Embed Size (px)
Citation preview
1
NCEP Operational Prediction:Current status and future plans
Stephen J. LordDirector
NCEP Environmental Modeling Center
NCEP: “where America’s climate and weather services begin”
2
Overview• Mission comparison with International Centers
– Current model suite• Performance comparison
– Global NWP– Hurricanes– S/I Climate– Precipitation (US)
• Improved strategy for forecast system enhancements
• Future model suite• Summary
3
NCEP Mission Requirements &
Forecast Suite Elements
Suite Elements
Global NWP
Meso NWP
Fire Wx
Rapid Update
Reg. Hurricane
Air Quality
Global Ensembles
Meso Ensembles
Real Time
Ocean
S/I Climate
NCEP X X X X X X X X
UKMO X X X X X
ECMWF X X X
GFS
CFS
GFDLHurricane
SREF
Eta
Noah Land Surface Model
Dispersion
Air Quality
2005 NCEP Production Suite Atmospheric Model Dependencies
Forecast
RUC
GDAS
EDAS
WRF-NMMWRF-ARWETARSM
L D A S
GENS
Sev Wx
WRF-NMMWRF-ARW
5
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
Per
cent
Use
d
RUCFIREWXWAVESHUR/HRWGFSfcstGFSanalGFSensETAfcstETAanalSREFAir QualityOCEANMonthlySeasonal
RUC GFS Anl Hur
GFS FcstNAM Fcst
NAM Anl Waves
SREF GENS
6
Performance ComparisonGlobal NWP
Gap widening for SH
“Constant” gap for NH
7
Performance ComparisonHurricanes
8
Raw Nino3.4 SST Correlation SkillAnnual Mean 1981-2001
0
20
40
60
80
100
1 2 3 4 5
Forecast Lead [ months ]
An
om
aly
Co
rre
lati
on
[ %
]
CFS
ECM
MFR
MPI
UKM
ING
LOD
CER
CA
wrt OIv2 1971-2000 climatology
European
Performance ComparisonSeasonal Forecasts
NCEP CFS
CA (Statistical)
9
Performance Comparison
BIAS
THREAT
--- ECMWF--- UKM___NCEP
Global Models
North American run
THREAT
1993 1996 1999 2001 2003 2005
24
48 72
Precipitation (24-72 h) 7/1/04-6/30/05
10
Improved Strategy
• Engage more partners from the US weather and climate community to:– Promote use of operational forecast systems by “non-
operational” users
• Adopt community model concept to:– Supply improved diversity of scientific solutions– Enhance links and partnerships between research
and operational communities– Support “Test Beds” which provide
• Technical support for codes and data• More efficient transition to operations path based on results
– Influence resource decisions based on operational research needs
11
Improved Strategy (cont)
• Examples–NASA-NOAA-DOD Joint Center for
Satellite Data Assimilation
–Real time ocean modeling
–Supported community code (Data Assimilation)
–WRF
12
NASA-NOAA-DOD Joint Center for Satellite Data Assimilation
(JCSDA)– Multi-agency partnership (NOAA, NASA,
DOD)– Mission
• Accelerate and improve the quantitative use of research and operational satellite data in weather and climate prediction models
– Current generation data– Prepare for next-generation (e.g. NPOESS, METOP,
COSMIC) instruments
– Supports applied research• Partners• University, Government and Commercial Labs
13
Examples of Instrument-Specific Development at the JCSDA
• GPS Occultation (COSMIC)
• AIRS• MODIS winds• Surface emissivity for microwave instruments
• Advanced SST physical retrievals for IR & MW instruments
A1
A1
currentcurrent
NewNew
14
US GODAE: Global Ocean Prediction with HYCOM
• Goal: to develop and demonstrate real-time, operational, high resolution ocean prediction systems for the Global Oceans and Basins
• NCEP Partners with
• University of Miami/RSMAS
• NRL Stennis, NRL Monterey, FNMOC
• NOAA PMEL, AOML
• Los Alamos National Laboratory
• Others (international, commercial)
• Hybrid isopycnal-sigma-pressure ocean model (called Hybrid Coordinate Ocean Model – HYCOM)
• Funded FY 2003-2007 by NOPP
Chesapeake Bay
15
HYCOM Deployment ScheduleNorth Atlantic
World Oceans
North-East Pacific
Hawaii
FY 2006 2007 2008
Global atmosphere-ocean Coupling and Hurricane-Ocean Coupling
Initiate interactions with NOS on bay and estuary model boundary conditions; Initiate wave-current interactions. Storm Surge Modeling
EcosystemModeling
16
Improved Strategy (cont)
• Data Assimilation Code– Gridpoint Statistical Interpolation (GSI) analysis
• Applied to global and regional (WRF) analyses• Community-based (currently with minimum support)
– 46 users
– NASA/GMAO has adopted code for their research and operations
• Ingests full suite of conventional and remotely-sensed (satellite and radar) observations
– Community Radiative Transfer Model (CRTM)
• Contains advanced treatment of background errors• Basis of advanced data assimilation techniques
