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