bluuebunny/crossref_metadata_2025 huggingface dataset:
Time-variable gravity and mass redistribution from synergistic use of GRACE-FO and Chinese gravity satellites
Authors: Lück Christina , Kusche Jürgen , Feng Wei , Shen Yunzhong , Chen Qiujie , Wang Changqing
Published: March 2022

The project „Time-variable gravity and mass redistribution from synergistic use of GRACE-FO and Chinese gravity satellites“ aims at establishing improved time-variable gravity field models. This work is a joint initiative of the National Natural Science Foundation of China (NSFC) and the German Research Foundation (DFG).

Gravity field estimation from the existing GRACE and GRACE-FO missions will be improved, e.g. by optimizing dealiasing signals, refining the noise modeling, accelerometer calibration and optimizing anisotropic filtering techniques. Furthermore, the possibilities of a combination with the upcoming Chinese gravity field mission TianQin-2 will be explored and optimal orbit parameters for TianQin-2 will be determined.

One focus area is the East China Sea. Here, we will isolate the ocean mass change signal over this study region and apply a joint inversion framework to close the regional sea level budget. The contribution of sediment discharge will be accounted for by evaluating oceanic velocities from an ocean model using a Lagrangian approach.

Groundwater storage (GWS) variations will be closely investigated over the North China Plain. First, GWS is calculated by evaluating GRACE(-FO) gravity solutions. For this aim, non-GWS compartments will be removed using global and regional models. An error-estimation considers the uncertainty of measurement errors, post-processing of the gravity field solutions and model errors. Secondly, GWS will directly be inferred from hydrological models. Observations from monitoring wells and GPS stations will be used as independent additional observations.

In this contribution, we will introduce our project and its objectives in more detail. Furthermore, we will show preliminary results regarding ocean mass change in the East China Sea and GWS variations over the North China Plain.
Do future projections in windstorm severity depend on climate model resolution?
Authors: Manning Colin , Kendon Elizabeth J. , Fowler Hayley J.
Published: March 2022

Extratropical windstorms can lead to considerable impacts in the UK. Anthropogenic climate change is likely to influence the frequency of extreme windstorms, although there is considerable uncertainty in the simulated response by climate models due to internal variability and differences in climate model formulations. A further source of uncertainty arises from model inadequacies in their representation of key processes that drive extreme winds and their future changes due to their spatial resolution. To assess this uncertainty, we study the UKCP18 climate projections, generated by the UK Met Office, which comprises a 12-member perturbed parameter ensemble from a 60km global climate model (GCM), downscaled by a 12km regional climate model (RCM) over Europe and a 2.2km convection-permitting model (CPM) over the UK. We study a control (1981-2000) and future (2061-2080, RCP8.5) period over a domain covering the UK and Ireland. Storm intensity is quantified using the storm severity index (SSI) which incorporates surface wind gusts, while we also assess wind speeds at 850hPa. The CPM and RCM project a future increase in the frequency of extreme windstorms and both are very similar in their representation of the SSI as well as extreme winds at 850hPa. In contrast, the GCM underestimates the severity of windstorms due to poorer representation of cold sector winds driven by cold conveyor belts and sting jets. Furthermore, the GCM projects little change in extreme windstorms in the future period resulting in a large underestimation in the future change compared to the CPM and RCM.  Overall, little difference is seen between the CPM and RCM, with CPM added value largely restricted to fine-scale detail in the spatial structure of storms. This may in part be due to the small domain size of the CPM, and the relatively high resolution of the RCM. Results for the GCM may bring into question the usefulness of coarser resolution models, such as those used in CMIP5 and CMIP6, for studying future changes in windstorm severity.
Identification of erosion rills via machine learning
Authors: Tejkl Adam , Kavka Petr
Published: March 2022

Water erosion is the physical wearing of the earth’s surface. Erosion removes surface soil material (topsoil), reduces levels of soil organic matter, and contributes to the breakdown of soil structure.

The large amount of time required for manual identification of the rills is an obstacle in effective erosion research. Nevertheless, a significant number of rills have already been manually marked for various studies. It is therefore possible to use these already obtained data to train an algorithm, which will then automatically identify the grooves. The experiment is carried out using a rain simulator. The first part of the precipitation lasts 30 minutes, followed by a 15-minute break and another 30-minute precipitation. Photos for SfM method of creation detailed DMT are taken in three states a) before the simulation, b) between the simulations and c) after the experiment. On the finished DMT rills are manually digitalized in ArcGIS Pro, and their cover polygons are thus created.

Nhu et al. 2020 in his work dealt with the evaluation of the capabilities of the Keras deep learning model and their optimization algorithms. Keras is a deep learning API written in Python, running on top of the machine learning platform TensorFlow.

The image is converted to a matrix using the Raster to Array tool. The corresponding square is selected from each band and a mosaic is then created from these squares. The length of the square edge is chosen. The resulting mosaic consists of individual squares of the image spectrum bands placed side by side to form a rectangular image.

