Transcript NAEFS and NCEP Global Ensemble Yuejian Zhu and Zoltan Toth NOAA/NWS/NCEP

NAEFS and NCEP Global Ensemble
Yuejian Zhu and Zoltan Toth
Environmental Modeling Center
NOAA/NWS/NCEP
Acknowledgements:
B. Cui, R. Wobus, D. Hou, M. Wei, M. Charles,
M. Pena, J. Du, M. Iredell and S. J. Lord EMC
J. Carr, B. Gorden, C. Magee NCO
E. Olenic, D. Unger and D. Collins CPC
A. Methot N. Gagnon and L. Poulin CMC/MSC
M. Sestak FNMOC
Presentation for 4th Ensemble User Workshop
May 13th 2008
Outlines
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NAEFS History and Milestones
GEFS, NAEFS and THORPEX
Review Major Implementation (FY07)
Review NAEFS Products (FY07)
Statistical Downscaling
Ensemble Data Distribution Information
GEFS Major Implementation Plan (FY08)
NAEFS Product Upgrade Plan (FY08)
NAEFS Expansion and Future Plan
NAEFS History and Milestones
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February 2003, Long Beach, CA
– NOAA / MSC high level agreement about joint ensemble research/development work
(J. Hayes, L. Uccellini, D. Rogers, M. Beland, P. Dubreuil, J. Abraham)
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May 2003, Montreal (MSC)
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November 2003, MSC & NWS
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CMC/GEFS increasing ensemble membership from 16 to 20 per cycle
December 2007, NWS
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NCEP/GEFS increasing ensemble membership from 14 to 20 per cycle
July 2007, MSC
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3rd NAEFS Workshop
March 2007, NWS
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1st Operational Implementation
• Bias correction
• Climate anomaly forecasts
June 2006, Montreal (MSC)
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Inauguration ceremony & 2nd NAEFS Workshop
• Leaders of NMS of Canada, Mexico, USA signed memorandum
• 50 scientists from 5 countries & 8 agencies
May 2006, MSC & NWS
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Initial Operational Capability implemented at MSC & NWS
November 2004, Camp Springs
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Executive Review
September 2004, MSC & NWS
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1st draft of NAEFS Research, Development & Implementation Plan complete
May 2004, Camp Springs, MD (NCEP)
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1st NAEFS Workshop, planning started
NAEFS adding new production for CONUS
September 2008, MSC, NWS
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Follow-up implementations-Improved and expanded product suite
GEFS, NAEFS and THORPEX
• NCEP Global Ensemble Forecast System (GEFS) is part of
NAEFS
• NAEFS is combining NCEP and CMC global ensemble
• THORPEX is the research project:
– Provides framework for transitioning research into operations
– Prototype for ensemble component of THORPEX legacy forecast system:
Global Interactive Forecast System (GIFS)
THORPEX Interactive Grand
Global Ensemble (TIGGE)
Transfers
New methods
Articulates
operational needs
North American Ensemble
Forecast System (NAEFS)
Review NAEFS Implementation (FY07)
• NAEFS: NCEP/GEFS.
– Increasing membership from 14 to 20 members per cycle.
• Tuning initial perturbations.
• Using 80 cold start initial perturbations (schematic map)
– From 24-h forecasts and many dates.
– To have large spread of sampling
– This change is intended to improve ensemble based
probabilistic forecast over all and to support NAEFS (North
American Ensemble Forecast System) project.
– Results:
• Improving probabilistic skills.
• Not much improvement for ensemble mean (expected).
Review NAEFS Implementation (FY07)
• NAEFS: CMC/GEFS
– Improvement of the data assimilation component
• Horizontal resolution is increased from 1.2 to 0.9 degree
• The 24 different configuration of the GEM model are introduced instead of
one to produce the trial fields.
