bluuebunny/crossref_metadata_2025 huggingface dataset:
Impact of improved land model depth and hydrology on climate change projections
Authors: Steinert Norman , González-Rouco Fidel , Hagemann Stefan , de Vrese Philipp , García-Bustamante Elena , Jungclaus Johann , Lorenz Stephan , Melo-Aguilar Camilo , Navarro Jorge
Published: March 2020

The representation of the thermal and hydrological state in the land model component of Earth System Models is crucial to have a realistic simulation of subsurface processes and the coupling between the atmo-, lito- and biosphere. There is evidence suggesting an inaccurate simulation of subsurface thermodynamics in current-generation Earth System Models, which have Land Surface Models that are too shallow. In simulations with a bottom boundary too close to the surface, the energy propagation and spatio-temporal variability of subsurface temperatures are affected. This potentially restrains the simulation of land-air interactions and subsurface phenomena, e.g. energy/moisture balance and storage capacity, freeze/thaw cycles and permafrost evolution. We introduce modifications for a deeper soil into the JSBACH soil model component of the MPI-ESM for climate projections of the 21st century. Subsurface layers are added progressively to increase the bottom boundary depth from 10m to 1400m. This leads to near-surface cooling of the soil and encourages regional terrestrial energy uptake by one order of magnitude and more.
The depth-changes in the soil also have implications for the hydrological regime, in which the moisture between the surface and the bedrock is sensitive to variations in the thermal regime. Additionally, we compare two different global soil parameter datasets that have major implications for the vertical distribution and availability of soil moisture and its exchange with the land surface. The implementation of supercool water and water phase changes in the soil creates a coupling between the soil thermal and hydrological regimes. In both cases of bottom boundary and water depth changes, we explore the sensitivity of JSBACH from the perspective of changes in the soil thermodynamics, energy balance and storage, as well as the effect of including freezing and thawing processes and their influence on the simulation of permafrost areas in the Northern Hemisphere high latitudes. The latter is of particular interest due to their vulnerability to long-term climate change.
Global Morphology of Lower-band Chorus Wave Intensity Reconstructed Using multi-year POES Electron Measurements
Authors: Zhang Yang , Ni Binbin , Gu Xudong , Shprits Yuri , Fu Song , Cao Xing , Xiang Zheng
Published: March 2020

Magnetospheric chorus is known to play a significant role in the acceleration and loss of radiation belt electrons. Interactions of chorus waves with radiation belt particles are commonly evaluated using quasi-linear diffusion codes that rely on statistical models, which might not accurately provide the instantaneous global wave distribution from limited in-situ wave measurements. Thus, a novel technique capable of inferring wave amplitudes from POES particle measurements, with an extensive coverage of L-shell and magnetic local time, has been established to obtain event-specific, global dynamic evolutions of chorus waves. This study, using 5 years of POES electron data, further improves the technique, and enables us to subsequently infer the chorus wave amplitudes for all useful data points (removing the electrons which were in the drift loss cone) and to construct the global distribution of lower-band chorus wave intensity. The results obtained from the improved technique reproduce Van Allen Probes in-situ observations of chorus waves reasonably well and reconstruct the major features of the global distribution of chorus waves. We demonstrate that such a data-based, dynamic model can provide near-real-time estimates of chorus wave intensity on a global scale for any time period when POES data are available, which cannot be obtained from in-situ wave measurements by equatorial satellites alone, but is crucial for quantifying the  dynamics of the radiation belt electrons.
CONFIRM – Copernicus Data for Novel High-Resolution Wildfire Danger Services in Mountain Regions
Authors: Zotta Ruxandra-Maria , Atzberger Clement , Degenhart Jörg , Hollaus Markus , Immitzer Markus , Krajnz Haimo , Lick Heinz , Müller Mortimer M. , Oblasser Harald , Schaffhauser Andreas , Schlaffer Stefan , Vacik Harald , Dorigo Wouter
Published: March 2020

Wildfires are becoming an increasing threat to human health, infrastructure, forestry, agriculture and biodiversity. In Alpine regions, fires are often at the start of cascading risks including avalanches, mudslides or rock fall due to the loss of forest and vegetation layers. Additionally, wildfires are expected to occur more frequently in the future as a result of a warming climate, which is estimated to affect alpine regions in particular.

Fire danger forecasts, such as the commonly used Fire Weather indices, indicate the danger of forest fires based on numerical weather forecasts. Such indices are typically available at coarse spatial resolutions and, hence, have limited use in mountainous regions with their highly variable weather and other environmental conditions. Stakeholders, such as fire departments and forest managers, require more detailed forecasts in order to make robust decisions and efficiently plan their resources. The CONFIRM project, which started in December 2019 with funding from the Austrian Research Promotion Agency (FFG) under the Austrian Space Applications Programme (ASAP), addresses this gap by using high-resolution earth observation data provided by the European Copernicus programme to develop a pre-operational fire danger forecast system.

