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UMAC data call page 1 of 25North American Ensemble Forecast System - NAEFS
EMC Operational Models
North American Ensemble Forecast System
Yuejian ZhuEnsemble Team Leader, Environmental Modeling CenterNOAA / NWS / NCEP
UMAC data call page 2 of 25North American Ensemble Forecast System - NAEFS
Statement
The North American Ensemble Forecast System (NAEFS) combines state
of the art weather forecast tools, called ensemble forecasts, developed at the US
National Weather Service (NWS) and the Meteorological Service of Canada
(MSC). When combined, these tools (a) provide weather forecast guidance for the
1-14 day period that is of higher quality than the currently available operational
guidance based on either of the two sets of tools separately; and (b) make a set of
forecasts that are seamless across the national boundaries over North America,
between Mexico and the US, and between the US and Canada. As a first step in
the development of the NAEFS system, the two ensemble generating centers, the
National Centers for Environmental Prediction (NCEP) of NWS and the Canadian
Meteorological Center (CMC) of MSC started exchanging their ensemble forecast
data on the operational basis in September 2004. First NAEFS probabilistic
products have been implemented at NCEP in February 2006. The enhanced
weather forecast products are generated based on the joint ensemble which has
been undergone a statistical post-processing to reduce their systematic errors.
UMAC data call page 3 of 25North American Ensemble Forecast System - NAEFS
North American Ensemble Forecast System
International project to produce operational multi-center ensemble products
Bias correction and combines global
ensemble forecasts from Canada & USA
Generates products for:Weather forecasters
Specialized usersEnd users
Operational outlet for THORPEX research using TIGGE archive
UMAC data call page 4 of 25North American Ensemble Forecast System - NAEFS4
NCEP CMC NAEFSModel GFS GEM NCEP+CMC
Initial uncertainty ETR ETKF ETR + ETKF
Model uncertainty/Stochasti
c
Yes (Stochastic Pert) Yes (multi-physicsand stochastic)
Yes
Tropical storm Relocation None
Daily frequency 00,06,12 and 18UTC 00 and 12UTC 00 and 12UTC
Resolution T254L42 (d0-d8)~55kmT190L42 (d8-16)~70km
About 50kmL72
1*1 degree
Control Yes Yes Yes (2)
Ensemble members 20 for each cycle 20 for each cycle 40 for each cycle
Forecast length 16 days (384 hours) 16 days (384 hours) 16 days
Post-process Bias correction (same bias for all members)
Bias correction for each member
Yes
Last implementation February 14th 2012 November 18th 2014
NAEFS Current StatusUpdated: November 18th 2014
UMAC data call page 5 of 25North American Ensemble Forecast System - NAEFS
NAEFS Milestones• Implementations
– First NAEFS implementation – bias correction Version 1.00 - May 30 2006– NAEFS follow up implementation – CONUS downscaling Version 2.00 - December 4 2007– Alaska implementation – Alaska downscaling Version 3.00 - December 7 2010– Implementation for CONUS/Alaska expansion Version 4.00 - April 8 2014 – Implementation of 2.5km NDGD for CONUS/Alaska Version 5.00 – September 2015
• Applications:– NCEP/GEFS and NAEFS – at NWS– CMC/GEFS and NAEFS – at MSC– FNMOC/GEFS – at NAVY– NCEP/SREF – at NWS
• Publications (or references):– Cui, B., Z. Toth, Y. Zhu, and D. Hou, D. Unger, and S. Beauregard, 2004: “ The Trade-off in Bias Correction between Using the Latest
Analysis/Modeling System with a Short, versus an Older System with a Long Archive” The First THORPEX International Science Symposium. December 6-10, 2004, Montréal, Canada, World Meteorological Organization, P281-284.
