bluuebunny/crossref_metadata_2025 huggingface dataset:
Exploiting kilometer-scale grid spacing for climate simulations over High Mountain Asia
Authors: Collier Emily , Ban Nikolina
Published: March 2022

Mountains play a major role in shaping the weather and climate of the world. However, current under- standing of mountain climate and how it will change with further warming of the atmosphere is still very limited. The uncertainty is in large part related to the coarse grid spacing of current climate models (12-50 kilometres in regional and >50 kilometres in global climate models), which are not able to properly represent the complex mountainous orography and related processes. Thus, employing climate models with a kilometer-scale grid spacing provides a promising path. Here, we present simulations using the COSMO (COnsortium for Small-Scale MOdelling) climate model (COSMO-CLM) performed with a horizontal grid spacing of 2.2 km over all of High Mountain Asia. We evaluate model performance based on preliminary results from case study simulations of different precipitation events and year-long simulations, as well as the added value of kilometer-scale grid spacing. Our analysis lays the foundation for future applications of kilometer-scale runs for decadal simulations of both past and future climate, which comprise the ultimate goal of our project.
An analysis of the future of quantum gravimeters in hydrology using computer modelling.
Authors: Pike Eleanor , Hannah David , Krause Stefan , Bongs Kai
Published: March 2022

There are still many unexplored hypotheses regarding subsurface water movement, and gravimetry could be a tool to elucidating them. The field of gravimetry has been used in hydrology as an auxiliary methodology for many years, but recent developments in quantum technology has improved the sensitivity and accuracy of gravimeters significantly. Computer modelling can provide a helpful way of assessing the benefits of new technologies. A number of soil types were modelled to determine their wetting and drying curves, as well as a number of weather event scenarios. From these hydrological models, the changes in density produced in accordance with the wetting and drying curves were determined. The resulting change in local gravity could then be calculated and modelled with the parameters for each instrument, to determine the detection thresholds and relevancy of classical and quantum gravimeters, as well as gravity gradiometry. The data shows not only the sensitivity and accuracy of each, but can also be scaled to show their utility in varying degrees of environmental noise, ensuring that these results can be relevant to field conditions. This project should clearly demonstrate the increased visibility of subsurface water storage and flux with the use of quantum technology, sparking a conversation around the future of data gathering in hydrology.
Multi-hazard, cross-border storm risk assessment in the Alps. First insights from the TRANS-ALP project
Authors: Renner Kathrin
Published: March 2022

Extreme hydrometeorological events such as late autumn and winter storms are being increasingly observed in southern Europe and particularly in the Alps, where they threaten environmental and socio-economic systems. An example is the 2018 Vaia (also known as Adrian) storm (Oct 28-Nov 04), which strongly affected Italy, Austria, France and Switzerland. Over the past decades several damaging storms strongly impacted (i.e., caused adverse consequences on assets, people, infrastructure or the environment) mostly those countries on the northern side of the Alps (e.g., Vivian 1990, Lothar 1999, Gudrun 2005, Kyrill 2007). The Vaia storm however affected the southern side, downing more than 8 million cubic meters of forests and causing extensive damage due to a combination of multiple compounded hazards including heavy rain, flooding and landslides, and strong winds. The event caused 12 fatalities and an economic loss exceeding 3 billion Euro. This storm has been considered exceptional yet could foreshadow multi-hazard phenomena whose frequency and intensity are likely to be influenced by climate change. In such conditions, currently available risk assessment and prevention tools may prove inadequate, particularly on a cross-border level and in vulnerable mountainous regions. Therefore, there is a need to provide decision makers and stakeholders with improved and harmonised tools and standardised frameworks to conduct efficient (climate) risk assessments for cross-border areas. Current and future impacts need to be systematically investigated to adopt prevention and disaster risk reduction measures for the mitigation of inherent risks. In its first year the TRANS-ALP project analysed the occurrence of severe weather events that can be classified as extreme and their specific features in the cross-border area between Austria and Italy (Trentino-Alto Adige/South Tyrol and Veneto). Furthermore, a systematic review of the mechanisms in place to collect impact, damage and loss data has been conducted to allow for a better conceptualisation of the different risk pathways that come into play in case of intense storms. Our findings indicate a noticeable increase of extreme weather conditions that can lead to adverse consequences, also from a systemic perspective, and a complex interplay of damaging factors and chained impacts that can extend for years after the occurrence of the generating events. The findings also highlight the importance of a comprehensive multi-hazard and transdisciplinary approach to storm risk assessment within a framework harmonising Disaster Risk Reduction (DRR) and Climate Change Adaptation (CCA) instances. In this contribution the first results and insights of the project will be presented and discussed.