Data from both optical and microwave sensors aboard satellites are known to be sensitive to changes in soil and vegetation water content. Exploiting this sensitivity, satellite data with high temporal and spatial resolutions from the Copernicus Sentinel-1 and Sentinel-2 missions will be used to estimate fuel moisture state. The estimates will be integrated with airborne Laser-scanning (LiDAR) data, high-resolution weather forecasts, socioeconomic and topographic data to develop a novel, high-resolution integrated forest fire danger system (IFDS) for Austria. The project team will apply its expertise in forest management, remote sensing, fire science and machine learning to estimate fire danger using the Austrian fire database, an extensive record of historic fire events, as a training dataset. Key stakeholders from national weather services (ZAMG, DWD), fire brigades, state forest administrations and infrastructure providers (Austrian Railways ÖBB) are continuously involved in the project to develop the IFDS according to their requirements. They will evaluate the prototype of the system during the fire season of 2021.
Coupled benthic cycling of iron, phosphorus and sulfur in the Benguela upwelling system
Authors: Ungerhofer Kristin Anna , Reichart Gert-Jan , Kraal Peter
Published: March 2020

The Benguela upwelling system (BUS) offshore Namibia is among the most productive ocean regions worldwide and is a globally important reservoir of biodiversity and biomass. The forcing of cold, nutrient-rich deep waters up the coastal shelf leads to high rates of primary productivity in surface waters, intense carbon remineralization and consequently to (bottom water) oxygen depletion on the shelf that varies temporally and spatially with the intensity of the upwelling.
Recurring events of deoxygenation have a severe impact on marine ecosystems, for instance increased mortality and altered biogeochemical cycles of key elements such as carbon (C), iron (Fe), phosphorus (P) and sulfur (S). Therefore, it is crucial that we establish a clear mechanistic framework of the impact of oxygen depletion on (global) biogeochemical cycles, not only to allow for the reconstruction of climate-ocean feedbacks in upwelling regions in the past, but to enable predictions of future behavior.
During an expedition with RV Pelagia in February of 2019, we collected water column and sediment samples from the shelf and slope off Namibia (100 to 1517 m water depth, bottom water O2 between 0.5 and 175 µmol L-1) and measured nutrient fluxes in on-board sediment incubations to understand the early diagenetic behavior of those key elements and trace metals underlying the (periodically) oxygen-depleted waters of the BUS.
We analyzed dissolved concentrations as well as solid-phase speciation of key elements such as iron (Fe), manganese (Mn), phosphorus (P) and sulfur (S) to understand the chemical and physical processes controlling their distribution along the depth/redox-transect.
Our results show intense P cycling on the shelf, as evidenced by very high pore-water P concentrations, an enhanced efflux of PO4 to suboxic bottom waters and indications of phosphorite formation at depth in the sediment. N/P ratios well below Redfield indicate N depletion and (relative) P accumulation in the water column, a shift in nutrient stoichiometry that can impact the composition of microbial communities in such waters. Meanwhile, the slope sediments are overlain by oxic bottom waters, retain P more efficiently and exhibit N/P ratios close to Redfield stoichiometry.
The capacity of the sediment to buffer toxic sulfide and prevent its release to the water column was dependent on the abundance of sulfide oxidizers at the sediment surface. Furthermore, the variable accumulation of sulfide affected Fe speciation and sedimentary P retention.
Overall, we show an intimate coupling between sedimentary cycles of essential elements in the Benguela upwelling system, a stark contrast between shelf and slope environments that is further enhanced by local variation of oxygen depletion and a very strong role of microbes in driving the cycles.
Integrating Model Evaluation and Observations into a Production-Release Pipeline
Authors: Sommer Philipp S. , Petrik Ronny , Geyer Beate , Kleeberg Ulrike , Sauer Dietmar , Baldewein Linda , Luckey Robin , Möller Lars , Dibeh Housam , Kadow Christopher
Published: March 2020

The complexity of Earth System and Regional Climate Models represents a considerable challenge for developers. Tuning but also improving one aspect of a model can unexpectedly decrease the performance of others and introduces hidden errors. Reasons are in particular the multitude of output parameters and the shortage of reliable and complete observational datasets. One possibility to overcome these issues is a rigorous and continuous scientific evaluation of the model. This requires standardized model output and, most notably, standardized observational datasets. Additionally, in order to reduce the extra burden for the single scientist, this evaluation has to be as close as possible to the standard workflow of the researcher, and it needs to be flexible enough to adapt it to new scientific questions.

We present the Free Evaluation System Framework (Freva) implementation within the Helmholtz Coastal Data Center (HCDC) at the Institute of Coastal Research in the Helmholtz-Zentrum Geesthacht (HZG). Various plugins into the Freva software, namely the HZG-EvaSuite, use observational data to perform a standardized evaluation of the model simulation. We present a comprehensive data management infrastructure that copes with the heterogeneity of observations and simulations. This web framework comprises a FAIR and standardized database of both, large-scale and in-situ observations exported to a format suitable for data-model intercomparisons (particularly netCDF following the CF-conventions). Our pipeline links the raw data of the individual model simulations (i.e. the production of the results) to the finally published results (i.e. the released data). 

