WRF Physics¶

Earth’s atmosphere houses a variety of interacting physical processes, as are illustrated in the above image.
Shortwave radiation from the sun is absorbed, reflected, and/or scattered by Earth’s surface, clouds, aerosols, gases, etc.
Longwave radiation emitted from Earth’s surface either exits the atmosphere or is deflected back by gas particles and clouds.
Heating from diurnal radiation creates a boundary-layer, which increases turbulence and potentially convection.
Clouds are created by radiative or lifting processes, and produce precipitation in various forms (e.g., rain, snow, and graupel).
Chemical components (e.g., aerosols, ozone, and pollutants) can modify clouds and radiation.
At the surface, the roughness and other properties of land types (e.g., mountains, trees, buildings) modify surface fluxes.
All of these processes work together to create our weather and climate. The WRF model code offers various physics that employ different calulation methods to best represent Earth’s atmospheric. The below image illustrates the ways in which the schemes interact.

Cumulus Parameterization¶

WRF Cumulus Parameterization Schemes
Physics schemes that parameterize sub-grid-scale effects of convective and shallow clouds.
Cumulus schemes activate column-by-column, depending on the presence of convective instability, and are responsible for the following:
Providing column tendencies of heat and moisture to the model
Providing the convective component of surface rainfall to the model
Redistributing air in gridded columns to account for vertical convective fluxes
Updrafts lift boundary layer air, while downdrafts bring mid-level air downward. Schemes determine when and how quickly to trigger a convective column.
WRF cumulus schemes (except BMJ) are mass flux schemes, determining updraft/downdraft mass (and other) fluxes - this can include momentum transport. Updrafts, driven by buoyancy, send moist surface air up to the upper troposphere, and condensation becomes convective rainfall. Downdrafts occur when convective rain evaporates, which cools air to the boundary layer. Subsidence, the primary warming contributor in the column, warms and dries the troposphere. The BMJ scheme is an adjustment type, and relaxes toward a post-convective (mixed) sounding.
It is not always necessary to use cumulus parameterization. It is designed for grid sizes unable to parameterize the convective processes (i.e., when updrafts and downdrafts are sub-grid).

The following are general rules for WRF cumulus parameterization, which are illustrated in the above image:
Domain Grid Spacing |
Guidelines |
---|---|
>=10km |
a cumulus scheme is necessary |
<=3km |
a cumulus scheme is likely unnecessary, though it may help if convection exists just prior to the simulation start time |
>=3km to <=10km |
This is a “gray zone” where cumulus parameterization may or may not be necessary; try to avoid domains this size; if unavoidable, use the Multi-scale Kain Fritsch or Grell-Freitas scheme, which account for these scales. |
See also
See the WRF Tutorial presentation on cumulus parameterization for additional details.
Cumulus Options¶
Moisture tendencies below represent mixing ratios of:
c : cloud water
r : rain water
i : cloud ice
s : snow
Scheme |
Option |
Moisture Tendencies |
Momentum Tendencies |
Shallow Convection |
Radiation Interaction |
---|---|---|---|---|---|
Kain-Fritsch (KF) |
1 |
Qc Qr Qi Qs |
no |
yes |
yes |
BMJ |
2 |
N/A |
no |
yes |
GFDL |
Grell-Freitas |
3 |
Qc Qi |
no |
yes |
yes |
Old SAS |
4 |
Qc Qi |
no |
yes |
GFDL |
Grell-3 |
5 |
Qc Qi |
no |
yes |
yes |
Tiedtke |
6 |
Qc Qi |
yes |
yes |
no |
Zhang-McFarlane |
7 |
Qc Qi |
yes |
yes |
RRTMG |
KF-CuP |
10 |
Qc Qi |
no |
yes |
yes |
Multi-scale KF |
11 |
Qc Qr Qi Qs |
no |
yes |
? |
KIAPS SAS |
14 |
Qc Qi |
yes |
use shcu_physics=4 |
GFDL |
New Tiedtke |
16 |
Qc Qi |
yes |
yes |
no |
Grell-Devenyi |
93 |
Qc Qi |
no |
no |
yes |
NSAS |
96 |
Qc Qi |
yes |
no/yes |
GFDL |
Old KF |
99 |
Qc Qr Qi Qs |
no |
no |
GFDL |
Cumulus Details and References¶
Kain-Fritsch (KF)¶
cu_physics=1
Deep and shallow convection sub-grid scheme using a mass flux approach with downdrafts and CAPE removal time scale
Kain, 2004
The following additional options may be used with this scheme:
kfeta_trigger :
=1 : default trigger
=2 : moisture-advection modulated trigger function (Ma and Tan, 2009), which can improve results in subtropical regions with weak large-scale forcing
=3 : RH-dependent perturbation - additional to option 1
cu_rad_feedback=.true. : allows sub-grid cloud fraction interaction with radiation (Alapaty et al., 2012)
Betts-Miller-Janjic (BMJ)¶
cu_physics=2
Operational Eta scheme. Column moist adjustment scheme relaxing towards a well-mixed profile.
Janjic, 1994
Grell-Freitas (GF)¶
cu_physics=3
An improved Grell-Devenyi (GD) that attempts smoothing the transition to cloud-resolving scales, as proposed by Arakawa et al., 2004
Grell and Freitas, 2014
Simplified Arakawa-Schubert (SAS)¶
cu_physics=4
Simple mass-flux scheme with quasi-equilibrium closure, that includes a shallow mixing scheme.
Pan et al., 1995
Grell 3D (G3)¶
cu_physics=5
An improved Grell-Devenyi (GD) that can be used with high (and coarse) resolution when subsidence spreading (cugd_avedx) is turned on.
Grell, 1993
Grell and Devenyi, 2002
Tiedtke scheme¶
cu_physics=6
(U. of Hawaii version); Mass-flux scheme with a CAPE-removal time scale, shallow component, and momentum transport.
Tiedtke, 1989
Zhang et al., 2011
Zhang-McFarlane¶
cu_physics=7
Mass-flux CAPE-removal deep convection scheme with momentum transport - from the CESM climate model.
Zhang and McFarlane, 1995
Kain-Fritsch (KF)¶
cu_physics=10
Cumulus Potential scheme, which modifies the KF ad-hoc trigger function. This scheme links to boundary layer turbulence via probability density functions (PDFs) and computes cumulus cloud fraction based on a time scale relevant for shallow cumuli.
Berg et al., 2013
Multi-scale Kain-Fritsch¶
cu_physics=11
LCC-based entrainment, using a scale-dependent dynamic adjustment timescale and a trigger function based on Bechtold et al., 2001; includes an option to use CESM aerosol. Since wrfv4.2 convective momentum transport is added and turned on, by default - turn off by setting cmt_opt_flag = .false. in wrf/phys/module_cu_mskf.F - then recompile WRF (no need to use ‘clean -a’ or reconfigure).
Zheng et al., 2016
Glotfelty et al., 2019
KIAPS SAS (KSAS)¶
cu_physics=14
Based on New Simplified Arakawa-Schubert (NSAS), but scale-aware
Han and Pan, 2011
Kwon and Hong, 2017
New Tiedtke¶
cu_physics=16
Similar to the Tiedtke scheme used in REGCM4 and ECMWF cy40r1.
Zhang and Wang, 2017
Grell-Devenyi (GD)¶
cu_physics=93
A multi-closure, multi-parameter, ensemble method with (typically) 144 sub-grid members.
Grell and Devenyi, 2002
New Simplified Arakawa-Schubert (NSAS)¶
cu_physics=96
A mass-flux scheme with deep/shallow components, and momentum transport.
Han and Pan, 2011
Old Kain-Fritsch¶
cu_physics=99
Deep convection scheme that uses a mass flux approach, including downdrafts and a CAPE removal time scale.
Kain and Fritsch, 1990
Shallow Convection¶
In addition to cumulus parameterization, shallow convection schemes can be used for grid sizes in which shallow cumulus clouds (>1 km) are not resolved. These scheme allow non-precipitating shallow mixing to dry the planetary boundary layer, and then moisten and cool above by enhanced mixing, or with a mass-flux approach.
The following cumulus schemes already include shallow convection:
Kain-Fritsch
Old SAS
KIAPS SAS
Grell-3
Grell-Freitas
BMJ
Tiedtke
The following standalone shallow schemes are available:
ishallow=1 |
Shallow convection that works with the Grell 3D scheme (cu_physics=5) |
shcu_physics=2 |
UW (Bretherton and Park) shallow cumulus option from the CESM climate model - includes momentum transport |
shcu_physics=3 |
GRIMS (Global/Regional Integrated Modeling System) scheme; represents the shallow convection process with eddy-diffusion and the pal algorithm, and couples directly to the YSU PBL scheme |
shcu_physics=4 |
NSAS shallow scheme; extracted from NSAS, and should be used with the KSAS deep cumulus scheme |
shcu_physics=5 |
Deng shallow scheme; only works with the MYNN and MYJ PBL schemes; (available since wrfv4.1) |
Microphysics¶

WRF Microphysics Schemes
Physics schemes that resolve cloud and precipitation processes, with some accounting for ice and/or mixed-phases processes.
WRF microphysics schemes provide atmospheric heat and moisture tendencies, and the resolved-scale (non-convective) rainfall at the surface. They consider various microphysical processes and different particle formation, depending on their type:
Cloud droplets (10s of microns) condense from vapor at water saturation
Rain (~mm diameter) forms from cloud droplet growth
Ice crystals (10s of microns) form from droplet freezing or deposition on nuclei, which are assumed or explicit (e.g., dust particles)
Snow (100s of microns) forms from growth of ice crystals at ice supersaturation and aggregation
Graupel/hail (mm to cm) form and grow from mixed-phase interactions between water and ice particles
Precipitating particles are typically assigned to an observationally-based size distribution
WRF includes the following types of microphysics schemes:
Note
More advanced scheme types are more computationally expensive.
Single-moment |
Use a single prediction mass equation per species, where particle size distribution is derived from fixed parameters (Qr, Qs, etc.) |
Double-moment |
Add a number concentration prediction equation per double-moment species (Nr, Ns, etc.), allowing for additional processes (e.g., size-sorting during fall-out, aerosol effects, etc.) |
Spectral bin |
resolve size distribution by doubling mass bins |
See also
See the WRF Tutorial presentation on microphysics for additional details.
