1,721,085 research outputs found
Stratospheric winds trigger cold spells:Changes in Arctic sea ice and snow cover can alter wind patterns at high altitudes
No full textThe role of the Pacific Decadal Oscillation and ocean-atmosphere interactions in driving US temperature variability
No full textHeatwaves can have devastating impact on society and reliable early warnings at several weeks lead time are needed. Previous studies showed that north-Pacific sea surface temperatures (SST) can provide long-lead predictability for eastern US temperature, mediated by an atmospheric Rossby wave. The exact mechanisms, however, are not well understood. Here we analyze two different Rossby waves associated with temperature variability in western and eastern US, respectively. Causal discovery analyses reveal that both waves are characterized by positive ocean-atmosphere feedbacks at daily timescales. Only for the eastern US, a long-lead causal link from SSTs to the Rossby wave exists, which generates summer temperature predictability. We show that this SST forcing mechanism originates from the evolution of the winter-to-spring Pacific Decadal Oscillation (PDO). During pronounced winter-to-spring PDO phases (either positive or negative) eastern US summer temperature forecast skill more than doubles, providing a temporary window of enhanced long-lead predictability.</p
Hidden amongst Chaos: Dynamics and predictability of weather on subseasonal-to-seasonal timescales
Full text linkWeather shapes societies in various ways, from daily routines to infrastructure, but the rapid climate change caused by human activities is exposing vulnerabilities to extreme weather events. While medium-range weather forecasting has improved, long-term forecasts spanning weeks to months, known as subseasonal-to-seasonal (S2S) timescales, remain challenging. The thesis focuses on using data-driven methods to improve the skill and understanding of subseasonal to seasonal (S2S) weather forecasts, with a particular emphasis on North America. The author explores four main areas: (1) predicting temperature extremes in the eastern United States (US), (2) studying the ocean-atmosphere interaction driving predictability in the eastern US, (3) predicting harvest failure in the eastern US, and (4) identifying challenges, opportunities, and a vision for exploring S2S dynamics and predictability using data-driven methods. (1) For temperature extremes, an algorithm is developed to extract a reliable preceding sea surface temperature (SST) pattern from the North Pacific, improving forecast skill for heatwave events. The trade-off between extremity and spatial aggregation is explored, indicating compromises needed for reliable forecasts at longer lead-times. Predicting event probabilities within wider time windows enhances forecast skill for moderate hot events up to 60 days ahead. (2) To address the issue of trustworthiness in purely statistical machine learning models, the author emphasizes the importance of incorporating physical understanding into forecast models. They employ causal discovery methods to learn physical relationships from data. By applying a causal discovery algorithm, they study the interaction between the atmospheric Rossby wave and the underlying ocean, revealing that summer temperature predictability in the eastern US originates from low-frequency variability in the north Pacific. The study demonstrates that the low-frequency Pacific variability, driven by atmosphere-to-ocean forcing and two-way feedbacks in winter and spring, leads to an upward forcing from the ocean to the atmosphere in summer. The presence of a strong horseshoe-shaped SST pattern in spring enhances predictability by causing more frequent and persistent atmospheric waves, which result in a high-pressure system, higher temperatures, and reduced rainfall in the eastern US. (3) The winter-to-spring horseshoe sea surface temperature (SST) pattern holds significant importance as it suggests the potential predictability of hot and dry weather in the mid-to-eastern United States (US) at long lead-times. This predictability opens up opportunities for the agricultural sector, enabling informed decisions to be made prior to the planting season. The author employs a response-guided dimensionality reduction method and a causal inference-based selection step to extract reliable input features from observational SST and soil moisture datasets. Using this approach, the forecast model successfully predicts poor soybean harvest years as early as February 1st, several months before sowing. This provides farmers with valuable information for decision-making, such as adjusting sowing density, avoiding drought-prone areas, or selecting drought-resistant seeds. (4) The thesis suggests that S2S forecasting potential and value may have been underestimated. However, challenges remain, such as establishing best practices for data-driven forecasting. The author advocates for dedicated open-source software and a collaborative community. Furthermore, operationalizing forecasts and supporting the required infrastructure are essential for societal benefits
Three arguments for increasing weather persistence in boreal summer –and why we should care
No full textClimate Coffee organised by ECRA and Blue-Action on 10 February 2022
Dim Coumou, Vrije Universiteit Amsterdam, Institute for Environmental Studies (homepage)
Is global warming making summer circulation more persistent
Erratum to: increased record-breaking precipitation events under global warming (Climatic Change, (2015), 10.1007/s10584-015-1434-y)
No full textThe weakening summer circulation in the Northern Hemisphere mid-latitudes
No full textRapid warming in the Arctic could influence mid-latitude circulation by reducing the poleward temperature gradient. The largest changes are generally expected in autumn or winter, but whether significant changes have occurred is debated. Here we report significant weakening of summer circulation detected in three key dynamical quantities: (i) the zonal-mean zonal wind, (ii) the eddy kinetic energy (EKE), and (iii) the amplitude of fast-moving Rossby waves. Weakening of the zonal wind is explained by a reduction in the poleward temperature gradient. Changes in Rossby waves and EKE are consistent with regression analyses of climate model projections and changes over the seasonal cycle. Monthly heat extremes are associated with low EKE, and thus the observed weakening might have contributed to more persistent heat waves in recent summers
Increased record-breaking precipitation events under global warming
No full textIn the last decade record-breaking rainfall events have occurred in many places around the world causing severe impacts to human society and the environment including agricultural losses and floodings. There is now medium confidence that human-induced greenhouse gases have contributed to changes in heavy precipitation events at the global scale. Here, we present the first analysis of record-breaking daily rainfall events using observational data. We show that over the last three decades the number of record-breaking events has significantly increased in the global mean. Globally, this increase has led to 12 % more record-breaking rainfall events over 1981–2010 compared to those expected in stationary time series. The number of record-breaking rainfall events peaked in 2010 with an estimated 26 % chance that a new rainfall record is due to long-term climate change. This increase in record-breaking rainfall is explained by a statistical model which accounts for the warming of air and associated increasing water holding capacity only. Our results suggest that whilst the number of rainfall record-breaking events can be related to natural multi-decadal variability over the period from 1901 to 1980, observed record-breaking rainfall events significantly increased afterwards consistent with rising temperatures
Record Balkan floods of 2014 linked to planetary wave resonance
Full text linkIn May 2014, the Balkans were hit by a Vb-type cyclone that brought disastrous flooding and severe damage to Bosnia and Herzegovina, Serbia, and Croatia. Vb cyclones migrate from the Mediterranean, where they absorb warm and moist air, to the north, often causing flooding in central/eastern Europe. Extreme rainfall events are increasing on a global scale, and both thermodynamic and dynamical mechanisms play a role. Where thermodynamic aspects are generally well understood, there is large uncertainty associated with current and future changes in dynamics. We study the climatic and meteorological factors that influenced the catastrophic flooding in the Balkans, where we focus on large-scale circulation. We show that the Vb cyclone was unusually stationary, bringing extreme rainfall for several consecutive days, and that this situation was likely linked to a quasi-stationary circumglobal Rossby wave train. We provide evidence that this quasi-stationary wave was amplified by wave resonance. Statistical analysis of daily spring rainfall over the Balkan region reveals significant upward trends over 1950-2014, especially in the high quantiles relevant for flooding events. These changes cannot be explained by simple thermodynamic arguments, and we thus argue that dynamical processes likely played a role in increasing flood risks over the Balkans
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