# Presentation: 631526

## May 2006 Upgrade of theNCEP Global Ensemble Forecast System(NAEFS)

- Yuejian Zhu,
-  Zoltan Toth, Richard Wobus, Mozheng Wei and Bo Cui
- Environmental Modeling Center
- NOAA/NWS/NCEP
- Acknowledgements:
- DingChen Hou and Ken Campana    EMC
- David Michaud, Brent Gorden and Luke Lin     NCO

## Planned Changes - Summary

- Increasing the number of perturbation runs
- 14 (20 later) perturbation runs for each cycle
- Adding control runs for 0600, 1200 and 1800 cycles.
- Use Ensemble Transform (ET) breeding method instead of breeding method
- ET breeding method will create initial orthogonal vectors instead of independent vectors
- NAEFS new products from NCEP-CMC joint ensemble
- Bias corrected forecast
- Forecast anomalies
- Weights

## GEFS configurations

|  | Current | Plan |
| --- | --- | --- |
| Model | GFS | GFS |
| Initial uncertainty | BV | ETBV |
| Model uncertainty | None | None |
| Tropical storm | Relocation | same |
| Daily frequency | 00,06,12 and 18UTC | same |
| Hi-re control 
(GFS) | T382L64 (d0-d7.5)
T190L64 (d7.5-d16) | same |
| Low-re control (ensemble control) | T126L28 (d0-d16)
00UTC only | T126L28 (d0-d16)
00,06,12 and 18UTC |
| Perturbed members | 10 for each cycle | 14 (20) for each cycle |
| Forecast length | 16 days (384 hours) | same |
| Implementation  | August 17th 2005 | May 30th 2006 |

_**GEFS configurations**_

## Planned Changes - 1

- Increasing the number of perturbation runs
- 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
- Slightly improving ensemble mean skills (seasonal dependent)

## Planned Changes - 2

- Adding control runs for 0600, 1200 and 1800 cycles.
- This change is intended to enable for relocation of perturbed tropical storm, to respond the ensemble initial perturbation changes from pairs to one side only. After this implementation, there will be complete ensemble package with control for each cycle. It is useful to compare different cycles and leg forecast.

## Planned Changes - 3

- Use Ensemble Transform (ET) breeding method instead of breeding method
- There is no pair anymore after this implementation (see next slide for details)
- This change is intended to improve probabilistic forecast skills for all lead-time.
- Results:
- Slightly reducing ensemble mean track errors (retrospective runs) for 12-96 hours
- Improving probabilistic forecast skills

## Ensemble Transform Bred Vector

- P1

- N1

- P2

- N2

- P#, N# are the pairs of positive and negative
- P1 and P2 are independent vectors
- Simple scaling down (no direction change)

- _Ensemble Transform Bred Vector_
- (Plan)

- P1, P2, P3, P4 are orthogonal vectors
- No pairs any more
- To centralize all perturbed vectors (sum of all vectors are equal to zero)
- Scaling down by applying mask,
- The direction of vectors will be tuned by ET.

- _Rescaling_

**ANL**

**ANL**

**ANL**

- _Bred Vector_
- (Current)

_**P1 forecast**_

_**P4 forecast**_

_**P3 forecast**_

_**P2 forecast**_

- t=t1

- t=t0

- t=t0

- t=t2

- t=t2

- t=t1

- _Rescaling_

## Planned Changed 4 – NAEFS Post Products

- NAEFS basic product list
- Bias corrected members of joint MSC-NCEP ensemble
- 35 of NAEFS variables
- 32(00Z), 15(06Z), 32(12Z) and 15(18Z) joint ensemble members
- Bias correction against each center’s own operational analysis
- Weights for each member for creating joint ensemble (equal weights right now)
- Weights don’t depend on the variables
- Weights depend on geographical location (low precision packing)
- Weights depend on the lead time
- Climate anomaly percentiles for each member
- 19 of NAEFS variables
- 32(00Z), 15(06Z), 32(12Z) and 15(18Z) joint ensemble members
- Use NCEP/NCAR 40-year reanalysis
- Considering the difference between current analysis and reanalysis
- Non-dimensional unit, allows downscaling of scalar variables to any local climatology

## List of Variables for Bias Correction, Weightsand Forecast Anomalies for CMC & NCEP Ensemble

## NCO parallel

- Start from 01/15/2006
- 14 perturbed runs and control for each cycle
- With new file structures
- Start from 02/01/2006
- Adding ET scheme (03/07/2006)
- Tuning TS relocation (?)
- Start from 04/01/2006
- Use GEFS new system (May implementation)
- Create bias correction forecast
- Forecast anomalies
- Evaluations