Microphysics Options¶
In the table below, abbreviations are defined as follows:

Scheme |
Option |
Mass Variables |
Number Variables |
---|---|---|---|
Kessler |
1 |
Qc Qr |
N/A |
Purdue Lin |
2 |
Qc Qr Qi Qs Qg |
N/A |
WSM3 |
3 |
Qc Qr |
N/A |
WSM5 |
4 |
Qc Qr Qi Qs |
N/A |
Eta (Ferrier) |
5 |
Qc Qr Qs Qt* |
N/A |
WSM6 |
6 |
Qc Qr Qi Qs Qg |
N/A |
Goddard 4-ice |
7 |
Qc Qr Qi Qs Qg Qh |
N/A |
Thompson |
8 |
Qc Qr Qi Qs Qg |
Ni Nr |
Milbrandt 2-mom |
9 |
Qc Qr Qi Qs Qg Qh |
Nc Nr Ni Ns Ng Nh |
Morrison 2-mom |
10 |
Qc Qr Qi Qs Qg |
Nr Ni Ns Ng |
CAM 5.1 |
11 |
Qc Qr Qi Qs |
Nc Nr Ni Ns |
SBU-YLin |
13 |
Qc Qr Qi Qs |
N/A |
WDM5 |
14 |
Qc Qr Qi Qs |
Nn Nc Nr |
WDM6 |
16 |
Qc Qr Qi Qs Qg |
Nn Nc Nr |
NSSL |
18 |
Qc Qr Qi Qs Qg Qh |
Nc Nr Ni Ns Ng Nh Nn |
WSM7 |
24 |
Qc Qr Qi Qs Qg Qh |
N/A |
WDM7 |
26 |
Qc Qr Qi Qs Qg Qh |
Nc Nr |
Thompson Aerosol |
28 |
Qc Qr Qi Qs Qg |
Nc Ni Nr Nn Nni |
HUJI Fast |
30 |
Qc Qr Qi Qs Qg |
Nn Nc Nr Ni Ns Ng |
Thompson Hail/Graupel/Aerosol |
38 |
Qc Qr Qi Qs Qg |
Nc Ni Nr Nn Nni Ng Vg |
Morrison 2-mom Aerosol |
40 |
Qc Qr Qi Qs Qg |
|
P3 |
50 |
Qc Qr Qi |
Nr Ni Ri Bi |
P3-nc |
51 |
Qc Qr Qi |
Nc Nr Ni Ri Bi |
P3-2nd |
52 |
Qc Qr Qi2 |
Nc Nr Ni Ni2 Ri Ri2 Bi Bi2 |
P3-3mc |
53 |
Qc Qr Qi |
Nc Nr Ni Ri Bi Zi |
ISHMAEL |
55 |
Qc Qr Qi Qi2 Qi3 |
Nr Ni Ni2 Ni3 Vi Vi2 Vi3 Ai Ai2 Ai3 |
NTU |
56 |
Qc Qr Qi Qs Qg Qh Qden Qten Qccn Qrcn |
Nc Nr Ni Ns Ng Nh Nin Ai As Ag Ah Vi Vs Vg Fi Fs |
Microphysics Option Details and References¶
Kessler¶
mp_physics=1
A warm-rain (no ice) scheme used commonly in idealized cloud modeling studies
Kessler, 1969
Purdue Lin¶
mp_physics=2
A sophisticated scheme that includes ice, snow, and graupel processes suitable for real-data high-resolution simulations
Chen and Sun, 2002
WRF Single-moment 3-class (WSM3)¶
mp_physics=3
A simple, efficient scheme with ice and snow processes, suitable for mesoscale grid sizes
Hong et al., 2004
WRF Single-moment 5-class (WSM5)¶
mp_physics=4
A slightly more sophisticated version of WRF Single-moment 3-class (WSM3) that allows for mixed-phase processes and super-cooled water
Hong et al., 2004
Ferrier Eta¶
mp_physics=5
The operational microphysics used in NCEP models; simple and efficient, with diagnostic mixed-phase processes; for fine resolutions (<5km)
NOAA, 2001
WRF Single-moment 6-class (WSM6)¶
mp_physics=6
Includes ice, snow and graupel processes, suitable for high-resolution simulations
Hong and Lim, 2006
Goddard 4-ice¶
mp_physics=7
Predicts hail and graupel separately; provides effective radii for radiation. Replaced older Goddard scheme since wrfv4.1.
Tao et al., 1989
Tao et al., 2016
Thompson et al.¶
mp_physics=8
Includes ice, snow and graupel processes suitable for high-resolution simulations
Thompson et al., 2008
Milbrandt-Yau Double-moment 7-class¶
mp_physics=9
Includes separate categories for hail and graupel with double-moment cloud, rain, ice, snow, graupel and hail
Milbrandt and Yau, 2005 (Part I)
Milbrandt and Yau, 2005 (Part II)
Morrison Double-moment¶
mp_physics=10
Double-moment ice, snow, rain and graupel for cloud-resolving simulations
Morrison et al., 2009
CAM V5.1 2-moment 5-class¶
mp_physics=11
User’s Guide to the CAM-5.1
Stony Brook University (Y. Lin)¶
mp_physics=13
A 5-class scheme with riming intensity predicted to account for mixed-phase processes
Lin and Colle, 2011
WRF Double-moment 5-class (WDM5)¶
mp_physics=14
Similar to WRF Single-moment 5-class (WSM5), but includes double-moment rain, and cloud and CCN for warm processes
Lim and Hong, 2010
WRF Double-moment 6-class (WDM6)¶
mp_physics=16
Similar to WRF Single-moment 6-class (WSM6), but includes double-moment rain, and cloud and CCN for warm processes
Lim and Hong, 2010
See also
See WRF/doc/README.NSSLmp for details about NSSL microphysics schemes.
If using WRF prior to v4.6.0, and an NSSL microphysics scheme, see NSSL Options Prior to v4.6.0.
NSSL 3-moment scheme with hail and CCN prediction¶
mp_physics=18
and either of the following:
nssl_3moment=1 : predict radar reflectivity from rain
nssl_3moment=2 : predict radar reflectivity of rain and hail
Note
This option is available for WRF v4.6.0+.
NSSL 2-moment scheme with hail and CCN prediction¶
mp_physics=18
Mansell et al., 2010
NSSL 2-moment scheme without hail¶
mp_physics=18
and either of the following:
nssl_hail_on=0
nssl_ccn_on=0
Note
This option is equivalent to mp_physics=22 from versions prior to v4.6.0.
NSSL 2-moment scheme with hail and constant background CCN¶
mp_physics=18, and
nssl_ccn_on=0
Mansell et al., 2010
Note
This option is equivalent to mp_physics=17 from versions prior to v4.6.0.
NSSL single-moment scheme, 7-class with predicted graupel density¶
mp_physics=18, and
nssl_2moment_on=0
nssl_ccn_on=0
Mansell et al., 2010
Note
This option is equivalent to mp_physics=19 from versions prior to v4.6.0.
NSSL single-moment scheme, 6-class with predicted graupel density¶
mp_physics=18, and
nssl_2moment_on=0
Mansell et al., 2010
Note
This option is equivalent to mp_physics=19 from versions prior to v4.6.0.
NSSL single-moment scheme, 6-class¶
mp_physics=18, and
nssl_2moment_on=0
nssl_hail_on=0
nssl_ccn_on=0
nssl_density_on=0
Mansell et al., 2010
Note
This option is equivalent to mp_physics=21 from versions prior to v4.6.0.
WRF Single-moment 7-class (WSM7)¶
mp_physics=24
Similar to WRF Single-moment 6-class (WSM6), but with an added hail category (effective beginning with v4.1)
Bae et al., 2018
WRF Double-moment 7-class (WDM7)¶
mp_physics=26
Similar to WRF Double-moment 6-class (WDM6), but with an added hail category (effective beginning with v4.1)
Bae et al., 2018
Thompson Aerosol-aware¶
mp_physics=28
Considers water- and ice-friendly aerosols
Thompson and Eidhammer, 2014
A climatology data set may be used to specify initial and boundary conditions for the aerosol variables; includes a surface dust scheme.
Since wrfv4.4 a black carbon aerosol category is added; biomass burning is an options.
Hebrew University of Jerusalem Fast (HUJI)¶
mp_physics=30
Spectral bin microphysics, fast version
Shpund et al., 2019
Thompson Hail/Graupel/Aerosol¶
mp_physics=38
Similar to Thompson Aerosol-aware, but computes two-moment prognostics for graupel and hail and includes a predicted density graupel category. Datafile qr_acr_qg_mp38V1.dat must be in the directory where wrf.exe is run, or it can alternatively be computed using namelist option write_thompson_mp38table=.true. (note this may take ~20 mins using 12 CPUs, ~5 mins with 128 CPUs, and several hours with a single CPU).
Morrison double-moment scheme with CESM aerosol¶
mp_physics=40
Similar to Morrison Double-moment, but with CESM aerosol added. This option is only valid with the Multi-scale Kain-Fritsch cumulus scheme (cu_physics=11) and requires CESM RCP4.5 data - after downloading, unpack the file and link one of the available files to the directory where wrf.exe is run.
No publication available for this specific scheme
Morrison and Milbrandt Predicted Particle Property (P3)¶
mp_physics=50
A single ice category representing a combination of ice, snow and graupel that carries prognostic arrays for rimed ice mass and volume; single-moment rain and ice.
Morrison and Milbrandt, 2015
Morrison and Milbrandt Predicted Particle Property (P3-nc)¶
mp_physics=51
As in Morrison and Milbrandt Predicted Particle Property (P3), but adds supersaturation-dependent activation and double-moment cloud water
Morrison and Milbrandt, 2015
Morrison and Milbrandt Predicted Particle Property (P3-2ice)¶
mp_physics=52
As in Morrison and Milbrandt Predicted Particle Property (P3), but with two ice arrays and double-moment cloud water
Morrison and Milbrandt, 2015
Morrison and Milbrandt Predicted Particle Property (P3-3moment)¶
mp_physics=53
As in Morrison and Milbrandt Predicted Particle Property (P3), but with 3-moment ice and double-moment cloud water
No publication available for this scheme
Jensen ISHMAEL¶
mp_physics=55
Predicts particle shapes and habits in ice crystal growth; (available since wrfv4.1)
Jensen et al., 2017
National Taiwan University (NTU)¶
mp_physics=56
Double-moment liquid phase and triple-moment ice phase, considers ice crystal shape and density variations; supersaturation is resolved so that condensation nuclei (CN) activation is explicitly calculated; CN’s droplet mass accounts for aerosol recycling.
