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NCEP Update: Review of Progress in Operational
Weather, Climate and Ocean Forecasts
“Where America’s Climate, Weather and Ocean Prediction Services Begin”
Louis W. UccelliniDirector, NCEP
University of Maryland
November 2, 2006
2
Overview
• Define NCEP• “Seamless Suite” of forecast products: climate/weather linkage• Recent Advances
– Seasonal to Interannual/Climate Forecast System– Ocean Prediction/HYCOM– “Medium range” Days 4-7/North American Ensemble Forecast System– Days1-3: Winter Weather Desk/Short-Range Ensemble Forecast System– Joint Center for Satellite Data Assimilation
• Performance Metrics• Future
– Community Models– Multi-model Ensembles
• New building– NOAA Center for Weather and Climate Prediction (Maryland)
3
Define NCEP
4
Research, Development and Technology Infusion
Respond & Feedback
Respond & Feedback
The Path to NOAA’s Seamless Suite of Products and Forecast Services
IBM Supercomputer at Gaithersburg, MD Computer Center
FeedbackFeedback
DistributeDistribute
LocalOfficesLocal
OfficesCentral
GuidanceCentral
GuidanceProcessProcess
ObserveObserve
Products & Forecast Services
To Serve Diverse Customer Base
e.g., National Association of State Energy Officials,
Emergency Managers, Water Resource Agencies, …
NCEP
5
The Environmental Forecast Process
Observations
Analysis
Model Forecast
Post-processed Model Data
Forecaster
User (public, industry…)
NumericalForecastSystem
Data Assimilation
6
NCEP Supports the NOAA Seamless Suite of Climate Weather and Ocean Products
Space Environment CenterAviation Weather Center NCEP Central Operations
Climate Prediction Center Environmental Modeling Center Hydrometeorological Prediction Center Ocean Prediction Center
Tropical Prediction Center
Vision: Striving to be America’s first choice, first alert and preferred partner for climate, weather and ocean prediction services.
Organization: Central component of NOAA National Weather Service
Total FTE: 430161 Contractors/47 Visitors
Mission: NCEP delivers analyses, guidance, forecasts and warnings for weather, ocean, climate, water, land surface and space weather to the nation and the world. NCEP provides science-based products and services through collaboration with partners and users to protect life and property, enhance the nation’s economy and support the nation’s growing need for environmental information.
Storm Prediction Center
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• Civil Service Positions– 430 civil servant positions
– Average 32 hires/year at all levels
– 2-4 entry-level hires/year
• Contract Positions– Average 140 contractors/year (over last 4 years)
– Currently have 161 contractors
– Approximately 28 contractor vacancies/year
• Student Programs– Average number of student interns - 6 (SCEP/STEP)
http://www.weather.gov/eeo/StudentResearchOpportunities.htm)
– 16 Summer hires in 2006 through various programs (http://epp.noaa.gov/ , http://www.oesd.noaa.gov/Hollings_info.html )
NCEP Employment Summary
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What Does NCEP Do?
