DISCLAIMERS

The following institutions were instrumental in the development of the WRF-Chem model and its 

documentation.

Department of Commerce/National Oceanic and Atmospheric Administration 

The Cooperative Institute for Research in Environmental Sciences 

The University Corporation for Atmospheric Research (UCAR) 

The National Center for Atmospheric Research (NCAR)

The Max Plank Institute 

The University of Chile

Centro de Previsão de Tempo e Estudos Climáticos

This document does not constitute endorsement of the information, products or services contained herein 

by the contributing institutions previously named or unnamed. For other than authorized activities, the 

contributing institutions do not exercise any editorial control over the information contained herein. Any 

opinions, findings, conclusions or recommendations expressed in this document are those of the authors 

and do not necessarily reflect those of the contributing institutions. In no event shall these institutions, or 

any unmentioned institution associated with WRF-Chem development, be liable for any damages, 

whatsoever, whether direct, indirect, consequential or special, that arise out of or in connection with the 

access, use or performance of WRF-Chem, including infringement actions.

The Weather Research and Forecasting model (WRF hereafter) was developed at the National Center for 

Atmospheric Research (NCAR) that is operated by the University Corporation for Atmospheric Research 

(UCAR). NCAR and UCAR make no proprietary claims, either statutory or otherwise, to this version and 

release of WRF and consider WRF to be in the public domain for use by any person or entity for any 

purpose without any fee or charge. UCAR requests that any WRF user include this notice on any partial or 

full copies of WRF. WRF is provided on an “AS IS” basis and any warranties, either express or implied, 

including but not limited to implied warranties of non-infringement, originality, merchantability and fitness 

for a particular purpose, are disclaimed. In no event shall UCAR be liable for any damages, whatsoever, 

whether direct, indirect, consequential or special, which arise out of or in connection with the access, use or 

performance of WRF, including infringement actions.
1

WRF-Chem Version 3.7 User’s Guide 

Table of Contents

1.1 WRF-Chem Introduction .............................................................................................. 3

1.2 WRF-Chem software .................................................................................................... 5

1.3 Possible applications of the current modeling system.................................................. 5

1.4 The WRF-Chem modeling system overview................................................................ 5

2.1 Software Installation Introduction ................................................................................ 8

2.2 Building the WRF-chemistry code ............................................................................... 9

2.2.1 Getting the code ..................................................................................................... 9

2.2.2 UNIX environment settings for WRF-Chem......................................................... 9

2.2.3 Configuring the model and compiling the code................................................... 10

3.1 Emissions Generation Overview.............................................................................. 12

3.2 Generating Dust Emissions...................................................................................... 12

4.1 Running WRF-Chem Introduction ............................................................................. 13

4.2 WRF-Chem name listname list options: the choice of CHEM_OPT ......................... 13

4.3 Other chemistry name list options .............................................................................. 18

4.3.1 Running with only dust aerosols.......................................................................... 24

4.3.2 Running with direct effect ................................................................................... 24

4.3.3 Running with indirect effect ................................................................................ 25

4.3.4 Tracers running with chemistry ........................................................................... 25

4.3.5 Considerations when running with CAM-MAM chemistry ................................ 26

4.4 Typical choices for name list options ......................................................................... 27

4.5 Input fields for chemical constituents......................................................................... 29

4.6 VPRM and Greenhouse Gas tracer name list options................................................. 30

4.7 Including an upper boundary bounary condition for chemical species ...................... 31

4.8 Making a nested domain WRF-Chem simulation....................................................... 32

5.1 Visualizing WRF-Chem Introduction......................................................................... 34

5.2 The ncdump application.............................................................................................. 34

5.3 Using NCL scripts....................................................................................................... 35

5.4 The ncview application............................................................................................... 37

5.5 The RIP application .................................................................................................... 38

5.5.1 Downloading and installing the RIP program ..................................................... 38

5.5.2 Pre-processing data from WRF-Chem................................................................. 39

5.5.3 Generating NCAR GKS plots using RIP............................................................. 40

6.1 WRF-Chem KPP Introduction.................................................................................... 43

6.2 KPP requirements ....................................................................................................... 44

6.3 Compiling the WKC ................................................................................................... 44

6.4 Implementing chemical mechanisms with WKC ....................................................... 44

6.5 Layout of WKC........................................................................................................... 45

6.6 Code produced by WKC, user Modifications............................................................. 46

6.7 Available integrators................................................................................................... 47

6.8 Adding mechanisms with WKC ................................................................................. 47

6.9 Adapting KPP equation files....................................................................................... 48

6.10 Adapting additional KPP integrators for WKC ........................................................ 49

7.1 Summary..................................................................................................................... 50
2

7.2 WRF-Chem publications ............................................................................................ 51

Appendix A: WRF-Chem Quick Start Guide ................................................................... 61

Appendix B: Using MOZART with WRF-Chem............................................................. 68

Appendix C: Using the Lightning-NOx Parameterization in WRF-Chem....................... 70
3

WRF-Chem Version 3.7 User’s Guide 

WRF-Chem Overview

Table of Contents

1.1 WRF-Chem Introduction .............................................................................................. 3

1.2 WRF-Chem software .................................................................................................... 5

1.3 Possible applications of the current modeling system.................................................. 5

1.4 The WRF-Chem modeling system overview................................................................ 5

1.1 WRF-Chem Introduction

The WRF-Chem User’s Guide is designed to provide the reader with information 

specific to the chemistry part of the WRF model and its potential applications. It will 

provide the user a description of the WRF-Chem model and discuss specific issues 

related to generating a forecast that includes chemical constituents beyond what is 

typically used by today’s meteorological forecast models. For additional information 

regarding the WRF model, the reader is referred to the WRF model User’s Guide

(http://www2.mmm.ucar.edu/wrf/users/docs/user_guide_V3/contents.html).

Presently, the WRF-Chem model is now released as part of the Weather Research 

and Forecasting (WRF) modeling package. And due to this dependence upon WRF, it is 

assumed that anyone choosing to use WRF-Chem is very familiar with the set-up and use 

of the basic WRF model. It would be best for new WRF users to first gain training and 

experience in editing, compiling, configuring, and using WRF before venturing into the 

more advanced realm of setting up and running the WRF-Chem model.

The WRF-Chem model package consists of the following components (in 

addition to resolved and non-resolved transport) as well as some additional unlisted 

capabilities: 

! Dry deposition, coupled with the soil/vegetation scheme

! Four choices for biogenic emissions:

" No biogenic emissions included

" Online calculation of biogenic emissions as in Simpson et al. (1995) and Guenther 

et al. (1994) includes emissions of isoprene, monoterpenes, and nitrogen 

emissions by soil

" Online modification of user-specified biogenic emissions - such as the EPA 

Biogenic Emissions Inventory System (BEIS) version 3.14. The user must 

provide the emissions data for their own domain in the proper WRF data file 

format

" Online calculation of biogenic emissions from MEGAN

! Three choices for anthropogenic emissions:

" No anthropogenic emissions
4

" Global emissions data from the one-half degree RETRO and ten-degree EDGAR 

data sets

" User-specified anthropogenic emissions such as those available from the U.S. 

EPA NEI-05 and NEI-11 data inventories. The user must provide the emissions 

data for their own domain in the proper WRF data file format.

! Several choices for gas-phase chemical mechanisms including: 

" RADM2, RACM, CB-4 and CBM-Z chemical mechanisms

" The use of the Kinetic Pre-Processor, (KPP) to generate the chemical 

mechanisms. The equation files (using Rosenbrock type solvers) are currently 

available for RADM2, RACM, RACM-MIM, SAPRC-99, MOZART and 

NMHC9 chemical mechanisms

! Three choices for photolysis schemes:

" Madronich scheme coupled with hydrometeors, aerosols, and convective 

parameterizations. This is a computationally intensive choice, tested with many 

setups

" Fast-J photolysis scheme coupled with hydrometeors, aerosols, and convective 

parameterizations

" F-TUV photolysis scheme. This scheme, also from Sasha Madronich, is faster 

than the previous Madronich scheme option.

! Five choices for aerosol schemes:

" The Modal Aerosol Dynamics Model for Europe - MADE/SORGAM

" The Modal Aerosol Dynamics Model for Europe with the Volitity Basis Set 

aerosols – MADE/VBS

" The Modal Aerosol Module (MAM) 3 or 7 bin schemes closely coupled to the 

CAM5 physics

" The Model for Simulating Aerosol Interactions and Chemistry (MOSAIC - 4 or 8 

bins) sectional model aerosol parameterization

" A bulk aerosol module from GOCART

! Aerosol direct effect through interaction with atmospheric radiation, photolysis, and 

microphysics routines. This is available for all aerosol options starting with version 

3.5

! Aerosol indirect effect through interaction with atmospheric radiation, photolysis, and 

microphysics routines. This feature is available for modal and sectional aerosol 

options starting with version 3.5.

! An option for the passive tracer transport of greenhouse gases

! Two options for a 10-bin volcanic ash aerosol scheme based upon emissions from a 

single active volcano. One scheme includes SO2 degassing from the volcano while 

the other ignores SO2 degassing. Volcanic ash emissions can also be coupled to some 

aerosol modules (bulk and modal)

! A tracer transport option in which the chemical mechanism, deposition, etc. has been

turned off. The user must provide the emissions data for their own domain in the 

proper WRF data file format for this option. May be run parallel with chemistry

! A plume rise model to treat the emissions of wildfires
5

1.2 WRF-Chem software

The chemistry model has been built to be consistent with the WRF model I/O 

Applications Program Interface (I/O API). That is, the chemistry model section has been 

built following the construction methodology used in the remainder of the WRF model. 

Therefore, the reader is referred to the WRF software description in the WRF User’s 

Guide (Chapter 7) for additional information regarding software features like the build 

mechanism and adding arrays to the WRF registry. And while the chemistry model has 

been built with the intent to work within the WRF framework, not all run time options 

(e.g., physical parameterizations) that are available for WRF will function properly with 

chemistry turned on. Therefore, care must be taken in selecting the parameterizations 

used with the chemistry schemes. 

1.3 Possible applications of the current modeling system

! Prediction and simulation of weather, or regional and local climate

! Coupled weather prediction/dispersion model to simulate release and transport of 

constituents

! Coupled weather/dispersion/air quality model with full interaction of chemical 

species with prediction of O3 and UV radiation as well as particulate matter (PM)

! Study of processes that are important for global climate change issues. These 

include, but are not restricted to the aerosol direct and indirect forcing

1.4 The WRF-Chem modeling system overview

The following figure shows the flowchart for the WRF-Chem modeling system 

version 3.7.
6

As shown in the diagram, the WRF-Chem modeling system follows the same structure as 

the WRF model by consisting of these major programs:

! The WRF Pre-Processing System (WPS)

! WRF-Var data assimilation system
7

! WRF solver (ARW core only) including chemistry

! Post-processing and visualization tools

The difference with regular WRF comes from the chemistry part of the model needing to 

be provided additional gridded input data related to emissions. This additional input data 

is provided either by the WPS (dust emission fields), or read in during the real.exe 

initialization (e.g., biomass burning, biogenic emissions, GOCART background fields, 

etc.), or read in during the execution of the WRF solver (e.g., anthropogenic emissions, 

boundary conditions, volcanic emissions, etc.). And while some programs are provided in 

an attempt to aid the user in generation of these external input data files, as stated earlier, 

not all emissions choices are set-up to function for all possible name list options related 

to the WRF-Chem model. In other words, the generation of emissions input data for 

simulating the state of the atmosphere’s chemistry can be incredibly complex. Some 

times the user will need to modify code, or the model configuration, to get it to function

properly for their project. For more information regarding the input of emissions the 

reader is directed to the WRF-Chem Emissions Guide.
8

Chapter 2: WRF-Chem Software Installation

Table of Contents

2.1 Software Installation Introduction ................................................................................ 8

2.2 Building the WRF-chemistry code ............................................................................... 9

2.2.1 Getting the code ..................................................................................................... 9

2.2.2 UNIX environment settings for WRF-Chem......................................................... 9

2.2.3 Configuring the model and compiling the code................................................... 10

2.1 Software Installation Introduction

The WRF modeling system software (including chemistry) installation is straight

forward on the ported platforms. The package is mostly self-contained, meaning that 

WRF requires no external libraries that are not already supplied with the code. One 

exception for WRF is the netCDF library, which is one of the supported I/O API 

packages. The netCDF libraries or source code are available from the Unidata homepage 

at http://www.unidata.ucar.edu (select the pull-down tab Downloads, registration 

required, to find the netCDF link). Likewise, there is one exception as well, the fast 

lexical analyser (FLEX) library (libfl.a) will be needed if compiling the KPP chemistry 

code. This library is commonly included with GNU bison and is freely available for 

download at http://www.gnu.org/software/bison if it is not already installed on your unix 

systm.