The Kaggle Cat Dog model was used as the basis for creating the model. This is a model designed to sort color images into two groups. This model was modified by inserting mosaics into the model instead of images. The training dataset is loaded into the model and divided into calibration and validation parts for the purpose of model calibration. This distribution was chosen to be 20%. The image size was specified as 100x200 pixels, with pixel of size 0,1 cm.

The individual mosaics not used for model training are then classified by this trained model. Loading mosaics for classification is controlled by a CSV file, which contains the name of the mosaic, the position of the mosaic in the image and whether it is intended for training or not. The probability value with which the mosaic is classified as erosive or not is then added to this CSV file. Training mosaics are omitted and assigned a no_data value.

The CSV file of the classified image is loaded back into the GIS environment using a Python script. The script loads the CSV file and creates an according classified raster.

The research is funded by the Technological Agency of the Czech Republic (research project SS01020366) and an internal student CTU grant (SGS20/156/OHK1/3T/11).
Establishing the potential impacts of climate change on extreme flood events across the UK.
Authors: Ramsamy Laura , Brennan James , Mitchell Hamish , Zeneli Markela , Burke Claire , Kluza Kamil
Published: March 2022

The severity and frequency of extreme flood events has intensified both globally, and across the UK. Climate change will influence weather patterns across the UK, making it increasingly important to understand the impacts this may have on future flood events.

We developed 90m hydraulic models to simulate extreme pluvial and fluvial flood events across the UK based on observed events. The models have been climate conditioned, allowing the potential impacts of climate change on extreme pluvial and fluvial flood events to be understood. Using different climate scenarios, we examine the variation in outcome depending on what efforts are taken to reduce emissions. Modelling the impacts climate change could have on flooding at a national scale, enables us to understand the spatial-temporal distribution of flood risk. This information can be used in the real world for decision making and providing a way to mitigate against the impacts of climate change.
Recent dust modeling developments in the ECMWF IFS in support to CAMS
Authors: Remy Samuel , Kipling Zak , Flemming Johannes
Published: March 2022

The Integrated Forecasting System (IFS) of ECMWF is core of the Copernicus Atmosphere Monitoring Service (CAMS) to provide global analyses and forecasts of atmospheric composition, including reactive gases, as well as aerosol and greenhouse gases. Desert dust is simulated globally in three size bins. This system has been extended in an experimental version to prognostically simulate twelve mineralogical components of dust, each of them in three size bins. The chemical composition of dust can be derived from the mineralogical information, which allows for comparison against surface observations, notable of Iron. Each of the dust mineralogical component uses specific optical properties.

Four years of dust simulated global mineralogical and chemical composition have been produced. Iron from dust have been compared against observations of surface concentration worldwide and against simulations from the atmospheric iron model intercomparison organized by the Group of Experts on the Scientific Aspects of Marine Environmental Protection (GESAMP). Both evaluations gave satisfactory results. Surface concentration of other dust chemical components have been evaluated against surface observations other US and Europe.

Simulation of the dust mineralogy allows for a better representation of the geographical variation in dust absorption, especially depending on the simulated burden of the most absorbing species, hematite and goethite. While this variability cannot yet be represented in the optical properties of the dust species used operationally within CAMS, the climatology of dust mineralogy helped to derive new dust optical properties in the visible part of the spectrum. It also provided a degree of regional information about dust size distribution at emission, which has been implemented in the IFS. These two developments, together with an update of the dust source function, led to a significant improvement in the skill of the IFS system for dust related parameters. They have been included in the next operational upgrade of the operational global CAMS system, cycle 48R1, which is planned in late 2022.
Rapid detection of complex deformation pattern following strong earthquakes through DInSAR measurements: the October 2016 central Italy case
Authors: Carboni Filippo , Porreca Massimiliano , Valerio Emanuela , Manzo Mariarosaria , De Luca Claudio , Ercoli Maurizio , Barchi Massimiliano
Published: March 2022

In the last three decades, remote sensing techniques, such as Differential Synthetic Aperture Radar Interferometry (DInSAR), Lidar differencing, optical imagery, and Global Positioning System (GPS) have been exploited for investigating, with high accuracy, ground displacement phenomena. Large seismic events (Mw > 5.5) can trigger deformations at the surface, such as ruptures related to the activation of main active faults and/or other deformations induced by seismic shaking (e.g., landslides, creeping, sinkhole).

In 2016-2017, a long earthquake sequence struck the Apennines in central Italy, producing impressive surface ruptures attributed to the 24 August Mw 6.0 and 30 October Mw 6.5 main-shocks. These ruptures were investigated and mapped by field geologists soon after the earthquakes.

We present detailed maps of the surface deformation pattern produced by the M. Vettore Fault System during the October 2016 earthquakes. The DInSAR analysis have been retrieved from ALOS-2 SAR data, via the Parallel Small BAseline Subsets (P-SBAS) algorithm. On these maps, we trace a set of cross-sections to analyse the coseismic vertical displacement, essential to identify both surface fault ruptures and off-fault deformations.

