The rapidly changing Arctic climate has far-reaching implications for global weather systems, particularly through teleconnections that link high-latitude processes to tropical regions. This study unravels the impact of Barents-Kara (B-K) region sea ice anomalies during the spring season (March-May) on the Indian Summer Monsoon Rainfall (ISMR) patterns from 1959 to 2021. By analyzing low- and high-sea-ice years, the study reveals contrasting atmospheric circulation patterns that drive monsoonal variability over India. During low-sea-ice years, weakened ice cover over the Arctic induces negative sea level pressure anomalies in summer over the Arctic region. This triggers cyclonic activity, which initiates southward-propagating Rossby wave trains. The wave train exhibits a distinct ridge-trough-ridge-trough pattern as it propagates from Europe to the Far East and towards the North Pacific. This atmospheric configuration shifts the subtropical westerly jet southward, enhancing subsidence and suppressing monsoonal convection over the Indo-Gangetic Plain, ultimately reducing the ISMR. Conversely, high-sea-ice years exhibit a reversed pattern, with negative geopotential height anomalies over the Arctic and a ridge over central Asia. This promotes upper-level divergence, enhancing convection and strengthening monsoonal rainfall over the Indo-Gangetic Plain. These findings reveal the critical role of springtime B-K sea ice in shaping summer atmospheric circulation and monsoonal rainfall patterns over India, highlighting the far-reaching impact of Arctic Sea ice variability on tropical weather systems.
How to cite: Sardana, D. and Agarwal, A.: Impact of Spring Sea Ice Variability in the Barents-Kara Region on the Indian Summer Monsoon Rainfall , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18136, https://doi.org/10.5194/egusphere-egu25-18136, 2025.
The Indian Summer Monsoon (ISM) is one of the most energetic components of the Earth system observed during the boreal summer. As a crucial freshwater source and a lifeline for billions, the ISM has been extensively studied to understand its variability and improve its predictability. However, accurately predicting the ISM remains challenging due to the shifting dynamics of established drivers and the increased influence of emerging teleconnection patterns. In recent years, the Arctic region, a hotspot of climate change, has emerged as a driver of global climate, with its influence hypothesized to extend from the mid-latitudes to the tropics. The strength of the large-scale ISM circulation has been found to influence summer Arctic sea ice through the monsoon-desert mechanism. Understanding and quantifying the two-way interactions between Arctic and ISM systems is crucial, as these teleconnections may help improve the predictions of extreme weather events and seasonal forecasts. Although a few studies have focused on quantifying the association between Arctic sea ice and the Indian Summer Monsoon, the causal mechanisms are yet to be fully explored. Traditional statistical methods for analyzing climate variability have primarily relied on correlations and composite analysis, which have several limitations. This study quantifies the Arctic-ISM teleconnections using a causal inference approach. This technique allows us to evaluate the importance and magnitude of tropical and extratropical drivers of ISM circulation and seasonal variability while controlling for confounding mechanisms. Furthermore, we examine the role of state dependencies, such as the phase of ENSO in modulating the strength of these causal pathways.
How to cite: kulkarni, S., Agarwal, A., and Kretschmer, M.: Causal Pathways connecting Indian summer monsoon to the Arctic sea ice decline, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2087, https://doi.org/10.5194/egusphere-egu25-2087, 2025.
The Arctic has warmed at more than twice the global mean rate in recent decades, resulting in rapid changes to the northern high latitude Earth system. This includes changes to essential climate variables and associated physical hazards, such as temperature, precipitation, storminess, and cryosphere conditions - in turn posing emerging impacts/risks for society and ecosystems. Here we use data from four large ensembles and perform a detailed and systematic characterization of the distribution and variability of key physical climate hazards across the high latitude and polar regions.
Climate change is known to manifest as shifts in the means and extremes of the variables but can also affect the shapes of their distributions. As highlighted in existing literature, comprehensive understanding of climate risk therefore involves quantification of the full, regional Probability Density Functions (PDFs), as these contain information on expected weather not apparent from the distribution mean or tails. Large initial condition ensembles of coupled climate model simulations have opened new opportunities for studying climate variability and how it evolves with warming, as well as diversity across models, in more detail. Building on methodology from Samset et al. (2019), we consistently quantify regionally (focusing on the northern hemisphere) and seasonally resolved PDFs of daily data for different scenarios and levels of global warming. The analysis also includes a reality check of model performance against reanalysis data for the recent past. Chosen hazards include core ETCCDI climate change indices, as well as specific indices identified of relevance to high latitude impacts through work in the EU Horizon 2020 project CRiceS.
Rapid warming and associated environmental changes are having increasingly significant socioeconomic consequences for high latitude settlements and populations. Our results provide a comprehensive picture of the projected evolution of high latitude climate impact drivers, providing knowledge of high relevance for further assessment of climate risk.
How to cite: Lund, M. T., Schuhen, N., and Samset, B. H.: Evolution of high latitude climate hazards with global warming in large climate model ensembles, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12157, https://doi.org/10.5194/egusphere-egu25-12157, 2025.
Numerous studies have highlighted the simultaneous relationship between the Arctic Oscillation (AO) and weather/climate in Asia. However, the stability of the precursor signals in AO for Asian surface air temperature (SAT), which is important for short-term climate prediction, has received little attention. In this study, a strengthened relationship is identified between the late-winter AO and the early-spring SAT over North and Northeast Asia (NNA) around the 1990s. During 1990–2022, a positive (negative) phase of AO during late winter is generally followed by significant warming (cooling) anomalies in the NNA during early spring, whereas this relationship is insignificant during 1961–1987. Further result shows a good persistence of the late-winter AO to early spring after the 1990s. Accordingly, the AO exerts a strengthened impact on Mongolian anticyclone and Asian westerly anomalies through modulation of a Rossby wave train that propagates from the Arctic to the NNA in early spring, leading to significant SAT anomalies at NNA. Additionally, the AO-related temperature anomalies intensified in the stratosphere after the 1990s, linking AO and stratosphere polar vortex (SPV). The intensified (weakened) SPV following positive (negative) AO facilitates warming (cooling) anomalies at NNA via downward-propagating Eliassen-Palm fluxes at wave number 1 and circumpolar westerlies in middle and lower troposphere. The seasonal persistence of AO and the strengthened relationship between AO and SPV synergistically enhance the influence of late-winter AO on early-spring SAT in the NNA, which might be attributed to the interdecadal changes in background circulation over the Arctic.
How to cite: Han, T. and Zhou, X.: Enhanced Influence of Late-winter Arctic Oscillation on Early-spring Temperature in North and Northeast Asia, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1243, https://doi.org/10.5194/egusphere-egu25-1243, 2025.
This study examines the interannual variability of the summer precipitation dipole pattern over northern eastern China, utilizing precipitation data and atmospheric reanalysis data from 1961 to 2020, along with an analysis of its underlying influencing mechanisms. Results indicate that the second mode of empirical orthogonal function (EOF2) mode of summer (June–August) precipitation in Northeast China presents a dipole pattern with opposite trends in the north and south, and its time series (PC2) demonstrates signifcant interannual variations. The South-North dipole pattern in summer precipitation over Northeast China are signifcantly correlated with the tropical Pacific sea surface temperature, Arctic sea ice, and Eurasian snow cover in the preceding spring (March–May) on an interannual scale. In the preceding spring, the increase in sea surface temperatures in the eastern equatorial Pacific, coupled with a decrease in temperatures in the western equatorial Pacific, stimulated the East Asia-Pacific and Eurasian teleconnections by weakening the Walker circulation near the equator. This alteration positioned a cyclonic center over Northeast China, subsequently influencing the dipole pattern of precipitation in the region. Furthermore, the anomalies in European snow cover and Arctic sea ice can lead to an increase in albedo and a decrease in upward heat flux, causing the lower atmospheric temperature to drop and persist into the summer. This causes the atmospheric Rossby wave to propagate eastward in the middle and high latitudes, promoting precipitation in the northeast through the occurrence of negative potential height anomalies over the Far East. These conditions influence the anomalies in the atmospheric circulation over the Eurasian continent, regulate moisture transport and vertical motion, and collectively contribute to the dipole pattern of summer precipitation in Northeast China over the past 60 years, with opposite trends in the north and south.
