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Pacific Northwest Air Modelingling Meetings 1NCAR/RAL - National Security Applications Program
22 – 25 October 2007 Seattle, [email protected]
The NCAR 4DWX Real-Time Four-Dimensional Data-Assimilation and Forecasting (RTFDDA) System for Mesoscale Weather-Sensitive
ApplicationsYubao Liu, Tom Warner and Scott Swerdlin
Research Applications LaboratoryNational Center for Atmospheric Research. Boulder, CO
Pacific Northwest Air Modelingling Meetings 2NCAR/RAL - National Security Applications Program
22 – 25 October 2007 Seattle, [email protected]
OutlineRTFDDA: Description and GoalsApplication Examples and Potentials C-FDDA and E-RTFDDAE-RTFDDA Design PhilosophyResults of E-RTFDDA During FFT07:MM5 vs. WRF; Mesoscale modeling challenges
Summary and Next-gen System R&D
Pacific Northwest Air Modelingling Meetings 3NCAR/RAL - National Security Applications Program
22 – 25 October 2007 Seattle, [email protected]
Weather Analysis and Fcsts over Complex Terrain
Measurements are relatively sparse and irregular in space and timeObservations are not sufficient to describe the structures of local-scale circulationsTerrain and underlying forcing flows are complex
A full-physics model + effective use of all dataDynamically-balanced and physically-consistent 4D-
continuous analyses and “spun-up” forecasts.
How to?How to?
An “inherent” challenging problem
Pacific Northwest Air Modelingling Meetings 4NCAR/RAL - National Security Applications Program
22 – 25 October 2007 Seattle, [email protected]
NCAR Real-time FDDA and Forecast System
WRF/MM5-RTFDDA
Multi-scale Modeling
Cold start
t
Forecast
FDDA
New 12 - 48 h forecasts every 1 -12 hrs, using all obs up to “now”
TAMDAR
MESONETs
GOES
Wind Profs
All WMO/GTS Radars
Etc.
ACARS
obs
Pacific Northwest Air Modelingling Meetings 5NCAR/RAL - National Security Applications Program
22 – 25 October 2007 Seattle, [email protected]
What is “Observation-nudging”
OBS
Dx/Dt = ... + GW (xobs – xmodel )
where x = T, U, V, Q, P1, P2 …
W is nudging weight function
G is called nudging factor
W = Wtime Wqf Whorizontal Wvertical
Weighting functions depend on grid sizes; local terrain; observation quality, location, time and platforms; and air stream properties.
Pacific Northwest Air Modelingling Meetings 6NCAR/RAL - National Security Applications Program
22 – 25 October 2007 Seattle, [email protected]
Incorporate Diverse and Frequent Observations
SFC
SndgsProfs
Sat Aircraft
Sat Aircraft
Sat Aircraft
00Z June 24 2005
850 hPa > 600 hPa
600 - 350 hPa < 350 hPa
Pacific Northwest Air Modelingling Meetings 7NCAR/RAL - National Security Applications Program
22 – 25 October 2007 Seattle, [email protected]
RTFDDA Model Advantages
Uses all synoptic and asynoptic observations Allows to weigh each observation according to its time,
location and quality, andMitigates dynamics (and also cloud/precipitation) “spin-
up” problem that exists in all cold-start operational models.These properties are uniquely beneficial for weather-sensitive
applications over complex terrain and for severe weather such as hurricane and summer convection.
