# Presentation: 024529

## Global Climate and Weather Modeling

**John H. Ward**
- NCEP Production Suite Review
- December 10, 2008

## Outline

- GC&WMB Responsibilities
- Global Model & the Production Suite
- Recent Changes
- Upcoming Changes
- Dropouts
- Future Plans

## GC&WMB Responsibilities

- GC&WMB presentation will be broken into four separate parts
- Overview of recent changes and test results from upcoming implementations for:
- Global Forecast System
- Global Data Assimilation
- Ensemble Forecast System
- Long Term planning
- Data Assimilation – John Derber
- Climate Forecast System – Hau-Lu Pan
- Ensemble Forecast System – Zoltan Toth

## NWS Seamless Suite of ForecastProducts Spanning Climate and Weather

- Linkage

***Forecast ***
***Uncertainty***

***Minutes***

***Hours***

***Days***

***1 Week***

***2 Week***

***Months***

***Seasons***

***Years***

- NWS Seamless Suite of ForecastProducts Spanning Climate and Weather

- North American Ensemble
- Forecast System

- Climate Forecast System

- Short-Range Ensemble Forecast

- Ocean Model
- Hurricane Models

- Global Forecast System

- North American Forecast

- Rapid Update Cycle for Aviation

- Dispersion Models for DHS

- GFDL
- WRF

**Maritime**

**Life & Property**

**Space Operations**

**Recreation**

**Ecosystem**

**Environment**

**Emergency Mgmt **

**Agriculture**

**Reservoir Control**

**Energy Planning**

**Commerce**

**Hydropower**

**Fire Weather**

**Health**

**Aviation**

## NOAA’s NWS Model Production Suite

- WRF NMM/ARW
- Workstation WRF

- WRF: ARW, NMM
- ETA, RSM

- GFS, Canadian Global Model

- Satellites
- 99.9%

_**Regional NAM**_
- WRF NMM

**North American Ensemble Forecast System**

**Hurricane **GFDL
- HWRF

**Global**
**Forecast**
**System**

**Dispersion**
- ARL/HYSPLIT

**Severe Weather**

**Rapid Update**
**for Aviation**

**Climate**
**CFS**

- 1.7B Obs/Day

**Short-Range**
**Ensemble Forecast**

**MOM3**

**NOAH Land Surface Model**

- Coupled

**Global Data**
**Assimilation**

**Oceans**
- HYCOM
- WaveWatch III

- NAM/CMAQ

## Recent Changes

- Data Assimilation
- Global GSI Upgrades – 1Q08 & 4Q08
- Ensemble Forecast System
- NAEFS – 1Q08
- Climate
- CFS/GODAS – 1Q08
- Global Forecast Model
- Physics upgrade – 3Q08  Withdrawn

## 3Q08 GFS Change

- GSI Bundle (see slide #10)
- RRTM1 long-wave radiation
- More accurate absorption coefficients
- RRTM shortwave radiation
- Major improvement in upper stratospheric cloudy skies
- Maximum-random cloud overlap for shortwave
- Unifies cloud treatment for long & shortwave radiation
- Hourly long-wave radiation
- Better definition of diurnal cycle.  Makes scheme consistent with short-wave radiation

## Generalized aerosol treatment
Code efficiency.  Aerosol algorithms will not have to be rewritten when radiation schemes change.
Realistic CO2
Model had been using old climatology.  Now uses observed CO2
Retuned mountain blocking
Update parameters for T382
Shallow convection up to sigma 0.7
Permits shallow convection over high terrain
Convective gravity wave drag
Improve stratospheric tropical winds

- Code efficiency.  Aerosol algorithms will not have to be rewritten when radiation schemes change.
- Realistic CO2
- Model had been using old climatology.  Now uses observed CO2
- Retuned mountain blocking
- Update parameters for T382
- Shallow convection up to sigma 0.7
- Permits shallow convection over high terrain
- Convective gravity wave drag
- Improve stratospheric tropical winds

- 3Q08 GFS Change(cont)