Tsai and Chen, 2020
Radiation¶

WRF Radiation Schemes
WRF physics schemes that obtain cloud properties from the microphysics scheme to compute atmospheric temperature tendency profiles and longwave/shortwave surface radiative fluxes.
- Longwave Radiation Schemes
Compute longwave radiation emitted and absorbed by the earth’s surface/clouds, and gases (e.g., water vapor, CO2). Wavelengths are thermal IR - longer than ~ 3 microns.
- Shortwave schemes
Compute incoming solar fluxes reflected by Earth’s surface/clouds or absorbed by gases (e.g., water vapor, ozone, aerosols). These schemes account for annual and diurnal cycles and include ultraviolet, visible, and near-IR solar spectrum wavelengths.

See also
See the WRF Tutorial presentation on radiation for additional details.
Longwave Radiation Schemes¶
WRF longwave radiation schemes:
Compute clear-sky and cloud upward and downward raditation fluxes
Consider infrared emissions from layers
Calculate surface emissivity based on the land type at each grid point
Cools each layer, due to flux divergence of layer emissions
Considers downward flux at the surface, which is crucial to the land-energy budget
Infrared radiation generally leads to cooling in clear air (~2K/day), with stronger cooling at cloud tops and warming at cloud bases
In the table below, microphysics interactions represent mixing ratios of:
c : cloud water
r : rain water
i : cloud ice
s : snow
g : graupel
Scheme |
Option |
Microphysics Interaction |
Cloud Fraction |
GHG |
---|---|---|---|---|
RRTM |
1 |
Qc Qr Qi Qs Qg |
1/0 |
constant or yearly GHG |
CAM |
3 |
Qc Qi Qs |
Max-rand overlap |
yearly CO2 or GHG |
RRTMG |
4 |
Qc Qr Qi Qs |
Max-rand overlap |
constant or yearly GHG |
New Goddard |
5 |
Qc Qr Qi Qs Qg |
Max-rand |
constant |
FLG |
7 |
Qc Qr Qi Qs Qg |
1/0 |
constant |
RRTMG-K |
14 |
Qc Qr Qi Qs |
Max-rand overlap |
constant |
Held-Suarez |
31 |
none |
none |
none |
GFDL |
99 |
Qc Qr Qi Qs |
Max-rand overlap |
constant |
The following are WRF’s available longwave radiation schemes:
RRTM¶
ra_lw_physics=1
Rapid Radiative Transfer Model. An accurate scheme using look-up tables for efficiency. Accounts for multiple bands, and microphysics species. For trace gases, the volume-mixing ratio values are CO2=379e-6, N2O=319e-9 and CH4=1774e-9. See the time-varying option in Options for Radiation Input.
Mlawer et al., 1997
CAM¶
ra_lw_physics=3
An option from CESM’s CAM 3 climate model that allows for aerosols and trace gases. It uses yearly CO2, and constant N2O (311e-9) and CH4 (1714e-9). See the time-varying option in Options for Radiation Input.
Collins et al., 2004
RRTMG¶
ra_lw_physics=4
A newer version of RRTM that includes the MCICA random cloud overlap method. For major trace gases, CO2=379e-6 (valid for 2005), N2O=319e-9, CH4=1774e-9. See the time-varying option in Options for Radiation Input.
Since wrfv4.2, the CO2 value is determined by the function: CO2(ppm) = 280 + 90 exp (0.02*(year-2000)). This function exhibits approximately 4% error when compared to observed values from the 1920s and 1960s, and about 1% error for years after 2000. A cloud overlap option is available beginning in wrfv4.4.
Iacono et al., 2008
New Goddard¶
ra_lw_physics=5
An efficient scheme with multiple bands that uses ozone from simple climatology. It is designed to run with Goddard microphysics particle radius information. The scheme had an update in wrfv4.1.
Chou and Suarez, 1999
Chou et al., 2001
Fu-Liou-Gu (FLG)¶
ra_lw_physics=7
A scheme with multiple bands that includes cloud and cloud fraction effects and profiles ozone based on climatology and tracer gases CO2=345e-6.
Gu et al., 2011
Fu and Liou, 1992
RRTMG-K¶
ra_lw_physics=14
An improved version of the RRTMG scheme.
Baek, 2017
Note
To use this option, WRF must be built with the configuration setting -DBUILD_RRTMK = 1 (this can be set by modifying configure.wrf prior to building WRF).
RRTMG-fast¶
ra_lw_physics=24
A fast version of the RRTMG scheme for GPUs and MIC. Beginning in wrv4.2, the following are the default GHG values:
co2vmr=(280. + 90.*exp(0.02*(yr-2000)))*1.e-6
n2ovmr=319.e-9
ch4vmr=1774.e-9
cfc11=0.251e-9
cfc12=0.538e-9
GFDL¶
ra_lw_physics=99
This is the Eta operational radiation scheme - an older multi-band scheme with carbon dioxide, ozone and microphysics effects
Fels and Schwarzkopf, 1981
Shortwave Radiation Schemes¶
WRF shortwave radiation schemes:
Compute clear-sky and cloudy solar fluxes
Include annual and diurnal solar cycles
Consider downward and upward (reflected) fluxes (with the exception of the Dudhia (option 1) scheme, which only considers downward flux)
Have a primarily warming effect in clear sky
Are an important component of surface energy balance
In the table below, microphysics interactions represent mixing ratios of:
c : cloud water
r : rain water
i : cloud ice
s : snow
g : graupel
Scheme |
Option |
Microphysics Interaction |
Cloud Fraction |
GHG |
---|---|---|---|---|
Dudhia |
1 |
Qc Qr Qi Qs Qg |
1/0 |
none |
Goddard |
2 |
Qc Qi |
1/0 |
5 profiles |
CAM |
3 |
Qc Qi Qs |
Max-rand overlap |
lat/month |
RRTMG |
4 |
Qc Qr Qi Qs |
Max-rand overlap |
1 profile or lat/month |
New Goddard |
5 |
Qc Qr Qi Qs Qg |
Max-rand |
5 profiles |
FLG |
7 |
Qc Qr Qi Qs Qg |
1/0 |
5 profiles |
RRTMG-K |
14 |
Qc Qr Qi Qs |
Max-rand overlap |
1 profile or lat/month |
GFDL |
99 |
Qc Qr Qi Qs |
Max-rand overlap |
lat/month |
The following are WRF’s available shortwave radiation schemes:
Dudhia¶
ra_sw_physics=1
A scheme that uses simple downward integration, allowing for efficient clear-sky absorption and scattering for clouds.
Dudhia, 1989
Goddard¶
ra_sw_physics=2
A two-stream, multi-band scheme that uses cloud effects and climatological ozone
Chou and Suarez, 1994
Matsui et al., 2018
CAM¶
ra_sw_physics=3
A scheme that originates from CESM’s CAM 3 climate model - allows for aerosols and trace gases
Collins et al., 2004
RRTMG¶
ra_sw_physics=4
A scheme that uses the MCICA random cloud overlap method; for major trace gases, use CO2=379e-6 (valid for 2005), N2O=319e-9, CH4=1774e-9. See the time-varying option in Options for Radiation Input. Since wrfv4.2, the CO2 value is determined by the function: CO2(ppm) = 280 + 90 exp (0.02*(year-2000)). This function exhibits approximately 4% error when compared to observed values from the 1920s and 1960s, and about 1% error for years after 2000.
To use the cloud overlap option (available beginning in wrfv4.4), add cldovrlp = 1,2,3,4,or 5. For cldovrlp=4 or 5, use the decorrelation length option idcor=0 or 1. See Namelist Variables for details.
New Goddard¶
ra_sw_physics=5
An efficient scheme with multiple bands that uses climatological ozone. It is designed to run with Goddard microphysics particle radius information. The scheme was updated in WRFv4.1.
Chou and Suarez, 1999
Chou et al., 2001
Fu-Liou-Gu (FLG)¶
ra_sw_physics=7
A scheme with multiple bands, cloud and cloud fraction effects, and uses a climatological ozone profile. This scheme has the ability to allow for aerosols
Gu et al., 2011
Fu and Liou, 1992
RRTMG-K¶
ra_sw_physics=14
An improved version of the RRTMG scheme
Baek, 2017
Note
To use this option, WRF must be built with the configuration setting -DBUILD_RRTMK = 1 (this can be modified in configure.wrf prior to compiling).
RRTMG-fast¶
ra_sw_physics=24
A fast version of RRTMG
Iacono et al., 2008
Held-Suarez¶
ra_sw_physics=31
A temperature relaxation scheme designed for idealized tests only
No publication available
GFDL¶
ra_sw_physics=99
The Eta operational two-stream, multi-band scheme that includes cloud effects and climatological ozone
Fels and Schwarzkopf, 1981
Options for Radiation Input¶
CAM Green House Gases¶
This option incorporates yearly green house gases from 1765 to 2500. Radiation schemes (ra_lw_physics)) CAM (option 3), RRTM (option 1), and RRTMG (option 4) work with this option. Set the following in namelist.input to turn it on:
&physics
ghg_input = 1
ra_lw_physics = 1, 3, or 4
The following files contain different scenarios and are available in the WRF/test/em_real and WRF/run directories:
from IPCC AR5: CAMtr_volume_mixing_ratio.RCP4.5/RCP6/RCP8.5
from IPCC AR4: CAMtr_volume_mixing_ratio.A1B/A2
from IPCC AR6: CAMtr_volume_mixing_ratio.SSP119/SSP126/SSP245/SSP370/SSP585
the default points to the CAMtr_volume_mixing_ratio.SSP245 file
Note
The ghg_input namelist option is not available in versions prior to WRFv4.4. If using an older version, to activate this option, the code must be configured with the -DCLWRFGHG macro (or set in configure.wrf) prior to compiling.
