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Recent and future changes in the NCEP Global Forecast System

Glenn White

Global Climate and Weather Modeling Branch Environmental Modeling Center

National Centers for Environmental PredictionNWS/NOAA/DOC

Presented byFanglin Yang

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Contents

1. 27-July-2010 Major Upgrade: Model Physics Change

2. May-9-2011 Minor Upgrade: Data Assimilation and Forecast Model

3. 22-May-2012 Major Upgrade: GSI Hybrid 3D-Var-EnKF.

4. Future Changes

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

(192-384 hr) .–

• 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

• 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.

28-July-2010 Major Implementation

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• 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.

• 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

Physics Changes

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• 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)

• 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

Physics 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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Cloud liquid water 15S7 day forecasts

T382 operationalT574

T574 with new convectionNew convection maintainsEastern ocean stratus in 7 day ForecastsNew convection increasesLow level stratus, realistic tiltWith longitudeDecreases CLW near 700

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

New

24 h 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

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New Issues:

1) Warm bias western US increased—decreased cloud liquid water, fewer clouds

Solution: New thermal roughness length reduces warm bias

2) QBO too weak Solution: Decrease background diffusion

3) Warm bias in tropics in upper troposphere

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T382 GFS is closer to ECMWF than the T574 GFS does.T574 GFS has weaker easterly than T382 GFS in 2009 and 2010.

A model problem? A GSI problem? Or both?

T574ECMWF

Ops T382

QBO transition from westerly phase to easterly phase

Fanglin Yang

Increased background diffusion may be to blame; changes to diffusion being tested

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Changes to GSI : - Upgrade to CRTM 2.0.2. - Inclusion of FOV size/shape for RT. - Moisture limited to >=1e-10 in outer iteration. - Relax QC for AMSU-A channel 5. - Ozone assimilation changes: retune SBUV version-8 ob errors. turn off assimilation of

total column SBUV version-8 ozone. turn on assimilation of N19 SBUV version-8 data. Radiance assimilation changes: - turn off assimilation of AMSU-B N15, turn on assimilation of MHS N19. Conventional data changes: - turn on assimilation of ASCAT winds. - turn on assimilation of GPS data from new satellites TerraSAR-X (id 042), C/NOFS (id

786) and SAC-C (id 820). - Retuned background error variances.

-Changes to GFS :- Correction to stratospheric water vapor limit- Thermal roughness- Background diffusion decreased in stratosphere

May-9-2011 Minor Upgrade

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Northern Hemisphere troposphere improved

Tendency for greater day 1 errors at low levels, especially tropics and Southern Hemisphere

Stratospheric rms errors in temperature and wind tend to be worse

GFS change • reduced low level warm bias over North America in

summer • reduced negative low level wind bias• increased wind speeds in tropical stratosphere

New GSI warmer analyzed temperatures over sea ice GFS weakens the warmer temperatures, resulting in greater errors In polar regions Which is wrong—GSI or GFS?

Fits to obs better in troposphere, worse in stratosphere

Rain/no-rain over CONUS worse in summer/fall, better in winter

Bias worse in summer/fall, improved in winter

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10m winds 24 hr forecasts averaged over Mar1-May 9 2011

OLDGSI + GFS bug fix

Effect of changesOn 10 m wind

Zonal wind 35 N Effect of changes

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GSI Hybrid 3D-Var-EnKFMay 22, 2012 Major Upgrade

See Presentation 1B1.1 b y William Lapenta

Under development since Jan 2010

Deterministic Forecasts: Operational GFS @ T574L64

Ensemble Configuration: 80 ensemble members out to 9h GSI for observation operators T254L64 using operational GFS configuration

Assimilate all operational observations Includes early (GFS) and late (GDAS/cycled) cycles Operational prepbufr files (no prep/additional qc)

Dual-resolution/Coupled High resolution control/deterministic component (T574L64) Ensemble is recentered every cycle about hybrid analysis Throw out EnKF analyis mean

Bias correction (satellite) coefficients come from GSI/VAR

Minimal tuning done for hybrid 1/4 static B, 3/4 ensemble

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• significantly improves most fields in troposphere during Week 1,

• significantly improves week 1 stratosphere outside the tropics and week2 troposphere and stratosphere in the Northern Hemisphere

• GSI hybrid forecasts fit observations better, but GSI hybrid analyses do not

• RMS fits of 2 meter temperature, 10 m winds to surface obs over CONUS tends to be reduced;

• Precip over CONUS some improvement in winter for day 2

• In summer day 1 rain/no rain slightly worse. GSI hybrid has more rain than operational over CONUS, increasing positive bias for light amounts.

• some evidence of more bullseyes in precipitation

GSI Hybrid 3D-Var-EnKFMay 22, 2012 Major Upgrade

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• Cloud Assimilation

• Hybrid enhanced (4d+) assimilation

• New observations – NPP, JPSS, GOES-R, METOP-B, etc.

