Special Issue in Atmosphere
The Mediterranean region is an area where prediction at different timescales (subseasonal to decadal or even longer timescales) keeps being a challenge. In order to improve future predictions, the study of the past climate is crucial. By improving our knowledge about the past and the current climate, our knowledge about the future climate will be improved. This Special Issue aims to collect as much information as possible about long-term climate variability in the Mediterranean region. We welcome different studies using observations, proxies, re-analyses and models for assessing the characteristics, the main processes, and the variability of the Mediterranean Climate from the past to the future.
Potential topics include but are not limited to:
- The past of the Mediterranean region: from the last millennium to historical climatology in the Mediterranean area (using models, proxies or observations);
- Mechanisms associated with extreme events in the Mediterranean region;
- Compounds events affecting the Mediterranean region;
- Assessing the role of the oceanic and atmospheric modes of variability in the Mediterranean region climate using models, observations or proxies;
- Teleconnections associated to the Mediterranean region;
- The future of the Mediterranean region: from subseasonal to decadal predictions;
- Climate change and the Mediterranean region: attribution studies of extreme events associated to the climate change;
- Risks, vulnerability, and impacts in the Mediterranean region: assessment, mitigation, and adaptation strategies.
Prof. Dr. Pedro Ribera
Dr. M. Carmen Alvarez-Castro
7 July 2020
Session EGU 4-8 May 2020
Co-organized by AS4/CL2/NH10
Convener: Davide FarandaECS | Co-conveners: Carmen Alvarez-CastroECS, Gabriele MessoriECS, Niklas BoersECS, Kai KornhuberECS, Catrin Ciemer, Francesco Ragone
Displays | Chat Tue, 05 May, 14:00-15:45 (CEST)
| Webinar Wed, 13 May, 15:30-17:30 (CEST)
- How extremes have varied or are likely to vary under climate change;
- How well climate models capture extreme events;
- Attribution of extreme events;
- Emergent constraints on extremes;
- Linking dynamical systems extremes to geophysical extremes;
- Extremes in dynamical systems;
- Downscaling of weather and climate extremes.
- Linking the dynamics of climate extremes to their impacts
Extremes in Geophysical Sciences: Dynamics, Thermodynamics and Impacts
16:00-16:45 PM: Ángel G. Muñoz
Cross-timescale interference and predictability of extremes: a chimera?D2814 | EGU2020-21105 | solicited
Cross-timescale interference involves linear and non-linear interactions between climate modes acting at multiple timescales (Muñoz et al., 2015, 2016, 2017; Robertson et al., 2015; Moron et al., 2015), and that are related to windows of opportunity for enhanced predictive skill (Mariotti et al., 2020), with relevant societal impacts (e.g., Doss-Gollin et al., 2018; Anderson et al., 2020). Using a simple mathematical model, reanalysis data and gridded observations, here we analyze plausible mechanisms for cross-timescale interference, describing conditions for coupling of oscillating modes and its impact on extreme rainfall occurrence and predictive skill. Concrete examples for Northeast North America and southern South America are discussed, as well as implications for climate model diagnostics.
16:45-17:30 PM: Theodore Shepherd
Storyline approach to extreme event characterization.
EGU2020-4896 | solicited | Highlight
Extreme climate events are invariably highly nonlinear, complex events, resulting from the confluence of multiple causal factors, and often quite singular. In any complex system there is a tension between analysis methods that respect the singularity of the extreme events at the price of statistical repeatability, and those that emphasize statistical repeatability at the price of nonlinearity and complexity; this dichotomy is found across all areas of science. In the climate context, the 'storyline' approach has emerged in recent years as a way of following the first of these two pathways. I will discuss how the storyline approach can be cast within the mathematical framework of causal networks, which provides a way to bridge between the storyline and probabilistic approaches. This also provides a way to interpret data in an appropriately conditional manner, thereby aiding model-measurement comparison.
15:30-17:30 PM (CEST)
3 de Abril 2019