How to cite: Shu, X. Y. and Wang, S. S.: Characteristics and mechanism analysis of dipole precipitation in Northeast China, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4665, https://doi.org/10.5194/egusphere-egu25-4665, 2025.
The connection between the tropical and Arctic climates exerts an important impact on the climate in Northern Hemisphere. This study finds that the connection between sea surface temperature anomalies (SSTA) of the central tropical Pacific and semi-circumpolar jet have enhanced during summer after mid-1980s. Our results indicate that the internal variability of Atlantic Multidecadal Oscillation (AMO) has a major influence on the enhanced connection, while the anthropogenic greenhouse gases forcing and aerosol forcing play minor roles. During the period of positive AMO phase, the warm SSTA of central tropical Pacific elicit an enhanced anomalous cyclone in northwestern Pacific, which is favorable for reinforced poleward Rossby waves and enhanced polar vortex. The intensification of the polar vortex enhances the meridional pressure gradient, which amplifies the intensity of semi-circumpolar jet. Furthermore, the anthropogenic forcing amplifies the response of tropical lower tropospheric moisture anomalies induced by the SSTA in the tropical Pacific. These moisture anomalies generate a positive feedback loop of downward latent heat, which further intensifies the SSTA over tropical Pacific and consequently reinforces the response of the semi-circumpolar jet. The findings in this study demonstrate significant changes in Arctic-tropical connection of climates due to combined effect of internal variability and external forcings.
How to cite: Li, W. and Sun, B.: Enhanced impact of tropical Pacific on semi-circumpolar jet attributed to internal variability and anthropogenic forcing, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4659, https://doi.org/10.5194/egusphere-egu25-4659, 2025.
The South Pacific Meridional Mode (SPMM) is a dominant air-sea coupling mode in the subtropical southeastern Pacific and a key precursor of equatorial Pacific variability. However, the mechanisms responsible for its distinct seasonality remain inadequately understood. Using reanalysis datasets, we conducted an ocean mixed-layer heat budget analysis to quantify the contributions of dynamic and thermodynamic processes to SPMM seasonality. Results show that while net surface heat flux dominates the sea surface temperature warming associated with SPMM in both boreal summer and winter, this warming is significantly dampened by meridional advective feedback in summer (approximately 47%) but weakly in winter (approximately 14%). Further analysis reveals that the meridional advective feedback is primarily attributed to Ekman heat transport driven by anomalous zonal wind stress. These findings underscore the critical role of meridional advective feedback in modulating SPMM seasonality and provide valuable insights for improving climate predictions related to the SPMM.
How to cite: Xu, J., Yang, S., Fan, H., Cai, Y., Collins, M., and Yu, W.: Observed Seasonality of the South Pacific Meridional Mode: The Role of Oceanic Meridional Advective Feedback, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13904, https://doi.org/10.5194/egusphere-egu25-13904, 2025.
Some traditional, climate-oriented sea surface temperature (SST) observational datasets do not generally include satellite data and are typically based on in-situ observations with a coarser spatial resolution (1 to 2 degrees), prominent examples being the Extended Reconstructed SST from NOAA (ERSST) and the Hadley Centre SST, version 3 (HadSST3). Other datasets combine both, in-situ and satellite observations, such as the Hadley Centre Sea Ice and Sea Surface Temperature dataset (HadISST).
The main objective of this work is twofold. First, we globally characterize and compare SST climatology and variability at grid-point level, considering seasonal averages (DJF, MAM, JJA, SON), between two standard, climate-oriented datasets, HadISST (1° resolution) and ERSST v5 (2° resolution), with the GHRSST product developed by the European Space Agency Climate Change Initiative (CCI) (0.05° resolution). Secondly, we assess the impact of temporal and spatial resolution in such SST characterization as well as on air-sea interaction, estimated by correlating SST with turbulent heat flux (THF; latent plus sensible). The study spans over 1982-2016 (35 years) that corresponds to the record of the satellite product (CCI).
Our results show that the coarser datasets (ERSST-HadISST) overall have a warmer mean-state, except in the more dynamically-active oceanic regions such as the western boundary currents where they yield a colder SST climatology. More interestingly, the high-resolution dataset (CCI) markedly displays larger SST variability in these dynamically-active oceanic regions, which is consistent along the seasonal cycle. Likewise, we also find higher correlations between SST and THF over the western boundary currents in CCI as compared to ERSST-HadISST, indicating a stronger ocean-atmosphere coupling. Our results suggest that the high temporal and spatial resolution provided by remote sensing is key to better resolve air-sea interaction.
How to cite: González-Haro, C., García-Serrano, J., García-Espriu, A., and Turiel, A.: Have we been underestimating midlatitude air-sea interaction?, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10933, https://doi.org/10.5194/egusphere-egu25-10933, 2025.
Causal questions are fundamental to scientific exploration. The study of causality and its applications has followed a nonlinear trajectory, shaped by diverse methodological developments and debates about their interpretations. Here, we unravel the evolution of these approaches, from Judea Pearl’s formal framework of causal inference (Pearl, Causality, 2009) to methods based on reductions in informational surprise, multivariate probability, and dynamical systems (Kondrashov et al., Physica D, 2015). While principled causal inference ideally relies on Pearl’s framework, its application is often unfeasible. Instead, methods grounded in information theory, combined with prior knowledge of the system, are widely used to assist in the causal inference process. Recent advances include nonlinear, higher-order information-theoretic approaches (Stramaglia et al., Phys. Rev. Res., 2024).
These methods are increasingly applied in Earth and climate sciences to address questions such as the causes of extreme events and global warming, or to explore the mutual influences between the ocean and atmosphere in driving the climate system. A key unresolved question concerns the nature of this interaction: does atmospheric weather drive the ocean, does the ocean steer the atmosphere, or does a coupled mode of variability govern the system?
In this context, we investigate the reciprocal influences of ocean and atmosphere using a low-order coupled ocean-atmosphere model that includes realistic thermal and mechanical coupling (Vannitsem et al. Physica D, 2015). By applying Transfer Entropy (Schreiber, Phys. Rev. Lett., 2000) and the Liang and Kleeman (Liang, Entropy, 2021) Information Flow, we analyze the dynamical directions within the coupled system. We uncover the directed dynamics of information exchange, adding insight on the emergence of low-frequency variability in the atmosphere. These results offer a new perspective on interannual and decadal-scale climate prediction.
How to cite: Zelco, C., Carrassi, A., Ghil, M., Marinazzo, D., and Vannitsem, S.: Unraveling ocean-atmosphere coupled variability with Transfer Entropy and Information Flow , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15880, https://doi.org/10.5194/egusphere-egu25-15880, 2025.
Missing data in Korea Ocean Research Stations (KORS) poses significant challenges for accurate oceanographic modeling and analysis. Such data gaps frequently occur during summer typhoon seasons, often spanning extended periods due to severe weather conditions. This study introduces a multi-layer perceptron neural network (MLP-NN) for missing data imputation, using reanalysis data as inputs. Reanalysis data are utilized as reference data to provide context on potential ocean events during missing periods. The model is trained and validated on periods with available observations, learning to utilize reanalysis data as supplementary inputs while aligning with observational patterns. The trained network is then applied to missing periods, utilizing reanalysis data to impute gaps. The test results show that the proposed model performs exceptionally well in filling long-term data gaps, demonstrating its robustness and reliability. Notably, the predicted water temperature exhibits high accuracy in reproducing abrupt drops and subsequent recoveries, which are often observed during typhoon periods. By utilizing reanalysis data for gap imputation, the method achieves high accuracy in reconstructing missing values, significantly enhancing the completeness and utility of datasets from ocean research stations for scientific and operational purposes.
