Decision support experiments and evaluations using seasonal to ...

The U.S. Climate Change Science Program Chapter 2
42
ary to be melted and washed away by March
rains. For the forecaster, predicting April-to-
July streamflow is difficult, particularly in
anticipating the quantity of water that is going
to “escape” before the target season begins.
Additional forecast errors in snowmelt river
basins can arise from the inability to accurately
predict the sublimation of snow (sublimation
occurs when ice or snow converts directly into
atmospheric water vapor without first passing
through the liquid state), a complex process that
is influenced by cloudiness, sequences of meteorological
conditions (wind, relative humidity
as well as temperature) affecting crust, internal
snow dynamics, and vegetation.
Some element of forecast
accuracy depends
on the variability of the
river itself. It would be
easy to incur a 100 percent
forecast error on,
for example, the San
Francisco River in Arizona,
whose observations
vary between 17
percent to more than
750 percent of average.
It would be much more
difficult to incur such
a high error on a river
such as the Stehekin
River in Washington,
where the streamflow
ranges only between 60
percent and 150 percent
of average. A user may
Figure 2.10 Mean percentages of annual precipitation that fell from April through June, 1971 to 2000
be interested in this as-
(based on 4-km PRISM climatologies). This figure was obtained from .
percent of normal error),
but most forecasters use skill scores
(e.g., correlation) that would normalize
for this effect and make the
results from these two basins more
comparable. As noted by Hartmann
et al. (2002), consumers of forecast
information may be more interested
in measures of forecast skill other
than correlations.
Figure 2.11 Recent operational National Water and Climate Center (NWCC) forecasts
of April-July 2007 streamflow volume in Birch Creek at Swift Dam near Valier, Montana,
showing daily median-forecast values of percentages of long-term average streamflow total
for summer 2007 (blue) and the long-term estimates of correlation-based forecast skill
corresponding to each day of the year. Figure obtained from the NWCC .
2.2.3.1 Skill oF current SeaSonal
hydrologic and wat e r-Supply
ForecaStS
As previously indicated, hydrologic
and streamflow forecasts that extend
to a nine-month lead time are made
for western United States rivers,
primarily during the winter and
spring, whereas in other parts of the
United States, where seasonality of
precipitation is less pronounced, the