![]() |
||||||||||||||
|
Australia: The Land Where Time Began |
||||||||||||||
|
Increasing Likelihood of Dry-Hot Extremes on a Continental Scale
revealed by Century of Observations
It is shown by this paper, based on more than a century of ground-based
observations over the contiguous US, that the frequency of compound dry
and hot extremes has increased substantially in the past decades,
together with an alarming increase in very rare dry-hot extremes. It is
indicated by the results of this study that the area affected by the
concurrent extremes has also significantly increased. Further, Alizadeh
et al. explored homogeneity
(i.e., connectedness) of dry-hot extremes across space. They have shown
that dry-hot extremes have enlarged homogeneously over the past 122
years, which points to a spatial propagation of extreme dryness and heat
and increased probability of continental-scale compound extremes. Last,
they have shown an interesting shift between the main drivers of dry-hot
extremes over time. While meteorological drought was the main driver of
dry-hot events in the 1930s, the observed warming trend has become the
dominant driver in recent decades. A deeper understanding of
spatiotemporal variation of compound dry-hot extremes is provided by the
results of this study.
Traditional climate risk analyses have focused on the
hazardous/anomalous states of 1 variable at a time (Zscheischler &
Seneviratni, 2017). E.g., it has been shown by studies that magnitudes
of heatwaves, their frequencies, intensities and spatial extents are
increasing over many regions (Schӓr et
al., 2004), a trend that is
projected to continue in a warming climate (Hansen, Ruedy, Sato & Lo,
2010). Moreover, analyses of historical precipitation, streamflow and
soil moisture indices have shown an increasing trend of aridity over
many regions around the globe (Dai, 2011) and an increasing drought
hazard in the 21st century is pointed to in model
simulations. Individually, these extreme events can cause significant
adverse impacts, however when they occur concurrently the effects can be
even more devastating (Mueller & Seneviratni, 2012; Leonard et
al., 2014). E.g., a
significant increase in tree mortality can result from the compounding
effects of drought and high temperatures, which, in turn, may cascade
into other hazards, such as wildfires (Williams et
al., 2013). The most damaging
stressors to the production of wheat are concurrent drought and
heatwaves with grave implications for global food security; they can
also jeopardise the reliability of electric grids and a wide range of
natural and built systems (Guerreiro, 2018). Between 2011 and 2013, 3
concurrent drought and heatwave events caused damage estimated at
roughly 60 billion U.S. dollars (USD). Typically, compound extremes are
characterised by a complex chain of independent processes at different
special and temporal scales (Zscheischler et
al., 2018). E.g., droughts
and heatwaves are initiated typically by similar anomalies of synoptic
circulation; local and regional scale land-atmosphere feedbacks drive
the evolution of compound drought-heatwave events and intensify both
extremes (Miralles et al.,
2019). Climate change has altered the relationships systematically
between drivers of natural hazard, which increases the probability of
their concurrence as well as their severity and magnitude, while the
probability of the multiple extremes occurring simultaneously or
successively has historically been low. Background warming resulting
from anthropogenic emissions, e.g., triggers initiation of and stronger
land-atmosphere feedback loops, extending their spatial impacts across
North America (Dirmeyer et al.,
2013) which in turn, can intensify drought-heatwave extremes and spread
their spatial extent. More frequent extremes across the entire globe are
shown by the literature (Sarhadi et
al., 2018). Concurrent
droughts and heatwaves have increased with a shift that is statistically
significant in their distribution between 1990 and 2010 and 1960 and
1980 across the contiguous US (CONUS) (Mazdiyasni & Kauchak, 2015).
Additionally, concurrent moderate droughts and heatwaves have increased
across India (Sharma & Mujumdar, 2017), and meteorological droughts are
associated with a more rapid warming rate than average climate over
southern and northwestern US (Chiang & Mazdiyasni, 2018).