At a local scale, we identify a lower number of coseismic ruptures respect to the ones recognised in the field, but they are in very good agreement and even more laterally continuous. At a larger scale, we observe the M. Vettore Fault System hanging-wall being characterized by a long-wavelength upward-convex curvature, which is less evident towards the south and locally interrupted by a steep vertical gradient, testifying the occurrence of an antithetic NE-dipping fault.

A quantitative comparison of DInSAR- and field-derived vertical displacement reveals that our approach is particularly effective to constrain ruptures characterized by spatial vertical displacement up to 50 – 60 cm, which, in the field, show an unclear lateral continuity.

The rapid detection of deformation patterns from DInSAR technique can furnish important constraints on the activated fault segments, their spatial distribution and interaction soon after the seismic events. Thanks to the large availability of satellite SAR acquisitions, the proposed workflow can be potentially applied worldwide. It might be fundamental not only to support field geological mapping activities during an ongoing seismic crisis but also to provide a wider and faster picture of surface ruptures crucial for emergency management by civil protection in densely populated areas.
Predictive performance of deep-learning-enhanced remote-sensing data for ecological variables of tidal flats over time
Authors: Madhuanand Logambal , Phillippart Katja , Nijland Wiebe , Wang Jiong , De Jong Steven M. , Bijleveld Allert I. , Addink Elisabeth A.
Published: March 2022

Tidal flat systems with a diverse benthic community (e.g., bivalves, polychaetes and crustaceans) is important in the food chain for migratory birds and fish. The geographical distribution of macrozoobenthos depends on physical factors, among which sediment characteristics are key aspects. Although high-resolution and high-frequency mapping of benthic indices (i.e., sediment composition and benthic fauna) of these coastal systems are essential to coastal management plans, it is challenging to gather such information on tidal flats through in-situ measurements. The Synoptic Intertidal Benthic Survey (SIBES) database provides this field information for a 500m grid annual for the Dutch Wadden Sea, but continuous coverage and seasonal dynamics are still lacking. Remote sensing may be the only feasible monitoring method to fill in this gap, but it is hampered by the lack of spectral contrast and variation in this environment. In this study, we used a deep-learning model to enhance the information extraction from remote-sensing images for the prediction of environmental and ecological variables of the tidal flats of the Dutch Wadden Sea. A Variational Auto Encoder (VAE) deep-learning model was trained with Sentinel-2 satellite images with four bands (blue, green, red and near-infrared) over three years (2018, 2019 and 2020) of the tidal flats of the Dutch Wadden Sea. The model was trained to derive important characteristics of the tidal flats as image features by reproducing the input image. These features contain representative information from the four input bands, like spatial texture and band ratios, to complement the low-contrast spectral signatures. The VAE features, the spectral bands and the field-collected samples together were used to train a random forest model to predict the sediment characteristics: median grain size and silt content, and macrozoobenthic biomass and species richness. The prediction was done on the tidal flats of Pinkegat and Zoutkamperlaag of the Dutch Wadden sea. The encoded features consistently increased the accuracy of the predictive model. Compared to a model trained with just the spectral bands, the use of encoded features improved the prediction (coefficient of determination, R2) by 10-15% points for 2018, 2019 and 2020. Our approach improves the available techniques for mapping and monitoring of sediment and macrozoobenthic properties of tidal flat systems and thereby contribute towards their sustainable management.
CPMIP: Computational evaluation of the new era of complex Earth System Models. Multi-model results from CMIP6 and challenges for the exascale computing.
Authors: Acosta Mario , Balaji Venkatramani , Palomas Sergi , Paronuzzi Stella
Published: March 2022

The increase in Earth System Models (ESMs) capabilities is strongly linked to the amount of computing power and data storage capacity available. The scientific community requires increased model resolution, large numbers of experiments and ensembles to quantify uncertainty, increased complexity of ESMs (including additional components), and longer simulation periods compared to the current state of climate models. HPC is currently undergoing a major change as is the next generation of computing systems (‘exascale systems’). These challenges cannot be met by mere extrapolation but require radical innovation in several computing technologies and numerical algorithms. Most applications targeting exascale machines require some degree of rewriting to expose more parallelism, and many face severe strong-scaling challenges if they are to effectively progress to exascale, as is demanded by their science goals. 

 

However, the performance evaluation of the new models through the exascale path will also increase its complexity. We do need new approaches to ensure that the computational evaluation of this new generation of models is done correctly. Moreover, this evaluation will help in the computational analysis during the model’s development and ensure the maximum throughput possible in the moment that operational configurations such as CMIP are run.

 

CPMIP metrics are a universal set of metrics easy to collect, which provide a new way to study ESMs from a computational point of view. Thanks to the H2020 project IS-ENES3, we had a unique opportunity to exploit this new set of metrics to create a novel database based on CMIP6 experiments, using the different models and platforms available all across Europe.

