7rsta.royalsocietypublishing.orgP h i l .T r a n s .R .S o c .A376:20160452 ........................................................
In the present study, processing errors in the input data for one ensemble member, the
HadGEM2-ES-driven member, caused the results to be invalid. Results for this member for the
HCVI are, therefore, not presented here.
(d) Freshwaterresources:run-off
Impacts on freshwater were assessed with a version of the JULES land surface model [ 24,25], a
coupled ecosystem–hydrology–surface exchange model which simulates land-atmosphere ﬂuxes
of water, energy and carbon in an internally consistent way, typically applied at global scales.
Variants of JULES form the land surface scheme of Met Ofﬁce Hadley Centre Earth System
Models [ 26,27] and have been used to assess impacts of climate change on global terrestrial
ecosystems and hydrology [ 28–30] within such models. JULES can also be used outside of the
Earth System Model (ESM), driven by meteorological outputs of other ESMs to assess impacts of
a wider range of climate projections [ 6,8]. Here we use a new, higher-resolution conﬁguration of
JULES on a global grid of 0.5° resolution [31].
It has been noted that hydrological impacts models driven by climate-change projections
from climate models tend to give more severe drying than simulated in the climate models
themselves [ 32–34]. This is largely attributed to the inclusion of plant stomatal closure in
response to elevated CO 2 in the climate model land surface schemes, which generally reduces
evapotranspiration relative to climate projections without this process and hence further increases
run-off/streamﬂow or ameliorates decreases [34]. This process is often omitted from standard
hydrological models. Plant physiological responses to CO 2 are included in the JULES model, so
our projections of changes in run-off here do account for this process.
We used each HadGEM3 simulation to drive JULES to simulate changes in run-off due to
the effects of climate change and CO 2 rise on precipitation, evaporation and transpiration. We
analysed 30 year periods centred around the year of crossing GWLs of 1.5°C and 2°C relative to
pre-industrial. We examined changes in both mean ﬂows and low ﬂows (deﬁned as the ﬂows for
the lowest 10% of time).
(e) Correctingbiasesinclimatemodeloutputandimplicationsfordefininglevelsofglobal
warming
The ClimPACT extreme weather indices, HCVI and JULES run-off simulations were all performed
using outputs from the higher-resolution HadGEM3 projections described in §2a. However, there
were some differences in how these data were applied, with different approaches to the treatment
of systematic biases in the climate model output. For the ClimPACT analysis, it was considered
important to assess changes in the raw climate model output, because this directly represents
the behaviour of the model itself. The main focus was on the changes relative to the present-
day baseline climate, deﬁned as 1981–2010, with absolute values in either the baseline or the
GWLs of 1.5°C and 2°C being only of secondary interest. For the HCVI and JULES run-off
analyses, however, it was considered important to correct for systematic biases in the climate
model output, because these can lead to unrealistic representations of the key quantities in the
present-day simulation [35]. A bias-correction methodology was, therefore, applied for these two
parts of the analysis, whereby the model output was adjusted to make it consistent with an
observed climatology [ 36]. We used a multi-segment statistical bias-correction methodology for
precipitation [37], and a modiﬁcation of this for other variables [37].
This difference in approach led to inconsistencies in the deﬁnitions of the dates of GWLs
in the two parts of the study. In the extremes analysis using raw model output, the dates of
passing GWLs were deﬁned on the basis of the global mean temperatures in the driving CMIP5