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Status and plans for the ECMWF forecasting System. Overview. Performance of the forecasting system Research highlights: CY36R2 (22 June 2010): GRIB API and Ensemble Data Assimilation (to initiate the EPS) CY36R4 (9 November 2010): New physics package, surface EKF, snow analysis,…

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overview
Overview
  • Performance of the forecasting system
  • Research highlights:
    • CY36R2 (22 June 2010): GRIB API and Ensemble Data Assimilation (to initiate the EPS)
    • CY36R4 (9 November 2010): New physics package, surface EKF, snow analysis,…
    • CY37R2 (in the pipeline): Ensemble Data Assimilation to provide flow-dependent variances to 4D-Var, reduction of observation error for AMSU-A, GRIB-2 for model level fields

Bilateral meeting 2011

overview1
Overview
  • Performance of the forecasting system
  • Research highlights:
    • CY36R2 (22 June 2010): GRIB API and Ensemble Data Assimilation (to initiate the EPS)
    • CY36R4 (9 November 2010): New physics package, surface EKF, snow analysis,…
    • CY37R2 (in the pipeline): Ensemble Data Assimilation to provide flow-dependent variances to 4D-Var, reduction of observation error for AMSU-A, GRIB-2 for model level fields

Bilateral meeting 2011

precipitation skill europe
Precipitation skill Europe

D+2

D+4

Bilateral meeting 2011

russian heat wave
Russian heat wave

Bilateral meeting 2011

overview2
Overview
  • Performance of the forecasting system
  • Research highlights:
    • CY36R2 (22 June 2010): GRIB API and Ensemble Data Assimilation (to initiate the EPS)
    • CY36R4 (9 November 2010): New physics package, surface EKF, snow analysis…
    • CY37R2 (in the pipeline): Ensemble Data Assimilation to provide flow-dependent variances to 4D-Var, reduction of observation error for AMSU-A, GRIB-2 for model level fields
    • others

Bilateral meeting 2011

november 2010 ifs cycle 36r4
Selected contents

Prognostic rain and snow with more comprehensive cloud microphysics

EKF for soil moisture analysis

New snow analysis (O-I)

Enhancement of all-sky radiance assimilation

November 2010 IFS cycle 36r4
new prognostic cloud microphysics scheme
New prognostic cloud microphysics scheme

WATER VAPOUR

Evaporation

Condensation

CLOUD FRACTION

CLOUD

Liquid/Ice

Evaporation

CLOUD FRACTION

Autoconversion

PRECIP Rain/Snow

Current Cloud Scheme

New Cloud Scheme

  • 5 prognostic cloud variables + water vapour
  • Ice and water now independent
  • More physically based, greater realism
  • Significant change to degrees of freedom
  • Change to water cycle balances in the model
  • More than double the lines of “cloud” code!
  • 2 prognostic cloud variables + w.v.
  • Ice/water diagnostic Fn(T)
  • Diagnostic precipitation
new prognostic cloud microphysics representation of mixed phase
New prognostic cloud microphysicsRepresentation of mixed phase
  • The most significant change in the new scheme is the improved physical representation of the mixed phase.
  • Current scheme: diagnostic fn(T) split between ice and liquid cloud(a crude approximation of the wide range of values observed in reality).
  • New scheme: wide range of supercooled liquid water for a given T.

PDF of liquid water fraction of cloud for the diagnostic mixed phase scheme (dashed line) and the prognostic ice/liquid scheme (shading)

a new snow analysis i
For snow SYNOP reports an satellite based snow cover are assimilatedA new snow analysis (I)

A new 4 km IMS snow cover is assimilated into a new OI analysis replacing Cressmaninterpolation

Here shown isthe analysedsnow cover

Cressman and IMS_24km OI and IMS 4km

impact of cycle 36r4
Impact of Cycle 36r4

Bilateral meeting 2011

seeps impact of 36r4
SEEPS: impact of 36r4

Bilateral meeting 2011

overview3
Overview
  • Performance of the forecasting system
  • Research highlights:
    • CY36R2 (22 June 2010): GRIB API and Ensemble Data Assimilation (to initiate the EPS)
    • CY36R4 (9 November 2010): New physics package, surface EKF, snow analysis…
    • CY37R2 (in the pipeline): Ensemble Data Assimilation to provide flow-dependent variances to 4D-Var, reduction of observation error for AMSU-A, GRIB-2 for model level fields
    • others

Bilateral meeting 2011

in the pipeline ifs cycle 37r2
Selected contents

Increased weight to AMSU-A data

Direct use of EDA in 4D-Var

Retuning of new physics

GRIB-2 for model level fields

In the pipeline: IFS cycle 37R2
ensemble of data assimilations eda
Ensemble of Data Assimilations (EDA)
  • Perturbed observations
  • Perturbed SSTs
  • Stochastic physics

Δx2

Δx1

Ensemble initial

perturbations

Δx3

Δx4

X0

4DVAR

X+12h

eda flow dependent variances
EDA – flow dependent variances

9h forecasts

23/1 2009 21 UTC

Standard deviation of zonal wind component at ~850hPa and pmsl

ms-1

24/1 2009 21 UTC

impact of cycle 37r2
Impact of Cycle 37R2

NH

SH

Z

VW

Bilateral meeting 2011

overview4
Overview
  • Performance of the forecasting system
  • Research highlights:
    • CY36R2 (22 June 2010): GRIB API and Ensemble Data Assimilation (to initiate the EPS)
    • CY36R4 (9 November 2010): New physics package, surface EKF, snow analysis…
    • CY37R2 (in the pipeline): Ensemble Data Assimilation to provide flow-dependent variances to 4D-Var, reduction of observation error for AMSU-A, GRIB-2 for model level fields
    • Others (small selection)

Bilateral meeting 2011

main research development topics 2011
Main research/development topics 2011:
  • Ensemble data assimilation methods (EDA, EKF)
  • Weak constraint, long window 4D-Var
  • Vertical resolution increase
  • Numerical experimentation into the “grey zone”
  • Improved physical parameterizations
  • Implement NEMO ocean model and NEMOVAR in EPS
  • Seasonal forecasting system 4
  • ERA-CLIM
  • MACC in Near-Real-Time
  • IFS maintenance and optimisation (cycles, code, scripts)
  • Object Oriented Prediction System

Research Department Annual Plan 2011

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