bluuebunny/crossref_metadata_2025 huggingface dataset:
Remote Reconnaissance Mission to the 14th August 2021 Haiti Earthquake; remote sensing and building damage assessments 
Authors: Whitworth Michael , Giardina Giorgia , Penney Camilla , Di Sarno Luigi , Adams Keith , Kijewski-Correa Tracy , Macabuag Josh , Foroughnia Mahtab , Macchiarulo Valentina , Ojaghi Mobin , Orfeo Alessandra , Pugliese Francesco , Dönmez Kökcan , Black Jacob , d Aktas Yasemin
Published: March 2022

Post-earthquake reconnaissance missions are critical to understand the event characteristics, identify building and infrastructure vulnerabilities, and improve future construction practice. However, in-field missions can present logistic and safety challenges that do not make them viable in every post-disaster scenario. Remote sensing technique can be used to rapidly collect a large amount information that can be used to enrich the post-event learning process. While the possibility to deploy teams in the field remain a valuable asset for an integrated understanding of technical and socio-economic factors, a mix of remote and in-field reconnaissance activities can be a way forward in post-disaster management.

This work presents the results of a hybrid mission mobilised by the Earthquake Engineering Field Investigation Team (EEFIT) after the 2021 Haiti earthquake. On 14 August 2021, a 7.2 magnitude earthquake struck the Tiburon Peninsula in the Caribbean nation of Haiti, approximately 150km east of the capital Port au Prince. The event was followed by numerous aftershocks up to magnitude 5.7, and tiggered over 1000 landslides. Over 2000 people lost their lives, with over 15,000 injured and over 137,000 houses damaged or destroyed. The estimated economic impact is of the order of US$1.6 billion. Due the complex political and security situation in Haiti, coupled with the global pandemic, a full in field mission was not considered feasible, so a hybrid mission was designed instead.

First, open-source information was collected and used to characterise the seismic event, analyse the strong ground motion and compare to established national and international earthquake codes and standard. Second, remote sensing techniques including Interferometric Synthetic Aperture Radar (InSAR) and Optical/Multispectral imagery were used to understand the earthquake mechanism, the ground displacement distribution and the possibility to detect landslide on a regional scale. The general applicability of remote sensing technique in the context of post disaster assessment was also evaluated. Finally, the earthquake impact on different building typologies in Haiti was investigated through the damage assessment of over 2000 buildings comprising schools, hospitals, churches and housing. This was done in collaboration with the Structural Extreme Events Reconnaissance (StEER) team, who mobilised a team of local non-experts to rapidly record building damage.

This talk summarises the mission setup and findings, and discusses the benefits of and difficulties encountered during this hybrid reconnaissance.
Measuring and modeling water fluxes across soil-plant-atmosphere continuum in a temperate forest environment
Authors: Vogel Tomas , Skalova Veronika , Dohnal Michal , Votrubova Jana , Tesar Miroslav
Published: March 2022

This study is focused on fluxes of water and energy associated with the plant transpiration in a temperate montane forest of Central Europe. The research is based on the long-term monitoring of basic hydrological and meteorological variables at two adjacent forest sites, covered with Norway spruce and European beech. The analysis of the observed variables is combined with the numerical modeling of soil-plant hydraulics.

Among the monitored variables, sap flow in tree xylem is measured continuously by thermal dissipation probes. Soil water pressure and soil water content are monitored by tensiometers and FDR sensors at several depths. Catchment discharge observations, reflecting the subsurface responses to major rainfall events, are used together with the soil water content data to provide the relevant information on the catchment water balance, which constrains the long-term cumulative transpiration amount.

A one-dimensional soil water flow model, involving vertically distributed macroscopic root water uptake and whole-plant hydraulic capacitance algorithm to account for the transient xylem water storage, is used to simulate the temporal variations of water fluxes in the soil-plant-atmosphere system.

The observed sap flow rates are compared with the simulated transpiration fluxes. A particular attention is paid to the different behavior of spruce and beech trees during periods with extreme transpiration demand (summer midday conditions). The results of the comparisons confirm the expected isohydric response of spruce in contrast to a more anisohydric behavior of beech trees.

The comparison of the modeling results with the in-situ observations reveals a complex interplay of soil and plant hydraulic properties determining the specific responses of spruce and beech forest stands to the same weather conditions.