The WRF-Chem model has been successfully ported to a number of Unix-based 

machines. We do not have access to all tested systems and must rely on outside users and 

vendors to supply required configuration information for compiler and loader options of 

computing architectures that are not available to us. See also chapter 2 of the User’s 

Guide for the Advanced Research WRF for a list of the supported combinations of 

hardware and software, required compilers, and scripting languages as well as postprocessing software. It cannot be guaranteed that chemistry will build successfully on all 

architectures that have been tested for the meteorological version of WRF.

Note that this document assumes a priori that the reader is very familiar with the 

installation and implementation of the WRF model and its initialization package (e.g., the

WRF Preprocessing System, or WPS). Documentation for the WRF Model and its 

initialization package can be found at (http://www2.mmm.ucar.edu/wrf/users/pubdoc.html). With this assumption in place, the remainder of this chapter provides a quick 

overview of the methodology for downloading the WRF-Chem code, setting the required 

environmental variables, and compiling the WRF-Chem model. Subsequent chapters 

assume that the user has access to the WRF-Chem model- and emission-data sets for their 

region of interest and has them readily available so that a full weather and chemical 

transport simulation can be conducted. 
9

2.2 Building the WRF-chemistry code

2.2.1 Getting the code

To obtain the WRF-Chem model one should follow these steps:

! Download, or copy to your working space, the WRF zipped tar file.

• The WRF model and the chemistry code directory are available from the 

WRF model download web site (http://www2.mmm.ucar.edu/wrf/users)

• The chemistry code is a separate download from the WRF model 

download web page and can be found under the WRF-Chemistry code title

• Always get the latest version if you are not trying to continue a long 

project

• Check for known bug fixes for both WRF and WRF-Chem by examining 

the WRF and WRF-Chem web pages

! Unzip and untar the file

• > gzip –cd WRFV3-Chem-3.7.TAR | tar –xf –

• Again, if there is a newer version of the code use it, 3.7 is used only as an 

example

• > cd WRFV3

Remember that bug fixes become available on a regular basis and can be downloaded 

from the WRF-Chem web site (http://www.wrf-model.org/WG11). You should check this 

web page frequently for updates on bug fixes. This includes also updates and bug fixes 

for the meteorological WRF code (http://www2.mmm.ucar.edu/wrf/users).

2.2.2 UNIX environment settings for WRF-Chem

Before building the WRF-Chem code, several environmental settings are used to 

specify whether certain portions of the code need to be included in the model build. In cshell syntax, the important environmental settings are:

setenv EM_CORE 1

setenv NMM_CORE 0

and they explicitly define which model core to build. These are the default values that are 

generally not required. The environmental setting

setenv WRF_CHEM 1

explicitly defines that the chemistry code is to be included in the WRF model build, and 

is required for WRF-Chem. This variable is required at configure time as well as compile 

time.
10

Optionally,

setenv WRF_KPP 1

setenv YACC ‘/usr/bin/yacc –d’

setenv FLEX_LIB_DIR /usr/local/lib

explicitly defines that the Kinetic Pre-Processor (KPP) (Damian et al. 2002; Sandu et al. 

2003; Sandu and Sander 2006) is to be included in the WRF-Chem model build using the 

flex library (libfl.a). In our case, the flex library is located in /usr/local/lib and compiles 

the KPP code using the yacc (yet another compiler compiler) location in /usr/bin. This is 

optional as not all chemical mechanisms need the KPP libraries built during compilation. 

The user may first determine whether the KPP libraries will be needed (see chapter 6 for 

a description of available options). One should set the KPP environmental variable to 

zero (setenv WRF_KPP 0) if the KPP libraries are not needed.

2.2.3 Configuring the model and compiling the code

The WRF code has a fairly complicated build mechanism. It tries to determine the 

architecture that you are on, and then present you with options to allow you to select the 

preferred build method. For example, if you are on a Linux machine, the code mechanism 

determines whether this is a 32-or 64-bit machine, and then prompts you for the desired 

usage of processors (such as serial, shared memory, or distributed memory) and 

compilers. Start by selecting the build method: 

! > ./configure

! Choose one of the options

• Usually, option "1" is for a serial build. For WRF-Chem do not use the 

shared memory OPENMP option (smpar, or dm + sm) as these options

are not supported. The serial build is a preferred choice if you are 

debugging the program and are working with very small data sets (e.g. if 

you are developing the code). Since WRF-Chem uses a lot of memory 

(many additional variables), the distributed memory options are preferred 

for all other cases

! You can now compile the code using

• > ./compile em_real >& compile.log

! If your compilation was successful, you should find the executables in the 

“main” subdirectory. You should see ndown.exe, real.exe, and wrf.exe listed

• > ls -ls main/*.exe

At this point all of the WRF-Chemistry model have been built. The model can be 

run and the run time messages should indicate that chemistry is included. But before one 

can use the WRF chemistry model to its full potential, the emissions input data needs to 
11

be generated. The manufacturing of the emissions input data is the subject of the next 

chapter and the WRF-Chem Emissions Guide.
12

Chapter 3: Generation of WRF-Chem-Emissions Data

Table of Contents

3.1 Emissions Generation Overview.............................................................................. 12

3.2 Generating Dust Related Emissions......................................................................... 12

3.1 Emissions Generation Overview

One of the main differences between running with and without chemistry is the 

inclusion of additional data sets describing the sources of chemical species. Ideally there 

would be single model, or utility code that would construct any and all emissions data 

sets for any domain and any chemistry option that a user selects. Unfortunately this is not 

the case and some of the emission files need to be prepared externally from the WRFChem simulation. This places the requirement the WRF-Chem model user to 

construct the emissions data set for your particular domain and desired chemistry

option from the wide variety of available data sources. This also places the WRFChem user in a position of needing to understand the complexity of their emissions data 

as well as having the control over how the chemicals are speciated and mapped to their 

simulation domain. While this can be a daunting task to the uninitiated, a separate guide 

has been written that should help illustrate the methodology through which emissions 

data is generated for a forecast domain. In short, there are several utility programs and 

data sets provided by the WRF-Chem user community that may be used to create an 

emissions data set. There are some restrictions on the domain location and the choice of 

chemical mechanism that need to be considered when using these programs. See the 

separate WRF-Chem emissions document to learn more about these programs and their 

use.

3.2 Generating Dust Emissions

Adding dust aerosols to a WRF simulation is perhaps the easiest of all WRFChem options at this time. The reason is becase the WRF-Chem model generates the dust 

emissions during the actual run. The “online” dust emissions data is provided through

land useage information produced by the WRF Preprocessing System (WPS) and the 

simulated meteorological fields. Hence, by compiling the WRF-Chem code and using 

the WPS to generate the WRF-Chem model input data the user has added the choice of 

using a simple aerosols scheme with no additional work. Additional information about 

running with dust aerosols is available in Chapter 4 as well as under the tutorials link 

from the WRF-Chem web page at http://ruc.noaa.gov/wrf/WG11.
13

Chapter 4: Running the WRF-Chemistry Model

Table of Contents

4.1 Running WRF-Chem Introduction ............................................................................. 13

4.2 WRF-Chem name listname list options: the choice of CHEM_OPT ......................... 13

4.3 Other chemistry name list options .............................................................................. 18

4.3.1 Running with only dust aerosols.......................................................................... 24

4.3.2 Running with direct effect ................................................................................... 24

4.3.3 Running with indirect effect ................................................................................ 25

4.3.4 Tracers running with chemistry ........................................................................... 25

4.3.5 Considerations when running with CAM-MAM chemistry ................................ 26

4.4 Typical choices for name list options ......................................................................... 27

4.5 Input fields for chemical constituents......................................................................... 29

4.6 VPRM and Greenhouse Gas tracer name list options................................................. 30

4.7 Including an upper boundary bounary condition for chemical species ...................... 31

4.8 Making a nested domain WRF-Chem simulation....................................................... 32

4.1 Running WRF-Chem Introduction

After successful construction of the anthropogenic- and biogenic-emission-input 

data files, it is time to run the model. This process is no different than running the 

meteorological version of the model. To make an air-quality simulation, change directory 

to the WRFV3/test/em_real directory. In this directory you should find links to the 

executables real.exe, and wrf.exe, other linked files, and one or more name list.input files 

in the directory. 

For larger domain simulations, one should use a DM (distributed memory) 

parallel system to make a forecast. This is of particular importance for WRF-Chem since 

much additional memory is required.

4.2 WRF-Chem name listname list options: the choice of CHEM_OPT

The largest portion of the chemistry name list options are related to the chemical

mechanisms and aerosol modules selection. The mechanism used during the forecast is 

decided with the name list name list parameter chem_opt that is described next. Some of 

these choices require other settings for other name list options. The options that are 

printed with red lettering indicate those options that are not fully implemented and tested. 

Model users are discouraged from selecting those options as they are not fully supported 

and could produce erroneous, or in the extreme case, detrimental results. In addition, it 

should be pointed out that the model developers most often work with just a few options 

at one time (e.g., RADM2/MADE-SORGAM, CBMZ/MOSAIC). Not all of the other 

available options are tested during development, but often it is a trivial exercise to make 

the other options functional. Therefore, users are encouraged to determine their desired 

settings that works best for their simulation, test the name list combination, improve the 
14

model code, and then communicate the improvements to the WRF-Chem user 

community. The chem_opt name list parameter is organized according to the chemical 

mechanism that is used.

&chem name 

list variable

Description Additional Comments

chem_opt = 0 no chemistry

 = 1 includes chemistry using the RADM2 

chemical mechanism - no aerosols

 = 2 includes chemistry using the RADM2 

chemical mechanism and 

MADE/SORGAM aerosols. 

 

 = 5 CBMZ chemical mechanism with 

Dimethylsulfide, or DMS

 = 6 CBMZ chemical mechanism without 

DMS

 = 7

CBMZ chemical mechanism 

(chem_opt=6) and MOSAIC using 4 

sectional aerosol bins. 

 = 8

CBMZ chemical mechanism 

(chem_opt=6) and MOSAIC using 8 

sectional aerosol bins. 

 = 9 CBMZ chemical mechanism 

(chem_opt=6) and MOSAIC using 4 

sectional aerosol bins including some 

aqueous reactions

For dust and sea salt use dust_opt=2, 

seas_opt=2

 = 10 CBMZ chemical mechanism 

(chem_opt=6) and MOSAIC using 8 

sectional aerosol bins including some 

aqueous reactions 

For dust and sea salt use dust_opt=2, 

seas_opt=2.

 = 11 RADM2 chemical mechanism and 

MADE/SORGAM aerosols including 

some aqueous reactions

For dust and sea salt use dust_opt=2, 

seas_opt=2.

 = 12 RACM chemical mechanism and 

MADE/SORGAM aerosols including 

some aqueous reactions

For dust and sea salt use dust_opt=2, 

seas_opt=2.

 = 13 Run with 5 tracers with emissions, 

currently set up for SO2, CO, no, ald, 

hcho, ora2

Use of tracer_opt suggested instead of 

this option.

 = 14 Single tracer run using tracer_1 array Use of tracer_opt suggested instead.

 = 15 Ensemble tracer option using 20 

individual tracers and an ensemble tracer 

array

Use of tracer_opt suggested instead.

