Using rare event algorithms to understand the statistics and dynamics of extreme heatwave seasons in South Asia DOI Creative Commons
Clément Le Priol, Joy Merwin Monteiro, Freddy Bouchet

et al.

Environmental Research Climate, Journal Year: 2024, Volume and Issue: 3(4), P. 045016 - 045016

Published: Sept. 26, 2024

Abstract Computing the return times of extreme events and assessing impact climate change on such is fundamental to event attribution studies. However, rarity in observational record makes this task a challenging one, even more so for ‘record-shattering’ that have not been previously observed at all. While models could be used simulate extremely rare events, an approach entails huge computational cost: gathering robust statistics with time centuries would require few thousand years simulation. In study, we use innovative tool, algorithm, allows us sample numerous much lower cost than direct simulations. We employ algorithm heatwave seasons, corresponding large anomalies seasonal average temperature, hotspot South Asia using global model Plasim. show estimates levels greater precision traditional statistical fits. It also enables computation various composite statistics, whose accuracy demonstrated through comparison very long control run. particular, our results reveal seasons are associated anticyclonic anomaly embedded within large-scale hemispheric quasi-stationary wave-pattern. Additionally, accurately represents intensity-duration-frequency sub-seasonal heatwaves, offering insights into both aspects seasons. This studies better constrain changes event’s probability intensity warming, particularly spanning or millennia.

Language: Английский

Machine learning–based extreme event attribution DOI Creative Commons
Jared T. Trok, Elizabeth A. Barnes, Frances V. Davenport

et al.

Science Advances, Journal Year: 2024, Volume and Issue: 10(34)

Published: Aug. 21, 2024

The observed increase in extreme weather has prompted recent methodological advances event attribution. We propose a machine learning–based approach that uses convolutional neural networks to create dynamically consistent counterfactual versions of historical events under different levels global mean temperature (GMT). apply this technique one heat (southcentral North America 2023) and several have been previously analyzed using established attribution methods. estimate temperatures during the southcentral were 1.18° 1.42°C warmer because warming similar will occur 0.14 0.60 times per year at 2.0°C above preindustrial GMT. Additionally, we find learned relationships between daily GMT are influenced by seasonality forced response meteorological conditions. Our results broadly agree with other techniques, suggesting learning can be used perform rapid, low-cost events.

Language: Английский

Citations

6
Contrasting Drivers of Consecutive Pre‐Monsoon South Asian Heatwaves in 2022: Waveguide Interaction and Soil Moisture Depletion DOI
Roshan Jha, Volkmar Wirth, Christopher Polster

et al.

Journal of Geophysical Research Atmospheres, Journal Year: 2025, Volume and Issue: 130(7)

Published: April 8, 2025

Abstract South Asian countries including India, Pakistan, and Afghanistan experienced consecutive heatwave episodes in 2022, with the first episode March, followed by an equally intense event April of same year. Here, we use diagnostics local wave activity, waveguidability, soil moisture‐temperature coupling to gain insights into previously underexplored dynamic land drivers underlying these early pre‐monsoon episodes. Our findings reveal a sudden surge activity upper troposphere over region during heatwave. The intensified results from strong transient waves, due transfer energy extratropical subtropical waveguide, leading anticyclonic circulation. event, contrast episode, is found be result region. Further, low‐level winds revealed advection heat highly coupled regions (Pakistan Afghanistan) Indian landmass April. indicate that waveguide interaction together equatorward drives subsequently setting stage for further following weeks depleting moisture levels.

Language: Английский

Citations

0
Soil Moisture‐Temperature Coupling Increases Population Exposure to Future Heatwaves DOI Creative Commons
Jingwei Zhou, Adriaan J. Teuling, Sonia I. Seneviratne

et al.

