bluuebunny/crossref_metadata_2025 huggingface dataset:
Measuring urban rainfall with a dense Commercial Microwave Link network in Lagos, Nigeria
Authors: Droste Arjan , Overeem Aart , Priebe Jan , Tricarico Daniele , Bogerd Linda , Leijnse Hidde , Uijlenhoet Remko
Published: March 2021

Measuring urban precipitation adds extra difficulty to the already challenging task of quantitative precipitation estimation. Buildings form obstructions that can block ground-based precipitation radar signals, and the complex urban microclimate makes gauge measurements representative for only a very small area. Performing precipitation measurements in an urban setting thus benefits from using many different data sources, to capture the largest possible range of scales. As such, opportunistic sensing techniques are especially valuable for urban hydrometeorological research: the use of unconventional data sources to extract valuable data that can allow us to estimate urban precipitation. One of the more prominent data sources is the use of Commercial Microwave Links –CMLs – to measure rainfall, by making use of the signal attenuation between cell phone towers. This method of estimating rainfall has been mostly tested and applied in developed countries that already have reasonable coverage of conventional precipitation measurements. However, the most benefits are to be made in developing regions lacking such measurement networks. Only few studies address this, generally using relatively small datasets.

This research focuses on tropical CML rainfall estimation in Lagos, Nigeria. This African megacity has a dense network of CMLs and few official measurement stations, making it an interesting area to study the effectiveness of urban CML precipitation measurements in such a region. We employ the open-source R package RAINLINK to obtain 15-min rainfall maps based on data from a few thousand CMLs during the rainy season. We optimise the most important RAINLINK parameters by comparing to rain gauge data, considering local network and environmental conditions. In addition, disdrometer data from Nigeria or similar climates are used to compute the values of the physically-based coefficients relating specific attenuation to rainfall rate.
Escarpment retreat on a viscoelastic lithosphere 
Authors: Ruetenik Gregory , Moucha Robert
Published: March 2021

Rift escarpments have long been the subject of coupled geodynamic/landscape evolution studies.  Many of these studies have shown that the flexural unloading response of the lithosphere plays a significant role in the rate of divide migration and the longevity of the escarpment topography, with lower elastic thickness values allowing for more localized isostatic rebound of the lithosphere in response to erosional unloading. However, rift escarpments are thought to last hundreds of millions of years, and therefore the lithosphere may exhibit viscoelastic behavior on this timescale.  Here we present a simplified model of a viscoelastic response to erosional unloading during escarpment evolution, and show that this drastically alters the behavior of the escarpment system.  Specifically, the escarpment retreat rate is significantly reduced, and topography maintained, when compared to a purely flexural model. Additionally, the area in front of the retreating the scarp (i.e., seaward of the scarp) experience delayed uplift response and topographic rejuvenation many millions of years after the divide passes.      
Physical a priori solar radiation pressure models for GNSS satellites with the focus on BDS
Authors: Duan Bingbing , Hugentobler Urs , Selmke Inga , Marz Stefan
Published: March 2021

A physical a priori box-wing solar radiation pressure (SRP) model is widely used by most analysis centers for Galileo and QZSS (Quasi-Zenith Satellite System) satellites, complemented by an ECOM or ECOM2 (Empirical CODE Orbit Model) model. For the other constellations, for instance GPS and GLONASS satellites, optical properties of satellite surfaces are not publicly available, especially for GPS Block IIF and GLONASS satellites. By fixing satellite surface areas and total mass to the values from some unpublished documents, we estimate satellite surface optical properties based on true GNSS measurements covering long time periods (typically this should be longer than a full beta angle time range to reduce correlations between parameters). Meanwhile, various physical effects are considered, such as yaw bias, radiator emission and thermal radiation of solar panels. We find that yaw bias of GPS Block IIA and IIR satellites does not dominate the Y-bias, it is likely that heat generated in the satellite is radiated from louvers or heat pipes on the Y side of the satellite. It is also noted that the ECOM Y0 estimates of both GPS and GLONASS satellites show clear anomaly during eclipse seasons. This indicates that the radiator emission is present when the satellite crosses shadows. Since satellite attitude during eclipse seasons could be different from the nominal yaw, potential radiator effect in the –X surface could be wrongly absorbed by the ECOM Y0 as well. By considering all the estimated parameters in an a priori model we observe clear improvement in satellite orbits, especially for GLONASS satellites. China’s Beidou-3 satellites are now providing PNT (positioning, navigation and timing) service globally. Satellite attitude, dimensions and total mass are publicly available. Also, the absorption optical properties of each satellite surface are given. With all this information, we estimate the other optical properties of Beidou satellites considering similar yaw bias, radiator and thermal radiation effects as those in GPS and GLONASS satellites.
Estimation of station-dependent LRA correction parameters for the TOPEX/Poseidon mission
Authors: Zeitlhöfler Julian , Bloßfeld Mathis , Rudenko Sergei , Seitz Florian
Published: March 2021

Launched in 1992, the TOPEX/Poseidon (T/P) mission is one of the first major altimetry missions. It is the predecessor of the Jason satellites which orbit the Earth on a very similar orbit. The geodetic space technique SLR (Satellite Laser Ranging) provides observations of this mission by targeting the Laser Retroreflector Array (LRA) mounted on the spacecraft. The T/P LRA is extremely large and not optimally designed. It thus causes big variations in the LRA phase center. These variations are a significant limiting factor of the orbit accuracy which makes it essential to apply a measurement correction for precise orbit determination. Up to now, only tabulated LRA corrections are available which require an interpolation.

