Table 1. Analysis/Assimilation Differences Possibly Leading to Reduced NAM Performance Relative to GFS
|
Priority |
Difference |
Global |
Regional |
Discussion |
|
Prediction Model |
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|
2008/ 2009/ 2010 |
Prediction model physics/dynamics |
GFS Spectral |
NMM Grid-point |
See Table 2 |
|
Domain Characteristics |
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|
2008 |
Horizontal Domain & Resolution |
Global 38 km |
Continental 12 km |
Large scales may not be properly corrected |
|
2009/ 2010 |
Top layer P Vertical Structure And Discretization Strategy |
0.267 mb 64 layers Hybrid (sigma-p) Slowly varying depth (z) |
14.5 mb 60 layers Different Hybrid Slowly varying mass (p) |
While not much mass, there are a lot more layers in GFS’ stratosphere than in NAM’s |
|
Assimilation Cycle Characteristics |
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|
2017 |
Lateral boundary conditions |
None |
6-hour old GFS |
Can fix this with concurrent running of GFS & NAM (can only do this in NEMS + NPOES era ~2017 ) |
|
2008/ 2009 |
Cycles per day / Analysis Updates per cycle / Number - range of forecasts per cycle |
4 / 1 / 1 - 9 hr (extra 3hr of fcst is for FGAT) GDAS does one analysis and one forecast covering 6 hour period |
4 / 4 / 4 - 3 hr NDAS does four analyses and four forecasts covering a 12 hour period |
NDAS is planned to go to hourly analysis updates to better capture all the available high frequency obs & will probably need DFI |
|
2008 |
Digital Filter Initialization (DFI) |
Yes |
No |
GFS’ DFI is centered on 3 hr w/ filter width of 6 hr, model is integrated 0-6 hr w/ full physics, then restarted from 3 hr with filtered result. |
|
2007 |
Precipitation forcing for land-surface energy balance etc. |
GFS model precipitation |
Stage II/IV precip analysis over CONUS, precip |
Considered a strength of NDAS over GDAS |
|
GSI Analysis Characteristics |
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|
2007/ 2008 |
Strong Balance Constraint |
Yes |
No |
A scheme was tried in regional but it assumed f-plane, did not perform well on large NAM domain; trying new approach |
|
2008 |
Satellite channel bias correction |
Global GFS
|
Regional NMM
|
Can’t impose global sum be zero and can’t use GFS Bias corrections because they depend on model and its vertical structure and discretization |
|
2008/ 2009 |
First Guess at Appropriate Time (FGAT) / First Order Time-extrapolation to Observation (FOTO) |
Yes / Not yet |
Not yet / Not yet |
Regional update is only 3 hrs so FGAT less necessary, plus FGAT requires more forecast time between analysis updates |
|
2007 |
Iterations used in variational solution: 1st Outer Loop / 2nd Outer Loop |
100 / 150 |
50 / 50 |
Regional domain requires fewer iterations to reach same amount of convergence as global |
|
Observational Differences |
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|
2017 |
Data cut-off time |
2 hr 45 min |
1 hr 15 min |
More obs available to GFS due to later data cut off |
|
2009 |
Observation time window |
6 hours |
3 hours with plans for hourly to better capture all high frequency obs |
Matches the analysis update frequency in GDAS & NDAS and ensures no obs are used more than once |
|
2008 |
Use of surface land obs of temperature, wind and moisture |
No |
Yes |
Heavily dependent on forward model, vertical background error covariance and its vertical sharpness |
|
2008 |
Use of 88D radial velocity |
No |
Yes |
Heavily dependent on forward model, vertical background error covariance and its vertical sharpness |
|
|
Use GPS-IPW |
No |
Yes |
Tests in GDAS had negative impact but positive in NDAS |
|
2009 |
Use GPS radio occultation refractivity |
Yes |
No |
|
|
2009 |
Use of satellite ozone obs |
Yes |
No |
Ozone is a predicted variable in the GFS but not in the NAM |
|
2008 |
Use METOP-2 HIRS-4, AMSU-A, MHS radiances |
Yes |
No |
|
|
2007 |
Use of AQUA/AIRS IR and AMSU-A every field-of-view radiances |
Yes |
Yes |
|
|
2009/ 2010 |
Use of TRMM/TMI and SSM/I rainfall data |
Yes |
No |
Forward model used is based on GFS convective physics |
|
2007 |
Use GOES-11 and -12 1x1 single field-of-view sounder radiances |
Yes over water |
Yes over water |
|
|
2007 |
Use Aqua/Terra MODIS IR and WV winds |
Yes |
Yes |
|
|
2007 |
Use QuikSCAT scatterometer winds |
Yes |
No |
|
|
2008 |
Use of SSM/I wind speed |
Yes calculated from Neural Net 3 algorithm |
Yes calculated from Goodberlet algorithm (Navy) |
|
|
2009 |
Tropical storm relocation |
Yes |
No |
|
|
2009 |
Use of tropical cyclone bogus winds |
No (unless weak or new storm and can’t relocate) |
Yes always |
|
Table 2. Prediction Model Differences Possibly Leading to Reduced NAM Performance Relative to GFS
|
Difference |
Global |
Regional |
Discussion |
|
dynamics |
Spectral T382 ~38 km gaussian grid |
Grid-point 12 km Arakawa E-grid |
Can’t run GFS regionally or with nesting, but there is a global version of NMM on a B-grid in new ESMF-based NEMS |
|
Lateral diffusion |
Computed on pressure levels & transformed back to hybrid |
Computed on hybrid surfaces |
A re-formulated lateral diffusion has been coded for NMM |
|
Gravity wave drag (also includes mountain blocking) |
Yes
|
Yes |
|
|
Vertical diffusion |
Yes |
MYJ level 2.5 closure in free atmosphere |
|
|
Land-surface |
Noah LSM 13 veg / 9 soil categories |
Noah LSM 27 veg / 16 soil categories |
terrain height, land-sea mask, roughness length and glacial ice differences exist as well |
|
SST |
1 degree Reynolds |
0.5 degree RTG_SST |
Both are updated once daily |
|
Surface layer |
GFS |
NMM |
Effectively the “marriage” between land or ocean & PBL: GFS and NAM use different surface layer schemes |
|
Boundary layer scheme |
MRF Non-local |
MYJ Level 2.5 |
|
|
Shallow Convection |
Tiedke |
BMJ |
GFS’ Tiedke is available in WRF but only through SAS |
|
Deep Convection |
SAS |
BMJ |
|
|
Gridscale clouds, precip microphysics |
Zhao |
Ferrier |
GFS version of Zhao is not available in WRF |
|
Shortwave Radiation |
NASA (simplified, faster Chou) |
GFDL (Lacis & Hanson w/ Ferrier tweaks) |
GFS radiation is not available in WRF |
|
Longwave Radiation |
RRTM (adapted to GFS from AER version) |
GFDL (Fels & Schwartzkopf) |
GFS radiation is not available in WRF |