outline introduction: e-rtfdda new enhancement to e-rtfdda preliminary verification
DESCRIPTION
Integration of NCAR DART-EnKF to NCAR-ATEC multi-model, multi-physics and mutli- perturbantion ensemble-RTFDDA (E-4DWX) forecasting system. - PowerPoint PPT PresentationTRANSCRIPT
NATIONAL CENTER FOR ATMOSPHERIC RESEARCH
Integration of NCAR DART-EnKF to NCAR-ATEC multi-model, multi-physics and mutli- perturbantion
ensemble-RTFDDA (E-4DWX) forecasting system
Linlin Pan 1, Yubao Liu 1, Gregory Roux 1, Wanli Wu 1, Yonghui Wu 1, Jason Knievel 1, John Pace 2, Scott
Halvorson 2, Frank Gallagher 2
1NCAR/Research Application Laboratory2Dugway Proving Ground, US Army
Outline
1. Introduction: E-RTFDDA2. New enhancement to E-RTFDDA3. Preliminary verification4. Summary and future work
RTFDDA E-RTFDDA
E-RTFDDA Perturbation Approaches
LSM LDAS
RadiationPrecipitation Upper-air weather forcingVegetation …
Para
mete
rs
ETKF CyclingPerturbationsAnd scaling
GFS
Stat. perturb.Other. Perturb.
NAMECMWF
ObsDataAssimilationWeights
Perturbationsin components
may becombined
200+members
MM5
WRFPh
ysics
Sch
em
es a
nd
Para
mete
r p
ertu
rbatio
ns
E-RTFDDA Design and New Features
• Multimodal models
WRF-ARW, MM5, WRF-NMM
• Multi-boundary conditions
GFS, NAM, GEM
• Multi-physics
Major WRF physics parameterization schemes; Stochastic Kinetic Energy Backscattering
• Multiple data assimilation
RTFDDA, 3DVAR, DART-EnKF
Case description and experiment design
• 2012033118 – 2012040318
• Western US
GFS GEM
NAM
06 Z, April 1, 2012 (6h Forecasts)
DART
DART-ENKF Surface Observations
NAM GEM
Wind Speed
GFS DART
Wind Direction
NAM GEM
GFS DART
GFS GEM
NAM DART
Spread of U, valid at 20120406, 6h fcsts
GFS GEM
NAM DART
Spread of V, valid at 20120406, 6h fcsts
GFS GEM
NAM DART
Spread of T, valid at 20120406, 6h fcsts
Combined spread
U
V
U
V
gfs+nam All
(need a meaningful title here!)
Summary• NCAR E-RTFDDA is a multi-model, multi-physics, multi-
boundary conditions, multi-data assimilation scheme, mesoscale ensemble weather analysis and forecast system for real-time operational forecasting.
• In the present work, we introduces several enhancements to the E-RTFDDA perturbation schemes ， using WRF-NMM, GEM, DART-ENKF and SKEB model and/or technologies.
• Initial tests show that these additional perturbation schemes work properly ， and help mitigate the known underestimation of the E-RTFDDA spread.
• Currently we are implemented these technologies into the operational E-RTFDDA systems. Validation of the real-time forecasts will be conducted to further quantify the effect.
Combined spread
T