bluuebunny/crossref_metadata_2025 huggingface dataset:
The Great Lakes of Turkana – a Novel Perspective on the African Humid Period
Authors: Fischer Markus Lothar , Junginger Annett
Published: March 2022

The Lake Turkana region in northern Kenya and southern Ethiopia is famous for its fossil richness including key sites for human evolution studies. Modern Lake Turkana is the last of numerous mega-paleo-lakes, that has persisted to dry up completely at the end of the last African Humid Period (AHP, 15 – 5 ka). The adjacent paleo-lakes Suguta (2,000 km²) and Chew Bahir (2,500 km²), which are desiccated today, have formed together with paleo-lake Turkana (20,000 km²) a N-S oriented mega-lake during the AHP that has being separated only by small morphological Barriers. While Turkana, Suguta and Chew Bahir have been part of intensive research during the past decades, paleo-lake Chalbi with 10,000 km² in size just 10 km east of Lake Turkana was out of sight for most archaeologists and geoscientist. Here we present the first attempts for enhancing our understanding of the paleoenvironmental consequences of paleo-lake Chalbi close to one of the key regions in human evolution.
Improving ECOSTRESS-based Evapotranspiration Estimates Using Harmonized Landsat Sentinel-2 Imagery
Authors: Rashid Taufiq , Tian Di
Published: March 2022

Evapotranspiration (ET) is a major component of the hydrologic cycle and plays a fundamental role in water and land management. However, previous studies have shown that estimating ET is quite challenging, particularly at fine temporal and spatial scales. Dense time series of harmonized Landsat 8 and Sentinel-2 imagery (HLS) combined with ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) data provide a unique opportunity to enhance monitoring, mapping, and characterizing ET at unprecedented spatial and temporal resolutions. In this study, we develop and evaluate an improved ET estimation method based on Priestley-Taylor Jet Propulsion Laboratory algorithm (PT-JPL) with HLS optical reflectance imagery and ECOSTRESS land surface temperature (LST) and surface emissivity, in addition to MODIS surface albedo and ERA5-Land climate reanalysis data. The new approach creates denser times series of ET from HLS imagery, which can also be used to map ET at 30 m spatial resolution. The new ET estimates are evaluated against ground-based observations from the AmeriFlux network and compared with the performance of the original ECOSTRESS PT-JPL ET estimates across different ecosystems and landcover settings over the continental United States. We present results for evaluating ET estimates, the remote sensing and climate reanalysis inputs, and illustrating the sensitivity and uncertainty of the improved ET method and its performance related to land cover and terrestrial ecosystem properties.
Reducing aviation emissions: investigating time minimal and fixed time trajectories for transatlantic flights.
Authors: Wells Cathie , Williams Paul , Nichols Nancy , Kalise Dante , Poll Ian
Published: March 2022

With full satellite coverage of transatlantic flight routes now a reality, situational awareness is no longer a limiting factor in planning trajectories. This extra freedom allows us to consider moving from the current Organised Track System to Trajectory Based Operations, in order to limit fuel use and thus reduce emissions.

In all parts of this research, flights between New York and London, from 1st December, 2019 to 29thFebruary, 2020 are considered. Average daily winds and temperatures are taken from a global atmospheric re-analysis dataset.

 

We first use optimal control theory to find the minimum time trajectories through daily wind fields. The aircraft is assumed to fly at Flight Level 340 with airspeeds ranging from 200 to 270 m s-1. Since fuel burn and greenhouse gas emissions are directly proportional to the product of time of flight and airspeed, this quantity, air distance, is used as a measure of route fuel efficiency. Minimum time air distances are compared with actual Air Traffic Management tracks, giving potential savings ranging from 0.7 to 16.4%. 

 

However, minimum time routes are not always practical. Airlines and airports require trajectories that will minimize fuel burn and thus carbon dioxide emissions, whilst adhering to a rigid timetable. To address this we again apply optimal control theory, but this time to find minimum fuel routes through the same wind fields. 

The control variable is expressed as a set of position-dependent aircraft headings, with the optimal control problem solved through a reduced gradient approach.  A second formulation is considered, wherein both heading angle and airspeed are controlled.  By comparing fuel burn for each of these scenarios, the importance of airspeed in the control formulation is established. 

 

Thus large reductions in fuel consumption and emissions are possible immediately, by planning time or fuel minimal trajectories, without waiting decades for incremental improvements in fuel-efficiency through technological advances.
Autonomous lineament detection in Galileo images of Europa
Authors: Haslebacher Caroline , Thomas Nicolas
Published: March 2022

Lineaments are prominent features on the surface of Jupiter's moon Europa. Analysing these linear features thoroughly leads to insights on their formation mechanisms and the interactions between the subsurface ocean and the surface. The orientation and position of lineaments is also important for determining the stress field on Europa. The Europa Clipper mission is planned to launch in 2024 and will fly by Europa more than 40 times. In the light of this, an autonomous lineament detection and segmentation tool would prove useful for processing the vast amount of expected images efficiently and would help to identify processes affecting the ice sheet. 

