A5034213012- Arctic and Antarctic ice dynamics
- Cryospheric studies and observations
- Methane Hydrates and Related Phenomena
- Climate variability and models
- Climate change and permafrost
- Oceanographic and Atmospheric Processes
- Meteorological Phenomena and Simulations
- Geophysics and Gravity Measurements
- Ionosphere and magnetosphere dynamics
- Geological Studies and Exploration
- Arctic and Russian Policy Studies
- Earthquake Detection and Analysis
- Iron and Steelmaking Processes
- Food Industry and Aquatic Biology
- Advanced Power Generation Technologies
- Indigenous Studies and Ecology
- Legionella and Acanthamoeba research
- Computational Physics and Python Applications
- Magnetic confinement fusion research
- Plasma Diagnostics and Applications
- Systemic Lupus Erythematosus Research
- Rabies epidemiology and control
- Hepatitis C virus research
- Energy Load and Power Forecasting
- Metallurgical Processes and Thermodynamics
CMCC Foundation - Euro-Mediterranean Center on Climate Change
2023-2024
NSF National Center for Atmospheric Research
2022-2024
Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou)
2023
Sun Yat-sen University
2023
Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai)
2023
Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung
2018-2022
University of Padua
2015
Ospedale San Bortolo
1994-1998
Abstract. We report on the first multi-year kilometre-scale global coupled simulations using ECMWF's Integrated Forecasting System (IFS) to both NEMO and FESOM ocean–sea ice models, as part of H2020 Next Generation Earth Modelling Systems (nextGEMS) project. focus mainly an unprecedented IFS-FESOM setup, with atmospheric resolution 4.4 km a spatially varying ocean that reaches locally below 5 grid spacing. A shorter simulation 2.8 has also been performed. number shortcomings in original...
Abstract With retreating sea ice and increasing human activities in the Arctic come a growing need for reliable forecasts up to months ahead. We exploit subseasonal‐to‐seasonal prediction database provide first thorough assessment of skill operational forecast systems predicting location edge on these time scales. find large differences between systems, with some showing lack predictive even at short weather scales best producing skillful more than 1.5 This highlights that area subseasonal...
Abstract. We report on the first multi-year km-scale global coupled simulations using ECMWF’s Integrated Forecasting System (IFS) to both NEMO and FESOM ocean-sea ice models, as part of Horizon 2020 Next Generation Earth Modelling Systems (nextGEMS) project. focus mainly two unprecedented IFS-FESOM setups, with an atmospheric resolution 2.8 km 4.4 km, respectively, same spatially varying ocean that reaches locally below 5 grid-spacing. This is enabled by a refactored model code allows for...
Abstract This paper describes and evaluates the assimilation component of a seamless sea ice prediction system, which is developed based on fully coupled Alfred Wegener Institute, Helmholtz Center for Polar Marine Research Climate Model (AWI‐CM, v1.1). Its ocean/ice with unstructured‐mesh discretization smoothly varying spatial resolution enables across wide range space time scales. The model complemented Parallel Data Assimilation Framework to assimilate observations in an Ensemble Kalman...
Abstract Correctly representing the snow on sea‐ice has great potential to improve cryosphere‐atmosphere coupling in forecasting and monitoring (e.g., reanalysis) applications, via improved modeling of surface temperature, albedo emissivity. This can also enhance all‐weather all‐surface coupled data assimilation for atmospheric satellite radiances. Using wintertime observations from two Arctic field campaigns, SHEBA N‐ICE2015, data, we explore merits different approaches represent over a set...
Machine learning models have emerged as powerful tools for simulating Earth system processes. Following their successful application in capturing atmospheric evolution medium-range weather forecasts, attention has increasingly shifted towards other components of the system, such marine and land environments. This interest is further driven by potential to enhance forecasting capabilities beyond medium range. frameworks offer remarkable flexibility integrating these model achieve a coherent...
Abstract. Leads and pressure ridges are dominant features of the Arctic sea ice cover. Not only do they affect heat loss surface drag, but also provide insight into underlying physics deformation. Due to their elongated shape referred as linear kinematic (LKFs). This paper introduces two methods that detect track LKFs in deformation data establish an LKF set for entire observing period RADARSAT Geophysical Processor System (RGPS). Both algorithms available open-source code applicable any...
Abstract Atmospheric reanalyses are widely used to estimate the past atmospheric near-surface state over sea ice. They provide boundary conditions for ice and ocean numerical simulations relevant information studying polar variability anthropogenic climate change. Previous research revealed existence of large temperature biases (mostly warm) Arctic in current generation reanalyses, which is linked a poor representation snow stably stratified layer forecast models produce reanalyses. These...
© 2024 American Meteorological Society. This published article is licensed under the terms of default AMS reuse license. For information regarding this content and general copyright information, consult Copyright Policy (www.ametsoc.org/PUBSReuseLicenses). Corresponding author: Clare Eayrs, clare.eayrs@kopri.re.kr
The PCAPS ORCAS task team is part of the WMO's World Weather Research Programme's (Polar Coupled Analysis and Prediction for Services) project. builds upon foundational work Polar Project its flagship activity, Year Prediction, to improve actionability, impact, fidelity environmental forecasting human well-being in Arctic Antarctic regions. a community effort that aims enhance capabilities by exploring potential new AI techniques. Outcomes from this initiative will contribute strengthening...