 = 16 Greenhouse Gas CO2 only tracer Use of tracer_opt might be a better 

choice in some cases

 = 17 Greenhouse Gas tracer

RADM2

/QSSA 

Chemistry
15

 = 30 CBMZ chemical mechanism 

(chem_opt=6) and MADE/SORGAM 

modal aerosol

 = 31 CBMZ chemical mechanism 

(chem_opt=6) and MOSAIC using 4 

sectional aerosol bin with dms

 

 = 32 CBMZ chemical mechanism with 

(chem_opt=6) and MOSAIC using 4 

sectional aerosol bins with dms. Some 

aqueous reactions included

 

 = 33 CBMZ chemical mechanism 

(chem_opt=6) and MOSAIC using 8 

sectional aerosol bin with dms. Some 

aqueous reactions included

 

 = 34 CBMZ chemical mechanism with 

(chem_opt=6) and MOSAIC using 8 

sectional aerosol bins with dms. Some 

aqueous reactions included.

 

 = 35 CBMZ chemical mechanism 

(chem_opt=6) and MADE/SORGAM 

modal aerosol. Some aqueous reactions 

included

 = 41 RADM2/SORGAM with aqueous 

reactions included.

 

 = 42 RACM/SORGAM with aqueous 

reactions included (KPP)

Includes less complex aqueous 

reactions following CMAQ 

methodology, SO4 and NO3 wet 

deposition

 = 43 NOAA/ESRL RACM Chemistry and 

MADE/VBS aerosols using KPP library. 

The volatility basis set (VBS) is used for 

Secondary Organic Aerosols

Includes less complex aqueous 

reactions following CMAQ 

methodology, SO4 and NO3 wet 

deposition

 = 101 RADM2 Chemistry using KPP library Includes less complex aqueous 

reactions following CMAQ 

methodology

 = 102 RACM-MIM Chemistry using KPP 

library

Rosenbrock solver, can use larger time 

step

 = 103 RACM Chemistry using KPP library Rosenbrock solver, can use larger time 

step

 = 104 RACM Chemistry and PM advection 

using KPP library

Rosenbrock solver, can use larger time 

step

 = 105 RACM Chemistry and MADE/SORGAM 

aerosols using KPP library

PM total mass. This was originally 

implemented for wildfires

 = 106 RADM2 Chemistry and 

MADE/SORGAM aerosols using KPP 

library

Rosenbrock solver, can use larger time 

step
16

 = 107 RACM Chemistry and MADE/SORGAM 

aerosols using KPP library using the 

ESRL chemical reaction table

Rosenbrock solver, can use larger time 

step

 = 108 NOAA/ESRL RACM Chemistry and 

MADE/VBS aerosols using KPP library. 

The volatility basis set (VBS) is used for 

Secondary Organic Aerosols

Rosenbrock solver, can use larger time 

step

 = 110 CB4 Chemistry using KPP library Rosenbrock solver, can use larger time 

step

 = 111 MOZART Chemistry using KPP library Rosenbrock solver, can use larger time 

step

 = 112 MOZART Chemistry and GOCART 

aerosols (MOZCART) using KPP library

Rosenbrock solver, can use larger time 

step. Use phot_opt=3

 = 120 CBMZ Chemistry using KPP library Rosenbrock solver, can use larger time 

step. Use phot_opt=3

 = 131 CB05 Chemistry with MADE/SORGAM Rosenbrock solver, can use larger time 

step.

 = 132 CB05 Chemistry with MADE sectional 

aerosols and includes volatility basis set 

(VBS) for organic aerosol evolution

Rosenbrock solver, can use larger time 

step.

 = 170 CBMZ Chemistry with MOSAIC aerosols 

using KPP library

Rosenbrock solver, can use larger time 

step

 = 195 SAPRC99 Chemistry using KPP library Rosenbrock solver, can use larger time 

step

 = 198 SAPRC99 Chemistry with MOSAIC 

using KPP library. The MOSAIC aerosols 

uses 4 sectional aerosol bins and includes 

volatility basis set (VBS) for organic 

aerosol evolution 

Rosenbrock solver, can use larger time 

step

 = 201 MOZART Chemistry with MOSAIC 

using KPP library. The MOSAIC aerosols 

uses 4 sectional aerosol bins and includes 

volatility basis set (VBS) for organic 

aerosol evolution

Rosenbrock solver, can use larger time 

step

 = 202 MOZART Chemistry with MOSAIC 

using KPP library. The MOSAIC aerosols 

uses 4 sectional aerosol bins and includes 

volatility basis set (VBS) for organic 

aerosol evolution. Also include aqueous 

phase chemistry.

Rosenbrock solver, can use larger time 

step

 = 203 SAPRC99 Chemistry with MOSAIC 

using KPP library. The MOSAIC aerosols 

uses 8 sectional aerosol bins and includes 

volatility basis set (VBS) for organic 

aerosol evolution. Also include aqueous 

phase chemistry.

Rosenbrock solver, can use larger time 

step
17

 = 204 SAPRC99 Chemistry with MOSAIC 

using KPP library. The MOSAIC aerosols 

uses 8 sectional aerosol bins and includes 

volatility basis set (VBS) for organic 

aerosol evolution. 

Rosenbrock solver, can use larger time 

step

 = 300 GOCART simple aerosol scheme, no 

ozone chemistry

Only 18 variables. Optionally use 

dmsemis_opt=1, dust_opt=1 or 3, 

seas_opt=1

 = 301 GOCART coupled with RACM-KPP Only 18 variables 

Optionally use dmsemis_opt=1, 

dust_opt=1, seas_opt=1

 = 303 RADM2 Chemistry and GOCART 

aerosols 

Simple aerosol treatment. Optionally 

use dmsemis_opt=1, dust_opt=1 

seas_opt=1

 = 400 Volcanic ash fall and concentration only Simple aerosol treatment. Optionally 

use dmsemis_opt=1 dust_opt=1, 

seas_opt=1

 = 401 Dust concentration only Simple ash treatment with 10 ash size 

bins

 = 402 Volcanic ash fall and SO2 concentration Simple dust treatment with 5 size bins

 = 403 Volcanic ash fall Simple dust treatment with 4 size bins

 = 501 CBMZ with CAM-MAM3 Simple ash treatment with 10 ash size 

bins and volcanic SO2 gas emissions

 = 502 CBMZ with CAM-MAM7 MAM chemistry with 3 mode aerosol 

species. Requires CAM5 Morrison 

and Gettleman scheme (mp_phys=11).

 = 503 CBMZ with CAM-MAM3_AQ MAM chemistry with 7 mode aerosol 

species. Requires CAM5 Morrison 

and Gettleman scheme (mp_phys=11).

 = 504 CBMZ with CAM-MAM7_AQ MAM chemistry with 3 mode aerosol 

species and aqueous chemistry. 

Requires CAM5 Morrison and 

Gettleman scheme (mp_phys=11).

MAM chemistry with 7 mode aerosol 

species and aqueous chemistry. 

Requires CAM5 Morrison and 

Gettleman scheme (mp_phys=11).

 = 600 CRIMECH chemical mechanism using 

the KPP library

 = 601 CRIMECH chemical mechanism using 

the KPP library with MOSAIC aerosols. 

The MOSAIC aerosols uses 8 sectional 

aerosol bins.

 = 601 CRIMECH chemical mechanism using 

the KPP library with MOSAIC aerosols. 
18

The MOSAIC aerosols uses 4 sectional 

aerosol bins and includes squeous phase 

chemistry.

4.3 Other chemistry name list options

input_chem_inname 

<string>

name of chemistry input file 

chem_in_opt = 0 uses idealized profile to initialize chemistry

 =1 uses previous simulation data to initialize chemistry. The input 

file name will have the structure wrf_chem_input_d<domain> and 

the data will be read in through auxiliary input port 12. Set as well 

if using a global model to provide chemical lateral BCs.

io_style_emissions = 0 no emissions data read

 = 1 two 12-h emissions data files used

 = 2 date/time specific emissions data files used

chemdt = 1.5 time step used by chemistry in minutes

bioemdt = 30 update time interval used by biogenic emissions in minutes

kemit = 8 number of vertical levels in the emissions input data file. 

(considering the domains name list; 0 < kemit < e_vert)

kemit_aircraft = 1 number of vertical levels for aircraft emissions. The aircraft 

emissions are read in through auxiliary input port 14

photdt = 30 update time interval used by photolysis routine in minutes

phot_opt = 0 no photolysis

 = 1 uses Madronich photolysis (TUV)

 = 2 uses Fast-J photolysis

 = 3 uses Madronich F-TUV photolysis (aerosol interaction is not 

hooked up with MOSAIC aerosols) 

emiss_opt = 0 no anthropogenic emissions

 = 2 uses radm2 anthropogenic emissions

 = 3 uses radm2/MADE/SORGAM anthropogenic emissions

(recommended if using NEI emissions from emiss_v03.F)

 = 4 uses CBMZ/MOSAIC anthropogenic emissions

 = 5 GOCART RACM_KPP emissions (recommended if using 

RETRO/EDGAR emissions from prep_chem_sources)

 = 6 GOCART simple emissions

 = 7 MOZART emissions

 = 8 MOZCART (MOZART + GOCART aerosols) emissions

 = 9 Converts default RADM2 gas emissions to CBMZ. Aerosol 

emissions are speciated to MAM 3-mode aerosols

 = 10 MOZART (MOZART + aerosols) emissions

 = 13 SAPRC99 emissions

 = 14 CB05 emissions based on CBMZ speciation and to be used with 

emiss_inpt_opt=102

 = 15 CB05 emissions based on CB05 speciation and to be used with 

emiss_inpt_opt=101
19

 = 16 Greenhouse Gas CO2 tracer emissions

 = 17 Greenhouse Gas tracer emissions

 = 19 CRIMECH emissions

 = 20 CRIMECH emissions including additional aerosol species

emiss_opt_vol = 0 no volcanic ash emissions

 = 1 Include volcanic ash emissions for 10 size bins

 = 2 Include SO2 as well as the volcanic ash emissions for 10 size bins

aircraft_emiss_opt = 0 no aircraft emissions

 = 1 uses aircraft emissions

gas_drydep_opt = 0 no dry deposition of gas species

 = 1 includes dry deposition of gas species

aer_drydep_opt = 0 no dry deposition of aerosols

 = 1 includes dry deposition of aerosols

depo_fact = 0.25 when using VBS for aerosols, the ratio between dry deposition 

velocities of organic condensable vapors and dry deposition of 

HNO3 (default value = 0.25)

bio_emiss_opt = 0 no biogenic emissions

 = 1 calculates biogenic emissions online using the Gunther scheme

 = 2 includes biogenic emissions reference fields in wrfinput data file 

and modify values online based upon the weather

 = 3 includes MEGAN biogenic emissions online based upon the 

weather, land use data. Need to include ne_area setting, the total 

number of chemical species, in the chemical name list.

 = 16 Include CO2 biomass emissions from the VPRM model. (Requires 

user to provide external files through auxiliary input port 15.)

 = 17 Include VPRM input fields, Kaplan wetland inventory input fields 

when chem_opt=17. (Requires user to provide external files 

through auxiliary input port 15.)

ne_area = 41 Used by MEGAN biogenic emissions to provide a minimum total 

number of chemical species used by specified chemistry option. 

Best to set to a value larger than all chemical species (i.e., ne_area 

> 100).

emiss_inpt_opt = 0 no emissions data read

 = 1 emissions are speciation for RADM2/SORGAM. Recommended 

when using the NEI-05 or EDGAR/RETRO emissions speciated 

for RADM2 chemical mechanism

 = 3 emissions are speciation for GOCART_SIMPLE from NEI-05. 

This is a kludge and its use is not recommended

 = 16 Used with chem_opt=16, or 17 only to add fluxes and emissions to 

passive tracers. 