RRTMG Climatological Ozone¶
When using RRTMG radiation (ra_sw(lw)_physics=4), ozone data, adapted from CAM radiation (ra_lw(sw)_physics=3), incorporates latitudinal (2.82 degrees), height, and monthly variations - unlike the default height-only option. Set the following in namelist.input to use this option:
&physics
o3input = 2
ra_sw_physics = 4 (for each domain)
ra_lw_physics = 4 (for each domain)
RRTMG Aerosol Options¶
aer_opt = 1
Aerosol data based on Tegen et al., 1997 are available for use with RRTMG radiation (ra_sw(lw)_physics=4). The data have spatial (5 degrees in longitude and 4 degrees in latitudes) and monthly variations, and include:
organic carbon
black carbon
sulfate
sea salt
dust
stratospheric aerosol (volcanic ash, which is zero)
Set the following in namelist.input to use this option:
&physics
aer_opt = 1
ra_sw_physics = 4 (for each domain)
ra_lw_physics = 4 (for each domain)
aer_opt = 2
When using RRTMG radiation (ra_sw(lw)_physics=4), Aerosol Optical Depth (AOD) - either alone or with the Angstrom exponent, single scattering albedo, and cloud asymmetry can be provided as constant namelist values or as 2D input fields (via auxiliary input stream 15), with an option to specify aerosol type. To activate this option, set the following in namelist.input:
&physics
aer_opt = 2
ra_sw_physics = 4 or 5 (for each domain)
ra_lw_physics = 4 or 5 (for each domain)
aer_opt = 3
When using RRTMG radiation (ra_sw(lw)_physics=4) and Thompson aerosol-aware microphysics (mp_physics=28), climatological water- and ice-friendly aerosols can be used. To activate this option, use the following namelist.input settings:
&physics
aer_opt = 2
ra_sw_physics = 4 or 5 (for each domain)
ra_lw_physics = 4 or 5 (for each domain)
mp_physic = 28 (for each domain)
RRTMG Effective Cloud water, Ice and Snow Radii¶
When using RRTMG radiation (ra_sw(lw)_physics=4), effective cloud water, ice, and snow radii data are available with the following namelist.input setting:
&physics
use_mp_re = 1
ra_sw_physics = 4 or 5 (for each domain)
ra_lw_physics = 4 or 5 (for each domain)
These data originate from the following microphysics schemes:
Thompson (mp_physics=8)
WSM (mp_physics=3,4,6,24)
WDM (mp_physics=14,16,26)
Goddard 4-ice (mp_physics=7)
NSSL (mp_physics=17,18,19,21,22)
P3 (mp_physics=50-53)
Clouds and Cloud Fraction Options¶
Longwave Radiation and Clouds¶
Every radiation scheme interacts with model-resolved cloud fields, which allows ice and water clouds and precipitating species, with the following nuances:
Some microphysics options pass their own particle sizes (cloud droplets, ice and snow) to RRTMG radiation.
Other combinations only use mass information from microphysics schemes, and assume effective sizes in the radiation scheme.
Rain and graupel effects are smaller than cloud and snow, and are not often explicitly considered.
Clouds have a significant effect on infrared radiation (IR) across all wavelengths. Considered “grey bodies,” they are nearly opaque to it.
Shortwave Radiation and Clouds¶
Considerations for shortwave radiation schemes are similar to those of longwave schemes (above). There are interactions with model-resolved clouds, and, in some cases, cumulus schemes. There are fraction and overlap assumptions, as well as cloud albedo reflection. Surface albedo reflection is based on the land-surface type and snow cover.
Cloud Fraction for Microphysics Clouds¶
icloud=1 : Xu and Randall method; fraction is only < 1 for small cloud amounts, 0 for no resolved cloud
icloud=2 : Simple 0 or 1 method with small resolved cloud threshold
icloud=3 : Thompson option (RH dependent); 1 > Fraction > 0 for high RH and no resolved clouds
Cloud Fraction for Unresolved Convective Clouds¶
cu_rad_feedback=.true. : only works for Kain Fritsch (cu_physics=1), Grell Freitas (cu_physics=3), Grell 3 (cu_physics=5), Grell-Devenyi (cu_physics=93) cumulus options.
ZM separately provides cloud fraction to radiation
Radiation Time Step¶
The namelist parameter radt (in the &physics record) controls the radiation time step. Consider the following when setting radt.
Radiation is too expensive to call every step
Frequency should resolve cloud-cover changes with time
radt should be set to about one minute per km grid size (of the innermost domain) (e.g., radt=10 for \(dx=10000\) - or 10 km).
When using feedback=1, it is recommended to set radt to the same value for each domain.
Planetary Boundary Layer Physics¶

WRF Planetary Boundary Layer (PBL) Schemes
WRF physics schemes that distribute surface fluxes with boundary layer eddy fluxes, allow for PBL growth by entrainment, and vertical mixing above the boundary layer.
There are two classes of PBL schemes:
Turbulent kinetic energy prediction schemes
The following WRF PBL schemes fall under this class:
MYJ (bl_pbl_physics=2)
MYNN (bl_pbl_physics=5,6)
QNSE-EDMF (bl_pbl_physics=4)
BouLac (bl_pbl_physics=8)
CAM UW (bl_pbl_physics=9)
TEMF (bl_pbl_physics=10)
QNSE-EDMF, MYNN, and TEMF schemes also include non-local mass-flux terms.
Diagnostic non-local schemes
The following WRF PBL schemes fall under this class:
YSU (bl_pbl_physics=1)
GFS (bl_pbl_physics=3)
ACM2 (bl_pbl_physics=7)
MRF (bl_pbl_physics=99)
Note the following regarding WRF PBL schemes:
Due to turbulence, all PBL schemes perform vertical diffusion above the PBL.
PBL schemes can be used for most grid sizes when surface fluxes are present; however, this assumption breaks down at grid size \(dx << 1 km\), when 3-D diffusion should be used instead of a PBL scheme (coupled to surface physics). This works best when \(dx\) and \(dz\) are comparable.
The lowest level should be located in the surface layer (0.1h) for correct surface (2m, 10m) diagnostic interpolation.
With ACM2, GFS, and MRF PBL schemes, the lowest full level should be .99 or .995 (not too close to 1).
TKE schemes and YSU can use thinner surface layers.
PBL schemes assume PBL eddies are not resolved.

See also
See the WRF Tutorial presentation on PBLi for additional details.
PBL Scheme Options¶
Scheme |
Option |
Works With |
Prognostic Variables |
Diagnostic Variables |
Cloud Mixing |
---|---|---|---|---|---|
YSU |
1 |
1 91 |
none |
exch_h |
QC QI |
MYJ |
2 |
2 |
4 |
EL_PBL exch_h |
QC QI |
QNSE-EDMF |
4 |
4 |
TKE_PBL |
EL_PBL exch_h exch_m |
QC QI |
MYNN2 |
5 |
1 2 5 91 |
QKE |
Tsq Qsq Cov exch_h exch_m |
QC |
MYNN3 |
6 |
1 2 5 91 |
QKE Tsq Qsq Cov |
exch_h exch_m |
QC |
ACM2 |
7 |
1 7 91 |
QC QI |
||
BouLac |
8 |
1 2 91 |
TKE_PBL |
EL_PBL exch_h exch_m |
QC |
UW |
9 |
1 2 91 |
TKE_PBL |
exch_h exch_m |
QC |
TEMF |
10 |
10 |
TE_TEMF |
*_temf |
QC QI |
Shin-Hong |
11 |
1 91 |
exch_h |
QC QI |
|
GBM |
12 |
1 91 |
TKE_PBL |
EL_PBL exch_h exch_m |
QC QI |
EEPS |
16 |
1 5 91 |
PEK_PBL PEP_PBL |
exch_h exch_m |
QC QI |
KEPS |
17 |
1 2 |
TPE_PBL DISS_PBL TKE_PBL |
exch_h exch_m |
QC |
MRF |
99 |
1 91 |
QC QI |
PBL Scheme Details and References¶
Yonsei University (YSU)¶
bl_pbl_physics=1
A non-local-K scheme with an explicit entrainment layer and parabolic K profile in the unstable mixed layer. This option includes top-down mixing for turbulence, driven by cloud-top radiative cooling (this is separate from bottom-up surface-flux-driven mixing).
Hong et al., 2006
Additional options specific for use with YSU:
topo_wind : =1 - applies a topographic correction to surface winds. The correction accounts for increased drag due to sub-grid topography and enhanced flow at hill tops (Jimenez and Dudhia, 2012); =2 - a simpler terrain variance-related correction
ysu_topdown_pblmix=1 : applies top-down mixing driven by radiative cooling (Wilson and Fovell, 2018)
Mellor-Yamada-Janjic (MYJ)¶
bl_pbl_physics=2
Eta operational scheme - a one-dimensional prognostic turbulent kinetic energy scheme with local vertical mixing
Janjic, 1994
Mesinger, 1993
Quasi-Normal Scale Elimination (QNSE-EDMF)¶
bl_pbl_physics=4
A TKE-prediction option that incorporates a theory for stably-stratified regions. For the daytime, an eddy diffusivity mass-flux method with shallow convection (mfshconv=1) is used. It includes shallow convection using a mass-flux approach through the entire cloud-topped boundary layer
Sukoriansky et al., 2005
Mellor-Yamada Nakanishi and Niino Level 2.5 (MYNN2)¶
bl_pbl_physics=5
Predicts sub-grid TKE terms; includes shallow convection using a mass-flux approach through the entire cloud-topped boundary layer; includes top-down mixing for turbulence driven by cloud-top radiative cooling, which is separate from bottom-up surface-flux-driven mixing
Nakanishi and Niino, 2006
Nakanishi and Niino, 2009
Olson et al., 2019
Additional options specific for use with MYNN:
icloud_bl=1 : option to couple MYNN subgrid-scale clouds with radiation
bl_mynn_cloudpdf : =1 - Kuwano et al., 2010 ; =2 - Chaboureau and Bechtold, 2002 (with modifications; this is the default setting)
bl_mynn_cloudmix=1 : mixing cloud water and ice (qnc and qni are mixed when scalar_pblmix=1)
bl_mynn_edmf=1 : activate mass-flux in MYNN
bl_mynn_mixlength : =1 is from RAP/HRRR; =2 is from blending
Mellor-Yamada Nakanishi and Niino Level 3 (MYNN3)¶
bl_pbl_physics=6
Predicts TKE and other second-moment terms
Nakanishi and Niino, 2006
Nakanishi and Niino, 2009
Olson et al., 2019
Note
This option is only available in versions, up through WRFv4.4.2. See the MYNN Closure option if using WRFv4.5+.
