John H. WardChief, Global Climate & Weather Modeling Branch

December 7, 2011

Global Climate and Weather Modeling

NCEP Production Suite Review

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Outline

Personnel FY11 Upgrades FY12 and Beyond Global Model Roadmap

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Personnel

Global Modeling Modeling Team Lead S. Moorthi Glenn White Jordan Alpert Mike Young Yutai Hou Huiya Chuang DaNa Carlis Henry Juang Diane Stokes Mark Rozwodoski Qingfu Liu Suru Saha Fanglin Yang Sajal Kar Yali Ma Kate Howard Jia-Fong Fan

Climate Modeling Climate Team Lead Dave Behringer Xingren Wu

Infrastructure Mark Iredell – Lead Edward Colon Ratko Vasic Dusan Jovic Dmitry Sheinin Weiyu Yang Jun Wang Nicole McKee Patrick Tripp Eugene Mirvis

Ensembles Yuejian Zhu – Lead Dinchen Hou Jun Du Richard Wobus Bo Cui M. Pena-Mendez Jesse Ma Jiayi Peng Yan Lou Bo Yang

Physics Hualu Pan Jongil Han Ruiyu Sun

Feds - Blue Visiting Scientists – Red Contractor - Black

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Data Assimilation John Derber – Lead Russ Treadon Daryl Kleist George Gayno Andrew Collard David Groff Greg Krasowski Xu Li Haixa Liu Shun Liu Mike Lueken Michiko Masutani Dave Parrish Jim Purser Miodrag Rancic Xiujuan Su

MingJing Tong Paul Van Delst Wan-Shu Wu Yanqiu Zhu Fedor Mesinger Lidia Cucurull - Boulder

Personnel

Feds - Blue Contractor - Black Visiting Scientists – Red

Land Surface Mike Ek – Lead Jiarui Dong Jesse Meng Helin Wei Vince Wong Yihua Wu Youlong Xia Ringqian Yang Weizhong Zheng

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Personnel

Dynamics S. Moorthi Henry Juang Sajal Kar Jia-Fong Fan Mike Young Jordan Alpert

Post Processing/Product Huiya Chuang DaNa Carlis Yali Ma

Radiation/Physics Yutai Hou Hualu Pan Jongil Han Ruiyu Sun Suru Saha

Diagnostics/Verification Glenn White Fanglin Yang

Ocean/SST Dave Behringer Diane Stokes

Programming/User Support Kate Howard Mark Rozwodoski

Climate Modeling Xingren Wu

Tropical Storms Qingfu Liu

Ensembles Yuejian Zhu Dinchen Hou Jun Du Richard Wobus Bo Cui M. Pena-Mendez Jesse Ma Jiayi Peng Yan Lou Bo Yang

Infrastructure Mark Iredell Edward Colon Ratko Vasic Dusan Jovic Dmitry Sheinin Weiyu Yang Jun Wang Nicole McKee Patrick Tripp Eugene Mirvis

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FY11 Changes

NAEFS: Downscaling for Alaska – 12/7/2010 NAEFS: Inclusion of FNMOC Ens – 3/1/2011 CFSv2.0.0 – 3/30/2011

CFSv1 will continue to be run until further notice WAFS: Blended US/UK products

Parallel for evaluation – 1/25/2011 Initially evaluation complete Changes implemented based on feedback – 6/15/2011

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FY11 Changes

GDAS/GFS Bundle – 5/9/2011 Improvement in 10m winds in Southwest U.S. has

resulted in unrealistic GFS MOS winds MDL is testing a fix – no implementation date as yet

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FY12 & Beyond

NAEFS: GEFS Upgrade – 2QFY12 Global Aerosol System (GOCART) – 2QFY12 Hybrid EnKF-3DVar GSI Data Assimilation –

3QFY12 GFS Resolution Increase – 1QFY13 Transition to NEMS – 3QFY13

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Global Modeling Roadmap

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Basic Strategy

All candidate models will be ported to the NOAA R&D system at Fairmont Site-B

Operational GDAS & GFS will be ported to the NOAA R&D system It will become the baseline for all tests The baseline version will evolve as the operational

GDAS & GFS are upgraded Models will eventually be transitioned into the

NEMS framework

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Basic Strategy

Establish verification package Combined UKMET, ECMWF analysis will be used for verification

If all forecast hours and/or variables are not available to verify a full 16-day forecast, the verification may need to be augmented with analyses from one or more of the candidate models.