We have trained a convolutional neural network to detect, classify and segment lineaments in images of Europa returned by the Galileo mission. The Galileo images that make up the training set are segmented manually, following a dedicated guideline. For better performance, we make use of synthetically generated data to pre-train the network. The current status of the work will be described.
Determining the dependence of the power supply to the ocean on the length and time scales of the dynamics between the meso-scale and the synoptic-scale, from satellite data
Authors: Wirth Achim
Published: March 2022

  

The input of mechanical power to the ocean due to the surface wind-stress, in regions which correspond to different regimes of ocean dynamics, is considered using data from satellites observations. Its dependence on the coarse-graining range of the atmospheric and oceanic velocity in space from 0.5° to 10° and time from 6h to 40 days is determined.

 

In the area of the Gulf Stream and the Kuroshio extensions the dependence of the power-input on space-time coarse-graining varies over tenfold for the coarse-graining considered. It decreases over twofold for the Gulf Stream extension and threefold for the Kuroshio extension, when the coarse-graining length-scale passes from a few degrees to 0.5° at a temporal coarse-graining scale of a few days. It increases over threefold in the Gulf Stream and the Kuroshio extensions when the coarse-graining passes from several days to 6h at a spatial coarse-graining of a few degrees. The power input is found to increase monotonically with shorter coarse-graining in time. Its variation with coarse-graining in space has no definite sign. Results show that including the dynamics at scales below a few degrees reduces considerably the power input by air-sea interaction in regions ofstrongly non-linear ocean currents. When the ocean velocities are not considered in the shear calculation the power-input is considerably (up to threefold) increased. The dependence of the power input on coarse-graining in space and time is close to being multiplicatively separable in all regions and for most of the coarse-graining domain considered.
Latent Linear Adjustment Autoencoder: a novel method for estimating dynamic precipitation at high resolution
Authors: Heinze-Deml Christina , Sippel Sebastian , Pendergrass Angeline G. , Lehner Flavio , Meinshausen Nicolai
Published: March 2022

A key challenge in climate science is to quantify the forced response in impact-relevant variables such as precipitation against the background of internal variability, both in models and observations. Dynamical adjustment techniques aim to remove unforced variability from a target variable by identifying patterns associated with circulation, thus effectively acting as a filter for dynamically induced variability. The forced contributions are interpreted as the variation that is unexplained by circulation. However, dynamical adjustment of precipitation at local scales remains challenging because of large natural variability and the complex, nonlinear relationship between precipitation and circulation particularly in heterogeneous terrain. 

In this talk, I will present the Latent Linear Adjustment Autoencoder (LLAAE), a novel statistical model that builds on variational autoencoders. The Latent Linear Adjustment Autoencoder enables estimation of the contribution of a coarse-scale atmospheric circulation proxy to daily precipitation at high resolution and in a spatially coherent manner. To predict circulation-induced precipitation, the LLAAE combines a linear component, which models the relationship between circulation and the latent space of an autoencoder, with the autoencoder's nonlinear decoder. The combination is achieved by imposing an additional penalty in the cost function that encourages linearity between the circulation field and the autoencoder's latent space, hence leveraging robustness advantages of linear models as well as the flexibility of deep neural networks. 

We show that our model predicts realistic daily winter precipitation fields at high resolution based on a 50-member ensemble of the Canadian Regional Climate Model at 12 km resolution over Europe, capturing, for instance, key orographic features and geographical gradients. Using the Latent Linear Adjustment Autoencoder to remove the dynamic component of precipitation variability, forced thermodynamic components are expected to remain in the residual, which enables the uncovering of forced precipitation patterns of change from just a few ensemble members. We extend this to quantify the forced pattern of change conditional on specific circulation regimes. 

Future applications could include, for instance, weather generators emulating climate model simulations of regional precipitation, detection and attribution at subcontinental scales, or statistical downscaling and transfer learning between models and observations to exploit the typically much larger sample size in models compared to observations.
Exploration of the theoretical, financial, technical and sustainable hydropower generation potential in the Upper Indus basin
Authors: Dhaubanjar Sanita , Lutz Arthur , Gernaat David , Nepal Santosh , Pradhananga Saurav , Khanal Sonu , Bhakta Shrestha Arun , Immerzeel Walter
Published: March 2022

