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The Exceptional 2018 European Water Seesaw Calls for Action on Adaptation


Abstract and Figures

Temperature and precipitation are the most important factors responsible for agricultural productivity variations. In 2018 spring/summer growing season, Europe experienced concurrent anomalies of both. Drought conditions in central and northern Europe caused yield reductions up to 50% for the main crops, yet wet conditions in southern Europe saw yield gains up to 34%, both with respect to the previous 5‐years' mean. Based on the analysis of documentary and natural proxy based seasonal paleoclimate reconstructions for the past half millennium, we show that the 2018 combination of climatic anomalies in Europe was unique. The water seesaw, a marked dipole of negative water anomalies in central Europe and positive ones in southern Europe, distinguished 2018 from the five previous similar droughts since 1976. Model simulations reproduce the 2018 European water seesaw in only four years out of 875 years in historical runs and projections. Future projections under the RCP8.5 scenario show that 2018‐like temperature and rainfall conditions, favourable to crop growth, will occur less frequent in southern Europe. In contrast, in central Europe high‐end emission scenario climate projections show that droughts as intense as 2018 could become a common occurrence as early as 2043. Whilst integrated European and global agricultural markets limited agro‐economic shocks caused by 2018's extremes, there is an urgent need for adaptation strategies for European agriculture to consider futures without the benefits of any water seesaw.
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The Exceptional 2018 European Water Seesaw Calls for
Action on Adaptation
Andrea Toreti1, Alan Belward1, Ignacio Perez-Dominguez2, Gustavo Naumann1,
Jürg Luterbacher3, Ottmar Cronie4, Lorenzo Seguini1, Giacinto Manfron1,
Raul Lopez-Lozano1, Bettina Baruth1, Maurits van den Berg1, Frank Dentener1,
Andrej Ceglar1, Thomas Chatzopoulos2, and Matteo Zampieri1
1European Commission, Joint Research Centre (JRC), Ispra, Italy, 2European Commission, Joint Research Centre
(JRC), Seville, Spain, 3Department of Geography, Climatology, Climate Dynamics and Climate Change, Centre for
International Development and Environmental Research, Justus-Liebig University of Giessen, Giessen, Germany,
4Department of Mathematics and Mathematical Statistics, Umeå University, Umeå, Sweden
Abstract Temperature and precipitation are the most important factors responsible for agricultural
productivity variations. In 2018 spring/summer growing season, Europe experienced concurrent anomalies
of both. Drought conditions in central and northern Europe caused yield reductions up to 50% for the main
crops, yet wet conditions in southern Europe saw yield gains up to 34%, both with respect to the previous
5-year mean. Based on the analysis of documentary and natural proxy-based seasonal paleoclimate
reconstructions for the past half millennium, we show that the 2018 combination of climatic anomalies in
Europe was unique. The water seesaw, a marked dipole of negative water anomalies in central Europe and
positive ones in southern Europe, distinguished 2018 from the five previous similar droughts since 1976.
Model simulations reproduce the 2018 European water seesaw in only 4 years out of 875 years in historical
runs and projections. Future projections under the RCP8.5 scenario show that 2018-like temperature and
rainfall conditions, favorable to crop growth, will occur less frequent in southern Europe. In contrast, in
central Europe high-end emission scenario climate projections show that droughts as intense as 2018 could
become a common occurrence as early as 2043. While integrated European and global agricultural markets
limited agro-economic shocks caused by 2018's extremes, there is an urgent need for adaptation strategies
for European agriculture to consider futures without the benefits of any water seesaw.
1. Introduction
Climate change poses particular challenges for agricultural production systems as plant growth is affected
by climate conditions (e.g., Gray & Brady, 2016; Lobell & Gourdji, 2012; Porter & Semenov, 2005). Rising
temperatures, changes in precipitation regimes, and increasing frequency, duration, and intensity of extreme
events negatively affect crop yields and fodder production (e.g., Asseng et al., 2014; Toreti, Bassu, et al., 2019;
Webber et al., 2018; Zhao et al., 2017). The adverse impacts of climate extremes on the main crops in the
last decades have been addressed in numerous studies (e.g., Deryng et al., 2014; Fontana et al., 2015; Lesk
et al., 2016; Rezaei, Siebert, Manderscheid, et al., 2018; Zampieri et al., 2017). Besides heat stress, drought
and water excess have been shown to trigger losses when occurring in critical phenological phases. Thus,
to reduce the impacts associated with these extreme events at the local scale, agricultural management and
planning need to consider them in the development and implementation of risk reduction strategies.
At the regional scale, the push/pull of droughts in one region and the absence of water stress elsewhere
(i.e., the water seesaw) can translate into crop yield differentials. Thus, it is key to estimate how often water
seesaw conditions have occurred and will occur and to understand if climate change adaptation strategies for
agriculture can count on recurrent water seesaws. The extreme climate conditions experienced by Europe
in 2018 have triggered all these questions.
2. Data and Methods
Starting from the 2018 event as a reference, we investigate past, current, and future water seesaw events.
The following data sets are used to perform such analysis: daily climate observations from ground weather
Key Points:
• Unique concurrent spring and
summer climatic anomalies affected
Europe in 2018
• 2018-like droughts could become a
common occurrence as early as 2043
• Climate change adaptation strategies
for agriculture in Europe cannot
count on recurrent water seesaws
Supporting Information:
• Supporting Information S1
Correspondence to:
A. Toreti,
Toreti, A., Belward, A.,
Perez-Dominguez, I., Naumann, G.,
Luterbacher, J., Cronie, O., et al.
(2019). The exceptional 2018
European water seesaw calls for action
on adaptation. Earth's Future,7,
Received 29 JAN 2019
Accepted 7 MAY 2019
Accepted article online 15 MAY 2019
Published online 19 JUN 2019
©2019. The Authors.
This is an open access article under the
terms of the Creative Commons
License, which permits use and
distribution in any medium, provided
the original work is properly cited, the
use is non-commercial and no
modifications or adaptations are made.
Earth’s Future 10.1029/2019EF001170
stations covering the last decades from 1976, remote sensing data, atmospheric reanalysis, paleoclimate
reconstructions covering the last 500 years, and climate projections till 2100. The observational climate
gridded data set (MarsMet) used is maintained by the Joint Research Centre of the European Commission
(Toreti, Maiorano, et al., 2019). This data set covers the European Union and its neighboring countries at a
spatial resolution of 25 km.
The remote sensing analysis of vegetation status is based on the fraction of absorbed photosynthetically
active radiation data (fAPAR; an indicator related to biomass; Verger et al., 2014) obtained from the
Copernicus Global Land Service, more specifically, the fAPAR version 2 at 1 km (Verger et al., 2014).
The large-scale atmospheric circulation during the spring-to-summer period is analyzed by using geopoten-
tial height values at 500 hPa from the ERA-Interim reanalysis (Dee et al., 2011).
