Climate change impacts and vulnerability in Europe 2016

Introduction
• attribution of an observed impact to anthropogenic
climate change (i.e. identifying an observed change
in regional climate as the main cause of an observed
regional impact and also identifying anthropogenic
greenhouse gas emissions as the main cause of the
observed change in regional climate);
• model-based projection of a climate variable into the
future;
• model-based projection of a climate-sensitive impact
variable into the future;
• identification of needs for adaptation.
One type of statement that is not fully reflected in this
list is model-based assessments of past changes in a
climate or impact variable (e.g. climate re-analysis).
Key messages are formulated so that it is clear what
type of statement they make. For the sake of clarity,
the combination of different types of statements in a
single message is generally avoided. In this context,
it is also important to carefully distinguish between
the three different types of attribution statements
(Hansen and Stone, 2015). Note that the type of
statement supported by a particular dataset may
depend on the spatial scale. For example, in the same
dataset, a significant climate trend may be detectable
at the continental scale (where year-to-year variability
is low) but not in each region (where year-to-year
variability is higher and regional factors may be
important).
Different types of statements are subject to different
sources of uncertainty (see Figure 1.4). The sources
of uncertainty generally increase from observations
and trends to attributions and projections, and from
climate variables to climate impacts and possibly to
adaptation needs. The term 'cascade of uncertainties' is
used to represent that the magnitude of uncertainties
in projections increases along the impact chain from
greenhouse gas emissions to radiative forcing, global
and regional climate change, and further to regional
climate change impacts (see, for example, Ahmad et al.,
2007).
Appropriate choice of the level of precision
The following levels of precision (or quantification) are
distinguished in key messages (ordered here from least
to most precise):
1. existence of effect (but the direction is ambiguous
or unpredictable);
Figure 1.4
Influence of key sources of uncertainty on different types of statement
Climate observation
Impact observation
Measurement errors
Aggregation errors
Climate trend
Impact trend
Natural variability
Model limitations
Emission trajectories
Climate projection
Climate attribution
Impact attribution
Non-climatic factors
Impact projection
Societal preferences
Adaptation needs
Note:
Source:
This graphic shows how various sources of uncertainty (in orange) influence different types of statements (in black), with those on the
left related to the past and those on the right related to the future.
EEA.
46 Climate change, impacts and vulnerability in Europe 2016 | An indicator-based report