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Zavisa Janjic 1
Nonhydrostatic Multiscale Model on the B grid (NMMB): Global Runs
Zavisa JanjicTom Black
Ratko VasicDusan Jovic
+MMB
…
Zavisa Janjic 2
Nonhydrostatic Multiscale Modelon the B grid (NMMB)
Intended for wide range of spatial and temporal scales (from meso to global, and from weather to climate)Further evolution of WRF Nonhydrostatic Mesoscale Model (NMM)Built on NWP and regional climate experience (Janjic et al., 2001, MWR; Janjic, 2003, MAP; Janjic & Gall, 2012, NCAR)Pressure based vertical coordinate, nondivergent flow remains on coordinate surfaces
Zavisa Janjic 3
Nonhydrostatic Dynamics
Inviscid adiabatic equationsNo over-specification of w!
TS Difference between hydrostatic pressures at surface and top
Hydrostatic pressure
p Nonhydrostatic pressure
pRT Gas law
Hypsometric (not “hydrostatic”) Eq.
0
ss
ssst ss
v Hydrostatic continuity Eq.
Continued …
Zavisa Janjic 4
1p
Third Eq. of motion
ws
swtw
gdtdwg s
sv
11
p
ssp
tp
cT
ssT
tT
sp
s vv
ss
tgdtdz
w ss
v1 Vertical velocity definition,
nonhydrostatic continuity Eq.
vkv fpdtd
ss )1( Momentum Eq.
Thermodynamic Eq.
Zavisa Janjic 5
Conservation of important properties of the continuous system aka “mimetic” approach in Comp. Math. (Arakawa 1966, 1972, …; Jacobson 2001; Janjic 1977, …; Sadourny, 1968, … ; Tripoli, 1992 …)
Nonlinear energy cascade controlled through energy and enstrophy conservation (finite-volume)A number of properties of differential operators preservedQuadratic conservative finite differencingA number of first order (including momentum) and quadratic quantities conservedOmega-alpha term, transformations between KE and PEErrors associated with representation of orography minimizedMass conserving positive definite monotone Eulerian tracer advection
Discretization Principles
Zavisa Janjic 6
Coordinates and GridsGlobal lat-lonRegional rotated lat-lon, more uniform grid sizeArakawa B grid
h h h v vh h h
Pressure-sigma hybrid (Simmons & Burridge 1981, Eckermann 2008)Flow remains on hydrostatic pressure coordinate surfaces in case of nondivergent flowLorenz vertical grid
Zavisa Janjic 7
No splitting (for computational efficiency)Additive splitting inadequate for large RoSplitting with multi-step iterative schemes too expensive
“Stabilized” Adams-Bashforth for horizontal advection of u, v, T and Coriolis forceCrank-Nicholson for vertical advection of u, v, T (implicit) because of CFL problems with thin layersForward-Backward (Ames, 1968; Gadd, 1978; Janjic and Wiin-Nielsen, 1977, JAS) fast wavesImplicit for vertically propagating sound waves (Janjic et al., 2001, MWR; Janjic, 2003, MAP)
Time Stepping
Zavisa Janjic 8
Lateral and Polar Boundaries, Polar Filter
Regional domain lateral boundariesNarrow zone with upstream advection, no computational outflow BC for advectionBlending zone
Conservative global polar boundary conditionsPolar filter
“Decelerator,” tendencies of T, u, v, Eulerian tracers, divergence, dw/dtPhysics not filtered
Zavisa Janjic 9
Physics
Upgraded NCEP WRF NMM “Unified” physicsRRTM, GFDL radiationNOAH, LISS land surface modelMellor-Yamada-Janjic turbulence
Elevated subgrid surface dragCloud topped marine BL
GFS Gravity Wave DragFerrier, Zhao microphysicsBetts-Miller-Janjic convection
High resolution enabled
Full NEMS GFS physics
Zavisa Janjic 10
27 km Global NMMB27 km Global NMMB
12 km NAM NMMB
12 km NAM NMMB
4 km NAM-nest NMMB
9 km Igor NMMB
9 km Julia NMMB
Hypothetical NMMB Simultaneous Run Global [with Igor & Julia] and NAM [with CONUS nest]
Courtesy of DiMego et al.
