bluuebunny/crossref_metadata_2025 huggingface dataset:
Merged Sea Ice Motion from Pattern-Matching and Feature-Tracking Vectors
Authors: Wang Xue , Fang Yan , Chen Zhuoqi , Hui Fengming , Cheng Xiao
Published: February 2023

Under the background of global warming, sea ice changes rapidly. Sea ice drift is an important indicator for sea ice flux, atmospheric and ocean circulation, and ship navigation. Considering that pattern-matching vectors and feature-tracking vectors retrieved from remotely sensed data provide complementary information, a novel sea ice motion estimation method was proposed by merging these two types of vectors. In this study, the DTU sea ice product was used as pattern-matching displacements, whereas feature-tracking vectors were derived from Sentinel-1 SAR images. The proposed method of sea ice motion retrieval is summarized as follows. Initial feature-tracking vector fields were first derived from Sentinel-1 SAR image pairs. Then, mismatched feature-tracking vectors were discarded based on a bad matches filtering step. Finally, the filtered feature-tracking vectors were merged with pattern-matching vectors based on Co-Kriging algorithm. The proposed method was evaluated by comparing merged vectors with buoy displacements, DTU sea ice drift product and filtered feature-tracking vectors. The results showed that the proposed method can retrieve accurate, high resolution and evenly distributed sea ice motions.
Observed Drag Coefficient Asymmetry in a Tropical Cyclone
Authors: Chen Sheng
Published: February 2023

The behavior of drag coefficient (CD) in two different motion-relative quadrants of Typhoon Mujigae (2015) is investigated through the flux observations conducted on a fixed platform over the coastal region in the northern South China Sea. Observations reveal that the variation of CD is closely related to the location relative to the tropical cyclone (TC) center. The CD  presents an enhancement when the typhoon is away from the observational site. The spatial distribution of CD on the periphery of a TC is asymmetric, and the CD in the right rear quadrant is much larger than that in the right front quadrant for the same wind speed range. This asymmetric distribution of CD can be explained by the differences in wave properties between the two quadrants. CD is smaller in cross-swell conditions than that in the along-wind wave conditions. Observations also confirm that CD tends to level off and even attenuate with the increase of wind speed, and the critical wind speed for CD saturation over the coastal region (~20 m/s) is much lower than that over the open ocean (~30 m/s). The observational spatial distribution of CD in TC quadrants not only improves our understanding on the air-sea momentum flux but also provides a potential solution for the long-standing scientific bottleneck on TC intensity forecasting.
Effective Methods for Increasing Model Background Error in the Ensemble Kalman Filtering in Aerosol Data Assimilation
Authors: Lee Seunghee , Lee Myong-In
Published: February 2023

The Ensemble Kalman Filter (EnKF) has been employed for updating the initial condition, and promising results have been reported. Unlike the variational assimilation method, the advantages of EnKF are flow-dependent background error covariance which is important in a fast-developing air quality system. However, assimilation of air quality observations often suffers from insufficient model background error due to a small ensemble spread when applying EnKF methods. This study suggests methods for effectively increasing model background error covariance (BEC) by perturbing prognostic variables and employing multiple physics parameterizations in the atmospheric chemical transport model.This study developed an aerosol data assimilation system with the WRF-Chem model and EnKF approach. In spite of considering flow-dependent BEC, the baseline run analysis exhibits poor performance, primarily due to the small ensemble spread. This study conducted new two effective methods for increasing ensemble spread: one considering the uncertainty of model physics and the other considering the uncertainty in the prognostic variables. Both methods improved the quality of surface PM analysis substantially, compared with the baseline run. And the DA_all experiment which incorporates both uncertainty in model physics and prognostic variables, demonstrates the best performance. Physical perturbation and multiplicative perturbation have a non-linear relationship. The forecast skill is also improved. With the substantial increase of BEC, the revised EnKF system has significantly improved the PM2.5 forecast skills.
UAV based High-resolution DEM for 1D Hydrodynamic modeling - A case of Flood Assessment of Sabarmati River, Gujarat, India.
Authors: Rana Mrunalini , Patel Dhruvesh , Vakhria Vinay
Published: February 2023

