Use and Application of EPS at the Swedish Meteorological and Hydrological Institute
By Ove Åkesson
SMHI
S-601 76 Norrköping
Sweden
At SMHI ensemble forecasts from ECMWF have been used for a number of years and some
applications have being developed. There is a gradually rising interest in EPS and its
potential by users and in this abstract a short overview is presented with some examples.
Plumes of temperature and precipitation
Plumes of 2m-temperature and precipitation are plotted and used mainly by forecasters for
predictions to the energy sector users but also for agriculture purposes (Fig 1). Median values
of temperature at each time step and accumulated precipitation since the last time step are also
indicated in the figure together with the total amount of precipitation throughout the 10-day
period. Median values are usually much lower than mean values but median values are
preferred by the forecasters in order to better differentiate between dry and wet cases. The
total amount will however be too low in general using medians.
Fig. 1. Plumes of 2m
temp (top) and 24 hrs ack. precipitation (bottom) for one location (Ritsem) based on 50 EPS
forecasts (thin solid) and the ordinary T319 forecats (thick dashed) from 24 Jan. 2000 with
confidence index based on 700 hPa geopotential height where MS= Very high confidence, S=
High confidence, N= Normal confidence, O= Low confidence, MO= Very low confidence,
that relates the uncertainty of the past 14 days statistics of all grid point values between 55N
and 70 N from these fields. Below the indices there are median values indicated for
temperature and precipitation respectively. For precipitation the total median amount for the
whole time period is indicated.
EPS- grams
An alternative way of presenting plumes is by the EPS- grams (Fig 2), where mean and
extreme values are indicated. The T319 forecasts is indicated by a dashed line. When high or
extreme values are predicted the risk percentage is indicated at the risk level, which can be
altered. For extreme events the ensemble member number is indicated above/below the
extreme value and the forecaster can then display that member with isobars, temperature and
precipitation if he or she wants to examine that member closer.
Fig. 2. EPSGRAM showing temperature at 2m, precipitation amount/12h, total cloud amount,
wind speed and wind direction of T319 (dashed) and ensemble median (solid). The extreme
interval (thin solid vertical line) and the 66% probability interval (thick solid vertical line)
are indicated every 12 hours.
Confidence index
At the +120, +144 and 168 hr time steps respectively there is a confidence index with five
classes plotted as capital letters above the plumes indicating MUCH BELOW (MO), BELOW
(O), NORMAL (N), ABOVE NORMAL (S) and MUCH ABOVE NORMAL (MS)
CONFIDENCE. It is based on the 700 hPa geopotential height forecast and its averaged
spread during the past 15 days over a rather large area over easter Atlantic and northern
Europe between latitudes 50N and 70N in order to get a representative spread for the season.
This spread is divided into equally likely quintiles and the latest forecast for a point is
checked for class and the index then plotted on the plume chart. It can be argued, however,
that 700 hPa height sometimes will have a low correlation with temperature near the ground
level or with precipitation amount in particular. Ideally the spread of 2m-temperature and
precipitation should be compiled separately using statistics from the same parameter for each
season and also for each station since the local influence could be rather large.
Probabilities
Probabilities are generated in the medium range for some customers but there is a certain
resistance using probabilities among end users which might be remedied by giving them
information of the increased predictability and potential from the use of probabilities
compared to deterministic forecast values only.
There is still a need for correction of the somewhat too narrow spread with some overconfidence but this has improved over the years as more ensemble members have been
included and with higher resolution models and other advances. We have tested calibration of
precipitation probability forecasts in the past but this is not carried out on a regular basis.
Use of EPS mean of temperature at 2 metres
Verification shows that blending a number of individual temperature forecasts, both DMO
and from different methods such as adaptive temperature forecasts, usually gives a better
result than the individual forecast from each model or method. Weights are given to the
individual forecasts based on recent verification results and can be be changed easily. A slight
further improvement can be achieved by reducing the blended temperature at each station by
part of the bias experienced during the last 5 days. For early forecasts out to D+2 the EPS
mean has only a minor influence on the temperatures but for longer forecast ranges the
influence increases and from D+4 onwards be the major contributor to the final forecast
values.
Extreme weather products
In order to view the extremes one can either pick out the most extreme member, which is the
tubing concept. Another way would be to pick out the most extreme (highest, lowest and
median) values respectively at each grid point and display the information on charts (Fig 3).
Overlaid on each chart there is also a representative pressure field. This is selected by
choosing the ensemble member which has the highest number of extreme grid point values at
each time step. Therefore sometimes there may be several ensemble members whose pressure
distributions are nearly equally representative. In this way precipitation amount and snowfall
since last time step, 2mTemp and wind speed are displayed at 12 hourly intervals to the
forecasters.
Fig. 3. Highest (left), median (middle) and lowest (right) extreme at any grid point of
precipitation (top) and 2m temp (bottom) together with isobars of a representative ensemble
member. See text for details.