recent development of the coupled ocean/atmosphere mesoscale prediction system (coamps tm )
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Recent Development of the Coupled Ocean/Atmosphere Mesoscale Prediction
System (COAMPSTM)
J. Doyle, S. Chen, R. Hodur, T. Holt, M. Liu, K. Sashegyi, J. Schmidt, S. Wang, D. Westphal, J. Cummings, X. Hong,
and J. Pullen
Naval Research Laboratory
• Introduction• Recent Development
• Atmospheric model• Ocean model
• Future Plans
NOGAPS: (Fleet Numerical)•Global coverage•1–10d forecaster guidance
NOGAPS: (Fleet Numerical)•Global coverage•1–10d forecaster guidance
Observations
BC, IC
COAMPS: (Fleet Numerical)•High resolution, nested
regional coverage•0-72h forecaster guidance
COAMPS: (Fleet Numerical)•High resolution, nested
regional coverage•0-72h forecaster guidance
DAMPS: (Regional Centers)•On-scene tactical-scale weather•0-48h forecaster guidance
DAMPS: (Regional Centers)•On-scene tactical-scale weather•0-48h forecaster guidance
COAMPS-OS: (Shipboard-NITES)•Battlegroup data assimilation
system•6-12h data assimilation cycle
COAMPS-OS: (Shipboard-NITES)•Battlegroup data assimilation
system•6-12h data assimilation cycle Battlespace
Awareness Cube
Local Model Output
Nowcast: (Shipboard-NITES)•Real-time, automatic, 4D data
fusion•Warfighter time & space
requirements•Common situational awareness
Nowcast: (Shipboard-NITES)•Real-time, automatic, 4D data
fusion•Warfighter time & space
requirements•Common situational awareness
On-Scene Obs
TDAs
On-Scene Obs
Data FusionAI
Nowcast
Navy Mesoscale Modeling Strategy Telescoping Systems Strategy for Mission Success
Navy StrategyCOAMPS: Flexibility in System Design
Atmospheric DataAssimilation System
Ocean DataAssimilation System
COAMPSCoupled Ocean/Atmosphere Mesoscale Prediction System:
Atmospheric Components
•Complex Data Quality Control•Analysis:
• Multivariate Optimum Interpolation Analysis (MVOI) (Near Future: 3D Var)•Initialization:
• Hydrostatic Constraint on Analysis Increments; Digital Filter•Atmospheric Model:
• Numerics: Nonhydrostatic, Scheme C, Nested Grids, Sigma-z, Flexible Lateral BCs• Parameterizations: PBL, Convection, Explicit Moist Physics, Radiation, Sfc Layer
•Features:• Globally Relocatable (5 Map Projections)• User-Defined Grid Resolutions, Dimensions, and Number of Nested Grids• 6 or 12 Hour Incremental Data Assimilation Cycle • Can be Used for Idealized or Real-Time Applications• Single Configuration Managed System for All Applications• Operational at FNMOC:
• 9 Areas, Twice Daily, using 81/27/9 km or 81/27 km grids• Forecasts to 72 hours
• Operational at all Navy Regional Centers (w/ GUI Interface)
NRL Background in Community Modeling
•Began development of COAMPS in 1988
•Began distribution to limited research community in 1995:• Lawrence Livermore National Laboratory• University of Oklahoma• North Carolina State University• Jackson State University• Desert Research Institute• U. S. Army Research Laboratory
•Began operations in 1997:• FNMOC• Navy Regional Centers
•COAMPS Process Action Team (PAT) recommended general release of COAMPS in 2000:
• Release via Web; open to all• Support for release now funded