Another benefit of the Freva-based evaluation is the enhanced exchange between the different compartments of the institute, particularly between the model developers and the data collectors, as Freva contains built-in functionalities to share and discuss results with colleagues. We will furthermore use the tool to strengthen the active communication with the data and software managers of the institute to generate or adapt the evaluation plugins.
Mapping extreme hot temperatures in Europe and their evolutions: sensitivity to data choices
Authors: Parey Sylvie , Michelangeli Paul-Antoine
Published: March 2020

Electricity generation and demand is highly dependent on the weather conditions and especially temperature. Ongoing climate change has already modified the very hot extremes in Europe, and this is projected to continue in the future. The anticipation of the necessary adaptations in the electricity sector necessitates information on the possible extreme levels susceptible to occur in the next decades or further future periods. This study aims at comparing different ways of producing maps of extreme temperature levels for different future periods. Extreme temperatures are defined here as an example as 20-year Return Levels, that is temperatures reached or exceeded on average once in 20 years over the considered period. The computation of the Return Levels is based on the methodology described in Parey et al. 2019, which consists in applying the statistical extreme value theory to a standardized variable. It can be proven that the extremes of this variable can be considered as stationary. Then, the changes in mean and variance of the summer temperature projected by different climate models from the CMIP5 archive can be used to derive Return Levels for any selected future period.

Producing maps necessitates the use of a dataset with a large geographical coverage over Europe. Such datasets are typically gridded, either based on spatial interpolations of station records or on reanalysis products. However, both spatial interpolation and model assimilation tend to smooth the local highest values. Thus, in order to analyze the impact of such smoothing, the Return Levels computed in the same way from different datasets: the European Climate Assessment and dataset station data, the gridded EOBS database or the ERA5-Land database are computed and compared for different future periods.
Geodiversity through time: Changing badland landscapes due to anthropogenic and climatic forcing in the Northern Apennines (Italy)
Authors: Soldati Mauro , Parenti Carlotta , Coratza Paola
Published: March 2020

Soil erosion is one of the most significant land degradation processes worldwide, and has produced diverse geomorphological effects in different environments according to anthropogenetic and climatic forcing. In times of global change, it is of remarkable interest to trace these changes also in terms of landscape geodiversity through time.

This is the case of the badland landscapes that characterize relatively large sectors of the Northern Apennines (Italy) where clayey and marly terrains outcrop. Erosion rates have locally been very high, which caused widespread badland landform development, also accompanied by hazardous processes, such as the retrogression of badland scarps and rapid soil depletion.

This study aimed at understanding the evolution of badlands in selected areas of the Province of Modena (Emilia Apennines) through landform inventory, morphometric analysis and statistical assessment of influencing factors (e.g., slope aspect, climate conditions, land use), accompanied by detailed field surveys aiming at detailed mapping the areas presently affected by badlands. Several sets of aerial photos and satellite images were selected in order to perform multitemporal geomorphological analysis, define the evolution of badlands through time and assess multitemporal geodiversity by monitoring key environmental elements. The morphometric analysis of badlands was performed with the aim of understanding the causes of their development since the 1950s in relation to anthropogenic activities and meteoclimatic trends. The research showed a progressive reduction of active badlands and stabilization of gully features, leading to a substantial diversity of geomorphological landscapes of wide sectors of the investigated area.

This study underlines that the investigation of landscape changes can provide useful elements for the assessment of geodiversity not only in space but also through time. This approach made it possible to outline changes in geodiversity at different period of time and thus gain information on dynamic geodiversity, which is worth to be considered in land management.
Modeling terrestrial gamma-ray flashes observed by ASIM
Authors: Dwyer Joseph
Published: March 2020

The Atmosphere-Space Interactions Monitor (ASIM) on the International Space Station is providing important observations of terrestrial gamma-ray flashes (TGFs), including new measurements of optical emissions associated with TGFs and new measurements of multi-pulsed TGFs.  TGFs are thought to be produced by bremsstrahlung emissions from relativistic runaway electrons accelerated inside thunderstorms.  However, the exact mechanisms for generating the large number of runaway electrons required to account for the observed TGF luminosities remains an active area of debate.  Two mechanisms being considered are cold-runaway electron production by streamer heads or leader tips in the high-field regions near lightning, and the self-sustained production of runaway electrons by relativistic feedback involving backward propagating runaway positrons and backscattered x-rays.  Because both mechanisms may require the presence of lightning leaders inside thunderstorms -- for the cold-runaway mechanism to emit the runaway electrons and for the relativistic feedback mechanism to drive the electric field above the feedback threshold -- it has been challenging to test which TGF production mechanisms are occurring.  The new ASIM TGF observations should help constrain TGF models and possibly identify which mechanisms are primarily responsible for the runaway electron production.  In this talk, I will present new TGF modeling results and compare them with available ASIM observations.   
Intra-community air quality monitoring in various urban microenvironments in South Korea: based on observations from highly dense cost-effective sensor network
Authors: Park Yongmi , Park Ho-Sun , Choi Wonsik
Published: March 2020

