased abundance of methanotrophs above soils with higher pore gas concentrations of methane. These methanotrophs have oxidised the rising methane producing small isolated anomalies of increased methane flux at the surface. This suggests that methanotrophs might be a tool for locating soils with an increased methane concentration.
High-resolution polarimetric radar network for improving urban resilience to natural disasters in a complex environment
Authors: Chandra Chandrasekar V. , Chen Haonan , Cifelli Rob
Published: March 2020

The operational Weather Surveillance Radar - 1988 Doppler (WSR-88D) network is an efficient tool for observing hydrometeorology processes and it forms the cornerstone of national weather forecast and warning systems. However, the observation performance of the WSR-88D network is severely hampered over the western U.S., due to 1) the radar network density is not as high as that over the eastern U.S.; 2) WSR-88D radar beams are often partially or fully blocked by the mountainous terrain in the western U.S. 

For example, the San Francisco Bay Area in Northern California, which supports one of the most prosperous economies in the U.S., is expected to be covered by two WSR-88D radars: KMUX and KDAX. The KMUX radar is located in the Santa Cruz Mountains at an elevation of over 1000 m above mean sea level (AMSL) compared with the densely populated valley regions which are near the sea level. Typically, the storms in Northern California have freezing levels approximately 1–2 km AMSL. As the distance from the radar increases, the KMUX radar beam can easily overshoot the mixed-phase hydrometeors in the bright band or snowflakes above the bright band, even if it is raining at the ground. The KDAX radar is located near the sea level in Davis, California. However, the KDAX radar beams are partially blocked by the Coast Ranges at low elevation angles. The coverage limitations of the KMUX and KDAX radars are further compounded by the complex precipitation microphysics as a result of land-ocean interaction in the coastal regions and orographic enhancement in the mountainous regions. As a result, it is still challenging to monitor and predict the changing atmospheric conditions using operational radars in the Bay Area, which will make the Bay Area particularly susceptible to catastrophic flooding that disrupts transportation, threatens public safety, and negatively impacts water quality. 

In this paper, we present an Advanced Quantitative Precipitation Information (AQPI) system built by NOAA and collaborating partners to improve monitoring and forecasting of precipitation and coastal flooding in the Bay Area. The high-frequency (i.e., C and X band) high-resolution gap-filling radars deployed as part of the AQPI program are detailed. A radar-based rainfall system is designed to improve real-time precipitation estimation over the Bay Area. The sensitivity of rainfall products on the occurrence of hydrologic extremes is investigated through a distributed hydrological model to improve the streamflow forecast. The performance of rainfall and associated hydrological impacts during the 2018-2019 and 2019-2020 winter storm seasons is quantified in the context of improving urban resiliency to natural disasters in such a complex environment. 
Exploring the variability of the venusian atmosphere above the clouds with the IPSL Venus GCM
Authors: Lebonnois Sebastien , Gilli Gabriella , Quirino Diogo , Silva Vasco , Navarro Thomas , Lefevre Franck , Määttänen Anni
Published: March 2020

To investigate the amount of data recently acquired by the Venus Express (VEx) and Akatsuki missions as well as from ground-based telescopes, Venus Global Climate Models (GCM) are powerful tools. Our understanding of the Venusian climate has increased with recent progresses with these models.
The IPSL Venus GCM has been used recently to investigate all regions of the Venusian atmosphere, as it covers the surface up to the thermosphere (150 km). It involves a photochemical module with a simplified cloud scheme that enables the study of the composition and the coupling with the upper atmosphere, where composition plays a crucial role on the non-LTE and EUV heating processes. Other relevant physical processes in the thermosphere (e.g. molecular diffusion and thermal conduction) are taken into account. Below 100 km, the infrared energy budget is computed based on a Net Exchange Rate formalism. The cold collar structure has been modeled when taking into account the latitudinal distribution of the cloud structure. Globally averaged profiles (e.g spatially and temporally) extracted from the state-of-the-art IPSL Venus GCM provide realistic templates of the atmosphere of Venus. 
VEx observations revealed a more variable atmosphere than expected, in particular the “transition” region (~70-120 km) between the retrograde superrotating zonal flow and the day-to-night circulation showed latitude and day-to-day variations of temperature up to 80 K above 100 km at the terminator, and apparent zonal wind velocities measured around 96 km on the Venus nightime highly changing in space and time. Those variations are not fully explained by current 3D models and specific processes (e.g. gravity wave propagation, thermal tides, large scale planetary waves) responsible for driving them are still under investigation. The role of convectively-generated gravity waves and their impact on zonal wind and temperature in the region of aerobraking can be explored with the IPSL-VGCM, thanks to the inclusion of a stochastic non-orographic gravity waves parameterization, based on the Earth GCM. Data-model comparison of distribution of dynamical tracers above the clouds  (e.g O2(1Δ) nightglow, CO and O density) will be crucial to shed a light on a region where no direct wind measurements are available.
Akatsuki’s LIR camera revealed the presence of  planetary-scale mountain waves at the cloud top in the afternoon. Simulations of the upper atmosphere suggest that mountain waves can easily reach the upper atmosphere, to polar latitudes and the nightside, thus affecting atmospheric dynamics as high as 130 km.
Role of structural inheritances in the development of the Mountain Front Flexure in the Lurestan region of the Zagros belt
Authors: Tavani Stefano , Camanni Giovanni , Nappo Michele , Snidero Marco , Ascione Alessandra , Valente Ettore , Gharabeigli Gholamreza , Morsalnejad Davoud , Mazzoli Stefano
Published: March 2020

