2016 L11 MEA716 2 18 CP1 - Nc State University€¦ · 3.) Control simulation, hypothesis...
Transcript of 2016 L11 MEA716 2 18 CP1 - Nc State University€¦ · 3.) Control simulation, hypothesis...
Thu 2/18/2016• Discuss some model capabilities relating to project• Final PBL wrap-up• Begin convective parameterization section
Reminders/announcements:- Convective parameterization assignment (short)- Project hypothesis assignment, due (presented) Tue 3/15
- Added a short “progress report”, due on 2/25, to allow feedback
- Midterm Thu 3/3
Under water?• WRF OML option (module_sf_oml.F) based on Pollard et al.
(1972): 1-D mixed layer, uniform T, SST returned
• Also 3-D ocean model (module_sf_3dpwp.F) based on Price et al. (1994, JPO), also Lee and Chen (2013, MWR)
• With both, can specify initial characteristics in namelist
PBL Wrap-Up
• Review: What are the “defining characteristics” of the different PBL schemes available in WRF?
– Local versus non-local (local schemes tend to be higher order)
– Explicit entrainment (more in non-local)
– Scale aware?
• Awareness of “history” of each scheme teaches about its “specialty”
• Many schemes tested in SCM mode against LES and/or field experiment data; not all exhaustively evaluated
PBL Wrap-Up• Basic concepts: Reynolds-averaged equations, closure
problem, boundary and surface layer structure
• Reviewed simplest methods (Bulk, K-theory), related these to more advanced methods
• Local versus non-local approaches, challenges of diurnal variations, physics interactions, scale separation
• Review of WRF PBL schemes, including some new ones: Goal is to allow informed physics choices
• Always, use SCM, examine tendencies to try and understand what a given scheme is doing
WRF PBL Options (partially from Dudhia)bl_pbl Scheme Sfc layer Characteristics Design Cloud mixing
1 YSU 1 Explicit entrainment, first order Local + non-local Qc, Qi
2 MYJ 2 TKE scheme Local, 1.5 order Qc, Qi
4 QNSE 4 TKE, a spectral scheme (quasi-normal scale elimination)
Local, 1.5 order Qc, Qi
5 MYNN2 1,2,5 Improves MY length scale, adds buoyancy effects
Local, 1.5 order Qc
6 MYNN3 1,2,5 Higher order version of MYNN2 Local, 2nd order Qc
7 ACM2 1,7 Combines non-local, eddy diff., asymmetric mixing
Local + non-local Qc, Qi
8 BouLac 1,2 TKE similar to MYJ, Tested for orographic turbulence
Local, 1.5 order Qc
9 UW 9 TKE scheme, for CAM, explicit entrainment
Local, 1.5 order Qc, Qi (?)
10 TEMF 10 Explicit shallow cumulus, considers total turb. energy
Local + non-local Qc, Qi
11 Shin-Hong 1 + others?
Scale-aware non-local PBL scheme for “gray zone” runs
Local + Non-local Qc, Qi
12 GBM 9 With entrainment, for coarse vert. resolution (GCM)
Local, 1.5 order Qc, Qi
99 MRF 1 Older version, YSU updates Local + non-local QC, QI
Semester OutlineModel Physics:
1.) Land-Surface Models (LSM)2.) Turbulence parameterization & the planetary boundary layer (PBL)3.) Convective parameterization4.) Cloud and precipitation microphysics5.) Parameterization of radiation
Project:1.) Topic selection, case identification2.) Hypothesis development3.) Control simulation, hypothesis presentation4.) Experiments and final presentation
Technical:1.) Running SCM2.) Running WPS, WRF, postprocessing for real-data cases3.) Model experiments: Terrain and physics modifications4.) Analysis and diagnosis of model output
DoneDoingNot yet
Project: WRF capabilitiesI’ve put some utility codes in class directory:• Terrain modification (2 methods)
– Modify at geogrid stage for consistency
– Use WPS version that modifies terrain (if 1-2-1 smoother specified in GEOGRID.TBL). See smooth_module.F in geogrid/src directory
– See ../class/model/WRF/WPSV371_c7_compiled_terropt.tar.gz
– Use read_wrf_nc.f, a utility program that easily modifies any aspect of a NetCDF file (see ../class/model/WRF/read_wrf_nc_method files)
Project: WRF capabilitiesI’ve put some utility codes in class directory:• Terrain modification (2 methods)
– Modify at geogrid stage for consistency
– Use WPS version that modifies terrain (if 1-2-1 smoother specified in GEOGRID.TBL). See smooth_module.F in geogrid/src directory
– See ../class/model/WRF/WPSV371_c7_compiled_terropt.tar.gz
– Use read_wrf_nc.f, a utility program that easily modifies any aspect of a NetCDF file (see ../class/model/WRF/read_wrf_nc_method files)
Project: WRF capabilities• Terrain modification: Recommend using geogrid/WPS
method for greater consistency – but read_wrf_nc for slope
• Need to modify SLOPECAT, not just HGT_M
Original HGT_M Modified HGT_M SLOPECAT for both
Project: WRF capabilities• Terrain modification: Recommend using geogrid/WPS
method for greater consistency – but read_wrf_nc for slope
• Need to modify SLOPECAT, not just HGT_M
Original HGT_M Modified HGT_M SLOPECAT for both
Project: WRF capabilities• Using read_wrf_nc.f is very easy, but dangerous!• Always make back-up of file to be modified first• Check carefully before and after to ensure desired results• See ../class/model/WRF/read_wrf_nc_method
• Only compiles (easily) in Centos 5– Make backup of file to be modified– Edit FORTRAN code (bottom)– Compile using script– Run separate script to apply
(file to modify specified there)– Check using ncview
Sea‐Level Pressure Evolution & Analysis – Hour 000
Removed Joaquin using vorticity inversion + read_wrf_nc.f
Convective ParameterizationOutline for convective parameterization (CP) section:
A. Concept 1.) Thought experiment2.) Equations and formulations
B. Why CP schemes are needed and matter1.) Types of NWP problems affected by CP schemes2.) Examples (time permitting)
C. CP Scheme Fundamentals1.) Adjustment versus mass-flux schemes2.) The Betts-Miller-Janjic CP scheme3.) The Fritsch-Chappell and Kain-Fritsch schemes4.) Tiedtke and Arakawa-Schubert schemes
D. Modifications to CP schemes, model experiments
Hurricane Joaquin case
Two WRF simulations identical, but one uses newer Tiedtke (16), the other uses older Tiedtke (6)
One *very* recent example of CP import:
Must evaluate importance of processes operating on spatial scales not resolved by model
If important, effects must be accounted for, even if not explicitly resolved in model
Must include account while keeping system closed
Examples: Turbulence, shallow (non-precipitating) convection, deep (precipitating) convection, etc.