Gridded multiproxy, documentary and natural proxy-based paleoclimate reconstructions of seasonal tem-
perature (Luterbacher et al., 2004) and precipitation (Pauling et al., 2006) covering the period back to
1500 CE are also used. The climate model projections under the high-end emission scenario RCP8.5 come
from the FP7-project HELIX (High-End cLimate Impacts and eXtremes; They have
been obtained with the atmospheric model EC-EARTH3-HR v3.1 (Hazeleger et al., 2012) at 0.35(with an
improved dynamics and parameterization) having prescribed Sea Surface Temperature and Sea Ice concen-
tration originating from seven independent CMIP5 GCMs (see Table S1 in the supporting information and
Naumann et al., 2018). The higher spatial resolution, compared to CMIP5 model runs, can positively affect
the representation of the hydrological cycle and the atmospheric blocking condition (Berckmans et al., 2013;
Dawson & Palmer, 2015; Wyser et al., 2017).
The 2018 drought affected central and northern Europe; however, in this study we focus only on central
Europe being the geographic core of the event and to facilitate the spatial analysis and comparison with the
other observed, reconstructed, and projected drought events. Central Europe is here defined as the region
spanning the following latitude/longitude limits: 3–20E, 46–56N. While southern Europe is defined by
10W–30E, 36.5–45.5N.
The water seesaw is characterized by using the Standardized Precipitation Evapotranspiration Index
(SPEI; Vicente-Serrano et al., 2010) computed by using precipitation data and the FAO-recommended
Penmann-Monteith evapotranspiration function (Allen et al., 1998). Furthermore, these anomalous cli-
mate conditions are also characterized and analyzed by studying concurrent seasonal (spring and summer)
temperature and precipitation extremes.
The spatial distributions of the temperature and precipitation quantiles, as well as of the SPEI values, are
compared with the ones in 2018 by using the Kullback-Leibler (KL) divergence. Given distributions Pand
Qto be compared, which have probability densities pand q, respectively, the KL divergence is defined as
D(P||Q)=p(x)log p(x)
Here Qis for instance the spatial distribution of the 2018 SPEI values in central Europe, while Pis the spatial
distribution of the SPEI values of any other year to be compared with 2018. Given observations x1,,xn,
we here estimate the KL divergence by means of (Perez-Cruz, 2008):
log ΔPc(xi)
where ΔPc(xi)=Pc(xi)−Pc(xi𝜖)for any 𝜖<mini{xixi1}and Pcis the continuous piecewise extension
of the stepwise empirical cumulative distribution function.
The spatiotemporal intensity functions of the drought events and the anomalous wet conditions are esti-
mated with a resample-smoothed Voronoi estimator (Moradi et al., 2019). Let Y={x1,,xN}[0,T]be
the collection of random time points associated to the events occurring in the time interval [0,T], and denot-
ing the associated spatial extents with ssī
s,i=1,,N, we obtain the spatiotemporal point process
X= {(x1,s1),,(xN,sN)} [0,T]×[s,̄
s]. Let further X1,p,,Xm,pbe m1independent p-thinnings
of X,0p1; we obtain each collection Xi,pby running through the points of Xand independently
Earth’s Future 10.1029/2019EF001170
throwing out each of its points with probability 1p. Then, the resample-smoothed Voronoi estimator
(Moradi et al., 2019) is given by
̂𝜌p,m(t,v)= 1
where for any (x,s)∈Xi,p,|(x,s)(Xi,p)|is the size of
s]∶||u−(x,s)|| ||u−(x,s)|| for any (x,s)∈Xi,p{(x,s)}},(4)
which is the Voronoi cell consisting of all points u∈[0,T]×[s,̄
s]closer to (x,s)than any (x,s)∈Xi,p{(x,s)}
in terms of the Euclidean distance. It has been suggested (Moradi et al., 2019) to choose pand msuch that
0<p0.2and m400. The interval [0,T]is here chosen empirically by letting 0 represent the first
observed event time minus half its distance to the second smallest observed event time. Tis chosen similarly
but considering the largest observed event, and this allows to correct for the edge effects/bias (Moradi et al.,
2019). The same procedure is applied to the spatial extension.
To identify when the 2018-like drought events will become a common occurrence in the climate projections,
we use the intensity function thresholded at 0.5; that is, we identify the year when the estimated intensity
function exceeds and remains above 0.5. This implies that in a given year it is more likely to observe an
extreme drought event, such as the one in 2018, than not.
3. Results
3.1. The 2018 Climate Extreme
In 2018 drought affected central and northern Europe, with an exceptionally negative spring/summer water
balance. At its geographic core, this deficit also affected the first months of the year (Figure S1). According
to the SPEI, the 2018 drought event can be classified as severe to extreme both at 3-month (June to August)
and 6-month (March to August) time scales (Figure 1). In central Europe over 34%of the landmass is used
for agriculture, and 52%of the entire region suffered severe-to-extreme drought (SPEI-6 less than 1.5;
Figure 1), while 20%was affected by extreme drought (SPEI-6 less than 2; Figure 1). Meanwhile, southern
Europe experienced wetter than usual spring (March to May) conditions, and to a certain extent also summer
(June to August), with large areas characterized by SPEI-6 higher than 1.5 and 2 (Figure 1). The exceptional
wet conditions in March 2018 over the Iberian Peninsula brought to an end the 2016–2017 drought and
were induced by an exceptional planetary wave activity, followed by a sudden stratospheric warming and a
subsequent persistent negative North Atlantic Oscillation anomaly (Ayarzagüena et al., 2018).
The 2018 drought was characterized by (i) a relatively dry spring (March, April, and May) with 3-month
total precipitation being in the lower percentiles of the 1976–2005 distribution (with the median of central
Europe equal to the 40th percentile; Figure S2). (ii) Exceptionally high mean spring temperatures were also
recorded, all in the highest percentiles of the 1976–2005 distribution (spatial median greater than the 99th
percentile; Figure S2). Finally, (iii) a dry summer (June, July, and August) with total precipitation in the low-
est percentiles (i.e., median equal to the 17th percentile) associated with (iv) very warm mean temperatures
in the highest percentiles of the 1976–2005 distribution (spatial median equal to the 97th percentile; Figure
S2) were observed. This comparison in terms of percentiles based on the 1976–2005 distribution helps to
understand and quantify how anomalous the 2018 conditions were in a climatological perspective.
The large-scale atmospheric circulation was characterized by pronounced positive geopotential height
anomalies in April (Figure 2), covering a large area centered over eastern Europe and extending to the
Mediterranean in the South and to central Europe in the West. These atmospheric conditions persisted in
subsequent months and moved northward bridging toward the North Atlantic. In May, the geopotential
height anomalies were covering a large area stretching from the Scandinavian Peninsula to the Atlantic. In
August, this anomaly moved South and elongated from the North Atlantic to western Russia (Figure 2). The
complex evolution of these blocking conditions highlights both the higher intensity of the anomalies and
the broader spatial extension (e.g., compared to the classification of Stefanon et al., 2012), which contribute
to explain the exceptional observed temperature anomalies. The occurrence and persistence of atmospheric
blocking conditions are key factors in the development of large-scale heat wave and drought, and to
trigger soil-moisture temperature feedbacks (Brunner et al., 2018, 2017; Miralles et al., 2014; Luterbacher
et al., 2004).