 

As urbanization has spread, increased energy consumption, complicated built environments, and dense road networks cause spatiotemporal heterogeneity of air pollutant distributions even in an intra-community scale. High spatiotemporal heterogeneity of air pollutant distributions can affect pedestrian and/or traffic users’ exposure to air pollutants according to where and when they are, potentially forming air pollution hotspots. Thus, it is important to understand the characteristics of spatiotemporal distributions in air pollutants in various micro-built environments in populated urban areas. However, current air quality monitoring performed by the government cannot capture these highly heterogeneous distributions of air pollutants due to the limitations of financial and human resources. In this respect, cost-effective sensors have great potential to build highly spatially dense air quality monitoring networks to address the low spatial resolution issue of conventional air quality monitoring stations.

In this study, we built a highly dense air quality monitoring network consisting of 30 sets of sensor nodes in an 800 m ´ 800 m spatial domain to understand the characteristics of air pollutant distributions in various urban microenvironments. The domain includes urban street canyon with moderate traffic, a mixture of high and low buildings with high traffic, an open space with minimal traffic, and others. The sensor node consists of sensors (for CO, NO2, O3, PM2.5, and PM10, temperature, and humidity) and communication/data storage parts (wifi, interface for smartphone connection, and SD card). We also conducted inter-sensor comparison among sensor nodes and intercomparison tests between the sensor node and conventional reference instruments.

Intra-community air quality monitoring with a sensor network was conducted for a couple of weeks in two distinct weather conditions (humid and hot summer and dry and cold winter) in 2017 and 2018. During the observation periods, the concentration distribution analyses for air pollutants (except CO, PM) showed significant heterogeneity in their distributions in space. In addition, the correlation analysis with the meteorological factors showed that CO concentrations were affected by wind speed (winter, R2=0.22-0.25), but the other air pollutants were not directly correlated. We also examined the effects of land-use and building configuration on air pollution distributions. More details concerning these results are presented.

Keywords: Sensor network, low-cost sensor, spatial heterogeneity, micro-built environments
Evaluation of Sentinel-2 SMI and Sentinel-3 SLSTR data for estimating evapotranspiration in an irrigated olive orchard in Southern Iberian Peninsula.
Authors: Aguirre García Sergio David , Aranda-Barranco Sergio , Nieto Hector , Serrano-Ortiz Penélope , Sánchez-Cañete Enrique P. , Guerrero-Rascado Juan L.
Published: March 2020

Olive trees are one of the most important crops in the Mediterranean basin (10.5 Mha), accounting for 97.5% of the world’s olive cultivation area with relevant social and economic benefits and ecological consequences. Concretely, it takes up 2.7 Mha in Spain, of which more than 1.6 are in Andalusia. Olive cultivation demands climate-smart management to facilitate crop adaptation to climate scenario and predictable development. A more efficient water use and management optimization is an especially important issue and, therefore, quantifying and modeling evapotranspiration (ET) is essential.
However, given the lack of a satellite thermal mission with both high spatial resolution and frequent revisit time, we have evaluated in this work a data fusion methodology (Gao et al., 2012) that combines Sentinel-2 and Sentinel-3 images with the two-source energy balance model (Norman et al.,1995) proposed by Guzinski & Nieto et al. (2019). Estimates of actual ET were produced at 20 m resolution from January 2016 to December 2019 in an irrigated olive grove in Southern Iberian Peninsula. Preliminary results have been validated (every 5-10 days depending on Sentinel images availability and cloud cover) by ground-based in situ data using Eddy Covariance (EC) technique, showing mean absolute errors between estimated values and those obtained by EC: 156 Wm-2 (net radiation), 76 Wm-2 (soil heat flux), 36 Wm-2 (sensible heat flux), 210 Wm-2 (latent heat flux).

Gao, F., Kustas, W. P., & Anderson, M. C. (2012). A data mining approach for sharpening thermal satellite imagery over land. Remote Sensing, 4(11), 3287–3319. https://doi.org/10.3390/rs4113287

Guzinski, R., & Nieto, H. (2019). Evaluating the feasibility of using Sentinel-2 and Sentinel-3 satellites for high resolution evapotranspiration estimations. Remote Sensing of Environment, 221, 157–172. https://doi.org/10.1016/j.rse.2018.11.019

Norman, J. M., Kustas, W. P., & Humes, K. S. (1995). Source approach for estimating soil and vegetation energy fluxes in observations of directional radiometric surface temperature. Agricultural and Forest Meteorology, 77(3–4), 263–293. https://doi.org/10.1016/01681923(95)02265Y
Developing a data-driven ocean model
Authors: Furner Rachel , Haynes Peter , Jones Dan , Munday Dave , Paige Brooks , Shuckburgh Emily
Published: March 2020

The recent boom in machine learning and data science has led to a number of new opportunities in the environmental sciences. In particular, climate models represent the best tools we have to predict, understand and potentially mitigate climate change, however these process-based models are incredibly complex and require huge amounts of high-performance computing resources. Machine learning offers opportunities to greatly improve the computational efficiency of these models.