## Summary of Subjective Evaluation

- The proposed GFS implementation shows, at best, little improvement over the operational GFS, and has several shortcomings
- Major concerns
- Increased feedback from grid scale overturning on mass fields and downstream QPF
- Less run-to-run consistency
- Loss of 6-12 h of skill in NH 500-mb anomaly correlation die off curves for days 5-7
- While the parallel does show signs of improved performance at medium ranges, this is offset by lack of run-to-run consistency

## Decision to Cancel Implementation

- Based on subjective review and a lack of an overwhelming improvement in objective statistics the proposed change was withdrawn
- Because of the complexity in testing and evaluating GFS changes it was also decided to separate data assimilation changes from future GFS bundles
- This will make it possible for more frequent changes in the assimilation system
- 4Q08 GSI implementation was a modified version from the GFS package.  Components retained:
- Observations
- assimilate WindSAT surface winds (new dataset)
- add assimilation of profile ozone quality flag 7 SBUV/2 observations
- reintroduce assimilation of AQUA AMSUA channels 6 and 8-13
- Code
- ability to distinguish between GPSRO data from various sources
- improved computational efficiency
- ability to directly read / use quadratic grid surface guess files

## Upcoming Changes

- Data Assimilation
- Global GSI Upgrades – 2Q09
- Ensemble Forecast System
- GEFS – 3Q09
- Climate
- Reanalysis & Reforecasting ongoing
- Global Forecast Model
- Coupled Ocean-Atm – 3Q08  Withdrawn
- Uncoupled physics upgrade being tested

## 2Q09 GSI Upgrade

- Addition of METOP/IASI data
- Improved atmospheric analyses, especially in S.H.
- Variational Quality Control
- Improved quality control of observations
- Eliminate need for OIQC step
- Change in land/snow/ice skin temperature variance
- Improved use of near surface radiance observations
- New Background error covariances
- Consistency with current version of system.  Improved upper atmosphere
- Reduce  number of AIRS water vapor channels
- Improved convergence and improved analysis

## 2Q09 GSI Upgrade

- New version and coefficients for CRTM
- Improved simulation of radiance observations
- Modification of height assignment for height based wind observations
- Improved use of these observations
- Retune observational errors
- Removed – results of impact of removal will be shown
- Modification of surface land use file
- Removes a few permanent (~12) glacial points to improve surface temperature forecasts
- Situation Dependent Background Variances

## New flow-dependent adjusted background error standard deviation

- “As is” 500 hPa
- streamfunction (1e6)
- background error
- standard deviation
- Valid: 2007110600

## Surface pressure background

- error standard deviation
- fields
- with flow dependent re-scaling
- without re-scaling
- 		Valid:  2007110600

## 2Q09 GSI Schedule

- 30-Day evaluation – 16 December
- Evaluation ends – 13 January
- Management Brief – 22 January
- Implementation – 27 January

## Red – New GSI

- operational through day 12 in Northern Hemisphere

**Red – New GSI**
**Black – Operational**

## Red – New GSI

**Red – New GSI**
**Black – Operational**

- New GSI generally better than current operational through day 11 in Southern Hemisphere

## Red – New GSI

**Black – Operational**

-  Threat Score better than current operational

- Bias better than current operational

## GFS vs. Proposed GSI

**Storm Tracks Derived**
** ****from GFS forecast**

- New GSI produces
- better storm tracks

## GFDL vs. GNEW

- New GSI produces
- slightly better
- GFDL storm tracks

## HWRF vs. H047

- New GSI produces
- slightly degraded
- HWRF storm tracks

## Global Ensemble Forecast System

## 3Q09 GEFS Upgrade

- Continue using current operational (n-1) GFS model
- Upgrade horizontal resolution from T126 to T190
- 4 cycles per day, 20+1 members per cycle
- Up to 384 hours (16 days)
- Use 8th order horizontal diffusion for all resolutions
- Improved forecast skills and ensemble spread
- Upgrade to ESMF (Earth System Modeling Framework) for GEFS Version 3.1.0r
- Allows concurrent generation of all ensemble members
- Needed for efficiency of stochastic perturbation scheme
- Add stochastic perturbation scheme to account for random model errors
- Increased ensemble spread and forecast skill (reliability)
- Add new variables (26 more) to pgrba files
- Based on user request
- From current 52 (variables) to future 78 (variables)
- For NAEFS ensemble data exchange