Model Development, Implementation and Applications for Global and Regional Weather, Climate, Oceans and now Space WeatherInternational and National Partnerships in Ensemble ForecastsData Assimilation including the Joint Center for Satellite Data AssimilationSuper Computer, Workstation and Network OperationsTransition Test Beds Being Developed throughout NCEP
“From the Sun to the Sea”
• Solar Monitoring, Warnings and Forecasts
• Climate Forecasts: Weekly to Seasonal to Interannual
• El Nino – La Nina Forecast
• Weather Forecasts to Day 7
• Hurricanes, Severe Weather, Snowstorms, Fire Weather
• Aviation (Turbulence, Icing)
• High Seas Forecasts and Warnings
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Service – Science Linkagewith the Outside Community
• EMC WRF Developmental Test Center, Joint Center for Satellite Data Assimilation
• CPC Climate Test Bed
• TPC Joint Hurricane Test Bed
• HPC Hydrometeorological Test Bed*
• SPC Hazardous Weather Test Bed with NSSL
• SEC Solar Test Bed
• AWC FAA Aviation Test Bed with NCAR RAP*
• OPC linked with EMC’s Marine Modeling and Analysis Branch
* Under development
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Seamless Suite of Forecast Products Climate-Weather Linkage
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Climate/WeatherLinkage
Week 2 Hazards Assessment
Forecast Forecast UncertaintyUncertaintyForecast Forecast UncertaintyUncertainty
MinutesMinutes
HoursHours
DaysDays
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NOAA Seamless Suite of ForecastProducts Spanning Climate and Weather
CPC
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WatchesWatches
ForecastsForecasts
Threats Assessments
GuidanceGuidance
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Fire
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He
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He
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TPCOPCHPC
SECAWCSPC
Service Center Perspective
Winter Weather Desk Days 1-3Tropical Storms to Day 5Severe Weather to Day 3
• •
NDFD, Days 4 -7
6-10 Day Forecast
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Climate/WeatherLinkage
Forecast Forecast UncertaintyUncertaintyForecast Forecast UncertaintyUncertainty
MinutesMinutes
HoursHours
DaysDays
1 Week1 Week
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NOAA Seamless Suite of ForecastProducts Spanning Climate and Weather
North American Ensemble Forecast System
Climate Forecast System
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WatchesWatches
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GuidanceGuidance
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of
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of
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Hyd
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Hyd
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Fire
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He
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He
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He
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Short-Range Ensemble Forecast Ocean Model
Hurricane Model
Global Forecast System
North American Forecast
Rapid Update Cycle for Aviation
Dispersion Models for DHS
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GFS
CFS
GFDL
SREF
NAM – WRFNMM
NOAH Land Surface Model
Dispersion
Air Quality
2007 NCEP Production Suite Atmospheric Model Dependencies
Forecast
GlobalData
Assimilation
WRF-NMMWRF-ARWETARSM
L D A S
Sev Wx
WRF-NMMWRF-ARW
NAEFS
NDAS
Rapid Update Cycle
Ensemble Hurricane
Global
Climate Regional
MOM3
HYCOMOcean
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Computing Capability
Commissioned/Operational IBM Supercomputer in Gaithersburg, MD (June 6, 2003)
Primary Weather Primary Weather $13.9 M$13.9 M
Primary Climate Primary Climate $5.3 M$5.3 M
Backup Backup $7.2 M$7.2 M
Total: Total: $26.4 M$26.4 M
•Receives Over 210 Million Global Observations Daily•Sustained Computational Speed: 1.485 Trillion Calculations/Sec•Generates More Than 5.7 Million Model Fields Each Day•Global Models (Weather, Ocean, Climate)•Regional Models (Aviation, Severe Weather, Fire Weather)•Hazards Models (Hurricane, Volcanic Ash, Dispersion)•3x upgrade scheduled for 2006 4th Q delivery
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Recent Advances
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Forecast Forecast UncertaintyUncertaintyForecast Forecast UncertaintyUncertainty
MinutesMinutes
HoursHours
DaysDays
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2 Week2 Week
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North American Ensemble Forecast System
Climate Forecast System
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WatchesWatches
ForecastsForecasts
Threats Assessments
GuidanceGuidance
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Short-Range Ensemble Forecast HYCOM Ocean Model
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The NCEP coupled Climate Forecast System (implemented August 24, 2004)
1. Atmospheric component• Global Forecast System 2003 (GFS03)
• T62 in horizontal; 64 layers in vertical
• Recent upgrades in model physics Solar radiation (Hou, 1996)
cumulus convection (Hong and Pan, 1998)
gravity wave drag (Kim and Arakawa, 1995)
cloud water/ice (Zhao and Carr,1997)
2. Oceanic component• GFDL MOM3 (Pacanowski and Griffies, 1998)
• 1/3°x1° in tropics; 1°x1° in extratropics; 40 layers
• Quasi-global domain (74°S to 64°N)
• Free surface3. Coupled model
• Once-a-day coupling
• Sea ice extent taken as observed climatology
4. Calibrated on past 38 years
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Climate Forecast System Availability
7 day average centered on March 8
• Real-time 2x daily, 9-month forecasts, monthly ensemble of 40-60 members.
