bluuebunny/crossref_metadata_2025 huggingface dataset:
Climate change impact on wheat yield in India: Study using CERES-wheat model
Authors: Lakshmanan Achanya , Shastri Yogendra , Singh Riddhi
Published: March 2024

Agriculture is highly dependent on climate because rainfall, temperature and sunlight are the primary determinants of crop development. Climate change driven effects such as variation in precipitation and changes in temperatures are likely to affect agricultural yields. Systematic planning of agricultural activities considering these effects is essential. As a first step towards this longer term objective, this work quantifies the effect of climate change on crop in short and long term in India. Wheat is chosen as the crop of interest. Madhya Pradesh, one of the leading wheat producing states in India, is the region under focus, and Betul district is selected for a initial studies. The CERES-wheat model in the Decision Support System for Agrotechnology Transfer (DSSAT) tool is used to estimate the impact of climate change on wheat yield. The CERES-wheat model has been calibrated and validated, and the calibrated parameters have been used to simulate wheat yield in the future. The base period for calculating base wheat yield is 2009-2019. Future wheat yields are calculated for two periods (2025-2055 and 2056-2085). The projected changes in precipitation, maximum temperature (Tmax) and minimum temperature (Tmin) in future compared to the base period are calculated using four different General Circulation Models (GCMs) and four Shared Socioeconomic Pathways (SSPs). To increase the study's robustness, 1000 samples are systematically generated using Latin Hypercube Sampling (LHS). A stochastic weather generator (WG), WeaGETS, is used to create a synthetic time series of climate variables. Using the 1000 different combinations of changes in climate variables, 1000 climate scenarios are generated using WeaGETS. The climate variables used to determine the relationship between climate and wheat yield were mean rainfall, rainfall variance, Tmax, and Tmin. Wheat yield ranged from 2065 to 3207 kg/ha during the baseline period, and it is expected to vary from 1629 to 3638 kg/ha between 2025 and 2055. Looking ahead to 2056-2085, wheat yields are estimated to range from 1363 to 3555 kg/ha. The sensitivity analysis results between climate variables and wheat yield for both periods suggest that wheat yield is positively correlated with mean rainfall and rainfall variance and negatively correlated with Tmax and Tmin. Maximum temperature has a significant negative correlation with wheat yield in both periods after excluding the effect of other climate variables. However, in the last stage of wheat yield development, the grain filling stage, Tmin is more critical than Tmax. These results highlight the need for systematic planning to manage negative impacts of climate change on wheat cultivation in India. These results will used as a basis for suggesting adaptation strategies to manage the impact of climate change on wheat yield.
Modelling of Haze Episode over Delhi Region using a Chemistry-Transport Model: Contribution of Emission and Meteorology
Authors: Srilekha Valasani , Verma Shubha , Ray Rhitamvar , Salvi Kuldeep
Published: March 2024

Haze episodes are often shrouded over Delhi-NCR and most of the Northern Indo-Gangetic Plain during the Post-Monsoon and Winter seasons, posing a huge negative burden on human health, the environment, and the economy. The combined influence of local emissions, meteorology, regional transport, and topography results in the complex chemical mechanism, which is difficult to predict based on observational studies, emphasizing the necessity of modelling the episodic haze in a chemistry-transport model. The present study adopted Weather Research and Forecasting (WRF) model, coupled with the CHIMERE chemistry-transport model, to simulate the haze event that happened in November 2019 over Delhi, to understand the chemical mechanism involved and to quantify the contribution of emissions and meteorology towards the increase of PM2.5 concentration. Temporal variations of the modelled PM2.5, air quality and meteorology variables are in good agreement with the observed data. Correlation coefficients (R) between simulated and observed values were larger than 0.7, and the normalized mean biases (NMB) were within ± 30%. The evaluations indicate that WRF-CHIMERE is able to capture the trends of haze events. Major fraction of PM2.5 during the haze was comprised of Organic Matter (OM) followed by secondary inorganic aerosols. It was also found that although OM was high in concentration, the rate of increase of nitrates was higher than OM, indicating an important role of inorganic aerosols in high PM2.5 concentration. In addition, sensitivity simulations revealed that anthropogenic emissions had a significant contribution for high particulates during the episode. Therefore, adopting the anthropogenic source emissions control startegy could be an effective control measure for reducing the severity of PM2.5 pollution over Delhi region.
Combining remote sensing products with crop and soil models to estimate changes in soil organic carbon on cropland
Authors: Pique Gaétan , Goussard Basile , Géraud Andréa
Published: March 2024