The Mountain Front Flexure is a major structure of the Zagros orogenic system, and is underlain by the deeply rooted and seismically active Mountain Front Fault system. These coupled structural features divide the belt from its foreland and their trace is sinuous, forming salients and recesses. The origin and tectonic significance of the Mountain Front Fault system and its sinuosity are still unclear, with most of hypotheses pointing to a strong structural control exerted by geological inheritances. In this work we combine interpretation of seismic reflection profiles, earthquake data, geomorphic analysis, and geological observations, to build a balanced cross section across the Mountain Front Flexure in the Lurestan region. Our data are suggestive of a hybrid tectonic style for the Lurestan region, characterised by a major and newly developed crustal ramp in the frontal portion of the belt (i.e the Mountain Front Fault) and by the reactivation of steeply dipping pre-existing basin-bounding faults, along with a minor amount of shortening, in the inner area. Specifically, the integration of our results with previous knowledge indicates that the Mountain Front Fault system developed in the necking domain of the Jurassic rift system, ahead of an array of inverted Jurassic extensional faults, in a structural fashion which resembles that of a crustal-scale footwall shortcut. Within this structural context, the sinusoidal shape of the Mountain Front Flexure in the Lurestan area arises from the re-use of the original segmentation of the inverted Jurassic rift system.
Future changes in atmospheric rivers and extreme precipitation in Norway
Authors: Whan Kirien , Sillmann Jana , Schaller Nathalie , Haarsma Rein
Published: March 2020

Atmospheric rivers (AR) are associated with flooding events in Norway, like the flood that impacted Flåm in 2014. We assess trends in Norwegian AR characteristics, and the influence of AR variability on extreme precipitation in Norway. After evaluating the global climate model, EC-Earth, compared to the ERA-Interim reanalysis, we show that ARs increase in both intensity and frequency by the end of the century. In two regions on the west coast, the majority of winter precipitation maxima are associated with AR events (> 80% of cases). A non-stationary extreme value analysis indicates that the magnitude of extreme precipitation events in these regions is associated with AR intensity. Indeed, the 1-in-20 year extreme event is 17% larger when the AR-intensity is high, compared to when it is low. Finally, we find that the region mean temperature during winter AR events increases in the future. In the future, when the climate is generally warmer, AR days will tend to make landfall when the temperature is above the freezing point. The partitioning of more precipitation as rain, rather than snow, can have severe impacts on flooding and water resource management in Norway.
Groundwater chemical composition response to the recent 2018 drought event in Europe (central part of Latvia)
Authors: Retike Inga , Bikše Jānis , Dēliņa Aija , Kalvāns Andis , Babre Alise , Popovs Konrāds
Published: March 2020

More severe and frequent drought events are one of the main challenges faced worldwide in the context of climate change. Now droughts can be observed in the areas that are typically not classified as drought prone regions and more often groundwater vulnerability to prolonged drought events is reported. Groundwater drought is relatively new drought type defined as lower than normal groundwater level.

Most recent drought event in Europe in 2018 significantly affected shallow groundwater aquifers in the Baltic states. That year, groundwater droughts in Latvia caused large financial losses to many farmers, and rural households frequently reported dry dug wells. Even though main groundwater drought consequences are depleted aquifers and/or reduced base flows to rivers, drought may have an influence on groundwater quality as well (e.g. reduced denitrification rates due to lower groundwater levels and shorter travel times in anoxic zone).

This study presents groundwater chemical composition changes with respect to groundwater level variations between six sampling campaigns carried out during the groundwater drought event in 2017-2018 in central part of Latvia. Groundwater samples were taken from specifically established monitoring network with seven stations, each having two to four shallow groundwater wells with the maximum depth of four meters. In total more than 100 groundwater, surface water and spring water samples were collected every two months for a one-year period. Major ions, water stable isotopes, biogenic and trace elements were analyzed in laboratory. Patterns were analyzed by multivariate statistical analysis (Principal Component Analysis, Cluster Analysis and Discriminant Analysis).  