• 15-member reforecasts per month (1981–2005)– Calibration– Skill estimates– Analog and statistical forecasts
• The website for real time data retrieval is at: ftp://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/MT.cfs_MR.fcst
• The climatological data is at: ftp://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/MT.cfs_MR.clim/
• Complete documentation available at: http://www.emc.ncep.noaa.gov/gmb/ssaha/cfs_data/cfs_data.pdf
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Climate Test Bed
Climate Climate Test BedTest Bed
Climate Community
Climate Community
Research &Development
Research &Development
NOAA Climate
ForecastOperations
NOAA Climate
ForecastOperations
Mission:Mission: to accelerate the transition of research and development into improved NOAA operational climate forecasts, products, and applications.
THE NOAA CLIMATE TEST BEDTHE NOAA CLIMATE TEST BED
Mission:Mission: To accelerate the transition of scientific advances from the climate research community to improved NOAA climate forecast products and services.
Priorities:• Improve Climate Forecast System
• Assess Multi-Model Ensemble Prediction System
• Fully Utilize Climate Reanalysis – An Ongoing Analysis of the Climate System
• Develop Climate Forecast Products for Decision Support
http://www.cpc.ncep.noaa.gov/products/ctb/http://www.cpc.ncep.noaa.gov/products/ctb/
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Current Projects By Programmatic Theme:
1)1) NOAA/NCEP Climate Forecast System ImprovementsNOAA/NCEP Climate Forecast System Improvements
Ocean Component of the NCEP ENSO CFS (PI: McPhaden, PMEL) Improvement of the GODAS at NCEP (PI’s: Xue and Behringer, NCEP) Using Initial Tendency Errors to Reduce Systematic Errors (PI: Delsole, COLA) Development of Neural Network Emulations of Model Physics for CFS (PI: M. Fox-Rabinovitz, UMD) NCEP Component of the NOAA Core Project for GAPP (PI: K. Mitchell, NCEP)
The NAME Climate Process Team (PI: J. Schemm, NCEP)
2)2) Multi-Model Ensemble Prediction SystemMulti-Model Ensemble Prediction System
Infrastructure for Multi-model Ensembles at the NOAA CTB (PI’s: Leetmaa, GFDL; Lord, NCEP)Explore MME with international operational centers
3)3) Climate Reanalysis – An Ongoing Analysis of the Climate SystemClimate Reanalysis – An Ongoing Analysis of the Climate System Regional Climate Data Assimilation System (R-CDAS) / NAME Data Impact (PI: K. Mo, NCEP)
4)4) Climate Forecast Products for Decision SupportClimate Forecast Products for Decision Support
Consolidation of Multi method Seasonal Forecasts at CPC (PI: van den Dool, NCEP) A Drought Monitoring and Early Warning System for the United States (PI: K. Mo, NCEP)
5) Assess development work, upgrade the CFS in FY10 and improve CFS products.Assess development work, upgrade the CFS in FY10 and improve CFS products.
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Ocean Prediction
• NCEP to provide “backbone” support for operational delivery of ocean model forecasts – In response to NOAA Science Advisory Board Report
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Forecast Forecast UncertaintyUncertaintyForecast Forecast UncertaintyUncertainty