 

The results and analysis are presented here, where both differences and similarities among the models can be observed on a variety of different hardware. Moreover, the current database is presented for different studies, such as the comparison of different models running similar configurations or the same model and configuration but executed on different platforms. All these possibilities create a unique context that has to be exploited by the community to improve the evaluation of the computational performance of the ESMs, using this information for future optimizations and preparing our models for the new exascale platforms. Eventually, general prescriptions on how to disseminate the work done are given, and the need for the community to undertake the use of CPMIP metrics both on actual and new generation's platform is presented.
Geography of World’s Water Risks
Authors: Varis Olli , Kummu Matti , Taka Maija
Published: March 2022

Water risks are perennially identified among the planet’s most stunning and influential factors of insecurity and underdevelopment by institutions such as the United Nations and The World Economic Forum. Scholarly water risk literature, however, suffers from many inconsistencies and the alignment of basic water risk concepts with key policy protocols such as those of the United Nations Post-2015 Agenda is not mature. Therefore, macro-level understanding of world’s water risks is subjected to inconsistencies. We analyze a set of water risks with a global-scale interest, namely the 13 water risks of the Aqueduct data product. First, their statistical structure is analyzed, grouping them into clusters. Second, a new classification of water risks is produced and used in a global mapping analysis of how the water risks manifest across the latitudes, including their relation to climatic zones, population density and socioeconomic development. This is done by adopting the Sendai framework’s hazard-exposure-vulnerability risk concept. The results reveal the importance of distinguishing clearly between water hazards and water risks and specifying (usually situation-specific) relevant components of exposure and vulnerability that link those. Aqueduct, for instance, uses the word risk in many instances that are factually hazards, and a similar unambiguity is present very widely in water literature. The most remarkable geographic pattern that we detected is the strong dependency of water hazards on latitudes; those related to variability being fiercest along the tropics, and those to infrastructure centering around the equator. Many chronic hazards are most pronounced in crowded latitudes, whereas those related to hydrological extremes have similarities with the patterns of variability related hazards. Besides detecting these global hotspots, our study underlines the importance of clarifying and systematizing the use of concepts of water risks, water scarcity, water security and others, and harmonizing their use to policy protocols such as those of the United Nations. Due to the underlying importance of water risks, their interrelations, and unveiled geographic patterns, this is essential in improving the scientific and policy-related understanding, and the consequent reduction, of the planet’s water risks.
Mitigation of Seismic Hazards from Hydraulic Fracturing Using Cyclic Injection
Authors: Yassine Dima , Yehya Alissar , Maalouf Elsa
Published: March 2022

Hydraulic Fracturing (HF) aims at enhancing the permeability of oil and gas production reservoirs by injecting fluids at high pressures into the formation. However, this practice has been a concern to researchers; it causes perturbation to the underground system, alters the pressures and stresses along the nearby dormant faults, and may therefore, induce earthquakes under specific conditions. In this work, we study the efficacy of using a newly emerging technique, Cyclic Hydraulic Fracturing (CHF), to reduce the risk of induced seismicity while efficiently enhancing the reservoir permeability. Instead of injecting the fluid all at once at a high pressure during each stage, CHF increases the connectivity of the reservoir by injecting the same volume in a stage through different cycles. Each cycle represents a pressurization (injection) phase and a depressurization (zero-injection) phase. The effect of CHF on the stability of a fault at a close proximity to the HF operations is assessed using different injection strategies: conventional HF (constant injection per stage) and 2 CHF schemes (3 or 5 cycles per stage). For each strategy, we calculate the Coulomb Failure Stress (CFS) and the rate of seismicity along the fault using a 2D Finite Element poroelastic model. Our numerical simulations show that CHF delays the pore pressure diffusion along the fault due to the depressurization phases that allow the relaxation of the pore fluid pressure. It also reduces the seismicity rate on the fault when compared to conventional HF. Our results suggest that the mitigation of induced seismicity is possible by using a CHF procedure optimized to reduce the seismicity rate i.e., optimized number of cycles and pressurization/depressurization periods. This development paves a way to exploit sites that are abandoned due to seismic hazards.
Quantifying 21st century Greenland ice mass loss from outlet glacier retreat and surface mass balance changes from coupled MAR-GISM simulations.
Authors: Le clec'h Sébastien , Fettweis Xavier , Huybrechts Philippe
Published: March 2022

Mass loss from the Greenland Ice Sheet ice sheet has increased sixfold since the 1990s. With accelerated ice mass loss rates, it could become the largest contributor to sea-level rise in the 21stcentury. Both the surface mass balance and outlet glacier retreat control this ice mass loss. The latter is decomposed between ice flow changes in the lower trunks of outlet glaciers (discharge) and calving of marine-terminating outlet glaciers. Partitioning between SMB and retreat contributors evolved through the last decade. It is uncertain how much they will contribute individually in the future. While a coupled RCM-ice sheet model helps to improve the SMB contribution, future glacier retreat contribution modelling is in its early stages. Using the RCM MAR, fully coupled to the GISM ice sheet model, we investigate the impact of the surrounding ocean on the outlet glaciers. Our parameterization, based on oceanic basins temperature and subglacial ice sheet runoff changes, simulates individual outlet glacier retreat rate. By forcing our atmosphere – GrIS – ocean-retreat-like model by several CMIP6 GCM models, we assess the 21stcentury Greenland ice mass loss. Partitioning between mass loss from SMB and outlet glacier retreat forced by various CMIP6 SSP scenarios is estimated both at the regional and large Greenland scale.
Impact of natural hazards on global ecosystems
Authors: Kropf Chahan M. , Vaterlaus Lisa , Bresch David N.
Published: March 2022