• Trial fields at 3, 4.5, 6, 7.5 and 9-h allow time interpolation toward
observation – become a 4-D data assimilation
– Increasing the membership
• from 16 to 20 per cycle, two cycle per day
– Modification to the forecast model
• Now only one dynamical core: GEM (SEF is dropped)
• Horizontal resolution is increased from 1.2 to 0.9 degree
• Addition of stochastic perturbation of the physical tendencies as in Buizza et
al (1999) (random number between 0.5 and 1.5)
• An stochastic kinetic energy back-scattering parameterization is used as in
Shutts (2005)
• The physical parameterization package was extended to include the Kain &
Fritsch deep convection scheme and the Bougeault-Lacarrere mixing length
formulation (see Table for details)
NAEFS current configurations
NCEP/GEFS
CMC/GEFS
Model
GFS
GEM
Initial uncertainty
ETR
ETKF
Model uncertainty
None
Yes
Tropical storm
Relocation
None
Daily frequency
00,06,12 and 18UTC
00 and 12UTC
Hi-re control
(GFS)
T382L64 (d0-d7.5)
T190L64 (d7.5-d16)
None
Low-re control
(ensemble control)
T126L28 (d0-d16)
00,0612 and 18UTC
~100km and L28
00 and 18UTC
Membership
Perturbed members
20 for each cycle
Multi-model/physics
20 for each cycle
Forecast length
16 days (384 hours)
16 days (384 hours)
Last implementation
March 27th 2007
July 10th 2007
Review NAEFS Product Upgrading (FY07)
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CMC web products
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http://www.meteo.gc.ca/ensemble/index_naefs_e.html
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NCEP web products for NCEP/GEFS (Plan for NAEFS 1Q/2009)
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http://www.nco.ncep.noaa.gov/pmb/nwprod/analysis/
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Temperature Anomaly: Day 8 to 14 Outlooks
EPSgrams for cities of Canada, Mexico and USA
Ensemble mean and standard deviation charts
Maps of probabilities of occurrence of several weather events
Spaghetti Charts for 200hPa, 500hPa height and MSLP
Mean, spread and vorticity for 500hPa, 700hPa and 850hPa height
Mean and spread for 500hPa, 700hPa, 850hPa and 2-m Temperature, 10-m winds
Dominate precipitation types
NCEP/EMC web products (experimental)
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http://wwwt.emc.ncep.noaa.gov/gmb/ens/NAEFS/NAEFS-prods-NCEP.html
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Climate anomaly for 10%, 50% and 90% 2-meter temperature
QPF/PQPF maps, side by side comparison
Bias comparison maps which include
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NCEP raw ensemble mean bias and accumulated difference between GDAS and CDAS
NCEP bias corrected ensemble mean bias
CMC control member bias
CMC bias corrected control member bias
NCEP/CPC week-2 web products (experimental)
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http://www.cpc.ncep.noaa.gov/products/predictions/short_range/NAEFS/Outlook_D264.0
0.php
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NAEFS 8-14 days guidance for
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2-meter temperature
500hPa height
Review NAEFS Product Upgrading (FY07)
(December 4th 2007)
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Bias corrected GFS forecast
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Combine bias corrected GFS and ensemble forecast
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Use the same algorithm as ensemble bias correction
Up to 180 hours (method and verify statistics)
Dual resolution ensemble approach for short lead time
Adjustable weight coefficient
GFS has higher weights at short lead time (figs)
NAEFS new products (example, verification, seasonal variation)
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Combine NCEP/GEFS (20m) and CMC/GEFS (20m)
All bias corrected forecast
Consider the difference between NCEP and CMC’s analyses
Produce Ensemble mean, spread, mode, 10% 50%(median) and
90% probability forecast at 1*1 degree resolution
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Climate anomaly (percentile) forecasts also generated for ens. mean
Statistical downscaling
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Use RTMA as reference - NDGD resolution (5km), CONUS only
Generate mean, mode, 10%, 50%(median) and 90% probability
forecasts
Statistical downscaling for NAEFS forecast
• Proxy for truth
– RTMA at 5km resolution for CONUS region
• RTMA represents “Real Time Meso-scale Analysis”
– Variables
• surface pressure, 2-m temperature, and 10-meter U and V
• Downscaling vector
– Interpolate GDAS analysis to 5km resolution
– Compare difference between interpolated GDAS and RTMA
– Apply decaying weight (w=0.3) to accumulate this difference – downscaling
vector
• Downscaled forecast
– Interpolate bias corrected 1*1 degree NAEFS forecast to 5km resolution
– Add the downscaling vector to interpolated NAEFS forecast
• Application
– Ensemble mean, mode, 10%, 50%(median) and 90% forecasts
• Verification statistics for 2-meter temperature
– Mean absolute errors (maps, all forecast lead time)
– Probabilistic verification (CRPS)
– Comparing to NDFD and GMOS (absolute errors)
NAEFS Products Distribution
System
Current available products
Config.