 = 101 RADM2 emission speciation adapted after reading the data file to 

follow the CBMZ/MOSAIC framework

 = 101 RADM2 emission speciation adapted after reading the data file to 

follow the CBMZ/MOSAIC framework

 = 102 RADM2 emission speciation adapted after reading data file to 

follow the RADM2/SORGAM framework (similar to 101, but 
20

with isoprene included)

 = 103 Carbon Bond 4-emission speciation adapted after reading the 

RADM2 data file

 = 104 Carbon Bond 4-emission speciation adapted after reading the 

RADM2 data file. Secondary Organic Aerosol (SOA) precursors 

computed from input data as well. Use for CAM5 micrphysics 

and MAM 3-mode aerosol

 = 111 RADM2 emission speciation adapted after reading data file to 

follow the MOZART framework

biomass_burn_opt = 0 no biomass burning emissions

 = 1 include biomass burning emissions and plume rise calculation

 = 2 include biomass burning emissions and plume rise calculation for 

MOCART

 = 3 include biomass burning emissions and plume rise calculation for 

MOZART

 = 5 include biomass burning emissions and plume rise calculation for 

GHG tracers fo CO2, CO and CH4 (needs chem_opt=17)

plumerisefire_frq = 180 time interval for calling the biomass burning plume rise subroutine

dust_opt = 0 no GOCART dust emissions included

 = 1 include GOCART dust emissions - need to provide fractional 

erosion map data

 =2 MOSAIC and MADE/SORGAM dust emissions option (does not 

requires extra input data)

 =3 Include GOCART dust emissions with AFWA modifications

 =4 Include GOCART dust emissions with UOC modifications, set 

dust_schme option as well.

dust_schme = 1 Dust emissions following Shao 2001

 = 2 Dust emissions following Shao 2004

 = 3 Dust emissions following Shao 2011

seas_opt = 0 no GOCART sea salt emissions

 = 1 include GOCART sea salt emissions 

 = 2 MOSAIC or MADE/SORGAM sea salt emissions

dmsemis_opt = 0 no GOCART dms emissions from sea surface

 = 1 include GOCART dms emissions from sea surface - need to 

provide dms reference field (currently only working for GOCART 

options)

aer_op_opt = 1 aerosol optical properties calculated based upon volume 

approximation

 = 2 aerosol optical properties calculated based upon Maxwell 

approximation

 = 3 aerosol optical properties calculated based upon exact volume 

approximation

 = 4 aerosol optical properties calculated based upon exact Maxwell 

approximation

 = 5 aerosol optical properties calculated based upon exact shell 

approximation
21

opt_pars_out = 0 no optical properties output

 = 1 include optical properties in output

gas_bc_opt = 1 uses default boundary profile

 = 16 sets values of CO2, CO and CH4 mixing ratios at boundaries to 

relevant constants. If a user wants to use boundary conditions from 

a global model, then the wrfbdy file should be modified and 

“have_bcs_chem” must be set to “.true.”

 = 101 uses modified default boundary profile – originally designed for 

use at Houston, TX

gas_ic_opt = 1 uses default initial condition profile

 = 101 uses modified default initial condition profile – designed for use at 

Houston, TX

 = 16 sets initial values of CO2, CO and CH4 mixing ratios to relevant 

constants

 = 101 uses modified default initial condition profile – designed for use at 

Houston, TX

aer_bc_opt = 1 uses default boundary profile

 = 101 uses modified default boundary profile – designed for use at 

Houston, TX

aer_ic_opt = 1 uses default initial condition profile

 = 101 uses modified default initial condition profile – designed for use at 

Houston, TX

gaschem_onoff = 0 gas phase chemistry turned off in the simulation (useful for 

debugging)

 = 1 gas phase chemistry turned on in the simulation (default)

aerchem_onoff = 0 aerosol chemistry turned off in the simulation (useful for 

debugging)

 = 1 aerosol chemistry turned on in the simulation (default)

wetscav_onoff = 0 wet scavenging turned off in the simulation, also see the 

“chem_opt” parameter

 = 1 wet scavenging turned on in the simulation, also see the 

“chem_opt” parameter

cldchem_onoff = 0 cloud chemistry turned off in the simulation, also see the 

“chem_opt” parameter

 = 1 cloud chemistry turned on in the simulation, also see the 

“chem_opt” parameter

vertmix_onoff = 0 vertical turbulent mixing turned off in the simulation (useful for 

debugging)

 = 1 vertical turbulent mixing turned on in the simulation (default)

chem_conv_tr = 0 subgrid convective transport turned off in the simulation (if no 

parameterization is used or for debugging)

 = 1 subgrid convective transport turned on in the simulation (default)

conv_tr_wetscav = 0 subgrid convective wet scavenging turned off in the simulation (if 

no parameterization is used or for debugging)

 = 1 subgrid convective wet scavenging turned on in the simulation 

(default)
22

conv_tr_aqchem = 0 subgrid convective aqueous chemistry turned off in the simulation 

(if no parameterization is used or for debugging)

 = 1 subgrid convective aqueous chemistry turned on in the simulation 

(default). Currently connected to “MADE” modal aerosol options.

have_bcs_chem = .false. gets lateral boundary data from idealized profile specified in 

chemistry routines (use caution when setting as the name list 

variable is defined as a logical)

 = .true. gets lateral boundary data from wrfbdy data file (use caution when 

setting as the name list variable is defined as a logical)

have_bcs_tracer = .false. does not use tracer lateral boundary data from wrfbdy data file 

(use caution when setting as the name list variable is defined as a 

logical)

 = .true. gets tracer lateral boundary data from wrfbdy data file for tracer 

species

aer_ra_feedback = 0 no feedback from the aerosols to the radiation schemes

 = 1 feedback from the aerosols to the radiation schemes turned on, see 

also chem_opt parameter

chemdiag = 0 turns off chemical tendency diagnostics

 = 1 turns on chemical tendency diagnostics for equation budget 

analysis

cam_mam_mode = 3 Number of MAM aerosol modes

cam_mam_nspec = 74 Number of MAM 3-bin aerosol species

CAM_MP_MAM_cpled Option to allow users to run Morrison-Gettleman micrphysics with 

prescribed aerosols (using &physics name list options 

accum_mode, aitken_mode and coarse_mode) with the RRTMG 

radiation scheme. The RRTMG scheme will still use prognostic 

aerosols. Default value is set to .true. so that both the MorrisonGettleman microphysics and the RRTMG radiation scheme use 

prognostic aerosols. 

In the physics name list, there are options that are directly related to the 

chemistry. These include the options related to the aerosol direct and indirect forcing

ra_sw_physics, progn, and mp_physics. In addition there is a cumulus radition feedback 

option, cu_rad_feedback, as well as online/offline cumulus cloud time average option, 

cu_diag. These options will only work with the GF or the G3 scheme (cu_phys=3 or 5). 

If the cu_rad_feedback is not turned on the radiation and photolysis schemes will not 

“see” parameterized clouds. If cu_diag is not turned on the time average cumulus cloud 

arrays will not be computed. These options will only work with WRF-Chem.

cu_rad_feedback = .false. no feedback from the parameterized convection to the 

atmospheric radiation and the photolysis schemes. (Use 

caution when setting as the name list variable is defined as a 

logical.)

 = .true. feedback from the parameterized convection to the radiation 

schemes turned on. (Use caution when setting as the name
23

list variable is defined as a logical)

cu_diag = 0 turns off time average cumulus cloud

 = 1 turns on time average cumulus clouds

progn = 0 turns off prognostic cloud droplet number in the Lin et al. 

and Morrison microphysics

 = 1 prognostic cloud droplet number included in the Lin et al. 

and Morrison microphysics scheme. This effectively turns 

the Lin et al. scheme into a second-moment microphysical 

scheme. If set with chem._opt=0 a default-prescribed 

aerosol concentration is used.

mp_physics = 11 CAM5 Morrison-Gettleman scheme to be used with MAM 

chemistry

cu_physics = 7 CAM5 Zhang-McFarlane scheme to be used with MAM 

chemistry

bl_pbl_physics = 9 CAM5 UW PBL scheme to be used with CAM-MAM 

chemistry

shcu_physics = 2 CAM5 UW shallow cumulus schemeto be used with CAMMAM chemistry

accum_mode = 1.e9 Background mass mixing ration for accumulation mode 

used with CAM_MP_MAM_cpled = .false.

aitken_mode = 3.e8 Background mass mixing ration for Aitken mode used with 

CAM_MP_MAM_cpled = .false.

coarse_mode = 2.e5 Background mass mixing ration for coarse mode used with 

CAM_MP_MAM_cpled = .false.

In the time_control name list there are options that are directly related to the 

chemistry, these include the options related to the reading of the various emissions data 

through the WRF auxiliary input ports and the methodology to read and write data files.

auxinput5_interval = 3600 input time interval for anthropogenic-emissions data. Typical 

settings are hourly for NEI emissions and monthly for the 

RETRO/EDGAR data

auxinput6_interval = input time interval for biogenic-emissions data. Typically 

biogenic emissions are static fields and this setting is not used

auxinput7_interval = input time interval for biomass burning (wildfire)-emissions data. 

For forecasts the wildfire emissions are often static fields and this 

setting is not used. For retrospective simulations the data can be 

updated according to the availability of additional fire information.

auxinput8_interval = input time interval for GOCART background fields. Typically for 

forecasts the monthly background data are static fields and this 

setting is not used.

io_form_auxinput5 = 2 anthropogenic-emissions input (wrfchemi_00z_d01 and 

wrfchemi_12z_d01) data format is WRF netCDF

 = 11 parallel netCDF

io_form_auxinput6 = 2 biogenic-emissions input (wrfbioemi_d01) data format is WRF 

netCDF. Can be used if bio_emiss_opt > 1
24

 = 11 parallel netCDF. Can be used if bio_emiss_opt > 1

io_form_auxinput7 = 2 biomass burning-emissions input (wrffirechemi_d01) data format 

is WRF netCDF

 = 11 parallel netCDF

io_form_auxinput8 = 2 GOCART background emissions input (wrf_gocat_bg_d01) data 

format is WRF netCDF

io_form_auxinput12 = 2 set to use previous simulation data to initialize chemistry 

(wrf_chem_input_d01). The data format is WRF netCDF

 = 11 Parallel netCDF

io_form_auxinput13 = 2 Volcanic ash emissions input (wrfchemv_d01) data format is WRF 

netCDF. Can be used if emiss_opt_vol > 1

 = 11 parallel netCDF. Can be used if emiss_opt_vol > 1

io_form_auxinput14 = 2 aircraft emissions input data format is WRF netCDF. 

 = 11 parallel netCDF. 

io_form_auxinput15 = 2 CO2 or GHG emissions input data format is WRF netCDF. Can be 

used if chem_opt = 16 or 17.

 = 11 parallel netCDF. Can be used if chem_opt = 16 or 17.

4.3.1 Running with only dust aerosols

The WRF-Chem code is able to predict dust transport along with the meteorology. 

To run with only dust, you should have obtained several input data files for the WRF 

Preprocessor System (WPS). These files are the dust related fields (erosion factor, clay

fraction, sand fraction) that are included in the WPS GEOG directory and the 

GEOGRIB.TBL_ARW_CHEM table file. After downloading and comiling the WPS, one 

needs to link the GEOGRIB table to GEOGRIB.TBL_ARW_CHEM. The WRF WPS can 

then be run so that the dust erosion fields will be included the geogrib output and 

subsequently included in the meteorology input data files. With the dust erosion data 

now in the input files WRF model can be run using the dust only name list settings 

(chem_opt=401). Be sure when running with the dust only option that the other 

chemistry name list settings (e.g., gaschem_onoff, phot_opt, gas_drydep_opt, etc.) are 

turned off and the dust_opt option is set to 1, 3, or 4.

4.3.2 Running with direct effect

Shortwave radiative feedbacks or what is known as the direct effect is included 

with the running of chemistry. To turn on the radiative feedbacks in your simulation you 

should select either the RRTMG radiation schemes, or the Goddard shortwave scheme 

and turn on aer_ra_feedback (aer_ra_feedback=1). With these options selected the

aerosol shading will be active and one can select an aerosol compostition assumption for 

the Mie radiation calculation using aer_op_opt. Another name list option related to 

radiation that is typically used in a simulation is cu_rad_feedback. When turned on 

(cu_rad_feedback = .true.) the shortwave and photolysis schemes will include the effects 

of unresolved clouds in the simulation. Otherwise, the simulation could have a grid cell 

containing a strong precipitating thunderstorm (parameterized instead of resolved 
25

precipitation) but the surface incident radiation and photolysis calculations will produce a 

result for an environment is totally cloud free.

