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Global Climate and Weather Modeling NCEP Production Suite Review. John H. Ward Chief, Global Climate & Weather Modeling Branch December 7, 2011. Outline. Personnel FY11 Upgrades FY12 and Beyond Global Model Roadmap. Personnel. Global Modeling Modeling Team Lead S. Moorthi Glenn White - PowerPoint PPT Presentation
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John H. WardChief, Global Climate & Weather Modeling Branch
December 7, 2011
Global Climate and Weather Modeling
NCEP Production Suite Review
2
Outline
Personnel FY11 Upgrades FY12 and Beyond Global Model Roadmap
3
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
5
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
6
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
7
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
8
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
12
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
13
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.
14
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.
15
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
16
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
17
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
18
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
20
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
21Back
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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
23
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
Back
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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
Back
25
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
Back
26
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
Back
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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
Back
34
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
35
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
36
Sample Forecast
Back
37
GFS 1QFY13 Upgrade
T1178L64 Semi-Lagrangian Resource Nuetral
Back
38
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
40
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)
41
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)
42
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
Back
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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