Drought-heatwave extremes can be intensified by land-atmosphere
feedbacks through 2 mechanisms: self-intensification and
self-propagation (Miralles et al.,
2019). Self-intensification refers to droughts and heatwaves being
intensified by each other, and self-propagation refers to the spreading
of droughts and heatwaves from a region to regions that are downwind
(Miralles et al., 2019;
Herrera-Estrada et al.,
2019). Examination of hot-dry (as well as their derivatives, i.e.,
compound drought-heatwave events have previously focussed on patterns of
synoptic circulation that initiate these extremes and self-intensifying
land-atmosphere processes that drive the evolution of these events
(Zscheischler & Seneviratni, 2017; Sarhadi, Ausin, Wiper & Touma, 2018;
Mazdiyasni & Kouchak, 2015; Chiang, Mazdiyasni, Kouchak, 2018). In this
study a mechanism that has been less explored of land-atmosphere
feedbacks that explains the propagation of atmospheric moisture deficit
that has been terrestrially sourced from one region to its neighbouring
areas, i.e., self-propagation. As manifested as trends in the spatial
homogeneity – connectedness – this process of concurrent dry-hot
extremes, has received less attention in past studies. Spatial
homogeneity of compound dry-hot extremes over CONUS was analysed by the
use of more than 100 years of climate data from ground observations.
Further, most of the literature analysed only the concurrence of
droughts and heatwaves after the 1950s (Mazdiyasni & Kouchak, 2015;
Sharma & Mujumdar, 2017; Hao, Kouchak & Phillips, 2013), which overlooks
the megadrought of the 1930s (Sarhadi, Ausin, Wiper & Touma, 2018).
Alizadeh et al. extended the
analysis to 1896-2017 (122 years) and provided a new perspective into
temperature trends of compound dry-hot events.
They used observations of monthly precipitation and average temperature
at the climate division scale to derive annual precipitation (water year
– WY: October to September), spring-summer (March to August) average
annual WY temperature, and average spring-summer (March to August)
temperature, which are, in turn, used in an empirical copula framework
to calculate the joint probability and return period of compound hot-dry
years, as well as various subannual events. Compound dry-hot extremes
were defined by Alizadeh et al.
as years that have joint return periods of deficit of precipitation and
excess of heat of more than 25 years (probability of joint annual
exceedance of less than 0.04), unless otherwise stated. They estimated
that the joint return period using the “AND” hazard scenario (drier than
a threshold) in a multivariate framework (Corbella & Stretch, 2012). It
is shown by the results of Alizadeh that the frequency of dry-hot
extremes is increasing across CONUS, which is a significant trend at the
5% level over the western US and parts of the northeastern and
southeastern US. It was demonstrated by spatial correlation analysis,
i.e., the connectedness of the areas that are impacted is increasing,
that these compound extremes are enlarging homogeneously. This has
significant environmental repercussions that are as large and extreme
events that are more intense can deplete rapidly regional and national
relief resources. This knowledge can help in the assessment of
regional-to-continental vulnerabilities of natural and built systems
under climate change and inform adaptation and mitigation efforts to
curb the grave compounding impacts of multiple extremes (Field et
al., 2014).
An increasing trend for the mean annual temperature between 1896 and
2017, which is statistically significant, across much of the CONUS, with
the exception of portions of the Southeast, east of the Southern Great
Plains, and the southern part of the Midwest, was shown by the
nonparametric Mann-Kendall analysis. There is a trend that is relatively
similar for mean spring-summer (March to August) temperatures, though
less pronounced for portions of the Northern Great Plains and Midwest.
Over much of CONUS annual precipitation has not changed significantly,
though patterns of precipitation and intensities may have shifted. There
is only a strip of land that extends from eastern Texas to the Great
Lakes and the Northeast that has a statistically significant increasing
trend (at the 5% level) for annual precipitation. When there are
persistent multiyear dry periods (Bayazit & Önöz, 2007), trend analysis
of precipitation at the annual scale, however, might be contentious in
the presence of autocorrelations among successive annual precipitation
values. It is shown by further investigation, however, that lag-1
autocorrelation values between annual precipitation – as well as
spring-summer precipitation – do not generally reach statistical
significance to justify removal of autocorrelation before trend
analysis. Similar behaviour is observed for high values of lag. The
interdependence of precipitation and temperature can intensify the
impacts state of each driver, while trends in both temperature and
precipitation have significant socio-environmental implications
(Kouchak, Cheng & Mazdiyasni, 2014).