Earth s Future, Journal Year: 2024, Volume and Issue: 12(7)

Published: July 1, 2024

Abstract Heatwaves have significant effects on ecosystems and human health. Human habitability is impacted severely as exposure to heatwaves projected increase, however, the contribution of soil moisture increased unknown. We use data from four climate models, in which two experiments are used isolate this way examine changes contributions increases heatwave events. Contributions future population also investigated. With combined with global warming, longest yearly found increase by up 20 days, intensify 2°C mean temperature, an increasing frequency 15% (the percentage relative total number days for a year) over most mid‐latitude land regions 2040–2070 under SSP585 high emissions scenario. Furthermore, role multiple characteristics regionally compared area contribute more exposed heatwaves.

Language: Английский

Citations

4
Friederike Otto: “The Paris Agreement Is a Human Rights Treaty” DOI Creative Commons

Karolin Stiller,

M. Schulz,

Ulrike Richter

et al.

SpringerBriefs in climate studies, Journal Year: 2025, Volume and Issue: unknown, P. 87 - 98

Published: Jan. 1, 2025

Language: Английский

Citations

0
Representing natural climate variability in an event attribution context: Indo-Pakistani heatwave of 2022 DOI Creative Commons
Shruti Nath, Mathias Hauser, Dominik L. Schumacher

et al.

Weather and Climate Extremes, Journal Year: 2024, Volume and Issue: 44, P. 100671 - 100671

Published: April 4, 2024

Attribution of extreme climate events to global change as a result anthropogenic greenhouse gas emissions has become increasingly important. Extreme arise at the intersection natural variability and forced response Earth system emissions, which may alter frequency severity such events. Accounting for effects both is thus central attribution. Here, we investigate reproducibility probabilistic event attribution results under more explicit representations variability. We employ well-established methodologies deployed in statistical System Model emulators represent informed from its spatio-temporal covariance structures. Two approaches towards representing are investigated: (1) where treated single component; (2) disentangled into annual seasonal components. showcase our by attributing 2022 Indo-Pakistani heatwave human-induced change. find that representation increases overall uncertainty considerably compared established World Weather Initiative. The increase likelihood an occurring warming differs slightly between approaches, mainly due different assessments pre-industrial return periods. Our approach explicitly resolves indicates median factor 41 (95% range: 6-603). robust signal increased intensification with increasing levels across all approaches. Compared present likelihood, 1.5 °C (2 °C) near-surface air temperature relative temperatures, would be 2.2 2.5 times (8 9 times) higher. note regardless variability, outcomes on conducted similar, minor differences ranges. Possible reasons evaluated, including limitations proposed this type application, well specific aspects it can provide complementary information

Language: Английский

Citations

2
Heat extremes linearly shift with global warming, with frequency doubling per decade since 1979 DOI Creative Commons
Robert Vautard, Clair Barnes, Sjoukje Philip

et al.

Environmental Research Letters, Journal Year: 2024, Volume and Issue: 19(9), P. 094033 - 094033

Published: Aug. 9, 2024

Abstract Heat extremes have been increasing both in frequency and intensity most land regions of the world, this increase has attributed to human activities. In last decade, many outstanding record shattering heat occurred worldwide, triggering fears a nonlinear behaviour or an ‘acceleration’ development conditions, considering warming level when event occurred. Here we show that evolution yearly temperature maxima, with return periods (RPs) above 10 years, consistently shifts global temperatures does not significantly depart from recent years decades considered globally at scale continents. This result is obtained by using classical statistical attribution technique, where assumption distribution block-maxima linearly tested across world regions. However, pace change large, probability exponentially rising nearly doubling every decade since 1979, particularly events RP about 10–50 2000. makes climate ago unrepresentative today’s climate. Our results overall mean do expect like undergo changes, despite fast changes. They also assumptions underlying techniques used studies are consistent trends.

