We explore the links between terrestrial temperature, sea levels and ice areas in both hemispheres with solar activity indices expressed through averaged sunspot numbers together with the summary curve of eigenvectors of the solar background magnetic field (SBMF) and with the changes of Sun-Earth distances caused by solar inertial motion resulting from the gravitation of large planets in the solar system. Using the wavelet analysis of the GLB and HadCRUTS datasets two periods: 21.4 and 36 years in GLB, set and the period of about 19.6 years in the HadCRUTS are discovered. The 21.4-year period is associated with variations in solar activity defined by the summary curve of the largest eigenvectors of the SBMF. A dominant 21.4-year period is also reported in the variations of the sea level, which is linked with the period of 21.4 years detected in the GLB temperature and the summary curve of the SBMF variations. The wavelet analysis of ice and snow areas shows that in the Southern hemisphere, it does not show any links to solar activity periods while in the Northern hemisphere, the ice area reveals a period of 10.7 years equal to a usual solar activity cycle. The TSI in March-August of every year is found to grow with every year following closely the temperature curve, because the Sun moves closer to the Earth orbit owing to gravitation of large planets (SIM), while the variations of solar radiation during a whole year have more steady distribution without a sharp TSI increase during the last two centuries. The additional TSI contribution caused by SIM is likely to secure the additional energy input and exchange between the ocean and atmosphere.

How to cite: Zharkova, V. and Vasilieva, I.: Terrestrial temperature, sea levels and ice area links with solar activity and solar orbital motion, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-22, https://doi.org/10.5194/ems2024-22, 2024.

An aspect of hydrologic sensitivity to climate change in snow dominated systems that has been moderately explored relates to the role of snowfall and snowpack accumulation in storing water throughout cold season months and releasing this water to terrestrial systems during warmer months when potential evapotranspiration (PET) is relatively elevated.  Importanlty, previous studies have not been able to document an explicit mechanism linking precipitation type to runoff production; yet several studies have noted that a sensitivity does exist.  Given that a shift from snowfall to rainfall is inevitable as the climate warms, this fundamental question as to how streamflow responds to a change in precipitation type is extremely timely and important for water resource management. Hence, one would expect that climate-related shifts toward earlier snowmelt or a shift from snowfall to rainfall would lead to an increased misalignment between the seasonality of surface water input (i.e. rainfall and snowmelt) and PET, and thus act to decrease annual partitioning to evapotranspiration and increase annual streamflow.  This shift from snowfall to rainfall, and it's associated influence on hydrologic partitioning will be refered to below as the 'energy-water-misalignment perspective'.  A second hypothesis, that is counter to the energy-water-misalignment perspective, has documented an increase in runoff partitioning with increased snowfall fraction which relates to a theorized greater effiency of soil-water drainage from snowmelt versus rainfall due to the high rate and duration of snowmelt; hereafter referred to as the 'snowmelt-rate perspective'.  In pursuit of this line of inquiry, this presentation will cover recent modeling and observation-based experiments that reveal the importance of both of the aforementioned runoff response perspectives.  The combination of these modeling and observation-based studies confirm that the energy-water misalignment perspective and the snowmelt-rate perspective both influence hydrologic partitioning sensitivity to precipitation type.  The resultant streamflow sensitivity to precipitation type and climate warming is therefore complex with the sign of the partitioning sensitivity being governed by the relative importance of the two paradoxical runoff response perspectives presented herein.  

How to cite: Molotch, N.: The influence of precipitation type on snowmelt partitioning between evapotranspiration and streamflow, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-930, https://doi.org/10.5194/ems2024-930, 2024.

