Coupling heat wave and wildfire occurrence across multiple ecoregions within a Eurasia longitudinal gradient DOI Creative Commons

Elia Mario,

Lafortezza Raffaele,

Onofrio Cappelluti

et al.

The Science of The Total Environment, Journal Year: 2023, Volume and Issue: 912, P. 169269 - 169269

Published: Dec. 11, 2023

Understanding the relationship between heat wave occurrence and wildfire spread represents a key priority in global change studies due to significant threats posed on natural ecosystems society. Previous have not explored spatial temporal mechanism underlying waves wildfires occurrence, especially over large geographical regions. This study seeks investigate such with focus 37 ecoregions within Eurasia longitudinal gradient. The analysis is based dataset provided by GlobFire Final Fire Event Detection meteorological ERA5-land from Copernicus Climate service. In both cases we focused 2001-2019 timeframe. By means of 12 km square grid, three metrics, i.e., density, seasonality, severity wildfires, were computed as proxy fire regime. Heat also characterized terms periods, duration, intensity for same period. Statistical tests performed evaluate different patterns area. using Geographically Weighted Regression (GWR) modeled varying relationships characteristics metrics. As expected, our results suggest that identified gradient differ regimes. However, did show differences among ecoregions, but more evident variability regime metrics outcome GWR allowed us identify locations (i.e., hotspot areas) where positive significant. Hence, hotspots presence can be seen driver forest steppe ecosystems. findings this could contribute comprehensive assessment region, thus supporting cross-regional prevention strategies disaster risk mitigation.

Language: Английский

Record-shattering 2023 Spring heatwave in western Mediterranean amplified by long-term drought DOI Creative Commons
Marc Lemus-Cánovas, Damían Ínsua-Costa, Ricardo M. Trigo

et al.

npj Climate and Atmospheric Science, Journal Year: 2024, Volume and Issue: 7(1)

Published: Jan. 23, 2024

Abstract The western Mediterranean region experienced an exceptional and unprecedented early heatwave in April 2023. By shattering historical temperature records, especially the Iberian Peninsula northwestern Africa, this extreme offers a stark illustration of drought–heatwave compound event. Here, we investigate soil moisture–temperature interactions that underpinned event, using most up-to-date observations robust statistical analysis. Our results reveal moisture deficit preconditions, concurring with strong subtropical ridge as synoptic driver, had key contribution to amplification duration record-breaking heatwave. Specifically, estimate records would have been 4.53 times less likely 2.19 °C lower soils wet. These findings indicate content may be crucial variable for seasonal forecasting HW other climate regimes are already suffering increment frequency events.

Language: Английский

Citations

23
Towards multi-scale and context-specific heat health risk assessment - A systematic review DOI
Jiaxing Ye, Feng Yang

Sustainable Cities and Society, Journal Year: 2025, Volume and Issue: 119, P. 106102 - 106102

Published: Jan. 5, 2025

Language: Английский

Citations

3
Mortality impacts of the most extreme heat events DOI Creative Commons
Tom Matthews, Colin Raymond, Josh Foster

et al.

Nature Reviews Earth & Environment, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 4, 2025

Language: Английский

Citations

3
Vegetation–climate feedbacks across scales DOI Creative Commons
Diego G. Miralles, Jordi Vilà-Guerau De Arellano, Tim R. McVicar

et al.

Annals of the New York Academy of Sciences, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 24, 2025

Abstract Vegetation is often viewed as a consequence of long‐term climate conditions. However, vegetation itself plays fundamental role in shaping Earth's by regulating the energy, water, and biogeochemical cycles across terrestrial landscapes. It exerts influence consuming water resources through transpiration interception, lowering atmospheric CO 2 concentration, altering surface roughness, controlling net radiation its partitioning into sensible latent heat fluxes. This propagates atmosphere, from microclimate scales to entire boundary layer, subsequently impacting large‐scale circulation global transport moisture. Understanding feedbacks between atmosphere multiple crucial for predicting land use cover changes, accurately representing these processes models. review discusses biophysical mechanisms which modulates spatial temporal scales. Particularly, we evaluate on patterns, precipitation, temperature, considering both trends extreme events, such droughts heatwaves. Our goal highlight state science recent studies that may help advance our collective understanding they play climate.

Language: Английский

Citations

2
Artificial intelligence for modeling and understanding extreme weather and climate events DOI Creative Commons
Gustau Camps‐Valls, Miguel‐Ángel Fernández‐Torres, Kai-Hendrik Cohrs

et al.

Nature Communications, Journal Year: 2025, Volume and Issue: 16(1)

Published: Feb. 24, 2025

In recent years, artificial intelligence (AI) has deeply impacted various fields, including Earth system sciences, by improving weather forecasting, model emulation, parameter estimation, and the prediction of extreme events. The latter comes with specific challenges, such as developing accurate predictors from noisy, heterogeneous, small sample sizes data limited annotations. This paper reviews how AI is being used to analyze climate events (like floods, droughts, wildfires, heatwaves), highlighting importance creating accurate, transparent, reliable models. We discuss hurdles dealing data, integrating real-time information, deploying understandable models, all crucial steps for gaining stakeholder trust meeting regulatory needs. provide an overview can help identify explain more effectively, disaster response communication. emphasize need collaboration across different fields create solutions that are practical, understandable, trustworthy enhance readiness risk reduction. Artificial Intelligence transforming study like helping overcome challenges integration. review article highlights models improve response, communication trust.

