Geography Reference
In-Depth Information
1
Introduction
The impact of climate change on society is of fundamental
importance for future planning and management. Statistics
of extreme events is considered as a part of the climate, and
their changes often have much higher impact on society than
changes in the mean climate. As the mean climate changes,
the characteristics of extremes may also change (e.g. Tren-
berth 1999; Easterling et al. 2000; Beniston and Stephenson
2004). For many impact applications and decision support
systems, extreme events are much more important than the
mean climate (e.g. Mearns et al. 1984; WISE 1999). Changes
in extremes may be due to changes in the mean (Wigley
1985), changes in the variance (Katz and Brown 1992), or
a combination of both factors (e.g. Brown and Katz 1995;
Beniston 2004).
Extreme climate events can be defined as events that occur
with extraordinary low frequency during a certain period of
time (rarity), events with high magnitude (intensity) or dura-
tion, and events causing sizeable impacts such as direct dam-
ages to assets, cultural heritage, ecosystem service and loss
of human lives. According to The Intergovernmental Panel
on Climate Change (IPCC) (IPCC 2001, p. 790), “An ex-
treme weather event is an event that is rare within its statisti-
cal reference distribution at a particular place. Definitions of
'rare' vary, but an extreme weather event would normally be
as rare as or rarer than the 10th or 90th percentile. By defini-
tion, the characteristics of what is called extreme weather
may vary from place to place. An extreme climate event is an
average of a number of weather events over a certain period
of time, an average which itself is extreme (e.g. rainfall over
a season).” This definition has also been used in the fourth
IPCC report published in 2007 (IPCC 2007).
Indices have been developed to measure the degree of
exceedance of specific thresholds (which define the rarity
of such an event) for maxima/minima during specific time-
periods (Jones et al. 1999). Examples are the number of very
warm and very cold days for the time of year, the number of
heavy rainfall days, and number of frost days (Frich et al.
2002). Some extremes are defined by natural thresholds,
while the majority of extremes are determined by the dataʼs
own distribution. The majority of indices relate to counts of
individual daily extremes, but a few are determined by spells
of exceptionally warm/cold temperatures or wet/dry periods
or the first/last occurrence of an event during a season (like
spring/autumn frosts, beginning/end of the summer dry sea-
son etc.). With respect to temperature and rainfall, spells of
extreme weather generally have large societal and economic
impacts. Examples of short-lived extremes that may cause
extensive damage are windstorms, hailstorms and extensive
and heavy snowfall.
Recently, there has been an international effort towards
developing a suite of standardized indices so that research-
ers around the world can calculate the indices in exactly the
same manner. This is important for detecting and monitoring
changes in the extreme climates and allows for comparison
of observations and model simulations at the global scale.
These analyses can then be combined into the regional and
global perspectives (Karl and Easterling 1999; Peterson et al.
2001; Frich et al. 2002). However, the definition of several
of the suggested indices is somewhat cumbersome and some
of the indices still exist in various forms. Consequently, dif-
ferent software may produce slightly different results. Sev-
eral EU research projects either use the indices in the Euro-
pean Climate Assessment (Klein-Tank et al. 2002a; Klein-
Tank and K￶nnen 2003) or a program developed within the
STARDEX project (STAtistical and Regional dynamical
Downscaling of EXtremes for European regions; Haylock
and Goodess (2004)). In this atlas we use the extremes in-
dices software developed within EMULATE (European and
North Atlantic daily to MULtidecadal climATE variability;
Moberg et al. (2006)).
While some of the climatic extremes are well described
by meteorological variables/indices, others may not be easily
defined with data for a single meteorological variable only.
This is true when the combined impact is involved (Pellikka
and J¦rvenp¦¦ 2003). For example, freezing rain is a special
combination of low temperature and rain that produces major
damages through ice loading on wires and structures. Other
examples are snow damage on forests (Solantie 1994) and
 
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