Review of NCEP GFS Forecast Skills and Major Upgrades

Fanglin YangIMSG - Environmental Modeling Center

National Centers for Environmental Prediction Camp Springs, Maryland

ESRL/GSD Assimilation and Modeling Branch Weekly Meeting, May 4th, 2012

Acknowledgments: numerous scientists at NCEP/EMC and in the community have made contributions to the development and application of the GFS. For this presentation, I would like to thank in particular Joseph Sela, Moorthi Shrinivas, Hualu Pan, Stephen Lord, Bill Lapenta, John Derber, Mark Iredell, Glenn White, Russ Treadon, Mike Ek, Henry Juang, Yu-Tai Hou, Suru Saha, Bob Kistler, Jordan Alpert, Daryl Kleist, Jongil Han, Peter Caplan, Yuejian Zhu, Jun Wang, Helin Wei, Sarah Lu, Hui-Ya Chuang and many others I am not be able to include here.

Annual Mean 500-hPa HGT Day-5 Anomaly Correlation19

8419

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0.55

0.65

0.75

0.85GFS-NHCDAS-NHGFS-SHCDAS-SH

In past 25 years GFS anomaly correlations increased by about 0.3 in both hemispheres (0.12/decade)

Annual Mean NH 500hPa HGT Day-5 AC

0.600000000000001

0.650000000000001

0.700000000000001

0.750000000000001

0.800000000000001

0.850000000000001

0.900000000000001 GFS-NHCDAS-NHECMWF-NHUKM-NHCMC-NHFNOMC-NH

• GFS falls behind ECMWF all the time.• GFS and UKMO were comparable for most of the time, but GFS trails UKMO

in recent years. • FNOMC has made significant improvement since 2009.

Annual Mean SH 500hPa HGT Day-5 AC19

8419

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0.55

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0.85

0.9GFS-SHCDAS-SHECMWF-SHUKM-SHCMC-SHFNOMC-SH

2011 Annual Mean 500hPa HGT AC

6

• GFS falls behind EC and UK, but is better than CMC, FNO and JMA.• GFS useful forecasts (>0.6) reached 8.0 days in the NH and 7.8 days

in the SH.

NH SH

0.6 – useful forecast

Day at which forecast loses useful skill (AC=0.6) N. Hemisphere 500hPa height calendar year means

Fore

cast

day

8 d

Credit:, Peter Caplan, Yujian Zhu, Fanglin Yang

8

Twenty bins were used to count for the frequency distribution, with the 1st bin centered at 0.025 and the last been centered at 0.975. The width of each bin is 0.05.

Look at the history of extremes in the distribution– Poor Forecasts (AC < 0.7 )– Excellent forecasts ( AC > 0.9 )

Reduced poorforecasts

10

Resolution:

1.2/2000: T126L28 T170L42 (70km)

2.11/2002: T170L42 T254L64 (55km)

3.6/2005: T254L64 T382L64 (38km)

4.7/2010: T382L64 T574L64 (23km)

Percent of Poor Forecasts (AC <0.7) v.s. Model Changes

Physics and Data Assimilation:

A. 3/1999: AMSU-A & HIRS-3 data

B. 5/2001: prognostic cloud water, cumulus momentum transport

C. 6/2005: OSU 2-L LSM to 4-L NOHA LSM

D. 5/2007: SSI to GSI; Hybrid sigma-p; New observations

E. 2/2009: flow-dependent error covariance; Variational QC

F. 7/2010: New shallow convection; updated SAS and PBL; positive-definite tracer transport.

A

1

B

2

3, C

4, F

year

NH

11

Percent of Poor Forecasts (AC <0.7) v.s. Model Changes

A

1

B

2 3, C 4, F

year

SH

D

Physics and Data Assimilation:

A. 3/1999: AMSU-A & HIRS-3 data

B. 5/2001: prognostic cloud water, cumulus momentum transport

C. 6/2005: OSU 2-L LSM to 4-L NOHA LSM

D. 5/2007: SSI to GSI; Hybrid sigma-p; New observations

E. 2/2009: flow-dependent error covariance; Variational QC

F. 7/2010: New shallow convection; updated SAS and PBL; positive-definite tracer transport.E

Resolution:

1.2/2000: T126L28 T170L42 (70km)

2.11/2002: T170L42 T254L64 (55km)

3.6/2005: T254L64 T382L64 (38km)