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Satellite(AVHRR, JASON, QuikSCAT)
In situ(ARGO, Buoys, Ships)
OCEAN DATA ASSIMILATION
RT-OFS-GODAENOPPEMC
CFS-GODASNCO/ODA
EMC NOPP-JPL (ECCO)
OPNL OCEAN FORECASTS
Climate Forecast System Real-Time Ocean Forecast System
Data Cutoff
CFS: 2 week data cutoff RTOFS: 24 hour data cutoff
Shared history, coding, and data
processing
MOM-3 MOM-4 HOME HYCOM HOME
NASA-NOAA-DODJCSDA
AMSR, GOES,AIRS, JASON, WindSat,
MODISAdvanced
ODA Techniques
Observations
CLIMATE FORECAST OCEAN FORECAST
http://cfs.ncep.noaa.gov/ http://polar.ncep.noaa.gov/ofs/
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Real-Time Ocean Prediction with HYCOM• Goal: to develop and implement 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)
•Implemented December 2005
Chesapeake Bay
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RT-OFSRT-OFSProductsProducts
http://polar.ncep.noaa.gov/ofs/
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North American Ensemble Forecast System
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Forecast Forecast UncertaintyUncertaintyForecast Forecast UncertaintyUncertainty
MinutesMinutes
HoursHours
DaysDays
1 Week1 Week
2 Week2 Week
MonthsMonths
SeasonsSeasons
YearsYears
NOAA Seamless Suite of ForecastProducts Spanning Climate and Weather
North American Ensemble Forecast System
Climate Forecast System
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WatchesWatches
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GuidanceGuidance
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em
Eco
syst
em
Eco
syst
em
Eco
syst
em
Sta
te/L
oca
l S
tate
/Lo
cal
Pla
nn
ing
Pla
nn
ing
Sta
te/L
oca
l S
tate
/Lo
cal
Pla
nn
ing
Pla
nn
ing
En
viro
nm
en
tE
nvi
ron
me
nt
En
viro
nm
en
tE
nvi
ron
me
nt
Flo
od
Miti
ga
tion
F
loo
d M
itig
atio
n
& N
avi
ga
tion
& N
avi
ga
tion
Flo
od
Miti
ga
tion
F
loo
d M
itig
atio
n
& N
avi
ga
tion
& N
avi
ga
tion
Ag
ricu
lture
Ag
ricu
lture
Ag
ricu
lture
Ag
ricu
lture
Re
serv
oir
Re
serv
oir
Co
ntr
ol
Co
ntr
ol
Re
serv
oir
Re
serv
oir
Co
ntr
ol
Co
ntr
ol
En
erg
yE
ne
rgy
En
erg
yE
ne
rgy
Co
mm
erc
eC
om
me
rce
Co
mm
erc
eC
om
me
rce
Benefits
Hyd
rop
ow
er
Hyd
rop
ow
er
Hyd
rop
ow
er
Hyd
rop
ow
er
Fire
We
ath
er
Fire
We
ath
er
Fire
We
ath
er
Fire
We
ath
er
He
alth
He
alth
He
alth
He
alth
Short-Range Ensemble Forecast HYCOM Ocean Model
30
North American Ensemble Forecast System
• Combines global ensemble forecasts from Canada & USA– Now:CAN 40/day out to 16 days, US – 56/day out to 16 days– ’07 – CAN 40/day out to 16 days, US – 80/day out to 16 days
• Generates products for– Intermediate users: forecasters at NCEP, WFOs, academia,
media, private sector, …– Specialized users: hydrologic applications in all three countries– End users: forecasts for public distribution
in US, Canada (MSC) and Mexico (NMSM)
• Future activities– Adding products (probabilistic in nature)– Incorporating ensemble data from
other centers (e.g., FNMOC)– Unified evaluation/verification procedures
International project to produce operational multi-center ensemble products
After bias correction
Raw ensemble
Probabilistic skill extended 1-3 days
31
NAEFS Products
• NAEFS basic product list– 11 functionalities
• Ensemble mean, spread, probabilities, etc.