## Statistic results

- NCO real-time parallel verification statistics are posted at:
- _[http://wwwt.emc.ncep.noaa.gov/gmb/yzhu/html/opr/prx_daily.html](http://wwwt.emc.ncep.noaa.gov/gmb/yzhu/html/opr/prx_daily.html)__ _(available now)
- Updated every morning
- Retrospective experimental verification statistics are posted at:
- _[http://www.emc.ncep.noaa.gov/gmb/yzhu/html/opr/et14m_daily.html](http://www.emc.ncep.noaa.gov/gmb/yzhu/html/opr/et14m_.html)__ _(available now)
- Updated as required

## Early studies for ET

- Northern Hemisphere

- Southern Hemisphere

- Tropical

_**Early studies for ET**_
- Winter of 2002-2003
- ROC scores for 32 cases
- ENS-o  control runs
- ENS-s  ET-20 members
- ENS-x  ET-10 members

## Summary of Retrospective Runs

- Period: 08/20/2005 – 09/30/2005
- Statistics for
- Hurricane track errors
- Atlantic-, East Pacific-, West Pacific- basins, total basins
- AC scores (Northern Hemisphere)
- RMS errors (Southern Hemisphere)
- Outlier for Northern Hemisphere
- ROC scores for NH and SH
- Conclusion
- Tropical  –  mean of track error (slightly improved)
- Improved (48-, 72-, 96-hours over all)
- NH – mean (improved), probabilistic (improved)
- SH – mean (slightly), probabilistic (improved)

## Hurricane Track Errors (Atlantic Basin: 08/20-09/30/2005)

**Cases**

**174**

**48**

**75**

**101**

**128**

**141**

**157**

**Hours**

- _AEMN-operational ensemble_
- _ETIM-retrospective runs_

- _ETIM is better than AEMN_

## Hurricane Track Errors (East Pacific Basin: 08/20-09/30/2005)

**Cases**

**181**

**69**

**85**

**109**

**135**

**149**

**165**

**Hours**

- _Ensemble need to improve in East Pacific Basin in the future_

## Hurricane Track Errors (West Pacific Basin: 08/20-09/30/2005)

**Cases**

**177**

**44**

**66**

**101**

**129**

**145**

**161**

**Hours**

- _ETIM is better than AEMN_

## Hurricane Track Errors (All Basins: 08/20-09/30/2005)

**Cases**

**532**

**161**

**226**

**311**

**392**

**435**

**483**

**Hours**

- _Overall, ensemble mean beat GFS from/after 72 hours for hurricane tracks, it is similar to NH/SH 500hPa height rms errors_

## Much better than GFS after 72 hours

- _Improving skills from/after day 3_

- _Much better than GFS after 72 hours_

- _65% AC scores – useful skill_
- _Ens. extended another 20 hours_

- _ENS_s – operational ensemble_
- _ENS_x – retrospective runs_

## Reduced initial spread

- _Reduced initial spread_
- _Growing faster than operational_

- _Reduced errors after day 6_

## Outlier zero is perfect

- _Outlier zero is perfect_

- _Due to reduce initial perturbation_

- _Better after day 4_

## Improved ROC scores for Northern Hemisphere

- _Improved ROC scores for Northern Hemisphere_

- _ENS_s – operational ensemble_
- _ENS_x – retrospective runs_

## Improved ROC scores for Southern Hemisphere

- _Improved ROC scores for Southern Hemisphere_

## Summary of NCO Parallel

- Period: 03/01/2006-current (more than 50 days)
- Statistics for
- RMS errors (Northern Hemisphere)
- AC scores (Southern Hemisphere)
- AC scores for tropical
- ROC scores for NH, SH and tropical
- Conclusion
- Tropical  –  no significant changes
- NH – mean (even), probabilistic (improved)
- SH – mean (improved), probabilistic (improved)

## Rms errors are slightly better for short lead time

- _Rms errors are slightly better for short lead time_

- _Less spread at initial, but growing faster_

## Significant improvement for Southern Hemisphere

- _Significant improvement for Southern Hemisphere_

- _Ensemble mean beat GFS from/after day 3_

## There is no big effect in Tropical by apply ET in generally

- _There is no big effect in Tropical by apply ET in generally_

## Improving for all lead time

- _Improving for all lead time_

- _Most considerable improvement for medium range_

## Improvement for all lead time

- _Improvement for all lead time_

- _It is very similar to NH_

## There is no big difference for Tropical region

- _There is no big difference for Tropical region_

## Perturbation versus Error Correlation Analysis (PECA)

- Retrospective runs

- NCO parallel runs

## Summary of NAEFS new products- Post process

- Early studies
- NCO parallel: 04/01/2006-current
- No new stats yet

## Ensemble size = 10 members

## Slide 33

## Slide 34

## Slide 35

## Example of percentile forecast in terms of climate

- ENSEMBLE 10-, 50- (MEDIAN) & 90-PERCENTILE FORECAST VALUES (BLACK CONTOURS) AND CORRESPONDING CLIMATE PERCENTILES (SHADES OF COLOR)