– Zhu, Y., and B. Cui, 2006: “GFS bias correction” [Document is available online]– Zhu, Y., B. Cui, and Z. Toth, 2007: “December 2007 upgrade of the NCEP Global Ensemble Forecast System (NAEFS)” [Document is
available online]– Cui, B., Z. Toth, Y. Zhu and D. Hou, 2012: "Bias Correction For Global Ensemble Forecast" Weather and Forecasting, Vol. 27 396-410 – Cui, B., Y. Zhu , Z. Toth and D. Hou, 2015: "Development of Statistical Post-processor for NAEFS" Weather and Forecasting (In process)– Zhu, Y., and B. Cui, 2007: “December 2007 upgrade of the NCEP Global Ensemble Forecast System (NAEFS)” [Document is available
online]– Zhu, Y, and Y. Luo, 2014: “Precipitation Calibration Based on Frequency Matching Method (FMM)” . Weather and Forecasting (in press)– Glahn, B., 2013: “A Comparison of Two Methods of Bias Correcting MOS Temperature and Dewpoint Forecasts” MDL office note, 13-1– Guan, H, B. Cui and Y. Zhu, 2015: “Guan, H., B. Cui and Y. Zhu, 2014: "Improvement of Statistical Post-processing Using GEFS Reforecast
Information", (accepted, in press)
UMAC data call page 6 of 25North American Ensemble Forecast System - NAEFS
Bias correction: • Bias corrected NCEP/CMC GEFS and NCEP/GFS forecast (up to 180 hrs)• Combine bias corrected NCEP/GFS and NCEP/GEFS ensemble forecasts• Dual resolution ensemble approach for short lead time• NCEP/GFS has higher weights at short lead time
NAEFS products (global) and downstream applications• Combine NCEP/GEFS (20m) and CMC/GEFS (20m) • Produce Ensemble mean, spread, mode, 10% 50%(median) and 90% probability forecast at 1*1 degree
resolution• Climate anomaly (percentile) forecasts• Wave ensemble forecast system• Hydrological ensemble forecast system
Statistical downscaling • Use RTMA as reference - NDGD resolution (5km/6km), Extended CONUS and Alaska• Generate mean, mode, 10%, 50%(median) and 90% probability forecasts
NAEFS Statistical Post-Processing
UMAC data call page 7 of 25North American Ensemble Forecast System - NAEFS
NAEFS Bias Correction (Decaying average method)
)()()( 0,,, tatftb jijiji
2). Decaying Average (Kalman Filter method)
)()1()1()( ,,, tbwtBwtB jijiji
1). Bias Estimation:
3). Decaying Weight: w =0.02 in GEFS bias correction (~ past 50-60 days information)
4). Bias corrected forecast:
)()()( ,,, tBtftF jijiji Simple Accumulated Bias
Assumption: Forecast and analysis (or observation) is fully correlated
UMAC data call page 8 of 25North American Ensemble Forecast System - NAEFS
Variables pgrba_bc file Total 51
GHT 10, 50, 100, 200, 250, 500, 700, 850, 925, 1000hPa 10
TMP 2m, 2mMax, 2mMin, 10, 50, 100, 200, 250, 500, 700, 850, 925, 1000hPa
13
UGRD 10m, 10, 50, 100, 200, 250, 500, 700, 850, 925, 1000hPa 11
VGRD 10m, 10, 50, 100, 200, 250, 500, 700, 850, 925, 1000hPa 11
VVEL 850hPa 1
PRES Surface, PRMSL 2
FLUX (top) ULWRF (toa - OLR) 1
Td and RH 2m 2
Notes CMC did not process bias correction for Td and RH
NAEFS bias corrected variables
Last upgrade: April 8th 2014 - (bias correction)
UMAC data call page 9 of 25North American Ensemble Forecast System - NAEFS
Continuous Ranked Probabilistic Skill Scores
5-day forecast
10-day forecast
NH 500-hPa Height30-day running mean
GEFSNAEFS
UMAC data call page 10 of 25North American Ensemble Forecast System - NAEFS
Statistical downscaling for NAEFS forecast
• Proxy for truth– RTMA at 5km resolution– Variables (surface pressure, 2-m temperature, and 10-meter
wind)• Downscaling vector
– Interpolate GDAS analysis to 5km resolution– Compare difference between interpolated GDAS and RTMA– Apply decaying weight to accumulate this difference –
downscaling vector• Downscaled forecast
– Interpolate bias corrected 1*1 degree NAEFS to 5km resolution – Add the downscaling vector to interpolated NAEFS forecast
• Application– Ensemble mean, mode, 10%, 50%(median) and 90% forecasts
UMAC data call page 11 of 25North American Ensemble Forecast System - NAEFS
11
Variables Domains Resolutions Total 10/10
Surface Pressure CONUS/Alaska 5km/6km 1/1
2-m temperature CONUS/Alaska 5km/6km 1/1
10-m U component CONUS/Alaska 5km/6km 1/1
10-m V component CONUS/Alaska 5km/6km 1/1
2-m maximum T CONUS/Alaska 5km/6km 1/1
2-m minimum T CONUS/Alaska 5km/6km 1/1
10-m wind speed CONUS/Alaska 5km/6km 1/1
10-m wind direction CONUS/Alaska 5km/6km 1/1
2-m dew-point T CONUS/Alaska 5km/6km 1/1
2-m relative humidity CONUS/Alaska 5km/6km 1/1
NAEFS downscaling parameters Last Upgrade: April 8 2014 (NDGD resolution)
All downscaled products are generated from 1*1 degree bias corrected fcst. globally Products include ensemble mean, spread, 10%, 50%, 90% and mode
UMAC data call page 12 of 25North American Ensemble Forecast System - NAEFS
12hr 2m TemperatureForecast Mean Absolute Error w.r.t RTMA for CONUSAverage for September, 2007
GEFS raw forecast
NAEFS forecast
GEFS bias-corr. & down scaling fcst.