Current NCEP verification package will be used, with some modifications

Options to verify a single forecast starting at a specific initial time rather than forecasts valid at a specific time

Guarantee a homogeneous set of dates for all models being evaluated – missing dates from one model will be eliminated for all models

Include near surface, sensible weather elements into routine package Both Grid-to-Grid and Fit-to-obs will be verified Develop a UKMET-like index to aid in determining the overall impact

of proposed models Specific variables and weights will be determined prior to any model

testing

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Basic Strategy

Candidate Models GFS NMMB FIM Cubed-Sphere MPAS

Model configuration Each modeling may have one or more configurations with various

physics, dynamic, radiation, resolution, etc. All models will output pressure GRIB files on a standard lat-lon

grid Limiting factor is the operational resource window (CPU x Wall-

clock) Since codes may not scale the same on different architectures, they

must be ported to the operational system to ensure each configuration will fit within the operational resource window

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Basic Strategy

Model configurations will be tested as members of a multi-model ensemble Two Step Process

Test at full resolution against the operational GFS Configurations that perform within a given delta of the GFS will

then be considered for an ensemble member at lower resolution Evaluation of value-added to the ensemble will be

determined using the techniques developed for NAEFS Configurations which add value will be implemented into an

operational multi-model ensemble, replacing the current GFS-based GEFS

Until the 2014/15 time frame, when the Operational CCS is expected to have its next resource increase, the total number of ensemble members will remain 20 and the model resolution of each member will be similar to the then Operational GEFS.

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Basic Strategy

All members of an Operational Multi-model Ensemble must be run on the NOAA Operational computer system Ensures all members will be available to produce ensemble

products NAEFS does produce Ensemble Products from members

provided by CMC & FNMOC, but all of those are supported operationally by their Center

Test or experimental products can be produced from Site-B runs or from members provided from other systems, but those should never be disseminated via Operational channels.

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Basic Strategy

Specific model configurations from the ensemble membership will then be tested for use as the Operational deterministic model, which will support Weather, Climate, and Data Assimilation This is the opposite of current NCEP Operations,

where the ensemble system is usually the n-1 deterministic model at lower resolution

With a multi-model ensemble, however, the n-l paradigm isn’t possible

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Next Steps

Infrastructure Code developers at each of the NOAA development sites

need easy access (on-site) to program analyst support for each of the NOAA R&D system architectures

A centralized group needs to be established to maintain common libraries and utilities at all NOAA R&D sites

A centralized group needs to be established to maintain data flow between the NOAA operational and R&D sites

The lack of development resources at NCEP will require both retrospective and near real-time runs at the NOAA R&D sites

Subversion repository will be established to hold all candidate codes

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Next Steps

Begin comparison of NNMB & FIM with current Operational GFS Routine FIM runs from ESRL are being verified with the standard

NCEP verification package 10 days only Initial results look very promising

NMMB with GFS physics in NEMS are running routinely for 00Z 6 days only Need to begin verifications

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Questions

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Statistical Down-Scaling Techniques for Alaska ♦ Variable: surface pressure, 2-m temperature, 10-meter wind component

work well using current operational technique for CONUS ♦ Variable: Tmax and Tmin

Using latest define Tmax and Tmin defined period for Alaska♦ Variable: wind speed and direction

Using equal weight for wind direction distribution Possible future improvement for wind direction

Alaska Verification♦ Stats for Tmax, Tmin, wind direction/speed♦ First a few key points:

Statistical down-scaling data adds value Bias correction alone is of value Bias correction with downscaling adds significant value to the forecasts NAEFS is better than lone GEFS

More members are better Present (latest) to HPC (Alaska desk)

Dec. 7th 2009

NAEFS: Downscaling for Alaska

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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 6km 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

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NAEFS: Current Configuration

NCEP CMCModel GFS GEM

Initial uncertainty ETR EnKF

Model uncertainty Stochastic

Yes (STTP) Yes (multi-physics)

Tropical storm Relocation None

Daily frequency 00,06,12 and 18UTC 00 and 12UTC

Resolution T190L28 ~70km 1.0 degree

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 February 23rd 2010 July 10th 2007

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NCEP CMC FNMOCModel GFS GEM Global Spectrum

Initial uncertainty ETR EnKF Banded ET

Model uncertainty Stochastic

Yes (STTP) Yes (multi-physics) None

Tropical storm Relocation None None

Daily frequency 00,06,12 and 18UTC 00 and 12UTC 00 and 12UTC

Resolution T190L28 ~70km 1.0 degree T119L30 ~1.0degree

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 23rd 2010 July 10th 2007 May 2010