Extreme temperatures, e.g., can induce “flash droughts” that have
devastating impacts such as causing large wildfires (Hoerling et
al., 2014; Mo & Lettenmaier,
2015). It is shown by Pearson linear correlation analysis that there is
significant negative association between annual precipitation and mean
annual temperature over much of the Great Plains and the Southwest.
However, this correlation is not statistically significant at the 5%
level for the west coast for much of the Pacific Northwest, and Midwest.
The interdependence is further pronounced between annual precipitation
and mean spring-summer (March to August) temperature as well as a
maximum spring-summer temperature. The dependence structure between
precipitation and temperature at different special and temporal scales
can be altered by climate change (Hao, Kouchak & Phillips, 2013). The
change in their association might, arguably, be more important than the
change (e.g., increasing trend) in each variable. Given that the mean
annual temperature shows a statistically significant trend across much
of the CONUS, unlike annual precipitation, Alizadeh et
al. linearly detrended the
mean annual (as well as mean annual and spring-summer) temperature and
reanalysed the linear association between temperature and precipitation.
A more pronounced Pearson correlation coefficient between annual
precipitation and mean annual temperature is pointed to by the results
of Alizadeh et al., when
temperature time series are detrended. There is a similar conclusion
when temperature is exponentially detrended. This shows that the
association between temperature and precipitation has been weakened by
climate change at the annual scale across CONUS. At first glance it
seems that this finding is counterintuitive, as it is believed
background warming has strengthened land-atmosphere feedbacks (Dirmeyer,
Jin, Singh & Yan, 2013). It is shown by a closer look, however, that
detrending strengthens the correlation between annual precipitation and
mean spring-summer temperature, as well as maximum, which confirms the
strengthening of land-atmosphere feedbacks. The land-atmosphere feedback
effects that are activated in the warm season are overwhelmed by the
more pronounced warming rate of winters, as a result of anthropogenic
background warming, at the annual scale. Nevertheless increasing
temperature trends increases the probability of dry and hot extremes.
Temporal trends in dry-hot extremes
Alizadeh et al. used return
period as a statistical measure of the severity and likelihood of an
extreme event. The expected recurrence of a phenomenon is signified by
return period (Sadegh et al.,
2018); e.g., a 25-year event is expected to occur once in 25 years, on
average, which is associated with the exceedance probability of 0.04
(nonexceedance probability of 0.96). For univariate extremes, the
definition is intuitive, such as dryness. The concept is complex,
however, for multivariate cases (Corbella & Stretch, 2012). In this
study the AND hazard scenario was used, which determines the probability
(or frequency) of a compound dry-hot event, i.e., drier than a threshold
AND hotter than a threshold event (Grӓler et
al., 2013). The empirical
copula was used and the entire 122 years of the record to estimate the
joint exceedance probabilities of dryness and heat excess. The annual
precipitation and mean annual temperature was focused on in this paper.
Mean annual temperature was selected to include winter temperature,
which, together with spring, is warming at a higher rate compared to
other seasons (Mello, Richmond & Yohe, 2014). There are important
environmental implications associated with winter temperatures that
range from snowmelt to the availability of water to phenology and the
health of wildlife. Moreover, an increase in mean annual temperature is
associated with a pronounced likelihood of extreme heat events
(Diffenbaugh et al., 2017).
There has been a significant increase in the frequency of more than
25-year compound dry-hot extremes (joint return period levels that
exceed 25 years) over the last 3 quarter-century periods. While most of
the climate divisions across CONUS in the period 1943-1967 observed only
1 more than 25-year compound dry-hot extreme (as expected per the
definition of such an event), and some climate divisions not observing
any this slightly increased to 1 to 3 bivariate events in 1968-1992
for almost all climate divisions in CONUS.