In this contribution, we present a new approach to determine station-dependent LRA corrections to improve the phase center variations. The approach is based on a continuous analytical correction function which only uses the observation azimuth and zenith angle in combination with four parameters. These parameters are computed within an estimation process for each observing SLR station. Therefore, uncorrected SLR residuals based on raw SLR normal point observations are used. The correction value is added to the SLR measurement and counteracts the LRA phase center variations.

The advantages of this method are the continuous functional, which is easy to implement in existing software packages, as well as the avoidance of an interpolation between tabulated values. Furthermore, the differences between orbits determined with and without the LRA correction will be presented. Station coordinate time series and orbit comparisons with external T/P orbits are investigated in order to prove the high quality of the obtained LRA corrections.
Generating families of synthetic forecasts of different skills from an existing forecast product
Authors: Rougé Charles
Published: March 2021

An emerging literature evaluates the water management benefits of hydroclimatic forecasts with timescales of a few days to several months ahead. These studies rely on existing forecast products, which they compare to one another and to baseline scenarios, such as perfect forecast or usual climate or streamflow conditions. Results compare the different products and baselines, both in terms of forecast skill and in terms of value for water management. Yet, the means to systematically explore the link between forecast skill and value (e.g., in terms of water supply reliability or hydropower production) are hampered by the lack of techniques to generate synthetic forecasts that 1) are realistic in that they present similar statistical properties to existing products, and 2) foster productive two-ways conversations between the analysts and academics who propose new products and those who use them to inform decision-making, so they can determine where to focus further product development efforts.

This work proposes a methodology for generating forecasts from an existing product and existing hydroclimatic records (rainfall, temperature, streamflow…). It perfects and extends a recent synthetic forecast generation technique that deterministically generates a forecast for a point in the future with the desired bias and accuracy, using a linear combination of the quantity to predict with a predictor. It perfects it by proposing a methodology to generate a family of forecasts with desired skill and bias, for several of the most common skill measures, including mean absolute error and (root) mean square error. Generated synthetic forecasts are therefore based on existing products and retain their statistical properties while presenting improved skill. The skill improvement can apply to the whole forecast or only to targeted conditions, e.g., drought or flood conditions, or forecasts during and for a certain period of the year. This opens the doors to systematic exploration of the benefits of marginal forecast improvements. The technique is also extended to ensemble (or probabilistic) forecasts, to allow for generating synthetic ensembles with targeted improvements to the continuous ranked probability skill score (CRPSS).
Man-made disaster on urban area: subsidence and underground salt dissolution in Maceio (Brazil) revealed by remote sensing and numerical modelling
Authors: Vassileva Magdalena , Al-Halbouni Djamil , Motagh Mahdi , R. Walter Thomas , Dahm Torsten , Wetzel Hans-Ulrich
Published: March 2021

Land subsidence hazard affects many highly populated urban areas of the world as a consequence of natural and/or anthropogenic derived geomechanical rock alterations. Here we exploit the full archive of Synthetic Aperture Radar (SAR data) and present a 16-years history (2004-2020) of surface displacement affecting the federal capital of Maceió (Alagoas, Brazil), where sinkhole formation and fractures on infrastructures have been intensified since early 2018, forcing authorities to relocate the affected residence and pose the building under demolition. The geodetic result shows that precursory deformations were already visible in early 2000’s, reaching in November 2020 a maximum cumulative subsidence of approximately 2 m near the Mundaú lagoon coast. The maximum rate of subsidence is estimated at 27 cm/year. Numerical elastic source modelling proves that the subsidence is associated with localized, deep seated material removal at the location and depth where salt mining is performed. More sophisticated 2D distinct element method highlights the formation of cracks in sedimentary layers that eventually enables strong water percolation from rather superficial aquifers into the deeper underground, with potential increase of material dissolution and erosion. We discuss the accelerating subsidence rates, the influence of severe precipitation events to the aforementioned geological instability and the related dynamic evolution of the subsidence hazard by generating dynamic geohazard maps valuable for further infrastructure risk assessment.
Anomalies of continental precipitation associated with El Niño Southern Oscillation: the role of moisture contribution from oceanic and terrestrial sources 
Authors: Sorí Rogert , Nieto Raquel , Liberato Margarida L.R. , Gimeno Luis
Published: March 2021