The most frequent catastrophic natural disaster is thought to be flooding. Due to climatic uncertainty, variable rainfall, a lack of river carrying capacity, illegal settlement along river banks, and dense population, flood magnitudes and vulnerabilities increased in the past ten years globally. There are 11,356 records of hydrological and meteorological occurrences from 1900 to 2020, according to the United Office of Disasters Risk Reduction's (UNDRR) International Database, with 8.6 million fatalities and 2600 million US dollars in economic damage. In the current climate, floods cannot be prevented, but their damages can be reduced with a thorough flood assessment. The identification of the flood inundation area, flood arrival time, and flow velocity in flood-prone areas can be accomplished using a variety of hydrodynamic models; however, the limited resolution of DEM (Digital Elevation Model) makes it impossible to determine the actual flooding state. To remedy this shortcoming, we developed a high-resolution DEM from UAV (Unnamed Aerial Vehicle) for this case study, which involves the well-known Sabarmati of Gujarat State, one of India's principal west-flowing rivers with a length of 371 kilometres, which was impacted by a flood in 2006. The 4RTK (Real-Time Kinematic) Phantom, a UAV survey, was used to acquire aerial pictures of a portion of the river Sabarmati. The image was then processed with 75% mosaicking using the Pix4D mapper tool for better accuracy. Later, with the aid of Global Mapper, various DEMs with grid sizes ranging from 0.5 m x 0.5 m to 10 m x 10 m are created with near precision of 3 cm spatial resolution. These generated DEMs are then used as input for the hydrodynamic simulation using Civil Geo-HECRAS. Hence, the hydrological data required for the hydrodynamic model has been assumed from past floods and the geometrical data for the study is derived from the UAV survey with four Manning's roughness coefficients—0.025, 0.030, 0.033, and 0.035 have been assumed for this case study considering the local conditions. The analysis of Manning's roughness value's influence reveals that when roughness increases, discharge reduces, and velocity and Froude's number decrease.Keywords: Flood, DEM-Digital Elevation Model, UAV-Unnamed Aerial Vehicle, Hydrodynamic modeling, Manning’s roughness
Assessment of the impact of 2022 extreme climate conditions on European forests
Authors: Gharun Mana , Shekhar Ankit , Buchmann Nina
Published: February 2023

The frequency and intensity of extreme climate events is increasing globally. In 2022, Europe experienced extreme heatwaves and prolonged droughts followed by clear indications of a devastating effect across many forest sites. Instrumental measurements show that 2022 contained some of the most extreme heat and dryness conditions ever recorded across Europe, particularly during the forest growing season. Such extreme conditions that follow a number of consecutive extreme years (e.g., 2019, 2018, 2015) with short intervals in between are becoming the new norm and the response of forests in terms of canopy condition, reduced productivity, and potential feedback to the climate is not clear. It is yet not clear how the negative and positive impacts of the most recent extreme temperature and dryness conditions differ from the impact of previous extreme conditions. This study aims to: 1) compare the severity of extreme conditions in 2022 (in terms of heat and dryness) with the preceding extreme years (i.e., 2003, 2015, 2018, 2019) and 2) to quantify forest canopy response (in terms of vegetation browning) and variables responsible for the feedback from forests to the climate (transpiration and solar induced fluorescence as a proxy for photosynthetic activity) across the main classes of forest types in Europe.For this assessment we use spatially explicit daily modelled top soil water content (0-7 cm), air temperature, and potential transpiration using the ERA5-Land spatial dataset (0.1° × 0.1°) between 1970 to 2022. Reference period for anomaly assessment is set to the 1970-2000 period and MODIS land cover type product is used to aggregate anomalies across forest types. SIF anomalies are extracted using an OCO-2 satellite based SIF dataset, and ground-based ecophysiological measurements collected across a few sites during heatwave and drought events in 2022 are compiled and used to link leaf-level processes to observed canopy response.Our initial assessment shows that conditions in July 2018 had the largest negative impact on transpiration of European forests, but in June 2022 we observed a far larger spatial extent of positive temperature anomalies across Europe. We compare the impact of 2022 extreme conditions with that of previous extreme years, and discuss our results in the light of underlying ecophysiological mechanisms that control the response and the feedback to climate across different forest types and climate regions.
Impact of planetary boundary layer in dense haze /smog event over South Asian Mega City; Lahore Pakistan
Authors: Shahid Imran , Shahzad Muhammad Imran
Published: February 2023

Air quality over North Eastern region of Pakistan is rapidly worsening over the years, especially over Lahore and adjacent areas reporting world record levels of pollutant concentrations including highest particulate matter (PM) levels during the autumn and winter seasons. Meteorological parameter plays an important role in extreme pollution episodes. In order to study the impact of meteorological condition such as planetary boundary layer (PBL) an intensive PBL measurements were conducted over Lahore from October 2019 to March 2021 using LUFT CHM15K Ceilometer LIDAR. The impacts of PBL structure on heavy haze pollution and the relationship with PM2.5 concentrations were studied. The boundary layer height drops clearly during winter period (December 2019 and 2020, usually lower than 500m. The PM2.5 concentrations increases when the PBL drops and vice versa. Key finding in this study is that the dynamics of the Planetary Boundary Layer (PBL) change significantly during heavily polluted days during intense autumn / winter smog periods, which indicates the role of aerosols in influencing meteorological conditions, besides having other impacts in the region of study.   
Large-eddy simulation of a two-layer boundary-layer cloud system from the Arctic Ocean 2018 expedition
Authors: Ekman Annica M. L. , Bulatovic Ines , Savre Julien , Tjernström Michael , Leck Caroline
Published: February 2023