1.deg 0-384h, every 6 hours, 20 members (NCEP) and 20 members (CMC), ens. control (NCEP and CMC)
Format
CCS
NCEP
FTPPRD
GRIB1 (and GRIB2, GIF images for web display)
NCEP: pgrba, pgrbb, pgrba_bc, pgrba_an, pgrba_wt, ensstat, ndgd
CMC: pgrba, pgrba_bc, pgrba_an, pgrba_wt, ensstat
NAEFS: ndgd, pgrba_an, pgrba_bc
ftp://ftpprd.ncep.noaa.gov/pub/data/nccf/com/gens/prod cd gefs.${yyyymmdd} for NCEP ensemble
1. pgrb2a (00, 06, 12 and 18UTC) (1.0 degree, all lead times, 1(c) + 20 (p))
2. pgrb2alr (00, 06, 12 and 18UTC (2.5 degree, all lead times, 1(c) +20 (p))
2. pgrb2b (00, 06, 12 and 18UTC) (1.0 degree, all lead times, 1(c) + 20 (p))
4. pgrb2blr (00 and 12UTC) (2.5 degree, all lead times, 1(c) + 20 (p))
5. ensstat (00UTC) (prcp_bc, pqpf and pqpf_bc files)
6. wafs (00 and 12UTC)
7. ndgd_gb2 (00, 06, 12, 18UTC) (CONUS-5km, all lead times and all probability forecasts)
ftp://ftpprd.ncep.noaa.gov/pub/data/nccf/com/gens/prod cd cmce.${yyyymmdd} for CMC ensemble
1. pgrba (00 and 12UTC) (1.0 degree, all lead times,1 control + 20 members)
ftp://ftpprd.ncep.noaa.gov/pub/data/nccf/com/gens/prod cd naefs.${yyyymmdd} for NAEFS products
1. pgrb2a_an (00, 12UTC) (1.0 degree, all lead times, anomaly for ensemble mean)
2. pgrb2a_bc (00,12UTC) (1.0 degree, all lead times, probabilistic forecasts)
3. ndgd_gb2 (00,12UTC) (CONUS-5km, all lead times, probabilistic forecasts)
TOC
ftp://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/ cd MT.ensg_CY.${cyc}/RD.${yyyymmdd} for NCEP only
1. PT.grid_DF.gr1_RE.high (00 and 12UTC) (Pgrba: 1.0 and 2.5 degree, 0-384 hrs, c + 10 (p))
2. PT.grid_DF.gr1_RE.low (00 and 12UTC) (Pgrbb: 1.0 degree, 0-84 hrs, 2.5 d, 90-384 hrs, c + 10 (p))
3. PT_grid_DF.bb
NOMADS
http://nomad5.ncep.noaa.gov/ncep_data/ for ftp: combined pgrba and pgrbb at 1 degree resolution, for all
ensemble members (c+14(p)) and all lead time (0-384 hours)
http://nomad5.ncep.noaa.gov/pub/gens/archive/ for http: combined pgrba and pgrbb at 1 degree resolution
NCEP/GEFS Major Implementation Plan (FY08)
• Using new GFS/GSI version??
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New radiation
New coordinates
New gravity wave drag
Configuration changes between GFS and GEFS (adv. And disadv.)