How to cite: Kim, N.-H., Park, S.-H., Jeong, J.-Y., Choi, J.-Y., Min, Y., and Heo, K.-Y.: A multi-layer perceptron approach for missing data imputation in ocean research stations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7831, https://doi.org/10.5194/egusphere-egu25-7831, 2025.
Water masses in the upper ocean play a critical role in modulating ocean stratification and circulation, serving as pathways for atmospheric signals to penetrate the ocean interior and influencing climate variability and marine ecosystems. The North Pacific Subtropical Mode Water (STMW) is a distinct water mass in the northwestern subtropical gyre of the North Pacific Ocean. Although previous studies have extensively highlighted the importance of investigating variations in STMW properties, they predominantly treated STMW as a homogeneous entity, overlooking differences across its different density ranges.
Building on this foundation, we examined spiciness anomalies (density-compensated salinity and temperature anomalies) and isopycnal thickness anomalies within STMW based on Argo observations from 2004 to 2018, with a focus on the comparisons between its lighter (L-STMW) and denser (D-STMW) portions.
Firstly, we investigated interannual to decadal variations in STMW properties across different density ranges. The isopycnal thickness anomalies exhibited a seesaw pattern between L-STMW and D-STMW, separated by a threshold at γ = 25.3 (Figure 1). The volume of D-STMW was primarily governed by decadal variability linked to the Kuroshio Extension, while L-STMW displayed weaker decadal variability with a different phase, as well as stronger interannual and seasonal variations. In contrast, STMW salinity and temperature showed consistent variations across different density ranges.
Secondly, the propagation patterns of thickness and potential vorticity (PV) anomalies differed markedly between L-STMW and D-STMW. For D-STMW, thickness and PV anomalies propagated steadily downstream from the southern edge of the outcrop area to the northern region of the southwestern corner of the gyre. In contrast, L-STMW experienced signal intrusions during certain years, likely caused by off-stream southward transport driven by mesoscale eddies, potentially influenced by topographic effects. However, spiciness anomalies in STMW displayed consistent downstream propagation on all the isopycnals, without significant difference between L-STMW and D-STMW.
These results provide insights into the seesaw structure of mode water variability and may offer broader implications for discovering similar processes in other ocean basins.
Fig. 1 Annual mean thickness anomalies of each 0.05 γ range, averaged in 20–30°N.
How to cite: Wang, T., Suga, T., Kouketsu, S., Schneider, N., Qiu, B., Richards, K., and Osafune, S.: Water mass spiciness and thickness anomalies, and their propagation in the North Pacific Subtropical Mode Water, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17502, https://doi.org/10.5194/egusphere-egu25-17502, 2025.
Large-scale ocean circulation modulates weather and climate patterns by distributing heat, nutrients, and carbon dioxide within and across ocean basins. The large-scale circulation is driven by processes at the ocean's surface (such as wind stress and heat/freshwater fluxes) and steered by processes in the ocean's interior (such as mesoscale eddies and flow-topography interactions).
Ocean gyres are generally thought to be driven by wind stress at the ocean's surface, however recent results have suggested that surface buoyancy fluxes may also contribute to, or at least modulate, the strength of the gyres. In this work, we present results from a series of ocean model simulations in which we independently estimate the effects of wind stress and surface buoyancy fluxes on gyre transport. We find that surface buoyancy fluxes control the near-surface density gradients, which in turn affect the gyre circulation. The relationship between surface heat flux gradients and the gyre circulation is linear for timescales shorter than a decade, after which the relationship becomes non-linear due to density advection by the circulation. The relative importance of wind and buoyancy forcing is different for subtropical and subpolar gyres, with the subpolar region exhibiting a more complex range of flow-topography interactions and stratification feedbacks.
Our work emphasizes the under-appreciated role of surface buoyancy fluxes in steering the circulation of large-scale oceanic gyres, with implications for how these gyres, and thus regional climate, may change in the future.
How to cite: Bhagtani, D., Hogg, A., Holmes, R., and Constantinou, N.: Ocean gyres and surface buoyancy forcing, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3126, https://doi.org/10.5194/egusphere-egu25-3126, 2025.
More than twenty years of air-sea flux observations have been collected at both the WHOTS and Stratus Ocean Reference Stations (ORS). Both are in trade wind regions, but WHOTS, just north of Oahu, Hawaii is rich in synoptic weather variability including storms, fronts, and cyclones, while Stratus, 1,500 km west of northern Chile and 1,900 km west of the Andes, has little synoptic weather variability. Time series of surface meteorology at each site are used to prepare time series of the air-sea fluxes of heat, freshwater, and momentum. Mean daily and annual cycles and the 365-day running mean low-passed times at each site are described and contrasted. The low-passed time series quantify the interannual variability at the two sites. After subtracting the long-term mean annual cycle from daily time series to create time series of anomalous interannual variability, the goal is to understand surface forcing contributes to periods of ocean warming and to periods of ocean cooling and to contrast the WHOTS regime's surface forcing by synoptic weather events with the Stratus regime's surface forcing absent synoptic weather variability. Because one approach to extending this to look over the regions around the ORS might be to use atmospheric reanalyses to provide gridded surface forcing, model time series are extracted at the ORS sites and analyzed in a similar way. Of interest is whether or not the ERA5, MERRA2, and NCEP2 reanalyses have realistic long-term means, daily and annual cycles, and interannual variability when compared to the ORS observations.
How to cite: Weller, R.: Contrasting how the ocean is forced by the atmosphere at the WHOTS and the Stratus Ocean Reference Stations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2939, https://doi.org/10.5194/egusphere-egu25-2939, 2025.
Most ocean observables are dominated by local variability, leading to the requirement of a dense observing array to calculate the integrated effects which are of broader scale relevance. Ocean bottom pressure (OBP), recently adopted as an Essential Ocean Variable, is an exception which shows coherent variations over extremely large length scales. In particular, we show that a model with realistic mesoscale variability demonstrates coherent OBP variability along the global continental slope with characteristic length scales of tens of thousands of kilometres. We show how these signals permit monitoring of the Meridional Overturning Circulation, and provide insights into the sources of that variability. We also show how boundary pressure measurements allow the global circulation of a realistic model to be understood in terms of classical idealised models, how they measure the integrated flow in boundary currents, and how they relate to global-scale dynamical sea level differences. Furthermore, we demonstrate an observational method that permits the clear separation of dynamical OBP changes from seismic changes and vertical land movement. We make the case that a small number of Eulerian observations could provide a disproportionately large amount of information about the global ocean circulation.
How to cite: Hughes, C., Gururaj, S., and Bingham, R.: Ocean Boundary Pressures as an efficient means to measure the global ocean circulation., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8543, https://doi.org/10.5194/egusphere-egu25-8543, 2025.
This study presents a ten-minute interval sea level height (SLH) time series observed from wave radar MIROS SM-140 equipped at the Ieodo Ocean Research Station (I-ORS), a steel framed tower-type multidisciplinary research platform, a unique in situ measurement in the open sea for over two decades. To assess the practicability of the observed SSH, we developed a tidal model-based QC procedure, which has two notable differences in characteristics from the typical ones: 1) a spatiotemporally optimized local range check based on the high-resolution tidal prediction model TPXO9 and 2) consideration of the occurrence rate of a stuck value over a specific period. Comprehensive comparisons with typical QC processes, satellite altimetry, and reanalysis products demonstrate that our approach could provide reliable SLH time series with few misclassifications. A budget analysis demonstrated that the barystatic effect primarily caused sea level rise around the I-ORS. As a representative of sea level fluctuations in the central East China Sea, this qualified SLH time series enables dynamic research, spanning from a few hours of nonlinear waves to a decadal trend with simultaneously observed environmental variables from the I-ORS’ air–sea monitoring system.
How to cite: Kim, Y. S., Jeong, T.-B., Cha, H., Jeong, K.-Y., Jang, M.-J., Jeong, J.-Y., and Lee, J.-H.: Multidecadal Sea Level Time Series at the Ieodo Ocean Research Station: A New Approach for the Assessment of Sea Level Rise in the East China Sea, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15138, https://doi.org/10.5194/egusphere-egu25-15138, 2025.