Here we discuss our recent efforts to reduce the computational cost associated with running a process-based model of the physical ocean by developing an analogous data-driven model. We train statistical and machine learning algorithms using the outputs from a highly idealised sector configuration of general circulation model (MITgcm). Our aim is to develop an algorithm which is able to predict the future state of the general circulation model to a similar level of accuracy in a more computationally efficient manner.

We first develop a linear regression model to investigate the sensitivity of data-driven approaches to various inputs, e.g. temperature on different spatial and temporal scales, and meta-variables such as location information. Following this, we develop a neural network model to replicate the general circulation model, as in the work of Dueben and Bauer 2018, and Scher 2018.

We present a discussion on the sensitivity of data-driven models and preliminary results from the neural network based model.

 

Dueben, P. D., & Bauer, P. (2018). Challenges and design choices for global weather and climate models based on machine learning. Geoscientific Model Development, 11(10), 3999-4009.

Scher, S. (2018). Toward Data‐Driven Weather and Climate Forecasting: Approximating a Simple General Circulation Model With Deep Learning. Geophysical Research Letters, 45(22), 12-616.
Lake coupled convection permitting simulations over the Lake Victoria basin with RegCM4.7: What is the benefit of permitting convection?
Authors: Müller Sebastian K. , Glazer Russell , Coppola Erika
Published: March 2020

The Lake Victoria Basin is home to largest freshwater lake (Lake Victoria; LV) in Africa and second largest in the world. Each year on the order of 1,000 fisherman are lost on LV during intense night-time thunderstorms. Despite this, until recently, understanding of the processes contributing to heavy rainfall events was very limited. In this study we present a 10-year (2006-2015) convection permitting (3km grid-spacing) simulation (CPS) of the Lake Victoria Basin using the RegCM version 4.7.0. A lake model is utilized in order to couple the lake regions with RegCM, which has been shown to be of great importance for simulating a realistic lake surface temperature (LST) over LV. The simulated LST from the CPS shows a general warm bias when comparing to ARC Lake observations, however the annual cycle of LST is well represented by the CPS. In the coarser simulation the LST has a large cool bias because of the absence of any lake coupling and this contributes to a large dry bias over LV. The CPS shows a much-improved seasonal rainfall pattern over LV, however there is a general overestimation of the rainfall by the CPS during the peaks in the rainy seasons (March-May; October-December). The CPS shows an improved ability to produce extreme rainfall (>100mm/day) over the western portion of the lake which is consistently found in satellite and in-situ observations. The distribution of rainrates over LV in the CPS is much closer to satellite derived rainfall observations compared to the coarse simulation, demonstrating the improvements made to the simulation of cloud microphysics processes when moving to convection permitting grid-spacing. Mesoscale circulations associated with the diurnal cycle over LV are an important driver of intense night-time thunderstorms. An analysis of the diurnal rainfall cycle over LV shows that the CPS well represents the timing of nocturnal rainfall over the lake which is associated with a strong landbreeze, however the daytime peak in rainfall over the land surrounding the lake is too early. Extreme nocturnal rainfall events over the lake in satellite observations show a clear migration from the previous daytime peak in rainfall westward onto the lake during the night. This suggests a connection between extreme rainfall events at night and the preceding daytime peak in rainfall over land. In the CPS these daytime peaks over the land occur too early and the lakebreeze circulation appears weak compared to the nocturnal landbreeze which is very prominent. The coarse resolution lake coupled simulation shows a surprisingly robust ability to simulate seasonal and annual rainfall associated with mesoscale lake circulations compared to the CPS. The improvement over the coarser simulation seems to be in the CPS’s ability to capture convection scale interactions which may be important for extreme rainfall events.
Global simulations of the atmosphere at 1.45 km grid-spacing with the Integrated Forecasting System
Authors: Düben Peter , Wedi Nils , Saarinen Sami , Zeman Christian
Published: March 2020

Global simulations with 1.45 km grid-spacing are presented that were performed with the Integrated Forecasting System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF). Simulations are uncoupled (without ocean, sea-ice or wave model), using 62 or 137 vertical levels and the full complexity of weather forecast simulations including recent date initial conditions, real-world topography, and state-of-the-art physical parametrizations and diabatic forcing including shallow convection, turbulent diffusion, radiation and five categories for the water substance (vapour, liquid, ice, rain, snow). Simulations are evaluated with regard to computational efficiency and model fidelity. Scaling results are presented that were performed on the fastest supercomputer in Europe - Piz Daint (Top 500, Nov 2018). Important choices for the model configuration at this unprecedented resolution for the IFS are discussed such as the use of hydrostatic and non-hydrostatic equations or the time resolution of physical phenomena which is defined by the length of the time step. 