Coldstart
t
Forecasts
FDDA
obs
(WRF/MM5)
(WRF/MM5)
Pacific Northwest Air Modelingling Meetings 8NCAR/RAL - National Security Applications Program
22 – 25 October 2007 Seattle, [email protected]
NCAR RTFDDA Applications
• 2002-SLC Olympics • 2004-Athens Olympics• 2006-Torino Olympics • Joint Urban 2003, OKC• Colorado wild fire
• Military operations• Army test ranges• Homeland security• Wyoming cloud seeding• FAA aviation weather
• Kauai island effect• New York City• 2005 Hurricanes• TAMDAR appli.• …
20+ Special Operation Sites12 Regular Operational RTFDDA Systems
Pacific Northwest Air Modelingling Meetings 9NCAR/RAL - National Security Applications Program
22 – 25 October 2007 Seattle, [email protected]
Typical RTFDDA Model Grid Configurations
SLC-2002 Olympics
130 km x 85 km DX = 1.33 km
Simulation of toxic release
Pacific Northwest Air Modelingling Meetings 10NCAR/RAL - National Security Applications Program
22 – 25 October 2007 Seattle, [email protected]
The Operational RTFDDA system at WSMR
DX1 = 30 km
DX2 = 10 km
DX3 = 3.3 km
Since 2002
Pacific Northwest Air Modelingling Meetings 11NCAR/RAL - National Security Applications Program
22 – 25 October 2007 Seattle, [email protected]
2004-Athens Olympics Operational RTFDDA
D4: 1.1 kmD1
D2
D3
Pacific Northwest Air Modelingling Meetings 12NCAR/RAL - National Security Applications Program
22 – 25 October 2007 Seattle, [email protected]
2004-Athens Olympics RTFDDA: Aug-16 case
Example of Etesian Flows(RTFDDADomain 4)
(Red wind barbs and Yellow labels of T and Td are Verification obs)
Athens
Pacific Northwest Air Modelingling Meetings 13NCAR/RAL - National Security Applications Program
22 – 25 October 2007 Seattle, [email protected]
An ExampleGOES
RTFDDA
Comparison of MM5-RTFDDA (12km) forecasts of cloud fields of hurricane Rita with GOES satellite observations.
Forecast from the Sept 23, 2005 17Z cycle
Animation started from 0-h forecast
Pacific Northwest Air Modelingling Meetings 14NCAR/RAL - National Security Applications Program
22 – 25 October 2007 Seattle, [email protected]
4-km WRF-RTFDDA vs. Op NAM and RUC3h rain, ended at 03Z, 15 August 2006. 0 – 3h fcsts
ST4 RTFDDA
RUCNAM
(mm)
Pacific Northwest Air Modelingling Meetings 15NCAR/RAL - National Security Applications Program
22 – 25 October 2007 Seattle, [email protected]
Two RTFDDA Extensions: C-FDDA and E-RTFDDA
1. RTFDDA for the history Climo-FDDA
timeFDDA
Forecast
New 12 - 48 h forecast every 1 - 12 hrs, using all obs up to “now”
obs
1973 19751974 2007…
2. RTFDDA for probabilistic forecasts Ensemble-RTFDDA
Produce ensemble RTFDDA analyses and predictions considering uncertainties in initial conditions and in the models.
Pacific Northwest Air Modelingling Meetings 16NCAR/RAL - National Security Applications Program
22 – 25 October 2007 Seattle, [email protected]
E-RTFDDA
The weather is chaotic processes that we can not observe and predict “precisely”Probabilistic forecasts Add information and economic values
Ensemble predictionA practical way for producing probabilistic prediction
“Cut-edge” DA approaches rely on error covariance which can be estimated from ensemble E-RTFDDA is a NCAR new-gen mesoscale DA and
forecasting system
A Mesoscale Ensemble Analysis and Forecast NWP System
Pacific Northwest Air Modelingling Meetings 17NCAR/RAL - National Security Applications Program
22 – 25 October 2007 Seattle, [email protected]
RTFDDA E-RTFDDA
Pacific Northwest Air Modelingling Meetings 18NCAR/RAL - National Security Applications Program
22 – 25 October 2007 Seattle, [email protected]
Ensemble Perturbation Generator
LSM LDAS
RadiationPrecipitation Upper-air weather forcing
Vegetation …
Para
mete
rs
ETKF
Perturbation transform
Error scaling…
GFS
Stat. perturb.Other. Perturb.