UMAC data call page 13 of 25North American Ensemble Forecast System - NAEFS
13
NCEP/GEFS raw forecast
NAEFS final products
4+ days gain from NAEFS
From Bias correction (NCEP, CMC)Dual-resolution (NCEP
only)Down-scaling (NCEP,
CMC)Combination of NCEP
and CMC
UMAC data call page 14 of 25North American Ensemble Forecast System - NAEFS
14
From Bias correction (NCEP, CMC)Dual-resolution (NCEP only)Down-scaling (NCEP, CMC)Combination of NCEP and CMC
NAEFS final products
NCEP/GEFS raw forecast
8+ days gain
UMAC data call page 15 of 25North American Ensemble Forecast System - NAEFS
Future Plan for NAEFS
• Short term plan– Exchange 0.5degree data every three hours for selected variables out to 7 days
between NCEP, CMC (and FNMOC).– Exchange wave ensemble data between NCEP, CMC (and FNMOC)– NAEFS (SPP) upgrade (v5.0) – Q4FY15
• Improving bias correction process (method)• Adding cloud cover variable for bias correction• The same algorithm for processing ECMWF ensemble for internal use only• Downscaled products from 5km to 2.5km, and extend CONUS domain to cover
most of Canada and Mexico• Downscaled products from 6km to 3km for Alaska
– NAEFS (SPP) upgrade (V6.0) – Q2FY16• Improving bias correction process (method)• Adding additional variables (wind gust and wave height) for bias correction and
downscaling• Adding ECMWF ensembles to NAEFS (for internal use only)• Adding new products (EFI and Anomaly Forecast) for extreme weather• Expand downscaling products for other domains (Hawaii, Guan and Puerto Rico)
UMAC data call page 16 of 25North American Ensemble Forecast System - NAEFS
Future Plan for NAEFS
• Long term plan– Collaborate with CMC and FNMOC (and MDL)– NAEFS welcomes other international center(s) to join (and/or
contribute)– Exchange extend forecasts (out to 30 days) between NCEP, CMC
(and FNMOC).– Exchange GEFS reforecast between NCEP, CMC (and FNMOC)– Extend downscaling products to cover whole North American– Improve NAEFS SPP – Develop new guidance for extreme weather events those include
weather and week 2, 3 & 4
UMAC data call page 17 of 25North American Ensemble Forecast System - NAEFS
Bias correction for
each ensemble member
+
High resolution
deterministic forecast
Mixed Multi- Model
Ensembles(MMME)
Probabilistic products at 1*1 (and/or) .5*.5
degree globally
Down-scaling (based on RTMA)
Probabilistic products at NSGD resolution(e.g. 2.5km – CONUS)
NCEP
Others
CMC
Reforecast
RBMPFor
blenderVaried
decaying weights
Auto-adjustment
of 2nd moment
Smartinitializatio
n
Future NAEFS Statistical Post-Processing
UMAC data call page 18 of 25North American Ensemble Forecast System - NAEFS
UMAC data call page 19 of 25North American Ensemble Forecast System - NAEFS
National Unified Operational Prediction Capability
• NUOPC (National Unified Operational Prediction Capability) is an agreement to coordinate activities between the Department of Commerce (National Oceanic and Atmospheric Administration) and the Department of Defense (Oceanographer and Navigator of the Navy and Air Force Directorate of Weather), in order to accelerate the transition of new technology, eliminate unnecessary duplication, and achieve a superior National global prediction capability.
• The NUOPC partners determined that the Nation’s global atmospheric modeling capability can be advanced more effectively and efficiently with their mutual cooperation to provide a common infrastructure to perform and support their individual missions.