Our simulations indicate that the IFS model — based on spectral transforms with a semi-implicit, semi-Lagrangian time-stepping scheme in contrast to more local discretization techniques — can provide a meaningful baseline reference for O(1) km global simulations.
Which Processes Sustain Biota in Open-Ocean Deep Chlorophyll Maxima?
Authors: Rigby Shaun , Williams Richard , Achterberg Eric , Tagliabue Alessandro
Published: March 2020

Deep chlorophyll maxima (DCM) are productive layers widespread throughout the global ocean. In the DCM, marine phytoplankton are adapted to low light conditions at the cost of elevated cellular iron (Fe) requirements, leading to Fe deficient growth. To sustain productivity, nutrient demands must be met by sources such as the dissolution of sinking lithogenic particles, recycling of biogenic particles and physical transport from below. The GEOTRACES programme has expanded the global ocean datasets for a suite of trace metals and also noble gases. Here, we exploit helium measurements to derive a vertical flux estimate of nitrate (NO3), phosphate (PO4), silica (Si) and Fe into the DCM in the subtropical North Atlantic and equatorial Pacific. We apply the Si* relation to show differences in nutrient deficiency between waters in the DCM and the upward flux into the DCM. The offset in Si* between the DCM and upward flux may be enhanced or reduced by the dissolution of sinking particles or internal recycling. We show that the upward Fe flux to the DCM is of similar magnitude to Fe supplied through regeneration. In contrast, we show that the upward Fe flux outweighs estimates of Fe supplied to the DCM via recycling or lithogenic particles in the subtropical North Atlantic. The muted role of lithogenic particles in our estimates leads to the question: what assumptions must be made about aeolian deposition to increase the relevance of lithogenic particles at the DCM?
A Eulerian Explosive Cyclogenesis climatology from the ERA5 reanalysis, 1979-2018
Authors: Cropper Thomas , Allen Stephanie
Published: March 2020

Using the criterion of one Bergeron (24 hPa change over 24 h at 60°), we present the creation of a Eulerian explosive cyclogenesis climatology using hourly-temporal resolution data from the European Centre for Medium Range Weather Forecasting’s ERA5 reanalysis (1979-2018). This approach differs to the typically used Lagrangian methodologies adopted by many studies. The climatology created by this approach results in similar patterns to previous studies.

Assessments on the dataset are undertaken to analyse the influence of seasonality, teleconnections, climate change and individual events (the method picks up tropical cyclones as well as mid-latitude storms). The location experiencing the most consistent explosive cyclongenesis conditions (15% of the time during the Northern Hemisphere winter) is to the east of the Avalon Peninsula, Newfoundland. The preferred location of explosive cyclogenesis is shown to change in relation to patterns such as the El Niño Southern Oscillation and North Atlantic Oscillation. Potential applications of the dataset are suggested.

                                                
Repeated ground-penetrating radar measurements to detect seasonal and annual variations of an englacial conduit network
Authors: Church Gregory , Bauder Andreas , Grab Melchior , Schmelzbach Cédric , Maurer Hansruedi
Published: March 2020

Surface meltwater is routed through the glacier’s interior by englacial drainage systems into the subglacial drainage system. The subglacial drainage system plays an important control on the glacier sliding velocity. Therefore, studying the evolution of englacial drainage systems throughout the melt season is key to understanding how these englacial drainage systems develop, and how they subsequently feed the subglacial drainage system.

We have conducted 10 repeated ground-penetrating radar using a Sensor & Software pulseEKKO Pro GPR system with 25 MHz antenna between 2012 and 2019 over an englacial conduit network, 90 m below the glacier’s surface, on the Rhonegletscher, Switzerland. These repeated measurements allowed insights into both annual and seasonal changes. We were also able to have direct observations into the englacial conduit network from six boreholes that were drilled in August 2018 using a GeoVISIONTM Dual-Scan borehole camera.

The annual results provided evidence that the englacial drainage network developed between 2012 and 2017. The seasonal evolution of the englacial conduit was studied by inverting the GPR data using an impedance inversion. The impedance inversion delivered reflection coefficients, which provides information on the englacial material properties associated with the englacial conduits. The inversion results provide evidence that during the winter season the englacial network is inactive. During June the englacial network becomes active by transporting surface melt water, and it becomes fully active later in the melt season (August). The reflectivity in summer (June-October) is -0.6, indicating the presence of water within the network. In winter (November-May) the reflectivity is around 0 indicating that the system is neither air or water filled and therefore the system physically closes.