Agricultural land is a major contributor to human greenhouse gas emissions, but it is also affected by climate change. At the same time, the recent 4p1000 initiative has identified cropland as having important the potential to sequester atmospheric carbon in the soil. However, there is currently a lack of robust and accurate tools to assess the carbon budget of cropland at plot level and over large areas. This lack is due to the heterogeneity of the landscape, characterised by a wide range of soil and climatic conditions and many agricultural practices. However, these tools are needed to better understand the contribution of cropland to greenhouse gas emissions and to properly identify the most efficient levers for sequestrating carbon in the soil.In this study we propose a modelling framework to estimate carbon budgets at plot scale and over large areas. This approach assimilates optical remote sensing products with high spatial and temporal resolution into a crop model (SAFYE-CO2). This model allows the estimation of CO2 fluxes as well as crop productions (biomass and yield) of the main crops and the cover crops. This information is then used as input to a soil model (RothC) to estimate the carbon storage following the introduction of the cover crops into the soil.This framework is validated using CO2 flux measurements from the ICOS network and cover crop in situ biomass data. This approach is in line with the search for the 'monitoring, reporting and verification' tools that is needed today to drive the agricultural transition, to enable sustainable agriculture that provides sufficient production in a changing climate, while identifying the best practices to use agricultural land as a way of achieving net zero carbon targets.
Origins, flow paths, and mean travel times of water in an Australian alpine catchment
Authors: Vervoort Willem , Keietel Claudia , Chisari Robert , Farrawell Kellie-Anne , Buzacott Alexander
Published: March 2024

Understanding water origins, flowpaths, and the timescales over which precipitation becomes streamflow are critical for knowledge of the functioning of catchments. Catchments on the Great Dividing Range along the east coast of Australia are important sources of flows into Murray Darling basin for agricultural and drinking water use. This study collected a unique dataset that includes hydrometric measurements and samples of groundwater, surface water and precipitation between 2016 to 2020 to investigate hydrological processes in the Corin catchment, an alpine catchment in south-eastern Australia. Water samples were analysed for major ion chemistry and stable isotopes in water, and eight samples were selected for analysis of tritium activities. Major ion chemistry and stable isotope values were used to assess the relative contributions of water from two contrasting geological areas of the catchment to streamflow. Streamflow exiting the catchment had a consistently different chemical and isotopic signature compared to the groundwater found in the catchment valley. Instead, streamflow consistently resembled water originating from the slopes of the catchment that are underlain by a relatively younger geology. The mean travel times (MTT) of valley groundwater are likely to be in the decades, while baseflows are estimated to have a MTT of around 7 years. This work demonstrates the power of a multi-tracer approach to unravel the hydrological complexities of headwater catchments in south-eastern Australia.
A climatological look on the intersection of synoptic conditions and extreme weather-induced potential impact events in the cross-border region of Austria and Italy
Authors: Lehner Sebastian , Enigl Katharina , Crespi Alice , Pittore Massimiliano , Haslinger Klaus
Published: March 2024

Extreme weather events and associated natural hazards pose a significant global threat to all levels of society. It is scientific consensus that climate change contributes to an increasing frequency and intensity of these events. One of the key challenges for decision-makers in the field of civil protection is to deal with the changing landscape of weather-induced impact events, that are driven by climate change. Hence, assessing the current and changing conditions across spatiotemporal scales for extreme weather events under a changing climate is essential.
This study explores the potential of utilizing weather circulation type classification through its correlation with observed weather-induced extreme events and their potential impacts on the local-scale. Thereby, high-impact weather types can be determined as a relevant background field, serving as a measure about the potential of severe weather hazards. We employ ERA5 reanalysis data as baseline meteorological input data to derive long-term and robust time series of weather types from mean sea level pressure that are relevant for the cross-border region of Austria and Italy. The classification scheme 'Gross-Wetter-Typen' (GWT) with 18 classes was used to assign each day a prevailing weather type class. The overlap between derived classes is further investigated by means of unsupervised clustering techniques, to evaluate clusters of groups across all GWT classes. Additional meteorological fields (e.g. equivalent potential temperature, geopotential height, precipitable water, ...) are validated on top of the GWT classes for further characterisation of extreme weather events. Days exhibiting extreme weather-induced potential impact events are derived via percentile methods applied to precipitation data from observational gridded datasets (Enigl et al., 2024, EGU24-10058). Finally, we extend our analysis with an evaluation of potential changes by applying found relationships to state-of-the-art climate model data from the Coupled Model Intercomparison Project 6 (CMIP6) to investigate the changing landscape of potential weather extremes.
Our findings indicate that a specific subset of large-scale weather circulation patterns acts as a crucial precursor to high-impact weather extremes. Furthermore, considering the climate change scenario SSP3-7.0, the frequency and associated precipitation totals linked to these weather patterns exhibit an increase. This suggests a potential rise in both the frequency and intensity of extreme weather events and their corresponding impacts if emissions continue to increase.
In search for liquid water using radio waves: from Earth to the icy moons of Jupiter
Authors: Pettinelli Elena
Published: March 2024