The East China Sea is a climate-sensitive hotspot where rapid changes in oceanic and ecological conditions have been observed in recent years. Long-term and systematic observational data are essential for accurately assessing these changes. The Ieodo Ocean Research Station (I-ORS), established in June 2003, has been monitoring various oceanic and atmospheric variables in real time. As the first OceanSITES-registered continental shelf observation platform, I-ORS has accumulated valuable data over the past two decades. This long-term dataset is critical for understanding the impacts of large-scale climate change on coastal and shelf regions, revealing significant signals of climate variability in the East China Sea. Notably, I-ORS observations show a significant rise in sea surface temperature, increasing by 0.6°C per decade since 2004—approximately two times faster than the global average rate of 0.3°C. This rapid warming trend underscores the East China Sea's increased vulnerability to climate change, with I-ORS data providing key insights for predicting future changes and mitigating marine disasters.
How to cite: Kim, G.-U., Min, Y., Lee, S.-W., Jeong, J., Lee, J., Lee, S.-C., Jeong, E. Y., Min, I.-K., Ok, J., and Jeong, J.-Y.: Long-Term Observations from Ieodo Ocean Research Station (I-ORS) for Monitoring Climate Change in the East China Sea, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16316, https://doi.org/10.5194/egusphere-egu25-16316, 2025.
Fram Strait, located between Svalbard and Greenland, serves as a crucial gateway connecting the Arctic Ocean and the North Atlantic, facilitating the exchange of heat and freshwater between these regions. Warm and saline Atlantic Water (AW) is carried northwards by the West Spitsbergen Current (WSC), and constitutes the main source of oceanic heat and salt entering the Arctic Ocean. Variations in the AW inflow strongly influence both Arctic ocean and sea ice conditions. An array of moorings has been monitoring the year-round inflow of AW in the WSC, providing hydrographic and current data from 1997 – 2024. A robust, long-term AW warming trend of 0.20°C/decade is identified, leading to a total increase of 0.54°C over the 27-year record. Distinct multi-annual warm and cold anomalies are identified, lasting ~2 years, with two warm periods (2005–2007 and 2015–2017) and two cold periods (1997–1999 and 2019–2024), linked to distinct shifts in the AW temperature regime. Notably, the most recent cold anomaly persisted for over five years—more than twice the duration of previous events. The interannual variability in AW temperatures results from a combination of advection from upstream in the Nordic Seas and local atmospheric forcing. Temperature anomalies propagate northward into the Arctic Ocean along the AW inflow pathway to the north of Svalbard, with a 2-month lag relative to Fram Strait, thus the expected continued rise in AW temperatures and associated heat transport will have profound and lasting impacts on the future state of the Arctic Ocean.
How to cite: McPherson, R., von Appen, W., de Steur, L., Kanzow, T., Beszczynska-Möller, A., and Renner, A.: Decades of Change: Warming Trends and Variability of Atlantic Water as observed in the West Spitsbergen Current (1997–2024), EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9037, https://doi.org/10.5194/egusphere-egu25-9037, 2025.
Dense Shelf Water (DSW) cascading in the northwestern Mediterranean Sea is an important winter phenomenon for the ventilation of deep-water ecosystems and modulation of the physical and chemical properties of deep waters. This study combines reanalysis data and recent observations to explore the drivers of DSW formation and cascading, across multiple spatial and temporal scales.
At the subsynoptic scale, in the Gulf of Lion area, the action of cold and dry northern winds, named Tramuntana, and freshwater inputs from rainfall, rivers, and continental runoff regulate the shelf water density. At the synoptic scale, persistent winds and the intrusion of cold air masses from continental Europe can induce Marine Cold Spells (MCS), which are extreme events marked by sustained periods of below-average sea surface temperatures. Notably, MCS occurring around mid-February, when shelf water reaches peak density, are closely linked to DSW formation.
On a larger scale, variability in the East Atlantic (EA) climate mode influences the frequency, persistence, and intensity of cold Tramuntana winds, connecting regional ocean-atmosphere interactions to broader climatic oscillations. Additionally, the combined negative phases of EA and North Atlantic Oscillation climate modes contribute to the formation of denser shelf water.
Amid recent trends of reduced Tramuntana wind intensity, rising shelf water temperatures, and a decline in MCS frequency, an analysis of all the factors contributing to DSW formation and cascading is key to understanding its future. These insights, in turn, will help to anticipate its impact on deep-water circulation and ventilation, biodiversity and functioning of the deep ecosystems.
How to cite: Fos, H., Peña-Izquierdo, S., Corral, S., Durrieu de Madron, X., Estella-Pérez, V., Florindo-Lopez, C., Lagarde, M., Pascual, J., Romero, L., Sanchez-Vidal, A., and Amblas, D.: Winter dense water formation and marine cold spells in the Northwestern Mediterranean: Multi-scale dynamics and implications for dense shelf water cascading, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1048, https://doi.org/10.5194/egusphere-egu25-1048, 2025.
Two moorings in the California Current Ecosystem (CCE) obtained long records of biogeochemical (O2, pCO2, pH, nutrients, Chl-a) and physical parameters (currents, temperature, salinity). Here, the data are used to investigate the seasonal variability of the mixed-layer carbon budget from 2008 to 2022. The moorings are located in the California Current offshore region (CCE1) and the upwelling region on the continental shelf (CCE2), recording high-resolution data at both the surface and the base of the mixed layer. On average, air-sea CO2 fluxes at the surface showed that the open ocean site acts as a sink for atmospheric CO2, with a net annual mean flux of -0.52 molC m-2 year-1, while the upwelling site is a carbon source, with a net outgassing of 0.56 molC m-2 year-1. At CCE1, sea surface temperature is the primary driver of seawater pCO2 and CO2 fluxes, whereas, at the upwelling site, dissolved inorganic carbon (DIC) associated with non-thermal processes acting on seawater pCO2 is the main driver of seasonal variability. To study which non-thermal processes, such as lateral advection, entrainment/detrainment, biological effects, and CO2 flux, affect the mixed layer DIC, we first quantify a climatological annual carbon budget via a mass balance at each site. Using this budget, we compute the anomalies that events such as La Niña, El Niño, and Marine Heatwaves create in relation to the observed mean conditions. Specifically, events such as Marine Heatwaves can reverse the mean surface CO2 flux at both sites, with the CCE1 site switching from a net CO2 sink to a net CO2 source and CCE2 from a CO2 source to a sink. The relevance of each driver during these events is explored with respect to the climatological annual carbon budget at each site. This study highlights the importance of long-term monitoring for accurately capturing the variability of marine carbon fluxes.
How to cite: Frazão, H. C., Send, U., Sutton, A. J., Ohman, M. D., Martz, T. R., Lankhorst, M., Sevadjian, J., and O'Brien, T.: Long High-Resolution Records of Mixed-Layer Carbon Budget Variability in the Southern California Current System, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11829, https://doi.org/10.5194/egusphere-egu25-11829, 2025.
Oceanic-dissolved gas concentrations in the upper ocean are governed by biological and physical processes. Biological activity comprises the oxygen (O2) production by phytoplankton during photosynthesis and consumption through respiration by the marine community. The balance between the two processes is the net community production (NCP). It can be estimated from a time series of oxygen measurements if the physical processes can be evaluated.
Among the physical, the air-sea gas exchange is the main one controlling oxygen concentrations in the ocean mixed layer, and the contribution of bubbles created by breaking waves is a first order event at moderate to high wind speeds (u10 > 7m/s), in young (wind) seas mainly.
In this work, we use different model of the role of bubbles in air‐sea gas exchange (different parameterizations calculated the contribution of bubbles in the air-sea exchange flux) to estimate the NCP in the North Atlantic. Biological contributions are calculated by subtracting the calculated physical changes from the measured dissolved oxygen and compared with primary production estimates based on chlorophyll algorithms.