The most common type of cloud in the Arctic latitudes is mixed-phase stratocumulus. These clouds play a critical role in the Arctic energy budget. Previous observations in the central (north of 80° N) Arctic have shown a high occurrence of prolonged periods of a shallow, single-layer mixed-phase stratocumulus at the top of the boundary layer (altitudes ~300-400m). However, recent observations from the summer of 2018 showed a prevalence of a two-layer boundary-layer cloud system. Here we use large-eddy simulation to examine the maintenance of one of the cloud systems observed in 2018 as well as the sensitivity of the cloud layers to different micro- and macro-scale parameters. We find that the model generally reproduces the observed thermodynamic structure well, with two near-neutrally stratified layers in the boundary layer caused by a low cloud (located within the first few hundred meters) capped by a lower temperature inversion, and an upper cloud layer (based around one kilometer or slightly higher) capped by the main temperature inversion of the boundary layer. The investigated cloud structure is persistent unless there are low aerosol number concentrations (<5 cm-3), which cause the upper cloud layer to dissipate, or high large-scale wind speeds (>8.5 m s-1), which erode the lower inversion and the related cloud layer. These types of changes in cloud structure led to a substantial reduction of the net longwave radiation at the surface due to a lower emissivity or higher altitude of the remaining cloud layer. The findings highlight the importance of better understanding and representing aerosol sources and sinks over the central Arctic Ocean. Furthermore, they underline the significance of meteorological parameters, such as the large-scale wind speed, for maintaining the two-layer boundary-layer cloud structure encountered in the lower atmosphere of the central Arctic.
Gradient boosting for socio-economic wildfire risk assessment
Authors: Steinmann Carmen B. , Koh Jonathan , Lüthi Samuel , Gübeli Samuel , Guillod Benoît P. , Bresch David N.
Published: February 2023

Wildfires are devastating events destroying large parts of physical assets exposed to them in many regions of the world. Therefore, a high-resolution hazard model is needed to accurately assess socio-economic impacts caused by wildfires. Moreover, a probabilistic representation of the hazard covering the range and likelihood of possible wildfire events under certain conditions allows for a more comprehensive risk assessment. This is crucial for many applications, among others the prioritization of adaptation measures and the pricing of insurance.We determine burning probabilities based on MODIS hotspots and a set of predictors (weather variables, geography, land use) by using a country-specific machine learning model based on the efficient tree boosting system XGBoost. Subsequently, stochastic wildfire events are generated on the basis of these burning probabilities.Lastly, the open-source climate risk assessment platform CLIMADA is used to compute socio-economic impacts as the combination of the newly developed hazard, an exposure and a vulnerability. The used exposure LitPop spatially distributes macroeconomic indicators (e.g. produced capital) as a function of night light intensity and population density. The vulnerability is represented by an impact function that was calibrated on historic fire damage data. Combining the stochastic impacts with their respective probabilities results in a globally consistent country-specific model of wildfire risk to physical assets.
Training program for PhD students in the field of heliophysics
Authors: Kilpua Emilia ,   SWATNet team
Published: February 2023

Space Weather Awareness Training Network (SWATNet; https://swatnet.eu) is a Marie Skłodowska-Curie Innovative Training Network (INT) in the field of heliosphysics that runs between 2021 - 2025. The project aims scientifically at breakthroughs in our physical understanding of key agents of Space Weather at Earth. The project educates twelve Early Career Researchers (ESRs) with joint or double degrees. The ESRs achieve a versatile scientific and transferrable skills through the ambitious SWATNet training program that comprises of three schools and seven workshops during the project. This presentation summarises the format of these training activities (held both online and face-to-face), their key educational methods and strategies as well as collecting the feedback. One of the key aspects we have strived in our training is to encourage ESRs to critical thinking and asking questions. SWATNet is funded by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 955620.
The impact of river plumes on the sea-level variability
Authors: Keyzer Lennart , Pietrzak Julie , Snellen Mirjam , Katsman Caroline , Zijl Firmijn , Afrasteh Yosra , Guarneri Henrique , Verlaan Martin , Klees Roland , Slobbe Cornelis
Published: February 2023

In the face of climate change and changing sea levels, it is important to understand the different drivers of sea-level variability. Tides and atmospheric forcing are the major drivers of sea-level variability, while steric contributions are often neglected in shallow coastal and shelf seas. Here, we investigate the impact of the Rhine River plume on the sea surface height in the North Sea.
Because the river plume is modulated by the tides, steric changes coincide with tidal signals. Therefore, they are hard to observe directly using tide gauge measurements or satellite altimetry. Here, we use a 3D hydrodynamic model, allowing us to quantify the steric contribution. We find steric contributions up to 15 cm in the estuary, 5 cm in the near-field plume and 1 cm in the far-field plume.
The exact height will depend on the river discharge, wind conditions and the tides, which strongly affect the river plume, and thus also the sea surface height. During the summer of 2022, the discharge of the Rhine River was historically low. We investigate the consequences for the river plume, and its impact on the sea surface height. We find that river plumes can induce significant steric changes in sea-surface height, however these are often neglected. Climate change will affect the different drivers of sea level variability in our coastal zones and shelf seas, including river discharges. Understanding their impact is therefore crucial to assess changing sea levels.
Modelling of biogeochemical parameters in the Baltic Sea with a NEMO-ERGOM model system and ensemble based data assimilation
Authors: Morrison Helen E. , Spruch Lena , Düsterhöft-Wriggers Wibke , Lindenthal Anja , Nerger Lars
Published: February 2023

