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Statistical-dynamical methods for scale dependent model evaluation and short term precipitation forecasting (STAMPF / FU-Berlin). E. Reimer, U. Cubasch, A. Claußnitzer, I. Langer P. Névir Institut für Meteorologie Freie Universität Berlin.

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slide1

Statistical-dynamical methods for scale dependent model evaluation and short term precipitation forecasting (STAMPF / FU-Berlin)

E. Reimer, U. Cubasch, A. Claußnitzer, I. Langer

P. Névir

Institut für Meteorologie

Freie Universität Berlin

slide2

The central focus of this project is a scale dependent evaluation of precipitation forecasts of the LMK / LME using dynamical, and statistical parameters as well as cloud properties.

  • Separation of stratiform and convective precipitation and objective analysis combing WMO observations, rain gauge data and Meteosat-8 cloud data.
  • Analyse of (convective) precipitation by high resolution data from Berlin rain gauge stations n combination to satellite data and radar data.
  • Process-oriented dynamical evaluation of precipitation forecasts using the Dynamic State Index (DSI)
  • Statistical diagnostics of precipitation fields by means of scaling exponents, or Shannon`s information entropy
  • Participation in campaign COPS/GOP in 2007 in Southwest Germany and Germany
convective and stratiform cloud types
Convective and stratiform cloud types
  • Separation of cloud types for convective and stratiform precipitation analysis
  • 1. cumulus2. cumulonimbus● cumulusmediocris ● cumulonimbus calvus● cumulus congestus ● cumulonimbus capilatus● cumulus and stratocumulus (weight by 33%)
  • 3. stratiform● cumulus and stratocumulus (weight by 67%) ● stratus nebulosus ● stratus fractus ● nimbostratus

Cumulonimbus

Nimbostratus

Stratus

interpolationscheme for precipitation analysis
Interpolationscheme for precipitation analysis

Precipitation scheme using simple linear Interpolation:

f0= precipitation amount [mm/h] atGridpoint

gi= Weight

fi = precipitation amount from observation

w0 = cloud weight t gridpoint

wi = cloud weight at observation site

di distance between gridpoint r0 and observation ri and w is the weight (shown above)

next step: statistical analysis scheme

beispiel einer niederschlagsanalyse vom 12 8 2002
Beispiel einer Niederschlagsanalyse vom 12.8.2002

Niederschlagssumme Niederschlagswahr- Niederschlagssumme

ohne Satellitenkorrektur scheinlichkeit aus Meteosat mit Satellitenkorrektur

slide8

Process-oriented dynamical evaluation with

Dynamic State Index (DSI)

The DSI locally combines information from energy (B), ERTEL’s potential vorticity (Π) and entropy (θ).DSI describes all non-stationary / diabatic processes!

Result: High correlation (40-60%) between DSI² and LM-precipitation shows, that the DSI is a dynamical threshold parameter for rainfall processes. Threshold: stationary, adiabatic solution of the primitive equations.

Correlation: DSI² / Precipitation

area mean from LM-output data

Workstep: Investigation of the vertically

integrated DSI-field, including information

of the vertical humidity profiles and liquid

water content. Cooperation with „QUEST“

slide9

Statistical evaluation of precipitation through scaling exponent

Scaling exponent α is a statistical parameter which indicates probability of extreme precipitation. Smaller values of α characterise distributions with high intensity tails.

Workstep: Further investigation of extreme

precipitation (temporal resolution of minutes)

Blackforest Brandenburg

Cumulonimbus α = 1.21 α = 1.84

Nimbostratus α = 2.13 α = 2.10

Stratus α = 2.48 α = 3.0

αBlackforest < αBrandenburg, more extrem values in the Blackforest area

Result:

slide10

Convective rain intensity versus duration obeys a

power law!

Result: Explanation using Turbulence

Theory of Kolmogorov and Richardson

Workstep:Testing the hypothesis that the turbulent momentum flux (friction

velocity), the mixing ratio r, energy dissipation and accelerations

determine the maximum rain intensity in convective cloud layers (COPS).

niederschlagssummen mm vom 12 8 2002 analyse
Niederschlagssummen (mm) vom 12.8.2002Analyse

Tagessumme des Niederschlags Monatssumme des Niederschlags

für den 12. August 2002

arbeiten und aussicht
Arbeiten und Aussicht
  • Weitere Aufbereitung der Berliner Niederschlagsdaten 2006 und 2007
  • Kontrolle der Niederschlagsmessungen über 5-Minuten- und Tagessummen
  • Verwendung der Radarechos für die Analyse der 5-Minutensummen im 500m bis 1km Gitter
  • Auswertung der Intensitäten für verschiedene Zeitintervalle
  • Teilnahme an GOP
  • Berücksichtigung der Windprofile aus dem LMK und Beobachtungen
  • Einbeziehung von Niederschlagsprofilen vom Vertikalradar (Peters, Hamburg) für 2007
  • Vergleich der Messungen und Radardaten mit LMK (2,8km Gitter) des DWD für 2002 jetzt und 2007
slide17

Scale Dependent Analysis of Precipitation

12 August 2002 20 UTC

3-hourly rainfall (WMO data)

hourly rainfall (WMO data)

Rainfall network of Berlin

(based on minutely data)

25 km

1 km / 500 m

7 km

Mean absolute error year 2002 (LM vs. OBS)

Data Basis

stratiform

MAE (mm/h)

convective

  • WMO synoptic observations
  • Satellite data (Meteosat, NOAA)
  • 60 rain gauges in Berlin (5 min)
  • 76 rain gauges in Berlin (1 day)
slide18

Mean absolute error (2004) for different forecast period (LM forecast- FUB analysis)

MAE of convective precipitation is greater than stratiform precipitation

Total precipitation is dominated by the convective precipitation

slide19

MAE 2004 (Juni, Juli, August) for the Blackforest and Brandenburg

Blackforest Brandenburg

stratiform

Mean = 0.059 [mm/1h]

Mean = 0.075 [mm/1h]

convective

overestimated by LM

Mean = 0.1751 [mm/1h]

Mean = 0.1332 [mm/1h]

slide20

DSI-forecasts as a new precipitation forecast tool

Rain: 00 UTC +12h

DSI: 00 UTC +12h

Analysis chart: 21.09.04

Result: Predicted DSI-field has the same filament-like precipitation structures.

Workstep: Exploring the precipitation forecast skill of the DSI by comparison

the correlation of the DSI on different isentropic levels with LMK precipitation

forecasts. / This workstep will also be extended to the special case studies.