The described research activities have been carried out within the framework of the DG-ECHO project TRANS-ALP funded by the European Union (Grant Agreement 101004843).
Spaceborne Water Mass formation detectability and temporal evolution 
Authors: Sabia Roberto , Caughtry Jessica , Fernandez-Prieto Diego , Piracha Aqeel
Published: March 2022

Remote sensing measurements of sea surface salinity (SSS) and sea surface temperature (SST) have been used to generate satellite-derived surface T-S diagrams [1], and to compute surface density flux, spiciness and water masses (WM) formation rates and extension [2].

More recently [3], this framework has been expanded in several directions, ranging from the extension of the studied basins and their temporal span, to the inclusion of a wider pool of source datasets. Satellite uncertainties have also been propagated to the final estimates (including also heat and freshwater fluxes uncertainties) of water masses formation rates and location. Several water masses have been characterized, showing a remarkable consistency with literature estimates.

The current efforts are devoted to additional investigation pathways. Firstly, it has been studied the impact on the actual estimates of water masses formation of satellite inputs at variable spatial (0,5  to 1 ) and temporal (weekly to monthly) scales. Secondly, the temporal evolution of the estimates over a 10-yr-long timespan has been studied, both in the T/S and geographical domains, detecting possible linear trends and anomalies. Lastly, investigation on additional water masses in the Pacific Ocean under the influence of ENSO variability is ongoing.

[1] Sabia R., et al. (2014), A first estimation of SMOS‐based ocean surface T‐S diagrams, J. Geophys. Res. Oceans, 119, 7357–7371.

[2] Sabia R., et al., Variability and Uncertainties in Water Masses Formation Estimation from Space, Ocean Sciences 2016, New Orleans, LA, USA, February 2016.

[3] Piracha A., et al., Satellite-driven estimates of water mass formation and their spatio-temporal evolution, Frontiers in Marine Science, 2019.
Vulnerability assessment for climate adaptation planning in a mediterranean basin
Authors: Solans Alba , Macian-Sorribes Hector , Martinez-Capel Francisco , Pulido-Velazquez Manuel
Published: March 2022

In the context of climate uncertainty, planning for resilient, robust and adaptive water measures to achieve social, economic and environmental objectives, is a challenge.

The aim of this study is to identify critical climatic conditions that cause system failure in a Mediterranean basin in order to evaluate vulnerabilities and design robust and adaptive measures of water supply. The methodology employed adopts a stress test under non-stationary climatic conditions consisting of: 1) generation of meteorological scenarios, by using a weather generator, 2) generation of hydrological scenarios by using a hydrological model, and 3) evaluation of system performance by using a water resource system model whose outcomes are used to identify climatic vulnerabilities .

Meteorological scenarios are built using, first, a weather generator at the sub-basin scale that generates synthetic precipitation (P) and temperature (T) time series at annual scale by using autorregressive models to extract low-frequency signals. Afterwards, these series are disaggregated to the monthly scale by the method of fragments. Finally, climate change modifications are introduced to alter weather variables outside of the range of historical variability. Changes in the precipitation monthly mean ranged from -30% to +30%, using increments of 15% (5 increments). The coefficient of variation of monthly precipitation changed from -30% to +30%, using increments of 30% (3 increments). A quantile mapping method altered the distribution of monthly precipitation. For temperature, shifts in the monthly mean ranged from 0ºC to 3ºC by increments of 1ºC (4 increments). An standard additive method was used for altering temperature distribution. The combination among modifications led to a total of 60 (5 x 3 x 4) climate change scenarios to consider.

This methodology is applied to the Serpis River basin, which has an area of 752.8 km2 and it is regulated by one reservoir whose main function is water supply to agriculture. A total of 434 generation runs per scenario were developed in MATLAB® in order to explore model uncertainty.

Potential evapotranspiration (ETP) time series were estimated from T by using a periodic factor previously obtained from historical data and using Fourier series method. A hydrological semi-distributed model (Temez model) was employed to transform meteorological data into hydrological discharges.

A water resource system model built using the GAMS software (General Algebraic Modeling System) was applied to evaluate the performance of the river network system and to identify critical conditions for allocation reliability. Identification of adaptation actions was based on future risk and the likelihood of future conditions that was defined by a high convergence in the GCM predictions from CMIP6.
Deep Learning for rainfall detection in a data scarce context: an application to the Sahelian Savanna
Authors: Estebanez Camarena Monica , Taormina Riccardo , van de Giesen Nick , ten Veldhuis Marie-Claire
Published: March 2022

The economy of West Africa largely relies on rain-fed agriculture, making economic growth and food security in this region highly dependent on rainfall and the knowledge of rainfall patterns. However, accurate rainfall information is currently missing due to a sparse rain gauge distribution and challenges in data transmission. Satellites could offer a solution, but existing products show poor correlation with rain gauge data. Possible reasons for this are the specific atmospheric characteristics of West Africa and rainfall processes still not fully understood.