## 3Q09 GEFS Schedule

- 30-Day evaluation will begin on Power6 system when NCO has completed a sufficient portion of the transition to free up staff resources
- Package would run in parallel on the P6 and become operational when the P6 becomes operational in mid-July

## NAEFS future configuration

|  | NCEP | CMC |
| --- | --- | --- |
| Model | GFS | GEM |
| Initial uncertainty | ETR | EnKF |
| Model uncertainty | None | Yes |
| Stochastic physics | Yes | Yes  |
| Tropical storm | Relocation | None |
| Daily frequency | 00,06,12 and 18UTC | 00 and 12UTC |
| Resolution | T190L28 (d0-d16)~70km | (d0-d16) ~1.0degree |
| Control  | Yes | Yes |
| Ensemble members | 20 for each cycle | 20 for each cycle |
| Forecast length | 16 days (384 hours) | 16 days (384 hours) |
| Post-process | Bias correction
for ensemble mean | Bias correction 
for each member |
| Last implementation  | July 2009 (plan) | July 10th 2007 |

_**NAEFS future configuration**_
- _Updated: December 2008_

## Horizontal resolution change

- _26 : 4_

_**Horizontal resolution change**_
- Ensemble control only (deterministic)
- From T126 to T190
- NH 500hPa geopotential height

- _Gains from short waves_

## May 2007

- OPR(T126)-4th order
- NHD(T126)-8th order

- _May 2007_

- _November 2007_

_**Horizontal diffusions**_
- Ensemble controls only

## Resolution and Diffusion for Global Ensemble

- E20s – T126 4th for all 16d (oper.)
- E20x – T190 8th out to 16d
- E20e – T190 8th (0-180h), then T126 4th

- When reducing resolution from T190 (8th order) to T126 (4th order), the ensemble forecast probabilistic skill score tends to t126 immediately, the example shows here for tropical 850hPa temperature. 8th order diffusion for t126 somewhat improves performance (not show here). Therefore, both the resolution and diffusion play an important role here.

_**Resolution and Diffusion for Global Ensemble**_

## Latest retrospective run (full package)

- _NH 500hPa height_
- _RMSE & Spread_

- _SH 500hPa height_
- _CRPSS_

- _NH 2-m temperature_
- _RMSE & Spread_

- _NH 500hPa height_
- _CRPSS_

- _E20s – T126L28_
- _E20g – T190L28 (0-180 only)_

_**Latest retrospective run (full package)**_

## CRPSS for NH 850hPa temperature

- Extend current 5-day skill to 6.5-day

- Extend current 5-day skill to 6-day

**OPER**

**OPER**

**EXP**

**EXP**

## NH Anomaly Correlation for 500hPa HeightPeriod: August 1st – September 30th 2007

- GEFSg is better than GFS at 48 hours

- GEFSg could extend skillful forecast (60%) for 9+ days
- 24 hours better than current GEFS
- 48 hours better than current GFS

## Conclusion

- Based on two sets of retrospective runs (summer and winter 2007)
- New package improved the forecast skill (score) significantly
- For deterministic (ensemble mean)
- For probabilistic (ensemble distribution)
- The better results is benefited from:
- Increase horizontal resolution (include diffusion)
- Stochastic perturbation scheme
- Better initial condition (analysis)
- Better forecast model (GFS)

## Experimental Coupled Ocean-Atmosphere Model

- No GSI changes
- RRTM1 long-wave radiation
- More accurate absorption coefficients
- RRTM shortwave radiation
- Major improvement in upper stratospheric cloudy skies
- Maximum-random cloud overlap for shortwave
- Unifies cloud treatment for long & shortwave radiation
- Hourly long-wave radiation
- Better definition of diurnal cycle.  Makes scheme consistent with short-wave radiation
- Generalized aerosol treatment
- Code efficiency.  Aerosol algorithms will not have to be rewritten when radiation schemes change.