NAEFS: NUOPC IOC

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CFS2.0.0

Forecast component frozen (T126L64) Assimilation component can evolve with GFS and

GSI Current CFS Data Assimilation is fully coupled

version of T574 GFS/GSI Will not change when the Hybrid data

assimilation is implemented

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WAFS

Harmonization of UKMET and US WAFS products UKMET & US utilize different forecast models and different

algorithms to produce WAFS products (Turbulence, Cb, Icing)

Produces inconsistencies between the products from both Centers

UKMET & US have agreed to move toward consistent algorithms to reduce differences

Both Centers are testing blended products Mean products are averages of Center’s products Maximum products are values from either Center

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GSI/GFS Bundle

Analysis Changes Improved OMI QC Removal of redundant SBUV/2 total ozone Retune SBUV/2 ozone ob errors Relax AMSU-A Channel 5 QC New version of CRTM 2.0.2 Inclusion of Field of View Size/Shape/Power for Radiative transfer Remove down weighting of collocated radiances Limit moisture >= 1.e-10 in each outer iteration and at end of analysis Inclusion of uniform (higher resolution) thinning for satellite radiances Improve location of Buoys in vertical (move from 20 to 10m) Improved GSI code with optimization and additional options Recomputed background errors Inclusion of SBUV from NOAA-19 Ambiguous vector quality control for ASCAT (type 290) data

Model Changes New Thermal Roughness Length Set minimum moisture Value in Stratosphere to Reduce background diffusion in the Stratosphere

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Wind Speed Bias

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Wind Speed Bias

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Temperature Bias

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500 MB Anomaly Correlation

Northern Hemisphere Southern Hemisphere

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Precipitation

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NAEFS: GEFS Upgrade

Major Improvements Resolution Increase

T190L28 T254L42 (0 - 192 hrs) T190L28 T190L42 (192 - 384 hrs)

Improved initial perturbations Improved stochastic total tendency perturbations

Product Delivery Delays Raw GFS GRIB data will be delayed ~20 minutes

Delays will gradually increase with forecast length Bias corrected GRIB will be delayed ~ 20 minutes Probabilistic Products will be ON TIME

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+5:00 +6:00 +7:00 +8:00 +9:00

FCST+4:35 --- +5:15

ENS_DEBIAS+4:40 --- +5:24

PROB_PRODUCTS+5:24 --- +6:45

FCST+4:35 --- +5:35

CMC_ENS_DEBIAS+7:22 --- +7:26

FNMOC_ENS_DEBIAS+7:20 --- +7:30

NAEFS_PROB_PROD (1)+7:33 -- +8:08

NAEFS products (2)+8:08 --- +9:08

GEFS/NAEFS 6-hr window flow chart

CMC_ENS_PREPCMC_ENS_POST+7:20 --- +7:22

+7:35

NAEFS products start

NCEP_POST+4:37 --- +5:17

Current Future

NCEP_POST (PGB)+4:37 --- +5:37

ENS_DEBIAS+5:00 --- +5:44

PROB_PRODUCTS+5:44 --- +6:40

20m late finish

20m late start

5m early finish

Delays grow to 20 minutes at 16 days

NO IMPACT ON NAEFS

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GSI Hybrid EnKF-3DVAR Upgrade

Possible components (NSST and Combination with CDAS removed) GPS RO bending angle rather than refractivity Inclusion of compressibility factors for atmosphere Retune SBUV ob errors – fix bug at top Update radiance usage flags Prepare for monitoring NPP and Metop-B Add GOES-13 data Add Severi CSBT radiance product Satellite monitoring stats code included in Ops. New Sat wind data and QC EnKF hybrid system – modify inflation factors Update to current version of trunk New version of Forecast model

Restructured to include options for Semi-Lagrangian & NSST Model, and corrected a bug in lake elevation.