The research is supported by the Czech Science Foundation Project No. 20-00788S.
High-performance Material Point Method for Landslide Simulation in Julia
Authors: Huo Zenan , Jaboyedoff Michel , Derron Marc-Henri , Wyser Emmanuel , Mei Gang
Published: March 2022

The study of landslides spans from pre-failure mechanisms to post-failure propagation. The risk posed by landslides often relies more on the latter, and quantitative analysis for it can also describe the hazard caused by landslides more intuitively. Traditional numerical methods, such as the finite element method (FEM), suffer from severe mesh distortions when dealing with the highly nonlinear problems of landslides, especially in the post-failure propagation, resulting in inefficient or even failed computations. Meshfree methods such as the material point method (MPM) can efficiently describe the large deformation process of a structure using material points by reducing the dependence on the mesh. However, its computational efficiency is much lower compared to FEM. Currently, MPM programs are written in languages like C/C++/Fortran, which are performant but difficult to implement and read, and in languages like MATLAB/Python, which are flexible and easy to read but at the cost of much lower performance. This is known as the “two-language problem”. A new programming language, Julia, recently rose to prominence in scientific computing. It is designed for high-performance computing, has many of the features of advanced programming languages, and solves the "two-language problem". Benefiting from the native support for GPU computing in Julia, we can easily introduce GPU computing in the program to efficiently simulate the dynamic process in the post-failure of landslide. Consequently, for such a computationally intensive task, programming a high-performance MPM in Julia would be an attractive alternative. We use the Generalized Interpolation Material Point (GIMP) method, a variant of MPM, to perform the simulations and demonstrate the capabilities of the Julia language for high-performance scientific computing.
Carbon fluxes estimation with aleatoric and epistemic uncertainties at high spatial resolution over large areas
Authors: Martínez-Ferrer Laura , Moreno-Martínez Álvaro , Kimball John S. , Running Steven W. , Clinton Nicholas , Camps-Valls Gustau
Published: March 2022

Gross primary production (GPP) represents the amount of carbon captured via vegetation photosynthesis,  being this process one of the main drivers of climate regulation. Due to its importance, GPP is routinely estimated at global scales using different operational algorithms combining remotely-sensed data from medium spatial resolution sensors and ancillary meteorological information. There are numerous processes at multiple spatio temporal scales that result in GPP variability. Since these processes occur simultaneously at finer resolutions but also across large areas there is a need for GPP products that meet these specifications. The estimation of GPP requires consistent mosaics and long time series of high spatial resolution satellite information, which are often plagued by data record gaps as a result of cloud contamination, radiometric differences across sensors, scene overlaps, and their inherent sensor noise. To overcome these constraints, we used the HIghly Scalable Temporal Adaptive Reflectance Fusion Model (HISTARFM) algorithm that fuses spectral data from Landsat and MODIS and produces monthly gap free surface reflectance data at 30m over large areas with associated well-calibrated data uncertainties. Combining this monthly high resolution data with daily meteorological information, along with in-situ eddy covariance GPP estimates leads us to be able to create accurate and continuous high spatial resolution GPP estimates and their corresponding uncertainties (aleatoric and epistemic) using machine learning approaches. The processing pipeline is implemented in the Google Earth Engine (GEE) to produce a long time series (20 years) of continuous GPP estimates over Europe at 30m. This work enables more precise carbon studies and understanding of land-atmosphere interactions, as well as the possibility of deriving other carbon, heat and energy fluxes at an unprecedented spatio-temporal resolution.
Spatial and temporal variability of rainfall on different time scales
Authors: Bárdossy András
Published: March 2022

Rainfall is highly variable in space and time. The knowledge of precipitation variability is very important for design or for uncertainty assessment of models. In this contribution two different aspects of variability are investigated – the treatment of zero observations for spatial interpolation and the problem of high order dependence. The finer the temporal resolution of precipitation observations the more zeros have to be considered. Should one include all zeros for the description of the spatial variability (for example variograms)? Examples corresponding to different time aggregations are show that zeros need a specific treatment. High order dependence is investigated using time series observed at multiple sites. Results are compared to a meta-Gaussian approach. A large high-resolution dataset from South-West Germany is used to demonstrate the problems and the different approaches.
The role of decarbonization and dehydration in aftershock genesis. 
Authors: Gunatilake Thanushika , Miller Stephen A.
Published: March 2022

The 2011 Tohoku earthquake in northern Japan triggered thousands of aftershocks within a few days. The 2016 Amatrice-Visso-Norcia (AVN) earthquake sequence in the central Apennines (Italy) triggered hundreds of thousands of aftershocks in the first year, and the 2021 earthquakes in Greece (March 3, 2021 and in Crete on September 12, 2021) triggered numerous sizable aftershocks within a few days. In contrast, an earthquake 100 km east of the Crete earthquake (Oct. 12, 2021) generated almost no aftershocks. Additionally, great earthquakes in Pakistan (M7.8, 2011) and Iran (M7.7, 2013) also spawned no aftershocks.  These observations contradict generally accepted physical models for aftershock genesis.  

In this talk, I compare the rich AVN earthquake sequence with earthquakes that generate few aftershocks and demonstrate through modeling that aftershocks are driven by co-seismically generated (high-pressure) fluid sources through thermal decomposition. Earthquakes without trapped fluid sources at depth, or without thermal decomposition generate few, if any aftershocks.

