Summer temperature extremes in Europe: how does the definition affect the results?

Sulikowska, Agnieszka; Wypych, Agnieszka

doi:10.1007/s00704-020-03166-8

Cited by 32 publications

(31 citation statements)

References 37 publications

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“…A hot day (HD) occurs when the daily TX exceeds the local daily 95th percentile of the 1981-2010 period (TX95p), computed using a 15-day-centered window [15,32]. Since seasonal variability of air temperature is taken into account in this method, a percentile-based threshold for detecting extremes is relevant for a given part of the year.…”

Section: Methodsmentioning

confidence: 99%

“…Since seasonal variability of air temperature is taken into account in this method, a percentile-based threshold for detecting extremes is relevant for a given part of the year. As shown by Sulikowska and Wypych [32], the choice of the period within a year that the percentile is calculated is meaningful, especially when one is interested in a detailed view of some event, i.e., a case study. The normal period of 1981-2010 is used, as the World Meteorological Organization recommends using the most recent normal period in order to describe events that occurred in the recent past [33].…”

Section: Methodsmentioning

confidence: 99%

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How Unusual Were June 2019 Temperatures in the Context of European Climatology?

Sulikowska

Wypych

2020

Atmosphere

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The aims of the study were to assess the severity of temperature conditions in Europe, in June 2019, using a newly developed extremes index, as well as to evaluate circulation conditions that favored the occurrence of extremely hot days in June 2019, as seen over the long term. The main focus of this work was on two European regions particularly affected by high temperatures in June 2019, namely Central Europe and Iberia. To comprehensively characterize heat events in terms of their spatial extent and intensity, we proposed the extremity index (EI) and used it to compare hot days occurring in areas of different sizes and with different climatic conditions. The role of atmospheric circulation in the occurrence of hot days was evaluated using the Grosswetterlagen (GWL) circulation types catalog, as well as composite maps created with the bootstrap resampling technique. Our results reveal that June 2019 was unusually hot, and in terms of the magnitude of the anomaly, it has no analogue in the 70-year-long temperature record for Europe. However, the properties of heat events in the two considered regions were substantially different. The occurrence of hot days in June 2019, in Europe, was mainly associated with the GWL types forcing advection from the southern sector and co-occurrence of high-pressure systems which was significantly proven by the results of bootstrap resampling. In terms of the applicability of the new approach, the EI proved to be a useful tool for the analysis and evaluation of the severity of hot days based on their intensity and spatial range.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

How Unusual Were June 2019 Temperatures in the Context of European Climatology?

Sulikowska

Wypych

2020

Atmosphere

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“…Several factors complicate interpretation of existing results and understanding of future changes in the temperature distribution shape. First, the temperature distribution varies across different time scales and temperature metrics (e.g., Sulikowska & Wypych, 2020). It is difficult to reconcile results based on annual means (e.g., Diffenbaugh & Charland, 2016; Diffenbaugh & Scherer, 2011) with those based on seasonal means (e.g., Wang et al., 2015), or annual‐maximum daily means or maxima (e.g., Diffenbaugh & Charland, 2016; Donat et al., 2017).…”

Section: Introductionmentioning

confidence: 99%

Three Regimes of Temperature Distribution Change Over Dry Land, Moist Land, and Oceanic Surfaces

Duan

Findell

Wright

2020

Geophysical Research Letters

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Climate model simulations project different regimes of summertime temperature distribution changes under a quadrupling of CO2 for dry land, moist land, and oceanic surfaces. The entire temperature distribution shifts over dry land surfaces, while moist land surfaces feature an elongated upper tail of the distribution, with extremes increasing more than the corresponding means by ∼20% of the global mean warming. Oceanic surfaces show weaker warming relative to land surfaces, with no significant elongation of the upper tail. Dry land surfaces show little change in turbulent sensible (SH) or latent (LH) fluxes, with new balance reached with compensating adjustments among downwelling and upwelling radiative fluxes. By contrast, moist land surfaces show enhanced partitioning of turbulent flux toward SH, while oceanic surfaces show enhanced partitioning toward LH. Amplified warming of extreme temperatures over moist land surfaces is attributed to suppressed evapotranspiration and larger Bowen ratios.

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“…The strong and very strong heat stress in the future will mainly cover central areas of these cities. Figure 9 presents the projection of UTCI under the extreme climate scenario which was defined with the use of the 90th percentile of maximum temperature of all climate change scenarios (Luo and Lau 2018;Wang et al, 2019;Sulikowska and Wypych, 2020). The result stated that Medan will experience the highest average increase of UTCI (+5.9°C), followed by Denpasar (+5.6°C) and Surabaya (+4.8°C).…”

Section: Future Projection Of Utci With CC Scenariomentioning

confidence: 99%

Accelerating Urban Heating Under Land-Cover and Climate Change Scenarios in Indonesia: Application of the Universal Thermal Climate Index

Setiawati

Jarzebski

Gomez-Garcia

et al. 2021

Front. Built Environ.

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Climate change causing an increase of frequency and magnitude of heat waves has a huge impact on the urban population worldwide. In Indonesia, the Southeast Asian country in the tropical climate zone, the increasing heat wave duration due to climate change will be also magnified by projected rapid urbanization. Therefore, not only climate change mitigation measures but also adaptation solutions to more frequent extreme weather events are necessary. Adaptation is essential at local levels. The projected increase of the heat wave duration will trigger greater health-related risks. It will also drive higher energy demands, particularly in urban areas, for cooling. New smart solutions for growing urbanization for reducing urban heat island phenomenon are critical, but in order to identify them, analyzing the changing magnitude and spatial distribution of urban heat is essential. We projected the current and future spatial variability of heat stress index in three cities in Indonesia, namely, Medan, Surabaya, and Denpasar, under climate change and land-cover change scenarios, and quantified it with the Universal Thermal Climate Index (UTCI) for two periods, baseline (1981–2005) and future (2018–2042). Our results demonstrated that currently the higher level of the UTCI was identified in the urban centers of all three cities, indicating the contribution of urban heat island phenomenon to the higher UTCI. Under climate change scenarios, all three cities will experience increase of the heat, whereas applying the land-cover scenario demonstrated that in only Medan and Denpasar, the UTCI is likely to experience a higher increase by 3.1°C; however, in Surabaya, the UTCI will experience 0.84°C decrease in the period 2018–2042 due to urban greening. This study advanced the UTCI methodology by demonstrating its applicability for urban heat warning systems and for monitoring of the urban green cooling effect, as well as it provides a base for adaptation measures’ planning.

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Summer temperature extremes in Europe: how does the definition affect the results?

Cited by 32 publications

References 37 publications

How Unusual Were June 2019 Temperatures in the Context of European Climatology?

How Unusual Were June 2019 Temperatures in the Context of European Climatology?

Three Regimes of Temperature Distribution Change Over Dry Land, Moist Land, and Oceanic Surfaces

Accelerating Urban Heating Under Land-Cover and Climate Change Scenarios in Indonesia: Application of the Universal Thermal Climate Index

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