Hydropower investment decisions in the Upper Indus take a short-sighted approach based on energy generation potential at individual hydropower sites considering historical hydro-climatology. But hydropower will increasingly be affected in the future by changing climate and demands for water, energy and food – all heavily dependent on water resources availability. The seasonality and variability in runoff are changing. Anthropogenic water consumption may see a two to three fold increase by the end of the century with socio-economic development. Climate change and interlinkages with the water-energy-food nexus are emerging as primary stressors to land and water resources availability for hydropower in the Indus. Hence, we assess the extent of the challenges posed by climate change versus the nexus linkages on hydropower potential in the Upper Indus. Our sustainable hydropower exploration framework takes a systems approach to quantify theoretical, technical, economic and sustainable hydropower potential by successively considering the impact of natural, technical, financial, anthropogenic, environmental, and geo-hazard constrains on hydropower potential at both the individual site and the basin scales. The framework explicitly considers the water available for hydropower versus other nexus usages. We combine the framework with downscaled CMIP6 general circulation models and water consumption projections to compare current and future hydropower potential. Thus, we present hydropower development portfolios that are more robust under climate change and changes across the water-energy-food nexus. Future changes in climate and water demands will increase the need for a multi-sectoral approach in the identification of potential sites to achieve sustainable hydropower development. We present a basin-scale analysis of hydropower potential in the Upper Indus, now and in the future, considering growing demands for water, food and energy to fulfill the Sustainable Development Goals.
Underwater altimetry – Extracting ICESat-2 bathymetry in shallow water areas
Authors: Ranndal Heidi , S. Christiansen Philip , B. Andersen Ole
Published: March 2022

With the Advanced Topographic Laser Altimeter System (ATLAS), ICESat-2 is able to map underwater topography, i.e., bathymetry. The ICESat-2 altimeter uses a green laser with a wavelength of 532 nm, which can penetrate the water surface and provide information about the distance to the ocean bottom if the conditions allow it, i.e., preferably over clear and calm waters and for depths up to 40 m.

Precise bathymetry estimates for shallow water areas are important for industry and modelling of phenomena such as tides, currents and water temperature. Obtaining direct measurements of bathymetry using airborne lidar or echo soundings from ship can be a tedious and expensive task. The data from the Advanced Topographic Laser Altimeter System (ATLAS) carried by ICESat-2 offers a fast an inexpensive way to obtain accurate coastal bathymetry, which can be used alone or together with global satellite imagery, such as from Sentinel-2, to create bathymetric maps in areas where there are no available in situ data from ships or airborne lidars.

Here we present the validation of a simple empirical method (Ranndal, 2021) to obtain bathymetry profiles using the geolocated photon data (ATL03) from ICESat-2. The bathymetry profiles obtained with the statistical method are compared to other bathymetry data sets in the Great Barrier Reef, Australia, and in the area around Sisimiut, Greenland, such as echo soundings and satellite derived bathymetry from WorldView2 imagery. Comparisons with machine learning derived bathymetry profiles reveal that the statistical model provides similar results.

Some of the challenges concerning the extraction of bathymetry profiles from ICESat-2 photon data, such as apparent multiple sea surfaces and the difficulty of distinguishing between bathymetry and sea surface returns in very shallow waters are also discussed. 

Finally, the potential of using a similar method for extracting inland water bathymetry is addressed.
Dry air intrusions link Rossby wave breaking to large-scale dust storms in North Africa
Authors: Fluck Elody , Raveh-Rubin Shira
Published: March 2022

Large-scale dust storms over North Africa transport mineral dust over thousands of kilometers equatorward and into the Mediterranean, thereby affecting human health and infrastructures. Dry Intrusions (DIs) are synoptic-scale descending airstreams from the midlatitude upper troposphere towards the surface. DIs occur behind midlatitude troughs and cyclones, and were shown to induce potential instability and enhance surface wind in the planetary boundary layer. Thus, DIs can potentially play a major role in the emission and transport of dust over North Africa.

Here, we aim to understand whether DIs are a common element that can link Rossby wave breaking, a known precursor of large emission events, to the high surface dust concentrations in Lagrangian sense, and to further understand the role of DIs in dust emission. By focusing on selected events and compiling a climatology for the years 2003-2018 we specifically aim to quantify the link between the co-occurrence of DIs and dust events, and identify common precursors. Using the Copernicus Atmosphere Monitoring Service (CAMS) reanalyzed dust optical depth (DOD), vertical dust mixing ratios, atmospheric fields from ERA-Interim reanalysis and a Lagrangian-based detection of DIs, we identify DI-dust events by applying a systematic matching algorithm.

We find that DI-dust events typically peak in winter to spring, and are associated with the maximal dust concentrations in the region. Multiple Rossby wave breakings in the eastern North Atlantic is a common precursor to DI-dust events. The DI airstream is found to connect the upper-tropospheric ridge/trough to the highest surface dust concentrations. Typically, a Mediterranean cyclone further steers the dust over North Africa and northward into the Mediterranean and Europe/Middle East. Vertical profiles of dust mixing ratios show that dust can reach the upper troposphere in the vicinity of the cyclone, attesting to long-range dust transport into the Mediterranean Sea and Europe.