Ultimately, human societies rely on the existence of functioning global ecosystems. Thus, avoiding the collapse of global ecosystems should be among the highest priorities of climate mitigation and adaptation efforts. However, "protecting" ecosystems is a challenge much more complex than avoiding adverse effects on human infrastructures, societies, economies or lives. For instance, natural hazards such as wildfires or floods can play a *functional* role for ecosystems, with species requiring those events in their life-cycle. Therefore simply trying to avoid the at-first-sight devastating effects of natural hazards on ecosystems can be counter-productive, and even be damaging.  

Here we present a statistical study made with the open-source, probabilistic risk model CLIMADA [1] about the frequency and magnitude distribution of several natural hazards affecting global terrestrial ecosystems. The hazard modelling is based on historical data augmented with probabilistic methods, and thus can be interpreted as providing a snap-shot of "current conditions". This can then be used as a baseline to be contrasted with future projections of climate change and socio-economic development. Further, this baseline can inform studies on the functional and vital relationship between natural hazards and ecosystems, which are necessary to design appropriate protection measures.

CLIMADA: https://github.com/CLIMADA-project/climada_python 

[1] Aznar-Siguan, G. et al., GEOSCI MODEL DEV. 12, 7 (2019) 3085–97
Reversibility experiments of present-day Antarctic grounding lines: the long-term perspective
Authors: Reese Ronja , Urruty Benoit , Hill Emily A. , Garbe Julius , Gagliardini Olivier , Durand Gael , Gillet-Chaulet Fabien , Gudmundsson G. Hilmar , Winkelmann Ricarda , Chekki Mondher , Chandler David , Langebroek Petra
Published: March 2022

The stability of the grounding lines of Antarctica is a fundamental question in glaciology, because current grounding lines are in some locations at the edge of large marine basins, and have been hypothesized to potentially undergo irreversible retreat in response to climate change. This could have global consequences and raise sea levels by several metres. However, their long-term reversibility for the current ice sheet geometry has not yet been questioned, i.e., if the present-day climatology is kept constant, will the grounding lines remain close to their currently observed position or will they retreat substantially? 

Here we focus on the long-term evolution of Antarctic grounding lines over millennial time scales. Using the Parallel Ice Sheet Model, an initial equilibrium state is created for historic climate conditions around 1850. Then the model is run forward until 2015 with atmospheric and oceanic changes from ISMIP6 to reflect recent trends in the ice sheet. After 2015, we keep the present-day climatology constant and let the ice sheet evolve towards a new steady state, which takes several thousand years. An ensemble over model parameters related to sliding and ocean forcing allows us to analyse the sensitivity of the grounding line evolution to model uncertainties. Since we start from a historic equilibrium state, we can use this approach to assess if the increase from historic to present-day climatology might push Antarctic grounding lines across a tipping point into a different basin of attraction that is characterised by a substantially retreated steady-state grounding line position. 

This work is part of the TiPACCs project and complements an overview presentation on the reversibility of present-day Antarctic grounding lines (EGU22-5176) as well as a presentation exploring the short-term reversibility experiments in more detail (EGU22-7802).
Design of solar power systems for autonomous instruments deployed in the polar regions
Authors: Prior-Jones Michael R , Bagshaw Elizabeth A , Nylen Thomas H , Pettit Joe , Carpenter Paul
Published: March 2022

Solar panels and batteries are commonly used to power autonomous instrumentation in remote locations. The use of solar power in the polar regions needs a special approach to the system design because of the need to store sufficient energy to cover the period of total darkness in the winter. In this presentation we review the key principles of solar power system design for the polar regions and provide a spreadsheet model to aid the design process. We demonstrate the importance of assessing the power consumption of ancillary electronics (such as solar regulators and low-voltage disconnect units), as this can often be greater or equal to that of the instrument itself. Consequently, the choice of solar regulator (and other ancillary devices) can have a major impact on the size of the battery required for successful operation. Controlled laboratory measurements  of power consumption for fourteen commonly-used models of solar regulator demonstrated that there can be disparity between the manufacturer’s specifications and measured power consumption, so we assess the most suitable  systems for low temperature, long-term deployment at polar latitudes.
Calibrating Climate Models – what observations matter?
Authors: Tett Simon , Gregory Jonathan , Freychet Nicolas , Cartis Coralia , Mineter Michael , Roberts Lindon
Published: March 2022

Using the 20-year-old climate model, HadCM3, we show that it is possible to calibrate the model to multiple observations by algorithmically changing parameters in the atmospheric model.  Fourteen atmospheric parameters were modified using a state-of-the-art derivative free optimization algorithm (DFOLS). The calibration reduces model-observational difference against hemispheric scale averages of multiple observations for the 2001-2005 period and used about 90 evaluations of the atmospheric model. The observations considered were outgoing longwave and shortwave radiation, land temperature and precipitation, sea level pressure, mid-tropospheric temperature and humidity, and global-average net flux into the Earth system. A 5-member ensemble was generated by starting the calibration from different initial parameter sets.

