Daniela Domeisen

Last Name

Domeisen

First Name

Daniela

ORCID

0000-0002-1463-929X

Organisational unit

09612 - Domeisen, Daniela / Domeisen, Daniela

Show all metadata

Search Results

Publications 1 - 10 of 107

Predictors and prediction skill for marine cold air outbreaks over the Barents Sea
Polkova, Iuliia; Afargan-Gerstman, Hilla; Domeisen, Daniela; et al. (2021)
Quarterly Journal of the Royal Meteorological Society
Marine cold air outbreaks (MCAOs) create conditions for hazardous maritime mesocyclones (polar lows) posing risks to marine infrastructure. For marine management, skilful predictions of MCAOs would be highly beneficial. For this reason, we investigate (i) the ability of a seasonal prediction system to predict MCAOs and (ii) the possibilities to improve predictions through large‐scale causal drivers. Our results show that the seasonal ensemble predictions have high prediction skill for MCAOs over the Nordic Seas for about 20 days starting from November initial conditions. To study causal drivers of MCAOs, we utilize a causal effect network approach applied to the atmospheric reanalysis ERA‐Interim and identify local sea surface temperature and atmospheric circulation patterns over Scandinavia as valuable predictors. Prediction skill for MCAOs is further improved up to 40 days including MCAO predictors in the analysis.
Projections and uncertainties of winter windstorm damage in Europe in a changing climate
Severino, Luca G.; Kropf, Chahan M.; Afargan-Gerstman, Hilla; et al. (2024)
Natural Hazards and Earth System Sciences
Winter windstorms are among the most significant natural hazards in Europe linked to fatalities and substantial damage. However, projections of windstorm impact in Europe under climate change are highly uncertain. This study combines climate projections from 30 general circulation models participating in Phase 6 of the Coupled Model Intercomparison Project (CMIP6) with the climate risk assessment model CLIMADA to obtain projections of windstorm-induced damage over Europe in a changing climate. We conduct an uncertainty-sensitivity analysis and find large uncertainties in the projected changes in the damage, with climate model uncertainty being the dominant factor of uncertainty in the projections. We investigate the spatial patterns of the climate change-induced modifications in windstorm damage and find an increase in the damage in northwestern and northern central Europe and a decrease over the rest of Europe, in agreement with an eastward extension of the North Atlantic storm track into Europe. We combine all 30 available climate models in an ensemble-of-opportunity approach and find evidence for an intensification of future climate windstorm damage, in which damage with return periods of 100 years under current climate conditions becomes damage with return periods of 28 years under future SSP585 climate scenarios. Our findings demonstrate the importance of climate model uncertainty for the CMIP6 projections of windstorms in Europe and emphasize the increasing need for risk mitigation due to extreme weather in the future.
The role of atmospheric dynamics and large‐scale topography in driving heatwaves
Jiménez Esteve, Bernat; Domeisen, Daniela (2022)
Quarterly Journal of the Royal Meteorological Society
Heatwaves are weather events characterized by extreme near-surface temperature anomalies that persist for several days, and therefore lead to catastrophic impacts on natural ecosystems, agriculture, human health, and economies. Different physical processes can contribute to the temperature anomaly associated with heatwaves. Previous studies have shown that increased solar radiation and adiabatic heating associated with blocking systems and local land–atmosphere coupling are important drivers of summer heatwaves. Less is known about the fundamental role of atmospheric large-scale dynamics and topography in generating heatwaves. Here, we perform idealized model simulations where all physical parameterisations are substituted by a simple zonally symmetric temperature relaxation scheme. This allows us to characterize the dynamical processes involved in the life cycle of heatwaves occurring at different latitudes. We find that blocking plays an active role in the life cycle of high- and midlatitude heatwaves, while blocking is less relevant for low-latitude heatwaves. Rossby-wave packets are the dominant drivers for midlatitude heatwaves, with horizontal advection being the main mechanism leading to heat extremes. Heatwaves exhibit a higher persistence and frequency near the pole and Equator compared with the midlatitudes, but a higher intensity in the midlatitudes compared with higher and lower latitudes. Topography located along the midlatitude jet has the largest impact on the heatwave distribution around the planet, resulting in increased heatwave frequency upstream for moderate topographic forcing and a circumglobal increase for topographic elevations above 6 km. Identifying the most relevant processes driving heatwaves can potentially benefit the prediction and representation of extreme events in operational weather and climate forecast systems.