To address this challenge, a new satellite rainfall product has been developed at TU Delft, within the Schools and Satellites (SaS) CSEOL project, funded by the European Space Agency through the IHE Institute for Water Education. SaS had the goal of producing reliable rainfall information for West Africa by combining Earth Observation, Deep Learning (DL) and Citizen Science. The focus area was the North of Ghana. The resulting product, RainRunner, performs rainfall detection at a 3-hour temporal and 0.03◦ x 0.03◦ spatial resolution, based only on TIR Meteosat Second Generation data. Two DL architectures have been designed: one using only Convolutional Neural Networks (CNN) and another one featuring a Convolutional Long Short-Term Memory layer before a CNN architecture. We have also introduced a methodology to train DL models when accurate high-density data are missing on the ground, that employs point-based instead of gridded rainfall data. RainRunner uses rain gauge data from the Trans-African Hydro-Meteorological Observation (TAHMO) as target data. A secondary validation with daily manual rain gauge data gathered by the SaS Citizen Observatory in the North of Ghana demonstrated that RainRunner has a remarkable generalization ability.

We will show that RainRunner achieves performance very close to that of Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrievals for GPM (IMERG) and outperforms the well-established Precipitation Estimation from Remotely Sensed Imagery Using an Artificial Neural Network Cloud Classification System (PERSIANN-CCS). Advantages of RainRunner are that it is fully data-driven, simpler to deploy, operating on a regional scale in quasi real-time, i.e., it can be applied as soon as GEO IR images become available.

This work illustrates the potential of DL for satellite rainfall retrieval in a data scarce context. To the best knowledge of the authors, this is the first study in which a DL-based rainfall detection model is trained locally over a region in Africa. This work could set a stage towards better rainfall information in areas of the world where it is currently missing, ultimately contributing to climate adaption worldwide.
The impact of preferential flow on Temperate Highland Peat Swamps on Sandstone soil hydrology
Authors: Wang Yusong , Shaygan Mandana , McIntyre Neil , Baumgartl Thomas
Published: March 2022

Temperate Highland Peat Swamps on Sandstone (THPSS) are ecological communities that consist of either ephemeral or permanent swamps developed in peat overlying Triassic sandstone formations in the Sydney Basin Bioregion of eastern Australia. THPSS with distinctive vegetation play an important role in biodiversity, carbon capture and storage, and the regional hydrological cycle. Some THPSS of Sydney Basin have underlying sandstone with cracks potentially formed over the past decades by human intervention. These cracks may create preferential flow paths that may accelerate the drainage process at the bottom of the swamps and may affect the soil moisture conditions of the swamps with ecological consequences. In order to understand and predict the impact of cracks on the swamps’ soil moisture and provide information to guide the management and restoration of the THPSS, 2D numerical simulations have been carried out using dual-porosity hydraulic models or explicit fast flow paths to represent the preferential flow paths. The models are calibrated and validated against historical soil moisture data and then used to evaluate the effect of cracks on soil moisture.
Controls on surface ozone pollution in the province of Nova Scotia, Canada
Authors: Mitchell Morgan , Wiacek Aldona , Wilson Alan , Ashpole Ian
Published: March 2022

Surface ozone (O3) is an air pollutant that is notoriously difficult to regulate due to its non-linear production that is dependent on emissions of precursor gases (NOx, VOCs) and meteorological conditions. As a small, but expanding, province, containing the largest urban centre in Atlantic Canada, Nova Scotia does not experience concentrations of ozone and its precursors that are characteristic of megacities. However, elevated levels of surface ozone are observed on some days and the chemistry and meteorology behind these events are not well characterized.

This study examines long-term (2000-2021) observational ozone and precursor gas data, as well as associated local emissions inventories, in order to define trends and explain changing ambient levels of ozone in the province. For example, provincial local emissions have been consistently decreasing but ozone concentrations are beginning to rise in recent years and the cause of this rise is investigated.  Although it is known that transboundary pollution is present on some days, the significance of this transported pollution to annual trends was unknown prior to this research.

We introduce and apply a spatial correlation algorithm as a novel method to diagnose transported pollution events that cause high ozone across the province and are able to estimate the proportion of transported pollution in the province over the study period. We find transported pollution to account for 45-63% of the elevated ozone days. We then identify source regions of this transported pollution as well as changes in source regions over time based on results from HYSPLIT model runs.  Vertical ozone concentrations obtained from model forecasts are examined during high ozone events in the province to determine the processes that bring pollutants to the surface from above the boundary layer.