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Figure 1. (a) 2018 estimated SPEI-6 (March–August) and (b) associated spatial extent (km2·105) of the severe-to-extreme (orange bars) and extreme (red bars)
drought events in central Europe from 1976 to 2018. The white boxes in (a) indicate the two regions of interest: southern Europe and central Europe. (c) 2018
estimated SPEI-3 (June–August) and associated (d) spatial extent (km2·105) of the severe-to-extreme (orange bars) and extreme (red bars) drought events in
central Europe from 1976 to 2018. SPEI = Standardized Precipitation Evapotranspiration Index.
The severity of the 2018 drought as well as the pronounced water seesaw can be visualized in the anoma-
lous fAPAR values from March to August (spring and summer) compared with the entire measurement
period 1999–2017 (Figure 3). The drought event impacted plant growth in large areas of central and north-
ern Europe and exceptionally reduced biomass accumulation, as suggested by fAPAR anomalies of 15–25%
(compared to 1999–2017; Figures 3 and S3 on agricultural areas) even exceeding 25% locally. In these
regions, the 2018 summer biomass accumulation in the agricultural areas (as inferred by the fAPAR) was
the lowest of the entire observational record since 1999 (Figure 3). In contrast, southern Europe experienced
above-normal biomass accumulation (Figure 3) sustained by the exceptional spring precipitation.
3.2. The 2018 Extreme Event in a Paleoclimate Perspective
By using the SPEI-6 spatial distribution applied to the available observational records since 1976, only five
events resemble the 2018 drought in central Europe: 1976, 1990, 1992, 2003, and 2015 (Figure S4). However,
none of these years was characterized by a water seesaw as/as pronounced as the one in 2018. The 2018
drought in central Europe compares well in extent with the drought in 1976 and 2003 (Figures 1 and S4).
The 1976 drought has often been considered a benchmark due to its severity (Burke et al., 2010; Briffa et al.,
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Figure 2. Anomalies (with respect to the available data period) of the 2018 monthly (from March to August)
geopotential height at 500 hPa as represented by ERA-Interim (values in meters).
2009), with one of the longest heat waves (in the observational records) from June to August and negative
rainfall anomalies from May to August. The 2003 event and its impacts have been described and analyzed in
several studies (Ciais et al., 2005; Fink et al., 2004; Garcia-Herrera et al., 2010). The 1990 and 1992 droughts
were among the biggest events in Europe since 1950 (Spinoni et al., 2015), while the 2015 event in central
Europe was even drier in summer than 2003 (Orth et al., 2016b). Concerning the summer heat waves in 1976,
1992, and 2003, the contribution of Mediterranean dry springs was highlighted by Zampieri et al. (2009).
The combination of dry spring, the exceptionally warm spring/summer temperatures, and the dry summer
makes the 2018 event unique in a longer climatological perspective. Studying seasonal European tempera-
ture and precipitation gridded paleo-reconstructions back to 1500 CE reveals no events similar to 2018 in
central Europe in terms of concurrent spring-to-summer temperature and precipitation quantiles spatial
distribution (Figure 4). Focusing on summer months alone (June to August), a few events appear to be sim-
ilar to 2018, notably the 1540 and 1947 droughts. According to reconstructed temperature and precipitation
fields, the 1540 event was characterized by a very dry and warm summer (similar to the 2018 one) though
spring conditions were even drier than in 2018 (Figure 4). However, though drier, the extreme 2018 spring
temperatures were not reached. The 1540 event is also unique from a climate perspective (Orth et al., 2016a;
Pfister, 2016; Wetter et al., 2014). In 1540, chronicles narrate of people taking refuge in cellars during the
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Figure 3. (Left panel) Anomalies (percent) of the fAPAR accumulated from March to August 2018 with respect to 1999–2017. (Right panel) Regions where the
2018, 2015, and 2003 summer (June to August) fAPARs (calculated on agricultural land) were the lowest, second lowest, and third lowest since 1999.
fAPAR = fraction of absorbed photosynthetically active radiation data.
day in France, of autumn-like trees and forest fires in many areas of Europe (Pfister, 2016), while the entire
agricultural sector was heavily affected with cattle dying of thirst and hunger and complete loss of spring
grains, legumes, and fruits (Pfister, 2016).
By looking only at the summer temperature conditions being as extreme as the 2018 one (or more), 14 events
can be identified since 1500 CE, 5 of them being in the 16th century and 3 in the 20th century and the 2003.
While 2018-similar extreme spring conditions are more rare with only five events detected in the last 500
years: 1794, 1822, 1994, 2000, and 2007. This points again to the importance and uniqueness of the concur-
rent extreme conditions both in spring and summer that characterized the 2018 event. The contribution of
the exceptionally and rare warm spring conditions can be evaluated by performing an idealized experiment:
Figure 4. (a) 2018-like summer drought events in central Europe identified by using as metric the concurrent spatial
distribution of spring and summer temperature and precipitation quantiles. (b) Estimated spatial probability density
functions of spring and summer temperatures (red for summer and violet for spring) and precipitation (yellow for
spring and brown for summer) in 1540 (dashed lines) and 2018 (bold lines).
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Figure 5. Estimated spatiotemporal (time of occurrence in the xaxis and spatial extent ×105in the yaxis) frequency of
extreme drought events (Standardized Precipitation Evapotranspiration Index-6 <2) in central Europe as identified in
the seven climate model simulations from 1976 to 2100 under the high-end emission scenario RCP8.5. Values in the
frequency legend are ×102.
the SPEI-6 (from March to August) and its spatial distribution in central Europe are rederived by replacing
the extreme spring temperatures with average values, while all the other factors (i.e., drier spring precipita-
tion, very warm, and dry summer) are kept as they were observed in 2018. The spatial distribution of this
idealized SPEI still points to severe drought conditions but not to extreme ones (not shown).
3.3. Future Projections
To understand how the frequency and severity of the 2018 water seesaw and its drought component
might change in the coming decades over Europe, climate projections till 2100 are analyzed. As done
for the period covered by observational gridded data (1976–2018), we derive SPEI-3 (June–August) and
SPEI-6 (March–August). Then, we investigate their changes and identify events similar to 2018 (i.e., with
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Figure 6. (a) 2018-like drought events in central Europe in the seven climate model simulations from 1976 to 2100
under the high-end emission scenario RCP8.5. The events have been identified by using the spatial distribution of the
estimated Standardized Precipitation Evapotranspiration Index-6. (b) Estimated frequency of occurrence of the
2018-like drought events in central Europe in the seven climate model simulations from 1976 to 2100. The dashed lines
indicate when these events will become the norm in each simulation.
similar spatial distribution of SPEI values). The combined spatiotemporal SPEI analysis (investigat-
ing both the occurrence and the spatial extent) of extreme drought events (SPEI less than 2) in
central Europe reveals an increased frequency toward the end of the century in all seven climate
realizations (Figure 5). However, the magnitude of these changes (especially concerning the spa-
tial extent) varies among the seven climate model projections (Figure 5). Similar findings character-
ize the severe-to-extreme drought events (SPEI less than 1.5; Figure S5). Regarding the 2018-like
drought events in central Europe (Figure 6), all seven climate model simulations show a fre-
quency similar to the one derived from observations in the historical period (1976–2005). Projec-
tions for the next decades (2006–2100) show a remarkable increase in the frequency of occurrence of
2018-like drought events (considering both the 6-month period from March to August and the sum-
mer months). All seven model simulations are coherent and consistent in this projected increase,
which can be better evaluated through the estimated nonstationary intensity functions (see section 2)
describing the frequency of occurrence of these large-scale drought events (Figure 6). The frequency of
occurrence also reveals how these events could become the norm (see section 2) as early as 2043 (Figure 6).