• Naval Postgraduate School• San Diego Supercomputer Center• Oregon State University• NOAA Forecast Systems Laboratory• Goddard Space Flight Center• Tulane University
COAMPS Recent Development
• Atmospheric Model
•NAVDAS•Moist physics•Aerosols•Moving nests•Land surface processes•Upper Boundary Condition
• Ocean Model
•Analysis•Forecast•WAM
RHHPQ
xHyQHPxxT
bc
bcT
bba
)(1
• cast in observation space
• correlation functions can be defined on isentropic surfaces (along dry air flow)
z z
xx
NAVDASNavy Atmospheric Variational Data Assimilation System
• non-separable error correlation functions providing scale-length variations with height and location
• error correlations have scale dependence
• vertical profiles are transformed into coefficients of background error correlation eigenvectors (10-25 fold speedup)
• operates on all grids for NOGAPS and COAMPSglobal regional
• uses Message Passing Interface for Massively Parallel Computers
• directly assimilates measured quantities SSM/I wind speed, TOVS radiances, SSM/I precipitable water
• Original RH83 scheme lacked secondary ice nucleation, CCN, drizzle, aggregates, and liquid to ice conversions (homogeneous freezing, graupel and/or hail production)
• Modified Adjustment to Saturation Scheme: Implicit solution for T,q (Soong and Ogura, 1974) Normalized microphysical rates • Modified ice nucleation (Meyers et al. 1992; Hallet and Mossop, 1974)• Allow nonzero fall speed for pristine ice• Implemented various autoconversion schemes• Implemented the RH84 graupel scheme and homogeneous freezing• Adapted the two-moment Khairoutdinov and Kogan (2000) drizzle parameterization (originally implemented by Dave Mechem, OU) • Modified the turbulence closure for mixed-phase clouds• Implemented a Hybrid time scheme (Clark 1979; Smolarkiewicz and Clark, 1986; Tripoli 1992; Wicker and Wilhelmson 1995)• Implemented a forward positive definite advection scheme (Bott, 1989)• Developing a full two-moment mixed-phase microphysics scheme (Reisner et al., 1998; Meyers et al., 1997; KK 2000 )• Coupling cloud microphysics with aerosol model(s)
Adjustments to COAMPS Bulk Microphysics
RFC Analysis Original RH83 Scheme
Modified Scheme Moist Physics ComparisonsWinter-time Precipitation (mm)
24 Hour COAMPS Grid 3Forecast Valid 01/25/02
kmx 9
00.05
0.10.15
0.20.25
0.30.35
0.4
0.25 2.5 5 10 15 25 35 50 75
Precipitation Threshold (mm/day)
E-T
H Bench
New Micro
0
0.2
0.4
0.6
0.8
1
1.2
0.25 2.5 5 10 15 25 35 50 75
Precipitation Threshold (mm/day)
Bia
s
COAMPS CONUS One-Week (20020125-20020201) Precipitation Scores
Addition of Aerosol Microphysics to COAMPS
• Objective: COAMPS with interactive clouds, radiation and aerosols
• Goal: COAMPS predictions of dust storms as weather events for strategic, tactical, surveillance, and operational uses
• Approach:
•Include source, dry deposition, and wet removal terms for dust (COAMPS already has accurate tracer transport code)
•Use remote sensing to improve specification of dust source areas•Validate model forecasts of occurrence and intensity of dust events in Southwest Asia region for spring 2002
Marine EnvironmentAerosol Concentration / cm3 Aerosol Concentration / cm3