Our results clarify the sensitivity of surface ozone levels in Nova Scotia to changing levels of precursor emissions in upstream areas like NE USA, which have seen an increase in recent years following decades-long reductions. This research has significance for policy-makers working to manage risks from air pollution in growing cities subject strong upstream pollution sources under a changing climate.
Point clouds and Hydroinformatics
Authors: Diaz Vitali , Liu Haicheng , van Oosterom Peter , Meijers Martijn , Verbree Edward , Baart Fedor , Pronk Maarten , van Lankveld Thijs
Published: March 2022

Point cloud is made up of a multitude of three-dimensional (3D) points with one or more attributes attached. Point cloud is the third data paradigm in addition to the well-established object (vector) and gridded (raster) representations, since point cloud data can be directly collected, computed, stored, and analyzed without converting to other types. Modern ways of data acquisition, including laser scanning from airborne, mobile, or static platforms, multi-beam echo-sounding, and dense image matching from photos, generate millions to trillions of 3D points with attached attributes. If the collection is carried out in different periods, one of the essential attributes is precisely time, allowing spatiotemporal analysis to be performed. Its use is widespread in some fields such as metrology and quality inspection, virtual reality, indoor/outdoor navigation, object detection, vegetation monitoring, building modeling, cultural heritage, and diverse visualization applications. There are some examples in fields related to hydroinformatics, mainly related to terrain modeling. Due to its nature of big data, over the past decades, a series of developments have been carried out in the different processing chains for the optimal use of point cloud. This research seeks to introduce the various point cloud developments from which the hydroinformatics community and research could benefit. A review of recent advances is made, mainly including the analysis and visualization of point cloud for dealing with water-related problems. Potential areas of application and development in hydroinformatics are identified. These include, for example, the topics of coastal monitoring, coastal erosion, shallow water assessment, ice sheet change analysis, sea-level rise assessment, monitoring of levels in water bodies, crop and vegetation monitoring, analysis of the effects of groundwater depletion, detail tracing of basins and channels, analysis of floods with detailed terrain models, and drought monitoring in crops and forests. The challenges to overcome and ongoing developments regarding point cloud application in hydroinformatics are also discussed.
The shallow crustal structure of the Volcàn de Colima: Evidence from ambient noise surface wave tomography
Authors: De Plaen Raphael , Mordret Aurélien , Arámbula-Mendoza Raul , Vargas-Bracamontes Dulce , Márquez-Ramírez Victor Hugo , Lecocq Thomas
Published: March 2022

The Volcán de Colima is one of the most active volcanoes in North America, but it still has a poorly constrained upper crustal structure. We used ambient seismic noise tomography to generate the highest-resolution three-dimensional shear-wave velocity model of the volcano to date. We measured group velocity dispersion curves of Rayleigh and Love waves extracted from the records of two distinct networks deployed on the Colima Volcanic Complex. Those were regionalized into 2-D velocity maps and then locally inverted using a neighborhood algorithm and an anisotropic parametrization to obtain an accurate shear-velocity model down to 4 km below sea level. 

The resulting model highlights a network of deeply rooted NE-SW low-velocity zones oriented along a local fault system. This low-velocity zone also roughly aligns with the north-south trend associated with the gradual trenchward shift of the magmatic front of the quaternary Colima Volcanic Complex. An overlapping negative radial anisotropy indicates that magma follows vertically oriented structures, such as interfingered dikes, faults, or cracks with a substantial vertical component. Our results also highlight the difference between the former active system, filled with solidified dikes and sills, and the current one, associated with a network of fluid-filled dikes.
The role of nonlinearity in the stability of the Pleistocene climate
Authors: Loskutov Evgeny , Vdovin Valey , Gavrilov Andrey , Mukhin Dmitry , Feigin Alexander
Published: March 2022

In this work the interval stability concept is used for study the stability of the Earth’s climate system during last 2.6 million years.  For the study we used an empirical model of the Earth’s climate in the Pleistocene [1] which was constructed on the basis of LR04 stack data. By means of this model, we analysed dependence of the Pleistocene climate interval stability on time, and compare the results with the behavior of local linear stability. We find that the global climate resilience to any perturbations decreases throughout the Pleistocene and the nonlinearity plays significant role in this phenomenon. The work was carried out within the framework of the Program for the Development of the Regional Scientifc and Educational Mathematical Center "Mathematics of Future Technologies", project #075-02-2020-1483/1.

1. Mukhin, D., Gavrilov, A., Loskutov, E. et al. Bayesian Data Analysis for Revealing Causes of the Middle Pleistocene Transition. Sci Rep 9, 7328 (2019). https://doi.org/10.1038/s41598-019-43867-3
Accounting for spatiotemporal complexities of drought in water accounting to inform integrated drought management
Authors: Kchouk Sarra , Ribeiro Neto Germano , Cavalcante Louise , Melsen Lieke , Walker David , Sonsol Gondim Rubens , van Oel Pieter
Published: March 2022