Three model runs show that these droughts will become the norm 13–23 years after global mean warm-
ing reaching 3(Table S1), while in other two model runs, this will happen exactly when 3of global mean
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Figure 7. Estimated spatiotemporal (time of occurrence in the xaxis and spatial extent ×105in the yaxis) frequency of
spring-to-summer anomalous wet events (Standardized Precipitation Evapotranspiration Index-6 >1.5) in southern
Europe as identified in the climate model simulations from 1976 to 2100 under the high-end emission scenario RCP8.5.
Values in the frequency legend are ×102.
warming will be reached. Only two model runs show these events being the norm already 1-6 years after
having reached 2of global mean warming (Table S1).
To better understand the projected drought events in central Europe as well as the uniqueness of the 2018
one, concurrent very warm and dry springs and very warm and dry summers are analyzed in the model pro-
jections (as done for the observational period and the paleoclimate reconstructions). Only a few events like
the 2018 one can be identified (Figure S6). This lack of 2018-like concurrent event is mainly due to projected
changes in spring precipitation regimes that reduce the frequency of as dry as 2018 conditions. Therefore,
future drought events in central Europe will be mainly associated with extreme summer conditions and very
warm springs.
Despite models' ability to reproduce drought events in central Europe during the historical simulations
(1976–2005; Figure 6), the 2018 water seesaw (with concurrent drought and anomalous wet conditions over
Europe) is reproduced only twice in two realizations, that is, in 4 years out of 875 simulated years. Fur-
thermore, model simulations reproduce large-scale wetter conditions, such as those observed in southern
Europe in 2018, very rarely. Projections show a decrease in the frequency of occurrence and spatial exten-
sion of anomalous wet conditions over those regions (Figure 7), with all model simulations pointing to
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almost no events by mid-21st century (already by 2030s in a couple of simulations). These results imply the
exceptionality of the 2018 compensation, which is not likely to occur again in the future.
4. Discussion
The 2018 drought had severe impacts in a number of socioeconomic sectors (beAWARE news, 2018; WMO
news, 2018), for example, higher than usual death rates among elderly people, difficulties in power plant
cooling, stability issues in The Netherlands' dike system due to lack of freshwater, extremely low river lev-
els with negative impact on the transport sector, and industries dependent on water way transport, forest
fires, and notably serious impacts on agriculture. Although official production and yield estimates are not
yet available, preliminary wheat production estimates (Eurostat, 2018) in the main affected countries report
losses from 9% to 50% with respect to the mean of the previous 5 years. Barley production dropped by 1%
to 27%. In Germany, a maize production reduction of 25% has been reported (Eurostat, 2018). Drought
also heavily affected pasture (generally not irrigated) with detrimental effects on the livestock/dairy sector.
However, the positive effects of Europe's 2018 water seesaw were manifest in favorable conditions in south-
ern Europe. Preliminary wheat production estimates report an increase of 19% in Spain and Portugal and
24% in Romania. Thus, market cooperation across the European Union could, in this instance, act as a form
of adaptation to the climatic extremes experienced preventing higher volatility and price spikes.
Observations and paleoclimate reconstructions have shown the uniqueness of the 2018 event, characterized
by concurrent seasonal anomalies in spring/summer temperature and precipitation. It is worth to point out
that the exceptionally warm spring of 2018 turned a severe drought into an extreme drought, while it is
virtually certain that the Northern Hemisphere heat events in 2018 have been caused by human-induced
climate change (Vogel et al., 2019).
In the future projections, similar drought conditions in central Europe will become a common occurrence,
but the 2018 event will remain unique in terms of concurrent spring and summer climate anomalies.
Drought events will indeed be mainly associated with extreme temperature conditions (both in spring and
summer) and very dry summer. Disentangling and quantifying the effects of mean warming conditions and
atmospheric dynamics on the identified future drought events is not straightforward and requires dedicated
analysis. However, an idealized experiment, obtained by rederiving the SPEI-6 from March to August (dur-
ing the identified drought events) considering only the temperature component due to the mean warming
(while keeping unchanged all the other factors), points to a time-dependent response. Up to a certain degree
of warming (e.g., more than 3for the first model simulation), the atmospheric dynamics seems to act by
enhancing the mean temperature warming effects in the drought conditions. Afterward, a change in this
mechanism seems to appear pointing to modified drought dynamics. Dedicated in-depth analyses are of
course needed to better understand these changes in very high warming scenarios.
The projected favorable change in the spring precipitation regime in central Europe could be seen as an
opportunity for adaptation, but it also points to issues that could affect agricultural risk assessments. Crop
growth models (often used in such assessments) could be indeed too positively responsive to future spring
precipitation, and thus, the need of having realistic representation of heat stress and soil-atmosphere fluxes
in these models is essential to avoid underestimating the impacts of future drought events.
5. Conclusions
The findings of this study point to the urgent need to identify realistic adaptation pathways to minimize
risks and losses induced by large-scale drought events in key and complex sectors such as the agricul-
ture. European resilience analysis for the coming decades needs to consider the projected reduced/lack of
compensation given by water seesaw. Adaptation strategies for the agricultural sector will need to address
concurrent water-stress conditions throughout Europe. Negative effects of the projectedincrease in extremes
might be only partially limited by shorter phenological cycles, new varieties, and fertilization effects of
increased atmospheric CO2concentration (Challinor et al., 2016; Kimball, 2016; Obermeier et al., 2017;
Parkes et al., 2018; Rezaei, Siebert, Hging, et al., 2018; Trnka et al., 2011). Crops, such as maize, could be
more affected by projected increases in severe drought events (Webber et al., 2018; Zampieri et al., 2019),
and as seen in 2018, the livestock sector will also be negatively impacted due to the lack of fodder crops.
