Options for Improving Climate Modeling to Assist Water Utility ...

Water Utility Climate Alliance White Paper
Options for Improving Climate Modeling to Assist Water Utility Planning for Climate Change
evidence from which he gains confidence in climate model projections: “Models are based on
physical principles; Models reproduce the mean state and variability in many variables; Models
reproduce observed global trends in many variables; Models are tested on more distant past
climate states; Multiple models agree on large scales; Projections from newer models are
(broadly) consistent with projections from older models; We can understand the results in terms
of simpler models and theoretical frameworks.” We mention these here only to emphasize that
model evaluation is more than simply a matter of statistical accuracy. A specific discussion of
the ability to simulate past climate and trends is discussed below.
Over time, there will be increasing observations on the effect GHGs are having on the Earth’s
climate. Thus, as time goes on, there will be more information to use to assess models’
performance in a changing climate.
3.1.7 Which processes are represented in the models?
Table 3.2 lists a typical breakdown of the main processes and parameterizations included in
AOGCMs that are important for generating output relevant to water quality and quantity. As an
example, the first row presents the convective parameterization, which computes the effect of the
small-scale thunderstorms averaged over the grid cell. The convective precipitation it generates
is particularly important for warm season precipitation totals and intense precipitation events.
The heating of the atmosphere generated by convective precipitation is the main driver of the
tropical atmospheric circulations that have global influence. Among the limitations include a
poor simulation of the diurnal timing of precipitation (it tends to happen too early in the day),
and the underestimation of intense rain events.
In reality, the processes listed in Table 3.2 are intricately connected, and models are evolving to
a more unified view of parameterization. This list of parameterizations is not complete, as some
processes of less relevance to water resources (such as gravity wave parameterization) are not
included. ESMs include many additional processes (such as vegetation models, soil carbon
processes, and surface ocean carbon uptake) that are not discussed here.
The strengths and limitations of the hydrologic processes in these models may be of particular
interest to water utilities. GCMs typically include a hydrology submodel within their land surface
component to account for the fate and transport of water (including solid and gas forms), but this
output is rarely used directly for water resource applications. Typically, those studying climate
change impacts on water resources use meteorological variables, such as temperature and
precipitation, as inputs into hydrology models to estimate runoff (see Chapter 5). While the
hydrology submodel in GCMs can be quite sophisticated in terms of the processes included, the
large spatial scale of the model grid cell does not resolve critical hydrological phenomena,
particularly in mountainous terrain. In addition, the climate biases of the GCM can also be
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