Zavisa Janjic 11
2D very high resolution tests
0 0
0
0
0
0
0
0
0
Warm bubble, 100 m resolution
10
0
0
Cold bubble, 100 m resolution
-2.5
-2.5-2.5
-2.5
00000
00
0 0000
00
00 000
0
0 0 0 0
00
00
000
000 0 0 00000 000
00
000
0
0000
00
00
000 000
00
00
00
0
000
00
00
00
00
00
00
000 0
00
0
0
0
0
000 00
0
00
0
00
0
00
00
00000000
0
0
0
0
00
0
0
0
0
00
00
00
00000
00
000
0
00
0000 000
00
2.52.5
2.5
2.5
2.5
2.5
2.5
Full compressible NMM Analytical (Boussinesque) ARPS (Boussinesque)
Nonlinear mountain wave 400 m resolution
0.00
1.00
1000
.00
1295
.77
1591
.55
1887
.32
2183
.10
2478
.87
2774
.65
3070
.42
3366
.20
3661
.97
3957
.75
4253
.52
4549
.30
4845
.07
5140
.85
5436
.62
5732
.39
6028
.17
6323
.94
9000
17000
Normalized vertical momentum flux, 400 m resolution
Zavisa Janjic 12
Mountain waves, 8 km resolution
Convection, 1 km resolution
Zavisa Janjic 13
Atmospheric Spectrum
Numerical models generally generate excessive small scale noise
False nonlinear energy cascade (Phillips, 1954; Arakawa, 1966 … ; Sadourny 1975; …)Other computational errors
Historically, problem controlled by:Removing spurious small scale energy by numerical filtering, dissipationPreventing excessive noise generation by enstrophy and energy conservation (Arakawa, 1966 …)
Zavisa Janjic 14
Atmospheric Spectrum
Classical paper by Sadourny, 1975, JAS:
One does not even need an atmospheric model for that!
Zavisa Janjic 15
Atmospheric Spectrum
Instead (Sadourny, 1975, JAS):
Philosophy built into the design of the compact nonlinear advection schemes for semi-staggered grids (Janjic, 1984, MWR)
Zavisa Janjic 16
Formal accuracy alone does not solve the problemDifferent nonlinear noise levels (green scheme) with identical formal accuracy and truncation error (Janjic et al. 2011, MWR) Green scheme, still energy & (alternative) enstrophy conserving
Second order schemes
Fourth order schemes
116 days
Zavisa Janjic 17
Atmospheric SpectrumNastrom-Gage (1985, JAS) 1D spectra in upper troposphere and lower stratosphere from commercial aircraft dataNo spectral gapTransition at few hundred kilometers from –3 to –5/3 slope in the 102-103 km (mesoscale) rangeInertial range, 0.01-0.3 m s-1 in the –5/3 range, not to be confused with severe mesoscale phenomena!
104
108
103
105
102
102 101103
-3
-5/3
Zavisa Janjic 18
Atmospheric Spectrum
What would the real atmosphere do in a short range run in a limited area domain starting from analysis with truncated spectrum?
Short time for statistical equilibriumLarge scales cut-off by domain size
NMMB well qualified for investigating numerical spectra by design
Zavisa Janjic 19
Atmospheric Spectrum
Are model simulated spectra forced by sigma coordinate errors?
Are model simulated spectra just projections of topography spectrum?
Topography squared
4
5
6
7
8
9
10
11
12
-6.0 -5.5 -5.0 -4.5 -4.0 -3.5
log10(wavenumber)
log
10
(to
po
gra
ph
y s
qu
are
d d
en
sit
y)
mnts k -̂3 k -̂5/3
-3
-5/3
630 km 63 km
Spectrum of topography squared over North America
Zavisa Janjic 20
No Physics With Physics
-5/3 -5/3
-3 -3
● Spectrum in agreement with observed spun-up given physical (or spurious, e.g. sigma) sources on small scales.
● Small scale energy in short regional runs with controlled nonlinear cascade and suppressed noise sources, where from?
Flat bottom (Atlantic), NMMB, 15km, 32 levels, 48h run (Loops)
Zavisa Janjic 21
No Physics With Physics
Where is the small scale energy in the observed spectrum coming from?
Atlantic case, NMM-B, 15 km, 32 Levels, 36-48 hour average
0
1
2
3
4
5
6
7
8
-6.0 -5.5 -5.0 -4.5 -4.0 -3.5 -3.0
oceanphy3648
k^-3
k^-5/3
0
1
2
3
4
5
6
7
8
-6.0 -5.5 -5.0 -4.5 -4.0 -3.5 -3.0
oceannop3648
k^-3
k^-5/3
-5/3 -5/3
-3 -3
No Physics With Physics
Zavisa Janjic 2222
Loop,decaying 3D turbulence, Fort Sill storm, 05/20/77.