– 50 variables• U,v,t,z,CAPE,
precip type, etc.– 7 domains
• Global, NH, NA, CONUS, SA, Caribbean, Africa• Over 600 products requested by users (will be supplied via
priority order)– Graphics
• Available on NAWIPS at NCEP Centers– Grids
• NAWIPS• ftp://ftpprd.ncep.noaa.gov/pub/data/nccf/com/grns/prod• NDGD in planning phase (Aug 07)
32
Short-Range Ensemble Forecast System
33
Forecast Forecast UncertaintyUncertaintyForecast Forecast UncertaintyUncertainty
MinutesMinutes
HoursHours
DaysDays
1 Week1 Week
2 Week2 Week
MonthsMonths
SeasonsSeasons
YearsYears
NOAA Seamless Suite of ForecastProducts Spanning Climate and Weather
North American Ensemble Forecast System
Climate Forecast System
Tra
nsp
ort
atio
nT
ran
spo
rta
tion
Tra
nsp
ort
atio
nT
ran
spo
rta
tion
Fo
reca
st
Lea
d T
ime
Fo
reca
st
Lea
d T
ime
Warnings & Alert Warnings & Alert CoordinationCoordination
WatchesWatches
ForecastsForecasts
Threats Assessments
GuidanceGuidance
OutlookOutlook
Pro
tect
ion
of
Pro
tect
ion
of
Life
& P
rop
ert
yL
ife &
Pro
pe
rty
Pro
tect
ion
of
Pro
tect
ion
of
Life
& P
rop
ert
yL
ife &
Pro
pe
rty
Sp
ace
S
pa
ce
Op
era
tion
Op
era
tion
Sp
ace
S
pa
ce
Op
era
tion
Op
era
tion
Re
cre
atio
nR
ecr
ea
tion
Re
cre
atio
nR
ecr
ea
tion
Eco
syst
em
Eco
syst
em
Eco
syst
em
Eco
syst
em
Sta
te/L
oca
l S
tate
/Lo
cal
Pla
nn
ing
Pla
nn
ing
Sta
te/L
oca
l S
tate
/Lo
cal
Pla
nn
ing
Pla
nn
ing
En
viro
nm
en
tE
nvi
ron
me
nt
En
viro
nm
en
tE
nvi
ron
me
nt
Flo
od
Miti
ga
tion
F
loo
d M
itig
atio
n
& N
avi
ga
tion
& N
avi
ga
tion
Flo
od
Miti
ga
tion
F
loo
d M
itig
atio
n
& N
avi
ga
tion
& N
avi
ga
tion
Ag
ricu
lture
Ag
ricu
lture
Ag
ricu
lture
Ag
ricu
lture
Re
serv
oir
Re
serv
oir
Co
ntr
ol
Co
ntr
ol
Re
serv
oir
Re
serv
oir
Co
ntr
ol
Co
ntr
ol
En
erg
yE
ne
rgy
En
erg
yE
ne
rgy
Co
mm
erc
eC
om
me
rce
Co
mm
erc
eC
om
me
rce
Benefits
Hyd
rop
ow
er
Hyd
rop
ow
er
Hyd
rop
ow
er
Hyd
rop
ow
er
Fire
We
ath
er
Fire
We
ath
er
Fire
We
ath
er
Fire
We
ath
er
He
alth
He
alth
He
alth
He
alth
Short-Range Ensemble Forecast HYCOM Ocean Model
34
Short Range Ensemble Forecast
21 members twice per day 87 hrs from 9 and 21Z Resolution 32km/60 levels Mean and spread charts
available for forecaster use Developing products on probability of snow and ice
accumulation http://wwwt.emc.ncep.noaa.gov/mmb/SREF/SREF.html
0.01” snow
35
SREF Upgrades
FY2006• Added six members twice per day (WRF ARW & WRF NMM) (Dec ‘05)
• Run SREF 4 times per day (03, 09, 15 and 21 UTC) (June, 2006)
• Implement Grid Based Bias Correction
• Improve Probabilistic verification
• Develop spread information
• Add WRF BUFR Files
• Implement ensemble mean BUFR files
36
850T (8/25/05-9/24/05)
0.5
0.7
0.9
1.1
1.3
1.5
1.7
1.9
2.1
2.3
2.5
9 15 21 27 33 39 45 51 57 63
Forecast Hours
rmse (
C)
15-mem
21-mem
12km NAM
Normalized Outlier of 850T (8/25/05-9/24/05)
10
12
14
16
18
20
22
24
9 15 21 27 33 39 45 51 57 63
Forecast Hours
chan
ce t
ruth
to
be
ou
t o
f en
sem
ble
ran
ge
(%)
15-mem
21-mem
Chance that truth is outside ensemble range
RMS Error
21 member
15 member
SREF Enhancement with 6 WRF-based Members
37
New Impact Graphics from SREF
• Probability event will last more than 12, 24, 48 hrs • Probability visibility will be reduced to 1/2, 1/4, or 1/8