The effects of anthropogenic climate change are particularly evident in mountainous regions, where the warming rate is higher than the global average. In this framework, the Alps have recently experienced multiple seasons characterized by a deficit of solid precipitation compared to the historical records. This deficit resulted in a critical situation regarding the status of the snowpack in the Alpine Region. Since the vast majority of the hydrological assets present in Northern Italy are highly dependent on the snow melting from the Alps, a lack of solid precipitation during the snow season could lead to dire impacts on the hydrological balance of the region, as it has already happened during the snow-drought events occurred in the years 2022 and 2023. Therefore, it is of the outmost importance to accurately assess the amount of water present in the snowpack of the Alps, especially at high elevation, where observations are lacking. The snow water equivalent (SWE) represents the equivalent amount of liquid water stored in the snowpack. It is usually measured in situ during campaigns carried out by researchers and technicians. However, the measurements obtained in the field with this method may lack temporal density and continuity. To address this problem, it is widespread practice to derive the SWE from models which account for the snow density and the snow height. Recently, instruments have been developed to perform continuous measurements of the SWE even in remote areas. Here we present the SWE data of the 2023-24 season retrieved from a high elevation monitoring station located on the Monte Rosa massif in the Western Italian Alps. The station (45°52’30’’ N; 7°52’18’’ E; 2900 m a.s.l.) is equipped with two sensors which measure the SWE adopting different techniques. The first, developed by Finapp Srl, is based on the Cosmic Ray Neutron Sensing (CRNS) technology, and retrieves hourly measures of the SWE integrated on a circular area with a diameter of roughly 20 m. The second sensor, developed by ANavS GmbH, employs antennas with Global Satellite Navigation System (GNSS) to evaluate the daily SWE in a solid angle with an amplitude in the order of ten degrees. The data from the sensors are compared with each other and with SWE values obtained during field campaigns and by means of model simulations (with data obtained using the model SNOWPACK) to assess the performance of the installed instruments. The main goal is to determine the feasibility and the limits of these kinds of solutions, with the aim of extending the framework adopted for this work to remote Alpine sites that would benefit from the possibility of retaining continuous monitoring of the snowpack status.

How to cite: Gallarate, M., Colombo, N., Freppaz, M., Gazzola, E., Henkel, P., Maiorano, M., Viani, C., Benech, A., Giardino, M., and Acquaotta, F.: Assessment on the continuous measurements of snow water equivalent on the Monte Rosa massif (Italy) performed with state-of-the-art sensors in the 2023-24 winter season, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-30, https://doi.org/10.5194/ems2024-30, 2024.

Mountainous areas are of particular interest due to their critical role in the hydrological resource, especially in the Iberian Peninsula, a region subjected to strong climate variability and change. In this work, we seek to evaluate the seasonal prediction of precipitation and temperature over these areas. Interannual variability of these two variables is of great importance, as it influences the onset, offset, melting rate and other characteristics of the seasonal snow cover. The seasonal snowpack is of great relevance, as its melting during late spring can reduce the impact of the summer drought by providing a crucial water resource.

To date, seasonal prediction models lack the necessary spatial resolution to resolve processes regarding complex orography or local phenomena. Furthermore, even widely used reanalysis products cannot accurately represent alpine sites, and therefore high-resolution products or on-site observations are required. In this regard, statistical downscaling methods can provide a necessary improvement at low computational costs. In this study, statistical methods, such as the analogs method and Principal Component Analysis (PCA), are employed to link large-scale atmospheric patterns predicted by seasonal prediction systems, such as ECMWF's fifth generation seasonal forecast system (SEAS5), to local data in the form of observations or high-resolution gridded products. These methods can provide a more accurate representation of local climatology in mountain regions, thereby improving seasonal forecasting skill in such crucial areas. Furthermore, the methodology allows for the calculation of snow-related indices that may prove useful for early water management decisions and for the interests of the ski industry. The findings of this research have significant implications for seasonal prediction and climate services, contributing to our understanding of climate variability and predictability in the Iberian Peninsula and in high-elevation areas within.

How to cite: García-Maroto, D., González-Cervera, Á., Mohino, E., and Durán, L.: Enhancing seasonal forecasting in mountain regions of the Iberian Peninsula through statistical downscaling, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-578, https://doi.org/10.5194/ems2024-578, 2024.

In recent years, a great deal of attention has been devoted to the study of past snowfall variability worldwide, mainly in mountain regions. The snow, in fact, is a pivotal component of the hydrological cycle and has a relevant impact on the energy budget, controlling the land surface albedo. In addition, the snow strongly affects the complex ecosystems of mountain areas, as well as the biogeochemical cycles. Therefore, considering also the recent climate changes, that are posing serious threats on the cryosphere and mountain regions, it is crucial to recover and analyse historical long-term time series of snowfall to assess its variability and tendencies.