For this aim, long-term oceanographic time series data from the ocean observatory SATS (Santander-Atlantic-Time-Series) have been employed. These data include measurements from the ocean-meteorological buoy (AGL) at its associated oceanographic station running since 2007 in the southern Bay of Biscay.
We find that the contribution of bubles is minor (5-10 %), thus we can assume that the estimates of NCP are reliable, in good agreement with primary production estimates at the surface. In addition, the wave age has been measured and found to be mostly a mature sea, with very few days of young waves.
How to cite: Merino-Sainz, I., Somavilla, R., Navarro-Engesser, M., Viloria, A., and Ibañez, L.: Comparison of net community and primary production estimates in the Bay of Biscay., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18194, https://doi.org/10.5194/egusphere-egu25-18194, 2025.
Extreme high temperatures occur frequently over the densely populated Yangtze River basin (YRB) in China during summer, significantly impacting the local economic development and ecological system. However, accurate prediction of extreme high-temperature days in this region remains a challenge. Unfortunately, the Climate Forecast System Version 2 (CFSv2) exhibits poor performance in this regard. Thus, based on the interannual increment approach, we develop a hybrid seasonal prediction model over the YRB (HMYRB) to improve the prediction of extreme high-temperature days in summer.The HMYRB relies on the following four predictors: the observed preceding April–May snowmelt in north western Europe; the snow depth in March over the central Siberian Plateau; the CFSv2-forecasted concurrent summer sea surface temperatures around the Maritime Continent; and the 200-hPa geopotential height over the Tibetan Plateau. The HMYRB indicates good capabilities in predicting the interannual variability and trend of extreme high-temperature days, with a markable correlation coefficient of 0.58 and a percentage of the same sign (PSS) of 76% during 1983–2015 in the one-year-out cross-validation. Additionally, the HMYRB maintains high PSS skill (86%) and robustness in the independent prediction period (2016–2022). Furthermore, the HMYRB shows a good performance for years with high occurrence of extreme high-temperature days, with a hit ratio of 40%. These predictors used in HMYRB are beneficial in terms of the prediction skill for the average daily maximum temperature in summer over the YRB, albeit with biases existing in the magnitude. Our study provides promising insights into the prediction of 2022-like hot extremes over the YRB in China.
How to cite: Pan, S.: Seasonal prediction of extreme high-temperature days over the Yangtze River basin, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1159, https://doi.org/10.5194/egusphere-egu25-1159, 2025.
Typhoon interacts with the ocean by inducing vertical mixing, which alters the ocean’s internal temperature structure. Typically, after a typhoon passes, the surface water temperature decreases while the bottom water temperature increases due to this mixing. However, observations at 5, 20, 40 meter depths at the Ieodo Ocean Research Station (I-ORS) during Typhoon Kong-Rey (2018) revealed an unexpected abrupt cooling of the bottom water, different from the usual pattern. On October 6, 2018, at 00:00, Typhoon Kong-Rey (2018) passed ~86 km from I-ORS, causing the sharp decrease in bottom water temperature from 24.8℃ to 12.2℃, contrary to the typical warming observed in bottom waters. To explain this anomalous cooling, we analyzed temperature and current data from HYCOM. The HYCOM simulations indicated that the abrupt cooling of bottom water was driven by the southward movement of a subsurface cold water mass located north of I-ORS. The southward movement of the subsurface cold water mass can be partially attributed to Ekman currents and the southeastward tidal residual current. Our study provides a valuable example of short-term, anomalous bottom water temperature changes induced by a typhoon. It emphasizes the diverse oceanic responses to typhoons on the continental shelf of the East China Sea, underlining the complexity of typhoon-ocean interactions.
How to cite: Lee, J., Lee, S.-W., Jeong, J., Jeong, J.-Y., and Jeon, C.: Unexpected abrupt cooling in bottom water driven by Typhoon Kong-Rey (2018) in the East China Sea, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7786, https://doi.org/10.5194/egusphere-egu25-7786, 2025.
The Ieodo Ocean Research Station (I-ORS), located southwest of Jeju Island, South Korea, is a remote offshore structure that has been monitoring 15 ocean and atmospheric parameters since 2003. Key parameters, including water temperature, salinity, air temperature, wind direction, wind speed, relative humidity, and atmospheric pressure, are measured at 10-minute intervals. These data are subjected to stringent quality control processes to ensure scientific validity and precision. The quality control process follows OOI (Ocean Observatories Initiative) protocols, employing automated checks such as physical limit verification, variability (standard deviation) analysis, spike detection, and constant value checks. These checks assign initial flags to identify potential anomalies. To further enhance data reliability, manual inspections are conducted, reviewing oceanographic conditions and maintenance reports of facilities and equipment. Flags are adjusted accordingly to refine the data's accuracy. The quality-controlled datasets, accompanied by metadata, are registered on international platforms such as OceanSITES and SEANOE. These platforms provide free access to the global scientific community, supporting diverse research areas such as oceanography, climate change studies, and atmospheric sciences. The Ieodo station's high-quality data contribute significantly to advancing scientific understanding of oceanic and atmospheric phenomena and fostering collaboration within international observation networks.
How to cite: Jeong, K.-Y., Seo, G.-H., Ham, H.-S., Kim, Y., Jeong, J., and Min, Y.: High-Quality Observation Data from the Ieodo Ocean Research Station: Management and Global Accessibility, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2627, https://doi.org/10.5194/egusphere-egu25-2627, 2025.
The ocean helps in mitigating climate change by absorbing a large part of the excess heat and atmospheric carbon dioxide (CO2) produced by human activities. A decrease in surface ocean pH, known as ocean acidification, is a consequence of an increase in ocean uptake of CO2 concentrations which presents a significant challenge to various marine organisms, particularly those that rely on calcium for their structures (Metzl et al., 2024; Petton et al., 2024). More than ever, consistent long-term observations of acidification and carbon cycling variables such as pH, temperature, salinity and CO2 are crucial to provide a quantitative assessment of the vulnerability of an area under climate and anthropogenic stressors. However, up to now, there are only a limited number of coastal observation sites where these parameters are measured simultaneously and at high frequency.
In the framework of the ITINERIS project, financed by NextGenerationEU Programme (2022-2025), data on ocean acidification and carbon cycling parameters acquired by the meteo-oceanographic buoy MAMBO-1 (Monitoraggio AMBientale Operativo) were harmonized and standardized in order to obtain a consistent, up-to-date and FAIR (Findable, Accessible, Interoperable and Reusable) continuous time series (1999-2024). The MAMBO-1 buoy was the first meteorological-maritime coastal station to be installed in the northern Adriatic sea capable of recording meteorological and oceanographic parameters in near-real time (Partescano et al., 2014). The buoy is anchored at about 17 m in the seabed within the border of the Miramare Marine Protected Area in the Gulf of Trieste (45.6976667 °N and 13.7083333 °E) and has been operative since January 1999 (M. Lipizer et al., 2017). Over the years, the configuration and instrumentation of the site have changed several times, so it is difficult to obtain a continuous long-term time series from a data management perspective.
The importance of the availability of the long-term time series justifies the reconstruction effort for future studies aimed at obtaining a clearer picture of ocean acidification and carbon cycle processes in the northern Adriatic Sea.