mile in winter precip• Probability winter precip rate will be more than 1, 2, or
3" per hr • Probability road sensor will detect winter precip
(relative to normal) “snow on road”• Probability Blizzard Criteria will be met • Probability Freezing Rain .01" or more will accumulate
on any surface • Probability NWS Winter Storm Warning criteria will be
met (under construction)
http://www.hpc.ncep.noaa.gov/wwd/impactgraphics/
38
Time line: Sep 15 – April 1 Participants
NCEP HPC Provide SREF based Winter Wx guidance Collaborate with WFOs (Chat Room Technology)
WFOs All CONUS WFOs Use guidance from NCEP to produce coordinated Winter Storm Watches/Warnings
Products: http://www.hpc.ncep.noaa.gov/wwd/winter_wx.shtml 24 h probability (low, moderate, high) of meeting/exceeding 4”, 8”, 12”
snow, 0.25” freezing rain (for day 1, 2, 3) 72h Low tracks graphic and discussion
NWS Winter Weather Desk
39
40
12Z, Feb 10, 2006 12Z, Feb 11, 2006
12Z, Feb 12, 2006 12Z, Feb 13, 2006
Daily Weather Map Web Site - http://www.hpc.ncep.noaa.gov/dwm/dwm.shtml
41
42
≥ 4 inches
≥ 8 inches
≥ 12 inchesDay 2 Snow Accum ProbabilityValid 00Z Feb 12 - 00Z Feb 13
43
44
45
Regional Stats
ER WWE1
01-02’
WWE2
02-03’
WWE3
03-04’
WWD*
04-05’
WWD*
05-06’
# WFO 8 23 23 ALL ALL
POD .89 .90 .92 .92 .91
FAR .33 .30 .32 .30 .35
CSI .62 .65 M .66 .61
LT Warn 13 15 18 21 19
CR WWE1
01-02’
WWE2
02-03’
WWE3
03-04’
WWD
04-05’
WWD
05-06’
# WFO NA 8 33 ALL ALL
POD NA .90 .88 .92 .91
FAR NA .40 .45 .32 .38
CSI NA .57 .51 .65 .53
LT Warn NA 13 13 17 17
WR WWE1
01-02’
WWE2
02-03’
WWE3
03-04’
WWD
04-05’
WWD
05-06’
# WFO NA NA 10 ALL ALL
POD NA NA .88 .88 .86
FAR NA NA .27 .30 .36
CSI NA NA .67 .64 .58
LT Warn NA NA 14 16 16
SR WWE1
01-02’
WWE2
02-03’
WWE3
03-04’
WWD
04-05’
WWD*
05-06’
# WFO NA NA 11 ALL ALL
POD NA NA .92 .90 .85
FAR NA NA .38 .39 .48
CSI NA NA .59 .57 .48
LT Warn NA NA 9 9 11
* Oct - Mar
46Five Order of Magnitude Increase in Satellite Data Over Next Ten YearsFive Order of Magnitude Increase in Satellite Data Over Next Ten YearsFive Order of Magnitude Increase in Satellite Data Over Next Ten YearsFive Order of Magnitude Increase in Satellite Data Over Next Ten Years
Count
(Mill
ions)
Daily Satellite & Radar Observation Count
20001990 2010 2010-10%of obs
2002 100 M obs
2003-4 125 M obs
Level 2 radar data 2 B
2005 210 M obs
Joint Center for Satellite Data Assimilation
47
JCSDA Mission and Vision
• Mission: Accelerate and improve the quantitative use of research and operational satellite data in weather and climate analysis and prediction models
• Near-term Vision: A weather and climate analysis and prediction community empowered to effectively assimilate increasing amounts of advanced satellite observations
• Long-term Vision: An environmental analysis and prediction community empowered to effectively use the integrated observations of the GEOSS – and be ready for NPOESS at “Day 1” after launch
48
JCSDA Major Accomplishments• Common assimilation infrastructure at NOAA and NASA • Community radiative transfer model V2 released• Common NOAA/NASA land data assimilation system• Interfaces between JCSDA models and external researchers• Operational Implementations Include:• Snow/sea ice emissivity model – permits 300% increase in sounding data