- percentiles

- Proposal future NDGD products

## Background !!!!!

## RAW & BASIC PRODUCT AVAILABILITY

*2005, **2006**, **2007**, **2008*

## END PRODUCTS

- End product generation
- Can be center specific
- Need to conform with procedures/requirements established at different centers
- End products generated at NCEP
- Based on prioritized list of requests from NCEP Service Centers
- Graphical products (including Caribbean, South American, and AMMA areas)
- NCEP official web site (gif – NA, Caribbean, SA, AMMA)
- NCEP Service Centers (NAWIPS metafile)
- Gridded products
- NAWIPS grids
- NCEP Service Centers (list of 661 products)
- GRIB2 format
- Products of general interest (Possible ftp distribution, no decision yet on products)
- NDGD (10-50-90 percentile forecast value + associated climate percentile)
- End products generated at MSC
- TBD
- End products generated jointly
- Experimental probabilistic Week-2 forecast
- Fully automated, based on basic products: bias corrected, weighted climate anomalies
- Can become official product once performance reaches current operational level

## ENSEMBLE PRODUCTS - FUNCTIONALITIES

|  | FUNCTIONALITY | CENTRALLY GENERATED | LOCALLY GENERATED | INTERACTIVE
ACCESS |
| --- | --- | --- | --- | --- |
| 1 | Mean of selected members  Done |  |  |  |
| 2 | Spread of selected members Done  |  |  |  |
| 3 | Median of selected values Sept. 2005 |  |  |  |
| 4 | Lowest value in selected members Sept. 2005 |  |  |  |
| 5 | Highest value in selected members Sept. 2005 |  |  |  |
| 6 | Range between lowest and highest values Sept. 2005 |  |  |  |
| 7 | Univariate exceedance probabilities for a selectable threshold value FY06? |  |  |  |
| 8 | Multivariate (up to 5) exceedance probabilities for a selectable threshold value FY06? |  |  |  |
| 9 | Forecast value associated with selected univariate percentile value Sept. 2005 - FY06? |  |  |  |
| 10 | Tracking center of maxima or minima in a gridded field (eg – low pressure centers) Sept. 2005, Data flow FY06? |  |  |  |
| 11 | Objective grouping of members FY08? |  |  |  |
| 12 | Plot Frequency / Fitted probability density function at selected location/time (lower priority) FY07? |  |  |  |
| 13 | Plot Frequency / Fitted probability density as a function of forecast lead time, at selected location (lower priority) FY07? |  |  |  |

- 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)*

***Potentially useful functionalities that need further development:***
- - Mean/Spread/Median/Ranges for amplitude of specific features - Mean/Spread/Median/Ranges for phase of specific features

***Additional basic GUI functionalities:**** *- Ability to manually select/identify members - Ability to weight selected members *Sept. 2005*

## ENSEMBLE PRODUCT REQUEST LIST

- NCEP SERVICE CENTERS, OTHER PROJECTS

## NDGD FORECAST UNCERTAINTY - DOWNSCALING

- Ensemble uncertainty information
- Sent on NDGD grid for convenience (if no big overhead)
- Valid on model grids (32km for regional, 110 km for global ensemble)
- How to bridge gap between model and NDGD grids?
- Anomaly uncertainty information – proposed methodology
- Establish reanalysis climatology
- In progress for global (NAEFS), methods can be transferred to regional reanalysis
- Bias correct ensemble forecasts (wrt operational analysis)
- Take 10-50-90 percentile values from bias corrected ensemble
- (For establishing anomaly forecasts, adjust 10-50-90 percentile values to look like re-analysis)
- Check climatological percentile corresponding to 10-50-90 forecast percentiles
- Provide climatological percentiles corresponding to 10-50-90 percentile forecast values as second set of guidance products

## Hurricane Track Errors (Atlantic+East Pacific Basins: 08/20-09/30/2005)

**Cases**

**355**

**117**

**160**

**210**

**263**

**290**

**322**

**Hours**

## Track errors and spreads2004 Atlantic Basin (8/23-10/1)

- From Timothy Marchok (GFDL)

- Reduced mean track errors and spreads

## Hurricane track errors2 basins (Atlantic and e-Pacific)

- Track errors (miles)

- Percentage improvement to operational ensemble

- Period: 20040824-20040930 (53-103 cases)