– High time and space density data
– Simplified 4D-Var capability
– Ready for ensemble information input
17
WRF
• Mesoscale community model: in development since 1997 – supported through USWRP, NOAA, DOD, FAA, UCAR, NSF
• Includes support for Boulder Development Testbed Center (DTC) and operational implementation at NCEP and DOD
• Currently supports same real-time code run at DTC and NCEP
CMI
NCARARW
NCEPNMM
Explicit Cores(e.g., Hurricane, Dispersion, Aviation)
18
WRF Implementation Schedule
• HiResWindow (Both cores): Implemented operationally at NCEP on 6/28/05 (~5 km)
• WRF SREF members: Operational FY05 (4th Qtr)• North American WRF: Operational in FY06• WRF SREF: Fully operational in FY07• Hurricane WRF: Operational in FY07*• Rapid Refresh WRF: Operational in FY07*• WRF Chem: Beyond 2008** As resources allow
GFS
CFS
GFDLHurricane
SREF
Eta
Noah Land Surface Model
Dispersion
Air Quality
2005 NCEP Production Suite Atmospheric Model Dependencies
Forecast
RUC
GDAS
EDAS
WRF-NMMWRF-ARWETARSM
L D A S
GENS
Sev Wx
WRF-NMMWRF-ARW
GFS
CFS
HurricaneWRF
SREF
WRF
Noah Land Surface Model
Dispersion
Chem WRF*Air Quality
2007 NCEP Production Suite Atmospheric Model Dependencies
Forecast
Rapid Refresh WRF
GGSI
RGSI
WRF-NMMWRF-ARWETA?RSM?
L D A S
GENS
Sev Wx
WRF-NMMWRF-ARW
*FY08
21
Summary• NCEP, DOD, research community making progress on
community model development and application– JCSDA– HYCOM– WRF
– Community codes
• Need to build off this community effort and increased partnerships
– Improve ongoing development and implementation process
• Work toward a full Earth System Modeling Framework for global and regional applications
• Ensure that the entire end-to-end effort is properly resourced
22
Backup
23
Earth System Modeling Framework
1. ESMF provides tools for turning model codes into components with standard interfaces and standard drivers
2. ESMF provides data structures and common utilities that components use
i. to organize codesii. to improve performance
portabilityiii. for common services such as data
communications, regridding, time management and message logging
ESMF InfrastructureData Classes: Bundle, Field, Grid, Array
Utility Classes: Clock, LogErr, DELayout, Machine
ESMF SuperstructureAppDriver
Component Classes: GridComp, CplComp, State
User Code
24
NCEP, ECMWF, UKM ComparisonOperating strategy
ECMWF UKMET NCEP Impact
Single forecast system with limited applications
Single forecast system with international and domestic applications
Multiple forecast systems with international and largest set of domestic applications
Dilution of EMC management and scientific resources
R:O Computing ratio ~4:1
Resources well planned
Unknown R:O computing ratio ~1.3:1
Recent increased and reorganized support for computing
Potential for improvement
Operations department takes major role in optimizing, reviewing code
Role of Operations Department unknown
Operations department (NCO) does not review or optimize code
EMC science resources diluted by software engineering
25
NCEP, ECMWF, UKM ComparisonOrganizational Factors
ECMWF UKMET NCEP Impact
Simpler chain of command (ECMWF Director to Council)
Single management chain for operations & development
Large management chain above EMC (NWS HQ, NOAA…)
Research less coordinated with NOAA
Dilution of EMC management resources; competition within NOAA for resources
Does not have direct forecast responsibilities
Forecast divisions & Field Offices
NCEP Service Centers, Forecast regions and local offices
Internal NWS competition for resources
26
NCEP, ECMWF, UKM Comparison
Scientific Development &
Community Relationships
ECMWF UKMET NCEP Impact
Operations drives research
Operations drives research
Weak influence over research community
Little directed research to benefit operations; difficult transition of research to ops
Recruits best scientists in Europe and U. S. – recruits U. S. scientists regularly
Strong University collaborations (e.g. Reading U.; consortium for research aircraft)
NCEP has little success recruiting top level U. S. scientists; with exceptions, NCEP community relationships weak
Easier to recruit lower level scientists who require more management; best scientists direct many projects
27
Outreach (cont)
• NASA-NOAA-DOD Joint Center for Satellite Data Assimilation– Global wx: GMAO– Radiative transfer: NOAA/NESDIS, AER, U.