usage over high latitudes – improved forecasts• MODIS winds, polar regions, - improved forecasts• AIRS radiances – improved forecasts• New generation, physically based SST analysis - Improved SST• Preparation for advanced satellite data such as METOP (IASI/AMSU/MHS),
DMSP (SSMIS), COSMIC GPS data, EOS AMSR-E, GOES-R • Impact studies of POES MHS, EOS AIRS/MODIS, Windsat, DMSP
SSMIS……. on NWP through EMC parallel experiments
49
Figure 3(b). 500hPa Z Anomaly Correlations for the GFS with (Ops.+AIRS) and without (Ops.) AIRS data, Northern hemisphere, January 2004
N. Hemisphere 500 mb AC Z 20N - 80N Waves 1-20
1 Jan - 27 Jan '04
0.6
0.65
0.7
0.75
0.8
0.85
0.9
0.95
1
0 1 2 3 4 5 6 7
Forecast [days]
An
om
aly
Co
rrel
atio
n
Ops
Ops+AIRS
50
Impact of AIRS increased spatial data density/improved QC(Snow, SSI/eo/April 2005/nw)
N. Hemisphere 500 mb AC Z 20N - 80N Waves 1-20
10 Aug - 20 Sep '04
0.75
0.8
0.85
0.9
0.95
1
0 1 2 3 4 5
Forecast [days]
An
om
aly
Co
rrel
atio
n Cntl AIRS
SpEn AIRS
51
Performance Metrics-- Models --
52
GFS Upgrade
GFS Upgrade
53
54
2001 2002 2003 2004 2005
0
5
10
15
20
25
30
JUL JAN JUL JAN JUL JAN JUL JAN JUL JAN JULN
um
be
r o
f H
its
(M
illi
on
s)
Popularity of NCEP Models Web Page
Comms Upgrade
2006
55
Performance Metrics-- Forecasters --
56
Impact of Models on Day 1 Precipitation Scores
0
0.05
0.1
0.15
0.2
0.25
0.3
0.3519
91
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
Th
reat
Sco
re
Human(HPC)
ETA
Linear(Human(HPC))Linear (ETA)
HPC Forecasters Add Value
Models provide basis for improvement Correlations
Of HPC with:
Eta: 0.99GFS: 0.74NGM: 0.85
(DOC GPRA goal)
57
58
Day 4 Gridded Temperature Forecast
Max Temp Min Temp
Valid November 6, 2006
59
NHC Atlantic 72 hr Track Forecast Errors
Advances RelatedTo USWRP
Major Upgrades in Global andHurricane Numerical models
60
In last 10 years, HPC forecasts have added 2 days of skill
Day 7
Day 5
Day 3
62
Future
• Community Models• Multi-Model Ensembles
63
Future
• Community models– Weather Research Forecast model
• Developmental Test Center (Boulder)– Outreach to academic community– Assessment of new model components
• Major implementation – replaced Eta in June 06
CMI
NCARARW
NCEPNMM
Explicit Cores(e.g., Hurricane, Dispersion, Aviation)
64
GFS
CFS
WRF
SREF
NAM - WRF
NOAH Land Surface Model
Dispersion
Forecast
GGSI
WRF-NMMWRF-ARWETARSM
L D A S
Sev Wx
WRF-NMMWRF-ARW
NAEFS
RGSI
Rapid Refresh WRF
EnsembleHurricane
Global
Climate Regional
MOM3
HYCOMOcean
Model Suite of the Future (2007-2008)
Chem WRFAir Quality
65
Multi-Model Ensembles Issue
• In 5-10 years will all forecasts be based on multi-model ensemble approach?• Climate Forecast System
• North American Ensemble Forecast System
• Short-Range Ensemble Forecast System
• Oceans
• Space Weather
• Answer(s) will have enormous implications for NCEP operational computer allocations
66
Multi-Model Ensembles
• Enormous implications for NCEP links to the research community
• How do we link all the players?
• Operational centers
• NCAR/NASA/DOE/Universities
• How do we link data assimilation infrastructure (all data types)?
• Ensemble-based Kalman Filter
• 3D or 4D Var
• How do we factor into transition process?