For several reasons, many mountain areas remain under-researched. In the Mediterranean, an example in this sense is represented by the Apennine region (Italy). A considerable lack, in fact, exists in the knowledge of the past snowfall variability for this area, although it has a good heritage of past in situ observations.

This work presents an analysis of historical snow precipitation data collected in the period 1951-2001 in Central and Southern Apennines. To pursue this aim, we used the monthly observations of the snow cover duration, number of days with snow and total height of new snow collected at 129 stations located between 288 and 1750 m a.s.l.. Such data have been manually digitized from the Hydrological Yearbooks of the Italian National Hydrological and Mareographic Service. The available dataset has been primarily analyzed to build a reference climatology (related to 1971-2000 period) for the considered Apennine region. More specifically, using a methodology based on Principal Component Analysis and k-means clustering, we have identified different modes of spatial variability, mainly depending on the elevation, which reflect different climatic zones. Subsequently, focusing on the number of days with snow and snow cover duration on the ground, we have carried out a linear trend analysis. An overall negative tendency has been found for both variables. For clusters including only stations above 1000 m a.s.l., a significant (at 95% confidence level) decreasing trend has been found in the winter season (i.e. from December to February): −3.2 [─6.0 to 0.0] days/10 years for snow cover duration and −1.6 [─2.5 to ─0.6] days/10 years for number of days with snow. Moreover, in all considered seasons, a clear direct relationship between trend magnitude and elevation has emerged. In addition, using a cross wavelet analysis, we found a close in-phase linkage on decadal time scale between the investigated snow indicators and the Eastern Mediterranean Pattern. For both snow cover duration and number of days with snow, such connection appears to be more relevant in full (i.e. from November to April) and in late (i.e. from February to April) seasons.

How to cite: Capozzi, V., Serrpaica, F., Rocco, A., Annella, C., and Budillon, G.: Historical evidence of snowfall variability and trends in the Central and Southern Apennine Mountains, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-275, https://doi.org/10.5194/ems2024-275, 2024.

The Mediterranean mountains are characterized by having most of its annual precipitation concentrated in winter and in the form of snow. They normally experience a summer drought with drier and hotter summers when compared with other mountain ranges. Therefore, snow is crucial as a water resource in these regions, providing water during the spring snowpack melting. On the other hand, according to the recent IPCC-AR6 report, the Mediterranean is a climate change hot spot, which threatens the future of snow in its mountains. Understanding the variability of winter precipitation and its underlying mechanisms on large time scales allow us to find predictability patterns, and thus to pursue mitigation and adaptation strategies.

This study employs reconstructions of meteorological series from mountain stations in the Iberian Peninsula, utilising a downscaling methodology derived from ERA20C and ERA5 reanalyses. The methodology for reconstruction is based on an analog method, which is presented and discussed. The methods and code for the reconstructions are publicly available.  A comprehensive analysis of the low-frequency variability and trends of the resulting winter precipitation and the frequency of snow days has been conducted for the period 1900-2024. This analysis encompasses the investigation of teleconnection patterns associated with the low-frequency variability of winter precipitation and snowfall, as well as the frequency and nature of synoptic circulation types that lead to orographic precipitation and large-scale precipitation enhancement. The analysis and conclusions presented here provide a more comprehensive understanding of the mechanisms involved in the occurrence of decades with more or less winter precipitation and snowfall frequencies.

How to cite: Durán, L., González-Cervera, Á., and Rodríguez-Fonseca, B.:  Multidecadal variability of winter precipitation and snowfall frequencies in a Mediterranean mountain range, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-649, https://doi.org/10.5194/ems2024-649, 2024.

Snow plays a fundamental role in the water cycle. In some areas, precipitation in the form of snow and the formation of a seasonal snow cover in the mountains is the main source of freshwater. Snow, accumulated during the winter, supplies drinking water during the spring by quenching the prolonged summer drought of mediterranean regions.

There are several methods for measuring snow, some of which are based on measuring the distance from a certain elevation to the ground. This distance can be used to infer the height of the snow cover. To measure this distance, ultrasound or lasers are used. These systems are usually expensive and require infrastructure, both to support the sensors and to be powered by solar panels during the winter. These systems sometimes suffer from operational, structural or energy problems. On the other hand, there are rudimentary manual techniques based on the introduction of probes that determine the distance to the ground in a very robust and simple way. It is also possible to extract samples for density calculation in trenches specifically dug for that purpose. These manual techniques are inexpensive, highly robust, but require human intervention for their operation, therefore, the spatial and temporal density is low.

