Post on 20-Jan-2016
Interagency Strategic
Research Plan for
Tropical Cyclones:
The Way Ahead
Dr. Naomi SurgiNOAA NCEP/EMC
March 6, 2007
• Key Findings and Recommendations
– NWP modeling and data assimilation
• Update on NCEP Hurricane Prediction System
• Collaborative Ventures
Overview
Key Findings & Recommendations
• NWP modeling and data assimilation
– Increased skill in forecasting intensity and structure, sea state and storm surge, and precipitation is now on the horizon, much as improving track forecast skill was two decades or so ago
– To meet operational needs, the Nation must be committed to supporting the key following areas:
• Advanced observations
• Advanced data assimilation technologies
• Advanced NWP models
• Investment in human and infrastructure resources
– Complimentary efforts in developing next-generation operational hurricane forecast systems should be a National priority
• NCEP Hurricane Prediction System
• Navy Tropical Cyclone System
Key Findings & Recommendations
• NWP modeling and data assimilation (continued)
– Development efforts of next-generation hurricane forecast systems
• Should form basis for projects supporting hurricane research and collaboration among experts from:
-- Other Federal Agencies
– Academia
– International NWP centers & research community
– Private sector
– Sufficient human / infrastructure resources should be provided for:
• Development of advanced data assimilation & NWP modeling systems
• Operational NWP computing
NCEP’s Advanced DA and Modeling Plans
• NCEP Data assimilation development strategy 2007-2010
• NCEP Hurricane Modeling
• Next-generation NCEP Production Suite– Preparing for the future– Production Suite: conceptual prototype– Implications
Data Assimilation Development Strategy
• Three closely related efforts– Develop Situation-Dependent Background Errors
(SDBE) and Simplified 4D-Var (S4DV)– “Classical” 4D-Var (C4DV)– Ensemble Data Assimilation (EnsDA)
• Partners– NCEP/EMC– NASA/GSFC/GMAO– THORPEX consortium
• NOAA/ESRL• CIRES• U. Maryland• U. Washington• NCAR
Advanced Data Assimilation Development Strategy
Lead Org.
Encouraging Risk FactorsAll: cost (computer+human)
increase ~3-10x
SDBE+S4DV
NCEP/EMC
Evolutionary development path
Experience through RTMA – SDBE critical for hurricanes
GSI operational 2007:Q3
Definition of appropriate covariance uncertain
Multiple approaches (incl. ensembles)
C4DV NASA/GMAO
Positive impact at other WX centers
(ECMWF, UKMO, CMC, JMA)
Various approximations
Cost + (3x code)
Which forecast model will be used?
EnsDA EMC/
UMd, CIRES, ESRL, UW NCAR
Good results at low res & low data volumes
Relatively simple algorithms
Ens. DOF may not be sufficient (esp. hires)
Data handling for large data volumes challenging
Obs & model bias correction
Covariance inflation req.
NCEP DA Development Strategy
• Adapt Hybrid (?) – combine best features of advanced techniques
Flexible schedule due to advanced nature of work~yearly upgrades of SDBE/S4DV from NCEP/EMC
S4DV + EnsDA – 2007-2008
• Prototype development– 2008
• Full parallel testing• Transition decision (between 3 candidates)
– 2009-2010 • Pre-implementation testing• Operational implementation
Next-generation NCEP Production Suite
• Motivation
• Production Suite: conceptual prototype
• Implications
Motivation • Support improved NWS forecast services
– Greater focus on high-impact events– Additional environmental information service
responsibilities– Provide more information to users and access to
more info– Probabilistic and ensemble methods
• Respond to external (NRC) reports– “Completing the Forecast” – “Fair Weather”
• Respond to NOAA Science Advisory Board reviews– Ocean modeling (National “backbone”)– Hurricane intensity (ensemble-based system)
Motivation
• Observations (number and availability)– Advanced Polar and Geostationary sounders
(~100 X greater)– < 60 minute delivery – Next-generation Doppler radar
• Advanced technologies for– Data assimilation
• Discussed earlier– Ensemble processing
• Bias and Ensembles (e.g. NAEFS)• Quantify value-added for multi-model ensemble
system (e.g. CPC “Consolidation”)– “Reforecast” data base (CFS, Week2 products)– Product delivery (e.g. NOMADS)
Production Suite: Conceptual Prototype
Model Region 1
Model Region 2
Global/Regional Model Domain
• Concurrent execution of global and regional applications– More efficient execution of rapid updating
• In-core updating for analysis increments • Regional (CONUS, Alaska, Hawaii, Caribbean & Puerto Rico, Hurricanes) • Global (if requirements and resources)
– All ensemble members may exchange information during execution• ESMF*-based Common Modeling Infrastructure
Analysis
* Earth System Modeling Framework (NCAR/CISL, NASA/GMAO, Navy (NRL), NCEP/EMC)
Analysis--------------
OtherForecastSystems
Physics(1,2,3)
ESMF Utilities(clock, error handling, etc)
Post processor & Product GeneratorVerification
Resolution change
1-11-21-32-12-22-3
ESMF Superstructure(component definitions, “mpi” communications, etc)
Multi-component ensemble+
Stochastic forcing
Coupler
Dynamics(1,2)
Application Driver
ESMF* Compliant Component System
* Earth System Modeling Framework (Navy (NRL), NCAR/CISL, NASA/GMAO, NCEP/EMC)
2, 3 etc: institutionally (non-NCEP) supported
EMC is exploring with NRL development of a mutually beneficial ESMF system
08 09 10 11 12
Radial vel./ reflectivity Adv. DA
SDBE
Mesoscale Data Assimilation for Hurricane Core
Advancing HURRICANE System
Atm. Model physics and resolution upgrades (continuous) Atm. Model physics and resolution upgrades (continuous)
Atm/ocean boundary layer: wave drag, enthalpy fluxes (sea spray) Atm/ocean boundary layer: wave drag, enthalpy fluxes (sea spray)
Microphysics, radiation Microphysics, radiation Incr. resolution Incr. resolution
(6km/>64L)(6km/>64L)
WavesWaves: surf-zone physics implement : surf-zone physics implement
Ocean:Ocean: 4km. - continuous upgrades in RTOFS 4km. - continuous upgrades in RTOFS
ENSEMBLES???
