Posters virtual: Wed, 30 Apr, 14:00–15:45 | vPoster spot 4
Climate change significantly impacts the hydrology and water resources of any region especially high mountain areas including cryosphere that consist of glaciers. Numerous studies report that glaciers are retreating and losing volume with time causing serious concerns over freshwater availability in the basins they feed water to. Assessment of these changes and their relationship with various climatic aspects are crucial to understand and tackle such challenges. Long-term trends in temperature and precipitation and their spatio-temporal distribution, for the mountainous state of Uttarakhand in India were assessed, utilizing the India Meteorological Department’s gridded precipitation and temperature datasets for the period 1951-2023. Mann-Kendall trend test was performed at 90% significance level, for each grid, to check monthly trends, which gave critical insights upon shifts in seasonal meteorology. Results reveal notable changes in the monthly distribution of precipitation with many grids reporting a decreasing winter precipitation (Oct-Jan) and many showing an increasing precipitation for May and August. Global warming impact is much visible through changes in minimum temperatures for almost all the grids, reporting a strong positive trend for February, March, August, September and November. Importantly, these changes are more prominent for the high-altitude areas, which highlights elevation dependent climate change pattern. Evidently, the precipitation is shifting from winters to summers and the minimum temperatures are increasing towards the end of ablation season (Aug-Sep), decreasing the chances of receiving solid precipitation or snowfall. Consequently, a decrease in snow cover is expected in the future, which from a hydrological perspective, would lead to a reduction in snowmelt discharge and its contribution to streamflow of the Himalayan perennial rivers. Moreover, the increasing temperature and precipitation during summers can generate huge discharges from glacierized catchments due to increased simultaneous contribution of glacier-melt and rainfall, causing destructive flash floods and debris flow events, as being witnessed in the recent past. Combination of decreased precipitation in winter months and increased temperatures overall, can prove detrimental to glaciers’ health as they will melt more, whereas their replenishment will be lesser, leading to negative mass balances. Climate change is certainly having an adverse effect on the mountain hydrology, especially that of the Himalayan cryosphere. The glaciated catchments are expected to have more glacier-melt and rainfall-runoff contribution and less snow-melt contribution in the near-future. The glaciers, present in the region, are expected to retreat and lose mass more rapidly, considering the meteorological changes in the high elevation areas. Small glaciers might deplete faster, which would lead to problems of freshwater availability in the nearer downstream areas dependent on the melt-runoff water. While there seems no immediate solution to the prevailing scenario of climate change, community-based measures can be adopted to tackle problems of water availability. Water conservation and springshed management in the mountainous regions are some focus areas to work upon, in order to ensure water security under the changing climate.
How to cite: Thapliyal, M., Singh, S., and Patel, L.: Climate Change and its Impact on the Hydrology of a Glaciated Mountainous Region, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4832, https://doi.org/10.5194/egusphere-egu25-4832, 2025.
This study investigates the spatio-temporal variability and long-term warming trends in sea surface temperature (SST) across the Arabian Sea from 2000 to 2019, using daily AVHRR satellite observations with a 1°x1° spatial resolution. Seasonal and interannual SST dynamics reveal patterns shaped by monsoonal processes and global climate phenomena, such as El Niño and La Niña. Wavelet spectrum analysis highlights periodic fluctuations and dominant frequencies associated with interannual climate variability, further emphasizing the influence of seasonal processes. Spring (MAM) exhibits the most pronounced interannual warming, particularly in the central and northern regions, while autumn (SON) demonstrates significant warming trends, especially in the southern basin. Monsoonal processes influence seasonal variability, with winter (DJF) cooling in the northern Arabian Sea and summer (JJA) upwelling along Oman and Somalia, resulting in localized cooling amidst broader warming trends in central and southern regions. Wavelet power spectra from critical regions, including the Gulf of Oman, Balochistan Coast, and Mumbai, indicate dominant periodicities of interannual warming, with variations corresponding to regional oceanographic processes. For instance, the Balochistan Coast displays the highest warming rate (0.0519°C/year), underscored by strong wavelet power at periodicities tied to El Niño–Southern Oscillation (ENSO) cycles. Similarly, the Gulf of Oman and Mumbai exhibit distinct spectral peaks, reflecting localized climate dynamics and variability. Regionally, the warming trend varies significantly. The Gulf of Aden (0.0181°C/year), Gulf of Oman (0.0164°C/year), and Gulf of Kutch (0.0269°C/year) exhibit moderate warming rates, while areas like the Balochistan Coast and South of Salalah (0.023°C/year) highlight significant localized warming. Southwestern Arabian Sea regions west of Kochi (0.0209°C/year) and Mangalore (0.0323°C/year) also demonstrate notable trends. In contrast, regions like Minicoy (0.0162°C/year) and the Male-Maldives area (0.0073°C/year) show relatively weaker warming. These findings underscore the critical role of spatial and seasonal variability in shaping SST changes and their implications for regional climate patterns, monsoonal behavior, marine ecosystems, and fisheries. The pronounced warming in key regions, coupled with insights from wavelet spectrum analysis, highlights the influence of localized oceanographic processes, such as upwelling, heat transport, and climate-induced variability. These results necessitate further study to assess future impacts and develop mitigation strategies for sensitive marine biodiversity and economic resources in the Arabian Sea .