Radar sounder (or Ice-penetrating radar) is one of the most suitable geophysical instruments to explore planets and moons given the very dry and/or cold conditions of their crusts, which favor the penetration of the radio waves at great depth. The first ever planetary subsurface radar was tested on the Moon, during the Apollo 17 mission: the ALSE (Apollo Lunar Sounder Experiment) multifrequency radar sounder operating onboard the Apollo Service Module (ASM) (Porcello et al., 1974). After this successful experiment more than twenty years passed before another radar sounder was included in the payload of a planetary mission. MARSIS was launched in 2003, on board Mars Express, and SHARAD in 2007 onboard Mars Reconnaissance Orbiter. Since the successful deployed on Mars, such radars collected data for more than 15 years, mapping the structures of the Martian poles and discovering the first extraterrestrial stable body of subglacial liquid water below the South pole cap. Six orbiting radar sounders have been employed so far to explore the Moon, Mars and the 67P/GC comet, and some of them are still in full operation today. The Jupiter icy moons will be the next destination of a new generations of radars: RIME, already on his way to Ganymede onboard JUICE and REASON that will be launch this year onboard Europa Clipper. These radars will explore the icy shells of Europa, Ganymede and Callisto to establish their habitability conditions and in search for evidence of liquid water. Finally, also Venus will be investigated in the next decade by a similar radar to help understand the geological and climatic evolution of the Earth twin.In this talk I will discuss the new opportunities and challenges for the radar sounder community in the years to come.
How to obtain a highly accurate dataset of the snow surface temperature with a thermal infrared camera?
Authors: Arioli Sara , Picard Ghislain , Arnaud Laurent , Gascoin Simon , Alonso-González Esteban , Poizat Marine , Irvine Mark
Published: March 2024

Snow plays a critical role in alpine areas, influencing the local climate and serving as a crucial water reservoir for downstream ecosystems and human activities. The surface temperature of snow provides many insights about the current state of the snowpack and helps water storage estimations. While satellites are regularly used to measure surface temperature of snow over alpine areas, accurate measurements are still difficult to retrieve from space, and calibration-validation initiatives over snow-covered areas are scarce. In this context, we produced a two-winter timeseries of approximately 130,000 maps of the radiative surface temperature of snow acquired with an uncooled Thermal Infrared camera. TIR images were acquired November 2021 to May 2022 and February to May 2023 at the Col du Lautaret, 2057 m a.sl. in the French Alps. During the first season, the camera operated in the off-the-shelf configuration, with a rough thermal regulation (7°C - 39°C) resulted in timeseries of snow surface temperature maps with an absolute accuracy
Spatio-temporal cryosphere variations in the headwater river basins of Central Asia
Authors: Gafurov Abror , Busch Friedrich , Mamaraimov Adkham , Gafurov Akmal , Georgi Alexander
Published: March 2024

Central Asia is facing a water shortage due to the negative impacts of climate change. Water resources in this region originate mainly in the mountains of Pamir and Tian-Shan due to snow-and glacier melt. Thus, it is important to understand variations in the cryosphere (snow and glaciers) in this region to foster climate change adaptation measures.This study focuses on the analysis of spatio-temporal changes of snow and glaciers in the Amu Darya, Syr Darya and Zerafshan river basins in Central Asia. Due to limited availability of observational network in the region, we used, besides available station data, also remote sensing-based snow cover area data for the period of 2000-2023. As for the glacier change analysis, we used a degree-day modelling approach to assess changes of glacier thickness in the period of 2000-2023. Eight glaciers were chosen for modelling purposes that are all located in the selected eight river basins for this study. Spatio-temporal analysis of snow cover area change show significantly decreasing number of snow cover days above a certain elevation in Upper Amu Darya and Upper Syr Darya river basins. In both river basins, there are regions with up to 40 days less snow coverage between 2000 and 2023. In the Upper Syr Darya river basins this change is observed in the Akshiirak Massif area, whereas in the Amu Darya River Basin, this change is observed in the Murghab area in the far western part of the river basin. Below a certain elevation zone, there are also areas with increased number of snow cover days of up to 10 days. The attribution of this change into meteorological parameters leads to various hypothesis. The modelling results of glacier thickness change was validated against glacier area evolution that was derived using the Landsat images.  In most of the river basins, a maximum of 60-70 meters of ice thickness loss was estimated with an increase of ice thickness of some glaciers in the accumulation area of about 10-15 meters. However, in two of the valley glaciers (Vanch and Zerafshan River Basins), higher amount of glacier thickness loss was estimated in the last 23 years.The study suggests quantified cryosphere changes in the last 23 years for Central Asian region and emphasizes the need for climate change adaptation as the water resources originating in the mountains of the region (water towers) are important for socio-economic stability.
Development and Evaluation of A Real-Time Hourly One-Kilometre Gridded Multisource Fusion Air Temperature Dataset in China Based on Remote Sensing DEM
Authors: Han Shuai
Published: March 2024