MYNN Closure¶
bl_mynn_closure
= 2.5 : level 2.5
= 2.6 : level 2.6
= 3.0 : level 3.0
ACM2¶
bl_pbl_physics=7
Asymmetric Convective Model with non-local upward mixing and local downward mixing
Pleim, 2007
BouLac¶
bl_pbl_physics=8
Bougeault-Lacarrère PBL; a TKE-prediction option; for use with the BEP urban model (sf_urban_physics=2)
Bougeault, 1989
UW¶
bl_pbl_physics=9
A TKE scheme from the CESM climate model; includes shallow convection using a mass-flux approach from the cloud base; includes topdown mixing for turbulence driven by cloud-top radiative cooling, which is separate from bottom-up surface-flux-driven mixing
Bretherton and Park, 2009
Total Energy - Mass Flux (TEMF)¶
bl_pbl_physics=10
Sub-grid total energy prognostic variable, plus a mass-flux approach for shallow convection throughout the entire cloud-topped boundary layer
Angevine et al., 2010
Shin-Hong¶
bl_pbl_physics=11
Includes scale dependency for vertical transport in the convective PBL; vertical mixing in the stable PBL and free atmosphere follows Yonsei University (YSU); this scheme includes diagnosed TKE and mixing length output
Shin and Hong, 2015
Grenier-Bretherton-McCaa (GBM)¶
bl_pbl_physics=12
A TKE scheme that has been tested in cloud-topped PBL cases, and includes shallow convection using a mass-flux approach from the cloud base
Grenier and Bretherton, 2001
TKE (E)-TKE dissipation rate (epsilon) (EEPS)¶
bl_pbl_physics=16
This scheme predicts and advects both TKE and the TKE dissipation rate
No publication available
Note
This option only works with sf_sfclay_physics=1,5, or 91.
K-epsilon-theta2 (KEPS)¶
bl_pbl_physics=17
This scheme includes two additional prognostic equations for dissipation rate and temperature variance.
Zonato et al., 2022
MRF¶
bl_pbl_physics=99
This is an older version of Yonsei University (YSU) (bl_pbl_physics=1) with implicit treatment of the entrainment layer as part of a non-local-K mixed layer
Hong and Pan, 1996
Additional PBL Options¶
LES PBL¶
Settings for a large-eddy-simulation (LES) boundary layer:
&physics
bl_pbl_physic = 0 *(for each domain)*
isfflx = 1
sf_sfclay_physics = *any option, except 0* *(for each domain)*
sf_surface_physics = *any option, except 0* *(for each domain)*
diff_opt = 2 *(for each domain)*
km_opt = 2 or 3 *(for each domain)*
Diffusion is optional for vertical mixing.
isfflx=0 or 2 can be used alternatively for idealized LES cases.
Use \(dx \approx dz\), especially in the boundary layer, and avoid stretching to very large \(dz/dx\) aspect ratios at upper levels. This works better with continuous stretching to the top, instead of a fixed upper-level \(dz\) when \(dz >> dx\).
SMS-3DTKE¶
3D TKE subgrid mixing scheme that self-adapts to the grid size between the large-eddy simulation (LES) and mesoscale limits. This option is available with WRFv4.2+ and is activated with the following settings:
&physics
bl_pbl_physic = 0 *(for each domain)*
km_opt = 5 *(for each domain)*
diff_opt = 2 *(for each domain)*
sf_sfclay_physics = 1, 5, or 91 *(for each domain)*
See Zhang et al., 2018 for details.
Gravity Wave Drag¶
gwd_opt
An option to represent sub-grid orographic gravity-wave vertical momentum transport; can be used for all grid sizes with appropriate geogrid input fields
=1 : (default); subgrid topography effects gravity wave drag and low-level flow blocking; recommended for all grid sizes; input wind is rotated to the Earth coordinate, and output is adjusted back to the projection domain, enabling use with all WRF-supported map projections; to apply this option, appropriate input fields from geogrid must be used; See Gravity Wave Drag Scheme Static Data for details.
=3 : gravity wave drag, blocking, small-scale gravity drag and turbulent orographic form drag; similar to option 1, with the following additional subgrid-scale sources of orographic drag:
Small-scale GWD (Tsiringakis et al., 2017), which represents gravity wave propagation and breaking in and above the stable boundary layer
Turbulent orographic form drag (Beljaars et al., 2004)
Both are applicable down to a grid size of 1 km. Large-scale GWD and low-level flow blocking from gwd_opt=1 are adjusted for horizontal grid resolution. More diagnostic fields from the scheme can be output by setting namelist option gwd_diags=1 in the &dynamics record. New GWD input fields are required from WPS.
Fog¶
grav_settling=2
Gravitational settling of fog/cloud droplets
PBL and Land Surface Time Step¶
The namelist parameter bldt (in the &physics record) controls the PBL time step in minutes between boundary layer and land-surface model calls. The default value of 0 (every step) is reasonable for all schemes, except the CLM land-surface scheme (sf_surface_physics = 5), which is expensive and bldt may need to be increased.
Model Grid Spacing¶

In the above image:
WRF PBL schemes are designed for \(grid resolution >> I\)
LES schemes are designed for \(grid resolution << I\)
With coarse grid spacing, eddies are sub-grid, and 1-D column schemes handle sub-grid vertical fluxes. For fine grid spacing, major eddies are resolved, and 3-D turbulence schemes handle sub-grid mixing.
The remaining sub-kilometer grid-spacing is a “grey-zone” with imperfect PBL and LES assumptions. The following scale-aware schemes are available for this zone:
Shin-Hong PBL based on Yonsei University (YSU), designed for sub-kilometer transition scales (200 m – 1 km); nonlocal mass-flux; the \(Kv\) term is reduced in strength as grid size decreases and resolved mixing increases
3d TKE option (km_opt=5) (available in v4.2+); becomes 3-D LES at fine scales; adds scale-dependent Shin-Hong nonlocal mass flux and implicit vertical diffusion at coarse grid sizes
Other schemes may work in this range but resolved/sub-grid energy fractions are not correctly partitioned.
LES is preferable for grid sizes up to about 100 m.
Turbulence and Diffusion¶
The diff_opt namelist option (in &dynamics) specifies the method used for turbulence and mixing. When diffusion is used with a PBL scheme, vertical diffusion is deactivated, therefore diff_opt only affects horizontal diffusion.
diff_opt=0 : no turbulence or explicit spatial numerical filters
diff_opt=1 : (default); evaluates the 2nd-order diffusion term on coordinate surfaces; uses the constant vertical diffusion coefficient (kvdif) unless a PBL option is used; do not use with calculated diffusion coefficient options (km_opt=2,3); can be used with PBL schemes that include internal vertical diffusion; horizontal diffusion acts along model levels - a simple numerical method with only neighboring points on the same model level
diff_opt=2 : evaluates mixing terms in physical space (stress form - \(x,y,z\)); strictly horizontal and better for complex terrain - avoids diffusion up and down slopes included in diff_opt=1; horizontal diffusion acts strictly on horizontal gradients; the numerical method includes a vertical correction term, using more grid points; for stability, diffusion strength is reduced in steep coordinate slopes (\(dz \approx dx\))
Recommended Diffusion Options¶
Real-data case with PBL option on
diff_opt=2
km_opt=4
Less diffusive in complex terrain (while diff_opt=1 diffuses along slopes)
These options compliment the PBL scheme vertical diffusion
High-resolution real-data cases (~100m grid)
No PBL scheme
diff_opt=2
TKE (km_opt=2) or Smagorinsky scheme (km_opt=3)
Idealized cloud-resolving modeling (\(dx\) = 1-3 km ; smooth or no topography, no surface heat fluxes)
diff_opt=2
km_opt=2 or 3
Surface Physics¶


WRF surface physics consist of surface layer (sfclay) schemes and land surface model (LSM) schemes.
WRF Surface Layer (sfclay) Schemes
WRF physics schemes that determine surface layer diagnostics, including exchange and transfer coefficients, and determine soil temperature, moisture, snow prediction and sea-ice temperature. They provide heat and moisture exchange coefficients to the land surface model (LSM).
WRF Land Surface Model (LSM) Schemes
WRF physics schemes that provide land-surface fluxes of heat and moisture to the planetary boundary layer (PBL).
See also
See the WRF Tutorial presentation on surface physics for additional details.
Surface Layer Schemes¶

The surface layer has a constant flux layer of about 0.1 x PBL height (~100 m). The lowest WRF model level is found within this layer (typically 10-50 m).
The WRF surface layer scheme is determined by the namelist setting sf_sfclay_physics (in the &physics namelist record). Some key notes about WRF sfclay schemes are:
They use similarity theory to determine exchange coefficients and diagnostics of 2m temperature, 2m qvapor, and 10m winds.
They provide exchange coefficients to land-surface models (LSMs).
They provide friction velocity to the PBL scheme.
They provide surface fluxes over water points.
Schemes have variations in stability functions and roughness lengths.
Surface Layer Scheme Details and References¶
Revised MM5¶
sf_sfclay_physics=1
Removes limits and uses updated stability functions; over the ocean, the COARE 3 forumula (Fairall et al., 2003) is used for thermal and moisture roughness lengths (or heat and moisture exchange coefficients)
Jimenez et al., 2012
Eta Similarity¶
sf_sfclay_physics=2
A scheme used in Eta model, based on Monin-Obukhov with Zilitinkevich thermal roughness length and standard similarity functions from look-up tables
Monin and Obukhov, 1954
Janjic, 1994
Janjic, 1996
Janjic, 2001
QNSE¶
sf_sfclay_physics=4
Quasi-Normal Scale Elimination PBL scheme’s surface layer option
No publication available
MYNN¶
sf_sfclay_physics=5
Nakanishi and Niino PBL’s surface layer scheme
Olson et al, 2021
Pleim-Xiu¶
sf_sfclay_physics=7
Pleim, 2006
Total Energy - Mass Flux (TEMF)¶
sf_sfclay_physics=10
Angevine et al., 2010
MM5 Similarity¶
sf_sfclay_physics=91
A scheme based on Monin-Obukhov, with Carslon-Boland viscous sub-layer and standard similarity functions from look-up tables; over the ocean, the COARE 3 forumula (Fairall et al., 2003) is used for thermal and moisture roughness lengths (or heat and moisture exchange coefficients)
Paulson, 1970
Dyer and Hicks, 1970
Webb, 1970
Belijaars, 1994
Zhang and Anthes, 1982
Land Surface Model¶

WRF LSM schemes are driven by surface energy and water fluxes. They predict soil temperature and soil moisture in 3 or 4 layers, depending on the scheme, as well as snow water equivalent on the ground.