How to cite: Saha, S. and Mukherjee, A.: Unraveling the Arabian Sea’s Thermal Pulse: Seasonal and Interannual SST Variability Amidst Climate Dynamics, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12429, https://doi.org/10.5194/egusphere-egu25-12429, 2025.
SnowMapPy is a Python-based package developed to streamline the collection, preparation, and analysis of MODIS NDSI data, specifically from the Terra and Aqua satellite products. By automating essential steps (data clipping, reprojection, filtering, and time series generation), SnowMapPy improves the efficiency and precision of snow hydrology research. The protocol allows users to work with both local and Google Earth Engine cloud-based datasets, enabling flexible data acquisition and processing tailored to the needs of snow hydrology, water resource management, and climate change studies. Designed for accessibility and flexibility, SnowMapPy supports large-scale, high-resolution snow cover analysis with minimal configuration. The package facilitates customized workflows through its modular structure, making it a valuable tool for researchers aiming to understand snow dynamics and their impact on seasonal water resources.
How to cite: Elyoussfi, H., Boudhar, A., Belaqziz, S., Bousbaa, M., Bechri, H., Sproles, E. A., and Benzhair, F.: SnowMapPy v1.0: A Python Package for Automated Snow Cover Mapping and Monitoring in Mountain Regions , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20632, https://doi.org/10.5194/egusphere-egu25-20632, 2025.
Ice crevasses are pervasive features across the Arctic and Antarctic ice sheets. These deep, open fractures in the ice surface serve as critical conduits for transporting surface meltwater into the englacial system, significantly impacting ice sheet hydrology and stability. Accurate mapping of the spatial and temporal distribution of ice crevasses is vital for advancing our understanding of ice sheet dynamics and their evolution. Remote sensing technology provides a robust platform to achieve this purpose, while the rapid advancement of machine learning algorithms offers substantial benefits for automated crevasse detection, facilitating efficient and large-scale mapping. This study conducts a comprehensive comparison of the performance of various machine learning models, including CNN, U-Net, ResNet, and DeepLab, for ice crevasse extraction. Through quantitative evaluation metrics and visual inspection, the optimal machine learning model was selected to map ice crevasses on Antarctic ice shelves using multi-source remote sensing data, such as SAR and optical satellite imagery. Furthermore, this work explores the strengths and limitations of various machine learning in detecting ice crevasse and proposes potential solutions for further refinement. This study aims to contributes to enhancing ice crevasse detection and offering robust ice crevasse datasets, which is crucial for reliable analyzing the dynamic of the Antarctic ice sheet in the future.
How to cite: Liang, S. and Xiao, X.: Antarctic ice shelf crevasse detection using multi-source remote sensing data and machine learning, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19031, https://doi.org/10.5194/egusphere-egu25-19031, 2025.