4.7/2010: T382L64 T574L64 (23km)

12

Major GFS Upgrades

• 3/1999– AMSU-A and HIRS-3 data

• 2/2000– Resolution change: T126L28 T170L42 (100 km 70 km)– Other changes

• 7/2000 (hurricane relocation)• 8/2000 (data cutoff for 06 and 18 UTC)• 10/2000 – package of minor changes• 2/2001 – radiance and moisture analysis changes

• 5/2001– Major physics upgrade (prognostic cloud water, cumulus momentum transport)– Improved QC for AMSU radiances– Other changes

• 6/2001 – vegetation fraction• 7/2001 – SST satellite data• 8/200 – sea ice mask, gravity wave drag adjustment, random cloud tops, land surface evaporation,

cloud microphysics…)• 10/ 2001 – snow depth from model background• 1/2002 – Quikscat included

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GFS Changes (cont)• 11/2002

– Resolution change: T170L42 T254L64 (70 km 55 km)– Recomputed background error– Divergence tendency constraint in tropics turned off– Other changes

• 3/2003 – NOAA-17 radiances, NOAA-16 AMSU restored, Quikscat 0.5 degree data• 8/2003 – RRTM longwave and trace gases• 10/2003 – NOAA-17 AMSU-A turned off• 11/2003 – Minor analysis changes• 2/2004 – mountain blocking added• 5/2004 – NOAA-16 HIRS turned off

• 5/2005– Resolution change: T254L64 T382L64 ( 55 km 38 km )– 2-L OSU LSM 4-L NOHA LSM– Reduce background vertical diffusion– Retune mountain blocking– Other changes

• 6/2005 – Increase vegetation canopy resistance• 7/2005 – Correct temperature error near top of model

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GFS Changes (cont)•8/2006

– Revised orography and land-sea mask– NRL ozone physics– Upgrade snow analysis

•5/2007– SSI (Spectral Statistical Interpolation) GSI ( Gridpoint Statistical Interpolation). – Vertical coordinate changed from sigma to hybrid sigma-pressure– New observations (COSMIC, full resolution AIRS, METOP HIRS, AMSU-A and MHS)

•12/2007– JMA high resolution winds and SBUV-8 ozone observations added

•2/2009– Flow-dependent weighting of background error variances– Variational Quality Control– METOP IASI observations added– Updated Community Radiative Transfer Model coefficients

•7/2010– Resolution Change: T382L64 T574L64 ( 38 km 23 km )– Major radiation package upgrade (RRTM2 , aerosol, surface albedo etc)– New mass flux shallow convection scheme; revised deep convection and PBL scheme– Positive-definite tracer transport scheme to remove negative water vapor

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Tropical Wind RMSE, 850-hPa Day-3 Forecast

July2010 T574 GFS Implementation

GFS tied with EC and UK after July 2010 implementation.

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Tropical Wind RMSE, 200-hPa Day-3 Forecast

• GFS has larger wind RMSE than EC and UK at the tropopause region.

• Improvement in the past 15 years is not significant.

Hurricane Track and Intensity Forecast Errors

2011 Hurricane Track and Intensity Forecast Errors

2011 Atlantic Hurricanes

2011 Eastern Pacific Hurricanes

http://www.wikipedia.org

2011 Atlantic Hurricane Track and Intensity Errors

22AVNO = GFSEMX = ECMWF 00Z and 12Z cycles

2011 Eastern Pacific Hurricane Track and Intensity Errors

23AVNO = GFSEMX = ECMWF 00Z and 12Z cycles

Hurricane Track and Intensity Forecast Errors

GFS: 2001-2011

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 20110

50

100

150

200

250

300Atlantic Hurricane Track Errors

0

12

24

36

48

72

96

120 (fhr)

Trac

k Er

ror (

nm)

Forecast within 3 days has been steadily improving, although the pace is slow. Beyond day 3, forecast still varies from year to year.