The current reanalysis and forecasting products provided by the Baltic Monitoring and Forecasting Centre (BAL-MFC) are based on an online one-way coupled NEMO-ERGOM system. Specifically, they use the 3D ocean-ice model NEMO v4.0 in combination with the sea ice and thermodynamic model SI3 and the biogeochemical model ERGOM in a version from 2015 developed at the Leibniz Institute for Baltic Sea Research (IOW). This contribution will highlight the status of the current system with respect to biogeochemical parameter modelling in the Baltic Sea. Furthermore, the advancements towards including biogeochemical ensemble based data assimilation into the products will be presented. For this, the Parallel Data Assimilation Framework PDAF v2.0 is used. The recent introduction of PDAF-OMI, the Observation Module Infrastructure, allows for a modular implementation of different observation types, thus ensuring that the data assimilation of both the physical parameters (satellite sea-surface temperature; temperature and salinity profiles) and the biogeochemical parameters (currently oxygen and nutrients profiles) can be done using the same code.Validation results of the NEMO-ERGOM-PDAF system with profile assimilation of dissolved oxygen, nitrate and phosphate will be presented. The validation focusses on the influence of the biogeochemical data assimilation on the oxygen and nutrient conditions in the deep basins of the Baltic Sea, which are typically anoxic. 
Mapping Elevation and Elevation Changes in the German Coastal Zone
Authors: Schröder Ludwig , Liebsch Gunter , Bauer Tobias , Rüsch Lukas , Gräwe Ulf
Published: February 2023

The Federal Agency for Cartography and Geodesy (BKG) is the central service provider of topographic data, cartography, and geodetic reference systems for the German government. As the marine sector is constantly gaining importance, e.g. for the transport of goods or energy security, precise geodetic information become more and more important. In this context, BKG uses satellite altimetry to map and monitor the sea surface heights of the North and the Baltic Sea. In order to calibrate and validate the satellite observations, we performed measurements on the offshore research platform FINO2 as well as on two shipborne field campaigns during 2021 and 2022. In order to improve the spatial and temporal resolution of the altimetry data, we combine the altimetry observations with the output of a regional ocean model from Leibniz Institute for Baltic Sea Research (IOW). Here we present the first results of these activities and our strategy of combining satellite altimetry with different other observation techniques of sea level changes and land uplift to map and monitor elevation and elevation changes in the German coastal zone.
Analyzing clogging and scaling processes in carbonate and siliciclastic ATES systems based on column and batch experiments
Authors: Arab Alireza , Gabler Leonie , Binder Martin , Engelmann Christian , Viehweger Christine , Scheytt Traugott
Published: February 2023

Aquifer thermal energy storage (ATES) is one of the main types of geo-storage concepts aimed at an efficient energy supply and for achieving a low-carbon energy balance. In ATES, thermal energy is stored underground for later use; for instance, by intentionally injecting warm water - heated up by excess heat energy of industry and commerce - into the aquifer, and recovering it later for heating purposes, e.g., during the winter period. However, a significant number of ATES projects suffer from operational and maintenance issues or failures. Mineral precipitation (scaling) and flocculation, or microbial growth are major risks for ATES. By reducing the permeability in reservoirs, these processes threaten medium- to long-term operational reliability.  The BMBF-funded research project ‘UnClog-ATES’ comprehensively investigates clogging and scaling in two typical reservoirs for ATES systems (siliciclastic sediments and carbonate-bearing sediments) which are widely distributed and exhibit different reactivity with respect to temperature and hydrochemical changes. Laboratory-scale flow-through column experiments as well as batch reactor experiments will be performed to simulate transport under representative ATES conditions (pressure, temperature, hydraulics, and chemical composition). Additionally, countermeasures (e.g., scaling inhibitors, acids, or CO2) will be investigated to maximize the potential of ATES in the future. Finally, based on numerical reactive solute transport models, a catalog of criteria for users and decision-makers will be created to facilitate an initial site assessment in order to minimize the operational risk of ATES at this level.
Spatio-temporal analysis of storm surge in the Korean Peninsula
Authors: Yang Jung-A
Published: February 2023