The study is supported by fundamental and applied science research programme, project Nr.lzp-2019/1-0165 “Spatial and temporal prediction of groundwater drought with mixed models for multilayer sedimentary basin under climate change”.
Direction of ionospheric structures in LOFAR calibration data
Authors: Budzińska Katarzyna , Mevius Maaijke , Grzesiak Marcin , Pożoga Mariusz , Matyjasiak Barbara , Rothkaehl Hanna
Published: March 2020

The Low Frequency Array (LOFAR) interferometer is a radio telescope
network that provides the radio astronomical observations with the highest
up-to-date sensitivity in the frequency regime between 10 and 240 MHz. As
these frequencies approach the ionospheric plasma frequency, ionospheric
perturbation of propagating electromagnetic signal is the main
environmental factor affecting the quality of observations. Removal of
ionospheric influence is a part of routinely conducted data calibration,
resulting in high sensitivity differential Total Electron Content (dTEC)
values between LOFAR stations.
In this study we present a method for medium scale ionospheric structures
detection applied to interferometric data obtained from calibration
solutions of one of the key LOFAR projects- the Epoch of Reionization.
Each observation spans 110-250 MHz of frequency range and lasts 6-8 hours
during winter nighttime. Due to operating frequency and sensitivity of
interferometric data, studies conducted with LOFAR can complement GNSS
research with medium scale structures.
Characterization of the atmospheric gravity waves on Mars at altitudes 10-180 km as measured by the ACS/TGO solar occultations
Authors: Starichenko Ekaterina , Belyaev Denis , Medvedev Alexander , Fedorova Anna , Korablev Oleg , Montmessin Franck , Trokhimovskiy Alexander
Published: March 2020

Atmospheric gravity waves (GW) are periodic oscillations of air masses that manifest themselves as fluctuations of density, temperature, pressure and other quantities. Studying vertical distributions of density and temperature helps to characterize vertical propagation of GWs and evaluate their influence on the coupling between atmospheric layers.

We report on the first results of GWs retrievals in the Martian atmosphere from the solar occultation experiment performed by the Atmospheric Chemistry Suite (ACS) onboard the ExoMars Trace Gas Orbiter TGO [1]. This is the first time when GWs were measured simultaneously in almost the entire atmosphere. The ACS is a set of infrared spectrometers operating on the orbit of Mars since April 2018. The mid-infrared channel (ACS-MIR) is a cross-dispersion spectrometer covering the 2.3–4.2 µm spectral range with the resolving power reaching ~30 000. In the solar occultation mode the spectrometer can observe thin layers of the Martian thermosphere and lower atmosphere in strong (e.g. 2.7 and 4.3 μm) and weak (about 3 μm) CO2 absorption bands with vertical resolution ~1 km. The near-infrared channel (ACS-NIR) is another echelle spectrometer working in the 0.73–1.6 µm spectral range with the resolving power ~25000 [2]. Due to the high resolution, these instruments (operating simultaneously) allow for deriving the temperature, pressure and density fluctuations at the unprecedented altitude range from 10 to 180 km. The dataset we present consists of more than 100 vertical profiles derived at seasons from the second half of MY34 to the beginning of MY35 in the both Martian hemispheres. The data analysis in IKI is supported by the RSF grant #20-42-09035.

 

REFERENCES

[1] Korablev O. et al., 2018. The Atmospheric Chemistry Suite (ACS) of three spectrometers for the ExoMars 2016 Trace Gas Orbiter. Space Sci. Rev., 214:7. DOI 10.1007/s11214-017-0437-6.

[2] Fedorova A. et al., 2020. Stormy water on Mars: The distribution and saturation of atmospheric water during the dusty season. Science, eaay9522. DOI: 10.1126/science.aay9522.
Insights into the African Humid Period from fossil stromatolites and Etheria elliptica shells from the Chew Bahir Basin, southern Ethiopia
Authors: Nickolaus Peter , Markowska Monika , Vonhof Hubert , Bocherens Hervé , Martin Ashley , Zinaye Bahru , Fischer Markus , Asrat Asfawossen , Junginger Annett
Published: March 2020