However, there is a spike in the number of >25-year compound
dry-hot extremes in the most recent period (1993-2017), with several
climate divisions observing more than 5 such compound events. The
increase is most pronounced for the Pacific Northwest, southern portions
of the Southeast, Florida, and portions of the Northeast. This
escalation in the frequency of dry-hot extremes extends beyond the
randomness of climate phenomena that is expected. A statistically
significant trend at the 5% level for the western CONUS, Florida, the
eastern portion of the Northeast, as well as some climate divisions in
Michigan, Minnesota, Mississippi, and Alabama, is shown by the
non-parametric Mann-Kendall trend analysis of the return period level of
compound events over the past 122 years. According to Alizadeh et
al., similar inferences about
more frequent compound dry-hot extremes could be made for >50-year and
>75-year events. Multiple >75-year compound events are observed in the
coastal Pacific, Northwest, inland Southern California, Florida, Maine,
and several climate divisions in Texas, which point to the
intensification of compound dry-hot extremes over many portions of CONUS
with significant social-environmental repercussions, such as causing
very large wildfires (Abatzoglou & Williams, 2016).
These results show an increasing frequency of concurrence of
precipitation and temperature extremes over the globe and CONUS,
respectively, which accords with the findings of Hao et al., (Hao,
Kouchak & Phillips, 2013) and Mazdiyasni & Kouchak, (Mazdiyasni, 2015).
In this study the compound the spatial distribution of compound
extremes, however, is not in complete agreement with that of Mazdiyasni
& Kouchak (Mazdiyasni & Kouchak, 2015), especially in the case of
California and the Pacific Northwest. This discrepancy results from
differences in the definition of compound events, as well as differences
in the study period. In this study the definition of compound events as
years when there is <0.04 exceedance of being dry AND hot (>25-year
return level), whereas they use meteorological drought and various
definitions of heatwaves as compound events. Also, the study of
Mazdiyasni & Kouchak spans 1960-2010, whereas this study spans
1896-2017. Significant information on the frequency of compound dry-hot
extremes can be added by this longer time period, as it includes the
megadrought of the 1930s (discussed in the next section).
Spatial trends in compound dry-hot extremes
The analysis of Alizadeh et al.
points to a substantial increase in the number of climate divisions
where the were >25-year compound extremes after the 1950s across all
climate regions in the CONUS. In many regions if a longer record is used
(1896-2017) this increasing trend is, however, not present.
There is, more specifically, no
increasing trend observed in the number of climate divisions that
observe >25-year compound dry-hot extremes for the Great Plains,
Midwest, and Southeast, and to some extent, the Northeast. There is,
however, an interesting shift in the dominant driver for these compound
events. A long, severe dry event that engulfed ⅔ of CONUS in the 1930s
was the dominating driver of the joint probability of compound dry-hot
extremes. The infamous dust storms of the Southern Great Plains were
contributed by this drought (Shubert et
al., 2014). Precipitation
deficit and an excess of heat contributed to the compound events across
many climate regions in the mid-2000s, and since 2010, hotter years
became the main driver of the compound events across all climate
regions. This observation accords with the findings Mo & Lettenmaier (Mo
& Lettenmaier, 2015), who reported flash droughts driven by heatwaves
have displayed an increasing trend across CONUS since 2011. It is
implied by this that the dominant triggering driver of the
land-atmosphere feedback has shifted from dryness in the earlier half of
the study to excess heat in recent decade(s).
The number of climate divisions over the entire CONUS with >25-, >50-,
>75-year events compound dry-hot extremes has shown a trend that is
increasing, with >75-yer events having the highest rate of increase
(i.e., longer slope of linear regression). It is also confirmed by these
results that the shift in the main driver of the compound extreme events
from dry years in the 1930s to hot years in recent decade(s). The
concurrence of droughts and heatwaves, and, in general terms, dry and
hot years, over the past 3-6 decades, has been focussed in by many
compound event studies. According to Alizadeh et
al., climate analysis studies
should use longer time series in order detect low frequency climate
cycles (Overpeck, 2013). They argued that the literature might
underestimate the risk of compound dry-hot extremes by not accounting
for longer climate cycles and events of lower frequency, such as the
drought in the 1930s. While both megadrought (Cook et
al., 2016) and megaheatwaves
(Dole et al., 2011) can
result from internal stochastic – not forced – variability of the
atmosphere, their probability of occurrence (Steiger et
al., 2019) and, most
importantly, their occurrence (Sarhadi et
al., 2018), has been
increased considerably by anthropogenic emissions.