High-resolution gridded 2 m air temperature datasets are important input data for global and regional climate change studies, agrohydrologic model simulations and numerical weather predictions, etc. In this study, the digital elevation model (DEM) is used to correct temperature forecasts produced by ECMWF. The multi-grid variation formulation method is then used to fuse the data from corrected temperature forecasts and ground automatic station observations. The fused dataset covers the area over (0–60°N, 70–140°S), where different un-derlying surfaces exist, such as plains, basins, plateaus, and mountains. The spatial and tem-poral resolutions are 1 km and 1 h, respectively. The comparison of the fusion data with the verification observations, including 2400 weather stations, indicates that the accuracy of the gridded temperature is superior to European Centre for Medium-Range Weather Forecasts (ECMWF) data. This is because a more significant number of stations and high-resolution terrain data are used to generate the fusion data than are utilized in the ECMWF. The obtained dataset can describe the temperature feature of peaks and valleys more precisely. Due to its continuous temporal coverage and consistent quality, the fusion dataset is one of China’s most widely used temperature datasets. However, data uncertainty will increase for areas with sparse observa-tions and high mountains, and we must be cautious when using data from these areas.
Bright-toned aeolian bedforms in Oxia Planum (Mars), the ESA ExoMars landing site
Authors: Silvestro Simone , Favaro Elena , Vaz David Alegre , Yu Tao , Valdez Andrew , Salese Francesco , Pacifici Andrea , Tirsch Daniela , Franzese Gabriele , Mongelluzzo Giuseppe , Popa Ciprian Ionut , Porto Carmen , Esposito Francesca
Published: March 2024

Bright-toned aeolian bedforms are abundant in Oxia Planum, the future landing site of ESA’s ExoMars rover mission [1-3]. Their NE-SW orientation differs from other aeolian landforms in the area, such as the E-W oriented ridges carved in the bedrock (periodic bedrock ridges – PBRs [4, 5]), suggesting major changes in wind and climatic conditions [2, 3]. At Oxia Planum, bedforms formative winds have been interpreted as blowing from the NW to the SE based on the difference between dark stoss slopes and bright lee slope albedo, with darker surfaces interpreted as coarse grained materials and brighter surfaces interpreted as fine grained material, a relationship recognized in terrestrial megaripples observed on the Argentinian Puna Plateau [2]. In another interpretation [3], bedform formative winds were interpreted as coming from the SE, as evidenced by the presence of regularly spaced low albedo bands found on bedforms SE slopes and interpreted as exposed cross-beds at their windward sides. The same interpretation was given by other authors for similar bandings found on bright bedform slopes in other areas of Mars [6]. Here we propose an alternative explanation for these bands, which we interpret as potential “sorting streaks”, analogous to what is observed over dunes in Great Sand Dunes National Park (CO, USA). The morphology of some crescent-shaped examples visible in the study area, with their tips pointing to the SE, confirms a formative wind from the NE. This scenario implies a complex wind regime where bright bedforms were first formed by winds blowing from the NE [2], and subsequently shaped by winds coming from the ESE (assuming that an oblique/parallel wind direction is necessary to deposit darker material in bands over the SE slopes). The presence of dark wind streaks pointing WSW supports this scenario. We also report the presence of similar regular bands on bright bedform slopes at the Zhurong rover landing site in Utopia Planitia. Due to the widespread nature of these banded landforms [6-8], this new interpretation might help to interpret paleo-wind conditions on Mars.References[1] Balme et al. 2017, Geomorphology, 101(4), 703–720.[2] Favaro et al. 2021, JGR, 126, e2020JE006723.[3] Silvestro et al. 2021, GRL, 48, e2020GL091651.[4] Montgomery et al. 2012, JGR, 117, E03005.[5] Hugenholtz et al. 2015, Aeolian Research, 18, 135–144[6] Day 2021, Geology, 49 (12): 1527–1530.[7] Gou et al. 2022, EPSL.[8] Bourke & Viles, 2016, GRL, 43, 12,356–12,362.
Evaluating the effects of the Earth's foreshock configurations on the "quiet-time" ionosphere
Authors: Urbar Jaroslav
Published: March 2024

The day-to day variability of quiet-time ionosphere is surprisingly high even during periods of negligible solar forcing. Relatively well understood is the high-latitude variability where the solar wind is directly driving the high latitude currents, convection electric field or polar aurorae. But the currentunderstanding does not allow to accurately model the ionospheric state during the quiet-time conditions at mid- and low-latitudes. Surprising effects remain even at mid-latitudes, including for instance double daily maxima of ionospheric critical frequency.European Space Agency's SWARM satellite constellation measurements allow the characterization of the upper atmospheric conditions and dynamics for already more than 10 years. The analysis of SWARM electron density and electric field data already showed that the ionosphere at mid-latitudes shows a non-negligible variability without a-priori solar driver, during negligible variations both in X-ray/EUV fluxes and missing disturbances in the solar wind. This often significant ionospheric variability currently remains unexplained, and further studies need to evaluate contributions by couplings from below comparing with those from above, i.e. checking the frequencies matching the foreshock waves with the local field-line resonances.After efforts to properly select such "solar-quiet" periods, we compare the SWARM-detected variability trying to relate them to observations of magnetospheric ULF waves and configurations of the Earth foreshock mainly infered from the NASA's THEMIS satellite fleet and Wind solar wind observations.
The response of the cometary ionosphere to space weather forcing
Authors: Timar Aniko , Nemeth Zoltan , Burch Jim
Published: March 2024

