Decision support experiments and evaluations using seasonal to ...

cal elements, including models, databases and
software for handling meteorological and hydrological
data, and for making, assessing and
disseminating forecasts (i.e., website structure).
Nonetheless, the RFCs themselves are regional
entities with regional concerns.
The NWS’s ESP approach warrants further
discussion. In the mid 1970s, the NWS developed
the hydrologic modeling, forecasting
and analysis system—NWS River Forecast
System (NWSRFS)—the core of which is the
Sacramento soil moisture accounting scheme
coupled to the Snow-17 temperature index snow
model, for ESP-based prediction (Anderson,
1972, 1973; Burnash et al., 1973). The ESP
approach uses a deterministic simulation of
the hydrologic state during a model spin-up
(initialization) period, leading up to the forecast
start date to estimate current hydrologic conditions,
and then uses an ensemble of historical
meteorological sequences as model inputs (e.g.,
temperature and precipitation) to simulate hydrology
in the future (or forecast period). Until
several years ago, the RFC dissemination of
ESP-based forecasts for streamflows at SI lead
times was rare, and the statistical forecasts
were the accepted standard. Now, as part of the
NWS Advanced Hydrologic Prediction Service
(AHPS) initiative, ESP forecasts are being aggressively
implemented for basins across the
United States (Figure 2.4) at lead times from
hours to SI (McEnery et al., 2005).
At the seasonal lead times, several western
RFCs use graphical forecast products for the
summer period streamflow forecasts that
convey the probabilistic uncertainty of the
forecasts. A unified web based suite of applications
that became operational in 2008 provides
forecast users with a number of avenues for
exploring the RFC water supply forecasts.
For example, Figure 2.5 shows (in clockwise
order from top left) (a) a western United States
depiction of the median water supply outlook
for the RFC forecast basins, (b) a progression
of forecasts (median and bounds) during the
water year together with flow normals and observed
flows; (c) monthly forecast distributions,
with the option to display individual forecast
ensemble members (i.e., single past years) and
also select ENSO-based categorical forecasts
(ESP subsets); and (d) various skill measures,
Decision-Support Experiments and Evaluations using Seasonal to
Interannual Forecasts and Observational Data: A Focus on Water Resources
Figure 2.4 Areas covered by the NWS Advanced Hydrologic Prediction Service
(AHPS) initiative (McEnery et al., 2005).
Figure 2.5 A graphical forecast product from the NWS River Forecast Centers,
showing a forecast of summer (April through July) period streamflow on
the Colorado River, Colorado to Arizona. These figures were obtained from
.
such as mean absolute error, for the forecasts
based on hindcast performance. Access to raw
ensemble member data is also provided from
the same website.
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