Continental Environment
Rain water (g/kg)21600 sec
Rain water (g/kg)21600 sec
Simulated Orographic Rainfall Structure
Aerosol Void Aerosol Void
COAMPS Transport Simulation24-h forecast Valid 12 UTC 24 July 2001
Color: Mass Load (kg m-2)
SeaWiFS Satellite Image24 July 2001
Mt. Etna Ash Plume
Moving Nest OptionFixed Nest Option
(m/s)
Nest 2: 36 h forecast valid 12 UTC 18 September 2000
0 4 8 12 16 20
Sea levelpressure (hPa)
10-m windspeed (m/s)
COAMPS MPI Moving NestsHurricane Gordon 00Z September 17- 00Z September 19, 2000
LSM
Seasonal variation(satellite-derived NDVI)
Meteorological model inputT,q, ps, u,v, precip. LW, SW radiation
DATABASES• Vegetation type (USGS 1-km global)• Soil texture (1-km USDA STATSGO; 1o GED)
A = precipitationB = condensationC = on vegetationD = on bare soilE = transpirationF = canopy water evaporationG = direct soil evaporationH = evaporation from open waterI = deposition/sublimation to/from snow packJ = turbulent heat flux to/from snow pack/soil/plant canopyK = soil heat fluxL = interflowM = internal soil fluxN = gravitational flowO = internal moisture fluxP = soil moisture fluxQ = runoffR = dust processesS = urban effects
LSM processes
HG
FE
D
CB
A J
RQ
P
O N M L
K
I
S
Proposed COAMPS Land Surface Model (LSM) System
Urban Canopy Parameterization
||)(... uuzaCft
udurb
(1) Momentum loss
(2) Turbulence production
(3) Radiation absorption
(4) Surface energy budget
)|||||)(|(...)( 333 wvuzaCf
t
TKEdurb
)(||)()1( 4 TTVCcTRRq roofDroofproofLWSWroof
]})()[()1
1()1{(1
... 1
roof
roofroof
Ncroofurb
urburb
Nurb
p C
qzbf
z
Rff
Bz
qf
z
Rf
ct
GNccnynGnetLW
netSWurbNG RfRRfR )]0([))(1(
• Originally developed by Brown and Williams (1998), modifiedby Chin et al. (2000)
(1)
(2)
(4)
(3)
• Roof albedo () = 0.22• Roof emissivity () = 0.91• Roof heat capacity (Croof) =9.681 e4• Roof drag coefficient (CDroof) = 7.1e-3• Urban drag coefficient (Cd) = 1.2e-2• Extinction coefficient (k) = 0.1• Bowen ratio (Br) = 1.5• Canopy area density (a(z))= linear in z
Analytic Solution Rigid Lid (wtop=0)
Radiation Condition (Klemp&Durran) MM5 Local Radiation Condition
w (105 m s-1) w (105 m s-1)
w (105 m s-1) w (105 m s-1)
COAMPS Upper Boundary ConditonLinear Hydrostatic Gravity Wave Test
COAMPSCoupled Ocean/Atmosphere Mesoscale Prediction System:
Ocean Components
•Data Quality Control•Analysis:
• 2D MVOI of Sea Surface Temp on All Grids• 3D MVOI Analysis of Temperature, Salinity, Surface Height, Sea Ice, Currents
•Ocean Model: Navy Coastal Ocean Model (NCOM)• Numerics: Hydrostatic, Scheme C, Nested Grids, Hybrid Sigma/z• Parameterizations: Mellor-Yamada 2.5
•Features:• Globally Relocatable (5 Map Projections)• User-Defined Grid Resolutions, Dimensions• Can be Used for Idealized or Real-Time Applications• Single Configuration Managed System for All Applications• Loosely coupled to COAMPS atmospheric model
•Strategy for testing coupled system:• construct a Mesoscale Atm-Ocean Data Assimilation System for the Med. Sea• quantify the skill of system• examine the Adriatic Sea at high resolution as a test-bed for coupling strategies
1 Oct 1999 3 Oct 1999
1 Oct 1999
5 Oct 1999