Overall, our detailed case studies and climatological results emphasize the central role of DIs in producing large-scale dust storms. The distinct regional and seasonal frequency of DI-dust occurrence and their coherent precursor signals over the North Atlantic provide valuable information for understanding the predictability of such hazardous events.

 

 
Risk analysis for reservoir flood control operation considering two-dimensional uncertainties based on Bayesian network
Authors: Lu Qingwen
Published: March 2022

Floodwater conservation in reservoir flood control capacity will lead to additional flood control risk for reservoir operation during flood seasons. Coupling the meteorological and hydrological uncertainties, the probability density function of reservoir initial flood regulation water level is derived to quantify the uncertainty in floodwater conservation through an analytical method. In reservoir flood control operation, the uncertainty of initial water level being above the designed flood limited water level and the uncertainty of inflow caused by flood forecast error are two main risk factors. This study developed a dynamic and intelligent risk prediction and diagnosis model for reservoir flood regulation under two-dimensional uncertainties based on Bayesian network. Three modules are included: Bayesian network structure learning, parameter learning, and probability inference. The nodes of Bayesian network are determined and the network structure is established with expert knowledge; the parameter learning is conducted with the training samples obtained from Monte Carlo simulation. Thereafter, through the prior probability inference without posterior information and the posterior probability inference with given posterior information, the variation of flood risk is analyzed under single-factor uncertainty and two-factors uncertainties. The model is applied to Xianghongdian Reservoir in China using a flood of 100 years return period. Results indicate: the risk resulted from inflow uncertainty is greater than that of the uncertainty of initial water level; there is a certain complementarity between the uncertainties of inflow and initial water level, and the combined risk is between the results of two single-factor risk levels. Moreover, Bayesian Network is able to conduct bi-directional inferences and infer the probability distribution of any other node, which has practical value for risk assessment and control of reservoir flood control operation.
Remote Sensing and Clustering Applications in Landscape Hydrology: Characterizing a Subarctic Watershed in Nunavik (Canada)
Authors: Sicaud Eliot , Franssen Jan , Dedieu Jean-Pierre , Fortier Daniel
Published: March 2022

Hydrological data are often sparse and incomplete for large northern watershed with difficult access. Landscape hydrology approaches are useful for the indirect assessment of their hydrological characteristics by analysing the landscape properties of the watersheds. In this study, we use unsupervised Geographic Object-Based Image Analysis (GeOBIA) paired with the Fuzzy C-Means (FCM) clustering algorithm to produce a total of seven high-resolution territorial classifications for the 1985-2019 time-period. Each classification spans 5-year period and is based on key hydro-geomorphic metrics. Our application site is the George River watershed (GRW), draining a 42 000 km2 area and is located in Nunavik, northern Québec (Canada). The retrieved subwatersheds within the GRW are used as the objects of the GeOBIA and are classified in function of their hydrological similarities.

First, classification results for the time-period 2015-2019 show that the GRW is composed of two main types of subwatersheds distributed along a latitudinal gradient. This indicates differences in water balance, and hydrological regime and response. Second, six other classifications are then computed for the period 1985-2014 to investigate past changes in hydrological behavior. The seven-classification time series present an expansion of the southern-type subwatersheds northwards, principally along the George River’s main channel. This expansion is due to increases of (i) vegetation production and (ii) moisture content in soil and canopy. These are the major changes occurring in the land cover metrics of the GRW. We speculate that a rise in vegetation production contributes to evapotranspiration increase and therefore induces changes in water balance, which could explain the measured decrease of about 1% in the George River’s discharge since the mid-1970s.

 
Geological Risk Hazardous Potentials of Buraydah City, Saudi Arabia  
Authors: AlHumidan Saad
Published: March 2022

Buraydah is the capital city of Al-Qassim Region and located in the northcentral of Saudi Arabia at the heart of the Arabian Peninsula. Buraydah lies at equidistant from the Red Sea to the west and Arabian Gulf to the east. It is a part of the Buraydah quadrangle. The entire Buraydah quadrangle is underlain by Phanerozoic sedimentary rocks of the western edge of the sedimentary basin that occupies the Arabian shield. These sedimentary rocks are cropped out and have been separated by depressions of varied width commonly occupied by eolian deposits (nafud). Buraydah quadrangle is part of Unayzah Formation. In general, the Unayzah Formation is composed of cycles of cross-bedded, fine to coarse grained quartz sandstones, siltstone, vary colored clay stones, and thin beds of argillaceous limestone. Such deposits cover a substantial area in the eastern part of the quadrangle. Buraydah has a hot desert climate (Köppen climate classification BWh), with long, extremely hot summers and short, very mild winters. Precipitation is very low, which falls almost entirely between November and May, leaving summers extremely dry. The city is known for its dates festival which is the biggest in the world with various types of dates, it’s called the city of dates. On November 8, 2021, the United Nations Educational, Scientific and Cultural Organization "UNESCO" included the city of Buraydah within the UNESCO Network of Creative Cities, in the field of gastronomy. It has experienced a very high rates of population growth, in 2010 it was 614,093 growing to an estimation of 745,353 in 2021. The sewage services of Buraydah is still under processing. The main procedure applied there is digging and rebuilding a wide hole in front of each building to collect the sewage water in it and artificially dewatered by time to time. Different types of geological hazards are noted including land subsidence and earth fissures, sinkholes, expansive soils, and flash floods. A wide variety of recent geological hazards have been reported in several areas, causing significant human and property losses. Human activities, most notably groundwater extraction, infrastructure development, and agricultural activities, have induced unstable conditions.
Climate-Invariant, Causally Consistent Neural Networks as Robust Emulators of Subgrid Processes across Climates
Authors: Beucler Tom , Iglesias-Suarez Fernando , Eyring Veronika , Pritchard Michael , Runge Jakob , Gentine Pierre
Published: March 2022