For several years, techniques have been employed to ascertain the height of the snowpack by analyzing temperature data collected at varying heights. These systems, commonly referred to as snow poles, combine the benefits of manual methods, particularly their simplicity, with those of automatic methods, such as their higher temporal resolution. Additionally, they offer further advantages, including their low cost and minimal environmental impact, which allow for a greater density of measurement points to be obtained. This is particularly crucial in complex terrain like mountains. This work presents the methods used to obtain not only the height of the snowpack, but also its equivalent in water using this type of snow pole. Obtaining the water content is especially important and novel in this field. Furthermore, it presents the evolution of the traditional snow pole with several enhancements related to new IoT hardware available. Also, sensitivity tests in the laboratory, network operation and mesh design results will be shown.

How to cite: Martínez Foronda, A., García Maroto, D., and Durán Montejano, L.: A new method for retrieving high spatial resolution snowpack height and water equivalent, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-472, https://doi.org/10.5194/ems2024-472, 2024.

Dramatic sea ice loss has recently occurred at both poles. Multiple studies have suggested that changes to sea ice can impact weather in both the polar regions and mid-latitudes. However, the current generation of climate models disagrees on the rate and location of sea ice loss, and on the rate of warming in the polar regions.Thus, the atmospheric response to sea ice loss within and outside the polar regions remains highly uncertain. To reduce this uncertainty, we have performed a set of coordinated simulations with four different atmospheric general circulation models (AGCMs) within the project “Climate Relevant interactions and feedbacks: the key role of sea ice and Snow in the polar and global climate system” (CRiceS). A baseline simulation and six perturbation simulations were performed, all of which were 40-years long and had prescribed  sea surface temperatures (SSTs) and sea ice concentration. In the perturbation simulations, the SSTs and sea ice concentration were changed independently, and then both were changed together. The SST and sea ice concentrations were obtained from CMIP6 simulations with the Australian Earth system model ACCESS-ESM1.5. Monthly-mean SST and sea-ice area averaged over 20 years of simulation were taken from 1) the historical simulation (years 1950-1970, Baseline simulation), 2) the scenario SSP1-2.6 simulation (years 2080-2100), and 3) the scenario SSP5-8.5 simulation (years 2080-2100) and were then used as perpetual monthly average values of SSTs and sea ice fraction in our model simulations, thus eliminating inter-annual variability in SSTs and sea ice. This array of perturbation experiments, performed with four AGCMs, allows us to isolate atmospheric responses in polar regions and mid-latitudes that are due to SST or sea ice changes, examine the linearity of these feedbacks, and investigate the robustness of the atmospheric responses. The results of this coordinated modelling experiment show that the models agree well on the magnitude and spatial distribution of the 2-m temperature and precipitation response. Increasing SSTs has a larger and more spatially extensive impact on the overall response than decreases in sea ice,  which primarily only cause a localised response in regions where sea ice disappears (most notably, a strong warming over the Arctic ocean in winter). The models agree less well on the magnitude and spatial distribution of the mean sea level pressure response, in particular over northern Europe and Antarctica, suggesting that modelled uncertainties associated with atmospheric circulation are larger than uncertainties associated with thermodynamics. These results and others, along with information about the openly available dataset, will be presented. 

How to cite: Naakka, T., Köhler, D., Nordling, K., Räisänen, P., Tronstad Lund, M., Makkonen, R., Merikanto, J., Samset, B., Sinclair, V., Thomas, J., and Ekman, A.: Role of sea surface temperature and sea-ice changes in high-latitude climate change: a multi-model experiment within the CRiceS H2020 project., EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-736, https://doi.org/10.5194/ems2024-736, 2024.