The regional and global precipitation pattern is highly modulated by the influence of El Niño Southern Oscillation (ENSO), which is considered the most important mode of climate variability on the planet. In this study was investigated the asymmetry of the continental precipitation anomalies during El Niño and La Niña. To do it, a Lagrangian approach already validated was used to determine the proportion of the total Lagrangian precipitation that is of oceanic and terrestrial origin. During both, El Niño and La Niña, the Lagrangian precipitation in regions such as the northeast of South America, the east and west coast of North America, Europe, the south of West Africa, Southeast Asia, and Oceania is generally determined by the oceanic component of the precipitation, while that from terrestrial origin provides a major percentage of the average Lagrangian precipitation towards the interior of the continents. The role of the moisture contribution to precipitation from terrestrial and oceanic origin was evaluated in regions with statistically significant precipitation anomalies during El Niño and La Niña. Two-phase asymmetric behavior of the precipitation was found in regions such the northeast of South America, South Africa, the north of Mexico, and southeast of the United States, etc. principally for December-January-February and June-July-August. For some of these regions was also calculated the anomalies of the precipitation from other datasets to confirm the changes. Besides, for these regions was calculated the anomaly of the Lagrangian precipitation, which agrees in all the cases with the precipitation change. For these regions, it was determined which component of the Lagrangian precipitation, whether oceanic or terrestrial, controlled the precipitation anomalies. A schematic figure represents the extent of the most important seasonal oceanic and terrestrial sources for each subregion during El Niño and La Niña.
Effect of bench terracing on ground dwelling arthropods 
Authors: Simões Liliana B , Martins Martinho  A S , Puga João R L , Keizer Jan J , Abrantes Nelson
Published: March 2021

Eucalypt trees are the most planted tree in the world, and in Portugal these plantations occupy 26% of the forested area. The area of Eucalypt monoculture is growing since the 50’s due to the importance of this tree for the pulp and paste industry. With short rotation cycles, it is important to facilitate the cut and transport of the logged trees. In this sense, many forested areas in mountainous regions are being terraced with bulldozers.

Terracing is a well know soil conservation practice, reducing runoff peak flows, increasing water infiltration and subsequent low soil erosion rates. Nevertheless, the impacts of terracing for eucalypt plantations are still unknown, especially in terms of biodiversity of soil fauna. Hence, to address this research gap, the present study aimed to assess the impacts of terracing on the ground dwelling arthropods in eucalypt plantations.

This study took place in a mountain slope with old eucalypt trees that were logged (May 2019) and then terraced (July) as ground preparation to receive a new eucalypt plantation. The community of ground dwelling arthropods were accessed using pitfall traps.  The arthropods were collected before the terracing process, in Spring 2019, and then seasonally after terracing until the Spring of 2020Total abundance and richness at order level, as well as, abundance, richness, Shannon-Wiener diversity and Pielou’s Evenness indexes, at Family level of Coleoptera, Araneae and Hymenoptera, were used to depict differences between pre- and post-terracing. The results showed that although terracing did not reduce the total abundance or richness, it changed the community structure. In particular, it was observed an increase in opportunist and generalist families after terracing such as Staphylinidae and Myrmicinae. The spider community also changed, with more hunter families captured after the terrace construction. In overall, the results of our study reveal that although the total abundance and richness of arthropods was not altered by the construction of terraces, their structure was modified.
Characterization of the morning transition from downslope to upslope winds and its connection with the nocturnal inversion breakup at the foot of a gentle slope
Authors: Farina Sofia , Zardi Dino , Di Sabatino Silvana , Marchio Mattia , Barbano Francesco
Published: March 2021

Thermally driven winds observed in complex terrain are characterized by a daily cycle dominated by two main phases: a diurnal phase in which winds blow upslope (anabatic), and a nocturnal one in which they revert their direction and blow down slope (katabatic). This alternating pattern also implies two transition phases, following sunrise and sunset respectively. 

Here we study the up-slope component of the slope wind with a focus on the morning transition based on from the MATERHORN experiment, performed in Salt Lake Desert (Utah) between Fall 2012 and Spring 2013. 

The analysis develops along three main paths of investigation. The first one is the selection of the suitable conditions for the study of the diurnal component and the characterization of the morning transition. The second one focuses on the deep analysis of the erosion of the nocturnal inversion at the foot of the slope in order to investigate the physical mechanisms driving it. And the third one consists in the comparison between the experimental data and the results of an analytical model (Zardi and Serafin, 2015). The study of the morning transition in the selected case studies allowed its characterization in terms of the relation with the solar radiation cycle, in terms of its seasonality and in terms of its propagation along the slope and along the vertical direction. Most of the results of this investigation are related to the identification of the main mechanisms of erosion of the nocturnal inversion at the foot of the slope and to its role to the beginning of the transition itself. Finally, it is shown how the above model can fairly reproduce the cycle between anabatic and katabatic flow and their intensity.