Between Sept. 4, 2023, and Sept. 12, 2023, a cyclogenesis develops close to the Greek coast in the Ionian Sea. The evolution of this cyclone is divided into two phases: a strongly baroclinic one with intense orographic precipitation in Greece, and a final barotropic phase with the formation of an intense tropical-like cyclone (TLC) impacting Libya. In this work, we investigate this TLC (named “Daniel”) initially using the standalone WRF model with different sea surface temperature sources, untile the use of the coupled atmosphere-ocean models. Preliminary results show that SST plays a crucial role in the intensification and tropicalization of the cyclone, with a strong impact not only along the cyclone track but especially in the neighboring areas, where high values of heat transport a precipitable water are found. We also observe how the use of a coupled model as a digital twin, shows strengths in the quality of the simulation and the physics of the process, but highlights some critical issues in the configuration of the marine model, which at small technical variations produces intense changes in the structure of the ocean and atmosphere.
How to cite: Ricchi, A., Ferretti, R., Pantillon, F., Dafis, S., Menna, M., Martellucci, R., Serafini, P., and Carrió, D. S. C.: On the role of air-sea-wave interaction in developing destructive Tropical-Like Cyclones DANIEL, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17499, https://doi.org/10.5194/egusphere-egu25-17499, 2025.
A wide range of problems in oceanic mass and energy transport involve learning submesoscale surface flow fields from diurnal geostationary satellite observations. Yet, traditional methods, such as the Maximum Cross-Correlation (MCC) algorithm, suffer from limited spatiotemporal resolution and extensive post-processing. Here, we present the RAFT-Ocean architecture, a deep neural network-based approach for learning submesoscale flow fields in pixel-to-pixel manner, to retrieve submesoscale surface flow fields from geostationary satellite data. Compared to the MCC algorithm, the RAFT-Ocean architecture significantly improves these methods, reducing the end-point error (EPE) uncertainty by more than 65% and the absolute angular error (AAE) by more than 55%. The RAFT-Ocean architecture, when transferred to the geostationary ocean color satellite (GOCI/CMOS and GOCI-II/GK2B) sea surface chlorophyll-a products for diurnal hourly flow field retrieval, produced more realistic, continuous, and refined sea surface flow field data compared to geostrophic flow data from altimeter data. The refined diurnal hourly flow field matched well with the filamentous structure of surface phytoplankton, demonstrating an advantage in spatiotemporal resolution for kinetic energy transfer across scales. This approach enhances flow field retrieval quality and opens new avenues for real-time marine environment monitoring and modeling.
How to cite: Ding, X., Zhao, M., and Li, H.: Deep learning for submesoscale surface flow retrieval from geostationary satellite observations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2306, https://doi.org/10.5194/egusphere-egu25-2306, 2025.
Breaking internal gravity waves cause small-scale turbulent mixing, which changes water mass properties, affects biogeochemical cycles, and contributes to driving the large-scale overturning circulation. Ocean general circulation models do not resolve this process and thus rely on a parameterization. The state-of-the-art IDEMIX (Internal wave Dissipation, Energy and MIXing) model predicts the propagation and dissipation of internal wave energy based on external forcing functions that represent the main generation mechanisms, notably the internal tide generation at the sea floor and the near-inertial wave generation at the sea surface. By linking small-scale mixing to internal wave energetics, IDEMIX allows the consistent parameterization of wave-induced mixing in ocean models. Its basic incarnation treats all internal waves as part of a horizontally homogeneous continuum and was shown to successfully reproduce observed turbulent kinetic energy dissipation rates and internal wave energy levels. In a newer configuration (IDEMIX2), the internal wave field is compartmentalized, distinguishing between a high-mode continuum on the one hand and low-mode near-inertial wave and internal tide compartments, whose horizontal propagation is explicitly resolved in wavenumber angle space, on the other hand. We present the evaluation of the IDEMIX2 model with a particular focus on the impact of applying an anisotropic internal tide forcing. So far, parameterizations of internal tide-driven mixing have not taken the strong anisotropy of the internal tide generation process into account. We demonstrate the need for doing so, showing a notable impact on the modeled internal wave energetics and predicted mixing when changing from the previous isotropic to the new anisotropic tidal forcing in IDEMIX2.
How to cite: Pollmann, F., Eden, C., Olbers, D., Nycander, J., and Zhao, Z.: Anisotropic internal tide forcing in the consistent internal wave mixing scheme IDEMIX, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8764, https://doi.org/10.5194/egusphere-egu25-8764, 2025.