The calibrated model simulated large scale observations better than almost all CMIP5 and CMIP6 ensemble.  Spatial patterns of variables from the calibrated ensemble except for outgoing SW, land precipitation and mid-tropospheric humidity are as well simulated as in the CMIP6 ensemble. For these variables, spatial patterns are as well simulated as the CMIP5 ensemble.   In the calibrated ensemble, uncertainty in effective climate sensitivity (ECS; relative error of 10%) and the transient climate response (TCR; relative error of 5%) is small. This is the case for the response at doubling and quadrupling of CO2 concentrations. Uncertainties in regional climate change are also small.

A linear analysis which combines observational uncertainty with the Jacobian of observational sensitivity with respect to parameter change gives a parameter covariance matrix. This is in turn can be combined with the Jacobian of climate response with respect to parameter to give a linear estimate of uncertainty in climate response. The linear uncertainty is similar to the ensemble uncertainty. By increasing individual observational uncertainty in the  linear analysis, it is possible to see which observations are providing the constraints in  transient climate response at 4 times CO2. This analysis finds that almost all the constraint comes from land precipitation, outgoing SW radiation and the net flux, suggesting these are key observations to constrain climate model behaviour.
Validation of low-cost receiver derived tropospheric products against ERA5 reanalysis
Authors: Stępniak Katarzyna , Paziewski Jacek
Published: March 2022

The aim of the study is to investigate the quality of the tropospheric estimates obtained with the use of the latest dual-frequency low-cost GNSS receivers. We aim to verify if the low-cost receivers may provide information on the parameters that describe the state of the troposphere with accuracy and reliability close to that of high-grade receivers. In this way, we address a scientific question on the potential usability of such receivers for climate applications. We investigate selected GNSS tropospheric estimates such as zenith tropospheric delays (ZTDs) and horizontal gradients. ZTD accuracy is validated in comparison to ERA5, which is the fifth generation reanalysis for the global climate and weather produced by European Centre for Medium-Range Weather Forecasts (ECMWF).

The experiment is based on GNSS data collected during two measurement campaigns. The 1st campaign was carried out over three days in the winter 2020; the 2nd one was held over three days in the summer 2021. Three collocated stations equipped with u-blox ZED F9P receivers and one station with a high-grade Trimble Alloy receiver were used. Receivers were connected to two different types of GNSS antennas: a surveying-grade Leica AR10 and a patch ANN-MB antenna. Collected GNSS data were processed using Bernese GNSS Software v.5.2 in Precise Point Positioning (PPP) mode based on dual-frequency ionosphere-free model.

The presented results confirm that the tropospheric solutions based on low-cost receivers data can achieve high accuracy. Low-cost equipment provides tropospheric parameters with precision and reliability only slightly lower than that of high-grade one. We also show that an application of a surveying-grade antenna to a low-cost receiver may noticeably enhance the accuracy of the tropospheric estimates derived with such receivers. Finally, validation against the ERA5 climate reanalysis confirms that both sets can provide high-quality, accurate tropospheric estimates, which can be further used in climate applications.
Sea Level Rise Weakens the Natural Protection against Storm Surges in Shallow Lagoons
Authors: Lorenz Marvin , Arns Arne , Gräwe Ulf
Published: March 2022

Sea level rise (SLR) increases the likelihood of storm surges by shifting their frequency distribution to higher base levels. Shallow lagoons are located along many coasts, providing natural protection against storm surges by significantly reducing the surge heights inside the lagoons compared to the open coast.

In this study, we investigate the effect of SLR on storm surge heights by using a numerical model of the Western Baltic Sea with a resolution of 200 m. We find that SLR linearly increases storm surge heights at most areas of the open Western Baltic Sea coast, e.g., a storm surge of one meter height in the present time would increase to 1.2 m height at an SLR of 20 cm. For shallow lagoons, on the other hand, the results suggest surge height increases of up to 30% additional to SLR, e.g., at an SLR of 20 cm, the surge height inside the lagoon would increase to 26 cm. We investigate this behavior in further detail with a box model to study the parameter space using the following lagoon parameters: lagoon surface area, depth and width of the connection to the open water, friction, and varying surge shapes and heights.