The data processing workflow provided a top and bottom reflection coefficient of the conduit. The travel time between the reflection coefficients can be converted to a thickness when using EM wave velocity of water (from 2018 borehole observations). During the summer months the englacial network is around a quarter wavelength thick (0.3 m), which is approximately the limit of the vertical resolution.
Cocccolithophore contribution to carbonate export to the deep sea in the Australian-New Zealand sector of the subantarctic Southern Ocean
Authors: Rigual-Hernandez Andres , Trull Thomas W. , Nodder Scott D. , Flores José A. , Bostock Helen , Abrantes Fátima , Eriksen Ruth S. , Sierro Francisco J. , Davies Diana M. , Ballegeer Anne-Marie , Fuertes Miguel A. , González Lanchas Alba , Northcote Lisa C.
Published: March 2020

Coccolithophores are ubiquitous marine unicellular algae belonging to the Class Prymnesiophyceae, division Haptophyta. They are distinct from other phytoplankton groups in their capacity to produce minute calcite platelets (termed coccoliths) with which they cover their cells. During the Cretaceous and throughout the Cenozoic era, pelagic sedimentation of carbonate was largely controlled by coccolithophores as evidenced by their major contribution to deep-sea oozes and chalks. In the modern Southern Ocean, coccolithophores represent an important component of the phytoplankton communities and carbon cycle. However, their contribution to total Particulate Inorganic Carbon (PIC) for large regions of the Southern Ocean remains undocumented.

Here we report the Particulate Inorganic Carbon (PIC) and coccolithophore fluxes collected over a year by sediment traps placed at two sites of the subantarctic Southern Ocean. We present coccolith mass estimates of the most abundant coccolithophore species and quantitatively partition annual PIC fluxes amongst heterotrophic calcifying plankton and coccolithophores. Our results reveal that coccolithophores account for approximately half of the annual PIC export in the subantarctic Southern Ocean. Moreover, in contrast to satellite estimations, that mainly reflect coccospheres and detached coccoliths of Emiliania huxleyi, less abundant but larger species make the largest contribution to CaCO3. Lastly, comparison of our data with previous studies suggest that projected environmental change in the Southern Ocean may result in a decline of coccolithophore PIC production and export.

 
The Dust Environment in the Inner Heliosphere
Authors: Howard Russell , Stenborg Guillermo , Malaspina David , Szalay Jamey , Pokorny Petr
Published: March 2020

The Parker Solar Probe (PSP) mission has completed 4 encounters through the solar corona significantly closer to the Sun than previous measurements. While PSP does not have a dedicated dust detector, measurements by the various instruments can provide insights into the dust environment in the inner heliosphere.  Throughout the PSP orbit, interplanetary dust is impacting the spacecraft.  Three-dimensional reconstructions of FIELDS observations show that the rate and direction of the dust impacts varies throughout the PSP orbit.  During the encounter WISPR also finds the rate of impacts changes through the encounter period, but also a decrease in the intensity of the light scattered by the dust particles.  The smooth decrease in the WISPR intensity beginning at about 0.1 AU is consistent with the production of Beta-meteroids seen by FIELDS. In this presentation, we will discuss the observations from the FIELDS and WISPR instruments and discuss initial models of the dust environment.  The authors acknowledge support from the NASA Parker Solar Probe program.
Impact of tropical cyclone storm surges on groundwater salinity in southwest regions of Bangladesh
Authors: Tsai Chi San , Butler Adrian P , Hoque Mo A
Published: March 2020

Excess salinity in drinking water is a serious issue along the southwest coastal of Bangladesh, mainly in reclaimed lands where around 14 million people live and sustain in low-lying deltas. The low-lying deltas are particularly vulnerable to episodic tropical cyclones. The tropical cyclones induced storm surges cause severe floods and extensive damage and result in the salinity in surface water and subsurface water, which have serious impacts on human health such as hypertension and food security due to loss in agricultural yield. In 2011, two years after Cyclone Aila hit the southwest regions of Bangladesh (in 2009), many parts of these regions were still underwater which caused disruption of water supply and contamination of drinking water. The lands were unproductive due to excessive salt in soil and water. A fully coupled surface-subsurface model of a coastal low-lying land is used to investigate the role of tropical cyclonic storm on long-term salinity of water resources in Bangladesh. The hydrogeological parameters of the model were calibrated using data from fieldwork at the site of a pond in Dacope, Khulna. We used the observed water level data from a station at Mongla during Cyclone Aila hit southwest regions of Bangladesh (26 May 2009).The results show how groundwater salinity changes in response to storm surges and monsoon in the coastal low-lying areas. Near-surface groundwater salinity (below 1m-2.3m) takes 4-6 years to return the salinities to pre-surge levels by monsoonal rainfall.
Evidence of increased density of LLVPs from vote map constrained density inversion
Authors: Szwillus Wolfgang , Ebbing Joerg , Steinberger Bernhard
Published: March 2020

The Large Low Velocity Provinces (LLVP) are two antipodal regions of reduced seismic velocity that extend about 800 km into the mantle from the core-mantle boundary. The LLVPs might affect the generation of plumes and organize large-scale plate motions.

However – except for the reduced velocity – almost all properties of the LLVPs are the subject of vigorous debate. The LLVPs could simply be hot upwellings, or they could be chemically different from normal mantle. They could be a transient feature, exist since the Early Earth or be the result of continuous accumulation as a result of plate tectonics. To some extent, determining the density of the LLVPs could help to distinguish between these scenarios. However, most seismic methods are only weakly sensitive to density and so far both negative and positive density anomalies have been proposed based on seismology. A more direct means of assessing the density structure comes from inverting the gravity field.