4.3.3 Running with indirect effect

There are several chemistry options that include the indirect effect and each of 

these options contain aqueous phase chemistry (e.g., RADM2SORG_AQ, 

RACMSORG_AQ, CBMZ_MOSIAC_4BIN_AQ, CBMZ_MOSAIC_8BIN_AQ, etc.). It 

has been assumed by the developers that if a user chooses to run with includes aqeuous 

phase chemistry, then they also choose to be running with the indirect effect (chemistrymicrophysics interactions). If you do not want to include the indirect effect then one 

must either include a prescribed climatological aerosol distribution (e.g., Gustafson et al., 

2007) or choose a chemistry option that does not include aqueous phase chemistry.

To run with indirect effect on, one should turn on the aerosol direct effect 

(aer_rad_feedback = 1 and aer_op_opt > 0). Next the user needs to select a double 

microphysics scheme; either Lin et al. or the Morrison microphysics schemes are the 

current possible choices. Next turn on the prognostic number density option (progn=1) in 

the physics name list to make the Lin et al. scheme double moment as well as 

communicate the desire to run indirect effect to other microphysics schemes. Finally, 

turn on the wet scavenging and cloud chemistry options (wetscav_onoff=1; 

cldchem_onoff=1).

4.3.4 Tracers running with chemistry

The WRF-Chem code is now able to predict chemical tracers alongside reactive 

chemistry. This tracer option is set in the namelist.input under the dynamics name

list and not the chemistry name list. This will allow a user to run WRF-Chem with 

chemistry and tracers simultaneously. To run with tracer edit your namelist.input file and 

add the following under the dynamics name list section:

tracer_opt = 0 no tracers

 = 1 smoke tracer which must run with biomass burning

 = 2 lateral boundaries, stratospheric, boundary layer, and surface 

tracers

 = 3 same as tracer_opt=2 but surface tracer is replaced by the biomass 

burning tracer

 = 4 same as as tracer_opt=2 with the addition of a Lightning-NOx 

(LNOx) tracer, so must have the lightning NOx parameterization 

turned on (see Appendix E)

tracer_adv_opt = 0 uses positive definite advection for tracers

 = 1 uses positive definite and monotonic advection for tracers. 

(Recommended)
26

The biomass-burning tracer (ppmv) obtains the carbon monoxide (CO) emissions 

from the biomass-burning-emissions input and provides this data as a tracer. Unlike the 

reactive species emitted from biomass-burning, the tracer experiences passive transport. 

When activating the tracer species using the tracer_opt name list option a pair of tracers 

is released in the run. The first tracer is considered completely passive, while the other 

has a first-order decay with a one-day lifetime. The lateral boundary data for each tracer 

sets the tracer concentration to a value of 1 and is advected into the model domain during 

the simulation. The stratosphere tracer is set to 1 above a specified minimum temperature 

at this time, but an update to using the World Meteorological Organization (WMO) 

tropopause definition is planned. The boundary layer tracer is set to 1 below the PBL 

height. And finally, the surface tracer is set to 1 at the lowest model level (k=1).

When setting tracer_opt=4 there will also be a pair of tracers produced for 

lightning-NOx (LNOx). The first tracer tracks NO produced from intra-cloud lightning; 

the second tracer tracks NO produced from cloud-to-ground lightning.

4.3.5 Considerations when running with CAM-MAM chemistry

Starting with version 3.5 of the WRF-chem model, the CAM5 micrphysics and 

MAM aerosol schemes has been made available. The MAM aerosol scheme, short for 

Modal Aerosol Model, is either a 7-mode and 3-mode modal aerosol scheme (Liu et al., 

2012) derived from the Community Atmosphere Model (CAM), a component of the 

CESM climate model. The MAM scheme provides internally mixed representations of 

number concentration and mass for Aitkin, accumulation, and coarse aerosol modes. At 

this time the MAM is coupled only with CBM-Z photochemistry within WRF-Chem. In 

addition to MAM, the microphysics scheme from CAM has been ported to the WRF 

model. This scheme represents stratiform microphysical processes through a prognostic, 

two-moment formulation following the original parameterization of Morrison and 

Gettelman (2008). It should be noted that the CAM-MAM scheme (chem_opt=503) was 

extensively tested with the CAM physics inside WRF (CAMMGMP, CAMUWPBL, 

CAMZM, CAMUWSHCU, and RRTMG). The CAM physics options as well as the 

MAM chemistry could run with different combinations of the pre-existing physics and 

chemistry parameterizations in WRF, however, it is not recommended due to the lack of 

evaluation. Runs not using the full CAM-MAM package options should be examined by 

the user to ensure accuracy or whether the results contain numerical artifacts. In addition, 

the user could encounter warning and error messages when running MAM chemistry 

independent of CAM microphysics as this is not fully tested and the model could be 

running in an unsupported configuration.

When running without chemistry, the CAM microphysics scheme (Morrison and 

Gettelman microphysics; Morrison and Gettelman, 2008) requires TKE to be computed 

in oder for the scheme to function properly, so it must be used with PBL a scheme that 

produces TKE (e.g., UW PBL or MYJ). This scheme also uses outputs from ZhangMcFarlane cumulus scheme and the UW shallow cumulus schemes as sources of input 

data (Zhang and McFarlane, 1995). Care must be taken as these fields are set to zero 

when Zhang-McFarlane cumulus scheme and the UW shallow cumulus scheme are not in 
27

use and could result in run time errors. It is recommend that one use the CAM 

microphysics with the complete CAM physics suite (the UW shallow cumulus, ZhangMacFarlane deep cumulus the UW PBL) when running the model to avoid encountering 

a run-time error. 

When running the CAM physics suite (Morrison and Gettelman microphysics, 

UW shallow cumulus, Zhang-MacFarlane deep cumulus and UW PBL) with chemistry, it 

is recommended that the user can select from the four MAM aerosol packages. The CAM 

microphysics suite has not been tested with the other chemisry packages and could result 

in run error. If however, one wanted to test the UW PBL scheme with other chemistry 

options, this PBL scheme should not produce run time errors as it is an independent 

package. It should also be noted that the CAM microphysics in WRF does not include 

the full CAM5 macrophysics treatments. For this model implementation a simplified

version of CAM5 macrophysics is incorporated in the CAM microphysics driver which 

aids in computing the CAM fractional clouds as opposed to pre-existing WRF cloud 

fractions (values between 0 and 1). The simplified cloud fraction inside WRF’s CAM 

scheme uses the same formulation to calculate convective cloud fraction, and liquid and 

ice cloud fraction for stratiform clouds.

4.4 Typical choices for name list options

The addition of chemistry to WRF is making the choice of runtime configuration 

options much more complicated than for the meteorological version of WRF. Not all 

chemistry options are interchangeable with each other (e.g. not every chemical 

mechanism will work with every available aerosol module), not all physics options will 

work with all chemistry options. The name list description in the previous sections gives 

the user an idea of what physics options have to be chosen when applying the modeling 

system to study the aerosol direct and indirect effect. Work is in progress to extend the 

list of radiation and microphysics routines that will work with the aerosol routines. Work 

is also in progress to generalize the aerosol direct/indirect effect with respect to all 

available aerosol modules (e.g. allowing GOCART routines to interact with the 

atmospheric radiation schemes and the photolysis routines as well as allowing the full 

indirect effect for the modal aerosol scheme).

Even for very simplistic chemical setups seemingly small changes in the name 

list, options can cause large differences in the results. For real-time and research

applications, we commonly use:

chem_adv_opt = 2

moist_adv_opt=2

scalar_adv_opt=2

tke_adv_opt=2

diff_6th_opt = 0
28

The above options should always be used when running chemistry simulations. The WRF 

advection scheme has the tendency to overshoot and produce locally unrealistically low 

values (referred to at times as “digging holes”) if those options are not turned on. This 

“digging” is stronger with stronger gradients like those found where there are high 

emission rates.

cu_phys = 3 or 5

cugd_avedx=1

cu_rad_feedback=.true

chem_conv_tr = 1

The above options should be used if a convective parameterization is desired. The option 

chem_conv_tr will work with any other parameterization. However, cu_rad_feedback 

will only work with cu_phys=3 or 5. The latter option ensures that areas with convective 

precipitation will be seen by the atmospheric radiation scheme and the photolysis 

scheme. Not using any of the above convection-related options (chem_conv_tr=0) will 

underestimate the transport out of the boundary layer significantly. Setting false the 

cu_rad-feedback option will lead to photolysis rates that are unaffected by convection 

(too high), as well as skin and surface temperatures that are too warm. The cugd_avedx 

parameter is used by cu_phys=5 (G3 scheme) and should be set to one (1), except for 

forecasts high resolution of dx larger than 2km, but smaller than 10km. It will turn on 

subsidence spreading over neighboring grid points from the convective parameterization. 

In that case, set cugd_avedx=3 and cu_phys = 5. Other values are currently not allowed:

sf_sfclay_physics = 1

sf_surface_physics=2

bl_pbl_physics =1

The choice of the PBL physics is the most contested. It might depend strongly on 

the users own preferences. The user must keep in mind that results can differ significantly 

depending on this choice. The YSU scheme will lead to the deepest boundary layers 

when using the above choices (1-2-1). The user may also go to 2-2-2, using the MYJ 

scheme. There is no sure way of telling which will work better. We also sometimes 

choose the RUC soil parameterization (2-3-2) in combination with either YSU or MYJ 

scheme. This may work fine when the input conditions come from the RUC. The 

question of what modeling system the input and boundary conditions come from (such as 

GFS, NAM, ECMWF, etc.) and what type of physics are used in that modeling system 

can play a role too in determining the choice of PBL physics. The user may want to try to 

be consistent with the larger scale model, or choose the larger scale model based on his 

preferred choice of physics options – if possible. An additional consideration here is also 

the availability of an initial cloud analysis. This is available WRF-based Rapid Refresh 

(RAP) and may be essential in reducing spin-up. New PBL parameterizations are now 

also available. These show great promise. You may try the MYNN scheme. It was tested 

successfully with chemistry:

mp_zero_out = 2
29

We always choose this option if not using positive definite advection. It ensures that 

hydrometeor mixing ratios are not allowed to grow smaller than a threshold value 

(mp_zero_out_thresh), in particular qv as well as other moisture-mixing ratios will never 

go negative.

chem_dt = 0 [sets chem_dt = time_step; remember that the units are in minutes]

If you are using chem_opt=1 or 2, we advise to use the timestep as is used by the 

meteorological part of the model. That is, set chem._dt = 0 and the chemistry will use the 

same time step as used by the meteorology dynamics part of the model. You can choose 

larger time steps for any of the other options of chem_opt, but may want compare your 

results to a control simulation with chem_dt=0.

4.5 Input fields for chemical constituents

Unless chemical fields are available from a modeling system (global model, larger

scale model, or even another WRF-Chem run), an idealized vertical profile for each 

chemical species is provided to start the model simulation. This vertical profile, obtained 

when the model is initialized with chem_in_opt set equal to zero “0” in the name 

list.input, is based upon northern hemispheric, mid-latitude, clean environment 

conditions. If modifications are required, the routine module_input_chem._data can be 

modified to produce the desired initial conditions. Note that if the initial fields are

modified, the boundary conditions will probably also need to be modified (also located in 

module_input_chem_data).

The idealized profile is obtained from climatology in the routine 

module_input_chem_data with data based upon results from a NOAA-Aeronomy 

Laboratory Regional Oxidation Model (NALROM). The profile is declared globally 

inside the routine so that the lateral boundary conditions for a chemistry simulation may 

also be derived from this idealized profile. For ease of use, please note that in this 

module, the variable "iref" is the reference index, and "fracref" is the reference fraction 

corresponding to iref. For example, the species number 1 for a WRF-Chem simulation is 

SO2. The first reference index for the idealized profile, iref(1), is set to the number 12, 

indicating that SO2 is taken from the 12th species in the input data table. Not all chemical 

species match up so cleanly. For example, the NALROM calculates its chemistry using 

lumped OX (where OX = O3 + NO2 + HNO3 + ...) and a lumped NOX is obtained from 

(NOX = NO + NO2 + NO3 + 2N2O5 + HO2NO2 + HONO). However, the RADM2 

chemical mechanism strictly uses O3, and NOx is a combination of NO + NO2 only. 

Therefore, fractions of chemical species based upon the values of fracref are used to 

separate the lumped chemical species into the chemical species used by the RADM2 

chemical mechanism.