The Rosetta spacecraft, traversing the inner magnetosphere of comet 67P/Churyumov-Gerasimenko, observed medium-energy ions of cometary origin. These ions, moving in the direction of the cometary nucleus, are likely accelerated in the outer regions of the comet's magnetosphere. Emerging from the low-energy ion background, their signal can reach energies between 50 and 1000 eV over a few hours or days in the ion spectrum measured by the RPC IES sensor of Rosetta. Over a similar time scale, they gradually lose their energy before disappearing again from the measurements. During these medium-energy ion events, the low-energy ion background is depleted. To explain the observed temporal characteristics of the ion spectrum, we investigated the effects of the dynamic pressure of the solar wind surrounding the comet on the medium-energy ions. We demonstrated that there is a very good correlation between the solar wind pressure and the quantity of medium-energy ions detected by Rosetta: when the solar wind pressure increases, the measured amount of medium-energy ions also increases. Additionally, we observe a significant correlation between ion energy and dynamic pressure as well, although the ion energy is also influenced by other parameters, such as cometary activity and the distance from the nucleus.
Linking Satellite and physics-informed Data with Phytoplankton communities Using Deep Learning
Authors: Ollier Luther , El Hourany Roy , Levy Marina
Published: March 2024

Understanding Phytoplankton community dynamics in response to environmental shifts is crucial for assessing the impact of climate change on marine biology. To this end, satellite observations offer a dataset spanning two decades, capturing diverse sea surface parameters, including temperature, ocean color, and surface height. Notably, ocean color data is processed to derive sea surface chlorophyll-a concentration, widely acknowledged as a reliable proxy for phytoplankton biomass. Lately, advances in ocean color observation allow us to describe the phytoplankton community structure in terms of groups (broad functional or taxonomic groups) or size classes. Although these advances provide more detailed information on phytoplankton diversity and structure, these datasets suffer from spatial and temporal coverage limitations due to strict quality control in the presence of atmospheric aerosols, clouds, sea ice, etc... As a result, studies examining phytoplankton trends over the past two decades and future projections rely on incomplete chlorophyll-a and ocean color data. Therefore this compromises the identification of consistent trends within phytoplankton datasets.In this study, we address this issue using a deep-learning approach. Our method constructs an attention network that learns from the available satellite dataset of Chla and phytoplankton size classes images (weekly and one-degree-degraded spatial resolution) while assimilating information from gap-free sea surface physics data originating from satellite observations and assimilated numerical models). The primary objective is to estimate the phytoplankton dataset based on the knowledge of physical factors, while filling the gaps within this datasetThe trained deep-learning model allows us to discern patterns and correlations between chlorophyll concentration and the phytoplankton size classes on one hand, and the physics-based data on the other hand. From a phytoplankton weekly database spanning from 1997 to 2020, with 50% missing pixels, our approach demonstrates promising results in replicating chlorophyll concentration and accurately inferring phytoplankton size classes.The methodology shows the potential of deep-learning for robust ecological applications but mainly lays the groundwork for future trend studies on phytoplankton communities.
Pyrogenic carbon: Is it a sink in the global carbon cycle? And why we can’t be sure.
Authors: Jones Matthew , Coppola Alysha , Santín Cristina
Published: March 2024

Fires play a critical role in modulating the quantity and quality of carbon (C) stored in the terrestrial biosphere, including in aboveground vegetation and soils. Via riverine transport routes, fires also affect the quantity and quality of C delivered to the global oceans.The mission of this talk is to set the scene on the multifaceted ways in which fire impacts the global C cycle, with a special focus on the widely-overlooked role of pyrogenic C.We will begin by summarising how fires impact on terrestrial stores of C, starting with natural cycles of disturbance and recovery that influence total stocks of C on the terrestrial landscape. We will then demonstrate how shifting fire regimes, related to climate change and changes in land use, are perturbing the cycle of C and influencing the quantity of C stored on the landscape. Increased fire frequency and intensity generally promotes a loss of C from landscapes, especially in cases where vegetation cannot recover completely in the shortening time available between disturbance events.Set within the broader cycle of biogenic C is a sub-cycle of highly recalcitrant ‘pyrogenic’ C – a by-product of incomplete combustion during fires. We will highlight how the special properties of this pyrogenic C promote its longevity in terrestrial stores in a manner that can offset (or ‘buffer’) losses of total C. The process of pyrogenic C storage has been widely overlooked in models of the global C cycle leading to C accounting errors, however we will highlight some recent examples of its implementation in land surface models and the lessons learned from doing so.Due to its exceptional longevity in terrestrial pools, pyrogenic C has enhanced odds of reaching the global oceans via rivers. We will discuss the disproportionate export of pyrogenic C to the global oceans (relative to biogenic C) and how this leads to an unusual potential for long-term C sequestration.Finally, we will provide an overview of the current understanding of the global budget of pyrogenic C, integrating best estimates for the fluxes of C to and from terrestrial stores and to and from marine stores. We will also highlight how uncertainties in the magnitude of fluxes in the C cycle lead to poor understanding of whether pyrogenic C currently acts as a sink or source of C to the atmosphere. We will underscore the particular need to constrain the decomposition rates and residence times of pyrogenic C in soils and marine stores if we are to build a complete picture of its role in the global C cycle.
A semi-analytical approach for flood control reservoir sizing and verification 
Authors: Pirone Dina , Cimorelli Luigi , Andrea D'Aniello , Domenico Pianese
Published: March 2024