The AVN sequence showed dramatic differences in aftershock rates along strike, with non-Omori type aftershock behavior. Using a non-linear diffusion model that captures permeability dynamics in the crust combined with a source term to account for thermal decomposition, we show excellent agreement between model and observations for the entire Italy AVN sequence.
Offshore wind and solar photovoltaic energy combination to stabilize energy supply in the western Iberian Peninsula in the near future. 
Authors: Costoya Xurxo , deCastro Maite , Carvalho David , Arguilé-Pérez Beatriz , Gómez-Gesteira Moncho
Published: March 2022

The expansion of marine renewable power is a major alternative for the reduction of greenhouse gases emissions. In Europe, however, the high penetration of offshore wind brings intermittency and power variability into the existing power grid. Offshore solar photovoltaic power is another technological alternative under consideration in the plans for decarbonization. However, future variations in wind, air temperature or solar radiation due to climate change will have a great impact on both renewable energy resources. In this context, this study focusses on the offshore energy assessment off the coast of Western Iberia, a European region encompassing Portugal and the Northwestern part of Spain. Making use of a vast source of data from 35 simulations of a research project called CORDEX, this study investigates the complementarity of offshore wind and solar energy sources with the aim of improving the energy supply stability of this region up to 2040. The most pessimistic greenhouse gases emission scenario (RCP8.5) is considered. The 35 simulations are validated by comparing wind speed at 10m, air temperature at 2m and solar radiation values with data from the ERA5 reanalysis database. Although the offshore wind energy resource has proven to be higher than solar photovoltaic resource at annual scale, both renewable resources showed significant spatiotemporal energy variability throughout the western Iberian Peninsula. When both renewable resources are combined, the stability of the energy resource increased considerably throughout the year. The proposed wind and solar combination scheme is assessed by a performance classification method called Delphi, considering stability, resource, risk, and economic factors. The total index classification increases when resource stability is improved by considering hybrid offshore wind-photovoltaic solar energy production, especially along the nearshore waters.
How do the local meteorology and turbulence influence the nitrogen dioxide concentration in Madrid?
Authors: Yagüe Carlos , Román-Cascón Carlos , Ortiz Pablo , Sastre Mariano , Maqueda Gregorio , Serrano Encarna , Artíñano Begoña , Gómez-Moreno Francisco Javier , Díaz-Ramiro Elías , Alonso Elisabeth , Fernández Javier , Borge Rafael , Narros Adolfo , Cordero José María , García Ana María , Núñez Andrés
Published: March 2022

The pollutant concentration close to the surface at specific sites of a city depends on multiple factors. However, disentangling the relative importance of them using observational data is not an easy task. To deepen into these relationships, in this study we use intensive and multiple data from several urban field campaigns that were developed in the city of Madrid (Spain) during 2020 and 2021 under the framework of the AIRTEC-CM (*) research project (Urban Air Quality and Climate Change Integral Assessment).
Among the most typical pollutants in cities, the nitrogen dioxide (NO2) is of crucial importance due to its negative impacts on human health. The diurnal cycle of this pollutant is closely related to the anthropogenic emissions in the area and to the local meteorology, as well as to the turbulent transfers in the atmospheric boundary layer. In this work, we analyse the relation between the NO2  concentration and different meteorological variables, including some turbulent parameters calculated from sonic anemometers: turbulent kinetic energy (TKE) and friction velocity (U*). In this sense, we have distinguished those situations where the turbulent parameters are more valuable (have better correlation) than the wind speed, which is the meteorological variable typically used to be correlated with the pollutant concentration.
The analysis of the data clearly reveals how the highest NO2 concentrations are associated with fair-weather (stable) synoptic conditions, as it is already known and expected. However, the detailed analysis of the diurnal cycle in these periods also highlights how the stability favours the appearance of mesoscale diurnal winds (mountain breezes) in the city, increasing the turbulence close to the surface and favouring the pollutants dispersion. This is of key importance because in some cases these processes are not correctly simulated by numerical models, which could lead to wrong predictions (overestimation) of the pollutant’s concentrations at specific hours. Specifically, the evening transition and the following hours during stable conditions are the most difficult periods, displaying the highest and quicker variability in NO2 concentration: very high concentration during calm periods in the transition followed by a rapid cleaning of the air a few hours later due to the breeze appearance.

 

(*) AIRTEC-CM research project (S2018/EMT-4329) is funded by The Regional Government of Madrid (Spain).
A novel approach to large-ensemble modelling: the time-slice Large Ensemble
Authors: Muntjewerf Laura , Bintanja Richard , Reerink Thomas , Van der Wiel Karin
Published: March 2022

Large-ensemble modelling has become an increasingly popular approach to study the climatic response to external forcing. The idea of a large ensemble is to generate different realizations of a forced climate to explicitly reproduce the system’s internal variability. With these large datasets it is not only possible to quantify and statistically test changes in the mean climate, but also changes in climate variability and subsequent changes in extremes. Typically, the approach to generate a large ensemble set is to force the model with a transient forcing and start the different simulations from slightly different initial conditions. However, this is expensive due to the high computational demand of full-complexity GCMs or ESMs.