The different existing frameworks of Water Accounting (WA) techniques have proven to be useful tools for managing water in situations of water scarcity. The indices derived from WA procedures typically focus at informing decisions related to two different targets. A first group focuses on estimating water availability in different parts of a river basin. A second group focuses on the effects of human activities (interventions) on the water balance. Both are precious tools for decision making when the water is even scarcer, like in drought situations. However, their frameworks remain limited for an application to drought and drought impacts as it eludes many specificities proper to droughts. The aim of our study is to explore how WA techniques and indices can thus be adapted for integrated drought management. We based our approach on the water-balance data from the Banabuiú River Basin located in the semi-arid and drought-prone Northeast of Brazil. This area is the place of varied agricultural activities, rainfed or irrigated from a dense network of reservoirs. Droughts, from flash droughts to sometimes pluriannual, can affect the water balance of those reservoirs and the basin, and pose a challenge to meet all the agricultural needs. We direct our results towards the investigation of spatiotemporal scale issues. Indeed, water balance assessments often do not consider spatial variations in a river basin area and only report average annual situations. However, the duration of droughts or their impacts can extend beyond this reference period until sometimes becoming persistent to the system. The same applies for spatial-scale issues. Actions and processes happening at different physical scales and levels, inside and outside the basin, can modify the water balance. By addressing these spatiotemporal complexities, we aim to develop indices that will account for the human activities and enable to better inform decisions for integrated drought management.
Relative continent/mid-ocean ridge elevation: a reference case for isostasy in geodynamics
Authors: Theunissen Thomas , Huismans Ritske S. , Lu Gang , Riel Nicolas
Published: March 2022

The choice of crustal and mantle densities in numerical geodynamic models is usually based on convention. The isostatic component of the topography is, however, in most if not all cases not calibrated to fit observations resulting in not very well constrained elevations. The density distribution on Earth is not easy to constrain because it involves multiple variables (temperature, pressure, composition, and deformation). We provide a review and global analysis of the topography of the Earth showing that elevation of stable continents and active mid-ocean ridges far from hotspots on average is +400 m and -2750 m respectively. We show that density values for the crust and mantle, commonly used for isostatic modeling result in highly inaccurate prediction of topography. We use thermodynamic calculations to constrain the density distribution of the continental lithospheric mantle, sub-lithospheric mantle, the mid-ocean ridge mantle, and review data on crustal density. We couple the thermo-dynamic consistent density calculations with 2-D forward geodynamic modelling including melt prediction and calibrate crustal and mantle densities that match the observed elevation difference. Our results can be used as a reference case for geodynamic modeling that accurately fits the relative elevation between continents and mid-ocean ridges consistent with geophysical observations and thermodynamic calculations. 
Extremely fresh biomass burning aerosol observed in Potenza by multiwavelength Raman Lidar MUSA and the CIMEL 318 sun-photometer.
Authors: De Rosa Benedetto , Mona Lucia , Amodeo Aldo , Papagiannopolos Nikos , Summa Donato , Mytilinaios Michalis , Veselovskii Igor
Published: March 2022

On 14 August 2021 a forest fire started at 16:00 U.T.C. were observed by the Lidar Raman MUSA and the CIMEL 318 sun-photometer of CNR IMAA of Potenza located at 1 km from the fire. Due to proximity to only 1 km this measurements represents an important case of study. Measurements carried out by the Lidar MUSA  reveal the presence of a smoke layer below 2.7 km  from 22:27 to 23:19 the. The optical parameters derived are backscattering at 355, 532 and 1064 nm, extinction at 355 and 532 nm, Lidar ratios at 355 and 532 nm wavelengths, Ångström exponents,  and particle and volume depolarization at 532 nm. Results indicate a low absorption  an high scattering of fire particles.

Lidar ratio are 40 sr at 355 and 38 at 532, particle depolarization is 0.025 and Ångström exponents are approx 1.5 for all wavelengths.

To derive microphysical properties are used The inversion of 3 β + 2 α. The values of surface concentration is 410 µm2 cm-3, the volume concentration is 21 µm3 cm-3and numeric density is  2300 cm-3. The size distribution is  bi-modal distribution with a peak at 0.13 µm. The effective radius is 0.15 µm. The single scattering albedo at 355, 532 and 1064 are 0.96, the real and the imaginary part of the refractive index are respectively 1.58 and 0.006.

Therefore, particles are small, spherical and weakly absorbing probably due to a minimum contribution of black carbon

The CIMEL 318 sun photometer measurements at 5:34 U.T.C confirm the results of MUSA.
Assessing annual and seasonal changes in the free-water reservoir surface state and turbidity conditions: implications for dam management in the Guadalquivir River Basin (Spain)
Authors: Contreras Arribas Eva , Pimentel Rafael , Aguilar Cristina , Aparicio Javier , Polo María José
Published: March 2022

In Mediterranean areas the high seasonal and annual variability in precipitation produces large changes in the reservoir water availability. However, the state of these water bodies is not only subjected to the weather and the natural hydrology of this kind of system, but is often modified on one hand by the water demands and on the other hand, by the land uses upstream which have serious effects on the water quality of the river contributions. Remote sensing and GIS methods are currently emerging as an alternative to traditional methods like field survey (usually laborious, time consuming and expensive) to analyse the evolution of the state of these water bodies in terms of the free-water reservoir surface.