Parameterization
What are some similarities between convection and turbulence parameterization?
What are some differences?
Convection and Turbulence
• Up-scale growth to grid-resolvable scales• Direct interaction with microphysics (radiation)• Larger spatial scales
• Reynolds-averaged equations to reveal closure problem due to sub-gridscale motions
• Similar issues with moist, convecting PBL• Assumed to act independently in grid column
Are some CP schemes less testable in SCM mode?
Why might this be the case?- Larger spatial scales involved- Trigger for convection often involves convergence, vertical
motion; could add to SCM forcing- Upscale growth of convection can affect surrounding grid
cells, important to represent
• CP scheme distinguishing characteristics:- “Adjustment” versus “mass flux” formulation- Account of shallow mixing?- Momentum adjustment or not (hurricanes!)
Model CP Schemes
What properties must hold for relations between the grid-scale quantities and sub-grid scale processes?
Must be quasi-universal (apply over a wide range of conditions and locations)
Must not compromise predictability of large-scale fields
• For convection, problem especially difficult when convection becomes organized, partially resolved
Model CP Schemes
x = 60 km
Scattered showers
and storms
Consider convective storms:
Storms are subgrid-scale
Grid box is NOT saturated
Storms must be handled by CP scheme
1 model grid cell:
= cloudy (saturated) air
Grid Length, representation of storms
x = 60 km
Organized
Convection
Consider a larger, organized storm complex: Mesoscale Convective System (MCS):
Storm is subgrid-scale
Grid box NOT saturated
Storm must be handled by CP scheme
1 model grid cell:
= cloudy (saturated) air
Adapted from presentation by Jason Millbrandt, McGill
Grid Length, representation of storms
x = 12 km
Model grid cells:
= cloudy (saturated) air
Now, storm partly resolved
Some grid boxes saturated
Handled by both CP, microphysics schemes
Note: 12 km is current grid length in NAM model
Organized
Convection
Grid Length, representation of storms
x < 3 km
Model grid cells:
Storm fully resolved
Some partially saturated grid boxes at edges
CP not required
Handled by microphysics scheme
= cloudy (saturated) air
Organized
Convection
Grid Length, representation of storms
x = 25 km
Model grid cells:
Real MCS for scale
At mature stage, system handled by CP,
microphysics schemes
Resolved on grid but without details of structure
31 December 2002
200 km
Grid Length, representation of storms
31 December 2002 MCS
1 10 100 km
Convective ParameterizationExplicit Convection
LES PBL Parameterization
Two Stream Radiation3-D Radiation
Model Physics and Resolution (modified from Jimy Dudhia, NCAR)
Physics
“No Man’s
Land”
Convective parameterization requires scale separationbetween resolved, parameterized processes
Problematic for grid lengths between ~ 5, 12 km: too coarse to run without convective scheme, but partially resolve convective systems
Weisman et al. (1997) show that 4-km grid length sufficiently matches 1-km grid length to justify omission of CP
Bryan et al. (2003) suggest that much higher resolution (order 100 m grid) required for research-grade simulations
Model CP Schemes
Parameterization problem especially difficult when mesoscale cloud organization present:
Convection partially resolved, partially parameterized
No clear scale separation, interaction between schemes can be problematic
Model CP Schemes: General
Cumulus ConvectionHow is the cumulus field on this day changing the larger-scale environment?
(problem 1 in thought experiment)
What physical processes are responsible, or need to be accounted for in this?
Convective Parameterization thought experiment
What is the impact of sub-grid scale convection on the grid-scale atmosphere over the Southeast?
Cooling
Warming
Require net drying in column
to allow precipitation
Cooling
Moistening aloft
Drying below
Wind field changes?
RQVCUTENRTHCUTEN
Ran SCM with BMJ CP
Cumulus ConvectionHow is the cumulus field on this day changing the larger-scale environment in which it is embedded?
- Stabilize environment (warming aloft, cooling below)
- Compensating subsidence warms, dries air outside convective towers
- Moistens air aloft, transports water vapor upward
- Produces cloud cover aloft (anvil material) if Cumulonimbus, alters grid-cell albedo
- Alters momentum
- Generates precipitation, results in net drying in column