NAMECMWF
ObsDataAssimilationWeights
Wang & Bishop (2003)
MM5
WRF
RadiationPBLCumulusCloud MPLand-surface
Water-bodies
TerrainSnowcover…
Para
mete
rizatio
ns
Sch
em
es
Para
mete
rs
Pacific Northwest Air Modelingling Meetings 19NCAR/RAL - National Security Applications Program
22 – 25 October 2007 Seattle, [email protected]
Ensemble Model ExecutionsPerturbations
observations
Member 1
Perturbations
observations
Member 2
Perturbations
observations
Member 3
Perturbations
observations
Member N
…
N forecasting nodes M pre/post- proc nodes
36-48h
fcsts
36-48h
fcsts
36-48h
fcsts
36-48h
fcsts
Input to decision support tools
Postprocessing
Archiving and verification
x spare nodes
RTFDDA
RTFDDA
RTFDDA
RTFDDA
Pacific Northwest Air Modelingling Meetings 20NCAR/RAL - National Security Applications Program
22 – 25 October 2007 Seattle, [email protected]
Operating E-RTFDDA for ATEC Relocatable pre-configured/real-time custom domains
ATC GRMDPG
30 - 50 members; 3 domains of 30/10/3.3-km grid sizes; Continuous FDDA and forecast cycling at 6h intervals;Each produces 6 hour analyses (-6 to 0 h) and 36 – 48h forecastsRapidly switch from one region to another on demand
Pacific Northwest Air Modelingling Meetings 21NCAR/RAL - National Security Applications Program
22 – 25 October 2007 Seattle, [email protected]
51-mem WSMR run: 1 August 2007
NMQ Q2 3h rain (obs)
Pacific Northwest Air Modelingling Meetings 22NCAR/RAL - National Security Applications Program
22 – 25 October 2007 Seattle, [email protected]
D1
D2
Forecasts of U wind profiles for
a blast test at ATC
Valid at ~12:00UTC
(59 members)
27 March 2007
Red: WRFBlue: MM5Green ETKFThick dashed: obs
Mean & +/- 1σ
24h-fcsts
Pacific Northwest Air Modelingling Meetings 23NCAR/RAL - National Security Applications Program
22 – 25 October 2007 Seattle, [email protected]
D1
D2
South-northWinds (V) At DIA
20 Dec. 2006 Colorado Blizzard with strong northerly winds blowing along foothills
Red: WRFBlue: MM5Thick dash: obs
Mean +/- 1σ
UTC, 20 Dec. 2006
0 - 24h forecasts
(69 members)
Pacific Northwest Air Modelingling Meetings 24NCAR/RAL - National Security Applications Program
22 – 25 October 2007 Seattle, [email protected]
DPG E-RTFDDA Operation (Debut on 10 Sep. 2007)
Pacific Northwest Air Modelingling Meetings 25NCAR/RAL - National Security Applications Program
22 – 25 October 2007 Seattle, [email protected]
Ensemble Mean (30 members) of Surface Flows
Early mornings (14:00 UTC) Early afternoons (18:00 UTC)
Daily animation 10 – 30 Sept. 2007 DPG Domain 3 (DX = 3.3 km)
30 km30 km
Pacific Northwest Air Modelingling Meetings 26NCAR/RAL - National Security Applications Program
22 – 25 October 2007 Seattle, [email protected]
Impacts of BCs on MM5/WRF Models
Upper temperature RMSE of individual ensemble members averaged on Domain 1 for the FFT07
period (Sept. 15 – 30, 2007)
Analyses 36h forecasts 36h forecasts
WRF
MM5
NAM
GFS
NAM
GFS
Pacific Northwest Air Modelingling Meetings 27NCAR/RAL - National Security Applications Program
22 – 25 October 2007 Seattle, [email protected]
RTFDDA: Capability SummaryNCAR RTFDDA is an application-oriented, multi-scale, rapid-cycling, 4-D data analysis and forecast (4DWX) system, proven to be a valuable tool with 20+ operational applications. The model DA, physics schemes, and the application capabilities have been continuously refined. RTFDDA are capable of generating microclimate and proba-bilistic analyses and forecasts: C-FDDA and E-RTFDDA.E-RTFDDA is built as a generic NWP tool for mesoscale DA and prediction research and operations:With built-in WRF and MM5 models, and diverse ensemble schemesCapable of rapid member (perturbs) re-configuration and relocation
Support studies on model physics and operational system “tune-up”
Ability to incorporate “cutting-edge” DA schemes and the other community achievements
Pacific Northwest Air Modelingling Meetings 28NCAR/RAL - National Security Applications Program
22 – 25 October 2007 Seattle, [email protected]
RTFDDA: Experience and Implications1. Although PBL representation is most critical for AQ purposes, a good
simulation depends on a full spectrum of model components: ICs and BCs, modeling dynamics formulation and physics parameterizations.