• Upgrade horizontal resolution from T126 to T190 for 20 perturbed forecasts
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4 cycles per day
Up to 180 hours
T126 from 180 hours , up to 384 hours (16 days)
Using 8th order horizontal diffusion for all leading time forecast
• Extended 16 days forecast to 31 days
– 00Z cycle only
– T126L28 resolution
– User request (for MJO prediction)
• Introduce ESMF (Earth System Modeling Framework) for GEFS
– Version 3.10
– allows concurrent generation of all ensemble members.
• Add stochastic perturbation scheme to account for model errors
– Increasing model spread
– Improving the forecast skills
NAEFS product upgrade plan (FY08)
• NAEFS data exchange
– Add approximately 15-23 new variables to current 51
pgrba for NAEFS data exchange (in discussion)
• Such as vertical shear, helicity, u,v, t, RH for 100, 50hPa, LH, SWR,
LWR at surface, and etc..
– Use GRIB2 format for data exchange
• Approximated 45-60m time saving
• New NAEFS downscaling products
– For Alaska region (~6km NDGD grids)
• Surface pressure, T2m, U10m and V10m
– Having new variables for both CONUS and Alaska regions
• Tman, Tmin, 10m wind direction and speed
• Dedicated line for NCEP and CMC NAEFS data
exchange
– DS-3 (sooner?)
– Time saving (high expectation)
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NAEFS Expansion and Future Plan
Plans to be coordinated with THORPEX
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Links with Phase-2 TIGGE archive and beyond (GIFS)
Expansion
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FNMOC (current status and future plan)
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ECMWF (current status)
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Apply to next computer
4 cycles per day
4/28 hind-casts for each cycle since 1979 (in discussion)
Using CFS reanalysis as initial conditions (T382L64 resolution)
Downscaling products
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Pending on RTMA availability
Extended variables and regions (Hawaii, Guam and Puerto Rico regions )
Statistical post-processing
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Enhance current bias correction method (mini-Bayesian, Krzystofowicz, UVA)
Bias correction for precipitation (jointed with pseudo-precipitation, Schultz ESRL)
Pending on hind-cast information for first and high moments bias correction
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Expressed interest, no detailed plans yet
Real-time generation of hind-cast at new GEFS resolution.
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Decision on going operational & possibly joining NAEFS - by 2008
KMA, CMA, JMA
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Start to collect ECMWF ensemble data from May 2008
Preliminary evaluation by May of 2009 (1 year evaluation period)
Operational adding bias corrected ECMWF ensemble to NAEFS (subject to improved performance)
UK Metoffice
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Experimental data exchange started from April 2008
Preliminary evaluation by end of 2008 (1 year evaluation period)
Operational implementation by summer 09 (subject to improved performance)
Full Bayesian
Apply to all model forecast variables
Verifications
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THORPEX LINKS
PRODUCT DEVELOPMENT
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Goals:
– Develop new numerical model applications
– Develop new product generation tools and products
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Participants / Contributions
– Scott Jacobs et al. (NCO)
• NAWIPS ensemble functionalities
– Richard Verret et al. (Meteorological Service of Canada, MSC)
• NAEFS web-based products
– David Unger et al. (CPC) and Richard Verret et al. (MSC)
• Week-2 NAEFS products
– Bob Grumbine (EMC)
• Sea ice ensemble application
– Dingchen Hou (EMC)
• River flow ensemble application
– Steve Silberberg, Binbin Zhou (NCEP)
• Aviation weather guidance
– Yuejian Zhu (NCEP)
• NAEFS coordination
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Supported partially by NOAA THORPEX program
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Thanks !!!