The Korean Peninsula (KP) located in the Northwest Pacific have different topographic features. West coast of the KP has large tidal variations. If storm surge occurred at high tide, the west coast is vulnerable to flooding. The south coast has a complex coastline with hundreds of islands. Its complex topography can amplify storm surge height (SSH) and it also makes it difficult to conduct numerical modeling for storm surge. Moreover, as the KP is located in the pathways of typhoons, it has been affected by an average of three typhoons every year. The KP has actually suffered from storm surge-induced disaster several times in the past. In order to plan efficient and effective countermeasures against storm surge disasters, it is required to identify the vulnerability of coastal regions in the KP. Therefore, this study quantitatively analyzed the frequency and cause of occurrence of storm surges that occurred along the Korean coast in the past.First, this study collected observed tidal data at 48 tide stations which are installed along the coast of the KP and performed a hormonic analysis on the observed tidal data to build a database of SSH information that occurred along the coast of the KP from 1979 to 2021. Next, the cause of the storm surge was evaluated based on the occurrence time of the high-level SSH. If the storm surge occurred in winter season, it was treated as being caused by an extra-tropical cyclone, and if in summer season, by and tropical cyclone. Lastly, storm surge vulnerable areas were assessed based on frequency and level of the SSH. To this end, the coast of the KP was divided into five zones: the northwest coast, the southwest coast, Jeju island, the southeast coast and northeast coast. The frequency of the high-level SSH generated in those zones was calculated, and areas where storm surge occurred a lot were selected as vulnerable areas.As a result of the study, it was found that the high-level SSH with more than 1 m in the KP are caused by tropical cyclone in summer, and the area most vulnerable to storm surge is the southeast coast.However, the observed tidal data used in this study has a limitation in that the collection period differs depending on the zone: the observation period is longer for the southeast coast than for the southwest coast. Looking at the paths of past typhoons, many typhoons passed through the west coast, so the possibility that the southwest coast would have been judged to be more vulnerable than the southeast coast cannot be ignored if the observed tidal data for the southwest coast were more abundant. In addition, since storm surge is phenomenon that is affected not only by meteorological conditions but also by topographic conditions (e.g., complexity of coastline, water depth, etc.), spatio-temporal analysis of storm surge by topographic conditions is going to be conducted through future research. AcknowledgementThis work was supported by the National Research Foundation of Korea grant funded by the Korea government(MSIT) (No. 2022R1C1C2009205). 
Assessment of land use land cover changes and its impact on groundwater resources of Kamrup along the banks of the River Brahmaputra
Authors: Deka Dhritilekha , Ravi Karangat , Nair Archana M
Published: February 2023

Urbanisation induced land use land cover changes (LULC) are irreversible and is an intensifying worldwide phenomenon. The unprecedented urban growth rate affects the hydrological system and its associated ecosystem services. This has led to a situation where even regions with huge water potential such as the Ganga-Brahmaputra basins of India, are experiencing potable water scarce conditions. Hence, this study is an effort to evaluate the role of LULC on the groundwater resources of Kamrup district, along the banks of River Brahmaputra in Assam. The study entails a quantitative analysis using GIS applications, whereas the statistical significance is evaluated using Man Kendall trend analysis. Satellite images of Landsat and Sentinel are clustered and segmented to classify six different classes. The cloud-based platform of Google Earth Engine (GEE) is utilised for the object oriented (OO) classification. A combination of Simple Non-Iterative Clustering (SNIC) and Random Forest Classifier is utilised to obtain an accuracy >85% for all the images. It is observed that the area under agriculture and wetlands has reduced by 58.99% and 44.7% between 1990 to 2020, respectively. On the other hand, the area under urban impervious cover has increased from 1.875% in 1990 to 17.05% in 2020. The Mann Kendall trend analysis of the groundwater levels shows that 69% of the well locations demonstrate a declining trend at 95% confidence interval. The maximum decline rate is of 0.13 m year−1 and minimum decline rate is 0.03 m year−1. Comparative investigation of the groundwater decline and urban growth shows that 47% of the groundwater wells with declining water levels are located in regions urbanised from 1990 to 2020. The decline in the groundwater levels can be attributed to increased impervious surfaces with the urbanisation. Further, the reduced chances of infiltration have led to amplified runoff and floods with reduced groundwater level in the wells. The results from this study indicate that the depletion in groundwater across the study area can be strongly linked to anthropogenic interferences. Such monitoring of LULC changes along with the dynamics in water levels across the study area, provide a necessary database for the protection, decision-making and sustainable management of the existing freshwater resources.
Mineral magnetic discrimination between diagenetic and hydrogenetic iron-manganese concretions
Authors: Wasiljeff Joonas , Salminen Johanna , Lahaye Yann , Virtasalo Joonas
Published: February 2023

Marine iron-manganese concretions are metal-containing biogeochemical precipitates abundantly encountered in the seafloors of the world ocean. Their importance in paleoenvironmental reconstructions as well as a source for critical metals has been recently realized. Diagenetic and hydrogenetic concretions, however, have different compositions and subsequently can have differing capacities for recording oceanographic processes and for economic utilization. Therefore, their genetic classification can provide crucial information for both environmental and economic applications. Traditionally discrimination of different marine iron-manganese concretion origins has been achieved with geochemical methods, such as investigating their rare earth element content. It is now evident that iron-manganese concretions also host magnetic minerals that are likely formed by facilitation by microbial processes. Currently it is unknown if the different genetic backgrounds of iron-manganese concretions are reflected in their magnetic properties.  We compared the geochemical and magnetic properties of diagenetic iron-manganese concretions from the Baltic Sea to hydrogenetic concretions from the Pacific. While the commonly utilized geochemical indicators differentiate the concretions found from the two localities as diagenetic and hydrogenetic, it also appears that concentration dependent magnetic parameters such as saturation magnetization and anhysteretic remanent magnetization effectively discriminate between the different types of concretions. Mineral magnetic methods are fast and cost-effective and may provide an alternative tool to quickly screen out diagenetic from hydrogenetic precipitates.This research is part of the Fermaid project, funded by the Academy of Finland grant 332249.
Improvements and validation of nextSENSE solar energy nowcasting and short-term forecasting system
Authors: Papachristopoulou Kyriakoula , Fountoulakis Ilias , Bais Alkiviadis F. , Psiloglou Basil E. , Kontoes Charalampos , Hatzaki Maria , Kazadzis Stelios
Published: February 2023