2. None of the physics schemes in MM5 and WRF displays persistent advantage over others for all weather variables and under different weather scenarios. Schemes should to be “tuned-up” for general weather and for the specific geographic regions of given applications.
3. Although there are many issues to be solved for mesoscale ensemble forecasting techniques, it is very limited to depend on deterministic forecasts from a single model, especially over complex terrain.
4. A proper data assimilation is necessary for producing small-scale weather analyses and very short-term forecasts. For forecast ranges beyond 24 hours, accuracy of large-scale models which provide BCs became critical.
5. For modeling PBL, precisely specification and parameterization of land-surface properties, including land use, soil types and moisture states, vegetation canopies, urban canopies, snow cover boundaries, sub-grid terrain roughness, and others is necessary.
Pacific Northwest Air Modelingling Meetings 29NCAR/RAL - National Security Applications Program
22 – 25 October 2007 Seattle, [email protected]
Thank you!
Pacific Northwest Air Modelingling Meetings 30NCAR/RAL - National Security Applications Program
22 – 25 October 2007 Seattle, [email protected]
Impacts of BCs on WRF Modeling
Surface wind dir RMSE of WRF model forecasts with same configuration but different BCs, averaged on Domain 1 daily for
the FFT07 period (Sept. 15 – 30, 2007)
Pacific Northwest Air Modelingling Meetings 31NCAR/RAL - National Security Applications Program
22 – 25 October 2007 Seattle, [email protected]
A Nudging Ensemble Kalman Filter
Obs-nudging:
Dx/Dt = ... + G W (xobs – xmodel)
W = Wq Whorizontal Wvertical Wtime
Obs-nudging vs. EnKF:
Xa = Xf + ∆tGW (xobs – xmodel )
where Xf = Xt-1 + ∆t (…)
∆tGW = Ke
∆tGW = G WqWtime Ke
EnKF
Nudging-EnKF
one ∆t nudging
( )a f o fx xKx ye H= + −
EnKF:
1( )
( )
f T f Te e
a fe
P H HP H R
P I KH P
Ke −= +
= −
Dx/Dt = ... + GWqWtimeKe ( yobs – Hxmodel )
Pacific Northwest Air Modelingling Meetings 32NCAR/RAL - National Security Applications Program
22 – 25 October 2007 Seattle, [email protected]
Implementation Strategy: 3-Tiers
1. Ensemble Generator
Construct an exhaustive ensemble member library
2. Member SelectorPick the most appropriate members of an affordable ensemble size for specific applications
3. Member ExecutionIntegrate data analysis and forecast with a continuous cycling mechanism
Probabilistic analysis and
forecast products
Pacific Northwest Air Modelingling Meetings 33NCAR/RAL - National Security Applications Program
22 – 25 October 2007 Seattle, [email protected]
SummaryE-RTFDDA is a multi-model, multi-approach and multi-scale continuously cycling mesoscale ensemble analysis and forecasting system.E-RTFDDA framework supports both real-time operation and R&D, and enables easy incorporation of new data assimilation and ensemble techniques.A 50-member 30/10/3.3km nested-grid real-time E-RTFDDA is deployed for Army applications. Initial results indicate benefit of multi-model approaches and ETKF scheme appears to be an effective component. Short-term: operations, R&D, V&V and calibration.Long-term: develop an ensemble-based hybrid 4D-ENKF with WRF “observation-nudging” weighting function defined using ensemble-based Kalman gain.