While density inversions are inherently non-unique, this can be somewhat alleviated by constraining the geometry of potential sources of the gravity anomalies. In this contribution, we use vote maps to constrain the geometry. A vote map is based on a collection of seismic tomographies and highlights areas of agreement between the seismic tomographies.

We find that the LLVPs possess a slight positive density anomaly between 0.1 and 0.6 %. The variation results from how the lithosphere is treated, since we use both an isostatic model and seismically determined Moho depths, with the isostatic model resulting in smaller LLVP densities. The combination of increased density and reduced velocity can only be explained if the LLVPs are somewhat chemically different from ‘normal’ pyrolitic mantle. Using petrophysical data bases we estimate that an enrichment of 1-1.5% iron oxide content together with a temperature increase of 260 – 380 K with respect to an adiabatic temperature curve can explain the density increase and velocity decrease. Alternatively, the LLVPs would have to contain 40-60 % Mid-Oceanic Ridge Basalt and be 870 – 960 K hotter in order to explain our findings.
Potential contribution from bioenergy with CCS to SDG13: an Earth system modelling perspective
Authors: Muri Helene , Næss Jan Sandstad , Iordan Cristina Maria
Published: March 2020

Renewable energy will play a key role in tranformation of the energy sector to reduce CO2 emissions. Integrated Assessment Modelling scenarios reaching the temperature targets of the Paris Agreement rely on large scale deployment of Bioenergy with Carbon Capture and Storage (BECCS). BECCS are a key contributor to reducing emissions and acheiving net negative emissions in such scenarios. The potentials of large scale BECCS deployment in reaching the 1.5°C target is evaluated using Earth system model simulations in the work presented here. Fully coupled carbon cycle and interactive biogeochemistry is used to assess different rates of BECCS deployment, alongside assuming strong mitigation. BECCS at large scale influence not only the global carbon cycle, but also the feedbacks between the atmosphere and land surface. Changing the land cover to biocrops affects the terrestrial store of carbon, and also the physical properties of the land surface, i.e. biogeophysical forcing, which leads to important feedbacks in the climate system. Renewable energy from BECCS may have implications on several of the SDGs, in particular #13 Climate, #7 Energy, #15 Life on land, as well as #2 Hunger. It is found that it remains a challenge to achieve the 1.5°C target, relying strongly on bioenergy with CCS, and the mitigation potential depends on geografical location, and availability of suitable land areas.
The future strong motion national seismic networks in Central America designed for earthquake early warning.
Authors: Massin Frederick , Clinton John , Racine Roman , Bose Maren , Rossi Yara , Marroquin Griselda , Strauch Wilfried , Arroyo Mario , Linkimer Lepolt , Chavez Esteban , Protti Marino , Yani Robin
Published: March 2020

The national seismic networks in Central America have been developing network-based early warning since 2016 for Nicaragua, 2018 for El Salvador and 2019 for Costa Rica. This effort is part of a project with the Swiss Seismological Service (ETH Zurich) including funds for accelerograph deployment. At each network, delay for first earthquake parameter estimations have been significantly reduced by optimizing data acquisition, metadata quality, and configuration of the EEW algorithms implemented in SeisComP3, i.e. Virtual Seismologist and the Finite fault rupture Detector. Issues remain with significant numbers of deployed instrumentation that for a variety of reasons, do not optimally contribute to the EEW systems. Building on our experience so far, we design national network upgrades that will optimize the earthquake early warning performance in the Central America region, mitigating the current issues with velocimeter clipping during large events, datalogger delays, and incomplete network coverage. The new instruments have been selected after testing all available EEW-capable accelerographs natively compatible with SeisComP3 including class A force balance accelerometers as well as MEMs. To justify our instrument selection, we summarize the performance of these different instruments. We model and discuss reference maps for performance expectations, and present planned instrument vaults. Our primary focus is on minimizing first alert times but we also wish to accentuate the broad value of the network upgrade for seismological monitoring showing changes in the magnitude of completeness in the region. We demonstrate the value of the network upgrade for earthquake early warning with real-time processing simulation using synthetic data for the maximum magnitude earthquake expected for the Central America subduction zone.
A novel approach for fast prediction of hydraulic vulnerability in conifers
Authors: Rosner Sabine , Voggeneder Klara , Nöbauer Sebastian
Published: March 2020

Global warming calls for fast and easily applicable methods to measure hydraulic vulnerability in conifers since they are one of the most sensitive plant groups regarding drought stress. Classical methods to determine P50, i.e. the water potential resulting in 50% conductivity loss, are labor intensive and prone to errors. In this study, the empirical relationship between percent loss of hydraulic conductivity and relative water loss in sapwood of six conifer species was used to establish a novel proxy for P50. Our new proxy P25W, defined as 25% of relative water loss induced by air injection, is easy and fast to measure and correlates strongly with P50 (r = 0.95) as well as with functional wood traits such as the tracheid wall/lumen ratio (r = -0.87). The method is regarded as a strong new phenotyping tool for screening trees for drought sensitivity.