Solar energy is one of the main sources of renewable energy nowadays. Since there is a strong dependence of solar power generation on the presence of clouds and aerosols, operational nowcasting and short-term forecasting of solar resources are essential for its integration into the grid.
The aim of this study is the assessment of the downwelling surface solar irradiation (DSSI) estimates from the nextSENSE operational service. This service uses as input earth observational data for clouds (EUMETSAT), aerosols (Copernicus Atmosphere Monitoring Service - CAMS) and other important atmospheric parameters to the fast radiative transfer model (RTM) techniques (look-up table – LUT and multi-parametric equations) in order to derive DSSI in real time over Europe and North Africa in high spatial resolution (5 km at sub-satellite point), every 15 min. Recent modifications relative to the older versions are: (i) the use of multi-parametric equations to obtain the effect of clouds from cloud optical thickness (COT) instead of using Artificial Intelligence techniques, and (ii) the use of more detailed LUT. Forecasted DSSI values are also produced up to 3-hours ahead with a 15-min time step by applying a cloud motion vector (CMV) technique to the COT product based on Meteosat second generation (MSG) satellite data.
The new modeled (nowcasted and forecasted) DSSI values were validated against ground-based global horizontal irradiance measurements from pyranometers operating at the Baseline Surface Radiation Network (BSRN) stations and at two additional stations, these of Athens and Thessaloniki, Greece, for the year 2017. The nextSENSE forecasted DSSI values were also benchmarked against the smart-persistence forecast method. The performance of the modeled DSSI values were assessed for different cloud conditions in terms of real cloud modification factor (CMF) values derived by ground-based measurements in conjunction with a clear sky model. Additionally, the effects of aerosol related inputs for estimating DSSI were quantified by comparing the utilized CAMS aerosol optical depth (AOD) forecasts against surface retrievals of the AERONET network.
Acknowledgements
This study was funded by the European Commission project EuroGEO e-shape (grant agreement No 820852).
Implementing Water Balance Model for Stormwater Management: the case of an Infiltration-Based Green Infrastructure Under Shallow Groundwater Levels
Authors: Masseroni Daniele , Niazkar Majid , Cislaghi Alessio
Published: February 2023

Infiltration-based green infrastructures (GIs) are commonly constructed to effectively storage the excessive stormwater runoff. These GIs exploit infiltration process, as the key natural phenomenon in the hydrological water balance, to detain excessive stormwater volume, especially at the outlet of the peri-urban watershed. Beside many factors playing significant roles in the performance of the infiltration-based GIs, implementing them in shallow groundwater area still represents a challenge that can restrict their widespread adoption. In fact, the groundwater level, if close to the bottom of infiltration-based GIs, can strongly influence the infiltration process. Basically, the shallow groundwater may theoretically play as a boundary conduction and subsequently reduces the infiltration rate.The present study investigated the activation of an infiltration-based GI located at the outlet of the combined sewer system in the municipality of Sedriano (12,000 inhabitants in province of Milan, North Italy), monitoring the inflow and the water depth over a period of almost two years. Meantime, groundwater level and meteorological measurements were observed (including precipitation, air temperature, solar radiation, wind velocity, and relative humidity). Using these observations, a Water-Balance Model (WBM) was calibrated on the hydrological response of the infiltration-based GI and then, used to simulate how much time is required to empty under a specific precipitation event, and to understand the spatial distributed performances of these measures under different groundwater levels.The implementation of an accurate WBM can be a useful tool for designing and assessing the performance of the infiltration-based GIs in shallow groundwater environments in peri-urban areas. This study is an integral part of the project Smart-Green (www.smartgreen.unimi.it) that developed online tools for supporting the water utilities to accelerate the transition towards the sponge cities utilizing GIs techniques.
Evaluating the explainability and performance of an elementary versus a statistical impact-based forecasting model
Authors: Sedhain Sahara , van den Homberg Marc , Teklesadik Aklilu , van Aalst Maarten , Kerle Norman
Published: February 2023