Flood control reservoirs help manage floods by temporarily storing excess incoming flow and slowly releasing it. Their design requires estimating the total storable water volume or the maximum allowable discharge of predefined return periods. The design storm approach often represents the state-of-the-art design for flood control reservoirs. This approach transforms the design storm into the design hydrograph and routes it into the reservoir to compute the maximum outlet discharge and, thus, the peak reduction effect. The critical part of this approach is that a plethora of shapes and durations of the design storms can be chosen. Moreover, the runoff process of the contributing catchment area is often neglected; thus, the results can be realistically oversized. Previous studies demonstrated that knowing the discharge hydrograph's shape is unnecessary, and what matters are the incoming volumes. Thus, reservoir designing can also employ the frequency law of the average volume over the duration with return period T, known as the Flow Duration Reduction (FDR) curves. This study exploits FDR curves and proposes a semi-analytical approach to find the maximum outlet discharge a detention pond can reach to store a flood event with a specific return period T. The proposed approach allows a rapid evaluation and comparison of the maximum reduction effect offered by different reservoir configurations, modelling the runoff of the contributing catchment.
Impacts and state-dependence of AMOC weakening in a warming climate
Authors: von Hardenberg Jost , Bellomo Katinka , Mehling Oliver
Published: March 2024

All climate models project a weakening of the Atlantic Meridional Overturning Circulation (AMOC) strength in response to greenhouse gas forcing. However, the climate impacts of the AMOC decline in relation to other drivers of climate change, cannot be assessed from existing Coupled Model Intercomparison Project (CMIP) simulations. To address this issue, we conduct idealized experiments using the EC-Earth3 climate model. We compare an abrupt 4xCO2 simulation with an identical one, except we artificially fix the AMOC strength at preindustrial levels. With this design, we can formally attribute differences in climate change impacts between these two experiments to the AMOC decline. In addition, we quantify the state-dependence of AMOC impacts by comparing the aforementioned experiments with a preindustrial simulation in which we artificially reduce the AMOC strength. Our findings demonstrate that AMOC decline impacts are state-dependent, thus understanding AMOC impacts on future climate change requires targeted model experiments.
Ground CO2 monitoring at Timanfaya volcano (Lanzarote, Canary Islands) during the period 1999-2023
Authors: Di Nardo Daniel , Paglia Silvia , Melián Gladys V. , Pérez Nemesio M. , Padrón Eleazar , Hernández Pedro A. , Rodríguez Fátima , Asensio-Ramos María
Published: March 2024

Lanzarote Island (795 km2) is a volcanic island located in the eastern part of the Canary Islands and approximately 100 km from the NW coast of Morocco. The largest historical eruption of the Canary Islands, Timanfaya, took place during 1730-36 in this island when long-term eruptions from a NE-SW-trending fissure formed the Montañas del Fuego. Tinguaton volcano, the last eruption at Lanzarote Island, occurred in 1824 and produced a much smaller lava flow that reached the SW coast. At present, one of the most prominent phenomena at Timanfaya volcanic field is the high maintained superficial temperatures occurring in the area since the 1730 volcanic eruption. The maximum temperatures recorded in this zone are 605ºC, measured in a slightly inclined well 13 m deep. Since fumarolic activity is absent at the surface environment of Lanzarote, to study the diffuse CO2 emission becomes an ideal geochemical tool for monitoring its volcanic activity. We report herein the results of eight soil CO2 efflux surveys performed from 2006 to 2023 at Timanfaya Volcanic Field (TVF) with the aim to evaluate the temporal variations of the diffuse CO2 emission. Approximately 400 sampling sites were selected at each survey to obtain an even distribution of the sampling points over the study area. Soil CO2 efflux was measured following the accumulation chamber method. Soil temperature at 40 cm depth and soil gas samples collected at each sampling site was also measured to evaluate the chemical and isotopic composition of soil gases. Diffuse CO2 emission values have ranged between non detectable values to 34 g·m-2·d-1, with the highest values measured in September 2008. Conditional sequential Gaussian simulations (sGs) were applied to construct soil CO2 efflux distribution maps and to estimate the total CO2 output from the studied area at the TVF. Soil CO2 efflux maps showed a high spatial and temporal variability. Most of the study area have shown relatively low values, around the detection limit of the instrument (~0.5 g·m-2·d-1). Higher soil CO2 diffuse emission values were observed where thermal anomalies occur, indicating a convective mechanism transport of gas from depth at these areas. Diffuse CO2 emission rates ranged between 41 and 519 t·d-1 during the study period (57 t·d-1 for 2023). Long-term temporal variation on total CO2 diffuse emission shows a peak recorded on winter 2011, suggesting a seasonal control on the CO2 emission. These observations along with the results from the eight soil gas surveys performed at TVF indicate that the short and long-term trends in the diffuse CO2 degassing are mainly controlled by environmental factors.
Geochemistry of tropical coastal lagoon sediments from Sungai Kilim, Langkawi, Malaysia: Implications for provenance and weathering
Authors: Abdul Razak Nur Sakinah , Shouye Yang , Shaari Hasrizal , Ana Cristina Vasquez , Junjie Guo , Xuechao Wu
Published: March 2024