In this paper, the Guadalquivir River Basin (southwest Spain), where the gradual and intense development of large irrigated areas (which has increased in the last 50 years by more than 50%) leads to an increase in the storage capacity in the basin (which doubles during the next 40 years), was taken as a research object. The Global Surface Water (GSWE) online machine, combined with historical, hydrological, meteorological and water quality data, were used to spatially quantify free-water reservoir surface during the period 1984-2020. This allowed us, through a water balance approach on a monthly basis, the estimation of water inputs and outputs to analyse the hydrological changes in terms of seasonality, but also considering the effects of the dam operations and the changes in water quality in terms of sediments loads in those reservoirs where turbidity data series are available. 

The results show the increase of the free-water reservoir surface along the study period, which is consistent with the dramatic decrease of the contribution of the water flowing into the last receiver of the network of reservoirs (Alcalá del Río dam). This also implies the storage of associated substances such as sediments (mainly from the extensive olive groves areas located upstream) that produce the filling of the reservoirs, and turbidity episodes in flood events, which was verified with field measurements in the main control points of the basin.

This work has been funded by the project Integrated Management for the control of water inputs and sediments in reservoir systems in the Guadalquivir basin, with the economic collaboration of the European Funding for Rural Development (FEDER) and the Office for Economy, Knowledge, Enterprises and University of the Andalusian Regional Government.
Short-term forecasting of renewable production trajectories at high-temporal resolution
Authors: Camal Simon , Van Der Meer Dennis , Kariniotakis George
Published: March 2022

High temporal resolution intra-day and day-ahead renewable energy source (RES) power forecasts are important to maximize the value of RES systems because they give stakeholders the opportunity to participate in both the energy and ancillary services markets. In the realm of electricity markets, day-ahead electricity markets often require bids at hourly temporal resolution. However, the requirements for temporal resolution on intra-day markets are more demanding and may require a temporal resolution of 5 minutes in the near future.

Moreover, high resolution forecasts offer the possibility to employ advanced control strategies to mitigate severe frequency fluctuations in, for instance, island grids. More specifically, battery integration can improve power system management in isolated grids with high RES power penetration. However, battery control requires high temporal resolution forecasts.

Since the temporal dependence structure between time steps is highly relevant in control problems, there is a need to efficiently generate trajectory forecasts that can be used in stochastic optimisation problems. This study proposes an efficient method to generate trajectory forecasts of RES power production that is based on pattern matching. Consequently, we do not need to forecast all forecast horizons separately and estimate a covariance matrix that represents the dependence structure between the forecast horizons. To compare our method against the state-of-the-art, we use quantile regression forests in combination with a Gaussian copula and show that our method performs similar in terms of relevant scores but is approximately 98% faster and simplifies the modelling chain considerably.

The proposed method is evaluated on real data from operating renewable sites in an isolated power system. Considering its fast computation and its applicability to diverse situations (different energy sources, individual sites or aggregated production), the method has the potential to be integrated into the decision-making process of forecasting end-users such as operators of power systems under high renewable penetration.
Local Emission of Whistler Waves by Landau Resonance As a Signature of a Converging Magnetic Hole
Authors: Jiang Wence , Verscharen Daniel , Li Hui , Wang Chi , Klein Kristopher
Published: March 2022

Magnetic holes are plasma structures that trap a large number of particles in a magnetic field that is weaker than its surroundings. The unprecedented high time-resolution in-situ observations by NASA's Magnetospheric Multi-Scale (MMS) mission enable us to study the particle dynamics in the Earth's magnetosheath plasma in great detail. For the first time, we reveal the local generation of whistler waves by the Landau-resonant instability of electron beams as a response to the large-scale evolution of a magnetic hole. As the magnetic hole converges, we find a pair of counter-streaming electron beams are formed near the hole's center as a consequence of the combined action of betatron cooling and Fermi acceleration. The beams trigger the generation of slightly oblique whistler waves near the hole center, which is supported by a remarkable agreement between observations and our ALPS model predictions. Our findings show that kinetic effects and wave-particle interactions are fundamental to the dynamics and the evolution of magnetic holes as an important type of coherent structures in collisionless plasmas.
A statistical framework to assess time trend and predict near-future climatic conditions
Authors: Faybishenko Boris , Arora Bhavna , Dwivedi Dipankar , Brodie Eoin
Published: March 2022

A statistical framework to assess the long-term climatic water balance changes includes the following phases of the data analysis and predictions: (1) Preparation of daily, monthly, and yearly averaged time series of meteorological parameters (temperature, relative humidity, precipitation, wind speed, etc.), and an evaluation of the temporal structural breakpoints (breakthroughs) of meteorological parameters trends, (2) calculations of potential evapotranspiration, aridity index, actual evapotranspiration (ET), Standard Precipitation Index (SPI), and Standard Precipitation-Evapotranspiration Index (SPEI), as well as an evaluation of breakthroughs of their trends, (3) climatic zonation based on the application of the hierarchical k-means and Principal Component Analysis (PCA) clustering of temporal trends of ET and SPEI for the periods before and after the breakthroughs, and (4) simple forecasting hierarchical time series for different forecasting situations.

