Evidence map›Paper›PMID 37872248›Full record

ArticleScientific reports2023

Hotspot movement of compound events on the Europe continent.

Smit Chetan Doshi, Gerrit Lohmann, Monica Ionita

Abstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Smit Chetan DoshiAlfred Wegener Institute Helmholtz Center for Polar and Marine Research, Bremerhaven, Germany. smitdoshi5@gmail.com.
Gerrit LohmannAlfred Wegener Institute Helmholtz Center for Polar and Marine Research, Bremerhaven, Germany.
Monica IonitaAlfred Wegener Institute Helmholtz Center for Polar and Marine Research, Bremerhaven, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Climate indices are often used as a climate monitoring tool, allowing us to understand how the frequency, intensity, and duration of extreme weather events are changing over time. Here, based on complex statistical analysis we identify highly correlated significant pairs of compound events at the highest spatial resolution, on a monthly temporal scale across Europe. Continental-scale monthly analysis unleashes information on compound events such as high-risk zones, hotspots, monthly shifts of hotspots and trends, risk exposure to land cover and population, and identification of maximum increasing trends. While there are many studies on single or compound climate extremes there are only a few studies that addresses the relationship between pairs of hazards, the incorporation of bioclimatic indices, the determination of a grid best-fit copula approach, and the outlining relevance of this work of compound event risks with exposures. In this respect, here, using 27-bivariate and 10-trivariate copula models, we show that the different hazard pairs have high combined risks of indices related to radiation, temperature, evapotranspiration, bioclimatic-based indices, such as the universal thermal climate index, wind chill index, and heat index, mainly over the northern and eastern European countries. Furthermore, we show that over the last 7 decades, agricultural and coastal areas are highly exposed to the risks of defined hotspots of compound events. In some of the hotspots of compound events-identified by clusters, there is no monthly shifts of hotspots, leading to higher impacts when compounded. Future work needs to integrate the framework and process to identify other compound pairs.

Identifiers

PMID37872248
PMCPMC10593787

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.