The disaster risk community has notably shifted from a response-driven approach to making informed anticipatory action choices through impact-based forecasting (IBF). Algorithms are being developed and improved to increase impact prediction abilities, and to allow automatic triggers to reduce the reliance on human judgement. However, as complexities in modelling algorithms increase, it becomes more difficult for decision makers to interpret and explain the results. This reduces the accountability and transparency, and can lead to lower adoption of the models. Therefore, humanitarian decision-makers can benefit from a mechanism to evaluate different IBF approaches, which has not yet been developed. Through a case study of anticipatory action for tropical cyclones in the Philippines, we evaluated two very different approaches to IBF: (1) a statistical trigger model that uses a machine learning algorithm with several predictor variables, and (2) an elementary trigger model that combines damage curves and weighted overlay of vulnerability indicators, to predict the impact and prioritize areas for intervention. The models were evaluated based on their performance for damage prediction and their sensitivity to different risk indicators for Typhoon Kammuri (2019) in the Philippines. The study also proposed a way of characterising the explainability specific to an IBF model, and that gives clarity on which elements, and why, influence the results, done via a model card. To facilitate this process a prototype interactive decision portal was built, which shows decision makers the sensitivity of the results to variations in input parameters. The results show that in relative terms the elementary model performed better and would have allowed to maximise impact reduction through early action, suggesting that, for this particular case, complex was not necessarily a better choice. However, the uncertainty in both models due to limitations in the initial hazard forecast indicates that multiple models need to be evaluated for practical cases that cover different characteristics of the hazard and socio-vulnerable situations. For this, the evaluation framework we developed can be expanded across operational IBF projects.
How to prepare for record-shattering hot events
Authors: Klok Lisette , Kelder Timo , van Vessem Elske , Hondema Laurens Severijn
Published: February 2023

The heat dome that Portland experienced in 2021 with temperatures up to 46 °C was unprecedented and unexpectedly severe, leading to the death of dozens of people. What if such an exceptional event were to occur somewhere else?  The Netherlands seems to be sensitive to such 'record-shattering' hot events, but luckily has not yet experienced them. Here, we show how to qualitatively connect the increasing scientific understanding of plausible record-shattering hot events with potential impacts and necessary responses for the city of Amsterdam. The expected impacts and potential responses of record-shattering hot events are identified through expert judgement with professionals from various disciplines. We asked what could possibly happen in Amsterdam if the temperature rises to 45 degrees, in particular what kind of problems and bottlenecks are expected and what possible solutions are. The results of this exercise provided additional insights to heat plans based on lived experiences. As such, this case study may prove a useful example for governments and private sectors wishing to prepare for future exceptional heat waves.
Warming of the Gulf of Eilat (Red Sea) water due to advection
Authors: Sengupta Sounav , Ashkenazy Yosef , Gildor Hezi
Published: February 2023

The Gulf of Eilat is a body of water located at the northern tip of the Red Sea and isknown for its unique marine ecosystem. We analyzed the sea temperature andsalinity, air temperature, heat flux, and other climatological data in order to betterunderstand the processes driving the Gulf's dynamics. The sea temperature datawas based on 18 years of measurements taken at depths up to 700 meters, whilethe meteorological data was based on 16 years of observations. The analysisindicates the sea temperature is significantly increasing at all depths; yet, no cleartrends were found in the air temperature. The increased warming is associated withmuch fewer deep mixing events and used to occur more frequently. We constructedthe ocean-atmosphere heat fluxes and concluded that the horizontal advection ofheat from the southern part of the Red Sea might underlie the increase in watertemperature in the Gulf of Eilat. This conclusion is also supported by the recent IPCCreports and previous studies. Our results indicate that local ocean warming is notnecessarily linked to a local increase in air temperature but rather to the warming ofother remote places.
3D groundwater salinity mapping of the global coastal zone
Authors: Oude Essink Gualbert , Zamrsky Daniel , King Jude , Delsman Joost , Verkaik Jarno , Bierkens Marc
Published: February 2023

Accessible and reliable freshwater sources are essential for human communities and freshwater ecosystems worldwide. In coastal regions, groundwater is the main freshwater sources for drinking water thanks to its high quality, easy accessibility and relatively constant supply. Both anthropogenic (e.g. poor water management and rising population numbers) and natural (e.g. climate change related sea-level rise and storm surges) create additional pressure on coastal freshwater resources. This pressure can lead to declines in fresh groundwater availability caused by salinization and over-exploitation, especially in densely populated areas with intensive agricultural production that already have a high freshwater demand. Groundwater salinization can have severe negative impacts on environmental, economic and human health conditions in these areas. Understanding of current and future threats to fresh groundwater availability by salinization allows coastal communities to better adapt to these risks. Groundwater salinity models are typically applied to study groundwater salinization in local and regional settings and thus provide information for water management bodies to improve their mitigation and adaptation measures. The added value of a global 3D coastal groundwater salinity map would be that it provides important insights into the most threatened regions worldwide, while also identifying coastal regions with similar groundwater salinization risks and similar suitable mitigation and adaptation measures to tackle them. The global 3D groundwater salinity map can also be used as a starting point to evaluate future groundwater salinity developments under multiple climate change and socio-economic scenarios. Hitherto, there were several key obstacles preventing us from building a global 3D groundwater salinity map; the most important ones being the lack of standardized global hydrogeochemical, geological and geophysical datasets and inadequate computational resources and numerical codes. Recent developments in code parallelization (e.g. iMOD-WQ and in due time MODFLOW6) and access to high performance computing allows us to simulate global 3D groundwater salinity by splitting the world into smaller regional scale 3D groundwater salinity models and simulating these in parallel. Moreover, the advancement in available global datasets and creation of a unified global hydrogeological database and schematization allow us to better estimate regional subsurface conditions. Here, we demonstrate the process of building the global 3D groundwater salinity map and show its potential applications. Ultimately, identifying the most threatened regions in near future can lead to better water management strategies to limit the negative impacts of groundwater salinization on fresh groundwater resources, and/or to come up with strategies to explore additional new ones.
Challenges for flood hazard and risk assessment in Mozambique: the case of Megaruma and Muaguide rivers
Authors: Rrokaj Sara , Corti Benedetta , Cancelliere Giorgio , Costa Alice , Giovannini Anna , Molinari Daniela , Paz Idarraga Charlie Dayane , Radice Alessio , Rotaru Ana Maria
Published: February 2023