## Experimental Coupled Ocean-Atmosphere Model (Cont)

- Realistic CO2
- Model had been using old climatology.  Now uses observed CO2
- Retuned mountain blocking
- Update parameters for T382
- Shallow convection up to sigma 0.7
- Permits shallow convection over high terrain
- Convective gravity wave drag
- Improve stratospheric tropical winds
- Improved low level Stratus – withdrawn early
- Enthalpy thermodynamic prognostic variable
- Improved Mesosphere for SWPC
- Coupling with MOM4 Ocean Model
- Improved week 2 forecast

## Operational GFS

**Operational GFS**
**Proposed GSI**
**Coupled GFS**

**Proposed Coupled System**** shows**
**reduced Threat Score and an  **
**increase in Precipitation Bias for**
**larger amounts compared to GSI**

## Physics Package without coupling

**Physics Package without coupling**
**shows only a slight reduction in**
**Threat Score but increase in **
**Precipitation Bias remains**

## Operational GFS

**Operational GFS**
**Proposed GSI**
**Couled GFS**

**Proposed Coupled System**
**Shows reduction in**
**NH 500 MB Anomaly Corr**
**compared to GSI**

## Physics Package without

**Physics Package without**
**coupling** **produces a larger **
**degradation in NH 500**
**mb Anomaly Correlation**

## Removing Enthalpy change (PRC8) shows

- Removing Enthalpy change (PRC8) shows
- An improvement in Threat Score, but still
- shows increase in Precipitation Bias for
- higher amounts

## Removing Enthalpy change (PRC8) 

- Removing Enthalpy change (PRC8)
- produces an improvement in 500 mb
- Anomaly Correlation

## Removing Enthalpy change

- produces improvement in RMS
- error for upper level tropical winds

## Removing Enthalpy change

- produces improvement in NH
- RMS temperature error

## Removing Enthalpy change

- produces improvement in
- NH RMS height error

## Removing Enthalpy change

- produces improvement in
- tropical wind bias

## Preliminary Summary 

- Objective analysis indicates significant improvement in a number of areas, but precipitation bias remains an issue.
- Do significant improvements in Height, Threat, & Hurricane Track outweigh the increase in precipitation bias?
- Testing of the Physics Package will continue with hopes of 3Q08 implementation

## Preliminary Summary 

- Objective analysis indicates significant improvement in a number of areas, but precipitation bias remains an issue.
**Do improvements in Height, & Threat outweigh the increase in precipitation bias?**
- Testing of the Physics Package will continue with hopes of 3Q08 implementation

## Future Approach 

- Continued development of major model upgrades
- Semi-Lagrangian Model
- Increased Model Resolution
- Identify know model weaknesses and develop targeted changes to address those short comings
- Identify poor forecasts from subjective scores and focus on diagnostics

## Poor forecasts or Skill Score “Dropouts” lower GFS performance.

*Poor forecasts or Skill Score “*_***Dropouts***_*” lower GFS performance.*

- 20081001-19

- Significantly reduced skill in AC or RMS (not shown) occur a little
- more than once a month.
- Shown above are the GFS 00, 06, 12, and 18 Z cycle, and the
- ECMWF 00 and 12 Z cycle anomaly correlation skill scores for 20-80 NH
- for the first half of October 2008 .

## GFS Diagnostics of “Dropouts”

## GFS Diagnostics of “Dropouts” (cont)

## Tools to compare ECMWF and NCEP Dropouts

- “ECM” Analysis: Use ECMWF analysis to generate “Pseudo Observations” for input to the Gridded Statistical Interpolation (GSI) to make analyses, for initial conditions, and integrate GFS forecasts.
- Compare these ECM runs with GFS runs made in the same way and w/ production.
- A Climatology of NH and SH dropouts – what are the systematic differences
- Interpolate ECM and GSI analyses to observations to determine comparative strengths and weaknesses.
-  using statistics of observation type fits
-  stratify by pressure, type, and difference magnitude
- Goal:	*Diagnose Quality Control problems,*
*	**	**Implementation of real time QC detection/correction and improvements to analysis system algorithms*