Here we propose a large-ensemble design that generates a multitude of years to describe the climate states of interest, while being more economical regarding computational resources: a time-slice Large Ensemble. The core of the concept is to generate multiple time slices rather than long transient simulations. The time slices represent the present-day climate and a future warmer climate. These are segments of, for example, 10-years; too short to show significant climate change. Using stochastic physics, we add a randomizing component to the simulations. This allows us to branch multiple simulations from one set of initial conditions.

We present the advantages and limitations of this design and we quantify the underlying assumptions. Further, we demonstrate examples of analyses from earlier work for which this type of large ensemble is well (or better) suited, in particular for studying future extreme events and finding analogues of observed extreme events. Finally, we present ongoing work on the generation and analysis of a new time-slice large-ensemble dataset with EC-Earth v3. The experimental set-up is to branch off from 16 full historical and SSP2-4.5 simulations to represent the present-day climate and a future +2K climate.
Evaluation of the ITRF2020P reference frame by means of Satellite Laser Observations (SLR) data analysis
Authors: Susnik Andreja , Appleby Graham , Rodriguez Jose
Published: March 2022

SLR data of LAGEOS-1/2 and Etalon-1/2 satellites were used for generating weekly solution sets containing station coordinates, Earth Rotation Parameters, as well as accommodating systematic range errors, for the period from 1993 to 2020. The solutions follow the approach developed within the ILRS Analysis Standing Committee, with smoothed systematic range errors applied to station range normal points where required. The satellite centre-of-mass corrections developed by Rodriguez et al (2019), and his continuing updates, were applied to the NP ranges. The solutions were used for an evaluation of the ITRF2020P reference frame and to conduct comparisons to ITRF2014. Following our previous investigations into the impact on the scale of the ITRF of systematic range errors, we investigate in particular the difference in scale of the reference frame from our current solutions when mapped using weekly Helmert transformations onto ITRF2014 and onto ITRF2020P.
The volcanic impact on convection and stratospheric ice
Authors: Kroll Clarissa , Kornblueh Luis , Dauhut Thibaut , Schmidt Hauke , Timmreck Claudia , Fueglistaler Stephan
Published: March 2022

Volcanic aerosol heating perturbs the tropical tropopause layer (TTL) and with it the stratospheric water budget. Whereas the effect of increased cold point temperatures on water slowly ascending into the TTL can be studied using general circulation models (GCM), the robustness of changes in convection after volcanic eruptions in these models is unclear as the TTL is tuned to unperturbed conditions and the simulations highly rely on parametrizations. Estimating the changes in the contributions of temperature effects, overshoots and vertical diffusion after a volcanic eruption or in a geoengineering study accordingly remains a challenge in GCM simulations. The emerging cloud resolving simulations however offer the unique possibility to gain insight into the sensitivity of the TTL to external forcings.

They allow in particular to study potential changes of convection, where two processes counteract each other after volcanic eruptions: the downwards shift of the lapse rate tropopause favoring overshooting convection in combination with increased stability in the TTL region suppressing overshooting convection.

We analyze these effects employing convection-resolving simulations for the atmosphere with the Icosahedral Nonhydrostatic Weather and Climate Model (ICON-A) at 10 km horizontal resolution in two scenarios: a control run and a volcanically perturbed run. The perturbed run has an aerosol layer in the lower stratosphere corresponding to the peak loading of an injection of 20 Tg sulfur using sea surface temperatures from the control run. In addition to a downwards shift of the lapse rate tropopause, we find that the level of neutral buoyancy, based on the temperature difference in convective areas and their surroundings, reaches the TTL more often in the volcanically perturbed simulations. This allows – contrary to previous assumptions - for more overshoots into the region above the tropical lapse rate tropopause.
Using long-lived radium isotopes as water-mass tracers in the North Sea and investigating their use for tracking artificial ocean alkalinization.
Authors: Mears Chantal , Thomas Helmuth , Wolschke Hendrik , Voynova Yoana , Schrader Anton
Published: March 2022

The long-lived radium isotopes, 226Ra (t1/2= 1600 yrs.) and 228Ra (t1/2 = 5.8 yrs.), are established shelf-sea tracers, capable of discerning key water-mass compositions and distribution patterns from source to sea. Within the North Sea, radium has not only been recognized as a suitable tool for identifying water-mass characteristics, but 228Ra has also been found to effectively trace total alkalinity (AT). Within the known continental shelf pump system of the North Sea, this indirect link between radium and the carbonate system has recently enticed greater interest for climate mitigation strategies, such as Artificial Ocean Alkalinization (AOA). But, prior to initiating intentional anthropogenic perturbations on the complex coastal North Sea, it is imperative to understand the initial state of the system. In order to do just that, our study builds on the previous knowledge of water-mass distributions within the North Sea, distinguishing the sources and mixing patterns which contribute to the three main water-masses (with particular focus placed on further identification of the North Atlantic input source components). Quantitatively, these patterns are further supported through the use of inverse modelling techniques, which highlight the importance of end members for each of the water-masses. Overall this study provides a more in-depth baseline understanding of water-mass distribution and mixing within the North Sea.
Adaptive emission reduction approach to reach the Paris Agreement temperature targets
Authors: Terhaar Jens , Frölicher Thomas , Aschwanden Mathias , Friedlingstein Pierre , Joos Fortunat
Published: March 2022