As a consequence of climate change and rapid urbanization, floods have increased both in terms of intensity and frequency, impacting especially the less developed countries of the World, and particularly sub-Saharan Africa. In such contexts, reliable flood risk assessments are of primary importance to support local authorities and stakeholders in emergency management and planning, and in the definition of effective risk mitigation measures. Still, their implementation is often hampered by lack of suitable data and resources. The present study has the main objectives of presenting challenges and identified solutions of performing flood hazard and risk analysis for the Megaruma and Muaguide rivers in Cabo Delgado, the northern province of Mozambique and also the poorest one. The downstream paths of the rivers cross the districts of Mecufi and Metuge, rural areas covered by fields cultivated by inhabitants who live on subsistence agriculture. During the wet season, some of the villages are completely isolated, with no access to adequate health services due to the floods that periodically affect the local population and their activities. As for many developing countries, data scarcity was the first limiting factor for quantitative analysis; therefore, much effort was primarily invested into data research. The hydrologic and hydraulic modelling to determine the flood hazard in the areas rely on free or at least cheap, global data (rainfall, terrain elevation and soil cover), meeting the second requirement of low available budget. On the contrary, an intensive field survey was required to collect data on the vulnerability of exposed assets at the base of damage assessment. Particular attention was also paid in the choice of free softwares and modelling tools. The resulting approach and methods can be easily exported to similar contexts, enabling robust flood risk analyses in the support of sustainable development.
Machine learning model to assess the spatial probability of Sentinel-1 based deformation trend changes
Authors: Medici Camilla , Confuorto Pierluigi , Bianchini SIlvia , Del Soldato Matteo , Rosi Ascanio , Segoni Samuele , Casagli Nicola
Published: February 2023

Satellite ground deformation monitoring is now a well-established reality and the MTInSAR (Multi-Temporal Interferometry Synthetic Aperture Radar) techniques have widely demonstrated their feasibility for detecting a wide range of slow-moving phenomena, e.g., landslides and subsidence at different scales. The launch of the ESA’s Sentinel-1 constellation has allowed acquiring massive quantities of radar images with a worldwide coverage and a short revisiting time. These characteristics, combined with the increasing computation capabilities and advanced processing techniques, have opened the opportunity of implementing a continuous monitoring service of ground surface deformations at regional scale. Tuscany, Veneto, and Valle d’Aosta regions (Italy) have benefited from this service exploiting ground deformation maps, periodically updated, and identifying the so-called anomalies of movement of radar targets, i.e., trend changes (e.g., accelerations) in the time series of displacement. However, the continuous monitoring system only has the ability to detect the anomalies of movement without being able to assess the propensity of a territory to be affected by them. Therefore, an approach for assessing the spatial probability of trend changes of InSAR-based ground deformations occurrence has been proposed. The occurrence probability of anomalies is determined by a Machine Learning (ML) algorithm, Random Forest, and the data used for the application of the model are the anomalies database and the predisposing factors (PF). The selected PFs can be split into two groups, indeed, in addition to the classical morphological and geological features, even five variables related to the radar system have been integrated. The latter parameters are two radar visibility indexes (C-index and R-index), the horizontal, along East-West direction, and vertical component of the velocity of displacement and the standard deviation of the satellite line of sight (LOS) velocity. These two groups of PFs can be considered a synthesis of the main factors that lead to the generation of anomalies. The procedure has been tested on the Tuscany region for assessing the spatial probability of anomalies occurrence related to landslides and subsidence. The outcomes of the procedure are two maps of the spatial probability of occurrence of landslides and subsidence anomalies. A cross-validation procedure has also been performed to verify the reliability of the final maps by exploiting anomalies collected in a different timespan from the input data and the official landslide and subsidence inventories. The resulting information, periodically updated, can represent a useful instrument for the regional authorities to identify the main driving forces leading to ground deformation anomalies and the areas where site investigations are to be carried out to assess the preliminary risk.