NMM-B, Ferrier microphysics, 1km resolution, 32 levels,112km by 112km by 16.4km, double periodic, Smagorinsky constant 0.32.
Note the hump with active convection
Spectrum of w2 at 700 hPa.
Zavisa Janjic 23
-5/3
Hours 3-4 average decaying 3D turbulence, Fort Sill storm, 05/20/77.
NMM-B, Ferrier microphysics, 1km resolution, 32 levels,112km by 112km by 16.4km, double periodic. Smagorinsky constant 0.32.
Spectrum of w2 at 700 hPa.
Zavisa Janjic 24
Parallel runs for testing and tuningInitialized from spectral GFS analyses
Compatibility issues between grid-point and spectral data (Gibbs phenomenon)
Verified against GFS analyses and climatology500 hPa Height Anomaly Correlation CoefficientsAlthough starting from “same” initial conditions, skill of NMMB and GFS forecasts often disparate
Major GFS update on July 28, 2010One year of parallel global forecasts before and after July 28, 2010
Global Scales
Zavisa Janjic 25
Global Resolution
“Resolution comparable to that of the GFS”
Txxx is the GFS triangular truncationΔλ≈360˚/(2 Txxx)Δφ≈Δλ cos(45˚)
Δx≈Δy at 45˚
Zavisa Janjic 26
Courtesy Dusan Jovic
Zavisa Janjic 27
Global NMMB 769 x 541 x 64 pts. vs. GFS T384 x 64
1 year 500 hPa Height Anomaly Correlation Coefficient vs. forecast time
NMMB initialized and verified using GFS analyses and climatology
NMMB comparable or lower resolution
Zavisa Janjic 28
Global NMMB 769 x 541 x 64 pts. vs. GFS T384 x 64
1 year 500 hPa Height Anomaly Correlation Coefficient vs. forecast time
NMMB initialized and verified using GFS analyses and climatology
NMMB comparable or lower resolution
Zavisa Janjic 29
Average of 32 GFS T574 dropout cases from 2011 (Alpert) ran with NMMB with 769x541x64 points from GFS and ECMWF analyses
Above dropout threshold!
From July 28 2010 GFS has 3.8 times more points & updated physics
500 hPa ACC Verification using GFS analyses and ERA Interim climatology
Courtesy of Dr. Vladimir Djurdjevic
Zavisa Janjic 30
NMMB with GFS analysis closer to GFS (14)NMMB with GFS analysis closer to NMMB with ECMWF analysis (14)Ties (2)Anomalous (2)
Courtesy of Dr. Vladimir Djurdjevic
Zavisa Janjic 31
Courtesy of Yuejian Zhu
Zavisa Janjic 32
Courtesy of Yuejian Zhu
Zavisa Janjic 33
Aerosol Climatology
Zavisa Janjic 34
Global NMMB 769 x 541 x 64 pts. vs. GFS T574 x 64
1 year 500 hPa Height Anomaly Correlation Coefficient vs. forecast time
NMMB initialized and verified using GFS analyses and climatology
From July 28 2010 GFS has 3.8 times more points & updated
Zavisa Janjic 35
Global NMMB 769 x 541 x 64 pts. vs. GFS T574 x 64
1 year 500 hPa Height Anomaly Correlation Coefficient vs. forecast time
NMMB initialized and verified using GFS analyses and climatology
GFS has 3.8 times more points
Global NMMB 769 x 541 x 64 pts. vs. GFS T574 x 64
1 year 500 hPa Height Anomaly Correlation Coefficient vs. forecast time
NMMB initialized and verified using GFS analyses and climatology
From July 28 2010 GFS has 3.8 times more points & updated physics
Zavisa Janjic 36
New testing strategyInsufficient computational resources for sustainable parallel NMMB tests with enhanced resolutionLong testing periods required in order to obtain robust representative average scores (a change bringing a noticeable improvement in one season may be detrimental in the other)
Increased Resolution
Zavisa Janjic 37
A sample of 105 cases over one year at three and a half day intervals created (~ 1/7 of the population)Both 00Z and 12Z initial data equally represented Since the cases are chosen randomly, it is expected that test results over this set of cases would be reasonably close to test results over a yearA number of initial data conversion algorithms, resolution settings and physical parameterization sensitivity studies carried out
Increased Resolution
Zavisa Janjic 38
PlanIncrease resolution to become comparable to that of GFSRetune the physics
1. Start from radiation (special kind of parameterization)2. Convection3. …
Increased Resolution
Zavisa Janjic 39
NMMB - RSWINNMMB - RLWIN
ECMWF - RSWINECMWF - RLWIN
NMMB - (RSWIN-RSWOUT)ECMWF - (RSWIN-RSWOUT)
NMMB - RLWTOAECMWF - RLWTOA
Zonal averages of radiation fluxes
forecast start: 2011122048h forecastNMMB vs ECMWF
Difference in RLWIN on north hemisphere50N-90N of about 50W/m^2
Courtesy of Dr. Vladimir Djurdjevic
Zavisa Janjic 40
GFS
NMMB
ECMWF
Mean downward long-wave radiation flux 6-12h forecast hour.