The statistical framework was applied to 17 locations at the East River watershed for the period from 1966 to 2020. Structural changes of time trends of measured and calculated water balance parameters are used to determine the time of abrupt climatic changes and breakthroughs. Calculations of the evapotranspiration are conducted using the Budyko model, with the potential/reference evapotranspiration (ETo) calculated using the Penman-Monteith (PM) equation. The results of calculations of ETo based on the PM model were compared to the ETo calculated using the Thornthwaite and Hargreaves equations. The results of the hierarchical clustering using ET and SPEI are illustrated using the tree dendrograms and the PCA plots of clusters of the studied sites for the periods of before and after the breakthroughs. A significant shift in the cluster arrangements for the time periods before and after the temporal structural breakpoints indicate that zonation patterns are driven by dynamic climatic processes, which are variable through time, and the watershed zonation requires periodic re-evaluation. Examples of time series forecasting are also shown.
Phenocams as a tool to investigate leaf economic spectrum relations in Seasonally Dry Tropical Forests
Authors: Morellato Patrícia , Neves Nattalia , Alberton Bruna , Moura Magna , Lima Romualdo , Souza Eduardo , Souza Rodolfo , Silva José Raliuson , Miatto Raquel , Domingues Tomas , Cunha John , Ramos Desiree
Published: March 2022

Leaf construction can be costly to plants with a short leaf lifespan (LLS), with a necessity to pay back the investment in leaf deployment. Costs of leaf construction are often measured as leaf mass per area (LMA) and the deciduousness strategies (deciduous, semideciduous or evergreen) used as proxy to LLS (evergreen species having longest leaf duration compared to semideciduous and deciduous species). According to the leaf economic spectrum theory, a positive correlation between LMA and LLS is expected, with evergreen species having higher LMA than deciduous species. Nonetheless, aridity constraints increase leaf maintenance costs in plants, and the deciduous strategy turns to be the most common leaf exchange behavior in Seasonally Dry Tropical Forests (SDTF). In this study we are testing if the relation of LMA and LLS is influenced by aridity in SDTF, using the length of growing season (LOS) as a proxy of overall response for drought. We expect that LMA: LLS relationship will become stronger towards driest sites. The caatinga vegetation is the largest SDTF in the New World, covering an area of ca. 850,000 km2 located in North-eastern Brazil. Although the region is characterized by having low amount of rainfall (<1100 mm per year), there is a gradient of aridity that affects plants living across these areas. We applied the near-surface remote method trough the usage of phenocams to simultaneously monitor leaf phenology of 27 tree species from four areas of Caatinga, in a gradient of aridity ranging from 387 mm to 800 mm total annual rainfall. For these species, we used the green chromatic coordinate (Gcc) time series to calculate the phenological transition dates of Start (SOS) and End (EOS) and the Length (LOS) of Growing Season, during two to four growing seasons, from 2017 to 2021. LOS presented high variability among species, ranging from 143 days for Manihot pseudoglaziovii and 314 days for Aspidosperma pyrifolium. In general, LOS tend to be shorter for species towards driest sites and analyes of the relation between LMA and LLS are suggesting trade-offs important to understand the acquisitive strategies of plants from semi-arid vegetation with implications for carbon fluxes.

Supported by FAPESP (#2019/11835-2); FAPESP-NERC (FAPESP #2015/50488-5; #2017/17380-1), by CNPq and FACEPE (Caatinga-FLUX, #483223/2011-5 and Caatinga-FLUX Fase 2, #0062-1.07/15); UNESP CAPES-PrInt Program (grant #88887.310463/2018-00; schoolarship ##88887.512218/2020-00) and CNPq productitivity fellowship (#428055/2018-4).
Towards Understanding Evapotranspiration Shifts Under a Drying Climate
Authors: Gardiya Weligamage Hansini , Fowler Keirnan , Peterson Tim , Saft Margarita , Ryu Dongryeol , Peel Murray
Published: March 2022