This study is part of a doctoral research project aimed at characterizing coastal sediments in relation to the presence of microplastics and marine litter. Within this framework, the present research seeks to establish an up-to-date knowledge base regarding the geochemical characterization of sediments across different seasons along the Ferrara coastal area, specifically at Lido degli Estensi (Ferrara, Italy). The objective is to identify potential vulnerabilities and/or critical aspects related to environmental pollution that require further investigation. Building upon the methodology of Aquilano et al. (2023) and adapting it to the experimental requirements of the current study, a research area was selected at Lido degli Estensi, outside zones allocated for tourism-related public concessions. This site is located on the southern side of the Porto Garibaldi navigation channel (Comacchio municipality, Ferrara), in a coastal section experiencing accretion due to the construction of artificial jetties at the port-channel entrance. These jetties trap sediment transported from the south as a result of longshore drift. Given the beach's width (approximately 150 m), a cross-shore profile was divided into five zones based on specific geomorphological characteristics: swash zone, lower backshore, upper backshore, dune scarp, and dune. Along this beach profile, variations in carbonate content, major oxide composition, and heavy metal concentrations were investigated across different seasons using eight sampling points per season. To evaluate sediment quality in terms of heavy metal contamination, the following indices were employed: Enrichment Factor (EF; Reinmann and De Caritat, 2005), Geoaccumulation Index (Igeo; Buccolieri et al., 2006), Contamination Factor (CF; Loska et al., 2004), and Pollution Load Index (PLI; Ferreira et al., 2022). Furthermore, heavy metal concentrations detected in the samples were compared with the limits established by current Italian legislation (Legislative Decree 152/06). This study was conducted as part of the ECS_00000033_ECOSISTER project, funded under the National Recovery and Resilience Plan (NRRP), Mission 04 Component 2 Investment 1.5 – NextGenerationEU (Call for Tender No. 3277, dated 30/12/2021).
How to cite: Buoninsegni, J., Marrocchino, E., Tassinari, R., Tessari, U., and Vaccaro, C.: Geochemical characterization of coastal sediments: a preliminary study of seasonal variations at Lido degli Estensi (Ferrara, Italy), EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3582, https://doi.org/10.5194/egusphere-egu25-3582, 2025.
Climate Change is expected to increase the intensity and frequency of extreme rainfall events in the coastal areas of Patagonia (Southwest Atlantic Ocean, SWAO). These events carry heavy loads of terrestrial materials and nutrients, and minor components such as kaolin and ash, into coastal areas through riverine inputs. The Chubut River estuary was used a reference coastal ecosystem in the SWAO. In its lower course, the river is diverted into irrigation channels that supply water for agricultural activities. These channels are open from spring to early autumn, increasing the runoff of terrestrial material, and are closed during the rest of the year. Furthermore, kaolin mines are located in the upper course of the river and ash deposition coming from volcanos have been registered. A monitoring of terrestrial material of the Chubut River estuary was conducted and the attenuation coefficients of the different components were evaluated, including terrigenous material, kaolin, and ash. The findings show that the terrestrial material, estimated as dissolved organic carbon (DOC), doubles during rainfall conditions and when irrigation channels are open. During extreme rainfall events, DOC concentrations increased by up to fivefold compared to normal conditions, being the main attenuator in the river. This resulted in a PAR attenuation coefficient variable between 1.3 m-1 under baseline conditions (closed channels, no rainfall) to over 8 m-1 following extreme rainfall events in the outer regime (seawater side) of the estuary. Further monitoring of the different under-studied estuarine components in the SWAO and their effects on the attenuation coefficient is crucial for primary productivity studies.
How to cite: Vizzo, J. I., Helbling, E. W., and Villafañe, V. E.: Inputs of Terrestrial Material, Kaolin and Ash into Coastal Patagonian Waters and their Effects on the Attenuation Coefficient of the Chubut River Estuary (Argentina), EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-434, https://doi.org/10.5194/egusphere-egu25-434, 2025.