• Aerosol and trace gas assimilation

• T1148 semi-Lagrangian or T878 Eulerian

• Improvements to radiation, land surface, convection, diffusion

• Coupled NWP system

• 91 levels

Future GFS Improvements

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Extra slides

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A tale of three successful implementations…

(And the problems they caused)

“We make mistakes and we correct most of them”

Joe Sela

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EMC has started a Model Evaluation Group

To increase synoptic evaluation and awareness

within EMC

to reduce number of surprise problems

After implementation

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Note weakerWinds at jet levelIn NH, betterfits to radiosondes

Note weaker winds in tropics At low levels—Potential Aviation hazardEast Caribbean

Old T382NewT574

Fit of 24 and 48 hr forecast winds to radiosondes

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Pre1: T382pre2: T574 Outstanding Issues: large tropical wind RMSE in the upper troposphere and stratosphere; large NH height bias near surface and in the lower troposphere in week one.pre2a: T574 with adjusted GWD and mountain block. What's Good: removed the large NH height bias near surface and in the lower troposphere in week one.Outstanding Issues: large tropical wind RMSE in the upper troposphere and stratosphere

Many more parallel tests run to determine best tuning of mountain forcing

Pre4: As pre2a, plus new radiation and albedoPre5a: As pre4,except with doubled GWDPre5b: As pre5, except with doubled mountain blockingPre5c: As pre5, except with 4 times stronger mountain blockingPre5d: As pre5, except with 8 times stronger mountain blockingPre5e: As pre5, except with 4 times stronger mountain blocking and half GWDPre5f: As pre5c, except with correction to remove negative water vapor

Parallel tests of higher resolution, mountain forcingFanglin Yang, Jordan Alpert

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Higher resolution by itselfChanges time-mean flow

Adjusted drag removes changeTo time-mean flow

Effect of higher resolutionHigher resolution plus Tuning of orographic forcing

Effect of tuning of orographic forcing

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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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New Issues:

1) Warm bias western US increased—decreased cloud liquid water, fewer cloudsSolution: New thermal roughness length reduces warm bias

2) Winds too weak—jet levelSolution: Decrease background diffusion

3) QBO too weakSolution: Decrease background diffusion

4) Easterly wind surges too weak over subtropical Atlantic

5) Too few clouds over oceans outside stratus regions

6) Warm bias in tropics in upper troposphere

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Northern Hemisphere Temperature bias againstGFS analyses

Low level bias increases when new GFS forecasts verify

Day 1 forecasts

Day 3 forecasts

Day 5 forecastsT574 Implementation: July 28, 2010

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• Stronger low level winds due to thermal roughness change

• Reduced a weak bias in low level winds

• However, bias corrected Model Output Statistics from MDL did not change bias correction

• Therefore bias corrected winds stronger, triggered false alarms for strong winds

• MDL redid bias correction for winds

Interaction with Downstream Users

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____ ECMWF____ GFS____ CDAS (frozen 1995)

Change in July 2010 improved500 height day 5 anomaly correlations

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Percent of Excellent Forecasts (AC >0.9)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 160

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20

30

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Percent Anomaly Correlations Greater Than 0.9GFS 00Z Cycle Day-5 500hPa Height

NH SH

Year

%

1996 2001200019981997 1999 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

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GFS Tuning reduces negative bias near 50 hPa

Summer FallTropics

Operational Package

New GSI

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

July 2010 implementation

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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

nk

nk AAA

nk

nkhh AB

p

qqV

t

q

*11 2 nk

nk

nk

nk AtBtqq

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

Data Assimilation

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New GSI

Summer

Package

Effect of GFS tuningGFS acts to reduce warming at low levels in NH midlatitudes

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Tuning reduces Low level Temperature error in NH midlatitudes

New GSISummer

New GSI+ GFS tuning

Effect of GFS tuning

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GSI Hybrid 3D-Var-EnKFMay 22, 2012 Major Upgrade

Under development since Jan 2010

Deterministic Forecasts: Operational GFS @ T574L64

Ensemble Configuration: 80 ensemble members out to 9h GSI for observation operators T254L64 using operational GFS configuration

Assimilate all operational observations Includes early (GFS) and late (GDAS/cycled) cycles Operational prepbufr files (no prep/additional qc)

Dual-resolution/Coupled High resolution control/deterministic component (T574L64) Ensemble is recentered every cycle about hybrid analysis Throw out EnKF analyis mean

Bias correction (satellite) coefficients come from GSI/VAR

Minimal tuning done for hybrid 1/4 static B, 3/4 ensemble

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EnKFmember update

member 2 analysis

forecastGSI

Hybrid Ens/Var analysis

member 1 analysis

member 2 forecast

member 1 forecast

EnKF ensemble perturbations

are "re-centered" around the high-res

analysis

Dual-Resolution CoupledHybrid 3D-VAR/EnKF

member 3 forecast

member 3 analysis

Previous Cycle Current Update Cycle

T254

L64

T574

L64

Deterministic forecast

Uses background error covariances computed

from the ensemble

Replaces the EnKF ensemble mean analysis

first-guess ensemble used to estimate background error

covariances

Used for GFS forecasts for next cycle

Generating new ensemble perturbations given the latest set of observations and a first-guess

ensemble

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• significantly improves most fields in troposphere during Week 1, • significantly improves week 1 stratosphere outside the tropics and

week2 troposphere and stratosphere in the Northern Hemisphere

• GSI hybrid forecasts fit observations better, but GSI hybrid analyses do not

• RMS fits of 2 meter temperature, 10 m winds to surface obs over CONUS tends to be reduced;

• Precip over CONUS some improvement in winter for day 2

• In summer day 1 rain/no rain slightly worse. GSI hybrid has more rain than operational over CONUS, increasing positive bias for light amounts, decreasing negative bias for medium amounts

• some evidence of more bullseyes in precipitation

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GSI hybrid GSI hybrid

500 heightAnomaly correlation

Jan.-May 2012NorthernHemisphere

Southern Hemisphere

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Fit of 24 and 48 hr forecast winds to radiosondes

____old------ GSI hybrid

Jan-May 2012

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GSI hybrid GSI hybridGSI hybrid GSI hybrid

Worse skill in lightest amounts

Worse bias light amountsAugust 27-Oct 6, 2011