Short-lived species are initialized to steady-state equilibrium - since they are 

short-lived. The short-lived species within a lumped category (Ox, NOx, or NO3+N2O5 
30

in our case) would be renormalized to the lumped class after the steady-state equilibrium 

concentrations are determined.

The following is the list of long-lived species provided by NALROM: 

 NAMEL( 1) OX 

 NAMEL( 2) NOX 

 NAMEL( 3) HNO3 

 NAMEL( 4) H2O2 

 NAMEL( 5) CH3OOH 

 NAMEL( 6) CO 

 NAMEL( 7) ISOPRENE 

 NAMEL( 8) CH2O 

 NAMEL( 9) CH3CHO 

 NAMEL(10) PAN 

 NAMEL(11) OTHER ALKA

 NAMEL(12) SO2 

 NAMEL(13) BUTANE 

 NAMEL(14) ETHENE 

 NAMEL(15) PROPENE

 NAMEL(16) PPN 

 NAMEL(17) MEK 

 NAMEL(18) RCHO 

 NAMEL(19) SO4 

 NAMEL(20) MVK 

 NAMEL(21) MACR 

 NAMEL(22) HAC 

 NAMEL(23) MGLY 

 NAMEL(24) HPAN 

 NAMEL(25) MPAN 

 NAMEL(26) PROPANE 

 NAMEL(27) ACETYLENE 

 NAMEL(28) OH 

 NAMEL(29) HO2 

 NAMEL(30) NO3 + N2O5 

 NAMEL(31) HO2NO2 

 NAMEL(32) SUM RO2 

 NAMEL(33) OZONE 

 NAMEL(34) NOX 

4.6 VPRM and Greenhouse Gas tracer name list options

There are several chemistry name list options that are used only by the CO2 tracer 

and Greenhouse Gas tracer chemistry options. These name list options are:

vprm_opt This option allows a user to select a parameter set for the VPRM 
31

model. There are three sets of parameters - “VPRM_TABLE_US”, 

“VPRM_TABLE_EUROPE” and “VPRM_TABLE_TROPICS” 

(included in chem/chemics_init.F) used for different regions. 

Users may need to build own parameter sets for the domain and 

time period of interest. (default is “VPRM_param_US”)

wpeat Used to specify the scaling factor for the CH4 wetland emissions 

from peatlands. It indicates the fraction of heterotrophic 

respiration that is considered to be CH4 emissions. (default is 

0.05) 

wflood Used to specify the scaling factor for the CH4 wetland emissions 

from floodplains. Weighting between peat and floodplain 

wetlands depends on the mean annual temperature. Users may 

need to calibrate the Kaplan wetland inventory with observations 

first and then adjust both scaling factors. (default is 0.19) 

term_opt user to select the parameter set for the calculation of the termite 

emissions. Two sets of parameters are included: 

"CH4_termite_NW" to be used for the American continent and 

Australia and "CH4_termite_OW" for Europe, Asia, and Africa. 

Both are included in chem/chemics_init.F. (default is 

"CH4_termite_NW") 

4.7 Including an upper boundary bounary condition for chemical species

An upper boundary condition for select gas species may be specified by setting 

the have_bcs_upper in the chemistry name list. The name list variable have_bcs_upper 

defaults to .false. meaning that no chemical species concentrations are specified near the 

upper boundary. By setting have_bcs_upper to “.true.” the model will specify the o3, no, 

no2, hno3, ch4, co, n2o, and n2o5 concentrations at the top of the model. These values 

will override the original values as defined in the idealized chemical profile (section 4.5). 

When have_bcs_upper = “.true.” the chemistry name list variable “fixed_upper_bc” is 

activated. This name list variable controls the lowest pressure level where the upper 

boundary concentrations are overwritten (default value of 50 mb). From the pressure 

level defined by “fixed_upper_bc” down to the tropopause the concentrations are relaxed, 

using a 10 day time constant, to fixed values. 

To use the upper boundary conditions, the user is required to provide two additional 

input data files: 

• the file clim_p_trop.nc that includes a climatology for tropopause levels

• an input file with upper boundary conditions for gas species. The filename for the 

boundary conditions is provided to the WRF model via the chemistry name list

variable “fixed_ubc_inname”. 

Climatologies for 4 different time periods derived from WACCM RCP simulations have 

been made available to users from the NCAR/ACD website (www.acd.ucar.edu/wrfchem). These files are named: ubvals_b40.20th.track1_1950-1959.nc, 
32

ubvals_b40.20th.track1_1980-1989.nc, ubvals_b40.20th.track1_1996-2005.nc, and 

ubvals_rcp4_5.2deg_2020-2029.nc where the years used to produce the climatology are 

specified in the file names. Additional output variables are included in the model when 

using the upper boundary conditions. These tropopause diagnostics (TROPO_P, 

TROPO_Z, TROPO_LEV) are listed in the registry and a user should verify that they 

will included in the output file before running the model. Additional information about 

the upper boundary condition scheme was provided in presentation 8A.2 (Barth et al.) 

given at the 2011 WRF User Workshop. The presentation can be accessed online at 

http://www2.mmm.ucar.edu/wrf/users/workshops/WS2011/WorkshopPapers.php. 

4.8 Making a nested domain WRF-Chem simulation

To make a nested domain run one should first produce wrfinput files for both 

domains following Chapter 4 of WRF Users Guide. Like the single domain WRF-Chem

simulations, it is probably best to start by making a nested domain weather forecast 

(Chapter 4 of WRF Users Guide). After the nested meteorology only simulation is 

functioning correctly, then move on to running with chemistry included in the simulation.

Once the input files are produced the user can generate the emissions files for 

both domains using their program of choice (e.g., the emiss_v03.F program discussed in 

section 9 of the WRF-Chem Emissions Guide). File anthropogenic emissions file names 

will be differentiated by the domain (ie., wrfem_00to12z_d01 and wrfem_00to12z_d02).

The convert_emiss.exe program is not currently designed to read the name 

list.input file and generate the nested domain emissions files. Therefore, run the 

conversion program treating the nested domain as if it was actually the mother domain. 

That is, for each domain you will run convert_emiss.exe using settings for a single 

domain in your name list.input file. More specifically, follow the description in section 3 

to generate wrfchemi_d01 for the coarse domain, and move it to a safe place by changing 

its name. Change the name list.input file, moving the nested information to the mother 

domain column. Move the wrfinput_d02 to wrfinput_d01, link the output from emisv03 

(for the nested domain) to the required filenames, and then run convert_emiss. Finally, 

move the resulting wrfchemi_d01 to wrfchemi_d02.

When running wrf.exe with more than one domain (e.g., 2-way nested 

simulation), nearly every chemistry name list option needs to be set for each domain. A 

user should always examine the Registry/registry.chem file and check each of the 

chemistry name list variables. Those variables that are dimensioned max_domains need 

to be set for each domain. The following example shows how the chemistry name list

variables might be configured for a simulation using more than one domain.

&chem

kemit = 19,

chem_opt = 301, 301,

bioemdt = 30, 30,
33

photdt = 30, 30,

chemdt = 2.0, 0.66666, 

io_style_emissions = 1,

emiss_opt = 5, 5,

emiss_opt_vol = 0, 0,

chem_in_opt = 1, 1

phot_opt = 1, 1,

gas_drydep_opt = 1, 1,

aer_drydep_opt = 1, 1,

bio_emiss_opt = 1, 1,

dust_opt = 0,

depo_fact = 0.25, 0.25,

dmsemis_opt = 0,

seas_opt = 0,

gas_bc_opt = 1, 1,

gas_ic_opt = 1, 1,

aer_bc_opt = 1, 1,

aer_ic_opt = 1, 1,

gaschem_onoff = 1, 1,

aerchem_onoff = 1, 1,

wetscav_onoff = 0, 0,

cldchem_onoff = 0, 0,

vertmix_onoff = 1, 1,

chem_conv_tr = 1, 1,

conv_tr_wetscav = 1, 1,

conv_tr_aqchem = 1, 1,

biomass_burn_opt = 1, 0,

plumerisefire_frq = 30, 0,

aer_ra_feedback = 0, 0,

aer_op_opt = 0, 0,

have_bcs_chem = .false., .false.,
34

Chapter 5: Visualizing WRF-Chem Data files

Table of Contents

5.1 Introduction................................................................................................................. 34

5.2 The ncdump application.............................................................................................. 34

5.3 Using NCL scripts....................................................................................................... 35

5.4 The ncview application............................................................................................... 37

5.5 The RIP application .................................................................................................... 38

5.5.1 Downloading and installing the RIP program ..................................................... 38

5.5.2 Pre-processing data from WRF-Chem................................................................. 39

5.5.3 Generating NCAR GKS plots using RIP............................................................. 40

5.1 Visualizing WRF-Chem Introduction

The WRF modeling system has a number of visualization tools that are available 

to display data. Since the model output data is netCDF format, essentially any tool 

capable of displaying this data format can be used to display the WRF model data. 

Currently, NCAR supports four graphical tool packages (NCL, RIP4, WRF-to-GrADS, 

and WRF-to-vis5d. A description of each of these tools is also available online at: 

http://www2.mmm.ucar.edu/wrf/users/graphics/WRF-post-processing.htm.

The WRF-Chem model, being part of the WRF modeling system, can likewise use any of 

the WRF netCDF visualization tools. A detailed description of all available visualization 

tools is beyond the scope of this User’s Guide. Instead this chapter will discuss a few of 

the tools that are being used to examine WRF-Chem input and output files – ncdump, 

ncview and RIP. However, each user is encouraged to explore the multitude of netCDF 

visualization tools that are available and use the one(s) that are best suited to their needs.

5.2 The ncdump application

The ncdump utility is distributed by Unidata and installed with the netCDF 

library. This application is a netCDF file viewer that can be used to generate ASCII 

representation of the data. There are some limits to what this program can do with point 

(e.g., surface station) data, but there are more options available for examining array data. 

However, ncdump can be cumbersome when examining large volumes of array data. The 

Unidata web page

http://www.unidata.ucar.edu/software/netcdf/docs/ncdump-man-1.html

contains a detailed description of the ncdump command and examples of its usage.
35

5.3 Using NCL scripts

NCL is among the many post-processing utilities to visualize WRF output. This 

section briefly describes a script that can be used to generate a plot of chemical species. 

For additional information about NCL, the reader is directed to Chapter 8 in the WRF 

Model User’s Guide.

Following the NCL script examples, the following script has been generated to 

plot ozone for the 1 August 2000 at 0000 UTC. The user is required to set the date and 

run directory (direc) as well as the header for the file name (filnm) and field to be plotted 

in the script. The gas phase species can be converted to ppm from ppb for easier plotting 

and viewing. The script is as follows:

load "$NCARG_ROOT/lib/ncarg/nclscripts/csm/gsn_code.ncl"

load "$NCARG_ROOT/lib/ncarg/nclscripts/csm/gsn_csm.ncl"

load "$NCARG_ROOT/lib/ncarg/nclscripts/wrf/WRF_contributed.ncl"

begin

; read in wrfout file

 date = "08-01_00"

 direc = "./"

; filename=filnm

 filnm = addfile(direc+"wrfout_d01_2000-"+date+":00:00.nc","r")

; extract field to be plotted from file

 ozone = filnm->o3

; scale by 1000 (convert ppm to ppb)

 ozone = ozone*1000.

 ozone@units = "ppbv"

;===============================================================

; set up plotting parameters

; creating 2 workstations to plot both to screen (x11) and to a pdf file

wks = gsn_open_wks("x11","ozone_lev50_"+date) 

wks_2 = gsn_open_wks("pdf","ozone_lev50_"+date)

gsn_define_colormap(wks,"WhViBlGrYeOrRe") ; choose colormap for wks

gsn_define_colormap(wks_2,"WhViBlGrYeOrRe") ; choose colormap for wks_2

; assign plotting resources

res = True

res@gsnMaximize = True
36

res@gsnSpreadColors = True ; use full range of color map

res@cnFillOn = True ; turn on color fill

res@cnLinesOn = False ; turn off contour lines

res@cnLineLabelsOn = False ; turn off contour line labels

res@cnLevelSelectionMode = "ManualLevels" ; set explicit contour levels

res@cnMinLevelValF = 60

res@cnMaxLevelValF = 110

res@cnLevelSpacingF = 5

;

res@tiMainString = "OZONE CONC. AT "+date+"UTC"

;===============================================================

; use WRF_contributed procedure to set map resources

 WRF_map_c(filnm,res,0)

; define lat, lon

 ozone@lat2d = filnm->XLAT(0,:,:)

 ozone@lon2d = filnm->XLONG(0,:,:)

;

; plot ozone at the lowest level

 plot = gsn_csm_contour_map(wks,ozone(0,0,:,:),res) 

 plotpdf = gsn_csm_contour_map(wks_2,ozone(0,0,:,:),res) 

end

By issuing the ncl execution command

ncl <script name>

The contour plot showing ozone concentration over the domain is generated (Figure 5.1).
37

Fig. 5.1 A sample of a color-filled contour plot generated using the NCL script. The 

colored regions represent locations in which the surface ozone concentration (ppbv) is in 

the range indicated by the color bar shown at the bottom of the figure. 