Wisc.– Ocean data assimilation: U Md– Land surface modeling & data assim:
NASA/HSB, Princeton U, U Wash.
28
Outreach (cont)
– WRF• Mesoscale wx (NAM, 2006): NOAA/FSL, NCAR, UOK, etc
– WRF-ARW & WRF-NMM are “5 km” models in NCEP operations
– WRF-ARW members in Short-Range Ensemble Forecast (SREF) Fall ’05
• Hurricane (2007): URI, NOAA/AOML• Rapid refresh (2007): NOAA/FSL• Code convergence for mesoscale forecast systems• SREF model diversity can be managed with minimum cost
– Climate Test Bed• S/I: GFDL, NASA/GMAO• Unified forecast system
– GFS: NOAA/FSL, U. Wisc. – hybrid coordinate model– Gridpoint Spectral Interpolation (GSI) analysis
29
Resource Comparison
• Ingredients for Improved Numerical Forecast Systems– Balance between
• Observations• Data Assimilation & Model technology• Computing resources
– Processor growth equal to Moore’s Law
– On-line disk proportional to processor capability
– Archive proportional to processor capability
– System support proportional to
» Number of computers
» Number of users
• Computing resources applied to– Operations
– Integration and Testing upgrades
30
Computing ComparisonsInternational Operational Weather & Climate
Forecast Centers2005-2006
WMO Survey (Majewski, 2005)
Center (vendor, architecture)MP=Massively Parallel
Peak Power (TF)
Throughput (TF)
NCEP (IBM, MP) 16 1.0
UKMET (NEC, vector) 5 1.5
ECMWF (IBM, MP) 36.5 2.2
China (IBM, MP) 21 1.3
Korea (Cray, vector) 18 5.4
Japan (Hitachi, vector) 28 8.4
31
Comparison of ECMWF and NCEP Operational Computing
October 2004
ECMWF NCEP
Processors 2 x 2176 2 x 1280
Speed 7.6 Gf 6.8 Gf
Sustained (6%) 2 x 1 Tf 2 x 0.5 Tf
Budget Cpu - $10 M
Tape,silo ~ $3.5
$11 M for all
32
EMC Mission
In response to operational requirements:• Maintain the scientific correctness and integrity of operational forecast
systems– Adapt to format changes and other changing operational requirements– Adapt to new computing hardware– Monitor and ensure the integrity of operational observing systems
• Enhance (Test & Improve) Numerical Forecasts Through Advanced– Data assimilation techniques– Model physics (parameterizations)– Numerical methods– Computational efficiency
• Transition and Develop Operational Numerical Forecast Systems for:– Weather prediction (domestic, global, 1-15 days)– Ocean prediction (daily to annual, coastal to global)– Climate prediction (seasonal to inter-annual)
Transition and Develop: transform & integrate code, algorithms, techniques from research status to operational status on NCEP computers
Enhance: Test and improve NCEP’s numerical forecast systems via scientific upgrades, tuning, additional observations, in response to user requirements
Maintain: Modify current operational system to adapt to ever-present external changes
33
FY05 EMC Budget
ORF
NOAA/HPCC
NOAA/Other
FAA
USN/ONR
NASA
DOE
Non-Navy DOD
ORF
NOAA/HPCC
NOAA/Other
FAA
USN/ONR
NASA
DOE
Non-Navy DOD
Kelly report (2000) recommendation: 75% ORF, 25% “soft”2002 budget supplement and adjustment: $2.8 M
Total: $17.5 M
<200 22
201-500
13
501-800
3
>801 3
Total 41
Funding Sources
34
Human Resource Comparison
• UKMET twice NCEP for Global & Mesoscale development• ECMWF 80% more than NCEP for Global development• ECMWF Ops same as NCEP ops• ECMWF covers computational• efficiency and porting to new
architecture
33
175.75
55.75
0
0
20
40
60
80
100
120
140
160
180
200
NCEP DEV (G&M) UK DEV (G&M)
Contractors
Civil Servants
42
17
32
24
0
10
20
30
40
50
60
70
80
ECMWF DEV Global Only NCEP DEV Global Only
Contractors
Civil Servants
Global & Mesoscale Dev Global Dev Only
7482
29 14
0
20
40
60
80
100
120
NCEP OPS ECMWF OPS
Contractors
Permanent
OperationsUKMET ECMWF
ECMWFNCEP
NCEPNCEP
35
Science plan for catching up• Goal: to produce the highest forecast scores by 2010
– Synoptic scale forecasts– QPF– Hurricanes– Aviation– Marine & land transportation– Week 2 to S/I climate