The Earth has warmed significantly over the past 40 years, and the fastest rate of warming has occurred in and around the Arctic. The warming of northern high latitudes at a rate of almost four times the global average (Rantanen et al., 2022), known as Arctic amplification, is associated with sea ice loss, glacier retreat, permafrost degradation, and expansion of the melting season. Since the mid-2000s, summer sea ice has exhibited a rapid decline, reaching record minima in September sea ice area in 2007 and 2012. However, after the early 2010s, the downward trend of minimum sea ice area appears to decelerate (Swart et al., 2015; Baxter et al., 2019). This apparent slowdown and the preceding acceleration in the rate of sea ice loss are puzzling in light of the steadily increasing rate of greenhouse gas emissions of about 4.5 ppm yr⁻¹ over the past decade (Friedlingstein et al., 2023) that provides a constant climate forcing. Recent studies suggest that low-frequency internal climate variability may have been as important as anthropogenic influences on observed Arctic sea ice decline over the past four decades (Dörr et al., 2023; Karami et al., 2023). Here, we investigate how unusual this decade-long pause in Arctic summer sea ice decline is within the context of internal climate variability. To do so, we first assess how rare this is deceleration of Arctic sea ice loss is by comparing it to trends in CMIP6 historical simulations. We also use simulations from the Decadal Climate Prediction Project (DCPP) contribution to CMIP6 to determine if initializing decadal prediction systems from estimates of the observed climate state substantially improves their performance in predicting the slowdown in Arctic sea ice loss over the past decade. As the DCPP does not specify the data or the methods to be used to initialize forecasts or how to generate ensembles of initial conditions, we also assess how different formulations affect the skill of the forecasts by analyzing differences between models. This work provides an opportunity to attribute this pause in Arctic sea ice retreat to interannual internal variability or radiative external forcings, something that observation analysis alone cannot achieve.

How to cite: DeRepentigny, P., Massonnet, F., Bilbao, R., and Materia, S.: How unusual is the recent decade-long pause in Arctic summer sea ice retreat?, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-1025, https://doi.org/10.5194/ems2024-1025, 2024.

The melting of snow and ice in Greenland has accelerated since the 1990s, resulting in significant impacts on the ecosystem, such as sea-level rise. However, the spatiotemporal evolution of Greenland's peripheral glaciers and ice caps (GICs) during the late Holocene period remains poorly understood. Understanding the maximum extent of these glaciers during the last millennium contextualize ongoing glacier trends in response to a changing climate. Currently, there is a lack of agreement between geological evidence of last-millennium maximum moraine extension and the prevailing climate conditions of that time. In this study, we aimed to model the past evolution of GICs in Central-Western Greenland and estimate anomalies relative to present-day conditions to reconcile past climate and quantify committed ice loss within a changing climate. We utilized the Instructed Glacier Model (IGM), a physically based glacier model incorporating mass conservation principles and deep learning emulator to estimate 3D ice-flow dynamics. Initially, the IGM was calibrated and validated using an ensemble of model parameterization options and climate perturbed conditions to reproduce the actual glacier area and ice thickness. The model successfully replicated ice-thickness and glaciers extension, reaching stable-state conditions for glacier area after a 500-year model run. This validated model was then forced with a range of potential air temperature and precipitation conditions based on estimates derived from ice core data near the study area. The resulting maximum glacier termini were validated with cosmogenic dating evidence from the last millennium (late Medieval Warm Period and onset of the Little Ice Age). The results indicated that air temperatures were at least < -0.75 ºC compared to the baseline climate (1960-1990 period) or <-0.5ºC with precipitation > 10%. These calibrated climate conditions suggested a reduction in glacier area and an ice thickness of approximately 20% compared to near present-day (2022) conditions. Using positive degree-day function calibrated with mass balance data, and a long-term model run (500 years after calibration), an increase of +1ºC would lead to a decrease in glacier area and ice thickness of around >50% compared to present-day conditions. These findings provide insights into the past glacier evolution within a long-term temporal perspective and help contextualize ongoing glacier retreat in response to climate change.

How to cite: Bonsoms, J., Oliva, M., López-Moreno, J. I., and Jouvet, G.: Glacier ice loss in Central-Western Greenland from last-millennium maximum to present, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-188, https://doi.org/10.5194/ems2024-188, 2024.