6 hours breeding cycle
6 hours breeding cycle
Old
New
Re-scaling
T00Z
6hrs
Re-scaling
Next T00Z
Up to 16-d
T00Z
56m
6hrs
Next T00Z
Up to 16-d
80m
Re-scaling
Up to 16-d
Re-scaling
T06Z
T06Z
56m
80m
Re-scaling
T12Z
56m
Up to 16-d
Re-scaling
T12Z
Up to 16-d
Up to 16-d
80m
Re-scaling
Re-scaling
T18Z
56m
BACK
T18Z
Up to 16-d
80m
Up to 16-d
Multi-model EPS for the assimilation
#
Deep convection
Surface scheme
Mixing length
Vertical mixing parameter
1
2
3
4
5
Kain & Fritsch
Oldkuo
Relaxed Arakawa Schubert
Kuo Symétrique
Oldkuo
ISBA
ISBA
force-restore
force-restore
force-restore
Bougeault
Blackadar
Bougeault
Blackadar
Bougeault
1.0
0.85
0.85
1.0
1.0
6
7
8
9
10
Kain & Fritsch
Kuo Symétrique
Relaxed Arakawa Schubert
Kain & Fritsch
Oldkuo
force-restore
ISBA
ISBA
ISBA
ISBA
Blackadar
Bougeault
Blackadar
Blackadar
Bougeault
0.85
0.85
1.0
0.85
1.0
11
12
13
14
15
Relaxed Arakawa Schubert
Kuo Symétrique
Oldkuo
Kain & Fritsch
Kuo Symétrique
force-restore
force-restore
force-restore
force-restore
ISBA
Blackadar
Bougeault
Blackadar
Bougeault
Blackadar
1.0
0.85
0.85
1.0
1.0
16
17
18
19
20
Relaxed Arakawa Schubert
Kuo Symmetric
Kain & Fritsch
Oldkuo
Relaxed Arakawa Schubert
ISBA
force-restore
ISBA
ISBA
force-restore
Bougeault
Bougeault
Blackadar
Bougeault
Blackadar
0.85
1.0
0.85
0.85
1.0
21
22
23
24
Relaxed Arakawa Schubert
Oldkuo
Kain & Fritsch
Kuo Symétrique
ISBA
force-restore
force-restore
ISBA
Blackadar
Bougeault
Blackadar
Bougeault
0.85
1.0
1.0
0.85
BACK
P. Houtekamer, ARMA
GFS bias correction based
on an accumulated bias by
using decaying average
weight (0.02) which is the
same as GEFS used
The absolute errors are
reduced after bias correction
for 2-meter temperature
(The stats are accumulated
from 0.02 decaying average)
BACK
Combined GFS and GEFS forecasts at first 180hr
GFS has more skill than ensemble
control for short lead time
Combined GFS and GEFS
Forecast has more skill (red)
than GEFS only (black)
BACK
Jun Du first introduced dual-resolution
to SREF, by using constant weight
BACK
2-meter temperature 10/90 probability forecast verification
Northern Hemisphere, period of Dec. 2007 – Feb. 2008
P10-expect
P90-expect
P10-ncepraw
P90-ncepraw
P10-naefs
P90-naefs
Probabilities (percent)
100
90
80
70
60
~40%
50
40
~80%
30
20
10
0
24
48
BACK
72
96
120
144
168
192
216
240
Lead time (hours)
264
288
312
336
360
384
2-meter temperature 10/90 probability forecast verification
Northern Hemisphere, seasonal variation for NAEFS
P10
P10-dec
P10-feb
P90
P90-dec
P90-feb
100
Probabilities (percent)
90
80
70
60
50
NAEFS final 10% and 90% probability forecast for Dec. 2007 and Feb 2008
40
30
20
10
0
24
48
BACK
72
96
120
144
168
192
216
240
Lead time (hours)
264
288
312
336
360
384
GEFS raw forecast
NAEFS forecast
GEFS bias-corr. & down scaling fcst.
12hr 2m T forecast
Mean Absolute Error
w.r.t RTMA for CONUS
Average for September
BACK
NCEP/GEFS raw forecast
4+ days gain from NAEFS
NAEFS final products
From
BACK
Bias correction (NCEP, CMC)
Dual-resolution (NCEP only)
Down-scaling (NCEP, CMC)
Combination of NCEP and CMC
NCEP/GEFS raw forecast
8+ days gain
NAEFS final products
From
BACK
Bias correction (NCEP, CMC)
Dual-resolution (NCEP only)
Down-scaling (NCEP, CMC)
Combination of NCEP and CMC
GMOS forecast
CONUS 2m Temperature
For September 2007
Verify against RTMA
From Bo Cui (EMC)
Verify against observation
From Valery Dagostaro (MDL)
NAEFS final products
From :
Bias correction (NCEP, CMC)
Dual-resolution (NCEP only)
Down-scaling (NCEP, CMC)
Combination of NCEP and CMC
BACK
Current/future FNMOC Global EFS
(From Michael Sestak)
• Current FNMOC GEFS
– 96 members with perturbed initial conditions from NOGAPS control run
– Updated 4 times per day from 00Z, 06Z, 12Z, 18Z
– Forecasts to 252 hours (10.5 days) for 16 members, once per day for 00Z (remaining runs
and updates 6 hr forecasts), full forecast members rotate through all members over 6 days.