In the context of human evolution and dispersal in Africa, it is important to understand past climate conditions and changes as possible drivers of these processes. One of the most recent climatic events was the end of the African Humid Period (AHP) at around 5 ka BP. This was marked by a decrease in precipitation following a long wet-phase in northern and eastern Africa, which caused many lakes to decrease in size or even desiccate. Although the termination of the AHP is well known, the timing and rate of the transition from wet to dry conditions is still heavily debated. To investigate the termination of the AHP at a high temporal resolution (subdecadal and subannual), fossil stromatolites and Etheria elliptica shells from paleo-shorelines in the Chew Bahir Basin, southern Ethiopia, were collected. Today, Lake Chew Bahir is a deltaic swamp, however in past pluvials a large lake was present that likely overflowed and connected to other basins similar to other amplifier lakes in the East African Rift System. Radiocarbon dating, oxygen and carbon stable isotope analyses, trace element analyses and petrographic mapping of stromatolite laminae structure were conducted. A strong correlation between δ18O and δ13C shows that paleo-lake Chew Bahir likely experienced highly evaporative conditions and indicate an endorheic state of the basin in times of stromatolite growth at 7.1, 5.8, 4.7 and 4.6 ka BP. Furthermore, our findings suggest highly fluctuating environmental conditions during these times and demonstrate that the transition to drier conditions was not a strictly linear trend. In summary, the stromatolites and Etheria elliptica shells are an excellent environmental archive due to their high temporal resolution, precise dating (± 30 yrs) and an indication of the paleo-lake water depth. These types of records provide insights to past changes in freshwater availability, the variability of which would have had large consequences for humans living in the region.
Reconstructing surface mass balance from the Greenland ice sheet stratigraphy.
Authors: Theofilopoulos Alexios , Born Andreas
Published: March 2020

Our knowledge of the past surface mass balance on Greenland depends on scarce paleoclimate reconstructions and uncertain climate simulations. However, reconstructions of the internal layering of the ice sheet can provide an independent dataset of accumulation. The thickness of isochronal layers is directly affected by accumulation, but modified over time by the flow of ice. Existing methods can disentangle these two effects only near the ice divide where assumptions of stationarity may be justified. To solve this problem and to obtain a spatially comprehensive reconstruction of accumulation, we use an ice sheet model with an isochronal grid. Thinning rates are calculated prognostically by the model and can be used to define an inverse problem that can be solved iteratively. The only input data is the final layer thickness of the target, e.g., reconstructed radio echo layers from the Greenland ice sheet. To test this method and its limitations, we reconstruct the accumulation histories from the stratigraphies of simulations for which the idealized accumulation time series and spatial distributions are known. These simulations represent a two-dimensional cross section of the Greenland ice sheet. The results are robust to a wide range of realistic variations in accumulation for all but the layers closest to the bedrock where the deformation by the flow is most severe.
A case study on severe hailstorm on 27 July 2019 in the province of Styria, Austria
Authors: Tani Satyanarayana , Paulitsch Helmut
Published: March 2020

A severe hailstorm activity on 27th July 2019 created significant damage to crops in the province of Styria, Austria. The hail reports from ESWD (European Severe Weather Database) shows with maximum diameter up to 8 cm was noticed in the vicinity of the storm occurred. Total 1040 crop damage reports were claimed from the Austrian Hail Insurance System due to this severe hailstorm event. A close inspection and understanding features of severe hailstorms is helpful for hail risk assessment. The present study investigates the associated synoptic weather conditions and life cycle of the thunderstorm, and its dynamics. Further analysis carried about hail detection methods and crop hail damage assessment based remote sending and crowdsourcing data. The spatial distribution and temporal development of severe thunderstorms details extracted from radar data. The 3D radar data and storm cell tracking software used to capture the thunderstorm life cycle from the beginning to the dissipating stage. Radar-derived parameters collected for each storm cells, i.e. Duration of the storm cell, volume and area the storm cell, the cloud top height and the maximum reflectivity. Hail detection algorithms (Waldvogel and Auer) used to identify hail event period. The spatial distribution total hail kinetic energy maps prepared to capture the swath and intensity of the hail storms to classify possible crop-hail damaged areas. Hail observational data from ESWD (European Severe Weather Database) and HeDi (Hail event Data interface) and crop damage reports from the Austrian Hail Insurance System are utilised as a ground truth information.  An event-based severe hailstorm analysis help to find proper risk transfer solutions for loss adjustment.
Unsupervised deep learning on seismic data to detect volcanic unrest
Authors: Cannavo' Flavio , Cannata Andrea , Palazzo Simone , Spampinato Concetto , Faraci Demian , Castagnolo Giulia , Kavasidis Isaak , Montagna Chiara , Colucci Simone
Published: March 2020

