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Juha Kilpinen Finnish Meteorological Institute (FMI), Finland

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Application of low-resolution ETA model data to provide guidance to high impact weather in complex terrain. Juha Kilpinen Finnish Meteorological Institute (FMI), Finland Juan Bazo, Gerardo Jacome & Luis Metzger Servicio National de Meteorologia e Hidrologia (SENAMHI), Peru.

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Presentation Transcript
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Application of low-resolution ETA model data to provide guidance to high impact weather in complex terrain

Juha Kilpinen

Finnish Meteorological Institute (FMI), Finland

Juan Bazo, Gerardo Jacome & Luis Metzger

Servicio National de Meteorologia e Hidrologia (SENAMHI), Peru

co operation between fmi and senamhi
Co-operation between FMI and SENAMHI

Institutional development

  • Among the items:
  • Forecast verification (training, application development: an entry level verification system)
  • Post-processing of NWP output (training, application development: testing of Kalman filtering for NWP data)

Kilpinen-Bazo-Jacome-Metzger

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EUMETCAL training tools used

Kilpinen-Bazo-Jacome-Metzger

introduction
Introduction
  • Peruvian ETA-model data is available for guidance at Peruvian Hydro-meteorological service (SENAMHI). The application of rather low resolution (22 km grid) data is not straight forward in complex terrain in terms of topography, climatic zones and sharp land-sea gradient.
  • The applicability of the data is evaluated and if some problems are encountered a solution will be searched. So far data has been partly verified and tests with Kalman filter have started. The test data includes maximum and minimum temperature.
  • Another focus is the heavy precipitation in Machu Picchu area resulting flooding and danger to life and property.

Kilpinen-Bazo-Jacome-Metzger

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Data

  • ETA-model
  • Resolution 22 km
  • 18 vertical levels
  • Output 6 h interval up to 72 h
  • Kain Frish cumulus parameterization
  • the GFS global model data is used for the lateral boundaries
  • No data assimilation is made
  • Test data periods: temperature 2009-2010
  • Precipitation 2010
  • Observations (21 stations)
  • Tumbes
  • Piura
  • Huánuco
  • Pucallpa
  • Lima
  • Andahuaylas
  • Cuzco
  • Tacna
  • Chiclayo
  • Chimbote
  • Cajamarca
  • Tarapoto
  • Yurimaguas
  • Iquitos
  • Tingo Maria
  • Trujillo
  • Ayacucho
  • Puerto Maldonado
  • Arequipa
  • Juliaca
  • Pisco

Kilpinen-Bazo-Jacome-Metzger

methods post processing kalman filter
Methods – post-processing/Kalman filter
  • Only for temperature forecasts:
  • Two state parameters
    • TKalman = B1 + B2 * TETA
  • Optimized estimation of measurement noise R and system noise Q

Kilpinen-Bazo-Jacome-Metzger

methods verification
Methods - verification
  • For temperature forecasts:
  • ME (Mean Error)
  • RMSE (Root Mean Squared Error)
  • HR (Hit Rate) (not shown)
  • Also other scores
  • For precipitation forecasts (categories):
  • B (Bias)
  • PC (Percent correct)
  • POD (Probability of Detection)
  • FAR (False Alarm Rate)
  • KSS (Kuipers Skill Score)
  • TS (Threat Score)
  • ETS (Equility Threat Score)

Kilpinen-Bazo-Jacome-Metzger

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Stations in focus:Cusco 3399 m Pucallpa 154 m Andahuaylas 2866 m Huanuco 1859 m Lima 13 mTacna 452 m Machu Picchu

Kilpinen-Bazo-Jacome-Metzger

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Temperature verification

Cusco (near Machu Picchu) 3399 m

machu picchu 2010
Machu Picchu 2010

Kilpinen-Bazo-Jacome-Metzger

categorical results machu picchu 2010
Categorical results: Machu Picchu 2010

Kilpinen-Bazo-Jacome-Metzger

conclusions
Conclusions
  • The preliminary results indicate that ETA model has problems with temperature forecasts in most regions; in tropical rain forest, at mountains and near coastline affected by cold sea current. The application of Kalman filter was used to minimize systematic errors from the ETA-model and rather encouraging results was received.
  • For precipitation forecasts ETA model is not able to forecast higher precipitation amounts correctly
  • A higher resolution (e.g. WRF) NWP model would be a way to inprove the forecast quality in complex terrain

Kilpinen-Bazo-Jacome-Metzger

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