3 Oct 1999 5 Oct 1999
NCOM Forecasts
Sea Surface Temperature (C)
Surface Velocity (cm/s)
12.8 10.9• •
24-h Forecast Valid at 1200 UTC 24 August 1998
Uncoupled Coupled
(x=6 km)
NASA Scanning Radar Altimetry
Wright et al. (2000)
Coupled COAMPS/WAM Simulation of TC BonnieSignificant Wave Height (m)
Future Plans
• Development and Implementation of:• 3D variational analysis (NAVDAS)• aerosol model• air-ocean coupled system• land-surface model (LSM) (NOAH)• improved microphysical parameterization• improved Mellor-Yamada Level 2.5 BL Param.• incorporation of WRF KF scheme• LES Option• mesoscale verification• efficiency improvements
Future Plans
• COAMPS and WRF Comparisons:• Idealized Simulations• Real Data Simulations
• Interchange of Key COAMPS/WRF Modules• Collaboration With WRF Community
• Land Surface Model (NOAH)• Physical Parameterization & Numerical Techniques• Ocean/Atmosphere Coupling Methods• Tropical Cyclones• Efficiency/MPI Issues• Proposed Next Generation Micro- Scale Model
COAMPS (400x100x30) (27,9,3 km) 12-h fcst ams1 (512p)
100
1000
10000
100000
25 50 100 200 400
No. of processors
Ela
pse
d t
ime
(sec
)
mpi-1mpi-2linear
COAMPS FNMOC Operational Areas
Arabian Sea
27 km
81 kmArea 1
27 km
81 km
9 km
Cent_Am27 km
81 km
Conus
E_Pac
As of:February 25, 2002
Europe
Southwest_Asia27 km
81 km
9 km
W_Atl
W_Pac
27 km
81 km
27 km
81 km
27 km
81 km27 km
81 km27 km
81 km
NAAPS Aerosol Optical DepthTOMS Aerosol Index
SeaWiFS True Color image
13 February, 2001
red – sulfategreen – dustblue - smoke
NAAPS/NOGAPS Simulates Large-scale Dust Storms
Mediterranean, 18 April, 2001
Africa Coast, 21 April, 2001
Arabian Sea, 7 December, 1999
Korea, 31 March, 2001
SeaWiFS images from Kuring/GSFC
Dust Storms: A Recurring, Worldwide ProblemMobilization and Transport Controlled by Mesoscale Dynamics
•Software developed using MPI•Makes use of existing COAMPS nesting software•Advantages:
•Allows for smaller nests (less resources required)•Flexibility in movement of nests:
•Namelist specified options:•Battle group option (“target” times/locations)•User specified grid point movement
•Nests automatically move together•Automated tropical cyclone movement option (under development)
COAMPS MPI Moving Nest Software Development
Recent Developments of the Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS), Ninth Conference on Mesoscale Processes
(1,1)
(m,n)(1,n)
(m,1)(1,1)
(m,n)(1,n)
(m,1)(1,1)
(m,n)(1,n)
(m,1)
Fixed Nest 1:(m x n) points 3 x 3 domaindecomposition2 Halo Points
Moveable Nest 2: Time = t0
(1,1)
(m,n)(1,n)
(m,1)(1,1)
(m,n)(1,n)
(m,1)(1,1)
(m,n)(1,n)
(m,1)
Dropped region
Interpolated region
Shifted region
Time = t1
MPI communicationsneeded for shifted and
interpolated areas
COAMPS MPI Moving Nest Software Development
Recent Developments of the Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS), Ninth Conference on Mesoscale Processes
COAMPS CONUS Model Grid Setup
Pacific Northwest (PNW)
Mississippi River Basin (MRB)
0
0.5
1
1.5
2
2.5
3
0.25 2.5 5 10 15 25 35 50 75
Precipitation Threshold (mm/day)
Bia
s
0
0.1
0.2
0.3
0.4
0.25 2.5 5 10 15 25 35 50 75
Precipitation Threshold (mm/day)
E-T
H 0-24 h24-48 h