## GFS:         Operational (Production) GFS

**GFS**:         Operational (Production) GFS
**ECMWF**: Their Operations
**ECM**:        Pseudo Obs from ECMWF analysis using the GSI as a “Grand Interpolator
**CNTRL**:   Updated GSI system with GDAS observations (GSI details change often across 	 the dropout accumulation period)
**InterpGES**:  Updated GSI with previous 3, 6, & 9-hour ECM forecasts as background guess plus GDAS observations

- GFS forecasts from
- ECMWF IC alleviate
- production dropouts

- New GSI is
- improvement but does not usually alleviate
- dropout

## Results from SH Dropout Experiments

- 90% ECM success in alleviating SH dropouts.
- Adding GDAS Obs (ecmanlGES) lowers the success rate to ~75%.
- GSI upgrades (CNTRL GFS Operations plus all Obs) improves GSI but not enough to alleviate dropouts
- InterpGES (Background Guess from ECM plus all Obs) runs also improves GSI but not enough to alleviate dropouts
- Composites show low level SH difference near 850mb in temperature.
*Adding the SH observations and the 3, 6, 9-h background guess degrade the ECM forecasts (from runs with ECM as the background guess)*

## Summary and Future Work

- ECM analysis show dropouts can be alleviated in GFS forecasts.
- Running the operational GSI with an ECM background guess offers a systematic approach for assessing observation types by removing observation types from control analyses
- There are systematic height differences between all models and ECMWF perhaps from the satellite window coverage of ECMWF (12-h) vs others (6-h)
- Work continues to analyze what is the optimal fit of analysis to observation types and to determine an implementable algorithm for QC, bias correction, and analysis weights

## Know Model Weaknesses(from internal evaluation)

- Large growth in rms error in first 24 hours in midlatitudes
- Large growth in rms error in first 48 hours in tropics
- Too much surface downward short wave radiation
- Warm low-level bias over western US in summer
- Negative height bias over Antarctica
- Poor scores in Southern Hemisphere
- Lack of stratus clouds in fcsts; displacement of stratus clouds from coasts
- Higher precipitation than independent estimates
- Cold bias over US in winter
- Negative moisture
- Relatively low QPF scores
- Failure to maintain rising motion over Indonesia in the forecasts
- Failure to capture early stages (TD) of tropical systems

## Know Model Weaknesses(from user feedback)

- High bias for areal coverage of low QPF amounts (< 0.10 in.)
- Grid scale overturning induces spurious mid-level vorticity maxima, particularly in the warm season.
- Too cold with the melting layer in wintry precipitation events
- Too flat with strongly amplifying troughs/closed lows in the western U.S. resulting in the model being too fast to eject these systems out to the east
- Too far east with the track of East Coast/Gulf Stream cyclones
- Lack of terrain resolution adversely impacts QPF in the western U.S. and in other areas of complex terrain, such as southern Mexico.
- GFS forecasts conditions favorable for heavy lake effect snow but has low amounts of QPF
- Routinely places a trough over the eastern Brooks Range in Alaska
- Too weak and fast with well-developed Pacific systems more than a couple of days into the forecast period
- Too aggressive bringing energy into the western side of ridges
- Cold bias in the longer ranges over the eastern U.S./western Atlantic
- Surface lows coming out of the west into the Plains are too far north The model tends to focus too much QPF in the cold sector of cyclones

## Schedule for Future Upgrades

- Power6 transition impacting possible FY09 implementations
- Physics upgrade on Power6 when it becomes operational in July 2009
- The go-operational date is during Hurricane Season, which would produces implementation of both GFS and HWRF during Hurricane Season.
- Next window would be 1Q10

## Schedule for Future Upgrades

- Earliest possible implementation of major upgrade package would be mid to late FY10
- Minor changes to improve efficiency and streamline post processing and product generation can take place at any time after the Power6 is operational
- Changes will not impact forecast product quality

## Questions