EUMETSAT GRAS SAF 2nd User Workshop June, 2003 The Role The Role of of GPS Atmosphere Profiling GPS Atmosphere Profiling in in Weather Forecasting Weather Forecasting and Atmosphere Research and Atmosphere Research Per Høeg Atmosphere Ionosphere Research Division (AIR) Danish Meteorological Institute (DMI)
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June, 2003EUMETSAT GRAS SAF 2nd User Workshop. 2 The EPS/METOP Satellite.
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Weather ForecastingWeather Forecastingand Atmosphere Researchand Atmosphere Research
Per Høeg
Atmosphere Ionosphere Research Division (AIR)Danish Meteorological Institute (DMI)
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EUMETSAT GRAS SAF 2nd User Workshop
The EPS/METOP Satellite
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EUMETSAT GRAS SAF 2nd User Workshop
The Observational Method
• The fundamental observable is the signal Doppler shift.
• Knowledge of the observational geometry results in the phase shift due to the medium along the ray path.
• The ionosphere, stratosphere and troposphere cause signal phase and amplitude changes.
Dry term Wet term Ionos. term
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101 fNCTPCPTC ew
LEO
GPS
Earth
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GRAS SAF Data Products
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EUMETSAT GRAS SAF 2nd User Workshop
Advantages of GPS Atmosphere Profiling
• Absolute measurement• The technique needs no calibration. The basics of the observation are a measurement of time.
• Global coverage• The geometry of the observation leads for one satellite to evenly distributed data on a 24-hour
interval. Observations over seas and oceans (covering 70% of the Earth) minimize the major error source in accuracy of weather forecast and climate models.
• High vertical resolution• The vertical resolution limited by the Fresnel zone of the observation leads to information of
atmosphere phenomena with scale sizes less than 0.5 km.
• Insensitive to clouds and precipitation• The wavelengths applied makes the measurement transparent to clouds and rain hampering other
space techniques.
• Data delivery• The EPS/METOP mission will deliver the operational data products with 3 hours of observation.
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EUMETSAT GRAS SAF 2nd User Workshop
Winter Frontal Zones and Jet Streams
The major frontal zones (left panel) and jet streams (upper panel) during winter.
The shaded regions (left panel) indicate major temperature contrasts mostly along mountain ranges and coasts. Arrows depict the dominant direction of the winds including the highs driving the wind patterns.
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NWP Data Assimilation
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Variational Data Assimilation
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Weather Prediction
Main indicators: Wind,Temperature, Pressure,Water Vapor
Weekly latitudinal distribution of occultations. Longitudinal variations still exist in the seven days simulation. Part of the spread in the plot is due to this effect.
For the 500 x 500 km cells the following statistics can be calculated:Average number of occultations in a cell: 22.49Standard deviation: 10.36
Average time difference (min) between profiles in each cell as function of latitude. The simulation covers a whole week of data.
Average time difference between the occultations: 482 min [8h 2min]Standard deviation: 216 min [3h 36min]