Data-driven algorithms, in particular neural networks, can emulate the effects of unresolved processes in coarse-resolution Earth system models (ESMs) if trained on high-resolution simulation or observational data. However, they can (1) make large generalization errors when evaluated in conditions they were not trained on; and (2) trigger instabilities when coupled back to ESMs.

First, we propose to physically rescale the inputs and outputs of neural networks to help them generalize to unseen climates. Applied to the offline parameterization of subgrid-scale thermodynamics (convection and radiation) in three distinct climate models, we show that rescaled or "climate-invariant" neural networks make accurate predictions in test climates that are 8K warmer than their training climates. Second, we propose to eliminate spurious causal relations between inputs and outputs by using a recently developed causal discovery framework (PCMCI). For each output, we run PCMCI on the inputs time series to identify the reduced set of inputs that have the strongest causal relationship with the output. Preliminary results show that we can reach similar levels of accuracy by training one neural network per output with the reduced set of inputs; stability implications when coupled back to the ESM are explored.

Overall, our results suggest that explicitly incorporating physical knowledge into data-driven models of Earth system processes may improve their ability to generalize across climate regimes, while quantifying causal associations to select the optimal set of inputs may improve their consistency and stability.
Is there a relationship between the intermodel spread of biases and historical simulation of Indian Summer Monsoon Rainfall in CMIP6 coupled models ?
Authors: Guilbert Marcellin , Mignot Juliette , Terray Pascal
Published: March 2022

Robust projections of the Indian Summer Monsoon Rainfall (ISMR) are critical as it provides 80 % of the annual precipitation to more than one billion people who are very vulnerable to changes. However, even over the historical period, CMIP (Coupled Model Intercomparison Project) coupled models have difficulties to reproduce the observed ISMR trends and are affected by a large inter-model spread, which question the reliability of the ISMR projections. When studying climate response, three main sources of uncertainties exist : scenario uncertainties, internal variability and models bias. We study the impact of the latter on the historical response of ISMR of 34 models from CMIP6. First we show that model local biases over India do not impact significantly how they simulate the response of ISMR over the recent period. However, when we enlarge the analysis to the whole tropics and study the impact of regional and remote rainfall and SST biases on ISMR historical response by using a Maximum Covariance Analysis (MCA), we do find statistical significant relationships, which may provide observational constraints on future ISMR projections. Our results highlight the key-role of the temperature gradient errors between the arid regions surrounding India and the Arabian Sea on one hand, and of Pacific rainfall and SST biases on the other hand, as an important source of inter-model spread in the ISMR response. The physical mechanisms underlying these statistical relationships between ISMR response and the inter-model spread are finally explored.
Combining satellite altimetry, in-situ observations, and models to improve hydrological forecasting in West Africa
Authors: Canedo Rosso Claudia , Andersson Jafet C.M. , Gustafsson David , Hamatan Mohammed , Machefer Mélissande
Published: March 2022