References
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Metzl, N., Lo Monaco, C., Leseurre, C., Ridame, C., Reverdin, G., Chau, T. T. T., Chevallier, F., & Gehlen, M. (2024). Anthropogenic CO 2 , air–sea CO 2 fluxes, and acidification in the Southern Ocean: Results from a time-series analysis at station OISO-KERFIX (51° S–68° E). Ocean Science, 20(3), 725–758. https://doi.org/10.5194/os-20-725-2024
Partescano, E., Giorgetti, A., Fanara, C., Crise, A., Oggioni, A., Brosich, A., & Carrara, P. (2014). A (Near) Real-time Validation and Standardization System Tested for MAMBO1 Meteo-marine Fixed Station. https://doi.org/10.13140/2.1.2788.4800
Petton, S., Pernet, F., Le Roy, V., Huber, M., Martin, S., Macé, É., Bozec, Y., Loisel, S., Rimmelin-Maury, P., Grossteffan, É., Repecaud, M., Quemener, L., Retho, M., Manach, S., Papin, M., Pineau, P., Lacoue-Labarthe, T., Deborde, J., Costes, L., … Gazeau, F. (2024). French coastal network for carbonate system monitoring: The CocoriCO2 dataset. Earth System Science Data, 16(4), 1667–1688. https://doi.org/10.5194/essd-16-1667-2024
How to cite: Reyes Suarez, N. C., Lipizer, M., Altenburger, A., Partescano, E., Plehan, S., Cociancich, A., Corbo, A., Brunetti, F., and Giorgetti, A.: Reconstructing the long-term time series of ocean acidification data in the Gulf of Trieste: the importance of metadata for data harmonisation and standardisation, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8797, https://doi.org/10.5194/egusphere-egu25-8797, 2025.
Recently, substantial effort has been made to understand the fundamental characteristics of warm ocean temperature trend (ocean warming) and extremes (marine heatwaves, MHWs). However, most research focused on surface signatures of these events, relying on satellite and reanalysis data. While surface ocean warming and MHWs can have dramatic impacts on climate change and marine ecosystems, these events along the seafloor can also significantly affect climate and ecosystems. Monitoring these changes requires long-term, fixed-point observations across multiple depth layers. In this study, we investigate long-term temperature trends and MHW characteristics by analyzing 20 years (2004–2023) of temperature data at three depths—surface (3 m), middle (20 m), and bottom (38 m)—collected at the Ieodo Ocean Research Station in the northern East China Sea near the Korean coast. We find that the air temperature increased by 0.70°C per decade. Correspondingly, ocean warming trends were 0.64°C/decade at the surface, 0.66°C/decade in the middle layer, and 0.88°C/decade at the bottom, with the greatest warming observed in the bottom layer. As MHW frequency and intensity increased across all three layers, bottom MHWs (BMHWs) were found to be more intense and persistent than surface MHWs (SMHWs). While BMHWs, middle MHWs, and SMHWs often co-occur, BMHWs can also exist independently of SMHWs. This study provides direct evidence of distinct warming trends and MHW characteristics across ocean layers based on long-term in situ observations, contributing a valuable dataset for understanding climate-driven changes in the marine environment and supporting efforts to predict and mitigate their ecological and environmental consequences.
How to cite: Lee, S.-W., Kim, G.-U., Min, Y., Oh, H., Jeong, J., Lee, J., Lee, S.-C., Ok, J., Min, I.-K., and Jeong, J.-Y.: Depth-dependent ocean warming and marine heatwaves through two decades at Ieodo Ocean Research Station in the East China Sea, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7901, https://doi.org/10.5194/egusphere-egu25-7901, 2025.
Based on data diagnosis and numerical experiments, this study investigated the changes in the interannual properties of the May North Atlantic Oscillation (NAO) and their impact on summer (June–July) sea ice in the North Atlantic during 1979–2021. Results showed statistically significant increase in the interannual variability of the May NAO after the mid-2000s, which had remarkably enhanced impact on summer sea ice in the eastern Hudson Bay (EHB) and the western Labrador Sea (WLS). During 2005–2021, corresponding to a positive phase of the May NAO, anomalous surface westerly or northwesterly winds prevailed over the Hudson Bay and Labrador Sea in May. This led to statistically significant increase in sea ice in both the EHB and the WLS in May via dynamic processes (favoring southeastward movement of the sea ice) and thermal processes (changing surface turbulent heating and shortwave radiation). In comparison with the situation in May, the increase in sea ice in the EHB developed further during summer mainly via thermal processes (positive feedback between the increased sea ice and shortwave radiation). In contrast, amplitude of the increased sea ice in the WLS was comparable between May and summer. Dynamic processes (southeastward movement of sea ice), which was induced by a barotropic anomalous high in the troposphere centered over the Labrador Peninsula, favored the increase in sea ice in summer in the WLS. The tripole sea surface temperature anomalies in the North Atlantic and increased snowpack on the Labrador Peninsula in May, triggered by the positive phase of the May NAO, played an important role in the formation of the anomalous high. During 1979–2004, the surface wind, snowpack, and tripole sea surface temperature anomalies in May, triggered by the May NAO, were relatively weak, leading to statistically insignificant changes in summer sea ice in the EHB and WLS.
How to cite: Xu, Z. and Fan, K.: Enhanced interannual variability of the May North Atlantic Oscillation and its impact on summer sea ice in the North Atlantic after the mid-2000s, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20281, https://doi.org/10.5194/egusphere-egu25-20281, 2025.
Sea fog is a type of fog occurring near marine surfaces, developing within the lower atmospheric boundary layer and influenced by atmospheric and oceanic conditions. The thermodynamic processes driven by the air-sea temperature difference (ASTD) are crucial factors determining sea fog formation mechanisms. Recent studies report a continuous increase in sea surface temperatures in the East/Japan Sea. These changes in the marine environment are likely to affect the frequency, intensity, and duration of sea fog, research on sea fog occurrences in the East Sea remains necessary. This study employs the Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST) model to conduct numerical simulations of a sea fog event that occurred over the East Sea of Korea from August 18 to 19, 2020. Standalone atmospheric models cannot simulate the SST and, tend to underestimate the duration of sea fog events. The coupled model incorporates ocean-atmosphere interactions, enabling the Regional Ocean Modeling System (ROMS) to simulate spatiotemporal variations in sea surface temperature (SST). It allows for an analysis of how SST changes influence heat and moisture fluxes within the atmospheric boundary layer and the effects on sea fog formation and persistence. This research emphasizes the importance of ocean-atmosphere interactions and the role of SST modeling in sea fog prediction. The findings are expected to contribute to the improvement of sea fog forecasting systems in the East Sea.
How to cite: Choi, J., Kim, B.-M., Sung, H.-J., Bae, H.-J., and Han, K.-H.: Impact of Atmosphere-Ocean Coupled Model on Sea Fog Formation Mechanism Simulation: A Case Study of Sea Fog in the East/Japan Sea of Korea, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17657, https://doi.org/10.5194/egusphere-egu25-17657, 2025.
Subseasonal reversal of warm Arctic–cold Eurasia (SR‐WACE) pattern has significant impacts on transitions of weather and climate extremes in Eurasia. This study explored the performances of climate models to simulate the main features of SR‐WACE. For real‐time predictions, most of the state‐of‐the‐art climate models showed limited ability to accurately forecast SR‐WACE in advance. Furthermore, most of the historical simulations from Phase 6 of the Coupled Model Intercomparison Project (CMIP6) hadalso difficulties in well simulating the SR‐WACE. Further exploration showed that the simultaneous reversal of the Ural blocking high (UB) and Siberian high (SH) is the key atmospheric driver of the SR‐WACE occurrences, which were verified by both of the real‐time predictions and historical simulations. Our results implied that the simulation of SR‐WACE was a huge challenge and the critical solutions included improving simulation of subseasonal reversals of UB and SH in the atmosphere.
How to cite: Xu, T.: Identification of Shortcomings in Simulating the Subseasonal Reversal of the Warm Arctic–Cold Eurasia Pattern, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1496, https://doi.org/10.5194/egusphere-egu25-1496, 2025.