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 20110

50

100

150

200

250

300Eastern Pacific Hurricane Track Errors

0

12

24

36

48

72

96

120 fhr

Trac

k Er

ror (

nm)

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 201110

20

30

40

50Atlantic Hurricane Intensity Errors

0

12

24

36

48

72

96

120 (fhr)

Inte

nsity

Err

or (k

ts)

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28-July-2010 Implementation

Resolution Change & Major Physics Upgrade

• Major changes• Testing and evaluation• Benefits and remaining issues

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Major Changes

• Resolution and ESMF– T382L64 to T574L64 ( ~38 km -> ~27 km) for fcst1 (0-192hr) & T190L64 for fcst2

(192-384 hr) .– fcst2 step with digital filter turned on– ESMF 3.1.0rp2

• Radiation and cloud– Changing SW routine from NASA/ncep0 to AER RRTM2– Changing longwave computation frequency from three hours to one hour– Adding stratospheric aerosol SW and LW and tropospheric aerosol LW– Changing aerosol SW single scattering albedo from 0.90 in the operation to 0.99– Changing SW aerosol asymmetry factor. Using new aerosol climatology.– Changing SW cloud overlap from random to maximum-random overlap– Using time varying global mean CO2 instead of constant CO2 in the operation– Using the Yang et al. (2008) scheme to treat the dependence of direct-beam surface

albedo on solar zenith angle over snow-free land surface

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Example: Improving GFS Surface Albedo Using ARM-SURFRAD Observations

Dependencies of direct-beam albedo, normalized by the diffuse albedo, on SZA. The ten colored long-dashed lines represent the empirical fits derived from observations at the three ARM and seven SURFRAD stations for the entire-day cases. The blue line with filled circles is based on the observations at all stations except the Desert Rock station (the line with crosses). The black lines with open circles and squares are governed by the NCEP GFS parameterization with the constant being set to 0.4 and 0.1, respectively.

Fits using data at ARM and SURFRAD stations

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1 cos34.2cos92.4cos02.427.2,

mndiff

mndirf

322 cos02.2cos13.4cos34.389.1

,60

,

omndir

mndirf

Fanglin Yang, Kenneth Mitchell, Yu-Tai Hou, Yongjiu Dai, Xubin Zeng, Zhou Wang, and Xin-Zhong Liang, 2008: Dependence of land surface albedo on solar zenith angle: observations and model parameterizations. Journal of Applied Meteorology and Climatology. No.11, Vol 47, 2963-2982.

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• Gravity-Wave Drag Parameterization – Using a modified GWD routine to automatically scale mountain block and

GWD stress with resolution.– Compared to the T382L64 GFS, the T574L64 GFS uses four times stronger

mountain block and one half the strength of GWD.

• Removal of negative water vapor– Using a positive-definite tracer transport scheme in the vertical to replace

the operational central-differencing scheme to eliminate computationally-induced negative tracers.

– Changing GSI factqmin and factqmax parameters to reduce negative water vapor and supersaturation points from analysis step.

– Modifying cloud physics to limit the borrowing of water vapor that is used to fill negative cloud water to the maximum amount of available water vapor so as to prevent the model from producing negative water vapor.

– Changing the minimum value of water vapor mass mixing ratio in radiation from 1.0e-5 in the operation to 1.0e-20. Otherwise, the model artificially injects water vapor in the upper atmosphere where water vapor mixing ratio is often below 1.0e-5.

Major Changes

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Vertical Advection of Tracers: Current GFS Scheme

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p

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t

q Flux form conserves mass

2

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Current GFS uses central differencing in space and leap-frog in time.

The scheme is not positive definite and may produce negative tracers.

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Example: Removal of Negative Water Vapor

Fanglin Yang et al., 2009: On the Negative Water Vapor in the NCEP GFS: Sources and Solution. 23rd Conference on Weather Analysis and Forecasting/19th Conference on Numerical Weather Prediction, 1-5 June 2009, Omaha, NE

Sources of Negative Water Vapor• Vertical advection• Data assimilation• Spectral transform• Borrowing by cloud water• SAS Convection

Ops GFS

_

Positive-definite

Data Assimilation

A: vertical advection, computed in finite-difference form with flux-limited positive-definite scheme in space

Flux-Limited Vertically-Filtered Scheme, central in time

1*

2

1 nk

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B: horizontal advection, computed in spectral form with central differencing in space

Data Assimilation

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Vertical Advection of Tracers: Flux-Limited Scheme

1211121 k

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121 2

1 kk

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11

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kk

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Van Leer (1974) Limiter, anti-diffusive term

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Special boundary conditions

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0 if 2 ,0max

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0q

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Vertical Advection of Tracers: Flux-Limited Scheme

kHkkkk qqqq

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Thuburn (1993)0 if 21 k

121 2

1 kk

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rr

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Van Leer (1974) Limiter, anti-diffusive term

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Lfor kSpecial boundary condition

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L

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rr

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0 if 2 ,0max

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Vertical Advection of Tracers: Idealized Case Study

wind

Upwind (diffusive)

Flux-Limited

GFS Central-in-Space

Initial condition

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Summary: Negative Water Vapor in the GFS

Causes Importance Solutions

Vertical Advection 1. Semi-Lagrangian2. Flux-Limited Positive-Definite Scheme for current Eulerian GFS

GSI Analysis Tuning factqmin and factqmax

Spectral Transform 1. Semi-Lagrangian GFS: running tracers on grid, no spectral transform2. Eulerian GFS: no solution yet.