COAMPS CONUS 2001 Cold Season (20011113-20020430) Precipitation Scores
0
0.1
0.2
0.3
0.4
0.25 2.5 5 10 15 25 35 50 75
Precipitation Threshold (mm/day)
E-T
H
PNW27PNW9MRB27MRB9
COAMPS CONUS Regional One-Week (20020125-20020201) Precipitation Scores
0
0.5
1
1.5
2
2.5
3
0.25 2.5 5 10 15 25 35 50 75
Precipitation Threshold (mm/day)
Bia
s
00.05
0.10.15
0.20.25
0.30.35
0.4
0.25 2.5 5 10 15 25 35 50 75
Precipitation Threshold (mm/day)
E-T
H Bench
New Micro
0
0.2
0.4
0.6
0.8
1
1.2
0.25 2.5 5 10 15 25 35 50 75
Precipitation Threshold (mm/day)
Bia
s
COAMPS CONUS One-Week (20020125-20020201) Precipitation Scores
COAMPS Availability
Download COAMPS
http://www.nrlmry.navy.mil/projects/coamps/index.html
• Innovations (ob-bckgnd) computed using highest resolution COAMPS background available for each observation
• Single merged analysis grid vectors formed by combination of all the nested grid points
• Analysis corrections added back to each nested grid on vertical sigma_z model levels
• Display on pressure levels
Wind speed analysis300 mb
NAVDAS: Nested COAMPS
108 km
36 km
12 km
COAMPS MPI Moving NestsHurricane Gordon 00Z September 17- 00Z September 19, 2000
Moving Nest Option is 2.7x Faster on O2K
Moving Nest Option
Nest 2 at tau = 0 h
Nest 2 at tau = 48 h
81 km (61x61)
27 km (46x46)
Fixed Nest Option
Forecast position: 0-48 h (every 6 h)
0 h
48 h
81 km (61x61)
27 km (121x85)
COAMPS Dipole Jewel 5 SimulationsImpact of Increased Horizontal Resolution
Nest 2 (9 km)
10-m dosage (arbitrary units) and model terrain (m)26-h forecast (valid 02 UTC 29 Oct)
Nest 3 (3 km) Nest 4 (1 km)
Control Simulations-3
log
-2 -1 0 1 2
COAMPSTM Urban 2000 SimulationsSalt Lake City Nest 4 1-km resolution (49 x 49 km): 12-h fcsts
5
20
0
4
BG
RW
SLC
10-m air temp 10-m wind speed
12 00 12 00 12 UTC16 Oct 17 Oct 18 Oct
15
10
deg
C
5
20
15
10
5
15
10
2
1
3
0
2
1
3
5
0
4
2
1
3
5
m/s
12 00 12 00 12 UTC16 Oct 17 Oct 18 Oct
Urban
Control
Obs
bias = 0.865, 0.099rms = 1.712, 1.391
bias = 0.103, 0.966rms = 0.394, 1.197
bias = 0.470, -0.441rms = 2.972, 2.849
bias =-0.292, 0.309rms = 0.856, 0.991
Urban too warm at night
Little daytime difference
Reduction and improvement in day and nighttime winds
Two-Way Coupling
- Important in Boundary Layer (Janssen et al. 1989)
- Improved Model Climate (Viterbo and Janssen 1996)
- Extratropical Cyclones (Doyle 1995; Lalbebarry et al. 2000; Lionello et al. 1998)
- ECMWF/WAM Coupled System ( Janssen et al. 2001)
WAM (Cycle 4) (WAMDI Group 1988)
Wave Spectrum Predicted From Energy Balance Equation
F(,): 2d Wave Variance Spectrum Coupling Methodology (Janssen 1989; Janssen 1991)
COAMPS (zo, Fluxes, e, Kh, m, , U10) WAM ()
DSNLg INF (V F) S S S
t
inw w
d d Sg
c
zo=U*
2/g, where =(1-w/)-0.5
e
tu
e
xv
e
y
eBP SP D K eH
,
4
Coupled COAMPS/WAM
Surface Wind Stress (dynes/cm2)
Surface Heat Flux (W/m2)
1 Oct 1999 3 Oct 1999 5 Oct 1999
1 Oct 1999 3 Oct 1999 5 Oct 1999
COAMPS Atmospheric Forcing
COAMPS Dipole Jewel 5 SimulationsNest4: Transport
Observed:Cloud Track to T+105 min.
DTRA
1-km Land-use Simulation
Asterisks every 5 min from2145-2330 UTC 28 Oct 98
24-h forecast valid0000 UTC 29 Oct 98
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