MAGIC
Introduction
Humidity is a highly variable parameter in atmospheric
processes and it plays a crucial role in atmospheric motions on a wide
range of scales in space and time. Limitations in humidity observation
accuracy, as well as temporal and spatial coverage, often lead to
problems in numerical weather prediction, in particular that of clouds
and precipitation. Due to these limitations, the verification of humidity
simulations in operational weather forecasts and climate modeling are also
difficult.
The emerging ground-based Global Positioning
System (GPS) networks present appealing opportunities for an improved
humidity observation source that can help resolve these difficulties. Estimation
of the integrated water vapor (IWV) in the atmosphere from the anomalous
delays in the radio signals transmitted by the GPS satellites has an accuracy
that is at least comparable to that of radiosondes and microwave radiometers,
which are presently the primary source of humidity data. In addition, ground-based
GPS receivers are portable and economic, providing continuous measurements
which are not affected by rain and clouds.
The objective of the MAGIC project is to develop
and test the capacity for meteorological organisations to benefit from
this new data source, in accord with the CEO objectives of increasing the
user base for Earth Observation data.
There are at least two potential benefits from
the GPS observations:
-
an independent data set for validating forecast and climate models, and
-
enhanced forecasting systems which make use of the extra humidity information.
Three focussed studies of testing and assimilation
are proposed for models at three different spatial and temporal scales:
-
a regional European
scale weather prediction model, HIRLAM,
-
a high resolution
mesoscale weather prediction model for Catalonia, Spain,
-
a European scale
climate model, HIRHAM.
HIRLAM (HIgh Resolution Limited-Area Model),
is developed in an international cooperation between weather services in
Denmark, Finland, France, Iceland, Ireland, the Netherlands, Norway, Spain
and Sweden. The Danish Meteorological Institute, which is responsible for
operational weather prediction in Denmark and participates in the development
and improvement of the HIRLAM system, will participate as a project partner.
The current analysis scheme is based on the Optimum Interpolation (OI)
method. A preliminary study has revealed some weaknesses in the HIRLAM
system where the forecasts tend to become wetter as the forecast length
increases. Independent data such as the GPS IWV measurements are needed
in order to improve model formulation and parameter tuning. In addition,
the GPS data are needed to augment the knowledge of the humidity field
by being directly incorporated into the model. However, in the current
OI scheme, the GPS data cannot influence the weather forecasts directly.
Therefore, a necessary and innovative component of this project is the
development of the next generation data assimilation system for HIRLAM.
With an enhanced data assimilation system, all HIRLAM members will be able
to improve their services.
The HIRHAM model (HIRLAM dynamics + the Hamburg
physics package) has been used at DMI to study the regional climate changes.
One of the important aspects in developing the model is the validation.
As water vapor is one of the key elements determining the climate, it is
essential to simulate it correctly in the climate model. The information
provided by the GPS data will help to identify weaknesses in the climate
model as it did for the forecast model.
There are two agencies in Spain interested in the use of GPS integrated
water vapor measurements. One is the Instituto Nacional de Meteorologia
(INM) , which has institutional responsibility for the meteorological activities
in Spain, and is a co-developper of HIRLAM in cooperation with their equivalents
in other European countries. Thus the INM has a vested interest in the
HIRLAM assimilation system to be developed by the HIRLAM member participating
in MAGIC. The other agency, with a smaller geographical scope, is
the Servei de Meteorologia de Catalunya (SMC). This organisation
is concerned with the prediction of catastrophic rainfall events for the
Catalonian region, due to storm systems unique to the western Mediterranean
that are difficult to predict with the operational (larger scale)
numerical weather prediction models. Such storm events are often associated
with flash floods with loss of property, and in some cases, human casualties.
The SMC is a user of the outputs from a high resolution mesoscale model
developed for Catalonia and the surrounding regions, an upgrade of the
Mesoscale Atmospheric Simulation System (MASS). While this local model
has had some success in predicting precipitation, key humidity data are
required to verify the derived humidity fields. For increasing the accuracy
of the precipitation estimates, a denser network of water vapor measurements
are required than are provided by the conventional global data sources.
GPS IWV measurements respond to this need, and also offer a high temporal
resolution that ulimately will be of benefit in predicting these rapidly
developing storm systems. Assimilation tests for incorporating GPS IWV
data into the MASS system or an equivalent mesoscale modeling system for
Catalonia will be carried out in the MAGIC project.
Expected Improvements for the HIRLAM and MASS numerical
weather prediction models:
-
Reduction of systematic
errors in the model forecasts
-
Improved initial
humidity fields from which forecasts are predicted
-
Improved precipitation
predictions
-
New assimilation
scheme that can exploit a wider variety of satellite data
Expected Improvements for the HIRHAM climate model:
-
Reliable validation
of predicted humidity fields
These meteorological agencies at present do not
have the expertise nor the infrastructure for retrieving these GPS measurements
for a preliminary analysis of their utility. A large number of permanent
GPS stations have been installed in Europe, and more are in the process
of being installed, to support geodetic and geodynamic research. In bringing
together the latest developments in techniques from the space geodetic
and meteorological communities, the MAGIC project will be instrumental
in making a significant advance in weather prediction and climate modeling.
This contributes directly to the objectives of the CEO programme by expanding
the customer base of this type of Earth Observation data to the meteorological
community. Through CEO enabling services and the European Wide Service
Exchange EWSE, the results of the project and example data sets suitable
for validation tests will be made available to other potential customers
and expand the use of this EO data to a larger group of meteorological
agencies and climate researchers.
Page last modified 11 November-1998
Mail to jh@acri.fr