The Arctic climate is changing rapidly, along with intensified melting of sea ice, which has significant impacts on surface air temperature (SAT) in Eurasia. This study reveals that the subseasonal response of SAT to the autumn Kara–Laptev Sea ice (KLSIC) differs significantly between early and late winter. The response of SAT to KLSIC forms a warm Arctic–cold Eurasia pattern in early winter. Conversely, the negative anomaly response of SAT to KLSIC in late winter is only distributed in the band range of Eurasia, without significant positive SAT anomaly over the Arctic Ocean. After further examination of the separate physical mechanisms involved in early and late winter, it is found that a decrease in KLSIC in autumn can lead to a strengthened Ural high and Siberian high in the Arctic–Eurasia region, which is conducive to cold events in the mid-latitudes of Eurasia in early winter. For late winter, a westward shift in the response of atmospheric circulation to KLSIC leads to a negative anomaly feedback of North Sea surface temperature, which triggers the propagation of Rossby waves to the Sea of Japan through the wave activity flux. Meanwhile, the deep trough of East Asia is strengthened and extends to the southeast, guiding northern cold air to the western Pacific. Our results highlight that different subseasonal effects of sea ice should be considered in Eurasian climate prediction, rather than only consider the effects in winter mean.
How to cite: Guo, H.: Different responses of surface air temperature over Eurasia in early and late winter to the autumn Kara–Laptev Sea ice, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1497, https://doi.org/10.5194/egusphere-egu25-1497, 2025.
The North Atlantic Oscillation (NAO) and North Atlantic tripole sea surface temperature (SST_tri) are important modes in the atmosphere and ocean over the North Atlantic, respectively. The link between the two is well-known. However, this link decreased significantly in 1980–2001 (P2), compared to 1959-1979 (P1) and 2002-2022 (P3). This is related to the significant interdecadal shift of the NAO south center. In late winter, the NAO south center experienced a significant "west-east-west" interdecadal shift, shifting eastward by up to 20° longitude during P2. The eastward shift of the NAO forced the region of strong air-sea interactions to shift, resulting in the collapse of NAO-related SST_tri during P2. In addition, the winter SAT reversal frequency in the mid-latitudes of Eurasia also experienced interdecadal changes. SAT reversal events in P1 and P3 are twice as frequent as those in P2, which is related to the interdecadal westward shift of the NAO south center in P1 and P3. When the NAO south center was westward in late winter, the North Atlantic jet stream retreated significantly from the early winter. The development of the Ural blocking caused the accumulation of cold air in Siberia, causing the reverse change of the Siberian High compared to the early winter, resulting in a SAT reversal in the mid-latitude of Eurasia.
How to cite: Song, X.: Interdecadal Shift of the NAO South Center in Late Winter and Its Climatic Impact, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1611, https://doi.org/10.5194/egusphere-egu25-1611, 2025.
Arctic amplification has been linked to significant changes in mid-latitude weather patterns, including the increasing frequency of extreme weather events. Understanding the mechanisms behind these connections remains a critical challenge in climate science, particularly as the Arctic climate experiences rapid changes. This project investigates the causal pathways linking Arctic amplification to mid-latitude dynamics, with a specific focus on the two-way interactions between Barents-Kara Sea ice loss and winter blocking in the Ural Mountains region, and their link to cold extremes in Eurasia. For this we compute two types of blocking diagnostics (one anomaly based index, and one reversal index) and quantify their changes over time in association with sea ice loss in the Barents and Kara region. Given the limited sample size of the observational record and the large internal climate variability, we not only use reanalysis data but also large-ensemble climate model simulations. Moreover, to address these complex interactions in the presence of potential confounding factors such as ENSO, the project employs causal inference theory within a causal network framework. By disentangling and quantifying sea ice-blocking interactions, the study aims to elucidate critical knowledge gaps in understanding Arctic-midlatitude linkages and to enhance the predictability of future extreme weather events under a warming climate.
How to cite: Agyemang-Oko, E. and Kretschmer, M.: Quantifying the influence of Barents-Kara Sea ice loss on Ural blocking, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1727, https://doi.org/10.5194/egusphere-egu25-1727, 2025.
| This study explores the response of Arctic sea ice to CO2 removal and its subsequent effects on the winter Northern Hemisphere atmospheric circulation. Using multimodel ensembles from the Carbon Dioxide Removal Model Intercomparison Project, we find that most models display incomplete Arctic sea-ice recovery when CO2 is stabilized back at preindustrial levels, with a deficit of sea-ice area of around 1 million km². This sea-ice deficit is associated with residual equatorward-shifted wintertime midlatitude jets. Sea-ice perturbation experiments from the Polar Amplification MIP provide evidence of a causal influence of residual sea-ice loss on the atmospheric circulation. Model uncertainty in the magnitude of the residual North Atlantic jet shift can be largely explained by the relative magnitudes of residual Arctic and tropical warming across the models. These findings suggest that Arctic sea-ice loss is not fully reversible after CDR, which leads to residual changes in the mid-latitude atmospheric circulation. |
How to cite: Yu, H., Screen, J., Xu, M., Hay, S., Qiu, W., and Catto, J.: Incomplete Arctic sea-ice Recovery under CO2 Removal and its Effects on the Winter Atmospheric Circulation, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6884, https://doi.org/10.5194/egusphere-egu25-6884, 2025.
The variability of deep currents flowing into the Ulleung Basin through the Ulleung Interplain Gap, located between Ulleungdo and Dokdo, is critical for understanding the meridional circulation of the East Sea and the changes in the deep waters of the Ulleung Basin. The deep currents in this region exhibit asymmetry due to the influence of the Dokdo Abyssal Current and are known to show variations with periods of 5–40 days, attributed to topographic Rossby waves. However, studies on the spatial distribution and causes of the 40-day period variability within the Ulleung Interplain Gap remain unknown. This study aims to address this gap. Deep currents were observed using five mooring lines (U1, U2, U3 or EC1, U4, U5) deployed across the Ulleung Interplain Gap from 2002 to 2004. In the upper layer (200 m), an increase in the 40-day period current variability was observed at U3 between October 2003 and March 2004. In the deep layer (from 1000 m to 2240 m), enhanced 40-day period variability of current occurred during the winter seasons (January–April 2003 and December 2003–March 2004) at four stations (U2, U3, U4, and U5), excluding U1. The first major fluctuation was observed at U3 and U5, while the second was observed at U2 and U4, showing increased amplitudes. This suggests that the cyclonic/anti-cyclonic deep currents within the Ulleung Interplain Gap are associated with changes in their radius or location. Furthermore, these cyclonic/anti-cyclonic deep currents exhibit characteristics distinct from the patterns reported in previous studies, which described deep currents flowing along the continental slope around the Ulleung Basin. This study aims to define the 40-day period deep current patterns and identify their causes by analyzing their relationship with variability in the upper layers.
How to cite: Go, G. and Park, J.-H.: Spatial Distribution of 40-Day Period Deep Currents in the Ulleung Interplain Gap, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7623, https://doi.org/10.5194/egusphere-egu25-7623, 2025.
| Subseasonal reversals of extreme cold days (ECDs) over Northeast China during the winters of 1980-2022 are investigated in this study. Almost half of the years (18 of the 43) experienced subseasonal reversals between early winter (December 1 to January 15) and late winter (January 16 to February 28), characterized by either "more-to-fewer ECDs (ECD+−)" or "fewer-to-more ECDs (ECD−+)." Subseasonal shifts of the North Atlantic Oscillation, the Scandinavian-like pattern, and the stratospheric polar vortex are associated with ECD+−/−+ years. Previous autumn sea surface temperature anomalies and Siberian snow cover anomalies can excite significant atmospheric circulation anomalies or Rossby wave trains that contribute to the subseasonal reversal of ECDs. Statistical forecast models based on physical mechanisms skillfully predict the early/late winter ECD index, with temporal correlation coefficient skill of 0.74/0.46 during the cross-validation period of 1980-2002 and 0.54/0.54 during the independent hindcast period of 2003-2022; moreover, extreme values of the ECD index are also reasonably predicted. The findings of this study offer new insights regarding the mechanism and prediction of subseasonal ECDs over Northeast China. |
How to cite: huang, Z.: Subseasonal Reversal of Extreme Cold Temperature Frequencies in Northeast China: Possible Mechanism and Prediction, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8746, https://doi.org/10.5194/egusphere-egu25-8746, 2025.