The parties of the Paris Agreement agreed to keep global warming well below 2°C and assess the necessary greenhouse gas emissions reductions every five years during the global stocktake. Globally, the necessary reductions in greenhouse gases are often derived using the remaining emissions budget concept. However, estimations of this budget vary by a factor of two to three and may hamper efforts to establish ambitions emissions reductions. Here, we propose an adaptive approach that side-step these uncertainties to quantify these global emissions reductions during the successive global stocktake solely based on regularly updated observations of past temperatures, radiative forcing, and emissions statistics. The approach consists of three main steps repeated every five years: (1) determining the anthropogenic warming to date and hence the remaining warming allowed, (2) estimating the remaining CO2 forcing equivalent (CO2-fe) emission budget, and (3) proposing a CO2-fe or CO2 emission trajectory for the next 5 years. We test this approach using the Bern3D-LPX Earth System Model of Intermediate Complexity and demonstrate that the temperature targets 1.5°C and 2°C can be reached following a smooth emissions pathway. The adaptive nature makes the approach robust against inherent uncertainties in the observational records, climate sensitivity to emissions, and effectiveness of emissions reduction implementations. The approach thus allows developing an emissions trajectory that would iteratively adapt to ultimately meet the agreed temperature goal. The approach also provides a strong alternative to the often-used pre-defined emissions or concentration pathways (such as SSPs), which can result in very different end-of-century temperatures for the same emission or concentration trajectories. Some of these pathways are developed to be consistent with a given warming level (e.g., SSP1-1.9 for 1.5°C), not knowing the actual response of the Earth system to emissions. As opposed to these simulations, simulations from different models using the adaptive approach we propose here would be directly comparable in terms of warming and broader climate impacts but would differ in terms of required emissions. Our approach would hence guide a valuable and highly policy-relevant complementary set of simulations for the next generation of CMIP models resulting in a range of future emission trajectories compatible with a given global warming target.
Natural and forced soil aeration during agricultural managed aquifer recharge (Ag-MAR)
Authors: Ganot Yonatan , Dahlke Helen
Published: March 2022

Agricultural managed aquifer recharge (Ag-MAR) is an emerging method for groundwater replenishment, in which farmland is flooded during the winter using excess surface water to recharge the underlying aquifer. Successful implementation of Ag-MAR projects requires careful estimation of the soil aeration status, as prolonged saturated (waterlogged) conditions in the rhizosphere can damage crops due to O2 deficiency. We studied the soil aeration status under almond trees and cover crops during Ag-MAR at three sites differing in drainage properties. We used O2 and redox potential as soil aeration quantifiers to test the impact of forced aeration compared with natural soil aeration. Forced aeration treatments included air-injection through subsurface drip irrigation, or dissolution of calcium peroxide powder (scattered on the soil surface before flooding). Our results suggest that forced soil aeration methods have an average increase of up to 2% O2 compared to natural soil aeration. Additionally, only a minor impact on crop yield was observed between treatments for one growing season. Results further suggest that natural soil aeration can support crop O2 demand during Ag-MAR if flooding duration is controlled according to O2 depletion rates. According to this concept, we developed a simple model based only on soil texture and crop type, for estimating Ag-MAR flood duration with minimal crop damage.
Forest biomass - an uncertainty source of land use and land cover change related carbon emissions in the Amazon
Authors: Tejada Graciela , V. Gatti Luciana , S. Basso Luana , A. V. Mataveli Guilherme , L.G. Cassol Henrique , Von Randow Celso
Published: March 2022