We have previously developed a 12-sample environmental DNA (eDNA) sampler designed for use in the marine surface. The sampler can collect and store eDNA samples on filter cartridges according to scheduled sequences. Communicating via mobile phone networks also makes it possible to collect samples on demand. For the underwater eDNA sample-return missions, we have designed and developed a compact eDNA sampler with an oil-filled (pressure-balanced) configuration, enabling its deployment at various depths. Field trials for the underwater eDNA sampler were performed using underwater platforms such as deep-sea landers. Here, we introduce the newly developed compact eDNA sampler and discuss its potential applications in mid- to deep-ocean layers, focusing on eDNA sample-return missions targeting jellyfish and other marine species.
How to cite: Fukuba, T. and Lindsay, D.: Development of an underwater eDNA sampler and its potential application in jellyfish eDNA detection, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14703, https://doi.org/10.5194/egusphere-egu25-14703, 2025.
The coastal ecosystems, including estuaries and mangroves, are highly vulnerable to anthropogenic intervention, particularly due to activities such as urbanization, wastewater discharge, and industrial development, which can alter their ecosystem services and affect habitat quality. In order to evaluate the impact of these interventions through the carbon and nitrogen isotopic composition of two macroalgae Boodleopsis verticillata and Bostrychia spp in four coastal ecosystems of the Colombian Pacific (Valencia - VAL, San Pedro - SPE, Chucheros – CHU with low intervention, and Piangüita - PIA with high intervention) were used to understand the sources of these elements. δ15N values is a commonly used to providing information about nitrogen sources in primary producers. δ13C values is used to investigate carbon sources i.e. terrestrial or marine. Samples were collected during 2014, 2015, and 2016, and analyzed by isotope ratio mass spectrometer. The results show that the δ13C values ranged from -33.97 to -31.93 ‰ in VAL, -33.78 to -30.09 ‰ in SPE, -31.12 to -28.45 ‰ in CHU, and -33.32 to -21.71 ‰ in PIA. δ15N values ranged from 0.32 to 3.18 ‰ in VAL, 0.57 to 5.47 ‰ in SPE, 1.82 to 3.39 ‰ in CHU, and 2.32 to 10.16 ‰ in PIA. Significant differences were found among the four areas with mean δ13C values by locality (VAL -30.21 ‰, SPE -31.71 ‰, CHU -30.09 ‰, and PIA -30.52 ‰) and δ15N values (VAL 1.74 ‰, SPE 2.30 ‰, CHU 2.40 ‰, and PIA 4.47 ‰) reflecting the impacts of human activities on the coastal ecosystems. This work contributes to understanding the effects of anthropogenic intervention on pollution and wastewater discharge in coastal ecosystems, providing key tools for the development of environmental management policies that support conservation in the Colombian Pacific.
How to cite: Arce-Sánchez, R. S., Medina-Contreras, D., and Sánchez-Gonzalez, A.: Primary producers as indicators of anthropogenic intervention in the Colombian Pacific, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7292, https://doi.org/10.5194/egusphere-egu25-7292, 2025.
This study explores the seasonal and lagged correlations between Chlorophyll-a (Chl-a) concentrations and vertical velocity (wT) to elucidate upwelling's role in driving phytoplankton productivity. In Oman (Region III), an immediate response to upwelling was observed, with the strongest correlation (r = 0.7) at lag 0 during peak upwelling months (June–July). In contrast, Iranian regions (I & II) exhibited delayed responses, with maximum correlations (r = 0.7) at lag 1 (occurring about a month later). This delay may result from processes like nutrient mixing and remineralization. Seasonal trends revealed sustained Chl-a concentrations in Oman, peaking at 2.39 mg m-3 in September, while Iran showed a steady decline after a July peak of 1.37 mg m-3. Stratification and horizontal currents modulated Chl-a distributions, with weaker stratification in Oman enabling efficient nutrient delivery. These findings reveal the intricate dynamics of upwelling-driven productivity across both semi -enclosed and open marine ecosystems. By examining regional variations in the context of broader oceanographic processes, this study offers valuable insights for the sustainable management of upwelling systems and for anticipating their responses to climate change.
How to cite: A. Ismail, K. and Salim, M.: Unveiling the Impact of Upwelling on Phytoplankton Productivity in the Arabian/Persian Gulf and Sea of Oman, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20989, https://doi.org/10.5194/egusphere-egu25-20989, 2025.