Water level information is highly sought-after by operational hydrologists and emergency managers to improve flood management in, for example, West Africa (Lienert et al 2020). A main constraint of large-scale flood forecasting systems is an inability to convert streamflow volumes to water level at specific locations. Accurately representing water levels – and hence potential impacts of peak flows on local scale – is possible through detailed field work and hydraulic simulations (e.g. Massazza et al 2020). However, large-scale implementation of such approaches is typically constrained by lack of detailed topographic data. In this study we therefore develop a pragmatic method to estimate water levels using rating curves created through a combination of ground-based (in-situ) hydrometric gauge observations, hydrological simulations, and satellite altimetry data. Specifically, rating curves are created based on simulated discharge from HYPE models and 305 in-situ discharge observations from 1980 to 2020, in addition to 42 in-situ and 558 virtual water level stations (i.e. locations where Sentinel-3 missions intersect large rivers) from 2018 to 2020. The rating curves were estimated by fitting a conventional power-law equation. For the in-situ data this could be done directly from the two variables. These were, however, very scarce. We therefore exploited the EO-based virtual stations to be able to predict water levels at many more locations. To this end, rating curves were estimated using simulated discharge together with EO-based water level data at the virtual station locations. The inverted rating curve equation was subsequently used to transform simulated discharge to water level. The water levels estimated from simulated discharge were finally compared with the in-situ and virtual altimetry stations using accuracy performance metrics such as Nash-Sutcliffe efficiency (NSE) and Kling-Gupta efficiency (KGE). Furthermore, we examine and compare the rating curve uncertainty obtained from different data sources (in-situ, modelled and satellite data). This pragmatic methodology can be used in operational hydrology, specifically flood forecasting, to render forecasts more relevant at local scale and hence enable better flood risk management.
Fluid migrations and volcanic earthquakes from depolarized ambient noise
Authors: De Siena Luca , Petrosino Simona
Published: March 2022

Ambient noise polarizes inside fault zones, yet the spatial and temporal resolution of polarized noise on gas-bearing fluids migrating through stressed volcanic systems is unknown. At Campi Flegrei caldera (Southern Italy), high polarization marks a transfer structure connecting the deforming centre of the caldera to open hydrothermal vents and extensional caldera-bounding faults during periods of low seismic release. Fluids pressurize the Campi Flegrei hydrothermal system, migrate, and increase stress before earthquakes. The loss of polarization (depolarization) of the transfer and extensional structures maps pressurized fluids, detecting fluid migrations after seismic sequences. After recent intense seismicity (December 2019-April 2020), the transfer structure appears sealed while fluids stored in the east caldera have moved further east. Our findings show that depolarized noise has the potential to monitor fluid migrations and earthquakes at stressed volcanoes quasi-instantaneously and with minimum processing.
Pulling up new chairs to the table: experiences of organising diversity and inclusion events during a pandemic
Authors: Cox Jana , Thorslund Josefin , Roelofs Lonneke , Ebner Ronja , Dunn Frances , van Rijsingen Noortje , Baxter Allix , Dhaubanjar Sanita , Postma Merel
Published: March 2022

Young Women of Geosciences (YWOG) is a group at Utrecht University (the Netherlands) which aims to create an equal and inclusive working environment for all employees in the faculty of Geosciences. Now in our fourth year, with an expanding committee and increasing support from the faculty, we share some details and insights from events held during the pandemic. After several years of having primarily the same small group of people attending our events (i.e. “preaching to the choir”) our aim was to engage with more people in our faculty. We wanted to pull up new chairs to the table and hear new opinions and thoughts and so, our events were planned with this primary goal in mind. However, under changing and variable conditions due to the pandemic, the planning of events to promote diversity and inclusion became more of a challenge. We had to devise strategies to keep people engaged in diversity and inclusion topics while people became tired of online events, and were busy just dealing with the pandemic.

Our primary success was a book giveaway and discussion where three books related to diversity and inclusion (some also with climate and environmental aspects) were given for free to 30 staff members. This was followed by an open online discussion about topics that arose in the books and how these issues were experienced in our own faculty. This session had the greatest number of male participants we have ever had at one of our events (despite all sessions always being open to all genders) and this led to great information sharing and discussions. We also organised two Wikipedia hackathons which aimed to improve information on Wikipedia about female and minority scientists. This event required a great deal of time and skill development which unfortunately many people were not able to commit to, which led to smaller numbers and less engagement than our book event.

Overall, we managed to introduce new groups of people to our discussions and engage with a broader audience than in previous years, within a virtual environment. We attribute this in large part to attractive events and hard work on our communication strategy. We found that engagement in activities, particularly for new attendees, was highly dependent on time availability and concrete communication of details of the event. We frequently used social media to communicate about our events and significant growth of these channels in the virtual-only environment of lockdowns led to overall increased engagement. This was particularly the case on Twitter, where we have found active and supportive fellow networks to engage with, be inspired by, and inspire.
Long-term evolution of eddying oceans in a warming world
Authors: Beech Nathan , Jung Thomas , Semmler Tido , Rackow Thomas , Wang Qiang , Danilov Sergey
Published: March 2022