Besides the local impacts, it will be important to define strategies to limit the propagating effects of economic
Earth’s Future 10.1029/2019EF001170
shocks induced by these extremes at the European level. While market forces can play a role in mitigat-
ing the adverse effects of extreme events (e.g., global cereal prices have stabilized after the summer peak in
2018, thanks to good forecasts for wheat production in the United States and Russia; European Commission,
2018) balancing higher than expected yields from one set of European countries against losses elsewhere
may not be a viable option in the future. The results presented here show that the push and pull of droughts
in one region and the absence of water stress elsewhere do translate into crop yield differentials, but they
also show that such water seesaw conditions are rare, and going to get rarer still, while drought occurrence
will increase. Furthermore, global concurrent climate extremes must be taken into account for robust risk
assessments (Toreti, Cronie, et al., 2019).
Climate change adaptation strategies for agriculture in Europe cannot count on recurrent water seesaws. It
may have taken more than 500 years to reach the concurrent extreme conditions experienced in 2018, but
the next 50 years will see similar conditions replicated many times over. 2018 should serve as a warning call.
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connection to the abrupt end of the 2016/2017 Iberian drought. Geophysical Research Letters,45, 12,639–12,646.
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jrc-climate- spei-drought
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raw HELIX projections can be
requested by contacting the HELIX
Project Manager https://helixclimate.
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... For west-central Europe precipitation increases are projected for winter and autumn, while smaller increases or small decreases are projected for spring and summer 70 (Jacob et al., 2014, Aalbers et al., 2018, Coppola et al., 2021, Gutiérrez et al. 2021. Soil moisture is projected to further decrease, with strongest responses in summer and autumn (Ruosteenoja et al., 2018, Van der Linden et al., 2019 and studies based on large model ensembles show increases in the frequency and severity of (multi-year) drought episodes (Samaniego et al., 2018, Toreti et al., 2019, Hari et al., 2020. The magnitude and direction of the precipitation changes and the magnitude and timing of the soil moisture drying response are uncertain, and depend on e.g. the climate model resolution and generation 75 (Jacob et al., 2014, Coppola et al., 2021, Van der Linden et al., 2019, biases in the mean climate state in the reference period, and the ability of climate models to realistically represent land-surface-atmosphere coupling (Orth et al., 2016, Van der ...
... However, the drought intensity indeed increases, yielding a 20% (EC) to 39% (HAD) increase in drought severity under 2°C global warming. From an impact perspective, this is a considerable increase, with substantial costs to society and nature already under present-day conditions (Van Hussen et al., 2019, De Brito et al., 2020, Toreti et al. 2019, Schuldt et al., 2020, Beillouin et al., 2020, Senf and Seidl, 2021. The increase in drought severity in summer co-occurs with an increase in local summer temperature that is considerably larger 490 than the mean climate response. ...
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Projections of changes in extreme droughts under future climate conditions are associated with large uncertainties, owing to the complex genesis of droughts and large model uncertainty in the atmospheric dynamics. In this study we investigate the impact of global warming on soil moisture drought severity in west-central Europe by employing pseudo-global warming (PGW) experiments, which project the 1980–2020 period in a globally warmer world. The future analogues of present-day drought episodes allow investigation of changes in drought severity conditional on the historic day-to-day evolution of the atmospheric circulation. The 2018 west-central European drought is the most severe drought in the 1980–2020 reference period in this region. Under 1.5 °C, 2 °C and 3 °C global warming, this drought episode experiences strongly enhanced summer temperatures, but a fairly modest soil moisture drying response compared to the change in climatology. This is primarily because evaporation is already strongly moisture-constrained during present-day conditions, limiting the increase in evaporation and thus the modulation of the temperature response under PGW. Increasing precipitation in winter, spring and autumn limit or prevent an earlier drought onset and duration. Nevertheless, the drought severity, defined as the cumulative soil moisture deficit volume, increases considerably, with 20 % to 39 % under 2 °C warming. The extreme drought frequency in the 1980–2020 period strongly increases under 2 °C warming. Several years without noticeable droughts under present-day conditions show very strong drying and warming. This results in an increase in 2003-like drought occurrences, compounding with local summer temperature increases considerably above 2 °C. Even without taking into account a (potentially large) dynamical response to climate change, drought risk in west-central Europe is strongly enhanced under global warming. Owing to increases in drought frequency, severity and compounding heat, a reduction in recovery times between drought episodes is expected to occur. Our physical climate storyline provides evidence complementing conventional large-ensemble approaches, and is intended to contribute to the formulation of effective adaptation strategies.
... These coherent meteorological variables are essentially linked with each other in physics. A high-pressure anomaly induces stronger heating by sinking air and increased solar radiation (Gao et al., 2018b;Qi et al., 2019;Wang et al., 2017), leading to a drier and hotter atmosphere and surface (Kautz et al., 2022;Toreti et al., 2019;Zhuang et al., 2021). The dry and hot climate anomalies make the vegetation more flammable through the atmosphere-land-fire physical linkages (Flannigan et al., 2009;Nolan et al., 2020;Thonicke et al., 2001). ...
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With the increased damage caused by wildfires under global warming, accurately predicting wildfires remains challenging yet crucial for regional disaster mitigation. The boreal summer (June–September: JJAS) wildfire burned area (BA) of Central Asia reaches the greatest seasonal extent and has the largest interannual variance over the Eurasian continent. Considering both physical relationships and prediction skills for the BA, two independent physical meteorological variables are found to dominate the interannual variance in Central Asian summer BA during 1996–2016. One is the decreased March snow water equivalent (SWE), consistent with the regional warming and increased soil moisture in March, which favors subsequent plant growth. The other is the increased JJAS 500 hPa geopotential height (GHT500) over Central Asia, corresponding to the summer dryness anomaly, which enhances the local fuel flammability. Accordingly, a physically-based statistical-dynamical seasonal model, starting from April 1st each year, is established for predicting Central Asian summer BA using the observed March SWE and dynamically-predicted JJAS GHT500. This model has the highest operational prediction skill (of 0.58) among numerous tests, and is shown to be stable by using K-Fold cross-validation. Although the pre-winter ENSO is correlated with the Central Asian summer circulation anomaly, the prediction skills using ENSO-based models (both statistical and statistical-dynamical) are either low or unstable. This study suggests that the regional wildfire can be accurately predicted by choosing relevant meteorological variables and optimal dynamically-predicted fields. This approach has a great potential to be useful for seasonal wildfire prediction and future projection under climate change.
... In central and northern Europe the 2018 summer was exceptionally hot and dry, and associated with forest fires in Scandinavia, heat stress, and agricultural production loss. 88,89 It has been very uncommon for the typically wet regime in northern Europe that soil moisture-temperature feedbacks amplify the warming. 89 Thus, the 2018 summer highlights again the important role of soil moisture-atmosphere feedbacks for summer heatwaves. ...
... In 2020 the global wheat production was 760 million tons according to the FAOSTAT (2020), a warming of 1.5°C would mean a loss of 68 million tons. As the climate warms, droughts or dry and hot conditions are expected to become the norm by mid-century in major growing regions such as parts of Europe, the USA and Canada, and wheat production will accordingly fall below its long-term average (Leng and Hall, 2019;Toreti et al., 2019). ...