The significant efforts of the last years in new monitoring techniques and networks have led to large datasets and improved our capabilities to measure volcano conditions.  Thus nowadays the challenge is to retrieve information from this huge amount of data to significantly improve our capability to automatically recognize signs of potentially hazardous unrest.
Unrest detection from unlabeled data is a particularly challenging task, since the lack of annotations on the temporal localization of these phenomena makes it impossible to train a machine learning model in a supervised way. The proposed approach, therefore, aims at learning unsupervised low-dimensional representations of the input signal during normal volcanic activity by training a variational autoencoder (VAE) to compress, reconstruct and synthesize input signals. Thanks to the internal structure of the proposed VAE architecture, with 1-dimensional convolutional layers with residual blocks and attention mechanism, the representation learned by the model can be employed to detect deviations from normal volcanic activity. In our experiments, we test and evaluate two techniques for unrest detection: a generative approach, with a bank of synthetic signals used to assess the degree of correspondence between normal activity and an input signal; and a discriminative approach, employing unsupervised clustering in the VAE representation space to identify prototypes of normal activity for comparison with an input signal.
Quantitative observations and numerical modeling of charge development in volcanic eruption clouds
Authors: Geisler Andre , Seelmann Benjamin , Hort Matthias , Bülow Joachim , Scharff Lea , Iguchi Masato , Miki Daisuke
Published: March 2020

In February 2019 we completed the installation of a ten instrument network at Sakurajima volcano, Japan. The network includes three Doppler radar systems to record eruption velocities and amount of ejected material at Minamidake crater. Those instruments are located to the East of the volcano at a distance of about 4.5 km to the vent. We also installed three field mills to measure the electric field that is generated during an eruption due to charging of the volcanic plume. Those instruments are located to the East, North and West of the volcano at different distances. The network is completed by a weather station to monitor environmental conditions, an absolute pressure sensor for recording infrasound data, and a broadband seismometer. As an additional instrument we installed a thunderstorm detector BTD300.

 

In a first step we use the infrasound data (complemented by four stations from the japanese network) to generate an event catalog. The main reason for doing this is the fact that the Japanese Meteorological Society (responsible for monitoring) only reports eruptions higher than 1000 m above the vent, but there are certainly more but smaller eruptions. The event catalog based on infrasound data is complemented by the events detected by our radar systems and the field mills. In the presentation we will discuss the detection limits of the network as well as the observed electrification of the volcanic cloud that may lead to lightning, which leaves a clear signal in the electric field data. We will present some initial numerical simulations on where the strongest electric field in an eruption column occurs and discuss the impact of charging due to fractoemission and triboelectrification. Using the measured data and our initial numerical model calculations we explore which dynamic conditions appear to be favorable for lightning to occur and which not.
Comparing the ionospheric response to the 2008/2009 and 2018/2019 SSW events
Authors: Siddiqui Tarique Adnan , Yamazaki Yosuke , Stolle Claudia
Published: March 2020

It is now well accepted that the ionosphere and thermosphere are sensitive to forcing from the lower atmosphere (troposphere-stratosphere) owing mainly to the progress that have been made in the last decade in understanding the vertical coupling mechanisms connecting these two distinct atmospheric regions. In this regard, the studies linking the upper atmosphere (mesosphere-lower thermosphere-ionosphere) variability due to sudden stratospheric warming (SSW) events have been particularly important. The change of stratospheric circulation due to SSW events modulate the spectrum of vertically upward propagating atmospheric waves (gravity waves, tides, and planetary waves) resulting in numerous changes in the state of the upper atmosphere. Much of our understanding about the upper atmospheric variability associated due to the SSWs events have been gained by studying the 2008/2009 SSW event, which occurred under extremely low solar flux conditions. Recently another SSW event in 2018/2019 occurred under similar low solar flux conditions. In this study we simulate both these SSW events using Whole Atmosphere Community Climate Model with thermosphere and ionosphere extension (WACCM-X) and present the findings by comparing the ionospheric and thermospheric response to both these SSW events. The tidal characteristics of the semidiurnal solar and lunar tides and the thermospheric composition for both these SSW events are compared and the causes of varying responses are investigated.
Catchment scale simulations of the climatic regulation of fine sediment evacuation after widespread landsliding
Authors: Croissant Thomas , Hilton Robert , Lague Dimitri , Densmore Alexander , Howarth Jamie , Steer Philippe , Wang Jin , Davy Philippe
Published: March 2020