We quantify the impact of interdecadal sea surface temperature (SST) variability on precipitation extremes over continental Europe and central Africa using the OpenIFS atmospheric general circulation model. We performed 45-member ensemble experiments in which we removed SST anomalies obtained from linear regression with either the Interdecadal Pacific Variability (IPV) or the Atlantic Multidecadal Variability (AMV) from the daily SST in the Pacific Ocean and the Atlantic Ocean over the period 1950–2013. We also used coupled model simulations, particularly the Component C of the Decadal Climate Prediction Project (DCPP-C) as part of the Coupled Model Intercomparison Phase 6 (CMIP6). We find that precipitation extremes amplify over western and central Africa during the positive phase of AMV and reduce there during the negative phase of AMV. The positive phase of IPV reduces the precipitation extremes over western and central Africa and amplifies them during the negative phase. However, AMV and IPV do not show a significant impact over Europe except in some parts of Eastern Europe, where AMV causes more extreme precipitation during the positive phases and the IPV causes more over the Turkish region. Results from the atmosphere model are mostly consistent with the coupled model simulations from DCPP-C.
We also compute time of emergence for climate change signals over the period 1950-2013 and estimate that it takes approximately 700 years for a significant change in European precipitation extremes changes to emerge from the natural climate noise. The time of emergence reduces somewhat when AMV and IPV are removed, but is still on the order of centuries. The preliminary results of this study suggest that the potential importance of the internal variability of the Pacific and Atlantic Oceans is more crucial for the African continents than for the European regions.
How to cite: Liu, Y., Kjellsson, J., Savita, A., and Park, W.: Impact of Atlantic and Pacific Decadal Sea Surface Temperature on precipitation extremes over the European and African continents, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17617, https://doi.org/10.5194/egusphere-egu25-17617, 2025.
Improving the current level of skill in seasonal climate prediction is urgent for achieving sustainable socioeconomic development, and this is especially true in China where meteorological disasters are experienced frequently. In this study, based upon big climate data and traditional statistical prediction experiences, a merged machine learning model (Y-model) was developed to address this, as well as to further explore unknown potential predictors. In Y-model, empirical orthogonal function analysis was firstly applied to reduce the data dimensionality of the target predictand (temperature and precipitation in the four seasons over China). Image recognition techniques were used to automatically identify possible predictors from the big climate data. These predictors, associated with significant circulation anomalies, were recombined into a large ensemble according to different threshold settings for five factors determining the statistical forecast skill. Facebook Prophet was chosen to conduct the independent hindcasts for each season’s climate at a lead time of two months. During 2011~2022, the seasonal climate in China was skillfully predicted by Y-model, with an averaged pattern correlation coefficient skill of 0.60 for temperature and 0.24 for precipitation, outperforming CFSv2. Potential predictor analysis for recent extreme events suggested that prior signals from the Indian Ocean and the stratosphere were important for determining the super Mei-yu in 2020, while the prior sea surface temperature over the western Pacific and the soil temperature over West Asia may have contributed to the extreme high temperatures in 2022. Our study provides new insights for seasonal climate prediction in China.
How to cite: Qian, D.: A merged Machine Learning model for seasonal climate prediction in China, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9985, https://doi.org/10.5194/egusphere-egu25-9985, 2025.
The Ieodo Ocean Research Station (I-ORS) is an Eulerian ocean observing platform providing long-term time series data of essential oceanic and atmospheric variables. The northern East China Sea, where the I-ORS is located, is characterized by strong tidal dominance but is also affected by surface inertial motions of non-tidal origin. These surface motions can resonate with local diurnal winds, such as the sea-land breeze (SLB), at inertial frequency because of its proximity to the diurnal critical latitude (~30˚N). This study investigates the amplification and damping of diurnal-inertial oscillations in the northern East China Sea by analyzing time series observations at the I-ORS from 15 May to 26 July 2023 and satellite-tracked surface drifters stayed nearby from 6 to 26 July 2023. In addition to the permanent I-ORS CT sensors installed at depths of 3.0, 20.5, and 38.0 m, 32 temperature sensors (thermistor string) were installed on the mooring line; Initial 16 sensors attached within ±1.5 m of the sea surface at an interval of 0.2 m while the other 16 sensors were attached between 3 and 21 m depths at an interval of 1.2m. All the I-ORS sensors including the thermistor string recorded data every minute or 10-minute interval. The location data of surface drifters, initially recorded hourly, were interpolated to 10-minute interval data to calculate zonal and meridional currents, kinetic energy per unit volume, and wind work rate along with wind stress estimated using the I-ORS sea surface wind data (speed and direction). The I-ORS thermistor string observations occasionally show significant diurnal-inertial oscillations in the mixed layer depth and thermocline depth with typical amplitudes of 1.5 m and 2.0 m, respectively, from 10 to 15 July, when strong eastward wind stress reached up to 0.04 N/m2 with an enhanced wind work rate of 0.069 W/m2. The amplitudes of the diurnal-inertial oscillations in the mixed layer depth and thermocline depth decreased to 0.5m or less from 18 to 22 July, when the wind stress became weaker (< 0.01 N/m2). The surface drifter observations show clockwise-rotating, circular inertial currents with a speed of 35-43 cm/s, separated from the diurnal tidal currents with a comparable speed. The kinetic energy of intermittently amplified, diurnal-inertial surface motions peaked at up to 100 J/m3 on 15 July, which is explained by the peak in wind work rate of 0.069 W/m2 considering mixed layer depth of 10 m and duration of 4 h, i.e., 0.069 J/s/m2 x 4 h / 3600 s/h / 10 m = 100 J/m3. This study presents the intermittent amplification of wind-induced, resonant diurnal-inertial oscillations at the upper ocean near the diurnal critical latitude based on the Eulerian time-series observations along with surface drifters. Further work is needed to address the generation and decaying dynamics and long-term variability of diurnal-inertial oscillations in this and other regions near the diurnal critical latitude.
How to cite: Kim, J. and Nam, S.: Amplifications and Damping of Diurnal-Inertial Oscillations Observed in the Northern East China Sea from Ieodo Ocean Research Station and Surface Drifters, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14541, https://doi.org/10.5194/egusphere-egu25-14541, 2025.
Posters virtual: Mon, 28 Apr, 14:00–15:45 | vPoster spot 5
EGU25-6053 | Posters virtual | VPS5
Coupling Atmospheric Dynamics and Ocean with Winds from SatellitesMon, 28 Apr, 14:00–15:45 (CEST) | vP5.15
An accurate description of air-sea interaction in atmospheric, ocean and coupled models remains problematic due to unresolved processes in atmospheric models. Systematic differences in winds occur (amongst others) due to undetermined geophysical dependencies. Systematic model errors in ocean winds found on large scale and atmospheric mesoscale propagate to the ocean circulation when used to force ocean models and affect coupled earth system dynamics.
Geolocated scatterometer-based corrections of wind forcing products already successfully correct for local wind vector biases, but this correction method is highly dependent on sampling. The growing virtual scatterometer constellation is very promising to better capture the detailed forcing errors over the day. Biases of the order of 0.5m/s in wind speed can introduce a large bias in wind stress, causing significant errors in ocean–atmosphere coupling and climate prediction.
Our focus is on unresolved processes in atmospheric Numerical Weather Prediction (NWP) models, namely systematic errors in boundary layer parameterizations such as lack of ocean currents and/or other biases that persist over time. An improved representation of surface turbulent fluxes relies on better estimates of: the roughness length, the stability function, the sea skin temperature, ocean currents and convective gustiness.
The goal is to apply model bias reduction schemes with respect to scatterometer winds. Consistent scatterometer corrections will lead to an improved understanding of the coupled atmospheric and oceanic model dynamical processes in the evolving earth system. In addition, corrected model winds reduce errors in ocean forcing and will be helpful in scatterometer data assimilation.
How to cite: Biri, S. and Stoffelen, A.: Coupling Atmospheric Dynamics and Ocean with Winds from Satellites, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6053, https://doi.org/10.5194/egusphere-egu25-6053, 2025.