Machine learning (ML) techniques have emerged as a powerful tool for predicting weather and climate systems, particularly in the short-term evolution of atmosphere. Here, we look at potential ML to predict 3d-ocean.  We present data-driven global ocean model, developed within Destination Earth project, form component fully earth system model. Following skill shown by AIFS (Lang et al, 2024), use graph-based encoder-decoder design, with transformer backbone. Our model is trained on...
Recent advancements in data-driven weather forecasting have demonstrated superior accuracy compared to traditional physics-based approaches for several components of the Earth system. While prior work on wave has focused wave-atmosphere interactions through fine-tuning pre-trained models or training specific forced models, we present results a joint model waves and atmosphere, two simultaneously.Surface winds, which can be well represented by atmospheric are highly coupled. Therefore, train...
Arctic sea ice has recently experienced rapid changes, indicating a transition toward new regime dominated by the marginal zone (MIZ) during summer. Modifications in extent, distribution, and volume of MIZ have significant implications for polar global climate, as physical processes largely differ from those pack ice, including air/sea exchanges, dynamic interactions with waves currents, fast thermodynamic impact on marine ecosystems.Copernicus Marine Service (CMS) provides wide range...
Abstract Coupled subseasonal forecast systems with dynamical sea ice have the potential of providing important predictive information in polar regions. Here, we evaluate ability operational ensemble prediction to predict location edge Antarctica. Compared Arctic, Antarctica shows on average a 30% lower skill, only one system remaining more skillful than climatological benchmark up ∼30 days ahead. Skill tends be highest west Antarctic sector during early freezing season. Most tend...
Abstract Models struggle to accurately simulate observed sea ice thickness changes, which could be partially due inadequate representation of thermodynamic processes. We analyzed co‐located winter observations the Arctic from Multidisciplinary Drifting Observatory for Study Climate evaluating and improving processes in models, aiming enable more accurate predictions warming climate system. model snow heat conduction transects forced by realistic boundary conditions understand impact...
Abstract A new version of the AWI Coupled Prediction System is developed based on Alfred Wegener Institute Climate Model v3.0. Both ocean and atmosphere models are upgraded or replaced, reducing computation time by a factor 5 at given resolution. This allowed us to increase ensemble size from 12 30, maintaining similar resolution in both model components. The online coupled data assimilation scheme now additionally utilizes sea‐surface salinity sea‐level anomaly as well temperature profile...
Abstract. We developed a new version of the Alfred Wegener Institute Climate Model (AWI-CM3), which has higher skills in representing observed climatology and better computational efficiency than its predecessors. Its ocean component FESOM2 (Finite-volumE Sea ice–Ocean Model) multi-resolution functionality typical unstructured-mesh models while still featuring scalability similar to regular-grid models. The atmospheric OpenIFS (CY43R3) enables use latest developments...
Abstract. The recent development of data-assimilative reanalyses the global ocean and sea ice enables a better understanding polar region dynamics provides gridded descriptions variables without temporal spatial gaps. Here, we study spatiotemporal variability Arctic area thickness using Global Reanalysis Ensemble Product (GREP) produced disseminated by Copernicus Marine Service (CMS). GREP is compared validated against state-of-the-art regional PIOMAS TOPAZ, observational datasets...
To counteract global warming, a geoengineering approach that aims at intervening in the Arctic ice‐albedo feedback has been proposed. A large number of wind‐driven pumps shall spread seawater on surface winter to enhance ice growth, allowing more survive summer melt. We test this idea with coupled climate model by modifying exchange processes such physical effect is simulated. Based experiments RCP 8.5 scenario forcing, we find it possible keep late‐summer sea cover current extent for next...
Abstract We have equipped the unstructured‐mesh global sea‐ice and ocean model FESOM2 with a set of physical parameterizations derived from single‐column Icepack. The update has substantially broadened range processes that can be represented by model. new features are directly implemented on unstructured mesh, thereby benefit flexibility comes it in terms spatial resolution. A subset parameter space three configurations, increasing complexity, been calibrated an iterative Green's function...
Abstract The impact of Arctic sea ice decline on the weather and climate in mid-latitudes is still much debated, with observation suggesting a strong models weaker link. In this study, we use atmospheric model OpenIFS, set experiments following protocol outlined Polar Amplification Model Intercomparison Project (PAMIP), to investigate whether simulated response future changes fundamentally depends resolution. More specifically, increase horizontal resolution from 125km 39km 91 vertical...
Abstract. As the demand for increased resolution and complexity in unstructured sea ice models is growing, a more advanced transport scheme needed. In this study, we couple Semi-implicit Cross-scale Hydro-science Integrated System Model (SCHISM) with Icepack, column physics package of model CICE; key step to implement total variation diminishing (TVD) multi-class module coupled model. Compared upwind central difference scheme, TVD found have better performance both idealized realistic cases,...