Zardi, D. and S. Serafin, 2015: An analytic solution for daily-periodic thermally-driven slope flow. Quart. J. Roy. Meteor. Soc., 141, 1968–1974.
Estimates of Southern Ocean carbon uptake from atmospheric inverse analyses
Authors: Chen Zhaohui , Suntharalingam Parvadha , Le Quere Corinne , Watson Andrew , Shutler Jamie
Published: March 2021

We present estimates of Southern Ocean air-sea CO2 fluxes for the period 2000-2018 derived with the GEOSChem-LETKF (GCL) inverse analysis system in conjunction with the NOAA surface CO2 monitoring network (ObsPack, Cooperative Global Atmospheric Data Integration Project, 2018).  We assess the impact of alternative representations of the ocean prior flux distribution and its associated uncertainties on derived flux estimates.  Ocean flux distributions assessed include the surface pCO2-based representation of Landschutzer et al. 2016 and the more recent pCO2-based estimates of Watson et al. 2020.  We present GCL estimates of the long-term trend and interannual variability of air-sea CO2 fluxes in the Southern Ocean (south of 45˚S). These results are assessed against independent estimates from atmospheric inverse analyses and ocean biogeochemical models taken from the Global Carbon Budget 2020 synthesis (Friedlingstein et al. 2020).
A methodological framework for assessing changes in future drought risk: evaluation over Australia
Authors: Araujo Diogo , Marra Francesco , Merow Cory , Nikolopoulos Efthymios
Published: March 2021

Accumulating evidence on the increase of intensity and frequency of climate extremes such as droughts, necessitates the development of effective climate adaptation procedures. To inform adaptation and mitigation strategies we need to develop improved methodologies for assessing future drought risk. The outputs of such methodologies must be usable by various stakeholders (e.g. water, energy and biodiversity conservation managers) and must be scalable (from regional to global) and methodologically robust. Severity-duration-frequency (SDF) curves serve as a concise way to quantitatively and qualitatively represent anticipated changes in drought risk and thus offer an optimum way to convey information on future drought risk across scientific disciplines and stakeholders. In this work we are presenting a methodological framework for assessing future drought risk that integrates state-of-the-art high-resolution (~10km) climate data from ERA5-Land reanalysis and downscaled CMIP6 projections with novel statistical procedures for robust estimation of SDF curves. Results are presented for Australia and are based on meteorological drought identification based on the widely established indicators of  Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI). Comparison between historic (1981-2019) and future (2020-2100) drought characteristics reveal that severity and duration tends to increase towards the end of the century. The spatial extent of severe and extreme droughts is also projected to increase, particularly in central and western Australia. The SDF analysis highlights a consistent increase in severity of extreme (i.e. 100yr) drought towards the end of century. While there is still significant uncertainty on the projected magnitude of increase, the multi-model analysis reveals that increasing trend of drought risk is consistent across models . The proposed framework can be applied at global scale and can be easily modified to incorporate additional drought indicators.
Supervised and unsupervised learning algorithms for extreme summer temperature prediction
Authors: Pyrina Maria , Zorita Eduardo , Wagner Sebastian
Published: March 2021

In order to predict the timing of extreme summer seasons in terms of 2 meters surface temperature (t2m), two algorithms are applied in the output of a global paleoclimate simulation. The model simulation is conducted with the Max Planck Institute Earth System Model configuration for paleoclimate (MPI-ESM-P). Global model output is provided for the period 0–1999 AD on a horizontal resolution of approximately 187 km (1.875°× 1.875°longitude by latitude grid). The t2m extremes are defined as the events with mean summer temperature higher than the 95th percentile of the training period (0-1970 AD) and are calculated separately for each grid point of the European region between 35ºN-70ºN, 10ºW-30ºE. The algorithms are trained only with data from the training period and are set to predict the summer t2m extremes of the test period 1971-1999 AD. The predictor data used for fitting the algorithms are chosen based on their known influence as boundary forcings of European summer climate. The predictor variables include springtime sea surface temperature (SST) from the NA region (0º-76ºN, 85°W-30°E) and springtime European soil moisture (SM). The skill of the predictions is evaluated based on the extremal dependence index (EDI), which depends on the hit rate and false alarm rate. The EDI values vary between -1 and 1, where 1 is the skill of a perfect forecast. The first algorithm tested is a supervised learning algorithm, which is based on a random forest classifier (RF). RF predicts the highest EDI values over Scandinavia, Scotland and around the Mediterranean region (EDI>0.5), with the SST predictor being the main contributor to that skill. The second algorithm tested, is an autoencoder neural network (AE) that learns data codings in an unsupervised manner. AE surpasses the RF skill above most European regions and predicts the highest EDI values over the southeast Mediterranean, Central Europe, and the British Isles. The AE neural network is also trained to predict the absolute value of the extreme t2m events. The skill of reproducing the absolute value of the target t2m extremes is evaluated with the Mean Absolute Error (MAE), only for those extreme events that are reproduced by the AE prediction. The MAE values for the southeast Mediterranean region, Central Europe, and the British Isles are around 2 ºC, 2.5 ºC, and 1.5 ºC, respectively. We have demonstrated the possibility of predicting a season in advance the occurrence of extreme summer t2m using an AE neural network. The AE neural network was tested in the virtual reality of a model simulation. The second step will be the application of the trained network on observational data.
Methane in the climate system -- from the last glacial to the future
Authors: Kleinen Thomas , Gromov Sergey , Steil Benedikt , Brovkin Victor
Published: March 2021

