Geoscience Reference
In-Depth Information
AR4 simulations of snow cover. Holland et al. (
2007
) investigated ten AR4 GCMs to
estimate change in the freshwater budget of the Arctic Ocean, including pan-Arctic scale
runoff, and Rawlins et al. (
2010
) used the same GCMs combined with reanalysis and
observational data in a pan-Arctic analysis of Arctic hydrological cycle intensification.
However, no basin-wise investigation and comparison of GCM results between the
TAR and AR4 has been performed for a larger set of basins within the PADB, and no
benchmark of AR4 GCM performance over such a set of basins exists for comparison with
the AR5 set of models. An evaluation of GCM projections in a hydrological context is
therefore motivated and would inform both the parameterization of land surface schemes in
GCMs, and the developers and end users of regional climate model and their results. In the
end, it would benefit anyone whose decisions are influenced by the reliability of water
change projections. Previous investigations into GCM agreement with hydro-climatic
observations, for other regions than the Arctic, have for instance revealed that GCM
projections of evapotranspiration may be more uncertain than originally thought (Mueller
et al.
2011
).
Even if projections of the atmospheric components of the Arctic hydrological cycle
(AHC) were satisfactory, it is the translation of changes in these components to water
system changes in the landscape that is central to adaptation. Spatial planning, infra-
structure dimensioning and water resources planning all depend on reliable understanding
and projection of changes to water availability, river flows, flood and drought frequencies.
Therefore, considerable efforts have been directed toward understanding the complex
changes in Arctic surface and groundwater systems in the recent decades. Several inte-
grative system assessments (e.g., V
¨
r
¨
smarty et al.
2001
; Serreze et al.
2006
; Slater et al.
2007
; Rawlins et al.
2009
,
2010
), together with numerous site-specific studies, have greatly
improved knowledge of the AHC. Nevertheless, a number of inconsistencies, gaps in
understanding and open questions still remain (Arctic-HYDRA consortium
2010
). Definite
understanding of several AHC components, and how they are linked, is still lacking.
To remediate these shortcomings, and advance the development of GCMs and our
understanding of hydro-climatic change, relevant and accessible observations have a
central role. Advances in theories, models, scenarios and projections fundamentally rely on
observational data. The importance of data and observation systems has also recently been
emphasized at intergovernmental summits (GEO
2010
) and recognized as one of five
''grand challenges'' for Earth system science and science policy over the next decade (Reid
et al.
2010
; ICSU
2010
). Constraints in the availability of data limit the ability to evaluate
projections, climate model parameterizations, and hypothesized changes and functions of
environmental systems. There is therefore a strong link between the output of GCMs,
observation systems and, in the end, the ability of society to plan for and adapt to
hydrological changes that affect industry, agriculture and water resource availability.
A primary class of environmental data required to assess AHC change is river discharge.
In addition, sediment and water chemistry data are needed to estimate the waterborne mass
fluxes of constituents in global biogeochemical cycles, such as carbon, nitrogen and
phosphorus. Besides their role in the global cycles, these elements are also directly related
to societal impacts through their links to eutrophication (Darracq et al.
2008
), aquatic
habitat and ecosystem changes (Palmer et al.
2009
), and feedbacks to climate change
(Lyon et al.
2010
). The collection of such hydrological and hydrochemical data is normally
conducted through continuous monitoring programs by various government agencies.
However, in many countries, hydrological observation systems have been in decline during
recent decades. The extent of monitoring generally peaked around 1980, after the signif-
icant
increases
in
monitoring
efforts
during
the
International
Hydrological
Decade