• Advanced data assimilation methods– Better use of time dimension– Improved background covariances
• Flow dependence• Ensemble methods
– New development (with JCSDA)• Clouds & precipitation • Snow, Ice & polar regions• Land & ocean surface
– Adjoint of analysis system for improved tuning & understanding (with NASA)
36
• Improved diagnostic analysis– Increased case study analysis– Work on “bust” cases– Greater effort on total system tuning
• Improved scientific development– Eddy simulation models* to advance PBL, stratus,
stratocumulus parameterizations– Cloud resolving models* to advance cumulus and
cloud fraction parameterizations– ECMWF, UKMET, NOGAPS initial states with GFS
• Higher resolution• Ocean-Atmosphere-Land-Ice coupling
Science plan for catching up (cont)
* Currently done by UKMET
37
Science plan for catching up (cont)
• Enhanced ensemble systems– Data assimilation– Postprocessed, downscaled products– International ensemble system
• Enhanced community collaborations & outreach– Outreach
• Education on best use of products +
• Regular Workshops+
– Full involvement in• International Model intercomparison projects• Field experiments+
– Vigorous Visiting Scientist Program– WRF, global (weather & S/I climate) systems– USWRP, NSF research support
+ Currently done by ECMWF
38
Science plan for catching up (cont)
• Single forecast system– Applicable to global & mesoscale
(nonhydrostatic)
• Software engineering group– Design systems which are easier to maintain– Improved software efficiency (so scientists
don’t have to do it)
39
Organizational & Political Factors• Organizational Factors
ECMWF UKMET NCEP ImpactSimpler chain of command (ECMWF Director to Council)
Single management chain for operations & development
Large management chain above EMC (NWS HQ, NOAA…)
Dilution of EMC management resources; competition within NOAA for resources
Does not have direct forecast responsibilities
Forecast divisions & Field Offices
Forecast divisions and WFOs Internal NWS competition for resources
Management makes commitment to scientific plan, obtains funds
Management makes commitment to scientific plan, obtains funds
NWP needs are lost in the budget process (NWS, NOAA, DOC, OMB, Congress). Initiatives have low success rate. No internal reallocation within NWS.
Reliance on soft money to expand and maintain capabilities
Operations department takes major role in optimizing, reviewing code
Role of Operations Department unknown
Operations department (NCO) does not review or optimize code
EMC science resources diluted by software engineering
Experienced staff culled from best of European Weather Services; Europeans better prepared in math, physics
Entry level positions require years of training; Europeans better prepared in math, physics
Entry personnel unfamiliar with operational NWP Center; “Black box” modelers require 1-3 years training
Greater spinup time for new employees
57% “permanent”; 43% contractors Higher, tax free salaries
100% Civil Servants 38% Civil Servants; 62% contractors
Increased management responsibilities on
Civil Servants
40
Organizational & Political Factors (cont)
• Scientific Development & Community Relationships
ECMWF UKMET NCEP Impact
Operations drives research
Operations drives research
Weak influence over research community
Little directed research to benefit operations; difficult transition of research to ops
International reputation & prestige
Some excellent scientific leaders
Scientists well recognized & respected internationally but not nationally, in NOAA or NWS
Little respect & recognition of EMC’s mission & capabilities; continually fighting critics
Recruits best scientists in Europe and U. S. – recruits U. S. scientists regularly
Strong University collaborations (e.g. Reading U.; consortium for research aircraft)
NCEP has little success recruiting top level U. S. scientists; with exceptions, NCEP – OAR relationships weak