Language: Английский

Citations

2
Analysis, characterization, prediction, and attribution of extreme atmospheric events with machine learning and deep learning techniques: a review DOI Creative Commons
Sancho Salcedo‐Sanz, Jorge Pérez-Aracíl, Guido Ascenso

et al.

Theoretical and Applied Climatology, Journal Year: 2023, Volume and Issue: 155(1), P. 1 - 44

Published: Aug. 28, 2023

Abstract Atmospheric extreme events cause severe damage to human societies and ecosystems. The frequency intensity of extremes other associated are continuously increasing due climate change global warming. accurate prediction, characterization, attribution atmospheric is, therefore, a key research field in which many groups currently working by applying different methodologies computational tools. Machine learning deep methods have arisen the last years as powerful techniques tackle problems related events. This paper reviews machine approaches applied analysis, most important extremes. A summary used this area, comprehensive critical review literature ML EEs, provided. has been extended rainfall floods, heatwaves temperatures, droughts, weather fog, low-visibility episodes. case study focused on analysis temperature prediction with DL is also presented paper. Conclusions, perspectives, outlooks finally drawn.

Language: Английский

Citations

28
Biodiversity and Climate Extremes: Known Interactions and Research Gaps DOI Creative Commons
Miguel D. Mahecha, Ana Bastos, Friedrich J. Bohn

et al.

Earth s Future, Journal Year: 2024, Volume and Issue: 12(6)

Published: June 1, 2024

Abstract Climate extremes are on the rise. Impacts of extreme climate and weather events ecosystem services ultimately human well‐being can be partially attenuated by organismic, structural, functional diversity affected land surface. However, ongoing transformation terrestrial ecosystems through intensified exploitation management may put this buffering capacity at risk. Here, we summarize evidence that reductions in biodiversity destabilize functioning facing extremes. We then explore if impaired could, turn, exacerbate argue only a comprehensive approach, incorporating both ecological hydrometeorological perspectives, enables us to understand predict entire feedback system between altered This ambition, however, requires reformulation current research priorities emphasize bidirectional effects link ecology atmospheric processes.

Language: Английский

Citations

15
Artificial intelligence for climate prediction of extremes: State of the art, challenges, and future perspectives DOI Creative Commons
Stefano Materia,

Lluís Palma García,

Chiem van Straaten

et al.

Wiley Interdisciplinary Reviews Climate Change, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 3, 2024

Abstract Extreme events such as heat waves and cold spells, droughts, heavy rain, storms are particularly challenging to predict accurately due their rarity chaotic nature, because of model limitations. However, recent studies have shown that there might be systemic predictability is not being leveraged, whose exploitation could meet the need for reliable predictions aggregated extreme weather measures on timescales from weeks decades ahead. Recently, numerous been devoted use artificial intelligence (AI) study make climate predictions. AI techniques great potential improve prediction uncover links large‐scale local drivers. Machine deep learning explored enhance prediction, while causal discovery explainable tested our understanding processes underlying predictability. Hybrid combining AI, which can reveal unknown spatiotemporal connections data, with models provide theoretical foundation interpretability physical world, improving skills extremes climate‐relevant possible. challenges persist in various aspects, including data curation, uncertainty, generalizability, reproducibility methods, workflows. This review aims at overviewing achievements subseasonal decadal timescale. A few best practices identified increase trust these novel techniques, future perspectives envisaged further scientific development. article categorized under: Climate Models Modeling > Knowledge Generation The Social Status Change Science Decision Making

Language: Английский

Citations

15
Research progresses and prospects of multi-sphere compound extremes from the Earth System perspective DOI
Zengchao Hao, Yang Chen

Science China Earth Sciences, Journal Year: 2024, Volume and Issue: 67(2), P. 343 - 374

Published: Jan. 4, 2024

Language: Английский

Citations

14
Role of atmospheric resonance and land–atmosphere feedbacks as a precursor to the June 2021 Pacific Northwest Heat Dome event DOI Creative Commons
Xueke Li, Michael Mann, Michael Wehner

et al.

Proceedings of the National Academy of Sciences, Journal Year: 2024, Volume and Issue: 121(4)

Published: Jan. 16, 2024

We demonstrate an indirect, rather than direct, role of quasi-resonant amplification planetary waves in a summer weather extreme. find that there was interplay between persistent, amplified large-scale atmospheric circulation state and soil moisture feedbacks as precursor for the June 2021 Pacific Northwest “Heat Dome” event. An extended resonant wave configuration prior to event created antecedent deficit lower warming through strong nonlinear feedbacks, favoring this unprecedented heat

Language: Английский

Citations

13