Modeling stratospheric polar vortex variation and identifying vortex extremes using explainable machine learning
Wu, Zheng; Beucler, Tom; Székely, Enikő; et al. (2022)
Environmental Data Science
The winter stratospheric polar vortex (SPV) exhibits considerable variability in magnitude and structure, which can result in extreme SPV events. These extremes can subsequently influence weather in the troposphere from weeks to months and thus are important sources of surface predictability. However, the predictability of the SPVextreme events is limited to 1–2 weeks in state-of-the-art prediction systems. Longer predictability timescales of SPV would strongly benefit long-range surface prediction. One potential option for extending predictability timescales is the use of machine learning (ML). However, it is often unclear which predictors and patterns are important for ML models to make a successful prediction. Here we use explainable multiple linear regressions (MLRs) and an explainable artificial neural network (ANN) framework to model SPV variations and identify one type of extreme SPV events called sudden stratospheric warmings. We employ a NN attribution method to propagate the ANN’s decision-making process backward and uncover feature importance in the predictors. The feature importance of the input is consistent with the known precursors for extreme SPV events. This consistency provides confidence that ANNs can extract reliable and physically meaningful indicators for the prediction of the SPV. In addition, our study shows a simple MLR model can predict the SPV daily variations using sequential feature selection, which provides hints for the connections between the input features and the SPV variations. Our results indicate the potential of explainable ML techniques in predicting stratospheric variability and extreme events, and in searching for potential precursors for these events on extended-range timescales.
Nonlinearity in the North Pacific atmospheric response to a linear ENSO forcing
Jiménez Esteve, Bernat; Domeisen, Daniela (2019)
Geophysical Research Letters
Exploring hydrological system performance for alpine low flows in local and continental prediction systems
Chang, Annie; Ramos, Marie-Helena; Harrigan, Shaun; et al. (2024)
Journal of Hydrology: Regional Studies
Study region: The European alpine space. Study focus: Despite the advancements in hydrological modeling, there is a lack of comparative studies quantifying the performance differences between local and large-scale models, particularly in the context of drought and low flow assessment. This study addresses this gap by designing a framework to evaluate the European Flood Awareness System (EFAS), a continental system, in simulating low flow events across 101 alpine stations from 1999–2018, with detailed comparisons to two local systems — GR6J in France and PREVAH in Switzerland — at 34 of these stations. New hydrological insights for the region: The results show that the local systems, PREVAH and GR6J, generally outperform the continental system EFAS for almost all stations. The performance gap between the systems increases as low flow conditions intensify, highlighting the importance of local systems for extreme low flow events. Despite EFAS not being specifically set up for low flows, it has shown an overall acceptable performance compared to the local hydrological systems, especially at locations that are not calibrated within the EFAS system, indicating its potential in ungauged areas. This study lays a foundation for understanding how a continental hydrological system like EFAS can complement local systems or fill the gap when a local system is unavailable to provide reliable predictions of low flow conditions.
Review article: The growth in compound weather and climate event research in the decade since SREX
Brett, Lou; White, Christopher J.; Domeisen, Daniela; et al. (2025)
Natural Hazards and Earth System Sciences