We find that the increase is largest for lagoons where the ratio of the width of the connection to the area of the lagoon is close to ~10⁻⁵ m⁻¹. The additional surge height decreases with increasing depth of the connection. We further find that surge height increases with surge height itself, e.g., higher surges will increase more in the future than lower surges. We find increases up to 30% for lagoons in the Baltic Sea and for lagoons in the Gulf of Mexico up to 10%.

In summary, our results highlight that additional (non-linear) surge height increase needs to be considered when evaluating and planning future coastal protection measures in shallow coastal lagoons.
Subsea Dispersant Injection: How to Assess Oil Droplets Behavior in the Water Column from Pilot-Scale Experiments
Authors: Le Bihan Thomas , Giraud William , Le Floch Stéphane
Published: March 2022

Every aspects of a hydrocarbon release in deep waters are accompanied by uncertainties. Theses releases can occur from leaking wrecks, pipeline ruptures, or even blowouts. As the most catastrophic event, the blowout (subsequent to the total loss of control of the well head) lead to a massive release of hydrocarbons in the water column which can drastically impact the ecosystem for a long time frame. When this event happens in deep sea, such as in DeepWater Horizon in 2010, subsea application of dispersant can be employed to reduce the surfacing amount of oil. This technics have several benefits as it limits the risks incurred by workers above the well by reducing the volatile organic component concentrations. In addition, dispersant volumes can be lessen by a factor 5 and the application of dispersant can be carried out 24/7 even under harsh conditions. With the addition of dispersant, the oil behavior in the water column is notably modified and many questions remain concerning the fate of the dispersed oil.

Acquiring data in deep waters is very challenging. In order to better understand the action of dispersant on oil we used the CEC (Cedre Experimental Column), an original tool developed at Cedre to study the behavior of substances in the water column. In this study, pilot-scale experiments were carried on using different ratios of oil/dispersant. Thanks to shadowgraph imaging method, set up with the use of two high speed cameras at different heights in the water column, processing the data acquired on the shape and sizes of oil droplets allow to assess how the droplets evolve after their formation.  

The results obtained show substantial differences in term of behavior between the different ratios of oil/dispersant tested. The tip-streaming phenomenon, known to take place in fluids with a low interfacial tension and a sufficiently high viscosity, was clearly identified. In addition, for each oil/dispersant ratio we were able to assess some characteristics of the plume and its evolution in the water column. Data collected from these experiments can be compared to field data and then, could be integrated to the validation process of modeling softwares.
Towards a hydrological consensus about the 2nd – 3rd October 2020 ALEX storm event in the French “Alpes Maritimes” region
Authors: Pons Frédéric , Bonnifait Laurent , Criado David , Payrastre Olivier , Billaud Felix , Brigode Pierre , Fouchier Catherine , Gourbesville Philippe , Kuss Damien , Le Nouveau Nathalie , Martin Olivier , Nomis Stan , Paquet Emmanuel , Cardelli Bernard
Published: March 2022

After having swept over western France, the ALEX storm led to an exceptional Mediterranean rainfall event which hit the “Alpes Maritimes” region during the night of the 2nd to 3rd October 2020. The rainfall accumulations observed on 12 to 24 hours durations were unique in this region, with a record of 663mm in 24h (EDF raingauge at Les Mesces).

Form West to East, several valleys, mainly those of Tinée, Vésubie, and Roya were affected by major floods, landslides, sediment transport and geomorphological changes. The hydrometric network was almost destroyed. The human and material damages were considerable, with many fatalities and missing people, several villages largely destroyed, and important destructions of communication and transport networks.

A lot of technical post-flood surveys were launched by national authorities to gather a detailed knowledge of the event characteristics, with regard to rainfall accumulations, water discharges, description the torrential phenomena, and inventory of damages. This communication is focused on the question of water discharges.

National and local authorities and organisms, universities and companies, were involved in different post-flood surveys aiming at gathering information on the peak discharges and the hydrographs of the floods, for their own needs and/or within structured programs (Administrative survey, HYMEX research project www.hymex.org).

Several kind of discharge field estimations were provided using field survey measurements, satellites images, post-event Lidar data, combined with hydraulic estimations based on hydraulic formulas, and 1D/2D hydraulic models. Several teams also applied hydrological models based on radar quantitative precipitation estimates, to calculate hydrographs at different basins outlets.

To combine and draw a uniform synthesis of all these results, a consensus exchange was launched to share the knowledge gathered by the different data providers. The objective was to compare, assess, and propose common intervals of peak discharges in the different impacted valleys. We also evaluated for each valley the return period of the final interval of discharge established by the consensus.

The final product is an official administrative document, established at the end of October 2021 by the French state authorities, providing the peak discharge values to be used for post flood studies, reconstruction, and prevention measures.
Citizen science - an invaluable tool for obtaining high-resolution spatial and temporal meteorological data 
Authors: Sepic Jadranka , Vranic Jure , Aviani Ivica , Milanovic Drago , Burazer Miro
Published: March 2022

Available quality-checked institutional meteorological data is often not measured at locations of particular interest for observing specific small-scale and meso-scale atmospheric processes. Similarly, institutional data can be hard to obtain due to data policy restrictions. On the other hand, a lot of people are highly interested in meteorology, and they frequently deploy meteorological instruments at locations where they live. Such citizen data are often shared through public data repositories and websites with sophisticated visualization routines.  As a result, the networks of citizen meteorological stations are, in numerous areas, denser and more easily accessible than are the institutional meteorological networks.  