In mountain ranges, widespread landsliding triggered by large earthquakes can mobilise large amounts of non-cohesive sediment and organic matter that can be transported by rivers during the post-seismic landscape relaxation phase. The timescales over which this occurs are likely to be decades, meaning that it is difficult to establish the controls on post-seismic sediment evacuation from modern-day case studies. River gauging station data, reservoir and lake sediments have been helpful to constrain the temporal dynamics of fine sediment evacuation. However, key unknowns remain, particularly with regard to the competition between sediment supply and river transport capacity in space and time. Here, we attempt to tackle this using a 2D morphodynamic approach by applying the numerical model Eros at the catchment scale. We aim to systematically investigate how the properties of landslide populations and the runoff intensity and variability combine to control fine sediment export as suspended load from storm events to years and decades. Our focus is on the Potters Creek catchment located in the Southern Alps of New Zealand, where the Alpine Fault can generate Mw 8 earthquakes and which has one of the highest precipitation rates measured in the world. The chosen tectonic scenarios encompass different earthquake shaking intensities that translate to various landslide densities. Landslide properties are randomly sampled from empirical scaling relationships and the mobilised sediment is introduced in the landscape using a runout algorithm. The runoff distribution is constrained by empirical data and applied as climate forcing of the simulations. Prior to the quantification of the sediment export, we set up a calibration phase to constrain the sediment entrainment and deposition laws against data measured in the West Coast of New Zealand. Subsequently, an exploration phase is developed to quantify the sediment evacuation sensitivity to climatic parameters and the earthquake-derived landslide distribution properties. We find that the post-seismic sediment discharge is strongly controlled by the amount of sediment supplied and the accessibility of the sediment to fluvial transport. These two properties control the power-law scaling relationship (intercept and slope) between daily sediment concentration and water discharge. Runoff intensity and the sequence of discharge events plays a central role on the export velocity of the fine sediment. Simulations show that fine sediment transport can rapidly (with year) return to apparent pre-disturbance levels, before experiencing a renewed wave of sediment at the catchment outlet from more distal sources. These simulations provide new insight on the common controls and complexities of the evacuation of fine sediment from earthquake-triggered landslides.
Recent trends of groundwater temperatures in Bavaria, Germany
Authors: Hemmerle Hannes , Bayer Peter
Published: March 2020

Surface temperature variations have been well shown to transfer their thermal signature into the subsurface. This continuous heat transfer manifests in altered thermal conditions in the subsurface where temperature variations over a long lapse of time are more pronounced than shorter ones. Hence, repeated temperature depth profiles allow to investigate the effects of recent climate change on the subsurface. In this study we present recent temperature trends in more than 40 observation wells in Bavaria, Germany. Temperature depth profiles have been quarterly measured for one year between 1992-1994 and measurements have been repeated two times in 2019. The quarterly measurements reveal that the periodic seasonal temperature signal dampens to around 0.1 K at a depth of 15 m below ground surface. This implies that temperature variations below this depth can be used as climate archives as they store the temperature history of multiple years. The measurements span a time period of almost 30 years which is the most common period of reference for deriving climate normals according to the World Meteorological Organization. Therefore, the findings of recent subsurface temperature variations are assessed versus and complemented by 22 air temperature stations. Preliminary results show, that the linear regression of the annual mean air temperature since 1990 yields a slope of 0.35 ± 0.11 K 10a-1. In the subsurface, median temperature differences of the respective baselines from 1992-94 period and 2019 are 0.26, 0.13 and 0.07 K 10a-1 at 20, 40 and 60 m depth below surface, accordingly. Despite the common magnitude and continuous downward decrease, subsurface temperature differences exhibit a much higher variance compared to air temperature changes. This is due to local effects, such as varying thermal conductivities of the subsurface, latent heat transport caused by evapotranspiration, lateral and vertical groundwater flow, and anthropogenic influences. Our contribution will feature a comparison of this temperature change in response to recent atmospheric climate change in Bavaria and link these results with perceptions gained by similar investigations on local scale in other European regions.
Change in Mt. Elbrus nival-glacial system in the last century
Authors: Sokratov Sergey , Seliverstov Yuri , Turchaniniva Alla , Kharkovets Evgenii , Evangelista da Silva Heitor
Published: March 2020

We investigated the long-term dynamics of four glaciers that are part of the nival-glacial system of Mount Elbrus and located on its southern slope: Terskol, Garabashi, Malyi Azau, Bol’shoi Azau. The time period of the study covers 1887–2017. Glaciological measurements were carried out using DEM, compiled from early-year maps and from the results of stereo surveys in 2017, made by UAVs and high-resolution digital camera. New results present the change in the area of these glaciers, the elevation of their lowest points and the height of the surface. All these characteristicsindicate decrease of glaciation at the southern slope of Elbrus and intensification of this process in the last decade. Some differences in dynamics of changes of different glaciers can be explained by differences in their morphological types, morphometric indicators, the state of the beds, which we do not have much information about. Additionally, cores of two near glaciers lakes sediments were extracted and analyzed, offering high resolution record of sedimentation. The age of the bottom lake sediments near Malyi Azau glacier corresponds to documented beginning of the lake formation due to glacier ice retreat in 1950th. The other lake to the side of the Garabashi glacier was formed much earlier and the upper 15 cm of the lake sediments core is formed between 1893 and 2016.