The interaction between land and sea in the coastal zone is dynamic and highly sensitive. It not only records past transgression history, coastal environmental evolution, and sea level changes, but also provides information on climate fluctuations, ocean and river changes, ecological environmental evolution, and human-induced environmental impacts. Coastal zone deposition plays a crucial role in preserving records of paleoenvironment changes and is therefore a key component larger ‘source to sink’ systems at continental margin. Therefore, it has attracted great academic interest in the field of geoscience in recent years. In this study, we measured trace elements and rare earth elements (REEs) in 20 surface sediment samples and a core (LKC 2) collected from the coastal lagoon of Sungai Kilim, Langkawi, Malaysia, to determine the possible sources and to reveal the variations in response to climate change and human activities. The distribution of trace elements (e.g., Li, Ti, Cr, Co, Ni, Cu, Zn, and Mn) was enriched in surface sediments, indicating those elements are affected by human activities. Besides, the concentrations of trace element in LKC 2, combined with AMS dating further confirmed the anthropogenic provenance in the uppermost core layers as a result of deforestation and urbanization in recent decades. However, the low Rb/Sr ratios in surface sediments and LKC 2 corresponds to higher intensity chemical weathering, resulting in higher concentrations of dissolved Sr in the sediments. The enrichment of REEs in surface sediments and LKC 2 indicates typical minerals present in the study area. Overall, the elemental flux patterns observed in this study are responses to complex interactions between intensified human activities and natural climate variability.
Optimising Submarine Cable Routes from Offshore Windfarms – Site Suitability Mapping
Authors: Walsh Kevin , Holloway Paul , Lim Aaron
Published: March 2024

The Irish Government’s Climate Action Plan aims to increase renewable energy generation capacity to 22GW by 2030, with at least 5GW of this to be produced by offshore wind. The potential to harness and develop this resource is significant; however not all areas offshore are suitable. Moreover, not all routes from windfarms to land are suitable for the submarine cables needed to transfer the energy produced offshore back to the onshore grid.This research utilizes geospatial analysis to identify the optimal route selection for offshore export cables. The area under consideration for this research encompasses the South and West coasts of Ireland in the North Celtic Sea and Eastern Atlantic Ocean, areas under intense development for offshore wind, particularly floating wind platforms.To achieve this, a geospatial repository of publicly available data was compiled to ensure the key features related to cable route feasibility were included in the spatial analysis. These layers included bathymetric, geological, and ecological data, as well as information on human activities in the area, to assess the potential hazards to a submarine cable within a particular region. Each variable was assessed as to its importance in the route selection model using criteria weights derived from the Analytical Hierarchical Process and expert opinion of a panel of industry representatives. The resulting data layers were combined into a suitability map of the seabed using a Weighted Overlay Analysis.Individual offshore wind sites and coastal landfall sites were selected based on proposed developments. GIS route selection methods were then implemented, principally the least-cost path algorithm, to identify the optimal route.The combined criteria map produced in this project classifies regions off the South and West coasts of Ireland into zones of suitability for cable routes and highlights the main areas along the coast most appropriate for cable landfall sites.  By using automated route selection tools in GIS along the suitability map surface, realistic paths along the seabed can be quickly designed to allow for adequate burial of the cable, and avoidance of obstacles, hazards and zones of exclusion.The findings of this research indicate that distance from existing coastal substations is a key factor in terms of the economic viability of a cable route. Many windfarms will require more than one export cable, and with several windfarm proposals within the same coastal region, bottle necks at suitable landfall sites may be expected.The results of the study provide a useful tool for policy makers and developers in the planning stage. In a broader context, these findings can be upscaled, customised and applied at a national level for other countries to allow a systematic approach to offshore renewable energy development.
Modeling Uncertainty of Copula-based Joint Return Period of Flood Events under Climate Change
Authors: Manekar Ankita , Ramadas Meenu
Published: March 2024