Language: Английский

Citations

2
Climate Change and its Impacts across Pakistan DOI Creative Commons

Sardar Sarfaraz,

Nadeem Faisal

International Journal of Economic and Environmental Geology, Journal Year: 2024, Volume and Issue: 14(04), P. 28 - 39

Published: July 28, 2024

Climate change and variability is best manifested by persistent global temperature rise, changing precipitationpatterns, increasing frequency of extreme weather events, rapidly shrinking ice sheets & glacier melting sea-levelrise. This study analyzed the rainfall (for three major seasons; monsoon, winter spring), (in indices;annual mean, annual daytime nighttime temperatures) events recorded at 56 data sites acrossPakistan over 63-years period (1961-2023) to investigate climate diagnose trends. We did time-seriesanalysis assess applied Mann-Kendall statistical trend test determine trend’ssignificance. Results showed a significant rise in annual-average temperature, maximum as well annualminimum temperatures all Pakistan 27 stations individually, 28 25 across Pakistan. In rainfall, spring (AMJ) rains have shown rising trendthroughout Pakistan, while, summer monsoon (JAS) statistically increase 8 stationsin north with decrease 2 southwest, (DJFM) witnessed an 3 so was thespring 7 mostly south, while country (all changes being significantat 95- 99% CI). Extreme include high-temperature (Tmax > 35 °C), inannual cool nights (Tmin < 10 °C) wet days. The snowfall has decreased both amount ofsnow days KP, GB Punjab hilly station, Murree. There cyclone formation theArabian Sea, particularly intensity significant. Sea-level analysis depicted 2.02 mm/year sea-level atKarachi coast. Increased cyclones coupled potentially heightened storm surges mayprove fatal coastal areas

Language: Английский

Citations

1
English and Regional Media Coverage of the 2022 Heatwave in India DOI Creative Commons
Jagadish Thaker, James Painter,

Vinamrata Borwankar

et al.

Environmental Communication, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 17

Published: Oct. 27, 2024

The 2022 heatwave in India formed part of a pattern extreme weather events the country, which are becoming more intense, frequent, or prolonged. aim this study is to explore media coverage climate change and multilingual context such as India. Data analysis large diverse sample Indian (n = 309) suggests that only 1 every 7 news articles (14%) mentioned their English press, less than 10% Hindi, Telugu, Marathi language media. However, many English-language reported links between heatwave, although figure was much lower for other languages. Two Event Attribution studies analyzing were widely quoted, albeit with some inaccuracies. scientists most cited, whereas politicians NGOs largely absent, contrast previous research. Journalists regularly covered three aspects affect impact on ordinary people, namely emergency responses, disaster planning, vulnerabilities. This concludes by exploring theoretical practical recommendations heatwaves change.

Language: Английский

Citations

1
Northward shift of pre-monsoon winds exacerbating heatwaves over India DOI Creative Commons
Arpita Mondal, Roshan Kumar Jha, Subimal Ghosh

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: Jan. 9, 2024

Abstract India has observed increasingly persistent heat extremes in recent decades, that pose environmental, agricultural, and human health challenges. North-Central India, a highly populated region prone to heatwaves, experienced record maximum temperatures (>48°C) during the pre-monsoon season. While studies have shown positive trends heatwaves due rising air temperature season, we identify shift mean daily over resulting an increase seasonal by 0.7°C post-1998. The jump is associated with weakening of mid-tropospheric zonal winds as result northward migration subtropical jet since 1998. Further, comparing two regimes before after shift, find frequency duration accelerated latter regime. We also observe negative vorticity indicating increasing anticyclonic circulations India. These findings highlight exacerbation primarily driven atmospheric dynamical changes triggered regime further compounded global warming.

Language: Английский

Citations

0
Northward Shift of Pre‐Monsoon Zonal Winds Exacerbating Heatwaves Over India DOI Creative Commons
Roshan Jha, Arpita Mondal, Subimal Ghosh

et al.

Geophysical Research Letters, Journal Year: 2024, Volume and Issue: 51(19)

Published: Oct. 3, 2024

Abstract India has observed increasingly persistent heat extremes in recent decades. North‐Central India, a highly populated region prone to heatwaves, experienced record maximum temperatures (48°C) during the pre‐monsoon season. While studies have shown positive trends heatwaves due rising air temperature, we identify shift mean daily temperature over resulting an increase by 0.7°C post‐1998. The jump is associated with northward migration of subtropical westerly jet since 1998. We find that meridional explains more than 25% variability heatwave characteristics implying post‐1998 jet. These findings highlight exacerbation driven atmospheric dynamical changes triggered regime shift, further compounded global warming.

Language: Английский

Citations

0