Debris flows and slush flows are mass movements that can be triggered abruptly by precipitation and snowmelt. They are a well known contributor to geomorphic changes and potential geohazards in areas such as the subpolar regions. In this study we discuss and analyze a series of mass movements linked to a single event that happened between July 6^th and 7^th 2023 in Central West Greenland. An atmospheric river led extreme precipitation into Qeqertarsuaq (Disko Island) and surrounding areas, increasing late spring snowmelt runoff significantly and causing hundreds of slush flows and debris flows, which also damaged local infrastructures. We combined remote sensing observations (Sentinel-2 and drone-based) before and after the event to map the larger mass movements. We then used the environmental monitoring dataset available in the area (Greenland Ecosystem Monitoring Disko) and climate reanalysis (Copernicus Arctic Regional Reanalysis) data to assess the synoptic pattern at the base of the event. We found almost 200 significant slush flows and debris flows only in Disko Island. During the 18-hours-event cumulative precipitation peaked 100mm being generally above 80mm in several portions of the island (mainly in the Southwest) where most events occurred. An increase in moisture transport through atmospheric rivers in a warming Arctic, has already been seen as a further contributor to abrupt glacial melting. We show here how such events are able to trigger potential hazards to local communities, making necessary to increase our knowledge about past events and future hazards in remote and less monitored areas, such as Greenland.

How to cite: Colucci, R. R., Securo, A., Del Gobbo, C., Sigsgaard, C., Svennevig, K., and Citterio, M.: Extensive hydrogeological disruption triggered by an atmospheric river affecting Disko Island (West Greenland) in summer 2023, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-857, https://doi.org/10.5194/ems2024-857, 2024.

How to cite: Meabe, N., Gonzalez-Rouco, J. F., García- Pereira, F., Martínez-Vila, A., Steinert, N. J., de Vrese, P., Jungclaus, J., and Lorenz, S.: Changes in Land Surface Model Thermodynamics and Hydrology: Implications for Arctic Amplification , EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-1112, https://doi.org/10.5194/ems2024-1112, 2024.

The land surface albedo is one of the key parameters and a driver in climate and weather models since it regulates the shortwave radiation absorbed by the Earth’s surface. In the Polar Regions, the high albedo of snow and ice helps to maintain low surface temperature by reflecting most of the incident solar energy. As the temperature increases and the snow and ice melt, the absorption of solar radiation increases, leading to more warming and melting. This positive ice-albedo feedback is partially responsible for the amplified warming in the Arctic compared to lower latitudes.

In remote areas, where in-situ instruments are absent, satellites are crucial to measure surface albedo changes.

 In this work, a comparison of satellite and in-situ measurements of surface albedo is conducted. The area of interest selected is around the Thule High Arctic Atmospheric Observatory (THAAO, https://www.thuleatmos-it.it) on the North-western coast of Greenland (76.5°N, 68.8°W), where the measurements of downwelling and upwelling solar irradiance have been started in 2016. The used radiometers are regularly calibrated, and corrections for thermal offset are applied.

Albedo determinations based on  MODIS observations from both Terra and Aqua (MODIS MCD43A3 dataset), consisting of daily values with a spatial resolution of 500 m, have been compared with the ground-based measurements.

The analysis has been carried out through five successive steps: the choice of the size of the area for averaging the satellite data; the application of data selection methods; the determination of Blue Sky Albedo by weighting Black and White Sky Albedo; the selection of clear sky conditions based on in-situ measurements; and the comparison of the ground-based and satellite albedo measurements for different areas (1 km x 1 km, 2 km x 2 km and 4 km x 4 km centred at THAAO and including only land surface) and sky conditions (all-sky and cloud-free)

Moreover, filters based on the quality flag have been applied to select the highest-quality data.

The albedo measurements were compared only for cloud-free cases selected using the in-situ solar irradiance measurements (332 cases out of 2922 in the period July 2016 – October 2023).

The results show an underestimation of albedo measurements from satellite compared to the ground-based measurements at the THAAO over a large part of the period considered. The best agreement is found in the summer when there is no snow around the observatory, and the mean measured albedo value is 0.202. The mean bias during this season is around 0.004 for cloud-free conditions and 0.016 for all sky conditions. In spring, when the in-situ albedo values are highly variable between (0.350 and 1), the mean bias is around 0.051 for cloud-free conditions and 0.076 for all sky conditions.