Tropical forest plays a fundamental role in the ecosystem services maintenance. Amazon forests have been subject to intense land use and cover changes (LUCC), mainly in the Southeast portion. Like many tropical countries, more than 70% of Brazilian greenhouse gasses emissions come from LUCC. Under the framework of the CARBAM Project, atmospheric CO2 measurements in four sites of the Amazon, show that there is a reduction in the Amazon forest capacity to absorb C in the proximities of previous deforested and degraded forest areas, such as the well-known “Deforestation Arc” in the Southeast amazon. There are many LUCC databases now available that allow to assess the deforestation, degradation and second forest dynamics and contribute to a better understanding of the carbon dynamics of nine years of in situ atmospheric CO2 measurements. Nevertheless, in order to know how much CO2 is released to the atmosphere due to LUCC, it is necessary to quantify how much carbon is stored in the forest biomass and to assess the biomass variability along the different datasets. Here we compared the forest biomass quantity of three biomass maps: the fourth national communication of Brazil map (official), a global map (Baccini et al. 2012) and a regional map for the Brazilian Amazon (EBA project). We found significant differences for the Brazilian Amazon: between the official biomass map and the regional map 27%, between the global and regional map 25% and the smallest difference was between the official and the global map (3%). Even though the official and the regional maps were obtained using the same data inputs, the official map refers to a potential biomass for 2010 and the regional map reflects the real biomass in 2016, this could explain the difference. The official and global maps represent the potential biomass, and as we used the mean forest area, the biomass content is similar. When comparing these maps at a deforested pixel level the differences could be larger. The spatial and temporal scale of biomass maps make it hard to estimate the CO2 emissions of degradation and secondary forest loss and growth which are fundamental to understand the Amazon C balance under climate change and LUCC pressures.  

Key words: Amazon, CO2 emissions, forest biomass, land use and cover change, carbon balance
Intense precipitation during the African Humid Period inferred from east Saharan fossil rivers: Implications for human dispersal   
Authors: Zaki Abdallah , King Georgina , Haghipour Negar , Giegengack Robert , Watkins Stephen , Gupta Sanjeev , Schuster Mathieu , Khairy Hossam , Ahmed Salah , El-Wakil Mostafa , Eltayeb Saleh , Herman Frédéric , Castelltort Sébastien
Published: March 2022

During Late Quaternary time, the paleoclimate of the eastern Sahara was punctuated by multiple pluvial periods, then dramatically and cyclically transformed to hyperarid conditions, receiving less than 2 mm/yr of precipitation at present. Geologists, climate modelers, and archaeologists, therefore, have used various proxies to reconstruct past climates during that time, a crucial period for human habitation and migration. These reconstructions, however, lack the precipitation pattern during those pluvial periods, which represents a significant control on weighing the hypotheses of human migrations and occupations. Here we reconstruct the chronology and paleohydrology of a set of fossil rivers expressed by ridges in the modern landscape due to differential erosion. Our 14C and Optically Stimulated Luminescence (OSL) ages of sediments preserved in these ancient rivers cluster within the last African Humid Period (AHP; ca. 14.8 – 5.5 ka BP) and hence support more significant fluvial activity during this distinct humid epoch. Based on median grain size (D50), paleochannel geometry, and drainage area, paleohydraulic reconstructions indicate that typical precipitation intensities of 55–80 mm/h occurred during sediment transport events. When combined with previous annual rainfall estimates, we find that such rainfall intensities were likely 3–4 times more frequent during the AHP. These climatic perturbations may have rendered some parts of the Nile River Valley inhospitable for occupation, driving humans to migrate away in the northwest and west of the Nile Valley between 10.2 and 7.2 ka BP. Ultimately, our results, along with the archeological data, tell a tale from the past of the dramatic climatic changes that our planet undergoes, demonstrating the critical role of climate in sustaining human populations. 

 
Positioning performance of the Neustrelitz Total Electron Content Model (NTCM) driven by Galileo ionization coefficients
Authors: Cahuasquí Juan Andrés , Hoque Mainul , Jakowski Norbert
Published: March 2022

GNSS single-frequency applications are affected by the interaction of the radio signals with the free electrons of the ionosphere, introducing range errors of up to 100 m in the L-band. Besides the GPS Klobuchar and the Galileo NeQuick ionospheric models, also the Neustrelitz Total Electron Content Model (NTCM) has been proposed as a practicable solution to mitigate such propagation errors.

In this investigation we present a global statistical validation of the NTCM version driven by Galileo ionization coefficients (NTCM-GlAzpar) by comparing its performance with the performance achieved by the NeQuickG and Klobuchar models in the position domain. For this aim, we used the ESA analysis tool “gLAB” in the Standard Point Positioning (SPP) mode and GNSS data over two different time periods. The first period covers one month of perturbed solar activity (December 2014) and the second period corresponds to a month of quiet conditions (December 2019). We achieved a worldwide coverage with data from up to 73 receivers of the International GNSS Service (IGS).

Our statistical analysis allows us to conclude that the NTCM-GlAzpar model clearly outperforms the results achieved with the Klobuchar model and is slightly better, or at least comparable, to the performance shown by NeQuickG. Indeed, the root mean squared (RMS) values of the hourly mean 3D position errors obtained for the global dataset are 4.36, 4.61 and 6.71 meters for perturbed conditions and 2.32, 2.35 and 2.75 meters for the quiet period, respectively for the NTCM-GlAzpar, NeQuickG and Klobuchar models. Nevertheless, through a geographic- and diurnal-specific analysis, we identify also that the performance of NTCM-GlAzpar slightly decreases for conditions of reduced solar activity – at night time, higher latitudes and low perturbations.