Vegetation and Soil¶
LSMs consider the effects of vegetation and soil components, such as vegetation fraction, vegetation categories (e.g., cropland, forest types, etc.), and soil categories (e.g., sandy, clay, etc.). Below are some key notes:
Processes include evapotranspiration, root zone, and leaf effects.
Vegetation fraction varies seasonally.
Soil categories are considered for drainage and thermal conductivity.
Snow Cover¶
LSMs include fractional snow cover and predict snow water equivalent development based on precipitation, sublimation, melting, and run-off. The number of layers is dependent on the scheme:
Single-layer snow (Noah - sf_surface_physics=2, PX - sf_surface_physics=7)
Multi-layer snow (RUC - sf_surface_physics=3, NoahMP - sf_surface_physics=4, CLM4 - sf_surface_physics=5, SSiB - sf_surface_physics=8)
The 5-layer option - sf_surface_physics=2 - has no snow prediction
Note
Frozen soil water is also predicted by the Noah, NoahMP, RUC, and CLM4 schemes.
Urban Effects¶
For larger-scale studies, the LSM urban category is usually sufficient. Alternatively, urban models are available for use with either the Noah (sf_surface_physics=2) or NoahMP (sf_surface_physics=4) LSM scheme by setting sf_urban_physics in the &physics namelist record to one of the following options:
=1 : Urban Canopy Model (UCM); single layer; The following options are available when sf_urban_physics=1
slucm_distributed_drag : An option to use spatially-varying 2-D urban zero-plane displacement, momentum roughness length, and frontal area index. This option requires SLUCM static input for the WPS/geogrid process
distributed_ahe_opt : An option to determine the method used for anthropogenic surface heat flux. An additional input to the wrfinput file is required.
=0 : do not use anthropogenic surface heat flux from the input data
=1 : (default) add to thefirst level temperature tendency
=2 : add to the surface sensible heat flux
=2 : Building Environment Parameterization (BEP); multi-layer; only works with YSU, MYJ and BouLac PBL schemes (bl_pbl_physics= 1, 2, and 8)
=3 : Building Energy Model (BEM); adds heating and air-conditioning to BEP; only works with YSU, MYJ and BouLac PBL schemes (bl_pbl_physics= 1, 2, and 8)
Note
NUDAPT detailed map data is available for use in WPS, and includes data for 40+ U.S. cities.
WRFv4.3+ code includes a capability to use local climate zones for all three urban applications (see the README file for details)
LSM Tables¶
LSM tables, found in WRF/test/em_real and WRF/run, are customizable text files with predefined categories.
Table |
LSM scheme that uses the table |
---|---|
VEGPARM.TBL |
Noah and RUC, for vegetation categories (albedo, roughness length, emissivity, vegetation properties) |
MPTABLE.TBL |
NoahMP |
SOILPARM.TBL |
Noah and RUC, for soil properties |
LANDUSE.TBL |
5-layer model (SLAB) |
URBPARM.TBL |
urban models |
Initializing LSMs¶
All LSMs (except the SLAB option) require the following additional fields for initialization:
Soil temperature
Soil moisture
Snow liquid equivalent
These fields are available in the first-guess input files processed in WPS. They originate from “offline” operational analysis or reanalysis modeling systems driven by observations for rainfall, radiation, surface temperature, humidity, and wind.
The following are model-derived data sets for Noah and RUC LSMs that correspond to WRF levels:
Eta/GFS/AGRMET/NNRP for Noah (older data have limited soil levels)
RUC for RUC (just North America; limited availability)
Note
When using ECMWF/ERA soil analyses, during real.exe mesoscale landuse resolution can cause inconsistency in elevation, soil type, and vegetation. Soil temperature adjustments occur during real.exe, and addresses elevation differences between the dataset and model elevations (using SOILHGT). Inconsistency leads to spin-up, as temperature and moisture adjustments occur at the beginning of simulation. This can be avoided by running an offline model on the same grid (e.g. HRLDAS for Noah), but soil moisture spin up may take months. Cycling the land state between forecasts also helps, but may propagate errors (e.g in rainfall effect on soil moisture).
LSM Scheme Details and References¶
5-layer thermal diffusion (SLAB)¶
sf_surface_physics = 1
A five-layer scheme that only considers soil temperature
Dudhia, 1996
Noah¶
sf_surface_physics = 2
The Unified NCEP/NCAR/AFWA four-layer scheme for soil temperature and moisture; includes fractional snow cover and frozen soil physics
Tewari et al., 2004
Activate sub-tiling with sf_surface_mosaic=1 in the &physics namelist record. The mosaic_cat namelist option defines the number of tiles per grid box (default : 3).
RUC¶
sf_surface_physics = 3
This model calculates energy and moisture budgets using a layer approach. Atmospheric and soil fluxes, computed at the middle of the first atmospheric layer and the top soil layer respectively, modify heat and moisture storage in the ground surface layer. The RUC LSM utilizes 9 soil levels, with higher resolution near the atmosphere interface.
Note
Initializing from a low-resolution surface model, such as Noah LSM, can lead to overly moist top levels, causing moist/cold biases. The solution is to cycle soil moisture for several days, allowing it to spin up and align with the RUC LSM’s vertical structure.
The RUC LSM models soil moisture as a prognostic variable - volumetric soil moisture content, minus residual soil moisture, which does not contribute to transport. It incorporates soil freezing and thawing processes and can utilize explicit mixed-phase precipitation from cloud microphysics schemes. For sea ice, the model solves for heat diffusion, allowing for evolving snow cover. During the warm season, the RUC LSM adjusts soil moisture in cropland areas to account for irrigation.
On soil, snow accumulates in up to two layers, depending on its depth (ref S16). Thin layers combine with the topsoil layer to prevent excessive night time radiative cooling. If the snow water equivalent is below 3 cm, grid cells can be partially snow-covered, with surface parameters like roughness length and albedo calculated as a weighted average of snow-covered and snow-free areas.
The energy budget employs an iterative snow melting algorithm. Melted water may partially refreeze within the snow layer; the rest percolates through the snowpack, infiltrates the soil, forming surface runoff. Snow density evolves based on snow temperature, depth, and compaction. Snow albedo, initialized from the given vegetation type’s maximum albedo, can be adjusted according to snow temperature and snow fraction. To better represent accumulated snow on the ground, the RUC LSM includes an estimation of frozen precipitation density.
The RUC LSM includes refined interception of liquid or frozen precipitation by the canopy, and a “mosaic” approach for patchy snow, which separately treats energy and moisture budgets for snow-covered and snow-free portions of each grid cell, aggregating the solutions at the end of each time step.
The following data sets are required to initialize the RUC LSM:
High-resolution soil and land-use types
Climatological albedo for snow-free areas
Spatial distribution of maximum surface albedo in the presence of snow cover
Grid cell vegetation-type fraction - for sub-grid-scale heterogeneity in surface parameter computation
Grid cell soil-type fraction
Climatological greenness fraction
Climatological leaf area index
Climatological mean temperature at the bottom of soil domain
Real-time sea-ice concentration
Real-time snow cover to correct cycled-in RAP and HRRR snow fields
Recommended namelist options:
sf_surface_physics=3
num_soil_layers=9
usemonalb=.true. ; uses monthly albedo fields from geogrid instead of table values
rdlai2d=.true. ; uses monthly LAI data from geogrid, which is included in the wrflowinp file if sst_update=1
mosaic_lu=1
mosaic_soil=1
Benjamin et al., 2004
Smirnova et al., 2016
Noah-MP¶
sf_surface_physics = 4
Uses multiple options for key land-atmosphere interaction processes, as well as the following:
Contains a separate vegetation canopy, defined by its top and bottom, with leaf physical and radiometric properties utilized in a two-stream canopy radiation transfer scheme that accounts for shading effects
Contains a multi-layer snow pack with liquid water storage, melt/refreeze capability, and a snow-interception model describing loading/unloading, melt/refreeze, and sublimation of the canopy-intercepted snow
Multiple options are available for surface water infiltration and runoff, and groundwater transfer and storage, including water table depth to an unconfined aquifer
Horizontal and vertical vegetation density can be prescribed or predicted using prognostic photosynthesis and dynamic vegetation models that allocate carbon to vegetation (leaf, stem, wood and root) and soil carbon pools (fast and slow)
Niu et al., 2011
Yang et al., 2011
Noah-MP Technical Note (He et al., 2023)
Community Land Model Version 4 (CLM4)¶
sf_surface_physics = 5
Contains sophisticated treatment of biogeophysics, hydrology, biogeochemistry, and dynamic vegetation. Each grid cell’s land surface is defined by five sub-grid land cover types: glacier, lake, wetland, urban, and vegetated. The vegetated sub-grid consists of up to 4 plant functional types (PFTs) that differ in physiology and structure. WRF input land cover types are translated into the CLM4 PFTs through a look-up table. The CLM4 vertical structure includes a single-layer vegetation canopy, a five-layer snowpack, and a ten-layer soil column.
Oleson et al., 2010
Lawrence et al., 2011
Note
An earlier version of CLM has been quantitatively evaluated within WRF; referenced in the following:
Jin and Wen, 2012
Lu and Kueppers, 2012
Subin et al., 2011
Pleim-Xiu¶
sf_surface_physics = 7
A two-layer scheme based on the ISBA model (Noilhan and Planton, 1989) that includes vegetation and sub-grid tiling, and provides realistic ground temperature, soil moisture, and surface sensible and latent heat fluxes in mesoscale models. It includes a 2-layer force-restore soil temperature and moisture model (1 cm thick top layer, 99 cm bottom layer). It derives grid aggregate vegetation and soil parameters from fractional coverage of land use categories and soil texture types. Two indirect nudging schemes correct 2-m air temperature and moisture biases by adjusting soil moisture (Pleim and Xiu, 2003) and deep soil temperature (Pleim and Gilliam, 2009).