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Drought events or the combination of drought and heat conditions are expected to become more frequent due to global warming, and wheat yields may fall below their long-term average. One way to increase climate-resilience of modern high-yielding varieties is by their genetic improvement with beneficial alleles from crop wild relatives. In the present study, the effect of two beneficial QTLs introgressed from wild emmer wheat and incorporated in the three wheat varieties BarNir, Zahir and Uzan was studied under well-watered conditions and under drought stress using non-destructive High-throughput Phenotyping (HTP) throughout the life cycle in a single pot-experiment. Plants were daily imaged with RGB top and side view cameras and watered automatically. Further, at two time points, the quantum yield of photosystem II was measured with a top view FluorCam. The QTL carrying near isogenic lines (NILs) were compared with their corresponding parents by t -test for all non-invasively obtained traits and for the manually determined agronomic and yield parameters. Data quality of phenotypic traits (repeatability) in the controlled HTP experiment was above 85% throughout the life cycle and at maturity. Drought stress had a strong effect on growth in all wheat genotypes causing biomass reduction from 2% up to 70% at early and late points in the drought period, respectively. At maturity, the drought caused 47–55% decreases in yield-related traits grain weight, straw weight and total biomass and reduced TKW by 10%, while water use efficiency (WUE) increased under drought by 29%. The yield-enhancing effect of the introgressed QTLs under drought conditions that were previously demonstrated under field/screenhouse conditions in Israel, could be mostly confirmed in a greenhouse pot experiment using HTP. Daily precision phenotyping enabled to decipher the mode of action of the QTLs in the different genetic backgrounds throughout the entire wheat life cycle. Daily phenotyping allowed a precise determination of the timing and size of the QTLs effect (s) and further yielded information about which image-derived traits are informative at which developmental stage of wheat during the entire life cycle. Maximum height and estimated biovolume were reached about a week after heading, so experiments that only aim at exploring these traits would not need a longer observation period. To obtain information on different onset and progress of senescence, the CVa curves represented best the ongoing senescence of plants. The QTL on 7A in the BarNir background was found to improve yield under drought by increased biomass growth, a higher photosynthetic performance, a higher WUE and a “stay green effect.”
... In central and northern Europe the 2018 summer was exceptionally hot and dry, and associated with forest fires in Scandinavia, heat stress, and agricultural production loss. 88,89 It has been very uncommon for the typically wet regime in northern Europe that soil moisture-temperature feedbacks amplify the warming. 89 Thus, the 2018 summer highlights again the important role of soil moisture-atmosphere feedbacks for summer heatwaves. ...
... Variations in crop yield at global and European scale have been shown to be strongly influenced by climate variability [1][2][3], and the frequency of extreme weather events, such as heatwaves, droughts and floods, is increasing [4][5][6]. This raises urgent food security concerns about crop yields and food production at local and global scale. ...
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The incidence of dry or wet day sequences has a great influence on crops management and development. The lack of spatialized observed data with appropriate temporal resolution to investigate the changes that has occurred during the last century regarding the length and frequencies of those sequences has led to reliance on reanalysis products. However, the question can be raised about the suitability of those products when evaluating such climate indices and their impacts on crop production. Different products are here investigated to evaluate how the succession of dry and wet days are depicted in Sweden. Results show that reanalysis product tends to overestimate the number of wet days and wet periods and underestimate dry periods. We also showed clearly that the frequency and intensity of dry and wet spells returned can differ widely between products. For instance, number of dry spell events can range from 1 to 11 over the same decade for two different products. This paper does not aim to classify the RPs regarding their goodness or efficiency but try to highlights the divergence between them in representation of spells which could generate substantial differences in climate impact analysis in agricultural modeling.
... trillion in economic losses and~495,000 human deaths. For example, daily maximum temperatures in Scandinavia, the Netherlands, and Belgium exceeded those in the historical record in the summer of 2018, triggering unprecedented forest fires [8,9]. Meteorological disasters in China have been responsible for 70% of total economic losses due to natural disasters, with extreme weather events accounting for 80% of the total [10]. ...
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Climate change has increased the frequency of extreme climate events, with different regions showing different sensitivities to these events. In this study, the full subset regression analysis, correlation analysis, and multiple linear regression analysis were used to analyze trends of extreme climate changes and their effects on vegetation on the Mongolian Plateau from both historical and future perspectives. The results showed significant increasing and decreasing trends in extreme warming and extreme cooling indices, respectively, over the past three decades. The extreme temperature indices and precipitation trends under three scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios) were consistent with historical trends, and the rates at which temperature and precipitation increased were positively correlated with increasing radiation intensity. In comparison with historical changes, there were gradual increases in areas of regions with increasing temperature and precipitation and decreases in areas with decreasing precipitation. There was an overall increasing trend in the normalized difference vegetation index (NDVI) of the Mongolian Plateau, and the indices that had the greatest influence on the NDVI during the analysis of climate extremes were: (1) the number of days of heavy rainfall (R20); (2) the number of summer days (SU25) and; (3) high extreme daily minimum temperature (TNx). There was an increasing trend in the NDVI from 2021 to 2080, and the rate of the NDVI increase decreased with increasing radiation intensity. The rates of change in the NDVI under all three scenarios were lower than that of the historical period.