Compound weather and climate events occur when multiple drivers or hazards combine to create societal or environmental risks. Many high-impact weather and climate events, such as simultaneous heatwaves and droughts, are compound in nature, leading to more severe consequences than individual events. This review examines the growth of compound event research in the decade since the IPCC Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation (SREX) in 2012, which built on existing approaches to highlight the need to better understand compound events. A systematic review catalogues 366 peer-reviewed papers published between 2012-2022, revealing an annual average increase of 60 % of papers across the decade, particularly on multivariate (co-occurring) events. Most studies focus on Europe, Asia, and North America, with significant gaps in Africa, South America, and Oceania. The review highlights certain modulators, such as the El Ni & ntilde;o-Southern Oscillation, and selected event types, including compound floods and high-temperature low-precipitation events, as the most studied in the literature. The review recommends expanding research in underrepresented regions and studying a broader range of typologies, events, and modulators. It also calls for greater cross-disciplinarity and sectoral collaboration to improve our understanding of compound event impacts and manage the evolving risks in a changing climate.
The influence of future changes in springtime Arctic ozone on stratospheric and surface climate
Chiodo, Gabriel; Friedel, Marina; Seeber, Svenja; et al. (2023)
Atmospheric Chemistry and Physics
Stratospheric ozone is expected to recover by the mid-century due to the success of the Montreal Protocol in regulating the emission of ozone-depleting substances (ODSs). In the Arctic, ozone abundances are projected to surpass historical levels due to the combined effect of decreasing ODSs and elevated greenhouse gases (GHGs). While long-term changes in stratospheric ozone have been shown to be a major driver of future surface climate in the Southern Hemisphere during summertime, the dynamical and climatic impacts of elevated ozone levels in the Arctic have not been investigated. In this study, we use two chemistry climate models (the SOlar Climate Ozone Links - Max Planck Ocean Model (SOCOL-MPIOM) and the Community Earth System Model - Whole Atmosphere Community Climate Model (CESM-WACCM)) to assess the climatic impacts of future changes in Arctic ozone on stratospheric dynamics and surface climate in the Northern Hemisphere (NH) during the 21st century. Under the high-emission scenario (RCP8.5) examined in this work, Arctic ozone returns to pre-industrial levels by the middle of the century. Thereby, the increase in Arctic ozone in this scenario warms the lower Arctic stratosphere; reduces the strength of the polar vortex, advancing its breakdown; and weakens the Brewer-Dobson circulation. The ozone-induced changes in springtime generally oppose the effects of GHGs on the polar vortex. In the troposphere, future changes in Arctic ozone induce a negative phase of the Arctic Oscillation, pushing the jet equatorward over the North Atlantic. These impacts of future ozone changes on NH surface climate are smaller than the effects of GHGs, but they are remarkably robust among the two models employed in this study, canceling out a portion of the GHG effects (up to 20% over the Arctic). In the stratosphere, Arctic ozone changes cancel out a much larger fraction of the GHG-induced signal (up to 50 %- 100 %), resulting in no overall change in the projected springtime stratospheric northern annular mode and a reduction in the GHG-induced delay of vortex breakdown of around 15 d. Taken together, our results indicate that future changes in Arctic ozone actively shape the projected changes in the stratospheric circulation and their coupling to the troposphere, thereby playing an important and previously unrecognized role as a driver of the large-scale atmospheric circulation response to climate change.
Stratospheric Nudging And Predictable Surface Impacts (SNAPSI): a protocol for investigating the role of stratospheric polar vortex disturbances in subseasonal to seasonal forecasts
Hitchcock, Peter; Butler, Amy; Charlton-Perez, Andrew; et al. (2022)
Geoscientific Model Development
Long-range prediction and the stratosphere
Scaife, Adam A.; Baldwin, Mark P.; Butler, Amy H.; et al. (2022)
Atmospheric Chemistry and Physics
Over recent years there have been concomitant advances in the development of stratosphere-resolving numerical models, our understanding of stratosphere–troposphere interaction, and the extension of long-range forecasts to explicitly include the stratosphere. These advances are now allowing for new and improved capability in long-range prediction. We present an overview of this development and show how the inclusion of the stratosphere in forecast systems aids monthly, seasonal, and annual-to-decadal climate predictions and multidecadal projections. We end with an outlook towards the future and identify areas of improvement that could further benefit these rapidly evolving predictions.

Publications 1 - 10 of 107

Daniela Domeisen

Last Name

First Name

ORCID

Organisational unit

Filters

Search Results