The PX LSM is primarily designed for retrospective simulations that utilize surface-based observations to guide indirect soil nudging. While soil nudging can be disabled (pxlsm_soil_nudge namelist ption in &fdda), this mode is not well-tested. Gilliam and Pleim, 2010 detail its WRF implementation and typical configurations. To activate soil nudging use the OBSGRID utility to produce a wrfsfdda_d0* surface nudging file, which the PX LSM uses for its 2-m temperature and mixing ratio re-analyses to nudge deep soil moisture and temperature. For forecast mode with soil nudging, OBSGRID can generate wrfsfdda_d01* files using forecasted 2-m temperature and mixing ratio with empty observation files, but results depend on the forecast model.
Note
See a detailed description of the PX LSM, including pros/cons, best practices, and recent improvements.
Additional References:
Pleim and Xiu, 1995
Xiu et al., 2001
Simplified Simple Biosphere (SSiB)¶
sf_surface_physics=8
This is the third generation of the Simplified Simple Biosphere Model, and is developed for land/atmosphere interaction studies within climate models. It calculates aerodynamic resistance values in terms of vegetation properties, ground conditions and the bulk Richardson number per the modified Monin-bukhov similarity theory. SSiB-3 includes three snow layers to realistically simulate snow processes such as destructive metamorphism, densification due to snow load, and snow melting, which makes it a strong candidate for cold season studies.
To use this option, ra_lw_physics and ra_sw_physics should be set to either 1, 3, or 4. The second full model level should be set to no larger than 0.982 so that its height is higher than vegetation height.
Xue et al., 1991
Sun and Xue, 2001
PBL and Land Surface Time Step (bldt)¶
See PBL and Land Surface Time Step in the PBL physics section.
Tropical Cyclone Options¶
The following namelist parameters are specific to tropical cyclone simulations and should be added to the &physics namelist record.
Ocean Mixed Layer Model¶
sf_ocean_physics=1
Ocean Mixed Layer Model; 1-d slab ocean mixed layer (specified initial depth); includes wind-driven ocean mixing for SST cooling feedback
Pollard et al., 1973
3d PWP Ocean¶
sf_ocean_physics=2
3-d multi-layer (~100) ocean, salinity effects; fixed depth
Price, 1981
Price et al., 1994
Lee and Chen, 2012
Alternative surface-layer option for high-wind ocean¶
surface (isftcflx=1,2)
Modifies the Charnock relation to decrease surface friction for high winds (lower \(Cd\)); modifies surface enthalpy (\(Ck\), heat/moisture) either with constant \(z0q\) (isftcflx=1) or Garratt formulation (isftcflx=2); must be used with sf_sfclay_physics=1
Fractional Sea Ice¶
The fractional sea ice option (fractional_seaice=1) includes input sea-ice fraction data that partitions land and water fluxes within a grid box, treating sea-ice as a fractional field. This option requires fractional sea-ice input using GFS or the National Snow and Ice Data Center data; use XICE for the Vtable entry instead of SEAICE; this option works with sf_sfclay_physics = 1, 2, 5, and 7, and sf_surface_physics = 2, 3, and 7.
Sub-grid Mosaic Option¶
Without an additional sub-grid mosaic option, WRF defaults to using a single dominant vegetation and soil type per grid cell. However, additional mosaic options are available to use with the following schemes:
Noah |
use sf_surface_mosaic=1 to allow for multiple categories within a grid cell |
RUC |
use mosaic_lu=1 and mosaic_soil=1 to allow for multiple categories within a grid cell |
Pleim-Xu |
additionally averages properties of sub-grid categories |
SST Update¶
To use the Sea Surface Temperature (SST) update option, set sst_update=1 in the &physics namelist record. This option reads a lower boundary file periodically to update SST (as opposed to a fixed-time SST).
Notes about this option:
It is recommended to use for simulations lasting ~5 or more days
A wrflowinp_d0* file is created by real.exe
Sea-ice can be updated, as well
Vegetation fraction update is included, allowing seasonal change in albedo, emissivity, and roughness length if using the Noah LSM
Set usemonalb=.true. to include monthly albedo input
Regional Climate Options¶
- tmn_update=1
Updates deep-soil temperature for multi-year future-climate runs
- sst_skin=1
Adds a diurnal cycle to sea-surface temperature
- output_diagnostics=1
Ability to output max/min/mean/std of surface fields in a specified period (e.g. daily)
- bucket_mm and bucket_J
Provides a more accurate way to accumulate water and energy for long-run budgets (see Accumulation Budgets)
Accumulation Budgets¶
Some outputs fields are accumulated from the start of the simulation. These include rainfall totals (mm or kg/m2) RAINC, RAINNC, and radiation totals (J/m2), ACLWUPT, ACSWDNB, etc. An average over any time period is determined by the output at the end, minus output at the beginning, divided by the time interval. For regional climate simulations (months), because of “32-bit accuracy,” adding small time-step values to accumulated totals causes these variables to be increasingly inaccurate with time because only ~7 significant figures are stored in model output.
To overcome this issue, use bucket_mm and bucket_J to carry the total in integer and remainder parts, e.g.
\(Total\ rain = RAINC + I\_RAINC * bucket\_mm\)
Default bucket value is typical monthly accumulation
bucket_mm = 100 mm
bucket_J = 109 Joules
Lake Model¶
The CLM 4.5 lake model (sf_lake_physics=1) was obtained from the Ommunity Land Model version 4.5 (CLM4), with modifications. It is a one-dimensional mass and energy balance scheme with 20-25 model layers, including up to 5 snow layers on the lake ice, 10 water layers, and 10 soil layers on the lake bottom. The lake scheme is used with actual lake points and lake depth derived from the WPS, and can also be used with user-defined lake points and lake depth in WRF (lake_min_elev and lakedepth_default). The lake scheme is independent of a land surface scheme and therefore can be used with any land surface scheme embedded in WRF.
Gu et al., 2013
Subin et al., 2012
Bathymetry¶
Global bathymetry data are available for most large lakes. They can be obtained from WPS Geographical Static Data Downloads, and are used during the WPS/geogrid process.
WRF-Hydro¶
This capability couples the WRF model with hydrology processes (such as routing and channeling). It requires a separate compile by setting the environment variable WRF_HYDRO. In a c-shell environment, issue:
setenv WRF_HYDRO 1
or in a bash environment, issue
export WRF_HYDRO=1
before configuring and compiling. Once WRF is compiled, copy files from the WRF/hydro/Run directory to the working directory (e.g. WRF/test/em_real). This option requires a special initialization for hydrological data sets. Please refer to the RAL WRF-Hydro Modeling System web page for details.
Using Physics Suites¶
A WRF physics suite is a set of physics options that performs well for a given application and is supported by a sponsoring group. Suites may offer guidance to users in applying WRF, improve understanding of model performance, and facilitate model advancement.
When running WRF, a suite of physics schemes can be chosen by setting physics_suite in the &physics namelist.input record. The physics options covered by this suite specification are:
mp_physics
cu_physics
bl_pbl_physics
sf_sfclay_physics
sf_surface_physics
ra_sw_physics
ra_lw_physics
Two approved physics suites are available:
NSF NCAR Convection-permitting Suite (CONUS)
NSF NCAR Tropical Suite (tropical)
When physics_suite is set in namelist.input, the included physics schemes are assumed and, therefore, the specific schemes (e.g., mp_physics, cu_physics, etc.) do not need to be set. These two suites consist of a combination of physics options that have been thoroughly tested and have shown reasonable results.
A summary of the physics schemes used in the simulation are printed to the WRF output log (e.g., rsl.out.0000).
NSF NCAR Convection-permitting Suite¶
physics_suite=’CONUS’
Real-time forecasting focused on convective weather over the contiguous U.S.
Physics Type |
Scheme Name |
Namelist Option |
---|---|---|
Microphysics |
Thompson |
mp_physics=8 |
Cumulus |
Tiedtke |
cu_physics=6 |
Longwave Radiation |
RRTMG |
ra_lw_physics=4 |
Shortwave Radiation |
RRTMG |
ra_sw_physics=4 |
PBL |
MYJ |
bl_pbl_physics=2 |
Surface Layer |
MYJ |
sf_sfclay_physics=2 |
LSM |
Noah |
sf_surface_physics=2 |
See also
See NSF NCAR Convection-permitting Physics Suite for WRF for additional details.
NSF NCAR Tropical Suite¶
physics_suite=’tropical’
Real-Time forecasting focused on tropical storms and tropical convection
Note
This suite is identical to the “mesoscale_reference” suite in the MPAS model.
Physics Type |
Scheme Name |
Namelist Option |
---|---|---|
Microphysics |
WSM6 |
mp_physics=6 |
Cumulus |
New Tiedtke |
cu_physics=16 |
Longwave Radiation |
RRTMG |
ra_lw_physics=4 |
Shortwave Radiation |
RRTMG |
ra_sw_physics=4 |
PBL |
YSU |
bl_pbl_physics=1 |
Surface Layer |
MM5 |
sf_sfclay_physics=91 |
LSM |
Noah |
sf_surface_physics=2 |
See also
See NSF NCAR Tropical Physics Suite for WRF for additional details.
Overriding Physics Suite Options¶
To override any of the above options, simply add that particular parameter to the namelist.
Example 1¶
Using the CONUS suite with cu_physics turned off for domain 3:
Note
A setting of “-1” means the default setting is used
physics_suite = 'CONUS'
cu_physics = -1, -1, 0
Example 2¶
Using the CONUS suite with a cu_physics option different than the default option for CONUS (cu_physics=6), and with cu_physics turned off for domain 3:
physics_suite = 'CONUS'
cu_physics = 2, 2, 0
Other Specific Applications¶
The following applications are discussed below. Click any link to go directly to that application.