– Grid resolution: spectral T119, truncated from T239 control
– 30 vertical levels from surface to 1 mb, same as control
– Perturbations created using the Ensemble Transform technique, analysis error estimate
from NAVDAS
– 16 global WaveWatch3 runs forced by the winds from the 16 NOGAPS full forecast
members
• Short-term plan (1-2 years)
– Full forecast twice per day 00Z and 12Z
– Full forecasts to 360 hours (15 days)
– Grid resolution: spectral T159 (approximately 2/3 degree in latitude and longitude)
• Long-term plan (>2 years)
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Grid resolution: spectral T239 (approximately 1/2 degree in latitude and longitude)
32 members
Perturbations using Ensemble Transform Kalman Filter (ETKF) technique
Mesoscale Ensemble from AFWA/FNMOC Joint Ensemble Forecast System
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BACK
ECMWF Global EFS
• Current ECMWF GEFS
– 51 (50+1) perturbed ensemble runs (SV)
– Variable resolutions
• T399L62 (0-7d, dt=1800s)
• T255L62 (6-15d, dt=2700s)
• T255L62 (15-32d, dt=2700s) coupling with ocean model
– Updated 2 times per day from 00UTC and 12UTC
– Addition of stochastic perturbation of the physical tendencies
• Currently NCEP received
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Partly forecasts (30 variables)
Twice per day 00UTC and 12UTC
Every 12 hour up to 240 hours
1*1 degree resolution
• What do we expect (in process)
– More forecasts (around 50 variables)
– Twice per day at 00UTC and 12UTC
– Every 6 hours up to 360 hours
BACK
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Background !!!!!
Example for using regional mask
MDL GMOS & NAEFS Downscaled Forecast
Mean Absolute Error w.r.t. RTMA Average For Sept. 2007
12-h GMOS
Forecast
12-h NAEFS
Forecast
For CONUS:
NAEFS(1.01) : GMOS(1.59)
36% impr. over GMOS
MDL GMOS & NAEFS Downscaled Forecast
Mean Absolute Error w.r.t. RTMA Average For Sept. 2007
24-h GMOS
Forecast
24-h NAEFS
Forecast
For CONUS:
NAEFS(1.45) : GMOS(1.72)
15% impr. over GMOS
Surface Temperature MAE
Surface Temperature MAE
CONUS, Sept. 2007
CONUS, Sept. 2007
00Z GMOS vs. 00Z NAEFS
12Z NDFD vs. 00Z MOS/GMOS/NAEFS
RTMA Analysis
METAR obs. 1221 sites
GMOS forecast
0.5°C
NAEFS products
0.5°C
Surface Temperature Pointwise
PointwiseBias
Bias
Surface Temperature Area
AreaMean
MeanBias
Bias
CONUS, Sept. 2007
CONUS, Sept. 2007
00Z GMOS vs. 00Z NAEFS
12Z NDFD vs. 00Z MOS/GMOS/NAEFS
RTMA Analysis
METAR obs. 1221 sites
GMOS forecast
0.6°C
0.6°C
NAEFS products
Western Rgn Pointwise Bias
Western Rgn MAE
Western Rgn Area Mean Bias
Western Rgn MAE
Central Rgn Pointwise Bias
Central Rgn Area Mean Bias
Central Rgn MAE
Central Rgn MAE
Eastern Rgn Pointwise Bias
Eastern Rgn MAE
Eastern Rgn Area Mean Bias
Eastern Rgn MAE
Southern Rgn Pointwise Bias
Southern Rgn Area Mean Bias
Southern Rgn MAE
Southern Rgn MAE
2-meter temperature 10/90 probability forecast verification
Northern Hemisphere, period of Jan-Feb 2008
p10_exp
p10_raw
p10_bc
p90_exp
p90-raw
p90-bc
100
Probabilities (percent)
90
80
70
60
50
40
30
20
10
0
24
48
72
96
120
144
168
192
216
240
Lead time (hours)
264
288
312
336
360
384
NH500hPa
NHT2M
NH1000hPa
All these stats show the best
values from probabilistic
distribution of joined
ensemble (NAEFS) for upper
atmosphere and near surface.