Pacific Northwest Air Modelingling Meetings 34NCAR/RAL - National Security Applications Program
22 – 25 October 2007 Seattle, [email protected]
Leverage Obs-nudging with Ensemble
Replace WhorizontalWvertical with Kalman Gain? Incorporate statistical background error covariance (Pf) like OI and 3DVAR?Use ensemble forecasts to estimate Pf like EnKF?
Dx/Dt = ... + GW (xobs – xmodel )
Cons: G and W are subjective
Xobs have to be model forecast variables
Pacific Northwest Air Modelingling Meetings 35NCAR/RAL - National Security Applications Program
22 – 25 October 2007 Seattle, [email protected]
Obs-nudging: Weighting Functions
Weighting functions should depend on grid sizes; local terrain; observation quality, location, time and platforms; and air stream properties.
W = Wtime Wqf Whorizontal Wvertical
OBS
OBS
Zi
sfc
Pacific Northwest Air Modelingling Meetings 36NCAR/RAL - National Security Applications Program
22 – 25 October 2007 Seattle, [email protected]
D1
D2
A blast test event
Soundings at ATC
Valid at ~12:00UTC
(59 members)
27 March 2007Red: WRFBlue: MM5Green ETKFThick dash: obs
Mean +/- 1σ
Analyses
Analyses24h-fcsts
24h-fcsts
Pacific Northwest Air Modelingling Meetings 37NCAR/RAL - National Security Applications Program
22 – 25 October 2007 Seattle, [email protected]
ETKF (Ensemble Transform Kalman Filter)Purpose:
Systematically sample analysis errors in initial conditions based on
observation errors and previous ensemble forecasts
Benefits:
The initial perturbations are balanced, structured and dynamics constrained, and contain a number of leading growth modes
Computationally efficient
Approach (Wang and Bishop, 2003):
Transform ensemble forecast perturbations to analysis perturbations:
Xa = Xf T
The transform matrix T is estimated according to relationship between analysis error covariance and forecasts error covariance defined by ensemble Kalman Filter
Pacific Northwest Air Modelingling Meetings 38NCAR/RAL - National Security Applications Program
22 – 25 October 2007 Seattle, [email protected]
20 Dec. 2006 Colorado-Blizzard
Comparison of ETKF and Non-ETKF (MM5) ensembles (12-h accumulative rainfall ending at 00Z Dec. 21, 2006)
ETKF Non ETKF
Ensemble Mean (mm)
15 members 15 members
Pacific Northwest Air Modelingling Meetings 39NCAR/RAL - National Security Applications Program
22 – 25 October 2007 Seattle, [email protected]
20 Dec. 2006 Colorado-Blizzard
ETKF Non ETKF
Ensemble Spread (mm)
Comparison of ETKF and Non-ETKF (MM5) ensembles (12-h accumulative rainfall ending at 00Z Dec. 21, 2006)
Pacific Northwest Air Modelingling Meetings 40NCAR/RAL - National Security Applications Program
22 – 25 October 2007 Seattle, [email protected]
Red dots – HPC report
22 / 03Z
24/ 08Z
25/ 03Z
WRFFDDA
analysesof
Hurricane Rita
Pmsl and winds
7 days From
00Z Sep. 19 to
00Z Sep. 26, 2005