Several examples of publicly available citizen meteorological networks, including school networks, are explored – and their application to published high-quality scientific papers is discussed. It is shown that for the data-based analysis of specific atmospheric processes of interest, such as mesoscale convective disturbances and mesoscale atmospheric gravity waves, the best qualitative and quantitative results are often obtained using densely populated citizen networks.  

Finally, a “cheap and easy to do” project of constructing a meteorological station with a variable number of atmospheric sensors is presented. Suggestions on how to use such stations in educational and citizen science activities, and even in real-time warning systems, are given.  
Potential economic value of seasonal forecasts of water flows for hydropower production.
Authors: Delpiazzo Elisa , Gianni Carlotta , Mazzoli Paolo , Dalla Valle Francesco , Bagli Stefano
Published: March 2022

Demonstrating the potential economic value of seasonal forecasts is a fundamental signal to mainstream their application in real life and make them actionable instruments to cope with future climate change and to promote adaptation measures and sustainable management of natural resources.

This presentation aims to explore the potential economic value of monthly seasonal forecasts of water flows in a reservoir located in Colombia (i.e. Betania) delivering hydropower production during the period 1993-2016. To assess the economic value a maximizing simulation is applied using two alternative forecasts samples, namely the climatological mean, and the forecasts produced by the climate service SCHT (www.https://gecosistema.com/climate-tools/scht-smart-climate-hydropower-tool/). Then, the simulation has been fed with effective realizations to produce a benchmark. Finally, we get the maximum potential value, when effective realization is considered, and the potential achievable values of the alternative forecasts and their deviation with respect to the benchmark. The simulation is set as a revenue maximizing problem for a representative producer according to a series of technical constraints, such as the reservoir capacity and its volume.

Results demonstrate that SCHT forecasts have a positive value compared to the climatological mean forecasts in normal conditions. For this reason, the analysis is enriched with a sensitivity test on the technical constraints. Therefore, we produce a set of alternative scenarios considering different capacity and volume levels. For volume, we assume either 100% or 50% (net of natural discharges), and for capacity, we assume either 900 m3/s (the maximum) or 600 m3/s. The final objective is to understand whether the technical constraints affect the results and which constraints has a higher impact.
Constraints on the Moon’s deep interior from tidal deformation
Authors: Briaud Arthur , Fienga Agnès , Melini Daniele , Rambaux Nicolas , Mémin Anthony , Spada Giorgio , Saliby Christelle , Hussmann Hauke , Stark Alexander
Published: March 2022

The Moon deforms in response to tidal forcing exerted by the Earth, the Sun and, to a lesser extent, by other planetary bodies. Their observations from ground-based and space-borne instruments, as well as Lunar surface missions, provide one of the most significant constraints that can be employed to unravel the deep interior (Williams et al. [2014], Williams and Boggs [2015]). The tidal forcing generates periodic variations of the harmonic degree-2 shape and gravity that depend on the internal composition and structure of the Moon. These changes in shape and gravity of the Moon are described by three geodetic parameters, called Tidal Love numbers (TLNs). Because of their low degree, these TLNs are sensitive to the structure of the deep interior (e.g., Khan et al. [2004]). Apart from the geodetic constraints, the Moon and Mars (e.g. Zweifel et al. [2021]) are the only other bodies besides the Earth for which seismic data are available. Seismic studies using the Apollo Passive Seismic Experiment (PSE) constrain the seismic wave velocity distribution and therefore give a glimpse of the Moon’s interior structure (Garcia et al. [2011], Weber et al. [2011]). However, at greater depth, seismic data do not provide sufficient resolution on the velocity profile, leaving the near-centre Moon structure uncertain. Other studies based upon geophysical constraints (Khan et al. [2004], Harada et al. [2014, 2016], Matsumoto et al. [2015]) and the re-analysis of the Apollo seismic data suggested the existence of an attenuated region called low viscosity zone (LVZ) originated from a melting layer at the core-mantle boundary (Khan and Mosegaard [2001], Weber et al. [2011], Harada et al. [2014], Rambaux et al. [2014]).

Based on geodetic observations and seismic studies, we perform Monte Carlo simulations for combinations of thicknesses, densities and viscosities for two classes of Moon’s models, one including an undifferentiated core and one including an inner and outer core, with both classes assuming an LVZ at the core-mantle boundary. By comparing predicted and observed tidal deformation parameters we find that the existence of an inner core cannot be ruled out. Furthermore, by deducing temperature profiles for the LVZ and the mantle following Earth assumptions, we obtain stringent constraints on the radius, viscosity, and density of the LVZ. We also infer the first estimation for the outer core viscosity, for our two possible scenarios.