The accumulative area (km2) affected by compound dry-hot
years also shows an increasing trend at the 10% level that is
statistically significant as determined by the nonparametric
Mann-Kendall trend analysis. The highest increase rate (slope of linear
regression of cumulative impacted area as a function of time) is
associated with the Southeast, Southwest and Northeast, respectively.
However, this does not account for the total area of each climate
region, and care is advised when interpreting these results for the
purpose of comparison. Also, the area that is affected by >25-year hot
years is also associated with an increasing trend across all of the
climate regions, which is determined to be nonsignificant at the 10%
level. The cumulative area where 25-year dry years are observed is,
however, not associated with an increasing or decreasing trend.
It was revealed by further analysis that the cumulative distribution of
the percent of CONUS that were observing >25-year compound dry-hot years
for 1993-2017 (the past period of 25 years) diverges from that of
1896-1920 (the first period of 25 years). This divergence is also
visible for >25-year hot years, though between the periods 1896-1920 and
1993-2017 it is less marked. Moreover, for the Kolmogorov-Smirnov,
Cramér-von Mises, and Anderson-Darling tests all point to shifts that
are statistically significant in the cumulative distributions in the
percent of CONUS that observed >25-yeaar compound hot-dry and univariate
hot years between 1993 and 2017 and 1896 and 1920, which correspond to
the last and first years of this study. This distribution for >25-year
dry years does, however, not differ statistically between the 2 periods
at the 5% (and the 10%) level using the Kolmogorov-Smirnov and
Cramér-von Mises test, though their significant divergence is pointed to
by the Anderson-Darling test. In this study these tests were repeated
for different 25-year periods compared to 1993-2017; generally, the
results pointed to significant changes in cumulative distribution of the
percent of CONUS affected by >25-year compound hot-dry extremes, with
the exception of the 1918-1942 period) and more than 25-year hot years,
though do not generally identify significant changes in distributions of
>25-year dry years. Rather, if the 2 periods 1896-1956 and 1957-2017 are
used (61-year periods), similar results are observed.
Spatial homogeneity of dry-hot extremes
Analysis of the homogeneity of the area that is affected by compound
dry-hot extremes is also important. Large compound events that are
spatially homogeneous can endanger natural and built system services
(Fischer, Beyerle & Knutti, 2013). For natural systems, heterogeneous
habitats that are connected are resilient to synchronous and large-scale
populations of aquatic species and collapse of ecosystems. Fragmentation
of this connectedness by homogeneous compound dry-hot extremes and
result in population collapse. Homogeneous compound extremes, in the
context of built systems, can damage harvests across a wide range of
agricultural lands and rapidly deplete federal and local relief
resources.
This study assess the connectedness of climate systems that experience >
25-year compound dry-hot extremes. The spatial correlation was
calculated in terms of area that is impacted (km2) through
Moran’s I as a proxy for spatial homogeneity for compound dry-hot as
well as univariate dry and univariate hot extremes for each year. The
results of the study show that spatial homogeneity of >25-year dry years
is associated with a nominal slope that fluctuates between negative and
positive values for different climate regions as well as the entire
CONUS over the past 122 years. An increasing trend with linear slope of
Moran’s I that ranges between 0,04 and 0.07 across various regions is
shown by the spatial homogeneity of about >25-year hot years. Similarly,
>25-year compound dry-hot extremes are also growing homogeneously with a
slope of linear regression of Moran’s I ranging from 0.1 to 0.18 across
different regions. Homogeneous enlargement of compound events is steeper
than each of the drivers alone, with the largest differences being
observed in the Southwest (0.18 versus 0.02). Moran’s I analysis was
performed on less (>5-year) and more (>75-year) intense extreme events,
in order to investigate the potential impact of the threshold of extreme
events (>25-year) on the observed connectivity trend (Western, Blöschl &
Grayson, 2001). Further, the cumulative distribution of annual Moran’s I
for >25-year compound dry-hot years between 1896 and 1956, and 1957 and
2017, is determined to be different, statistically, based on the
Kolmogorov-Smirnov, Cramér-von Mises, and Anderson-Darling tests at the
5% level. These tests are also applied to the distribution of Moran‘s I
for various 25-years periods.