Tropical Storms and Cyclones¶
Options to use for tropical storms and tropical cyclone/typhoon/hurricane applications. All options are set in the &physics record in namelist.input.
sf_ocean_physics=1¶
A simple 1-D ocean mixed layer model following Pollard et al., 1972. The following two additional namelist options are available for use with sf_ocean_physics=1:
oml_hml0 : Specifies the initial ocean mixed layer depth; a setting \(< 0\) initializes with real-time ocean mixed depth; setting the value to \(=0\) initializes with climatological ocean mixed depth. Note that users may also use their own real mixed layer depth data).
oml_gamma : Specifies a deep water temperature lapse rate (\(K/m\)); this option works with all sf_surface_physics options.
sf_ocean_physics=2¶
3D Price-Weller-Pinkel (PWP) ocean model based on Price et al., 1994. This model predicts horizontal advection, pressure gradient force, and mixed layer processes. Only simple initialization via namelist variables ocean_z, ocean_t, and ocean_s is available.
ocean_z : vertical profile of layer depths for ocean (in meters)
ocean_t : vertical profile of ocean temps (K)
ocean_s : vertical profile of salinity
For e.g.,
&physics
sf_ocean_physics = 2
&domains
ocean_z = 5., 15., 25., 35., 45., 55.,
65., 75., 85., 95., 105., 115.,
125., 135., 145., 155., 165., 175.,
185., 195., 210., 230., 250., 270.,
290., 310., 330., 350., 370., 390.
ocean_t = 302.3493, 302.3493, 302.3493, 302.1055, 301.9763, 301.6818,
301.2220, 300.7531, 300.1200, 299.4778, 298.7443, 297.9194,
297.0883, 296.1443, 295.1941, 294.1979, 293.1558, 292.1136,
291.0714, 290.0293, 288.7377, 287.1967, 285.6557, 284.8503,
284.0450, 283.4316, 283.0102, 282.5888, 282.1674, 281.7461
ocean_s = 34.0127, 34.0127, 34.0127, 34.3217, 34.2624, 34.2632,
34.3240, 34.3824, 34.3980, 34.4113, 34.4220, 34.4303,
34.6173, 34.6409, 34.6535, 34.6550, 34.6565, 34.6527,
34.6490, 34.6446, 34.6396, 34.6347, 34.6297, 34.6247,
34.6490, 34.6446, 34.6396, 34.6347, 34.6297, 34.6247
isftcflx¶
Modify surface bulk drag (Donelan) and enthalpy coefficients to be more in line with modern research results for tropical storms and hurricanes. This option includes a dissipative heating term in heat flux. It is only available for sf_sfclay_physics=1. Two options are available for computing enthalpy coefficients:
isftcflx=1 : constant \(Z0q\) for heat and moisture
isftcflx=2 : Garratt formulation, slightly different forms for heat and moisture
Long Simulations¶
tmn_update=1 : update deep soil temperature
sst_skin=1 : calculate skin SST based on Zeng and Beljaars, 2005
bucket_mm=1 : bucket reset value for water equivalent precipitation accumulations (value in mm, -1 =inactive); see Accumulation Budgets for details
bucket_J: bucket reset value for energy accumulations (value in Joules, -1 =inactive); only works with CAM and RRTMG radiation options (ra_lw_physics = 3, 4, 14, 24 and ra_sw_physics = 3, 4, 14, 24); see Accumulation Budgets for details
To drive the WRF model with climate data that does not include a leap year, prior to compiling WRF, edit the configure.wrf file by adding -DNO_LEAP_CALENDAR to the macro “ARCH_LOCAL.”
Windfarm¶
windfarm_opt=1¶
Wind turbine drag parameterization scheme that represents sub-grid effects of specified turbines on wind and TKE fields. The physical charateristics of the wind farm are read-in from a file; use of the manufacturer’s specification is recommeded. An example of the file is provided in WRF/run/wind-turbine-1.tbl. The location of the turbines are read-in from the file windturbines.txt. See README.windturbine in the WRF/doc directory for additional details.
This option only works with 2.5 level MYNN PBL option (bl_pbl_physics=5).
windfarm_opt=2¶
Available for WRFv4.6.0+
Wind farm parameterization scheme (mav scheme) based on Ma et al., 2022. This scheme is similar to option 1 (above), but has the ability to directly account for the individual and overlapping sub-grid wakes of wind turbines within a wind farm. With this option turned on, the following additional namelist options are valid:
windfarm_wake_model : Subgrid-scale wind turbine wake model (default =2)
1 = Jensen model
2 = XA model
3 = GM model (windfarm_method is not used)
4 = Jensen and XA ensemble
5 = Jensen, XA and GM ensemblewindfarm_overlap_method : Wake superposition method for the Jensen and XA wind turbine wake model (default = 4)
1 = linear superposition
2 = squared superposition
3 = modified squared superposition
4 = superposition of the hub-height wind speed (Ma et al., 2022)windfarm_deg : The rotation degree of the wind farm layout; only valid when windfarm_opt=2 and windfarm_ij=1; `See Namelist Variables`_.
Note
When using windfarm_opt=2, the file winturbines-ll.txt must be present in the WRF running directory. The file is formatted with the wind turbine coordinates in the first two columns, followed by the windfarm_id and windturbine_type. For e.g.,
33.0563 -78.6556 2 1
33.0534 -78.6407 2 1
33.0505 -78.6257 2 1
33.0446 -78.6594 2 1
33.0388 -78.6931 2 1
33.0359 -78.6781 2 1
33.0329 -78.6631 2 1
33.0271 -78.6332 2 1
Surface Irrigation Parameterization¶
Available with WRFv4.2+
Three irrigation schemes are available that allow representation of surface irrigation processes within the model, with explicit control over water amount and timing (see Vira et al., 2019 for additional details). The schemes are set in the &physics namelist.input record and represent varying techniques, depending on the water evaporative loss in the application process. The evaporative processes consider loss from:
sf_surf_irr_scheme=1 : surface evapotranspiration; only works with Noah-LSM (sf_surface_physics=2)
sf_surf_irr_scheme=2 : leaves/canopy interception and surface evapotranspiration
sf_surf_irr_scheme=3 : microphysics process, leaves/canopy interception and surface evapotranspiration
With sf_surf_irr_scheme options, the following namelist options are valid:
irr_daily_amount : The daily irrigation water amount applied (\(mm/day\))
irr_start_hour : UTC start hour for irrigation
irr_num_hours : The number of consecutive hours for irrigation
irr_start_julianday : The Julian start day of irrigation (e.g., 135)
irr_end_julianday : The Julian end day of irrigation (e.g., 255)
irr_freq : Irrigation frequency in days; can be set to values >1 to account for irrigation intervals greater than daily, thus water applied in the active day within the irr_freq period is: (\(irr\_daily\_amount * irr\_freq\))
irr_ph : Regulates spatial activation of irrigation (with irr_freq >1), especially determining whether it is activated for all domains on the same day (irr_ph=0); non-zero options are:
irr_ph=1 : Psedo-random activation field as a function of (\(i,j,IRRIGATION\)); ensures repeatability across compilers
irr_ph=2 : Random activation field is created with the fortran RANDOM function; results may depend on the fortran RANDOM_SEED function
Important
When using multiple domains (nests), irrigation schemes should be to to run on only one domain per simulation. This ensures the water application is not repeated and is consistent with the irr_daily_amount calculated. See the Irrigation Scheme GitHub Code Commit for additional details.
The following is an example of irrigation namelist parameters for a two domain case:
sf_surf_irr_scheme = 0, 1
irr_daily_amount = 0, 8
irr_start_hour = 0, 14
irr_num_hours = 0, 2
irr_start_julianday = 0, 121
irr_end_julianday = 0, 170
irr_ph = 0, 0
irr_freq = 0, 3
These settings use the channel method to irrigate the inner domain starting at 14 UTC, for 2 hours, with a value of 8 \(mm/day\). Irrigation starts on Julian day 121 and ends on Julian day 170. Water is applied to the entire inner domain for all irrigated grid-points simultaneously, every 3 days (irr_freq=3). This leads to an hourly irrigation of 12 \(mm/h\) (daily application of 24 \(mm\)), which is then multiplied by the irrigation percentage within the grid-cell (given by the IRRIGATION field processed in WPS).
WRF-Solar¶
WRF-Solar is a specific configuration and augmentation of the basic WRF model specifically designed for specialized numerical forecast products for solar energy applications. For additional information and instructions for use, visit the NSF NCAR Research Applications Laboratory’s WRF-Solar site.
Note
WRF-Solar is managed and supported by the NSF NCAR/RAL group. All support inquiries should be posted to the WRF-Solar forum within the WRF & MPAS-A Support Forum.
MAD-WRF¶
The MAD-WRF model is designed to improve cloud analysis and solar irradiance short-range forecasts. Two options are available to run MAD-WRF:
madwrf_opt = 1 : The initial hydrometeors are advected and diffused with the model dynamics without accounting for any microphysical processes; this should be used with mp_physics=96 and use_mp_re=0 in the &physics namelist.input record
madwrf_opt = 2 : A set of hydrometeor tracers are advected and diffused within the model dynamics. At initial time the tracers are equal to the standard hydrometeors. During the simulation the standard hydrometeors are nudged toward the tracers. namelist.input variable madwrf_dt_nudge sets the temporal period for hydrometeor nudging (in mins), and madwrf_dt_relax sets the relaxation time for hydrometeor nudging (in seconds).
MAD-WRF includes an option to enhance cloud initialization. Use namelist.input option madwrf_cldinit=1 (0) to turn cloud initialization on (off). By default the model enhances cloud analysis based on the analyzed relative humidity.
Cloud initialization can be enhanced by providing additional variables to metgrid via the WPS intermediate format:
Cloud mask (CLDMASK variable): Remove clouds if clear (cldmask=0)
Cloud mask (CLDMASK variable) + brightness temperature (BRTEMP variable) sensitive to hydrometeor content (e.g. GOES-R channel 13):
Remove clouds if clear (cldmask=0)
Reduce/extend cloud top heights to match observations
Add clouds over clear sky regions (cldmask=1)
Cloud top height (CLDTOPZ variable) with 0 values over clear sky regions:
Remove clouds if clear (cldmask=0)
Reduce/extend cloud top heights to match observations
Add clouds over clear sky regions (cldmask=1)
Either 2 or 3 + the cloud base height (CLDBASEZ variable):
Remove clouds if clear (cldmask=0)
Reduce/extend cloud top/base heights to match observations
Note
Missing values in any of these variables should be set to -999.9i.
Physics Sensitivity Options¶
no_mp_heating=1 : turns off latent heating from microphysics; only works with cu_physics=0
icloud=0 : turns off cloud effect on optical depth in shortwave/longwave radiation options 1 and 4; this also controls which cloud fraction method to use for radiation
isfflx=0 : turns off both sensible and latent heat fluxes from the surface. This option works for sf_sfclay_physics = 1, 5, 7, 11
ifsnow=0 : turns off snow effect in sf_surface_physics=1