• The NUOPC Tri-Agency (NOAA, Navy, Air Force) agreed to work on a collaborative vision through coordinated research, transition and operations in order to develop and implement the next-generation National Operational Global Ensemble modeling system. This NUOPC plan consists of the following elements:
UMAC data call page 20 of 25North American Ensemble Forecast System - NAEFS
NCEP CMC FNMOCModel GFS GEM Global Spectrum
Initial uncertainty ETR EnKF (9) Banded ET
Model uncertainty Stochastic
Yes (STTP) Yes (multi-physics and Stochastic)
None
Tropical storm Relocation None None
Daily frequency 00,06,12 and 18UTC 00 and 12UTC 00 and 12UTC
Resolution T254L42 (d0-d8)~55kmT190L42 (d8-16)~70km
~ 50kmL72
T239L50 ~ 55km
Control Yes Yes Yes
Ensemble members 20 for each cycle 20 for each cycle 20 for each cycle
Forecast length 16 days (384 hours) 16 days (384 hours) 16 days (384 hours)
Post-process Bias correction for ensemble mean
Bias correction for each member
Bias correction for member mean
Last implementation February 14 2012 November 18 2014 May 21 2014
NUOPC Current StatusUpdated: May 21 2014
UMAC data call page 21 of 25North American Ensemble Forecast System - NAEFS
NUOPC (FNMOC) Grid Exchange VariablesUpdate: May 21 2014
21
Variables Pgrba file Total 80/73
GHT Surface, 10, 50, 100, 200, 250, 500, 700, 850, 925, 1000 hPa 11/(11)
TMP 2m, 2mMax, 2mMin, 10, 50, 100, 200, 250, 500, 700, 850, 925, 1000 hPa 13/(13)
RH 2m, 10, 50, 100, 200, 250, 500, 700, 850, 925, 1000 hPa 11/(11)
UGRD 10m, 10, 50, 100, 200, 250, 500, 700, 850, 925, 1000 hPa 11/(11)
VGRD 10m, 10, 50, 100, 200, 250, 500, 700, 850, 925, 1000 hPa 11/(11)
PRES Surface, PRMSL 2/(2)
PRCP APCP, CRAIN, CSNOW, CFRZR, CICEP 5/(4)
FLUX (surface) LHTFL, SHTFL, DSWRF, DLWRF, USWRF, ULWRF 6/(2)
FLUX (top) ULWRF (OLR) 1/(1)
PWAT Total precipitable water at atmospheric column 1/(1)
TCDC Total cloud cover at atmospheric column 1/(1)
CAPE Convective available potential energy, Convective Inhibition 2/(2)
SOIL/SNOW SOILW(0-10cm) , TMP(0-10cm down), WEASD(water equiv. of accum. Snow depth), SNOD(surface)
4/(1)
Other 850 hPa vertical velocity 1/(1)
Notes Original NAEFS grids currently being sent to NCEP by FNMOC, Require model change to add. (future plan)Not available
FNMOC=72
UMAC data call page 22 of 25North American Ensemble Forecast System - NAEFS
National Unified Operational Prediction Capability
• NAVGEN ensemble (FNMOC) data at NCEP– Twice per day (00UTC, 12UTC)– Every 6 hours, out to 16 days– 20+1 ensemble members for each lead time– 1*1 degree raw ensembles (72 variables) forecasts
• Post process – bias correction– NCEP runs bias correction for NAVGEN ensembles– The same algorithm as NCEP and CMC
• Public data access– NCEP ftp – real time– NCEP NOMADS – real time– NCDC NOMADS – real time?
UMAC data call page 23 of 25North American Ensemble Forecast System - NAEFS
Northern Hemisphere 500hPa height (against consensus analysis):
Latest 3-month winter scores: CRP scoreRMS error and ratio of RMS error / spreadAnomaly correlation
NH CRPS skill scores
NH anomaly correlation
500hPa Height
NH RMS errors
UMAC data call page 24 of 25North American Ensemble Forecast System - NAEFS
Ratio of RMS error over spread
Northern Hemisphere 500hPa height (against consensus analysis):
30-day running mean scores of day-5: CRP score RMS error and ratio of RMS error / spread Anomaly correlation
NH 500hPa anomaly correlation
5-day forecast
NH 500hPa CRP scores
Under-dispersion
Over-dispersion
NH 500hPa RMS errors
UMAC data call page 25 of 25North American Ensemble Forecast System - NAEFS
The results demonstrate:1. BMA could improve 3 ensemble’s mean, but
spread could be over if original spread is larger2. RBMP could keep similar BMA average future, but
2nd moment will be adjusted internally3. All important time average quantities are decaying
average (or recursive – save storage)
NUOPCIBC – simple combine three bias corrected ensembles
DCBMA – decaying based Bayesian Model Average
RBMP – Recursive Bayesian Model Process (built in decaying average and internal 2nd-moment adjustment)
Solid line – RMS errorDash line - Spread
Over-dispersion
Multi-modelPost-processing