Around 60 percent of terrestrial precipitation on the global average transforms into evapotranspiration. However, reliable estimation of actual evapotranspiration (AET) is challenging as it depends on multiple climatic and biophysical factors. Despite developments such as remotely sensed AET products, AET responses to prolonged drought is still poorly understood. Therefore, this study focuses on understanding long-term changes and variability of AET prior to and during the Millennium Drought in Victoria, Australia. We also investigate the capability of commonly used rainfall-runoff models to simulate AET under multiyear droughts. Therefore, we employ simple sensitivity analysis to examine four different water balance approaches between pre-drought and drought periods in six different study catchments in Victoria. The first water balance approach is the simplest long-term water balance approach, partitioning long-term precipitation into evapotranspiration and runoff. The second water balance approach adopts a long-term change in storage to the water balance during the Millennium Drought by employing regional-scale change in GRACE estimates derived from Fowler et al. (2020). The third and fourth water balances are based on simulations from SIMHYD and SACRAMENTO. Surprisingly, the adoption of long-term change in storage during the Millennium Drought indicates that the annual rates of pre-drought AET were largely maintained throughout the drought; i.e. the rate was relatively constant with time. This suggests that AET gets priority over streamflow following a drying shift in precipitation partitioning; resulting in a relatively constant AET under multiyear drought. In contrast, the rainfall-runoff models underestimated AET during the drought compared to both water balance approaches. These results broadly acknowledge the need for model improvements to provide more realistic AET estimates under future drying climates and provide a new perspective on recent hydrological phenomena such as changing rainfall-runoff relationships in these regions. Furthermore, this sensitivity analysis was augmented and confirmed by a regional-scale water balance approach.

Keywords: Catchment water balance, Evapotranspiration, Change in storage, Rainfall-runoff models

References: Fowler, K., Knoben, W., Peel, M., Peterson, T., Ryu, D., Saft, M., Seo, K.W., Western, A., 2020. Many Commonly Used Rainfall-Runoff Models Lack Long, Slow Dynamics: Implications for Runoff Projections. Water Resour. Res. 56. https://doi.org/10.1029/2019WR025286

 
Characterisation of discolouration plumes resulting from submarine volcanism using remote sensing techniques between 2000 and 2018
Authors: Domingues Joana R. , Mantas Vasco , Pereira Alcides
Published: March 2022

There’s still a poor understanding of how submarine volcanism works, although the majority of Earth’s volcanic activity happen in submarine context, forming new crust and ejection large amounts of material into the ocean.

This type of eruption has associated risks such as tsunamis and problems with shipping and air traffic, and is a source of natural pollution - gases such as sulphur and particulates are released into the atmosphere - hence the need for monitoring. Also, the study of submarine volcanic products will help understand in more detail how these volcanic processes evolve. Due to the remote location of submarine volcanoes, the use of remote sensing and earth observation techniques can be helpful in the monitoring process in order to mitigate the consequences of volcanic activity.

To answer this problem, a database of pre-registered submarine volcanic eruptions between 2000 and 2018 was created, with results stating 60 eruptions referring to 31 different volcanoes. A total of 450 satellite images were detected through observations of discoloration plumes associated with submarine events, and 82 of these images were subsequently selected for extraction of spectral signature, through what were considered to be the most representative images for the eruption in question, in order to proceed to the extraction of spectral signatures.

The spectral signature of the 263 sample points has similar characteristics within the different types of discoloration plumes (green coloration, brown coloration, and associated with pumice rafts) and can therefore be classified into several classes.

It can be concluded that the detection and differentiation of discoloration plumes associated with submarine volcanic events using remote sensing data can be accomplished effectively, confirming why remote sensing is an efficient and affordable technique for the regular detection, monitoring, and study of submarine volcanic eruptions in near-real time.
Importance of surface pesticide residues in the quantitative mitigation of pesticides with vegetative filter strips: VFSMOD development and analysis
Authors: Muñoz-Carpena Rafael , Reichenberger Stefan , Sur Robin
Published: March 2022

Regulatory exposure assessments (EA) are a cornerstone in the registration of new or existing agrochemicals in the EU, USA and many other countries to preserve ecosystem health and water quality. VFSMOD (Muñoz-Carpena et al., 1999; 2004) is a numerical, storm-based design model that quantifies the performance of vegetative filter strips- VFS (grass buffers) to mitigate pesticide runoff into surface waters. The model has been coupled into current USA and EU long-term (20 to 30 yr), higher-tier regulatory pesticide EAs to estimate potential pesticide load reductions by the VFS before entering the aquatic environment. A new comprehensive modeling component has been added to VFSMOD to quantify the fate of pesticides residue on the VFS between events in the context of long-term simulations. The aim of this study is to present the verification of the assumptions and accuracy of the new pesticide residue component within VFSMOD in the context of continuous simulations by exploring a wide range of conditions (Koc, half-life, remobilization processes) of importance to improve current understanding of quantitative mitigation of pesticides in the regulatory environment.  The results show the complex interaction in the VFS amongst surface pesticide runoff, sedimentation, infiltration and leaching, degradation, evapotranspiration and soil moisture change, and mixing layer remobilization that produces emergent behavior in the amount of pesticide residue potentially remobilized in the next event in the series.