5.4 The ncview application

The Ncview application is a visual browser for netCDF data developed by David 

W. Pierce of the Scripps Institution of Oceanography. Ncview reads the wrfout files (also 

all input files, including the emissions) directly using the simple command “>ncview 

wrfout....”. This makes it a very useful tool for a quick look analysis or diagnosis of a 

problem with the model run, including problems with any of the input files. Ncview 

installs onto UNIX platforms under X11 and provides an easy, push-button method to 

examine the contents of a netCDF file (Fig. 5.2). When looking at the data you can 

change the color maps, invert the data, generate line plots, etc. In addition, if the file 

contains a time series, Ncview permits simple animation of the data. An additional 

information program as well as a link to download the source code is available online at:
38

http://meteora.ucsd.edu/~pierce/ncview_home_page.html. 

Fig. 5.2 A screen-capture image showing how the Ncview user interface allows the user 

to examine the WRF-Chem emissions-input data file. The color image shows the surface 

emissions for carbon monoxide and the plot shows the temporal evolution of the surface 

CO emissions at a single point.

5.5 The RIP application

5.5.1 Downloading and installing the RIP program

The FORTAN program RIP (Read/Interpolate/Plot) invokes NCAR Graphics 

routines to produce two-dimensional images from gridded numerical model data. 

Originally designed to work with the PSU/NCAR Mesoscale Model (i.e., MM5), it has 

been modified by Mark Stoelinga to work with the WRF model. RIP is officially 

supported by the National Center for Atmospheric Research (NCAR) and functions on 
39

UNIX systems that have a FORTRAN 77/90 compiler and the NCAR Graphics Library. 

Documentation regarding the RIP program is available online at:

http://www2.mmm.ucar.edu/wrf/users/docs/ripug.htm.

RIP is not fully interactive, but instead it requires the user to specify the desired 

plots through a formatted text file. NCAR Graphics CGM files are created when the RIP 

program is executed and these files can be viewed with any one of several different 

metacode translator applications (i.e., idt, ctrans). Additional plots or modification of any 

existing plots is accomplished through changing the formatted text file and re-executing 

the RIP program.

5.5.2 Pre-processing data from WRF-Chem

Before using RIP to plot WRF-Chem output, one first needs to specify the 

location of the RIP executable by setting the environmental variable RIP_ROOT. In cshell syntax, if the RIP code is located in /home/username/RIP, the command is:

setenv RIP_ROOT /home/username/RIP.

After setting the RIP_ROOT environmental variable, the WRF-Chem data files 

need to be converted to data files having the format expected by the RIP program. The 

RIP data preprocessor program, or rip_dp, is used to accomplish this task. Like RIP, a 

formatted text file is needed to specify what operations are to be performed. The rip_dp 

input data file (named ripdp.in for example) might look similar to the following example:

&userin

ptimes=0,-

72,3,ptimeunits='h',tacc=30.,discard='QGRAUP','Q2','T2','TH2','AC0','AC

O3','ALD','ANTHA','CANWAT','cor','CORN','COSALPHA','CSL','CU_CO_TEN','D

CB','DEP_VEL','dmap','E','ECI','E_ECI','orgaro1j','orgaro2j','orgaro1i'

,'orgaro2i','orgba1i','orgba1j','orgba2i','orgba2j','orgba3i','orgba3j'

,'orgba4i','orgba4j','orgole1i','orgole1j','orgpai','orgpaj','p25i','p2

5j','nh4ai','nh4aj','no3ai','no3aj','E_NH3','E_ORGI','E_SO2','ETH','EXC

H_H','GLW','GLY','GRDFLX','h2o2','hc3','hc5','hc8','hfx','hno3','hno4',

'ho','ho2','hono','ISLTYP','ISO','IVGTYP','KET','LANDMASK','LH','MGLY',

'MU','MUB','n2o5','nh3','nu0','ol2','olt','onit','op1','op2','paa','pan

','rtc','rte','SEAS','SFROFF','SH2O01','SH2O02','SH2O03','SH2O04','SINA

LPHA','tol','tpan','UDROFF','xyl',

iexpandedout=1

&end

In this file the number of hours (72), the time interval (3) and the arrays that are to be 

excluded from preprocessing are specified.

The command to run the rip_dp program might look like the following:

ripdp_wrf –n ripdp.in /Data/wrfplots all /WRFV3/test/em_real/wrfout_d01_2008-07-14_12:00:00
40

The execution of the rip_dp program will produce many small Rip data files. These files 

are located in the Data Directory and are named like the following files:

wrfplots_0000.00000_ALBEDO 

wrfplots_0000.00000_V10 

wrfplots_0000.00000_ALT 

wrfplots_0000.00000_VEGFRA 

wrfplots_0000.00000_TMN 

wrfplots_0000.00000_SO2 

...

5.5.3 Generating NCAR GKS plots using RIP

Before generating the NCAR graphics data files, the user needs to provide all of 

the specific details in RIP user input data file, rip.in. The first part of this data file 

consists of two name lists: the userin name list that holds the general input specifications 

and the trajcalc name list that controls the creation of trajectory plots. The second part of 

the rip.in file holds a specification table that controls the generation of the plot(s). The 

reader should examine the online RIP documentation for a more detailed explanation. 

For the generation of a horizontal plot showing the fine particulate matter 

(PM2.5) and the horizontal winds at the surface and placed on a map of the simulation 

domain, the rip.in data file would look similar to the following:

&userin

idotitle=1,title='PM2.5 Level 1',titlecolor='def.foreground',

ptimes=${hour},

ptimeunits='h',tacc=180,timezone=-7,iusdaylightrule=1,

iinittime=1,ivalidtime=1,inearesth=0,

flmin=.09, frmax=.92, fbmin=.10, ftmax=.85,

ntextq=0,ntextcd=0,fcoffset=0.0,

idescriptive=1,icgmsplit=0,maxfld=10,itrajcalc=0,imakev5d=0

&end

&trajcalc

rtim=15,ctim=6,dtfile=3600.,dttraj=600.,vctraj='s',

xjtraj=95,90,85,80,75,70,65,80.6,80.6,80.6,80.6,80.6,80.6,

yitraj=50,55,60,65,70,75,80,77,77,77,77,77,77,

zktraj=.9,.9,.9,.9,.9,.9,.9,.99,.9,.8,.7,.6,.5,

ihydrometeor=0

&end

=======================================================================

-------------------- Plot Specification Table -------------------

=======================================================================

feld=PM_2.5_DRY; ptyp=hc; vcor=s; levs=b1; cint=.5; cmth=fill;>

 smth=2;cosq=.0,violet,2.,dark.blue,4.,blue,6.,green,>

8.,light.green,10.,dark.yellow,15.,yellow,>

20.,red,30.,red.coral,40.,orange,50.,tan,>

60.,light.gray,70.,med.gray,80.,black,100.,white

feld=uuu,vvv; ptyp=hv; nttl;vcmx=-1; colr=black;linw=2

feld=map; ptyp=hb

feld=tic; ptyp=hb
41

=======================================================================

Generation of a NCAR CGM data file is done by issuing the command:

${RIP_ROOT}/rip rip.in wrfplots

in the /Data directory. With the successful execution, a file named wrfplots.cgm is

created. As mentioned previously, the CGM data file can be viewed using any of the 

CGM file viewers like ctrans. For example, to use ctrans to view the CGM file, issue 

the command:

${NCARG_ROOT}/bin/ctrans -d X11 wrfplots.cgm.

The product from executing this command will be an image like the one shown in Fig. 

5.3.
42

Fig. 5.3. An NCAR GKS figure produced using by the RIP visualization tool. The image 

shows the surface fine particulate matter (PM2.5) concentration (micrograms per cubic 

meter) and the horizontal surface winds (barbs).

With the successful visualizing of the results from a WRF-Chem simulation, one could 

add additional fields to plot by making additional RIP user-input data files for each 

individual plot, or modify the previous image specifications in a user-input data file. 

After modifying the user-input data file(s), you would only need to (re)create the NCAR 

CGM file(s).
43

Chapter 6: WRF-Chem KPP Coupler

Table of Contents

6.1 Introduction................................................................................................................. 43

6.2 KPP requirements ....................................................................................................... 44

6.3 Compiling the WKC ................................................................................................... 44

6.4 Implementing chemical mechanisms with WKC ....................................................... 44

6.5 Layout of WKC........................................................................................................... 45

6.6 Code produced by WKC, User Modifications............................................................ 46

6.7 Available integrators................................................................................................... 47

6.8 Adding mechanisms with WKC ................................................................................. 47

6.9 Adapting KPP equation files....................................................................................... 48

6.10 Adapting additional KPP integrators for WKC ........................................................ 49

6.1 WRF-Chem KPP Introduction

Coupled state-of-the-art meteorology/chemistry models such as WRF-Chem 

typically include hundreds of reactions and dozens of chemical species. Solving the 

corresponding huge systems of ordinary differential equations requires highly efficient 

numerical integrators. In the case of hard-coded manually “tuned” solvers, even minor 

changes to the chemical mechanism, such as updating the mechanism by additional 

equations, often require recasting the equation system and, consequently, major revisions 

of the code. This procedure is both extremely time consuming and error prone. 

In recent years, automatic code generation has become an appreciated and widely 

used tool to overcome these problems. The Kinetic PreProcessor (KPP) is a computer 

program which reads chemical equations and reaction rates from an ASCII input file

provided by the user and writes the program code necessary to perform the numerical 

integration (Damian et al. 2002; Sandu et al. 2003; Sandu and Sander 2006). 

Computational efficiency is obtained by automatically reordering the equations in order 

to exploit the sparsity of the Jacobian. While still in a developmental stage, KPP Version 

2.1 has been sucessfully implemented into WRF-Chem. Furthermore, a preprocessor for 

WRF-Chem has been developed that automatically generates the interface routines 

between the KPP-generated modules and WRF-Chem, based on entries from the WRFChem registry files and the KPP input files. This WRF-Chem-KPP coupler, WKC 

hereafter, is automatically executed during code compilation and considerably reduces 

the effort to add chemical compounds and/or reactions to existing chemical mechanisms. 

Likewise, the effort needed to construct new chemical mechanisms code has been greatly 

reduced due to the addition of KPP into WRF-Chem.

The WRF-Chem KPP Coupler, or WKC, was discussed by Salzmann and 

Lawrence (2006) at the WRF-User Workshop. The abstract is for the presentation is 

available with the KPP documentation in the WRF-Chem code 

(WRFV3/chem/KPP/documentation/abstr_wkc.pdf). A more complete set of 
44

documentation for KPP (Kinetic PreProcessor) is also provided on line by Adrian Sandu 

at:

http://people.cs.vt.edu/~asandu/Software/Kpp/.

References for the KPP are Damian et al. (2002); Sandu et al. (2003); Sandu and 

Sander (2006) and it is requested that these references are cited when presenting results 

from the KPP generated code. KPP and WKC are distributed under the GNU General 

Public License (GPL). Constructive comments and suggestions regarding the coupler 

and/or this documentation are welcome. Only a limited number of all KPP features are 

available for use with WKC, but more features may be added in the future. In the 

remainder of this chapter, the WKC as implemented into the WRF-Chem model is

described. Since the coupler has been only recently added to the WRF repository, it is 

possible that some design details could change based upon response from the WRF 

model developers as well as the WRF-Chem user community.