Between the last glacial maximum (LGM) and preindustrial times (PI), the atmospheric concentration of CH4, as shown by reconstructions from ice cores, roughly doubled. It then doubled again from PI to the present. Ice cores, however, cannot tell us how that development will continue in the future, and ice cores also cannot shed light on the causes of the rise in methane, as well as the rapid fluctuations during periods such as the Bolling-Allerod and Younger Dryas.

We use a methane-enabled version of MPI-ESM, the Max Planck Institute for Meteorology Earth System Model, to investigate changes in methane cycling in a transient ESM experiment from the LGM to the present, continuing onwards into the future for the next millennium. The model is driven by prescribed orbit, greenhouse gases and ice sheets, with all other changes to the climate system determined internally. Methane cycling is modelled by modules representing the atmospheric transport and sink of methane, as well as terrestrial sources and sinks from soils, termites, and fires. Thus, the full natural methane cycle – with the exception of geological and animal emissions – is represented in the model. For historical and future climate, anthropogenic emissions of methane are considered, too.

We show that the methane increase since the LGM is largely driven by source changes, with LGM emissions substantially reduced in comparison to the early Holocene and preindustrial states due to lower temperature, CO2, and soil carbon. Depending on the future climate scenario, these dependencies then lead to further increases in CH4, with a further doubling of atmospheric CH4 easily possible if one of the higher radiative forcing scenarios is followed. Furthermore, the future increases in CH4 will persist for a long time, as CH4 only decreases when the climate system cools again.
Effects of lead width variation, re-freezing and mixing events on lead water structure in the central Arctic
Authors: Nomura Daiki , Web Alison , Li Yuhong , Dall’osto Manuel , Schmidt Katrin , Droste Elise , Chamberlain Emelia , Kawaguchi Yusuke , Inoue Jun , Damm Ellen , Delille Bruno
Published: March 2021

We undertook a lead survey during the international drift campaign MOSAiC, Leg 5 (from 22 August to 17 September 2020) to understand the effects of lead width variation, re-freezing, and mixing events on lead water vertical structure. At the beginning of the survey period, the freshwater layer was occupied for the top 1 m depth and there were strong vertical gradients in temperature, salinity, and dissolved oxygen (DO) within 1 m depth: from 0.0°C to –1.6°C for temperature, from 0.0 to 31.4 psu for salinity, and 10.5 to 13.5 mg L–1 for DO. A strong DO minimum layer corresponded with a salinity of 25 psu, and usually occurred at the freshwater–seawater interface at approx. 1 m depth, most likely as a result of an accumulation of organic matter and ongoing degradation/respiration processes at this interface. However, during the survey period, these strong gradients weakened and reduced the freshwater layer thickness (FLT). In the first half of the sampling period (until 4 September), FLT changed due to variations in lead width: as lead width increased, FLT decreased due to a stretching of the freshwater layer. In the second half of the sampling period, FLT was controlled by the surface ice formation (re-freezing) and mixing processes along the lower boundary of the freshwater layer. Surface ice formation removed freshwater and the formation of surface ice (about 0.2 m thick) explains 20% of the reduction of FLT. The remaining 80% of the reduction of FLT was due to the mixing process within the water column that was initiated by cooling and re-freezing. This mixing process diluted the salinity from 31.6 to 29.3 psu in the water below freshwater layer towards the end of the survey period. Our results indicate that lead water structure can change rapidly and dynamically and that this has significant effects on the biogeochemical exchange between lead systems and the atmosphere.
Ancient warming pushed wetlands across biogeochemical tipping points
Authors: Pancost Richard , Naafs David , Inglis Gordon , Lauretano Vittoria
Published: March 2021

Ancient peat deposits provide valuable and complementary insight into the biogeochemical response of wetlands to climate perturbations, including potential tipping points in such systems. The combination of temperature (GDGTs) and hydrology (leaf wax hydrogen isotopic compositions) proxies with qualitative proxies for methanogenesis (archaeal lipid abundances) and methanotrophy (bacterial lipid carbon isotopic compositions) has revealed dramatic perturbations to the carbon cycle during transient warming events, including the Palaeocene Eocene Thermal Maximum.  Bacterially-derived hopanes in at least two PETM-spanning lignite sequences record negative carbon isotope excursions of near-unprecedented magnitude in response to rapid global warming.  The warming – either directly or indirectly – clearly caused a fundamental reorganisation of the carbon cycle in those ancient wetlands. Intriguingly however, these excursions persist for a far shorter duration than the PETM warming. Similarly, hopane δ13C values in lignites of the Early Eocene Climate Optimum, the warmth of which was reached more gradually, are similar to those of today. This suggests that these unusually isoptopically light hopanoids represent a transient disruption to the methane cycle associated with a climate perturbation rather than an equilibrium response to warmer temperatures.  Such an interpretation is consistent with Deglacial and Holocene peat-derived records, in which hopane δ13C values exhibit large responses to transient drying events and modest responses to longer-term change. Such findings could have implications for future climate change feedbacks, with the wetland methane cycle being particularly sensitive to the rate of climatic change.
Modelling clinopyroxene/melt partition coefficients for higher upper mantle pressures 
Authors: Schmidt Julia Marleen , Noack Lena
Published: March 2021