Mesoscale ocean eddies impact atmosphere-ocean gas exchange, carbon sequestration, and nutrient transport. Studies have attempted to identify trends in eddy activity using satellite altimetry; however, it is difficult to distinguish between robust trends and natural variability within the short observational record. Using a novel climate model that exploits the variable-resolution capabilities of unstructured meshes in the ocean component to concentrate computational resources in eddy-rich regions, we assess global mesoscale eddies and their long-term response to climate change at an unprecedented scale. The modeled results challenge the significance of some trends identified by observational studies, as well as the effectiveness of linear trends in assessing eddy kinetic energy (EKE) change. Some anticipated changes to ocean circulation, such as a poleward shift of major ocean currents and eddy saturation in the Southern Ocean, are reinforced by the modeled EKE changes. Several novel insights regarding the evolution of EKE in a warming world are also proposed, such as a decrease of EKE along the Gulf Stream in unison with weakening Atlantic meridional overturning circulation (AMOC); increasing Agulhas leakage; and accelerating, non-linear increases of EKE in the basins of the Kuroshio Current, Brazil and Malvinas Currents, and the Antarctic Circumpolar Current (ACC).
Ensemble forecast of the Madden Julian Oscillation using a stochastic weather generator based on analogs of  Z500
Authors: Krouma Meriem , Yiou Pascal , Silini Riccardo
Published: March 2022

Skillful forecast of the Madden Julian Oscillation (MJO) has an important scientific interest because the MJO represents one of the most important sources of  sub-seasonal predictability. Proxies of the MJO can be derived from the first principal components of wind speed and outgoing longwave radiation (OLR) in the Tropics (RMM1 and RMM2). The challenge is to forecast these two indices. This study aims at providing ensemble forecasts MJO indices  from analogs of the atmospheric circulation, mainly the geopotential at 500 hPa (Z500) by using a stochastic weather generator. We generate an ensemble of 100 members for the amplitude and the RMMs for sub-seasonal lead times (from 2 to 4 weeks). Then we evaluate the skill of the ensemble forecast and the ensemble mean using respectively probabilistic and deterministic skill scores. We found that a reasonable forecast could reach 40 days for the different seasons. We compared our SWG forecast with other forecasts of the MJO.
Acoustic tomography assessment of the acoustic characteristics of bubble clouds
Authors: Bae Ho Seuk , Son Su-Uk , Kim Hyoung Rok , Kim Woo-Shik , Park Joung Soo
Published: March 2022

In the seawater environment, interactions of the rotation of ship propellers with the wind tend to produce masses of localized bubbles. These bubble clouds cause acoustical interference in the acquisition of sonar data during marine surveys and marine exploration. For example, pronounced bubble-attenuation of pressure levels results in acoustic signals received by sonar equipment being below predicted values. In addition, a strong backscattering signal may be detected due to the impedance difference between liquid water and intra-bubble air. These effects distort underwater sonar measurement data. If the acoustic characteristics of a bubble cloud in the seawater environment can be known in advance, more precise measurement data could be obtained through data processing. Thus, the aim of this study was to assess the acoustic characteristics of experimenter-produced bubbles. Acoustic tomography techniques were used to obtain data descriptive of the acoustic characteristics and distribution of bubble clouds. We developed six sets of buoy systems equipped with multiple projectors and hydrophones for acoustic tomography. The buoy systems were installed in a hexagonal arrangement in seawater. A transmitter emitted sequential sound signals into the water in response to radiofrequency-transmitted commands from a control device located on land. Each acoustic signal was recorded by multiple hydrophones. Applying repetitive optimization techniques to the tomography data, it was possible to analyze acoustic characteristics such as transmission loss of signals transmitted through bubble clouds, magnitude of backscattering associated with bubble clouds, and bubble distributions. The acoustic effects and distribution characteristics of bubbles documented in this experiment will be used as foundational data for subsequent research.
Nutrient scarcity strengthens soil fauna control over leaf litter decomposition in tropical rainforests
Authors: Peguero Guille , Sardans Jordi , Richter Andreas , Janssens Ivan , Peñuelas Josep
Published: March 2022

Soil fauna is a key control of the decomposition rate of leaf litter, yet its interactions with litter quality and the soil environment remain elusive. We conducted a litter decomposition experiment across different topographic levels within the landscape replicated in two rainforest sites providing natural gradients in soil fertility to test the hypothesis that low nutrient availability in litter and soil increases the strength of fauna control over litter decomposition. We crossed these data with a large dataset of 44 variables characterizing the biotic and abiotic microenvironment of each sampling point and found that microbe-driven Carbon (C) and Nitrogen (N) losses from leaf litter were 10.1 and 17.9 % lower, respectively, in the nutrient-poorest site but this among-site difference was equalized when meso- and macrofauna had access to the litterbags. Further, on average soil fauna enhanced the rate of litter decomposition by 22.6%, and this contribution consistently increased as nutrient availability in the microenvironment declined. Our results indicate that nutrient scarcity increases the importance of soil fauna on C and N cycling in tropical rainforests. Further, soil fauna is able to equalize differences in microbial decomposition potential thus buffering to a remarkable extent nutrient shortages at an ecosystem level.
3D sequential data assimilation in Elmer/Ice with Stokes
Authors: Cook Samuel , Gillet-Chaulet Fabien
Published: March 2022