ENSEMBLES???
Prototype
Ens w/Navy
Prototype
Ens w/Navy
Transition to ESMFTransition to ESMF
Storm surge???
NCEP Production SuiteWeather, Ocean & Climate Forecast Systems
Version 3.0 April 9, 2004
0
20
40
60
80
100
0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 6:00
6 Hour Cycle: Four Times/Day
Pe
rce
nt
Us
ed
RUCFIREWXWAVESHUR/HRWGFSfcstGFSanalGFSensETAfcstETAanalSREFAir QualityOCEANMonthlySeasonal
GD
AS
GF
S an
al
NA
M an
al
CFS
RTOFS
SR
EF NAM
AQ
GFSHUR
RD
AS
Current (2007)
GENS/NAEFS
Current - 2007
NCEP Production SuiteWeather, Ocean, Land & Climate Forecast Systems
CFSMFS
NCEP Production SuiteWeather, Ocean & Climate Forecast Systems
Version 3.0 April 9, 2004
0
20
40
60
80
100
0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 6:00
6 Hour Cycle: Four Times/Day
Pe
rce
nt
Us
ed
RUCFIREWXWAVESHUR/HRWGFSfcstGFSanalGFSensETAfcstETAanalSREFAir QualityOCEANMonthlySeasonal
WAV
CFS & MFS
GENS/NAEFSGFS
Next Generation PrototypePhase 4 - 2015
Regional
Rap Refresh
Global
HURSREF
Reforecast
Hydro / NIDIS/FF
Hydro
NAM
GDAS
RDAS
RTOFS RTOFSAQ
NCEP Production SuiteWeather, Ocean, Land & Climate Forecast Systems
AQ
Computing factor: 81
Concurrent• GFS*• NAM• SREF Hourly• GDAS• RDAS• Rapid Refresh Expanded• Hurricane capability (hires)• Hydro/NIDIS• Reforecast
* Earlier delivery of GFS concurrent combined products from NAM, GFS, SREF
CFS & MFS
NCEP Production SuiteWeather, Ocean & Climate Forecast Systems
Version 3.0 April 9, 2004
0
20
40
60
80
100
0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 6:00
6 Hour Cycle: Four Times/Day
Per
cen
t U
sed
RUCFIREWXWAVESHUR/HRWGFSfcstGFSanalGFSensETAfcstETAanalSREFAir QualityOCEANMonthlySeasonal
CFSMFS
WAVGFSRegional
Rap Refresh
GlobalSREFReforecast
Hydro
NAM
GDAS
RDAS
RTOFS
RT
OF
S
CFS & MFSAQ Hydro / NIDIS/FF AQ
GENS/NAEFS
>100% of 2015 computing
Next Generation PrototypeFinal – 2017+
NCEP Production SuiteWeather, Ocean, Land & Climate Forecast Systems
GLOBAL NGATS
HU
R
Computing factor: > 240
ECOSYSTEMS
SPACE WEATHER
HENS
• Principals for moving forward1. Data assimilation advances
• Major factor in improved forecast performance• Provide return on investment in costly observing systems • Require greater fraction of NCEP’s Production Suite
2. Maturing, ensemble-based, probabilistic systems offer the most potential benefits across wide spectrum of forecast services
3. Product delivery• Time is critical (perishable product)• Information availability must be maximized
Conclusion
Summary• Comprehensive Data Assimilation (DA) development strategy
– 2007-2010• Phased evolution of the NCEP Production Suite
– 2009-2015– Results in
• Improved services for high impact weather• Application of advanced data assimilation techniques for improved
model initial conditions• More efficient
– Use of computing– Incorporation of new product lines for improved services
• Earlier product delivery• More uniform and informative product stream
– Advanced ensemble suite including components supported outside NCEP– Improved statistical post-processing– Reforecast and Reanalysis become operationally supported
– Consistent with• ESMF • DA development strategy and interagency collaborations (current and
anticipated)
Resources
• Improving intensity/structure, etc. - complex problem – not only scientifically
• Requires resources for science, obs, modeling systems, computing and infrastructure (in correct proportions)
• Collaborations are integral to effort• Will only prove beneficial IFF
collaborative efforts have sufficient resources (both $$$ and human)