When partial melt occurs in the mantle, redistribution of trace elements between the solid mantle material and partial melt takes place. Partition coefficients play an important role when determining the amount of trace elements that get redistributed into the melt. Due to a lower density compared to surrounding solid rock, partial melt that was generated in the upper mantle will rise towards the surface, leaving the upper mantle depleted in incompatible trace elements and an enriched crust. Studies investigating trace element partitioning in the mantle typically rely on constant partition coefficients throughout the mantle, even though it is known that partition coefficients depend on pressure, temperature, and composition. Between the pressures of 0-15 GPa, partition coefficients vary by two orders of magnitude along both, solidus and liquidus. Since partition coefficients exhibit a parabolic relationship in an Onuma diagram, a similar variation is expected for all trace element partition coefficients that can be derived from the sodium partition coefficients.

In this study, we developed a thermodynamic model for sodium in clinopyroxene after Blundy et al. (1995). With the thermodynamic model results, we were able to deduce a P-T dependent equation for sodium partitioning that is applicable up to 12 GPa between the peridotite solidus and liquidus. Because sodium is an almost strain-free element in jadeite, it can be used as a reference to model partition coefficients for other elements, including heat producing elements like K, Th, and U. This gives us the opportunity to insert P-T dependent partition coefficient calculations of any trace element into mantle melting models, which will have a big impact on the accuracy of elemental redistribution calculations and therefore, if the partitioning of the heat producing elements is taken into account, also the evolution of the mantle and crust.

Blundy, J. et al. (1995): Sodium partitioning between clinopyroxene and silicate melts, J. Geophys. Res., 100, 15501-15515.

Schmidt, J.M. and Noack, L. (2021): Parameterizing a model of clinopyroxene/melt partition coefficients for sodium to higher upper mantle pressures (to be submitted)
Establishing an automatic atmospheric measurement network across an Arctic fjord system in Svalbard
Authors: Frank Lukas , Opsanger Jonassen Marius , Claes Stefan , Schalamon Florina
Published: March 2021

During the last couple of decades the sea-ice cover on Isfjorden at the west coast of Spitsbergen in Svalbard has seen a dramatic reduction, which has been linked to, amongst others, regional and local changes in weather patterns. As Isfjorden is the most heavily trafficked fjord in Svalbard, these changes directly impact all kinds of operations at sea. Therefore, good information about the atmospheric state over the fjord system does not only enhance our scientific understanding of air-ice-sea interactions and the local processes leading to the formation of sea ice, but furthermore contribute to planning and conducting field activities in a safer manner.

With a horizontal resolution of 2.5 km, the current operational version of the AROME-Arctic weather forecasting model of the Norwegian Meteorological Institute can provide a good overall representation of the atmospheric state over the Isfjorden fjord system. However, the complex topography, as well as fine-scale variations in the surface cover and the sea surface temperature due to the oceanographic circulation within the fjord, lead to local variabilities of atmospheric variables, which are only poorly resolved by the model. Amongst others, high-wind events and associated phenomena like channeling effects are suspected to have a large effect on both the air-ice-sea interactions and the formation of sea ice within the fjord as well as the safety at sea.

Therefore, we aim at establishing an automatic meteorological measurement network across Isfjorden. The network will consist of several all-in-one weather stations deployed at lighthouse stations all around the fjord. Additionally, mobile stations will be installed onboard small tourist fjord cruise ships. In that way, small-scale local variations in near-surface atmospheric wind and temperature fields can be resolved and their changes can be monitored throughout the year. By making use of already existing infrastructure as platforms for the instrumentation, the high-resolution measurements can be performed in remote areas at low costs and with a minimal environmental impact. In the end, a real-time transfer of the measured data via the cellular network will additionally provide very valuable information for planning and execution of field activities performed by e.g. UNIS, tourist companies, private individuals or the Governor of Svalbard.

We will in detail present the measurement network, the status of its setup and first results. A special focus will be put on the comparison of the measurements with the AROME-Arctic model data.
Development of a common definition approach for multi-event attribution of fire weather extremes
Authors: Liu Zhongwei , Eden Jonathan , Dieppois Bastien , Blackett Matthew
Published: March 2021

In response to the occurrence of large wildfire events across both hemispheres in recent years, the effort to understand the extent to which climate change may be altering the frequency of fire-conducive meteorological conditions has become an emerging subfield of attribution science. However, to date, the relative paucity of wildfire attribution studies, coupled with limited observational records, makes it difficult to draw solid and collective conclusions to better inform forest management strategies. The inter-study differences that emerge due to the choice of methodology and event definition are common to many attribution studies; for wildfire attribution in particular, the lack of consensus on how fire danger should be defined in a meteorological context presents an additional challenge.