RRTM w. hydrometeor clouds
By far largest fluxes in NMMB!
Courtesy of Dr. Vladimir Djurdjevic
Zavisa Janjic 41
GFS
NMMB NMMB
NMMB
RH clouds, no ice Hydrometeor clouds, no ice
Courtesy of Dr. Vladimir Djurdjevic
Zavisa Janjic 42
ECMWF; Vertical section
Downward LW flux
NMMB; Vertical section
NMMB (F_ICEC=0); Vertical section
Downward LW flux
Downward LW flux
Problem with radiation-ice interaction, fallback to no ice Zhao microphysics
Zavisa Janjic 43
Global NMMB 1149 x 811 x 64 pts. vs. GFS T574 x 64
105 randomly chosen cases from 1 year
500 hPa Height Anomaly Correlation Coefficient vs. forecast time
NMMB initialized and verified using GFS analyses and climatology
New Linux cluster test
Global NMMB 1149 x 811 x 64 pts. vs. GFS T574 x 64
105 randomly chosen 00Z and 12Z cases over 1 year
500 hPa Height Anomaly Correlation Coefficient vs. forecast time
NMMB initialized and verified using GFS analyses and climatology
Zavisa Janjic 44
New Linux cluster test
Global NMMB 1149 x 811 x 64 pts. vs. GFS T574 x 64
105 randomly chosen 00Z and 12Z cases over 1 year
500 hPa Height Anomaly Correlation Coefficient difference vs. forecast time
NMMB initialized and verified using GFS analyses and climatology
Zavisa Janjic 45
New Linux cluster test
Global NMMB 1149 x 811 x 64 pts. vs. GFS T574 x 64
105 randomly chosen 00Z and 12Z cases over 1 year
500 hPa RMSE difference vs. forecast time
NMMB initialized and verified using GFS analyses and climatology
Zavisa Janjic 46
Tropics
What is the truth?Insufficient data, more weight on model in DASWeak connection between mass and windDirect circulationsGravity wavesExtrapolation undergroundDifferent gravity-inertia wave frequency errors and computational dispersion in different models (semi-implicit vs. explicit)Different geostrophic adjustmentEach model should have its own DAS for fair comparison
Zavisa Janjic 47
Janjic, Z., A. Wiin-Nielsen, 1977: On Geostrophic Adjustment and Numerical Procedures in a Rotating Fluid. J. Atmos. Sci., 34, 297–310. doi: http://dx.doi.org/10.1175/1520-0469(1977)034<0297:OGAANP>2.0.CO;2
Zavisa Janjic 48
Semi impliciit, 5 leapfrpg time steps
Correct
Zavisa Janjic 49
Global, nonhydrostatic, full physicsResolution 1149 x 811 x 64, ~ 22 km
500 processors, 7.9 wall clock min/day1000 processors, 4.7 wall clock min/day2000 processors, 3.3 wall clock min/day4000 processors, 2.8 wall clock min/day, (1 year of simulation in < 17 hours, climate studies?)
Scaling on Zeus
Zavisa Janjic 50
Global, nonhydrostatic, full physicsResolution 2305 x 1623 x 64, ~ 11 km (8 x more work than 1149 x 811 x 64, ~ 22 km)
3600 processors, 7.6 wall clock min/dayPerfect scaling!
Technology for ~ 10 km global resolution forecasts already exists!
Scaling on Zeus
Zavisa Janjic 51
Summary and Conclusions
New testing paradigm for high resolution global runsGlobal NMMB shows good results in medium range forecasting ~10 km resolution global forecasts?
Technology existsResolutions less than <10 km km possible soon