The obtained results are compared with the results of other investigations. We believe that the new data of glaciers dynamics is more accurate and more promising in understanding the specific of accumulation and melt in dependence on elevation, slopes aspect s and angle.
Elimination of the geomagnetic field impairs adult hippocampal neurogenesis and cognition
Authors: Zhang Bingfang , Wang Lei , Zhan Aisheng , Tian Lanxiang , Wang Min , Guo Weixiang , Pan Yongxin
Published: March 2020

Elimination of the geomagnetic field impairs adult hippocampal neurogenesis and cognition

Bingfang Zhang1,2,4, Lei Wang3,4, Aisheng Zhan1,2,4, Min Wang3, Lanxiang Tian1,2,*, Weixiang Guo3,4,*, Yongxin Pan1,2,4,

1Biogeomagnetism group, Key Laboratory of Earth and Planetary Physics, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing 100029, China

2Innovation Academy for Earth Science, Chinese Academy of Sciences, Beijing 100029, China

3State Key Laboratory for Molecular and Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China

4University of Chinese Academy of Sciences, Beijing 100049, China

The geomagnetic field (present-day intensity 25-65 μT, GMF) plays a fundamental role in the survival and evolution of organisms, but organisms including human beings could be exposed to hypomagnetic field (HMF, intensity < 5 μT), e.g., during geomagnetic polarity reversals, some artificial environments without GMF such as magnetic shielded room, and the prolonged periods in deep-space travelling. Previous studies have shown that HMF exposure could trigger central nervous system (CNS) dysfunction-like behavioral effects and influence the cognitive processes of various animals, from insects to human beings. However, the underlying mechanism is still an enigma. In general, adult hippocampus continuously generates new-born neurons throughout animals’ life which are functionally integrated into hippocampal circuits and contribute to memory and learning, and the process of adult neurogenesis has been shown to be strongly influenced by a variety of environment stimuli. Here, we show that long-term HMF exposure markedly attenuates cell proliferation, influences multiple stages of neurogenesis of adult hippocampus, resulting in the impairments of hippocampal neurogenesis and hippocampus-dependent cognition of mice. This study provides new insights into the potential risk of long-term HMF exposure on adult hippocampus in deep space missions.
Quantifying uncertainty in the ESA Ocean Colour – Climate Change Initiative dataset for assimilation of total chlorophyll and phytoplankton functional types
Authors: Fowler Alison , Skákala Jozef , Ciavatta Stefano
Published: March 2020

Monitoring biogeochemistry in shelf seas is of great significance for the economy, ecosystems understanding and climate studies. Data assimilation can aid the realism of marine biogeochemistry models by incorporating information from observations. An important source of information about phytoplankton groups and total chlorophyll is available from the ESA OC-CCI (ocean colour - climate change initiative) dataset.

For any assimilation system to be successful it is important to accurately represent all sources of data uncertainty. For the ocean colour product, the propagation of errors throughout the ocean colour algorithm makes the characterisation of the uncertainty challenging. However, the problem can be simplified by assuming that the uncertainty is a function of optical water type (OWT), which characterises the water column of each observed pixel in terms of their reflectance properties.

Within this work we apply the well-known Desroziers et al. (2005) consistency diagnostics to the Met Office’s NEMOVAR 3D-VAR DA system used to create daily biogeochemistry forecasts on the North-West European Shelf. The derived estimates of monthly ocean colour error covariances stratified by OWT are compared to previously derived estimates of the root mean square errors and biases using in-situ data match ups (Brewin et al. 2017). It is found that the agreement between the two estimates of the error variances have a strong seasonal and OWT dependence. The error correlations (which can only be estimated with the Desroziers’ method) in some instances are found to be significant out to a few 100km particularly for more turbid waters during the spring bloom. The reliability and limitation of these two estimates of the ocean colour uncertainty are discussed along with the implications for the future assimilation of ocean colour products and for ecosystem and climate studies.
An Assessment of Long-Term Temperature Variability in the Sierra de Guadarrama (Spain)
Authors: Vegas Cañas Cristina , González Rouco J. Fidel , Navarro Montesinos Jorge , Lucio Eceiza Etor E. , García Bustamante Elena , Álvarez Arévalo Inés , Rodríguez Camino Ernesto , Chazarra Bernabé Andrés , García Pereira Félix
Published: March 2020

This work provides a first assessment of temperature variability from interannual to multidecadal timescales in the Sierra de Guadarrama, located in central Spain, from observations and regional climate model (RCM) simulations. Observational data are provided by the Guadarrama Monitoring Network (GuMNet; www.ucm.es/gumnet) at higher altitudes and by the Spanish Meteorological Agency (AEMet) at lower sites. An experiment at high horizontal resolution of 1 km using the Weather Research and Forecasting (WRF) RCM, feeding from ERA Interim inputs, is used. Through model-data comparison, it is shown that the simulations are annually and seasonally highly representative of the observations, although there is a tendency in the model to underestimate observational temperatures, mostly at low altitudes. Results show that WRF provides an added value in relation to the reanalysis, with improved correlation and error metrics relative to observations.