Here, we present a framework for the simultaneous attribution of multiple extreme fire weather episodes of using an empirical-statistical methodology. Key to this framework is the development of a common spatiotemporal definition for extreme fire weather events. With reference to the fourth version of Global Fire Emissions Dataset (GFED4), we focus on all parts of the world that have experienced fires during the period 1995-2016. At each target grid point, we fit a Generalized Extreme Value (GEV) distribution, scaled by global mean surface temperature (smoothed over 4 years), to the annual maxima of a series of reanalysis-derived fire danger indicators (including the fire weather index) for the period 1980-2018. Using global maps of risk ratios and percentage of changes, we quantify the influence of recent global warming on the frequency and magnitude of fire weather extremes according to a common ‘event type’ definition, irrespective of their spatiotemporal occurrence. We subsequently conduct a collective attribution analysis of a series of recent exceptional events. We conclude with suggestions for further application to climate model ensembles and a discussion of the potential of our findings to inform decision-makers and practitioners.
Thermal properties evaluation of granitoid rocks by using Digital Imaging Analysis (DIA) and 2D modelling simulation
Authors: Sassi Raffaele , Coletti Chiara , Borghi Alessandro , Cossio Roberto , Dalconi Maria Chiara , Dalla Santa Giorgia , Peruzzo Luca , Vettorello Arianna , Galgaro Antonio
Published: March 2021

Seven granitoid rocks were selected due to the well-defined mineralogical content, the typical the holocrystalline texture, their absent (or very poor) Crystal Preferred Orientations (CPOs), and very-low porosity in order to apply a predictive approach that quantifies and simulates the rock thermal properties by considering the contributions of the mineral phases content. For this purpose, thermal properties of granodiorite, tonalite, granite, and gabbro rock samples were analysed and compared by (i) direct measurements on the bulk rock samples, (ii) by applying Quantitative Phase Analysis (QPA) on Digital Imaging Analysis (DIA) and Xray diffraction Rietveld method, and (iii) by 2D numerical modelling.

The results confirm the good accuracy of DIA-QPA method by the good according with data refined by X-Ray diffraction Rietveld method, and indicate the potential reliability of the more attractive approach in terms of prediction of the 2D modelling starting by the Quantitative Phase Analysis (QPA) based on Digital Imaging Analyses (DIA). This method, indeed, permits to observe concurrently different mineralogical and textural parameters (such as mineral abundance, grain size and grain size distribution), and it also provides a deep knowledge of the rock’s thermal behaviour.

Numerical modelling results indicate that a steady-state condition (SSC) is reached by the combination of thermal contribution given both in terms of modal mineral abundance (mainly controlled by mineralogical phase content related to the quartz occurrence) and in terms of rock texture (by the grain-size dimensions and the geometrical distribution of minerals), considering negligible the porosity.

The use of predictive models for the evaluation of the rocks thermal properties can find many important applications (e.g., in deep and shallow geothermal systems, as well as in building construction materials), and also permits to evaluate the expected energy performance of borehole heat exchange probes, involving granitoid lithologies, representing a suitable alternative also in cases where direct measures are not possible.
Characterizing waste disposal sites by using multi-spectral satellite imagery
Authors: Ganci Gaetana , Cappello Annalisa , Bilotta Giuseppe , Pollicino Giuseppe , Lodato Luigi
Published: March 2021

The application of remote sensing for monitoring, detecting and analysing the spatial and extents and temporal changes of waste dumping sites and landfills could become a cost-effective and powerful solution. Multi-spectral satellite images, especially in the thermal infrared, can be exploited to characterize the state of activity of a landfill.  Indeed, waste disposal sites, during the period of activity, can show differences in surface temperature (LST, Land Surface Temperature), state of vegetation (estimated through NDVI, Normalized Difference Vegetation Index) or soil moisture (estimated through NDWI, Normalized Difference Water Index) compared to neighboring areas. Landfills with organic waste typically show higher temperatures than surrounding areas due to exothermic decomposition activities. In fact, the biogas, in the absence or in case of inefficiency of the conveying plants, rises through the layers of organic matter and earth (landfill body) until it reaches the surface at a temperature of over 40 ° C. Moreover, in some cases, leachate contamination of the aquifers can be identified by analyzing the soil moisture, through the estimate of the NDWI, and the state of suffering of the vegetation surrounding the site, through the estimate of the NDVI. This latter can also be an indicator of soil contamination due to the presence of toxic and potentially dangerous waste when buried or present nearby. To take into account these facts, we combine the LST, NDVI and NDWI indices of the dump site and surrounding areas in order to characterize waste disposal sites. Preliminary results show how this approach can bring out the area and level of activity of known landfill sites. This could prove particularly useful for the definition of intervention priorities in landfill remediation works.
Early Observations from the Solar Orbiter SWA/Electron Analyser System
Authors: Owen Christopher ,   the International SWA, MAG and RPW teams.
Published: March 2021