Easier to recruit lower level scientists who require more management; best scientists direct many projects
41
ECMWF – NCEP(EMC,NCO, OD)comparison for global wx & climate
ECMWF NCEP
Total Employees 206 151
Ops employees (NCO) 96 101
Scientific staff 74 41
Director & infrastructure 36 9
Total budget ~$54 M $52.7* M
* Clearly overestimated: NCEP OD, NCO + EMC (Global Wx & Climate)
42
Human Resource Comparison (cont)
Numerical Weather Prediction Development Personnel
0
10
20
30
40
50
60
70
80
NCEP UK
Satellite Data Assimilation
Global & Mesoscale ModelDevelopment
Forecast System Maintenance
Ensemble Development
Ocean & Climate Dev
Miscellaneous
• UKMET three times more than NCEP for Satellite Data Assimilation
43
EMCNCO
R&D Operations Delivery
Criteria
Transition from Research to Operations
Requirements
EMC
NCEP’s Role in the Model Transition Process
OPS Life cycleSupport
Service Centers
NOAAResearch
Concept of Operations
ServiceCenters
Test BedsJCSDA
CTBWRF/Model
JHT
User
Ob
serv
atio
n
Sys
tem
Launch List – Model Implementation Process
FieldOffices
Effort
EMC and NCO have critical roles in the transition from NOAA R&D to operations
Other Agency
&International
44
EMC
R&D Operations Delivery
Criteria
Requirements
OPS Life cycleSupport
Service Centers
Concept of Operations
User
Ob
serv
atio
n
Sys
tem
6. EMC Pre-Implementation
Testing (Packaging and Calibration)
7. NCO Pre-Implementation
Testing
8. ImplementationDelivery
5. Level II:-Preliminary
Testing(DA/Higher Resolution)
4. Level I:-Preliminary
Testing(Lower Resolution)
3. Interface with Operational Codes
2. Code/Algorithm Assessment and/or
Development
1. Identified for Selection
1 2 3 4 5 6 7 8
Launch List – Model Implementation Process
NCEP’s (Modeling) Transition to Operations: Focus on EMC and NCO
NCO EMC
Effort
Test Beds
45
Code/Algorithm Assessment and/or Development
Transition Steps (Modeling)
Identification for Selection1
2
Interface with Operational Codes3
Level I: Preliminary Testing (Lower Resolution)4
Level II: Preliminary Testing (DA/Higher Resolution)5
EMC Pre-Implementation Testing (Packaging/Calibration)6
NCO Pre-Implementation Testing7
Implementation/Delivery8
46
0.5
0.55
0.6
0.65
0.7
0.75
0.8
0.85
0.9
Jan Feb Mar Apr May
NCEP-O NCEP-Y ECMWF UKMET
Anomaly correlation for 5-day forecasts of 500hPa geopotential height
0.50.550.6
0.650.7
0.750.8
0.850.9
0.95
NCEP-O NCEP-Y ECMWF UKMETNorthern Hemisphere (20N-80N)
Southern Hemisphere (20S-80S)
O P E U O P E U
ImprovementFrom latest
GFSImplementation
(P)
47
NOAA Planning & Resource Allocation
• Example of new resources for expanded mission– Air Quality
• Contractor personnel• Computing supplement• NWS HQ management• EMC management resources lacking
• NOAA Planning, Programming, Budgeting and Execution System (PPBES)– Environmental Modeling Program (EMP)– Addresses resources vs. forecast requirements
• Human• Computing• Observational
48
Additional Research Computing
• Former NCEP operational computer– 1/3 current operational capability– Allocated to 3 major projects
• Satellite data assimilation• Climate forecast development• Advanced modeling (WRF, global)
• New NOAA “research” computer in procurement– October 2006 delivery– Replaces former NCEP operational computer
49
NCEP Global Model Strategy & ESMF
• Concept of operations– Single system for global and regional models– Performance permitting
• Migration to single model or• Multiple dynamics and physics options in single structure
– Single verification, observations data base obeying WMO standards
– Single analysis code– All components ESMF compatible
• Enables multiple models and standard for coupling models• Decreases code maintenance and code reuse
• Overall positive experience at Met Office & ECMWF
50
The Environmental Forecast Process
Observations
Analysis
Model Forecast
Post-processed Model Data
Forecaster
User (public, industry…)
NumericalForecastSystem
Data Assimilation
