Large‐Scale Drivers of Persistent Extreme Weather During Early Summer 2021 in Europe

Tuel, Alexandre; Steinfeld, Daniel; Ali, S. Mubashshir; Sprenger, Michael; Martius, Olivia

doi:10.1029/2022gl099624

Cited by 9 publications

(5 citation statements)

References 66 publications

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“…Extreme weather could also be a contributing factor. As plants grow to match the current water supply within the soil, if they are suddenly hit by an extreme drought, this causes them to gradually die since they cannot adjust their water conservation mechanisms [69][70][71][72].…”

Section: Discussionmentioning

confidence: 99%

A Comparison of Water Uptake by Transpiration from Different Soil Depths among Three Land Cover Types in the Arid Northwest of China

Qin,

Zhang,

Zhang

et al. 2023

Forests

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In recent decades, the frequency, intensity, and extent of extreme drought events have posed serious threats to ecosystems in vulnerable regions. With low annual precipitation, the arid area in northwest China is a typical ecologically fragile area, and extreme drought events will aggravate desertification in this area. In order to control desertification, various experimental plantations have been established in Northwest China. However, there is no consensus on which plantations are more suitable to become widespread. To explore this, we conducted a comparative study on different plantations from the perspective of long-term deep (100 cm depth) soil moisture balance. In our study, six typical ecosystems were selected for comparison of the variation of soil moisture and control factors. The results showed three main findings. First, the soil moisture of all six ecosystems showed a similar hierarchy of increasing moisture with the increasing depth of the soil layer. However, the deep layer soil moisture (mean = 0.33 ± 0.22 cm3·cm−3) of the artificial poplar (Populus alba) forest exhibited a downward trend over time after the fifth year, but did not at the shallow layer for this ecosystem. Second, the trends of the maximum canopy coverage between the different ecosystems from 2010 to 2019 showed significant differences from one another, with the maximum value of the leaf area index for the poplar forest being the highest (Maximum = 7.13). Third, a negative correlation (R2 = 0.52) was found between deep soil moisture and transpiration for the poplar forest, and a positive correlation (R2 ≥ 0.23) between these two metrics was found for the other five ecosystems. The results revealed that transpiration processes had a different consumption of deep soil moisture due to the differences in the root and canopy density of several plantations. Among these ecosystems, the transpiration of the artificial poplar forest is noticeably large, resulting in a unilateral decline in soil moisture.

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Section: Discussionmentioning

confidence: 99%

A Comparison of Water Uptake by Transpiration from Different Soil Depths among Three Land Cover Types in the Arid Northwest of China

Qin,

Zhang,

Zhang

et al. 2023

Forests

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“…Blocks are defined as regions with persistent negative anomalies of 500-150 hPa vertically averaged potential vorticity (PV) exceeding −1.3 PVU (1 PVU = 10 −6 Km 2 s −1 kg −1 ) and a spatial overlap of at least 70% between successive 6 hourly time steps for at least 5 days [10,11]. Recurrent Rossby wave packets can repeatedly pass and amplify at the same longitude in the same phase, resulting in recurring ridging or troughing patterns and persistent cold or hot extremes [12,13]. The strength of the transient Rossby wave packets is described by a 'R' metric, which is a timeand wavenumber-filtered signal derived from the Hovmöller diagram of 250 hPa meridional winds averaged over 35 • N-65 • N [14].…”

Section: Methodsmentioning

confidence: 99%

What caused the unseasonal extreme dust storm in Uzbekistan during November 2021?

Xi,

Steinfeld,

Cavallo

et al. 2023

Environ. Res. Lett.

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An unseasonal dust storm hit large parts of Central Asia on 4-5 November 2021, setting records for the column aerosol burden and fine particulate concentration in Tashkent, Uzbekistan. This dust storm originated from an agropastoral region in southern Kazakhstan, where the soil erodibility was enhanced by a prolonged agricultural drought resulting from La Niña-related precipitation deficit and persistent high atmospheric evaporative demand. The dust outbreak was triggered by sustained postfrontal northerly winds during an extreme cold air outbreak. The cold air and dust outbreaks were preceded by a chain of processes consisting of recurrent synoptic-scale transient Rossby wave packets over the North Pacific and North Atlantic, upper-level wave breaking and blocking over Greenland, followed by high-latitude blocking over Northern Europe and West Siberia, and the equatorward shift of a tropopause polar vortex and cold pool into southern Kazakhstan. Our analysis suggests that the historic dust storm in Uzbekistan was a compound weather event driven by cold extreme, high winds, and drought preconditions.

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“…We first evaluate whether MPI‐GE CMIP6 is capable of simulating heat and precipitation extremes that were recently observed (Figure 2). We focus on the Siberian heatwave in spring 2020 (Ciavarella et al., 2021), the Pacific North American heatwave in summer 2021 (Philip et al., 2022), the extreme precipitation event in western Europe in summer 2021 (Ibebuchi, 2022; Tuel et al., 2022), and the extreme precipitation event in northern Italy in autumn 2020 (Davolio et al., 2023). To do so, we use daily surface maximum temperature and daily precipitation from MPI‐GE CMIP6, and use ERA5 (Hersbach et al., 2020) and E‐OBS (Klein Tank et al., 2002) as observational reference.…”

Section: Power Of Mpi‐ge Cmip6 Beyond Mpi‐ge Cmip5mentioning

confidence: 99%

The New Max Planck Institute Grand Ensemble With CMIP6 Forcing and High‐Frequency Model Output

Olonscheck,

Suarez‐Gutierrez,

Milinski

et al. 2023

J Adv Model Earth Syst

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Single‐model initial‐condition large ensembles are powerful tools to quantify the forced response, internal climate variability, and their evolution under global warming. Here, we present the CMIP6 version of the Max Planck Institute Grand Ensemble (MPI‐GE CMIP6) with currently 30 realizations for the historical period and five emission scenarios. The power of MPI‐GE CMIP6 goes beyond its predecessor ensemble MPI‐GE by providing high‐frequency output, the full range of emission scenarios including the highly policy‐relevant low emission scenarios SSP1‐1.9 and SSP1‐2.6, and the opportunity to compare the ensemble to complementary high‐resolution simulations. First, we describe MPI‐GE CMIP6, evaluate it with observations and reanalyzes and compare it to MPI‐GE. Then, we demonstrate with six application examples how to use the power of the ensemble to better quantify and understand present and future climate extremes, to inform about uncertainty in approaching Paris Agreement global warming limits, and to combine large ensembles and artificial intelligence. For instance, MPI‐GE CMIP6 allows us to show that the recently observed Siberian and Pacific North American heatwaves would only avoid reaching 1–2 years return periods in 2071–2100 with low emission scenarios, that recently observed European precipitation extremes are captured only by complementary high‐resolution simulations, and that 3‐hourly output projects a decreasing activity of storms in mid‐latitude oceans. Further, the ensemble is ideal for estimates of probabilities of crossing global warming limits and the irreducible uncertainty introduced by internal variability, and is sufficiently large to be used for infilling surface temperature observations with artificial intelligence.

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Large‐Scale Drivers of Persistent Extreme Weather During Early Summer 2021 in Europe

Cited by 9 publications

References 66 publications

A Comparison of Water Uptake by Transpiration from Different Soil Depths among Three Land Cover Types in the Arid Northwest of China

A Comparison of Water Uptake by Transpiration from Different Soil Depths among Three Land Cover Types in the Arid Northwest of China

What caused the unseasonal extreme dust storm in Uzbekistan during November 2021?

The New Max Planck Institute Grand Ensemble With CMIP6 Forcing and High‐Frequency Model Output

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