Modeling the joint behavior of flood characteristics under climate change is necessary for understanding the potential changes in associated flood risk and hazards. In this study, we assessed the changes in flood duration, peak, and volume between historical and future periods through copula-based flood frequency analysis, employing the Soil and Water Assessment Tool (SWAT) hydrological model for modeling flood risk in a tropical watershed (Govindpur) lying in eastern India. Observed streamflow at the watershed outlet is obtained for the baseline period (1990-2014) for flood analysis. A suitable copula model is selected for bivariate flood frequency analysis while assuming copula parameters vary between baseline and future periods under climate change. In this study, high-resolution (12-km) climate reanalysis dataset from the Indian Monsoon Data Assimilation and Analysis (IMDAA) and future climate projections from general circulation models (BCC-CSM2-MR, MPI-ESM1-2-HR) after downscaling and bias correction, are used for simulating flood events using SWAT. The use of high-resolution climate data for hydrological modeling and flood frequency analysis is a novel aspect of the presented study. Uncertainty in the estimation of joint return periods of flood events under climate change due to climate model selection and assumption of stationarity is also quantified in this study for the near future (2041-2070) period under the shared socio-economic pathway (SSP585) scenario. Among the GCMs used, BCC-CSM2-MR performed relatively better in simulating baseline period streamflow in the study watershed. In this study, the Clayton copula is obtained as the most suitable based on its lowest Akaike information criterion (AIC) value, and joint return periods are then derived with the help of a conditional copula. It is found that flood events are projected to become more severe in the near future; the flood peak value increased by more than 90%, while the duration is projected to decrease. Flood volume may likely double in the future, as per our analysis, suggesting the need for mitigation and precautionary measures to reduce flood risk in the watershed. Based on the analysis, uncertainty in flood return period estimation under changed future climate is to be accounted for extreme event studies, and that can aid in managing and minimizing the flood-associated risks.Keywords: Climate Change, Flood Frequency Analysis, Soil and Water Assessment Tool, Copula, General Circulation Model, Uncertainty Analysis
Loss of safe land on atolls highlights need for immediate emissions reductions to support coastal adaptation
Authors: Möller Tessa , Martyr-Koller Rosanne , Kulp Scott , Lissner Tabea , Strauss Benjamin H , Nicholls Zebedee , Nauels Alexander
Published: March 2024

The impacts of climate change and sea level rise are posing substantial threats to the long-term habitability of low-lying atolls. As of today, the sparse data coverage of these islands limits the ability to assess and respond to climate change related risks.
Advances in coastal digital elevation models provide data for very remote coastal regions with low vertical bias. Here, we combine the Intergovernmental Panel on Climate Change regional sea level rise projections under its illustrative emissions scenarios, with the coastal digital elevation model CoastalDEM and COAST-RP, a dataset of storm tide return periods to assess the exposure to rising sea levels and coastal flooding of 166 atolls. Our results show that in 2050 and under a very low emissions scenario (SSP1-1.9), atoll area exposure to SLR and coastal flooding will amount to 35% [34-36%] and that only 64% of atoll area can still be considered safe. By the end of century and under the same scenario, only 61% can be considered safe. Under an intermediate emissions scenario (SSP2-4.5), a scenario roughly capturing projected warming under current policies and actions, the share of safe land further reduces to 58% by 2100. By 2150, only 58% or 51% of the land can still be considered safe under the very low and intermediate emissions scenario respectively. Our results show that the habitability of atolls is already threatened in the near future, but that near-term mitigation can limit the pace at which atolls are flooded in particular beyond 2100. Our results imply that in addition to immediate and rapid emission reductions in line with the Paris Agreement, remaining adaptation options must be enabled and implemented today to reduce the future exposure of atolls.
Greenhouse gas emissions and nitrate leaching as a result of grassland renovation practices
Authors: Ros Mart , van 't Hull Jordy , Velthof Gerard
Published: March 2024

Grasslands are a major sink of organic carbon and for that reason are interesting as a means to achieve national and international climate goals. Grassland renovation (reseeding or conversion to arable land) is a common measure to counteract yield declines in intensively managed agricultural grasslands. The destruction of the sod that accompanies this practice induces a strong increase in mineralization of soil organic carbon and can therefore be a major source of nitrate (NO3) leaching and emissions of carbon dioxide (CO2) and nitrous oxide (N2O). Most farmers prefer reseeding in autumn instead of spring because of better establishment of the sward and low weed infestation. However, limited crop nitrogen (N) demand during autumn increases the risk of NO3 leaching and N2O emissions. Potentially, such N losses could be mitigated by measures such as reducing tillage intensity, reducing fertilizer N application, or applying nitrification inhibitors. In 7 different experiments, we studied the effect of various grassland renovation practices on soil N cycling, greenhouse gas emissions, and nitrate leaching. We hypothesized (i) that conversion to arable land leads to greater CO2 and N2O losses than the reseeding of grassland; (ii) that reseeding in autumn causes enhanced risk of NO3 leaching during winter; and (iii) that these losses can be mitigated by reducing tillage and/or N application rates. Results show that NO3 concentrations in groundwater after harvest were higher for observed after autumn reseeding combined with mitigation strategies than for reseeding in spring. This implies that confining the renewal of grassland to spring season could be a viable strategy to mitigate NO3 leaching. Emissions of N2O varied between experiments and could generally be linked to precipitation events and agricultural management (fertilization and renovation). Grassland renovation led to higher N2O (and CO2) emissions, but the effects of mitigation practices were inconsistent. The results from these experiments will be discussed in more detail. Mitigation strategies for N2O are less straightforward than those for nitrate leaching.