Green line is from NAEFS.
Ensemble Functionalities
List of centrally/locally/interactively generated products required by NCEP Service Centers for each functionality
are provided in attached tables (eg., MSLP, Z,T,U,V,RH, etc, at 925,850,700,500, 400, 300, 250, 100, etc hPa)
FUNCTIONALITY
CENTRALLY
GENERATED
1
Mean of selected members Done
2
Spread of selected members Done
3
Median of selected values Done Sept. 2005
4
Lowest value in selected members Done Sept. 2005
5
Highest value in selected members Done Sept. 2005
6
Range between lowest and highest values Done Sept. 2005
7
Univariate exceedance probabilities for a selectable threshold value Done, Dec 05
8
Multivariate (up to 5) exceedance probabilities for a selectable threshold value Done,
Dec 05
9
Forecast value associated with selected univariate percentile value Done Sept. 2005
10
Tracking center of maxima or minima in a gridded field (eg – low pressure centers)
Done Sept. 2005
11
Objective grouping of members Planning starts FY06, Deliver FY07-08
12
Plot Frequency / Fitted probability density function at selected location/time (lower
priority) Detailed Planning FY06, Deliver FY07
13
Plot Frequency / Fitted probability density as a function of forecast lead time, at
selected location (lower priority) Detailed Planning FY06, Deliver FY07
14
Spaghetti (ability to interactively change contour/domain etc) Basic function done;
Interactive version to be scheduled (TBS)
Additional basic GUI functionalities:
- Ability to manually select/identify members (TBS)
- Ability to weight selected members Done, Sept. 05
LOCALLY
GENERATED
INTERACTIVE
ACCESS
Potentially useful functionalities that need further development:
- Mean/Spread/Median/Ranges for amplitude of specific features (TBS)
- Mean/Spread/Median/Ranges for phase of specific features (TBS)
NCEP/GEFS raw forecast
4+ days gain from new products
Final products: NCEPbc+CMCbc
+dual-resolution+down-scaling
24-h GMOS
Forecast
12-h NDFD
Forecast
For CONUS:
GEFS(3.07) : NDFD(3.60)
17% impr. over NDFD
GEFS(3.07) : GMOS(3.37)
10% impr. over GMOS
24-h GEFS
Forecast
40 day average absolute errors of 2-meter temperature (NDFD has 12hr advantage)
COUNS only – verified against RTMA
2-m temp. forecast errors
NDFD
GMOS
GEFS
6
5
4
3
2
1
0
24
48
72
96
120
forecast hours
144
168
Bias Correction Method & Application
 Bias Assessment: adaptive (Kalman Filter type) algorithm
decaying averaging mean error = (1-w) * prior t.m.e + w * (f – a)
For separated cycles, each lead time and individual grid point, t.m.e = time mean error
6.6%
• Test different decaying weights.
0.25%, 0.5%, 1%, 2%, 5% and
10%, respectively
3.3%
1.6%
• Decide to use 2% (~ 50 days)
decaying accumulation bias
estimation
Toth, Z., and Y. Zhu, 2001
 Bias Correction: application to NCEP operational ensemble 15 members
T2M for CONUS
U10m for CONUS
Continuous Ranked Probability
Scores (CRPS) is to measure
the distance of truth from
ensemble’s distribution. These
two stats show which decaying
weight is best to CONUS
region statistical down-scaling
List of Variables for Bias Correction, Weights
and Forecast Anomalies for CMC & NCEP Ensemble