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IFS Documentation
front page
Table of contents
Chapter 1. Introduction
Chapter 2. The kinematic part of the
energy balance equation
Chapter 3. Parametrization of source terms and the energy balance
in a growing wind sea
Chapter 4. An optimal interpolation scheme for assimilating altimeter data
into the WAM model
Chapter 5 Numerical scheme
Chapter 6 The WAM-model software
Chapter 7 Wind-wave interaction at ECMWF
REFERENCES
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In this final section we briefly describe how wave forecasts are validated
and the way we apply wave forecasting at ECMWF .
Figure 7.1 Standard deviation of wave height error of day 1, 3, 5,
7 and day 10 wave forecast. Here, the wave forecast is validated against
the wave analysis, and the period is August 1995 until January 2001.
An important task of any weather centre is the verification of the forecast.
We routinely verify analysed and forecast wave products against buoy data,
we verify forecast wave height against the analysis. An example of forecast
validation over the Northern and the Southern Hemisphere is given in Fig. 7.1 . A more detailed discussion
of the quality of the ECMWF wave forecast is given by Janssen et al.
(1997, 2000). Furthermore, we have been validating extensively the quality
of wave products from Altimeter and SAR from ERS1/2 and will do so from
ENVISAT which will be launched in the middle of 2001. An account of this
work may be found in Hansen
and Günther (1992), Janssen
et al. (1997a) and Janssen (2000).
Following the work of Janssen
(1982, 1989, 1991) on the feedback of ocean waves on the airflow we have
made a dedicated effort towards an integrated forecasting system for our
geosphere. Ultimately, it is expected to have a model consisting of the
atmosphere and the oceans where the ocean waves are the agent that transfer
energy and momentum oss the interface in accordance with the energy balance
equation. This role of the ocean waves is illustrated in Figs. 3.3 and 3.4 . On the one hand ocean waves receive
momentum and energy from the atmosphere through wind input (hence they control
to a large extent the drag of airflow over the oceans), while on the other
hand, through wave breaking, the ocean waves transfer energy and momentum
to the ocean, thereby feeding the turbulent and large scale motions of the
oceans. Ocean waves are in general not in an equilibrium state determined
by a balance of the three source functions, because advection and unsteadiness
are important as well. Typically, of the amount of energy gained by wind
about 90% is lost locally to the ocean by wave breaking, while the remaining
10% is either advected away or is spent in local growth.
Presently, we have taken the first step by coupling the IFS atmospheric
model with the WAM model in a two-way interaction mode. This coupled model
provides the 10 day weather and wave forecast since the 29th of June 1998.
Here, every coupling time step surface winds are passed through the WAVEMDL
interface towards the wave model, while the Charnock parameter as determined
by the sea state (cf. Eq. (3.11)
) is given to the atmospheric model and is used to estimate the slowing
down of the surface winds during the next coupling time step. An overview
of results is given by Janssen et al. (2001) who show that
the introduction of two-way interaction gives improvements in the prediction
of surface winds and waves. As a next step ECMWF is developing a coupled
atmosphere, ocean-wave, ocean-circulation model. This coupled model will
be used in seasonal forecasting and monthly forecasting in the near future.
Finally, since December 1992 ECMWF is providing estimates of forecast error
by running an ensemble prediction system. With the introduction of the coupled
wind-wave prediction scheme in June 1998, ensemble wave products became
available as well. This new product may provide useful information on the
uncertainty in the prediction of ship routes (Hoffschildt et al., 1999).
This concludes our discussion of the software aspects of the ECMWF version
of the third generation WAM model. Although the software description only
comprises a small part of this document, it should be realised that the
greater part of the efforts of the WAM group was devoted to the development
of the WAM model code. One can imagine how the strong involvement of a number
of WAM people in the wave model development has led to heated debates on
aspects of the model design during the yearly WAM meetings. However, all
this has paid off. The present cycle 4 version of the WAM model is a beautiful
looking fortran code. It combines efficiency with flexibility. It has been
installed at over 200 institutes world wide and is used for research and
operational applications. Furthermore, at ECMWF we have seen a steady evolution
of the WAM software towards a better integration in the ECMWF software system
and towards a tight coupling with the atmospheric model.
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