Providing suitable initial states is a long-standing problem in numerical modelling of glaciers and ice sheets, as well as in other areas of the geosciences, due to the frequent lack of observations. This is particularly acute in glaciology, where important parameters such as the underlying bed may be only very sparsely observed or even completely unobserved. Glaciological models also often require lengthy relaxation periods to dissipate incompatibilities between input datasets gathered over different timeframes, which may lead to the modelled initial state diverging significantly from the real state of the glacier, with consequent effects on the accuracy of the simulation. Sequential data assimilation using an ensemble offers one possibility for resolving both these issues: by running the model over a period for which various observational datasets are available and loading observations into the model at the time they were gathered, the model state can be brought into good agreement with the real glacier state at the end of the observational window. The mean values of the ensemble for unknown parameters, such as the bed, then also represent best guesses for the true parameter values. This assimilated model state can then be used to initialise prognostic runs without introducing model artefacts or a distorted picture of the actual glacier.

In this study, we present a framework for conducting sequential data assimilation and retrieving the bed of a glacier in a 3D setting of the open-source, finite-element glacier flow model, Elmer/Ice, and solving the Stokes equations rather than using the shallow shelf approximation. Assimilation is undertaken using the open-source PDAF library developed at the Alfred Wegener Institute. We demonstrate that the set-up allows us to accurately retrieve the bed of a synthetic glacier and present our plans to extend it to a real-world example.
Assessing the seasonal forecast performance of hydrological extremes over Europe
Authors: Du Yiheng , Pechlivanidis Ilias , Clemenzi Ilaria
Published: March 2022

The attention given to hydro-climate services is continuously increasing due to the scientific improvements of hydrological models and numerical weather forecasts. However, there is still an urgent need to highlight the predictability of hydrological droughts and floods in order to meet the growing demand on hydrological forecast information from socio-economic sectors, such as energy production and agricultural irrigation. In this study, we evaluated the seasonal hydrological reforecasts generated by the E-HYPE hydrological model forced with predictions from the fifth-generation seasonal forecasting system of the European Centre for Medium-Range Weather Forecasts (ECMWF SEAS5), covering the period 1993-2015. The forecast skill was benchmarked to the simulated streamflow climatology by calculating the Brier Skill Scores for both high and low streamflow for each initialization month and lead time. Results show that both hydrological droughts and flooding over Europe are generally well predicted, with spatial and temporal variability depending on the initialization month and lead time. The results are of high importance since geographical areas and times are identified where the seasonal hydrological forecasts provide an added-value for flooding and droughts, and consequently contribute to decision-making in water resources management.
Using Value Chain Approaches to Evaluate End-to-End Warning Systems
Authors: Hoffmann David , Ebert Beth , Mooney Carla , Golding Brian
Published: March 2022

The weather information value chain provides a framework for characterising the production, communication, and use of information by all stakeholders in an end-to-end warning system. Since the generation of weather warning and climate services has become more complex, both technically and organizationally, the value chain concept has become a popular tool for describing and assessing the production, use and benefits of such services.

The end-to-end warning system for high impact weather brings together hazard monitoring, modelling and forecasting, risk assessment, communication and preparedness activities and systems and processes which support people to take timely action to reduce risks. Weather and associated warning services are typically developed and provided through a multitude of complex and malleable value chains (networks), often established through co-design, co-creation and co-provision.  

A 4-year international project under the WMO World Weather Research Programme that started in November 2020 is using value chain approaches to describe and evaluate the end-to-end warning system for high impact weather. Its aims are

To review value chain approaches used to describe weather, warning and climate services to assess and provide guidance on how they can be best applied in a high impact weather warning context that involves multiple users and partnerships;

To generate an easily accessible means (an End-to-End Warning Chain Database) for scientists and practitioners involved in researching, designing and evaluating weather-related warning systems to review previous experience of high impact weather events and assess their efficacy using value chain approaches.

We encourage the research and operational community to participate in this project by contributing case studies of high impact events and collaborating in their analysis. Integration of the physical and social sciences in this project will lead to new insights that we hope will ultimately improve the effectiveness of warnings for high impact weather.
Zero-height geopotential level estimation for the homogenization and modernization of the Vertical Datum of Greece
Authors: Andritsanos Vassilios D. , Grigoriadis Vassilios N. , Natsiopoulos Dimitrios , Vergos Georgios S.
Published: March 2022

Within the frame of the “Modernization of the Hellenic Gravity Network” project, the homogenization of the Hellenic Vertical Datum is investigated. Two study areas in northern and southern Greece were selected, where the zero-level geopotential value Wo is estimated for each area. Additionally, a combined value is also estimated using a weighted least squares adjustment of Helmert orthometric heights and surface gravity values, that were recently measured, as well as recent global geopotential models. The biases in the vertical datum between northern and southern Greece are investigated through the comparison with a global conventional value. The validation of the results can lead to valuable conclusions on the possibility of a contemporary definition of the Hellenic Vertical Datum.