Solar Orbiter carries a total of 10 instrument suites making up the payload for the mission.  One of these, the Solar Wind Analyser (SWA) instrument, is comprised of 3 sensor units which are together served by a central DPU unit.  Of particular focus in this presentation are the early measurements from one of these sensors, the Electron Analyser System (EAS).  EAS is a dual-head, top-hat electrostatic analyser system that is capable of making 3D measurements of solar wind electrons at energies below ~5 keV from a vantage point at the end of a 4-metre boom extending into the shadow of the spacecraft.  The sensor was accommodated in this location to both maximise the unobstructed field of view and to minimise the effect of spacecraft related disturbances on the low-energy (less than a few tens of eV) electrons expected the core population of the solar wind.

To date the SWA instrument sensors have operated sporadically during the mission cruise phase, which began in June 2020.  This is due to a number of operational issues faced by the SWA team, which mean we have not been able to take data in a continuous manner.  However, the data that has been taken shows the clear promise of the SWA measurements, in general, once these issues can be overcome.  For example, EAS is using a novel sample steering mechanism in burst mode which, with reference to a magnetic field vector shared onboard by the MAG instrument, allows the capture of the electron pitch angle distribution at unusually high time resolution.  We discuss these observations here, and illustrate the potential science returns from the burst mode.  We also present results from the new EAS observations in the vicinity of reconnecting current sheets in the solar wind, to more generally illustrate the capability of the sensor. 
Internal Model Variability of a Regional Coupled Wave-Atmosphere Model
Authors: Wiese Anne , Staneva Joanna , Ho-Hagemann Ha Thi Minh , Grayek Sebastian , Koch Wolfgang , Schrum Corinna
Published: March 2021

In this study (Wiese et al., 2020) ensemble simulations are performed, in order to assess the significance of the impacts of wave-atmosphere coupling on simulations of both waves and atmospheric models on a regional scale as well as to quantify the internal model variability of both the regional atmospheric model and wave-atmosphere coupled model system. Comparing the magnitude of the internal model variability of the atmospheric model with the internal model variability of the coupled model system shows that the internal model variability can be reduced in the coupled system. While this effect is more pronounced during extreme events, it is still present in a general assessment of the mean internal model variability during the whole study period. Moreover, the impacts of this wave-atmosphere coupling can be distinguished from the internal model variability of the atmospheric model since the effects of the wave-atmosphere interaction are larger than the internal model variability. This study shows that in operational and climate research systems the internal model variability of the atmospheric model is reducible when the ocean waves are coupled to the atmosphere. Clear influences of the wave-atmosphere interaction on both the atmosphere and wave models can be detected and differentiated from the internal model variability. Furthermore, the results of the coupled system have a better agreement with observational data than the results of the reference set up.

 

References:

Wiese A, Staneva J, Ho-Hagemann HTM, Grayek S, Koch W and Schrum C (2020) Internal Model Variability of Ensemble Simulations With a Regional Coupled Wave-Atmosphere Model GCOAST. Front. Mar. Sci. 7:596843. doi: 10.3389/fmars.2020.596843
Coupled water, vapor and heat flow in evaporation experiments under different boundary conditions
Authors: Iden Sascha , Blöcher Johanna , Diamantopoulos Efstathios , Durner Wolfgang
Published: March 2021

Evaporation from bare soil is an important hydrological process which influences the water and energy budget at all scales. Modelling soil evaporation is complex because it involves coupled liquid, vapor and heat flow. Although high-quality experimental data and use of different boundary conditions is mandatory to validate theory and to discriminate between models, many controlled experiments are still restricted to single boundary conditions. We conducted laboratory bare-soil evaporation experiments with a sand and a silt loam with three atmospheric forcings, (i) wind, (ii) wind and short-wave radiation, and (iii) wind and intermittent short-wave radiation. The soil columns were instrumented with temperature sensors, mini-tensiometers, and relative humidity probes, and evaporation rates were measured gravimetrically. The evaporation experiments were then simulated with a coupled water, vapour and heat flow model. We show that the coupled model reproduces measured evaporation rates and soil state variables (pressure head and temperature) of the evaporation experiments very well. In particular, the onset of stage-two evaporation, characterized by a decrease in evaporation rate and an increase in soil temperature is predicted correctly. Notably, a soil surface resistance, which has been suggested in the literature as a necessary component of evaporation models, led to a gross underestimation of the evaporation rate and a mismatch of the transition to stage-2 evaporation for both soils, for all boundary conditions, and for different soil surface resistance models. This illustrates that the use of resistance factors in coupled water, vapor and heat flow modelling studies is not justified.