The analysis of long term trends shows no significant temperature trends in the area during the last 20 years. However, when spanning the analysis to the whole observational period, back to the beginning of the 20th century at some sites, significant annual and seasonal temperature increases of ca. 1degC/century develop, most of it happening during de 1970s.

The temporal variability of temperature anomalies in the Sierra de Guadarrama is highly correlated with the temperatures in the interior of the Iberian Peninsula. This relationship can be extended broadly over south-western Europe.
The future of soil biochemistry and services in the UK under plausible climate, land use and land management scenarios
Authors: Yumashev Dmitry , Janes-Bassett Victoria , Davies Jess
Published: March 2020

In this study, we explore plausible future states of soil organic matter, biomass, food production and soil greenhouse gas emissions across the UK under a range of climate, land use and land management scenarios. We use state-of-the-art soil biochemistry model, N14CP-Ag, combined with UKCP18 climate scenarios and ASSET land cover change and crop scenarios mapped onto a UK-wide grid with around 100,000 land parcels. Historic runs cover the period from the start of the Holocene interglacial (-12 kyr BP) to 2015; scenarios run from 2016 out to 2100. The results show variations of soil organic carbon (SOC) of around 10% between 2016 and 2100 relative to the simulated starting value of 1.4 Gton in 2015, with reductions of up to 7% under arable expansion scenarios and increases of up to 3% under grassland restoration scenarios. The effect of changing cropping patterns on UK-wide SOC is comparatively small. As climate scenarios move from lower to higher global emissions, the SOC reductions under arable expansion become more pronounced, while the SOC increases under grassland restoration diminish and eventually turn into losses. UK-wide crop yields show resilience to climate change and are maximised for the arable expansion scenario with protected sites of special scientific interest. Soil CO2 and nitrogen emissions get progressively higher in warmer climates. The results of this study are expected to contribute to a future UK agricultural policy aimed at rewarding farmers for sustainable land management practices.
Impact of soil wetness on plant litter decomposition using low-cost soil moisture sensors and off-the-shelf tea bags
Authors: Xaver Angelika , Sandén Taru , Spiegel Heide , Zappa Luca , Rab Gerhard , Hemment Drew , Dorigo Wouter
Published: March 2020

Soil organic matter plays a key role within the nutrient cycle, serves as an agent to improve soil structure, and is also known to impact concentrations of greenhouse gases and stabilize soil pollutants. Thus, the soil organic matter content and its potential losses through decomposition are of high interest, especially in the light of a changing climate. As the decomposition process is significantly influenced by climatic conditions, it is important to understand the relationship between decomposition and environmental variables. Previous studies primarily focused on determining the influence of air temperature and precipitation on litter decomposition, but the impact of soil moisture has hardly been investigated.

In this study, we evaluate the relationship between plant litter decomposition, using commercial tea bags (Green and Rooibos tea) as standardized plant litter, and soil moisture, observed with low-cost sensors used within the European citizen science project GROW Observatory (GROW; https://growobservatory.org/). The low-cost soil moisture sensors were placed alongside the tea bags at eight different locations, covering four different land cover types, within the Hydrological Open Air Laboratory (HOAL), a small agricultural catchment in Petzenkirchen, Austria. Data has been collected for two years providing decomposition rates (k) and stabilization factors (S) for the four different seasons of both years. Apart from soil moisture, we investigate air and soil temperature, precipitation and soil parameters as drivers for litter decomposition.

We will show preliminary results on the relationship between decomposition and different environmental variables, in particular soil moisture, throughout all seasons and various land cover classes.

 

This study was funded by the GROW Observatory project of the European Union’s Horizon 2020 research and innovation programme (https://growobservatory.org/).
From climate variability to heavy precipitation – Learning transfer functions from data
Authors: Kałczyński Michał , Krawiec Krzysztof , Kundzewicz Zbigniew
Published: March 2020

The contribution deals with spatial extremes of intense precipitation at the global scale, with the help of data-driven modelling. We ask whether the inter-annual and inter-decadal climate variability track plays a dominant role in the interpretation of the variability of heavy precipitation, globally. The study aims at discovering spatially and temporally organized links between climate oscillation indices, such as El Niño-Southern Oscillation, North Atlantic Oscillation, Pacific Interdecadal Oscillation, Atlantic Multidecadal Oscillation and heavy precipitation. To this aim, we induce a range of machine-learning models, primarily recurrent neural networks, from multiple sources of global observations, including E-OBS data set from the UERRA project, GPCC Full Data Daily, and climate variability indices. The models are thoroughly tested and juxtaposed in hindcasting mode on a separate test set and scrutinized with respect to their statistical characteristics. We expect to identify climate-oscillation drivers for spatial dependence of heavy precipitation.