Cloud Water Borrowing Limiting the borrowing to available amount of water vapor

SAS Mass-Flux Remains to be resolved

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• New mass flux shallow convection scheme (Han & Pan 2010)– Use a bulk mass-flux parameterization same as deep convection scheme– Separation of deep and shallow convection is determined by cloud depth (currently 150 mb)– Entrainment rate is given to be inversely proportional to height (which is based on the LES

studies) and much smaller than that in the deep convection scheme– Mass flux at cloud base is given as a function of the surface buoyancy flux (Grant, 2001), which

contrasts to the deep convection scheme using a quasi-equilibrium closure of Arakawa and Shubert (1974) where the destabilization of an air column by the large-scale atmosphere is nearly balanced by the stabilization due to the cumulus

• Revised deep convection scheme (Han & Pan 2010)– Random cloud top selection in the current operational scheme is replaced by an entrainment

rate parameterization with the rate dependent upon environmental moisture– Include the effect of convection-induced pressure gradient force to reduce convective

momentum transport (reduced about half)– Trigger condition is modified to produce more convection in large-scale convergent regions but

less convection in large-scale subsidence regions– A convective overshooting is parameterized in terms of the convective available potential

energy (CAPE)

Major Changes

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• Revised Boundary Layer Scheme (Han & Pan 2010)– Include stratocumulus-top driven turbulence mixing based on Lock et al.’s

(2000) study– Enhance stratocumulus top driven diffusion when the condition for cloud top

entrainment instability is met– Use local diffusion for the nighttime stable PBL rather than a surface layer

stability based diffusion profile– Background diffusivity for momentum has been substantially increased to 3.0

m2s-1 everywhere, which helped reduce the wind forecast errors significantly

• Hurricane relocation– Running hurricane relocation at the 1760x880 forecast grid instead of the

1152x576 analysis grid– Posting GDAS pgb files first on Guassian grid (1760x880), then convert to 0.5-

deg for hurricane relocation.

Major Changes

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Operational shallow convection scheme (Diffusion scheme, Tiedke, 1983)

New shallow convection scheme (Mass flux scheme)

Mass flux analogy (de Roode et al., 2000) :

Au (updraft area)=0.5

Ad (downdraft area)=0.5

Au~0.0; Ad~1.0

Environment is dominated by subsidence resulting in environmental warming and drying.

Example: New Mass-Flux Based Shallow ConvectionBy Jongil Han and Hua-lu Pan

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Ops GFS New shallow convection scheme

Heating by Shallow Convection

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ISCCP

Last Operational GFS New Shallow

Low cloud cover (%)

Marine StratusStratocumulus

Han and Pan, 2010

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No stratocumulus top driven diffusion

With stratocumulus top driven diffusion

Low cloud cover (%)

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Reduce unrealistic excessive heavy precipitation (so called grid-scale storm or bull’s eye precipitation)

New

24 h accumulated precipitation ending at 12 UTC, July 24, 2008 from (a) observation and 12-36 h forecasts with (b) control GFS and (c) revised model

OBS CTL

Upcoming Changes

Hybrid-Ensemble Data Assimilation. Implementation scheduled for May 22nd, 2012.

Semi-Lagrangian dynamics, T1148L64. Implementation ??

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T574L64 Hybrid Ensemble GFS

NH

SH

The parallel outperformed operational GFS in both NH and SH.

Increases in the SH is historical.

Parallel run by Russ Treadon

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T574L64 Hybrid Ensemble GFS Parallel

Tropical Wind RMSE, verified against model analyses

Global Temp RMSE, verified against RAOBS

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Most Recent T1148L64 Semi-Lag GFS Test

NH

SH

Promising, but still has issues. Still testing different package options and tunable parameters.

Parallel run by Fanglin Yang on ESRL Jet