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Quantification of land surface-atmosphere fluxes of carbon dioxide (CO2) fluxes and their trends and uncertainties is essential for monitoring progress of the EU27+UK bloc as it strives to meet ambitious targets determined by both international agreements and internal regulation. This study provides a consolidated synthesis of fossil sources (CO2 fossil) and natural sources and sinks over land (CO2 land) using bottom-up (BU) and top-down (TD) approaches for the European Union and United Kingdom (EU27+UK), updating earlier syntheses (Petrescu et al., 2020, 2021b). Given the wide scope of the work and the variety of approaches involved, this study aims to answer essential questions identified in the previous syntheses and understand the differences between datasets, particularly for poorly characterized fluxes from managed ecosystems. The work integrates updated emission inventory data, process-based model results, data-driven sectoral model results, and inverse modeling estimates, extending the previous period 1990–2018 to the year 2020 to the extent possible. BU and TD products are compared with European National Greenhouse Gas Inventories (NGHGIs) reported by Parties including the year 2019 under the United Nations Framework Convention on Climate Change (UNFCCC). The uncertainties of the EU27+UK NGHGI were evaluated using the standard deviation reported by the EU Member States following the guidelines of the Intergovernmental Panel on Climate Change (IPCC) and harmonized by gap-filling procedures. Variation in estimates produced with other methods, such as atmospheric inversion models (TD) or spatially disaggregated inventory datasets (BU), originate from within-model uncertainty related to parameterization as well as structural differences between models. By comparing NGHGIs with other approaches, key sources of differences between estimates arise primarily in activities. System boundaries and emission categories create differences in CO2 fossil datasets, while different land use definitions for reporting emissions from Land Use, Land Use Change and Forestry (LULUCF) activities result in differences for CO2 land. The latter has important consequences for atmospheric inversions, leading to inversions reporting stronger sinks in vegetation and soils than are reported by the NGHGI. For CO2 fossil emissions, after harmonizing estimates based on common activities and selecting the most recent year available for all datasets, the UNFCCC NGHGI for the EU27+UK accounts for 3392 ± 49 Tg CO2 yr-1 (926 ± 13 Tg C yr-1), while eight other BU sources report a mean value of 3340 [3238,3401] [25th,75th percentile] Tg CO2 yr-1 (948 [937,961] Tg C yr-1). The sole top-down inversion of fossil emissions currently available accounts for 3800 Tg CO2 yr-1 (1038 Tg C yr-1), a value close to that of the NGHGI, but for which uncertainty estimates are not yet available. For the net CO2 land fluxes, during the most recent five-year period including the NGHGI estimates, the NGHGI accounted for -91 ± 32 Tg C yr-1 while six other BU approaches reported a mean sink of -62 [-117,-49] Tg C yr-1 and a 15-member ensemble of dynamic global vegetation models (DGVMs) reported -69 [-152,-5] Tg C yr-1. The five-year mean of three TD regional ensembles combined with one non-ensemble inversion of -73 Tg C yr-1 has a slightly smaller spread (0th–100th percentile of [-135,45] Tg C yr-1), and was calculated after removing land-atmosphere CO2 fluxes caused by lateral transport of carbon (crops, wood trade and inland waters) resulting in increased agreement with the the NGHGI and bottom-up approaches. Results at the sub-sector level (Forestland, Cropland, Grassland) show generally good agreement between the NGHGI and sub-sector-specific models, but results for a DGVM are mixed. Overall, for both CO2 fossil and net CO2 land fluxes, we find current independent approaches are consistent with the NGHGI at the scale of the EU27+UK. We conclude that CO2 emissions from fossil sources have decreased over the past 30 years in the EU27+UK, while large uncertainties on net uptake of CO2 by the land surface prevent trend identification. In addition, a gap on the order of 1000 Tg C yr-1 between CO2 fossil emissions and net CO2 uptake by the land exists regardless of the type of approach (NGHGI, TD, BU), falling well outside all available estimates of uncertainties. However, uncertainties in top-down approaches to estimate CO2 fossil emissions remain uncharacterized and are likely substantial. The data used to plot the figures are available at
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Heatwaves are one of the most dangerous natural hazards in the world. Higher daily peak temperatures, duration, intensity and frequency of heatwaves are increasing globally due to climate change. In India, the instances of heatwaves have increased in recent years along with their intensity which has resulted in increased casualties. For the purpose of mitigation and reduction of damages due to heatwaves timely and accurate forecasts of such events are required. In order to check the accuracy and to generate more confidence in using these forecasts, an in-depth verification of the forecasts is required. Many traditional verification methods are commonly used to assess the performance of numerical weather prediction (NWP) models in predicting extreme weather like heatwaves. These methods have a limited utility as they are dependent only on a match at a grid-to-grid level. Spatial verification techniques, such as features or object-based approaches, can illustrate the model performance in a significant way by differentiating between forecast and observed features and comparing their spatial scale, shape, size, orientation, coverage area, displacement and intensity. In this study, we have tried to demonstrate the ability of a global model in predicting a maximum 2m temperature ( Tmax ), particularly in the heatwave-prone zones of India. For this purpose, the forecasts of Tmax obtained from the National Centre for Medium Range Weather forecasting (NCMRWF) Unified Model (NCUM) are verified using the Method for Object-Based Diagnostic Evaluation (MODE). The study period is chosen to be March to May 2022. This study showed that NCUM forecast objects had a possible perfect timing and propagation of Tmax ≥ 41°C and ≥ 43°C objects when compared to the observations. It was also noticed that the NCUM model had a southwesterly bias in the location of Tmax objects for Tmax ≥ 45°C, indicating a potential lag in system propagation. On the seasonal scale assessment showed that the forecast performance of the model for heatwaves ( Tmax ≥ 41°C and ≥ 43°C) is reasonably good which is supported by many attributes like centroid distance; there was a small variation in the centroid distance median is ~ 150–200 km up to 120 hr lead times. The complexity ratio showed that the internal structure of the forecast matched ~ 83% and this result was supported by the curvature ratio was the near to perfect i.e. 95–97%, the 50th percentile intensity ratio which is also near to perfect 98–99% and the symmetric difference is the small enough to coincide with the observed heatwave zones. Based on the total interest varying in the range of 90–97% up to 120 hr lead times it is evident that NCUM model accurately forecasts the heatwaves structure, shape and size well in advance up to 120 hr lead times.
Throughout history, Europe and North America have experienced intense and long-lasting droughts with large impacts on society and ecosystem such as the recent drought 2018/2019 and historical drought 1540 in Europe, or the US Dust Bowl of the 1930s. To increase resilience and develop adaptation strategies to such extreme droughts, it is important to understand how dry a worst-case drought would be and how long it would take to recover from it. This study introduces and evaluates a methodological framework to generate coherent climate model-based drought storylines of different severities and for different locations. The so-called iterative ensemble resampling method repeatedly runs large ensembles and only keeps those ensemble members, which minimize local precipitation. The drought storylines are developed with the fully coupled global climate model CESM1. The first part of the analysis demonstrates the feasibility of the framework by generating some of the most extreme droughts possible. Using stringent precipitation criteria, accumulated precipitation is reduced by 80% relative to the long-term average in western Europe and by 77% in central North America, respectively, over multiple years. The number of dry days in the Western European storyline corresponds to estimates in the reconstructed drought 1540 in Central Europe. The low precipitation induces soil moisture deficit storylines that are physically consistent but beyond high return levels estimated based on purely statistically fitted generalized extreme value (GEV) distributions. In the second part, the drought storylines are used as a setup to assess the recovery time of such extreme soil moisture deficits. Over the driest regions in central and western Europe as well as central and eastern North America, the soil moisture recovers over a period of a few months up to more than five years, depending on the mean atmospheric circulation rather than on the strength of the soil moisture deficit. The framework of iterative ensemble resampling can generate up to very rare physically consistent storylines to conduct idealized experiments. When lowering the selection criteria for precipitation, the framework can be used to generate less extreme drought storylines that are more likely to occur in the real world. This approach can help to stress test the socioeconomic system and adaptation strategies for potential long-lasting drought periods.
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Extremely high temperatures pose an immediate threat to humans and ecosystems. In recent years, many regions on land and in the ocean experienced heat waves with devastating impacts that would have been highly unlikely without human-induced climate change. Impacts are particularly severe when heat waves occur in regions with high exposure of people or crops. The recent 2018 spring-to-summer season was characterized by several major heat and dry extremes. On daily average between May and July 2018 about 22% of the populated and agricultural areas north of 30° latitude experienced concurrent hot temperature extremes. Events of this type were unprecedented prior to 2010, while similar conditions were experienced in the 2010 and 2012 boreal summers. Earth System Model simulations of present-day climate, that is, at around +1 °C global warming, also display an increase of concurrent heat extremes. Based on Earth System Model simulations, we show that it is virtually certain (using Intergovernmental Panel on Climate Change calibrated uncertainty language) that the 2018 north hemispheric concurrent heat events would not have occurred without human-induced climate change. Our results further reveal that the average high-exposure area projected to experience concurrent warm and hot spells in the Northern Hemisphere increases by about 16% per additional +1 °C of global warming. A strong reduction in fossil fuel emissions is paramount to reduce the risks of unprecedented global-scale heat wave impacts.
