Imagine you're forecasting for a major public outdoor event
that will be taking place in and near the flood plane of a river.
You have this single value forecast
of the expected river level for the time frame of this outdoor event.
You can see that the river level is expected to peak
just below the action stage during the period of concern.
Taking this at face value would suggest
that the river will remain below the action stage.
But your experience tells you that there could be some error
in this forecast in both the peak level and the timing.
A multi value forecast, also called an ensemble forecast, can help
account for this uncertainty by showing a range of possible river levels.
Working with this series of possible forecasts,
we can derive the probabilities for different outcomes.
This information allows decision makers
to plan their actions based on the known risks.
We can see that there may be a relatively high
probability of the river level passing the action stage
and reaching an initial flood stage at this specific time.
This would cause minor impacts, such as closure of the pedestrian
and bicycle pathways.
A smaller probability may
exist for a moderate flood stage associated with greater impacts,
such as closure of access roads and public buildings.
Ensemble forecasts allow forecasters to provide a more complete picture
of a range of possibilities by incorporating forecast uncertainty.
And this allows the forecast users then to be better informed
for making decisions.
The Hydrologic Ensemble Forecast Service,
or HEFS is a part of the next generation of probabilistic
forecasting services being deployed by the National Weather Service.
The National Weather Service has deployed HEFS to fill a need
for a nationally consistent ensemble
hydrologic forecasting
by combining.
The meteorological and hydrological uncertainty.
HEFS produces a better estimate of the total uncertainty
in the streamflow forecast.
The meteorological component of HEFS
is called the Meteorological Ensemble Forecast Processor or MEFP.
In the first step of HEFS, MEFP combines a current single value forecast
with historical forecast error information to create an ensemble
of meteorological inputs or forcing data for the hydrological model.
The hydrological
model then translates the ensemble of meteorological
forcing data into an ensemble of streamflow forecasts.
This can be represented as a range of values with associated probabilities.
This is the uncertainty in the streamflow forecast generated by the meteorology.
However, if the uncertainty were only coming from the meteorology
and ensemble
streamflow forecast might not capture an adequate range of possible outcomes.
This is because the hydrology also introduces uncertainty.
We call this a lack of spread or under-dispersion.
This is why HEFS also captures uncertainty, using another component
known as the ensemble post processor or EnsPost.
EnsPost is the component of HEFS that adjusts the ensemble of raw
streamflow forecasts to account for uncertainty and correct for bias,
both of which originate from the hydrological modeling.
In this step, uncertainty arises from the different components
of the hydrological modeling,
such as the soil moisture states or the hydrological routing parameters.
The implementation of
EnsPost currently varies by location, so consult with your regional river
forecast center for information on
if and how it is used in your local HEFS forecast.
The end product of HEFS is an ensemble of bias-corrected forecast stream flows
that account for the meteorological and hydrological modeling
uncertainty.
MEFP and EnsPost, working together, serve to introduce
historically informed uncertainty to the ensemble forecast of streamflows.
By using HEFS we will be able to deliver consistent, nationally based,
probabilistic hydrological forecasting services for decision support.
HEFS helps the National Weather Service
better communicate a range of outcomes for an upcoming flood event.
So decision makers have a heads up, possibly up to ten days in advance.
By providing more complete forecast information.
HEFS supports impact-based decision making to better protect life and property
and to increase public safety.