• Research to Operations AND Operations to Research
• Many issues will influence NCEP’s participation in THORPEX (Zoltan Toth, focal point)
67
NOAA Center for Weather and Climate Prediction
• Defined requirements for 268,762 RSF • Includes housing 850+ Federal employees, contractors, and
visiting scientists • 5 NCEP Centers• NESDIS research and satellite services• OAR Air Resources Laboratory
• Begin move to new facility September ’07; complete by Feb ’08
• Space for 40 visitors• Groundbreaking occurred
for March 13, 2006
68
NOAA Center for Weather and
Climate Prediction
NORTH
69
Summary
• NCEP spanning “Sun to the Sea”; many new programmatic areas (oceans, air quality, space weather…)
• Many science-service opportunities/challenges exist• NCEP is uniquely positioned to handle transition issues
from research to operations• Actively engaged with the research community
– Test beds– Experiments (NAME, THORPEX)– Other programs (USWRP, CLIVAR, …)
• Still consider NCEP to be an underutilized entity by the research community
70
Appendix
71
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 DTC
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 Agencies&
International
Forecast benefits, Efficiency, IT Compatibility, Sustainability
72
R&D
NCEP
Operations
User Community
Transition from
researchto
operations/applications
1. Large “volume” of R&D,funded through AOs,Agency Labs…
2 Smaller set of R&Dproducts suitable foroperations.
3. Systematic transition steps.
4. New products can servediverse and expandinguser community.
5. Delivery to diverse USERcommunity
Applying the “Funnel” to the Transition Process
1
2
3
4
NCEPis uniquelypositioned
to provide an operational
infrastructure for the
transition process
5
73
CDAS/Reanl vs GFSNH/SH 500Hpa day 5
Anomaly Correlation (20-80 N/S)
40
45
50
55
60
65
70
75
80
85
90
1960 1970 1980 1990 2000
YEAR
An
om
aly
Co
rrela
tio
n
NH GFS
SH GFS
NH CDAS/Reanl
SH CDAS/Reanl
74
75
Without skill mask
CFS SeasonalPrecip Forecast
(mm/month)
76
With skill mask
• If anomaly correlation between forecast and observed conditions over the 1982-2003 period is below 0.3, values are not shown
CFS SeasonalPrecip Forecast
(mm/month)
77
Without skill mask
CFS SeasonalTemp Forecast
(deg K)
78
With skill mask
• If anomaly correlation between forecast and observed conditions over the 1982-2003 period is below 0.3, values are not shown
CFS SeasonalTemp Forecast
(deg K)
79
GSI/GFS Impact studies: Preliminary Results (CHAMP)2-month cycling at T62L64
• There are some encouraging preliminary results. Before being able to assimilate the RO data in operations we need to:
– Understand the differences between the assimilation of N and BA. Why in some cases the assimilation of N results in a larger improvement than the assimilation of BA and visa versa?
– Understand the strengths and weaknesses of the GPS RO data and the model in weather analyses and forecasts. Why does the assimilation of N or BA degrade the forecasts in some cases?
• The sensitivity of the impact of GPS RO to model resolution, QC parameters and error characterization is under current study.
• The results of these experiments will accelerate the tuning for the assimilation of COSMIC data.
Cucurull et al. 2006, submitted to MWR
ControlRefractivity
Bending Angle
80
• The figures show the day-2 anomaly correlation scores for temperature at 300mb for the NH, Tropics and SH. Results for the control (COSM_CTL) and bending angle (COSM_BND) are indicated.
• Early results on the assimilation of COSMIC bending angles at NCEP show a good performance of the DA system.
• The same experiments could have assimilated observations of refractivity instead of bending angle.
• Results are encouraging and more data needs to be assimilated for further tuning and evaluation of the impact of the GPS RO in weather analyses and forecasts.
Early Results: COSMIC
81
S. Hemisphere 500 hPa AC Z 1 Jan - 15 Feb '04
0.6
0.65
0.7
0.75
0.8
0.85
0.9
0.95
1
0 1 2 3 4 5 6 7
Forecast [day]
An
om
aly
Co
rrel
atio
n
Control Windsat
Figure 2. The 500HPa Geopotential Anomaly Correlations versus forecast period for GFS forecasts using the operational data base without QuikSCAT data (Control) and using the operational database without QuikSCAT data but with WindSat data (WindSat) over the Southern Hemisphere.
82
NATIONAL HURRICANE CENTER ATLANTIC TRACK FORECAST ERRORS
NATIONAL HURRICANE CENTER ATLANTIC TRACK FORECAST ERRORS
12 24 36 48 72 96 120
Forecast Period (hours)
0
100
200
300
400
500
Err
or
(nau
tica
l mile
s)
1964-1973
1984-1993
1974-1983
1994-2003
2003-2005
23 May 2006