We further discuss the applicability of the NTCM-GlAzpar ionospheric model in GNSS single-frequency applications motivated by its simple software adaptations and low computational cost.
Investigating Spatial Patterns And Characteristics Of Preconditioned Compound Flooding Over Europe
Authors: Manoj J Ashish , Pérez Ciria Teresa , Chiogna Gabriele , Salzmann Nadine , Agarwal Ankit
Published: March 2022

Preconditioned compound events are defined as events in which an underlying weather-driven or climate-driven precondition causes an increase in the impacts of a hazard. In state-of-the-art risk assessment studies, the dependencies and cross-correlations between multiple variables/processes are usually difficult to account for. However,  previous studies have shown that some of the most devastating extreme events in the past years occurred within a cascade of interdependent and interrelated hazards. This is particularly true in the case of initial hydrologic conditions for large scale pluvial events (Eg: European Floods – 2021). The lack of proper characterisation of the spatiotemporal patterns and impacts of antecedent soil moisture conditions on extreme precipitation events hinder our understanding of such high impact flooding events and subsequently the early warning and mitigation or reduction of severe impacts for the society. Hence with this critical research gap in mind, in the present work, we employ Event Coincidence Analysis (ECA) to identify and characterise the regions over which Precipitation extremes (P) occur over Soil Moisture extreme states (SM). Precursor coincidence rate calculates the fraction of such preconditioned SM-P events out of total P extremes. The datasets used include the E-OBS v24.0 gridded product for precipitation and GLEAM v3.5a for soil moisture modelled product. Our results indicate strong seasonal variations in such SM-P preconditioning over Europe. A significant shift in the magnitude and spatial extent of SM-P coupling is seen within the seasons for the various regions. Strong coincidence is seen for western and central Europe in winter, and the coincidence weakens in summer. For eastern Europe, stronger preconditioning is seen in the summer compared to the winter season. The observed trends over the study duration of 1980 to 2020 are in line with the historical climatological and meteorological patterns of the regions. We further made use of the timings of annual maximum discharge (Peak flood values) at a catchment scale from a European flood database to investigate how the seasonal and spatial variations in the timings of floods could be interpreted from the SM-P preconditioning perspective. Our results will aid in strengthening existing flood risk assessment initiatives while providing new avenues and implications for a better understanding and proper representation of preconditioned compound flooding events over Europe.
Revisiting ENSO and IOD contributions to Australian Precipitation
Authors: Liguori Giovanni , McGregor Shayne , Singh Martin , Arblaster Julie , Di Lorenzo Emanuele
Published: March 2022

Tropical modes of variability, such as El Niño–Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD), exert a strong influence on the interannual variability of Australian precipitation. Nevertheless, commonly used indices of ENSO and IOD variability display significant co-variability that prevents a robust quantification of the independent contribution of each mode to precipitation anomalies. This co-variability issue is often addressed by statistically removing ENSO or IOD variability from the precipitation field before calculating teleconnection patterns. However, by performing a suite of coupled and uncoupled modelling experiments in which either ENSO or IOD variability is physically removed, we show that ENSO-only-driven precipitation patterns computed by statistically removing the IOD influence significantly underestimate the impact of ENSO on Australian precipitation variability. Inspired by this, we propose a conceptual model that allows one to effectively separate the contribution of each mode to Australian precipitation variability.
A Statistical Downscaling Approach of Soil Moisture Estimations by Synergistically using Optical Remote Sensing and Ground Soil Moisture Measurements at the Valencia Anchor Station
Authors: Ansari Amoli Abdolreza , Mahmoodi Ali , Lopez-Baeza Ernesto
Published: March 2022

A multifractal technique has been used to downscale 1 km optical remote sensing MODIS derived soil moisture index (SMI) to the scale of interpolated soil moisture map produced by ground measurements at the Valencia Anchor Station (VAS) during the SMOS Validation Rehearsal Campaign (2008) with the spatial resolution of 32 meters. Scale invariance assessment shows a constant behavior of soil moisture variability at all scales of aggregation. This result proves the homogeneity of the VAS region from a mathematical point of view and exempts or allows us from using ancillary data such as topography, soil texture and vegetation characteristics in our downscaling model. Our predicted soil moisture values compared to the observed ground data show RMSE ranges from 0.026 to 0.039 for 2008/05/02, indicating accurate predictions for this date. However, there are high RMSE values in the range of 0.761 to 0.784 for 2008/04/24, due to rainfall events (30 mm accumulated) occurring in the region a few days prior to the measurements, which influenced the result of the downscaling model. At the same time, the strong correlation (77%) between the predicted and the observed data is promising and warrants further application of the model to other homogeneous areas with or without rainfall events.
Correlation of Wind Speed and Eruption Frequency ofStrokkur Geyser, Iceland
Authors: Hamzaliyev Shaig , Eibl Eva P.S. , Hersir Gylfi Páll , Petersen Guðrún Nína , Dahm Torsten
Published: March 2022