The homogenous spatial growth of >25-year compound dry-hot years shows a
slope that is even steeper if the past 50 years alone are analysed,
which is driven mainly by the homogeneous enlargement of hot years. For
different regions the slope of Moran’s I for compound extreme ranges
between and 0.1 and 0.6 and 0.7 for the entire CONUS. Conversely, not
much change is exhibited in dry years in terms of spatial homogeneity.
In this period, though the growth rate (slope of linear regression to
Moran’s I) for the compound events and the univariate hot extremes for
the Northwest, Northern Great Plains, and Midwest are rather similar
(slightly higher for compound events) the increase in homogeneity for
compound events over the remainder of the CONUS occurs at a much higher
rate than the univariate hot extremes increase.
Discussion
Persistent anomalies in the large scale circulation are generally known
to initiate drought and heatwave events and their co-occurrence;
land-atmosphere feedbacks can, however, also intensify and propagate
those anomalous climate events (Schumacher et
al., 2019). E.g.,
megaheatwaves are generally preceded by persistent anticyclones, which
enable cloud free conditions and advection of hot air (Schumacher et
al., 2019), but heatwaves are
intensified by drier soils by partitioning the incoming solar radiation
into heat that is more sensible and less latent heat. It is noted that
natural atmospheric variability can generate megaheatwaves even with
land-atmosphere feedbacks (Dole et
al., 2011). Land-atmosphere
feedbacks, however, increase the probability of heatwaves occurring
(Fischer, 2014). The probability of the Russian megaheatwave event in
2010, e.g., increased 13-fold as a result of the self-intensification
feedback of drought and heatwave (Hauser, Orth & Seneviratni, 2016).
Evaporation decreases as does partitioning of solar radiation into
latent heat, with a lack of soil moisture; therefore, a larger fraction
of the incoming solar radiation is translated into sensible heat, which,
in turn, warms the environment (Fischer et
al., 2007). Soils that are
desiccated contribute to increase in temperature, heat entrainment, and
deepening of the atmospheric boundary layer. In turn, the latter
increases the evaporative demand and desiccates soils further and
increases the temperature. The formation of clouds is inhibited by the
cycle of drying and warming and, in turn, restrains local convective
precipitation, which intensifies the drought still further (Fischer et
al., 2007).
Self-propagation is a mechanism that has been explored less as a
mechanism of land-atmosphere feedback (Fischer et
al., 2007). Atmospheric
moisture deficit and heat can propagate from a single location to
locations downwind, in a Lagrangian perspective (Herrera-Estrada et
al., 2019). Though heat
advection and its impact on the formation and expansion of heatwaves
have been explored in the literature, especially in the cases of the
European megaheatwave in 2003 and the Russian megaheatwave in 2010
(Miralles et al., 2014),
terrestrially sourced advection of atmospheric moisture has been
explored in much less detail, but it is receiving more attention in the
recent literature (Herrera-Estrada et
al., 2019). The concept of
“teleconnected land-atmosphere feedbacks” has been promoted by
intracontinental transport of moisture that has been sourced
terrestrially (Miralles, Gentine, Seneviratni & Teuling, 2019). It is
believed that these teleconnected land-atmosphere feedbacks help
propagate droughts to neighbouring regions, though this concept is still
in its infancy (Miralles, Gentine, Seneviratni & Teuling, 2019;
Herrera-Estrada et al.,
2019). For regions that depend on precipitation that is sourced
terrestrially, which includes large parts of North America, the
propagation of droughts is more important (van der Ent et
al., 2010). It is shown by
the analysis of Alizadeh et al.
that compound dry-hot extremes have enlarged homogeneously, i.e., areas
that have been impacted are increasingly becoming connected, which
points to the propagation of atmospheric moisture deficit AND heat from
a region to its neighbouring regions. Significant natural and societal
repercussions can result from spatial growth, which is connected, of
compound dry-hot events. The summer drought of 2010 and heatwave in
Russia that decreased crop production by 25%, caused more than 500
wildfires that burned more than 1 million hectares, and induced economic
loss that was estimated to be 15 billion USD, is an example of a
spatially large and severe compound extreme (van der Ent et
al., 2010).