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Climate extremes have profound impacts on key socio-economic sectors such as agriculture. In a changing climate context, characterised by an intensification of these extremes and where the population is expected to grow, exposure and vulnerability must be accurately assessed. However, most risk assessments analyse extremes independently, thus potentially being overconfident in the resilience of the socio-economic sectors. Here, we propose a novel approach to defining and characterising concurrent climate extremes (i.e. extremes occurring within a specific temporal lag), which is able to identify spatio-temporal dependences without making any strict assumptions. The method is applied to large-scale heat stress and drought events in the key wheat producing regions of the world, as these extremes can cause serious yield losses and thus trigger market shocks. Wheat regions likely to have concurrent extremes (heat stress and drought events) are identified, as well as regions independent of each other or inhibiting each other in terms of these extreme events. This tool may be integrated in all risk assessments but could also be used to explore global climate teleconnections.
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We estimate the effects of climate anomalies (heat stress and drought) on annual maize product ion, variability and trend from the country level to the global scale using a statistical model. Moderate climate anomalies and extremes are diagnosed with two indicators of heat stress and drought computed over maize growing regions during the most relevant period of maize growth. The calibrated model linearly combines these two indicators into a single Combined Stress Index (CSI). The CSI explains 50% of the observed global production variability in the period 1980 - 2010. We apply the model on an ensemble of high-resolution global climate model simulations. Global maize losses, due to extreme climate events with 10 - year return times during the period 1980 - 2010 will become the new normal already at 1.5 ° C global warming levels (ca. 2020s). At 2 ° C warming (late 2030s), maize areas will be affected by heat stress and drought never experienced before, affecting many major and minor production regions.
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Voronoi estimators are non-parametric and adaptive estimators of the intensity of a point process. The intensity estimate at a given location is equal to the reciprocal of the size of the Voronoi/Dirichlet cell containing that location. Their major drawback is that they tend to paradoxically under-smooth the data in regions where the point density of the observed point pattern is high, and over-smooth where the point density is low. To remedy this behaviour, we propose to apply an additional smoothing operation to the Voronoi estimator, based on resampling the point pattern by independent random thinning. Through a simulation study we show that our resample-smoothing technique improves the estimation substantially. In addition, we study statistical properties such as unbiasedness and variance, and propose a rule-of-thumb and a data-driven cross-validation approach to choose the amount of smoothing to apply. Finally we apply our proposed intensity estimation scheme to two datasets: locations of pine saplings (planar point pattern) and motor vehicle traffic accidents (linear network point pattern).
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Southwestern Europe experienced extraordinary rainy and windy conditions in March 2018, leading to the end of the most severe drought since 1970 at continental scale. This anomalous weather was linked to a persistent negative North Atlantic Oscillation pattern. Two weeks earlier a sudden stratospheric warming (SSW) took place, preceded by the strongest planetary wave activity on record. In this study, we explore the connection between the SSW and the weather shift by employing a weather regime approach and flow analogues. The timing of the downward propagation of the stratospheric anomalies, the transition to and persistence of the negative North Atlantic Oscillation weather regime, and the sudden precipitation increase are all consistent with the typical tropospheric state after SSWs. Our results evidence a significant role of the 2018 SSW in the record-breaking precipitation event.
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Understanding the drivers of yield levels under climate change is required to support adaptation planning and respond to changing production risks. This study uses an ensemble of crop models applied on a spatial grid to quantify the contributions of various climatic drivers to past yield variability in grain maize and winter wheat of European cropping systems (1984–2009) and drivers of climate change impacts to 2050. Results reveal that for the current genotypes and mix of irrigated and rainfed production, climate change would lead to yield losses for grain maize and gains for winter wheat. Across Europe, on average heat stress does not increase for either crop in rainfed systems, while drought stress intensifies for maize only. In low-yielding years, drought stress persists as the main driver of losses for both crops, with elevated CO2 offering no yield benefit in these years.
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Maize (Zea mays) is one of the staple crops of West Africa and is therefore of high importance with regard to future food security. The ability of West Africa to produce enough food is critical as the population is expected to increase well into the twenty-first century. In this study, a process-based crop model is used to project maize yields in Africa for global temperatures 2 K and 4 K above the preindustrial control. This study investigates how yields and crop failure rates are influenced by climate change and the efficacy of adaptation methods to mitigate the effects of climate change. To account for the uncertainties in future climate projections, multiple model runs have been performed at specific warming levels of + 2 K and + 4 K to give a better estimate of future crop yields. Under a warming of + 2 K, the maize yield is projected to reduce by 5.9% with an increase in both mild and severe crop failure rates. Mild and severe crop failures are yields 1 and 1.5 standard deviations below the observed yield. At a warming of + 4 K, the results show a yield reduction of 37% and severe crop failures which previously only occurred once in 19.7 years are expected to happen every 2.5 years. Crops simulated with a resistance to high temperature stress show an increase in yields in all climate conditions compared to unadapted crops; however, they still experience more crop failures than the unadapted crop in the control climate.
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Weather observations are essential for crop monitoring and forecasting but they are not always available and in some cases they have limited spatial representativeness. Thus, reanalyses represent an alternative source of information to be explored. In this study, we assess the feasibility of reanalysis-based crop monitoring and forecasting by using the system developed and maintained by the European Commission- Joint Research Centre, its gridded daily meteorological observations, the biased-corrected reanalysis AgMERRA and the ERA-Interim reanalysis. We focus on Europe and on two crops, wheat and maize, in the period 1980–2010 under potential and water-limited conditions. In terms of inter-annual yield correlation at the country scale, the reanalysis-driven systems show a very good performance for both wheat and maize (with correlation values higher than 0.6 in almost all EU28 countries) when compared to the observations-driven system. However, significant yield biases affect both crops. All simulations show similar correlations with respect to the FAO reported yield time series. These findings support the integration of reanalyses in current crop monitoring and forecasting systems and point to the emerging opportunities linked to the coming availability of higher-resolution reanalysis updated at near real time.
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The impact of atmospheric blocking on European heat waves (HWs) and cold spells (CSs) is investigated for present and future conditions. A 50-member ensemble of the second generation Canadian Earth System Model is used to quantify the role of internal variability in the response to blocking. We find that the present blocking-extreme temperature link is well represented compared to ERA-Interim, despite a significant underestimation of blocking frequency in most ensemble members. Our results show a strong correlation of blocking with northern European HWs in summer, spring, and fall. However, we also find a strong anticorrelation between blocking and HW occurrence in southern Europe in all seasons. Blocking increases the CS frequency particularly in southern Europe in fall, winter, and spring but reduces it in summer. For the future we find that blocking will continue to play an important role in the development of both CSs and HWs in all seasons.