A geyser is a multiphase geothermal feature that exhibits frequent, jetting
eruptions of hot water and non-condensable gases such as CO2. In Iceland it
was noted that Strokkur geyser erupts at regular intervals. Following single
eruptions the typical waiting time is for example 3.7 ± 0.9 min. However, we
noted that single eruptions are sometimes followed by an up to 7 min long
gap and are the first ones to investigate this in the context of the weather at
Strokkur.
A local broadband seismic network at Strokkur geyser, Iceland recorded more
than 300000 eruptions during 2017-2018 and 2020-2021. The hourly weather
data was acquired from the Hjardarland meteorological station at a few kilome-
ters distance from Strokkur maintained by the Icelandic Meteorological Office.
First we calculate the waiting time after eruptions and to make it comparable
with the hourly weather data we calculate hourly means. First we used a sim-
ple pearson correlation to calculate the correlation in different time windows.
As the time window increased the correlation between the waiting time and
wind speed increased. No substantial increase in the correlation coefficients was
visible for window lengths of more than 8 hours. So we chose an 8 hour long
time window for the further analysis. We compare the averaged waiting time
after eruptions, with wind speed, temperature, air pressure and humidity. To
understand the relation more deeply, we plot each weather parameter vs. the
waiting time average and fit linear and quadratic functions to the data. We
find a strong correlation with the wind speed and minor anticorrelation with
temperature and humidity. After calculating residuals the results indicate that
there is a quadratic relation between the waiting time and wind speed. This
highlights the sensitivity of the pool geyser with respect to environmental factors
interfering with the heat balance of the system.
Interaction between disturbances and their effects on the recovery of a heterogeneousMediterranean landscape in South America
Authors: Hernandez-Duarte Ana , Saavedra Freddy
Published: March 2022

Fires and droughts are important drivers of disturbance in Mediterranean forests. Despite this, there is a gap of knowledge of the effect of climate change and particularly the interaction of longer periods of drought with other disturbance processes in remnants of native forests. As the frequency of these events is expected to increase in the future, it is important for forest managers to understand recovery patterns and the response of vegetation to these interactions. The objective of this work is to quantify the effects of the interaction of drought and fires in the recovery of Mediterranean-type forests at a local scale in South America using field data, satellite images, and trend analysis. These forests have experienced significant reductions in their extension and fragmentation, and in recent years have been subjected to the longest drought since there are records and that occurred between 2010 and 2020. Using a time series of Landsat satellite images (1986-2020) and the fire registry of the National Forestry Corporation (CONAF) we evaluate the relationship between the Normalized Difference Vegetation Index (NDVI) and other vegetation indices with characteristics measured in the field to evaluate the recovery after a fire event. We quantify the temporal trends of the NDVI to discover the location, direction, and timing of the change. In addition, we evaluate the interaction of climate, soil, and topography by forest type. We observe that the NDVI recovery slope is less steep in burned areas in the periods after 2015, exacerbating in topographic conditions of northern exposure (of the southern hemisphere). Even for the time period analyzed, some areas were reported where recovery levels still do not show a significant positive trend. We also observed a difference in the recovery of areas that experienced high severity fires versus low or intermediate severity fires in a period of drought, the recovery of areas exposed to a high severity fire takes twice as long to recover. These results indicate that the vegetation recovery processes can be negatively affected by the drought that occurs before, during, and after fires. Our analysis identifies spatially explicit patterns of short- and medium-term trends in these “new” regimes of prolonged droughts and fires, providing insight into forecast warmer and drier weather conditions so that our results can serve as a general framework for the resource management of these highly stressed areas, which can be applied to similar Mediterranean ecosystems.
Characteristic buttressing of Antarctic ice shelves
Authors: Schöll Simon , Reese Ronja , Winkelmann Ricarda
Published: March 2022

The increasing dynamical loss of grounded ice in response to thinning of surrounding ice shelves is the main driver of the current sea level rise contribution of Antarctica. The observed acceleration of the ice streams is caused by reduced buttressing of the ice shelves connecting the grounded ice flow to the warming ocean. Several methods have been used to analyze the back-stress of the ice shelves at individual grounding line locations, however none of those quantify the state of the whole shelf. Here we present shelf-wide definitions of buttressing for major Antarctic ice shelves, based on the stress-balance at the grounding line, that respond consistently to ocean warming. We use the Parallel Ice Sheet Model (PISM) at 8km grid resolution and diagnostic output from Úa with a resolution of 200m at the grounding line. We show an increase in buttressing for more confined ice shelves and a decrease under idealized ocean warming. With the shelf-wide buttressing, the role of buttressing in the (de-)stabilizing capabilities of ice shelves on marine ice streams can be investigated.