How to cite: Tosco, M., Meloni, D., di Sarra, G. A., Calì Quaglia, F., Muscari, G., Di Iorio, T., and Pace, G.: Comparison of land surface albedo between MODIS and ground-based measures at the Thule High Arctic Atmospheric Observatory (THAAO) in Pituffik, Greenland, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-253, https://doi.org/10.5194/ems2024-253, 2024.

Antarctic sea ice plays an important role in the global climate through its influence on local and global oceanic and atmospheric circulations, planetary radiative balance, and the crucial support it provides for Southern Ocean ecosystem. Understanding the physical processes influencing Antarctic sea ice, and the drivers of its change are therefore of broad interest. The sea ice–covered the Southern Ocean, has relatively weak stratification in the upper ocean, where a relatively thin halocline separates the cold winter mixed layer from significantly warmer ocean interior. When warmer waters from the ocean interior enter the mixed layer, it can melt sea ice at its base. Features in the upper ocean, like mesoscale eddies can impact the thermohaline structure and stratification in this region and can then influence the heat delivered to the surface. However, the mesoscale dynamics in the polar regions, especially under sea ice cover, is little known due to the limited observations and the inability of many numerical models to resolve mesoscale processes in the high latitudes.   

This study aims to understand better the interaction between ocean mesoscale eddies and sea ice using high-resolution European Eddy RIch Earth System Models (EERIE) models. We investigate the effect of mesoscale eddies locally, and the integrated effect of eddy-sea ice interaction in the circumpolar Southern Ocean. Previous studies have identified eddy ice interactions to vary within regions of varying sea ice concentrations, such as in the high concentration pack ice and low-concentration marginal ice zones. The variations in the eddy-sea ice interaction in the Southern Ocean, within the open ocean, pack ice, and marginal ice zones are further investigated in this study.  

How to cite: Libera, S., Goosse, H., Chen, T.-C., and Putrasahan, D.: Evaluation of Mesoscale Eddy-Ice interaction in the Southern Ocean using High-Resolution models, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-24, https://doi.org/10.5194/ems2024-24, 2024.

Understanding the evolving dynamics of El Niño teleconnections is crucial due to its profound global impact. While current climate models consistently predict a shift in these teleconnections towards the east and poles, the mechanisms behind this shift remain unclear. Surprisingly, previous studies have overlooked the role of barotropic Rossby waves, which are fundamental to teleconnections. This investigation aims to fill this gap by examining the changes in these waves through spectral analysis, measuring circulation anomaly distances, and exploring their dispersion relationship.

The results indicate that as the climate warms, the wavelength of teleconnection-forming waves is expected to increase, with a greater prevalence of zonal-wavenumber-2 waves. This shift in wavelength suggests alterations in the propagation characteristics of Rossby waves, potentially influencing the spatial distribution and intensity of teleconnection patterns associated with El Niño events. Additionally, changes in the mean state, such as the strengthening of westerlies in high-emission scenarios, lead to shifts in wave frequencies. In particular, the Southern Hemisphere exhibits a more pronounced response due to the smaller inter-model spread of the mean state compared to the Northern Hemisphere.

Consequently, El Niño's influence is forecasted to extend towards higher latitudes in both hemispheres, impacting regions that may not have experienced significant El Niño-related effects in the past. In the Southern Hemisphere, where the impacts of climate change are already evident, this shift in El Niño teleconnections could have far-reaching consequences. For instance, warming oceans near West Antarctica and increased moisture transport towards Antarctica, driven by El Niño events, are projected to shift eastward under high-emission scenarios. These changes could have implications for regional climate variability, sea ice dynamics, and ecosystems in the Antarctic region, highlighting the interconnected nature of global climate systems.

These findings shed light on the complex interplay between climate change and El Niño teleconnections, offering valuable insights into future climate patterns. Understanding these dynamics is crucial for policymakers, stakeholders, and communities to better prepare for and adapt to the impacts of climate change, particularly in regions like Antarctica where the effects can be significant and wide-ranging. By elucidating the mechanisms driving changes in El Niño teleconnections, this research contributes to our broader understanding of how global climate patterns may evolve in a warming world, informing strategies for mitigation and adaptation efforts.

How to cite: Jin, E. K. and Lee, H.-J.: Unraveling the dynamics behind future changes in El Niño teleconnections impacting Antarctica, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-796, https://doi.org/10.5194/ems2024-796, 2024.