It is sown by the results of this study that the frequency of compound
dry-hot extremes in CONUS has increased substantially over the past 50
years, though this trend is less pronounced if a longer period analysis
is used (1896-2017). Background warming that result from anthropogenic
emissions has strengthened, caused by earlier start of, and, extended
the spatial impact of land-atmosphere feedbacks in North America, though
anomalous synoptic circulation patterns are recognised for initiation of
compound dry-hot events (Dirmeyer, Jin, Singh & Yan, 2013). It was
reported by Alizadeh et al.
that there is a shift in the dominant driver of compound dry-hot
extremes from precipitation deficit in the 1930s to excess heat in
recent decade(s). I.e., there has been a change in dominant driver that
triggers the land-atmosphere feedbacks from meteorological drought to
excess heat. This is similar in concept to the precipitation
deficit-driven and heatwave-driven flash drought categorisation of Mo &
Lettenmaier (Mo & Lettenmaier, 2015; Mo & Lettenmaier, 2016), in spite
of temporal scale differences. It was shown by Mo & Lettenmaier (Mo &
Lettenmaier, 2015) that the frequency of flash droughts that are driven
by heatwaves was associated with a trend that has been decreasing over
the last century, which rebounded after 2011, though flash droughts of
all categories are shown to have increased in frequency around the globe
over the last century. This is in agreement with the argument of
Alizadeh et al. of the
changing nature of the dominant driver of compound dry-hot events in the
recent decade, i.e., from precipitation deficit to an excess of heat.
Further, anthropogenic emissions have enhanced significantly the
probability of concurrent drought and heat waves, and aggressive
emissions reduction is the only strategy that can mitigate the risks
associated with their increasing frequency (Sarhadi et
al., 2018). Last there is no
significant increasing trend in the frequency of dry years, though there
are no notable variations over the different regions of CONUS; however,
univariate hot years are becoming more frequent as well as more intense.
It has been argued by Alizadeh et
al. that the recent literature may underestimate the risks of dry
and hot episodes, as they only study the post-1950s period with no
recourse to the meteorological drought of the 1930s that engulfed almost
⅔ of CONUS for almost a decade. Alizadeh et
al. argue that if
meteorological droughts of the length and severity that were observed in
the 1930s occur during the hot years that are increasingly common in
recent decades due to global warming, their concurrence can have
devastating impacts (Mueller & Seneviratni, 2012; Overpeck, 2013;
Diffenbaugh & Ashfaq, 2010). It has been shown by the recent literature
that no major region in the U.S. is immune to the multi-decadal
continental-scale megadroughts that occurred in the 12th and
13th centuries (Cook et
al., 2014), and their return
has been markedly increased by global warming (Steiger et
al., 2019). Moreover, water
demand is increased by a hotter climate (Das et
al., 2011), concurrence of
which, with dry years, would strain social, built and natural systems
(Williams et al., 2013) and
might push them to unprecedented states (van den Pol et
al., 2017). The results of
this study contribute to a deeper understanding of the spatiotemporal
patterns of compound events to help with reliable risk projections in
the context of climate change. The consequences of increased frequency,
intensity and spatial homogeneity of climate extremes for compound
events with multiple drivers are far graver than the effect of each
driver individually (Zscheischler et
al., 2018), and risk
assessment frameworks need to consider the compounding effects of
multiple extremes rather than addressing a single driver at a time
within the traditional univariate framework.
Alizadeh, M. R., et al. (2020). "A century of observations reveals
increasing likelihood of continental-scale compound dry-hot extremes."
Science Advances 6(39): eaaz4571.
|
|
|||||||||||||
|
||||||||||||||
| Author: M.H.Monroe Email: admin@austhrutime.com Sources & Further reading | ||||||||||||||