Updated postprocessor CAPE, CIN, & Lifted Index calculated from virtual temperature Ability to output GRIB2 directly 10 new variables for Fire Wx & 6 for Wind Energy Back

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120-hr dust-only forecast once per day (00Z) ICs: Aerosols from previous day forecast and meteorology from

operational GDAS 3-hourly products: 3d distribution of dust aerosols (5 bins from 0.1 –

10 µm) Automatic output archive, post-processing and web update since

June 11, 2011 Same physics and dynamics as operational GFS with the following

exceptions: Lower resolution (T126 L64) Use Relaxed Arakawa-Schubert scheme [Moorthi and Suarez, 1999] with

convective transport and tracer scavenging Aerosol-radiation feedback turned off

Experimental (non-operational)Experimental (non-operational)

NRT NGAC configuration

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Sample Forecast

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GFS 1QFY13 Upgrade

T1178L64 Semi-Lagrangian Resource Nuetral

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FIM purpose and configurations

Purpose: A next-generation global model for NOAA (candidate for NCEP ops, coupled model research)

Resolution Real-time testing at 60km, 30km, 15km resolution -

icosahedral horizontal grid 64 vertical levels – hybrid θ-σ Ptop = 0.5 hPa, -top = 2200K

Physics Currently GFS physics suite (2010 version)

Initial conditions •GFS/GSI spectral data to FIM icos hybrid θ-σ vertical coordinate•Ensemble Kalman using GFS T254 – Jeff Whitaker, ESRLApplication at NCEPLikely application in GEFS, candidate for future global model

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Resolution Init conds

Physics Stream 1.5

FIM 30km GSI GFS (July 2010) No

FIMY- Stream 1.5

30km EnKF GFS Yes

FIM9 15km EnKF GFS No

FIMX 60km GSI/cyc chem

GFS + WRF-chem, testing of Grell cu

No

FIM7 60km GSI GFS No

FIMens 60km, 10mem

EnKF GFS No

FIMens 27km, 4mem EnKF GFS No

Versions of FIM running – Fall 2011

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FIM Development at NCEP

Strong progress toward NCEP operational statusPreliminary tests of FIM done on NCEP CCSMOA with NCEP to run FIM as part of Global Ensemble Forecast System (GEFS) under NEMS.GSD’s Advanced Computing Group worked closely with NEMS developers at NCEP to work out basic NEMS design issues as well as to get FIM under NEMSTesting of FIM to start within NEMS GEFS framework at NCEP in next few monthsNCEP doing their own verification now of FIM38-level version of FIM tested – equal performance with L64 – readiness for GEFS. (Fewer levels should fare well with isentropic-hybrid coordinate …. and apparently do)

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HFIP Global Model/Physics Team plans for FY12

FIM - Testing in GEFS under NEMS Model enhancements toward efficiency      

Testing of WRF physics (Grell cumulus), other physics Critical for improving tropical cyclone diversity

Physics – diversity between GFS and FIM should improve multi-model TC ensemble Grell 3-d convective scheme – now in testing FIM-chem with more complex microphysics (2-moment cloud at least) for

coupling with aerosol (Saharan dust, sea salt, etc.) – Georg Grell Stochastic physics, other devices to increase ensemble diversity – Jian-Wen

Bao, Georg

Continued development of CFIM (coupled atmosphere-ocean FIM with icos HYCOM)

Use of long runs for evaluation of FIM TC climate and diagnosis of physics problems

Continue work toward FIM-based EnKF-hybrid (Phil Pegion, Jeff W)

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7-day 500 hPa anomaly correlation1 Aug – 31 Dec 2010, 135 cases

N. Hemis 20-80N

S. Hemis 20-80S

Arctic 70-90N

Antarctic 70-90S

New version of FIM – Nov 2011

73.46 65.66 66.66 46.97

GFSDC 72.90 65.20 65.49 44.46

Verification against GFS analyses, GFS used for initial conditions

NOTE: FIM physics matches that used for GFS in fall 2010, not using the May11GFS physics modifications

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NMM-B Dynamical Core Nonhydrostatic Multiscale Model on B grid (NMM-B) (Janjic,

2005; Janjic and Black, 2007) Further evolution of WRF NMM (Nonhydrostatic Mesoscale Model) Intended for wide range of spatial and temporal scales, from meso

to global, and from weather to climate Evolutionary approach, built on NWP and regional climate study

experience by relaxing hydrostatic approximation (instead of extending cloud models to large scales; Janjic et al., 2001, MWR; Janjic, 2003, MAP)

Applicability of the model extended to nonhydrostatic motions Favorable features of the hydrostatic formulation preserved

The nonhydrostatic option as an add–on nonhydrostatic module Reduced cost at lower resolutions Easy comparison of hydrostatic and nonhydrostatic solutions

Pressure based vertical coordinate Nondivergent flow on coordinate surfaces (often forgotten) No problems with weak static stability on meso scales

Zavisa Janjic

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Global North Hemisphere

South Hemisphere Tropics

Global NMMB

~1 year 500 hPa Height Anomaly Correlation Coefficient vs forecast time

NMMB initialized and verified using GFS analyses

Zavisa Janjic Back