6.2 KPP requirements

KPP requires the UNIX tool programs flex, yacc, and sed to be installed on your 

system before compiling the code. Check with your system administrator if these 

programs are not installed. The path to the flex library (either libfl.a or libfl.sh) is 

specified by the environment variable FLEX_LIB_DIR. The default path for these 

libraries is assumed to be /usr/lib. If the library libfl.a (or libfl.sh) is not located in /usr/lib 

on your system, the variable FLEX_LIB_DIR should be set prior to compiling WRFChem. The C compiler is set by configure_kpp based on the settings in configure.wrf.

6.3 Compiling the WKC

The WKC, and therefore KPP as well, are compiled and executed automatically 

when WRF-Chem is compiled with the WRF_KPP environmental variable set (setenv 

WRF_KPP 1). The WKC copies the KPP generated code to the WRFV3/chem directory 

and automatically modifies the chemistry Makefile so that the KPP generated code is 

compiled and linked with the model. The KPP and WKC-generated modules in the chem 

directory contain the string “kpp” in their file names. Running the clean script removes 

these modules. 

6.4 Implementing chemical mechanisms with WKC

KPP files for chemical mechanisms that have already been implemented with

WKC are located in subdirectories of WRFV3/chem/KPP/mechanisms. The 

corresponding packages are declared in the WRFV3/Registry/registry.chem file and 

contain the suffix “kpp” in their name. In order to use one of these mechanisms with 

WRF-Chem, set the chem_opt variable in the name list.input file to the appropriate value. 

The following mechanisms are currently available:

• RACM/SORGAM
45

• RACM (Stockwell et al. 1997)

• RACM-MIM (Geiger et al. 2003)

• RACM/SORGAM

These WKC implemented mechanisms have chem_opt greater than 100. The 

methodology for implementing additional mechanism(s) using KPP is discussed later in 

this chapter.

6.5 Layout of WKC

WKC reads KPP species input files with suffix .spc and the file 

Registry/registry.chem and automatically generates the Fortran 90 interface routines 

between WRF-Chem and the KPP generated code (see Fig. 6.1). It is in part based on the

WRF registry mechanism. The WKC related files are located in the chem/KPP directory. 

This directory contains:

• a subdirectory mechanisms which holds directories with KPP input files for 

different mechanisms;

• a compile and a clean script for WKC (which are executed from the WRF-Chem

compile script);

• a version of KPP v2.1 in the kpp subdirectory. This version of KPP was adapted 

to produce code which can directly be used with WRF-Chem (using the #WRF 

Conform option in the .kpp file);

• the source code of WKC in the util/wkc subdirectory;

• module wkpp_constants.F which allows to specify input to kpp such as RTOL 

and ATOL (likely to be extended in the future); and

• a subdirectory inc containing files which are included during compile time (using 

“#include” statements). The files in chem/KPP/incare not removed by the WKC 

clean script. Their purpose is to allow user modifications to WKC generated code.

At the heart of WKC is the routine gen kpp.c that is located in the util/wkc directory.
46

Fig. 6.1. Schematic showing the flow structure of KPP in the WRF-Chem model. 

Flowing down from the top, the Registry and KPP input data files (ASCII) are 

preprocessed into Fortran 90 and C code which is coupled to the WRF-Chem solvers.

6.6 Code produced by WKC, user Modifications

The code produced by WKC is called from the chem driver (see schematic call 

tree in Fig. 6.2). Since parts of the code are generated automatically, manual changes will 

be lost when recompiling WRF-Chem (as indicated by a warning in the header of the 

corresponding files). There are, however, a number of “#INCLUDE” preprocessor 

statements in the WKC generated code. The files included (in the .f files) are located in 

the chem/KPP/inc directory. These files are not removed by the clean script and can be 

used to inline user supplied code. In case this should not be enough, there are two ways to 

edit automatically generated files permanently: The files can either be renamed in such a 

way that they won’t be removed by the clean kpp script; or the C code which generated 

the files (either KPP or WKC) can be edited. The latter is generally the better solution. 

However, the method of using include files in the chem/KPP/inc directory is strongly 

recommended.
47

Figure 6.2: Schematic of the KPP call tree. Here the chem_driver routine in WRF-Chem

calls a separate mechanism driver for each chemical mechanism implemented with KPP. 

This model configuration requires only one additional subroutine to be added to WRFChem so that the user can switch between the different implemented chemical 

mechanisms.

6.7 Available integrators

References for the chosen integrator after compiling WRF-Chem with KPP can be 

found in the chem directory in module kpp my mechanism Integrator.f90, where ‘‘my 

mechanism’’ refers to the chemical mechanism chosen in the WRF-Chem name list. 

Currently, only Rosenbrock type integrators are available for the use with the WKC. 

More on the methodology to add additional integrators to the WKC will be discussed in a

later section.

6.8 Adding mechanisms with WKC

When implementing new mechanisms, it is often necessary to calculate additional 

photolysis rates, include new emission datasets, specify initial and boundary conditions, 

calculate additional dry deposition rates, specify Henry’s law coefficients for soluble 

trace gases and carry them through the wet deposition routines, etc., in addition to the 

following steps.

The following basic steps are necessary in order to add a mechanism:

• edit the registry file Registry.EM_CHEM to

o add species to the chem array structure (if necessary), and

o add a package (a mechanism) with a name ending on “_kpp”, e.g.,

my_mechanism_kpp;
48

• provide input files my_mechanism.eqn, my_mechanism.spc, my_mechanism.kpp 

for KPP in a sub-directory of WRFV3/chem/KPP/mechanisms named after the 

package (i.e. my_mechanism, not my_mechanism_kpp); and

• optionally provide a file (my_mechanism_wrfkpp.equiv) for mapping variable 

names in WRF-Chem to variable names in KPP (e.g. HO to OH).

For additional examples, you can examine the chemical mechanisms that have already 

been implemented. You should note that when copying one of the directories in 

WRFV3/chem/KPP/mechanisms to another directory, it is necessary to change the name 

of #Model in the .kpp file and the names of the .eqn and the .spc file in the .def file. 

When introducing a “new” .kpp file you should set the #INTEGRATOR to an integrator 

contained in the directory WRFV3/chem/KPP/kpp/kpp-2.1/int/WRF_conform. For 

example, set

#INTEGRATOR WRF conform/rosenbrock

and add the line

#WRFCONFORM

to your new .kpp file. You should remember that not all KPP options are supported by the 

WKC. Also, the WKC is currently not able to handle comments in the .spc file!

6.9 Adapting KPP equation files 

The process of adapting a KPP equation file for use with WRF-Chem involves

renaming a few variables in the equation file:

KPP equation file Equation file units Registry

Photolysis rate J(Pj_no2) s

-

1 ph_no2

Temperature TEMP K t_phy

Third body 

concentration

C_M (molecular moist air) cm3 Calculated from 

density

Water vapor 

concentration

C_H20 Molecules cm3 Calculated from 

qvapor

#EQUATIONS!{!racm1mim!}

{001}!NO2+hv=O3P+NO!:!j(Pj_no2)!;

{002}!O3+hv=O1D{+O2}!:!j(Pj_o31d)!;

...

{242}!MACP+HO2=MAHP!:!ARR2(!1.82e113!,!11300.0,!TEMP!)!;

{243}!MACP+MACP=HACE+MGLY+0.5!HCHO+0.5!CO+HO2!:!2.00e112!;

{244}!MSACP+NO2=MPAN!:!TROE(!9.70e129!,!5.6!,!9.30e112!,!1.5!,!TEMP,!C_M)!;

...
49

Example File 1: Excerpt from the KPP equation (.eqn) file for the RACMMIM (Geiger et al. 2003) mechanism.

Photolysis rates, temperatures, third body concentrations, and water vapor 

concentrations are passed down from the WRF-Chem KPP interface routines. Photolysis 

rates are stored pointwise in a 1-D array and addressed by pointers defined in the 

automatically generated interface routine. For example, the NO2 photolysis rate ph_no2 

in the Registry. EM CHEM becomes j(pj_no2) in the KPP equation file (see example in 

Example File 1). Additional variables (e.g. user calculated N2O5 hydrolysis rates) can be 

passed down by modifying .inc files in the WRFV3/chem/KPP/inc directory.

6.10 Adapting additional KPP integrators for WKC

As previously mentioned, only Rosenbrock type solvers are currently available 

for use with the WKC. Introducing additional integrators which come with KPP into 

WRF-Chem is rather straight forward, but the process can be very time consuming. The 

integrator files which come with KPP are located in the directory 

chem/KPP/kpp/kpp2.1/int. Integrators which have been adapted for WRF-Chem are 

located in a subdirectory of chem/KPP/kpp/kpp2.1/int named WRF_Conform. The 

methodology for adapting an additional solver for WRF-Chem is as follows:

• Copy the .f90 and the .def file to the WRF_Conform directory

• Add KPP ROOT as a prefix to the names of the subroutines in all subroutine and 

end subroutine statements

• Change the arguments in the SUBROUTINE (KPP_ROOT_)INTEGRATE 

statements to match the calling routine (see the existing integrator routines for an 

example)

Remove all the USE statements in which non-constant data are used. Instead pass down 

the data in the subroutine statements. And be aware that, depending on the chosen solver, 

there may be additional required steps that have not been mentioned above.

 
50

Chapter 7: Summary

Table of Contents

7.1 Summary..................................................................................................................... 50

7.2 WRF-Chem publications ............................................................................................ 51

7.1 Summary

Presented in this User’s Guide is version 3.7 of the WRF-Chem model. This 

guide is not intended to be an exhaustive report about all that is needed to set up and use 

the WRF-Chem model. While it does attempt to provide the latest and most accurate 

information about the configuration and running of the WRF-Chem model, errors or 

incomplete information may have been unintentionally presented. Also, due to the 

complexity of the model and the diverse needs of each user, there may be insufficient 

information for your particular research or operational application. If a user has questions 

regarding the model that this document fails to answer, the one should contact the WRFChem help desk at wrfchemhelp.gsd@noaa.gov, or explore the WRF community forum 

and see if the user community can povide an answer.

As was stated in beginning chapters, you will need to consider your needs and/or 

requirements for the domain of interest before beginning the simulation. This includes, 

but is not limited to the available meteorological and anthropogenic-emissions data sets. 

Also, the WRF model, and likewise the WRF-Chem model, is being continuously 

updated. Therefore, you are advised to stay involved in the WRF-Chem user community 

to be made aware of any and all updates to or issues with the code.

All WRF-Chem users are also advised to link their web browser to the WRFChem user group web page (http://www.wrf-model.org/WG11) and periodically scan the 

pages for changes and/or updates to the model. These web pages contain answers to 

frequently asked questions, or FAQ’s. So this is a good place to start when you have a 

question regarding the setup, use, or performance of the WRF-Chem model. Finally, this 

web page contains the most up to date list of relevant publications regarding the WRFChem model. When presenting, or publishing results from studies using the WRF-Chem

model, it is requested that you cite the Grell et al. (2005) and Fast et al. (2006) 

manuscripts provided in the relevant publications section of this chapter. For any 

application that uses the indirect effect, please also cite Gustafson et al. (2007). And 

likewise, when using other significant features in the WRF-Chem model, the user should 

examine the reference list on the WRF-Chem web page and cite the developer’s paper(s) 

(http://ruc.noaa.gov/wrf/WG11/References/WRF-Chem.references.htm). A more detailed 

model description with a series of papers is in the works and may appear in a new journal 

that is intended for model description papers only. 
51

7.2 WRF-Chem publications

Ahmadov, R., et al., 2012: A volatility basis set model for summertime secondary organic 

aerosols over the eastern United States in 2006, J. Geophys. Res., 117, D06301, 

doi:10.1029/2011JD016831

Barnard, J.C., J.D. Fast, G.L. Paredes-Miranda, and P.W. Arnott, 2008:

Closure on the single scattering albedo in the WRF-Chem framework using data 

from the MILAGRO campaign. Atmos. Chem. Phys. Discuss., 9, 5009-5054.

Barnard, J., J. Fast, G. Paredes-Miranda, W. Arnott, and A. Laskin, 2010: Technical 

Note: Evaluation of the WRF-Chem "Aerosol Chemical to Aerosol Optical 

Properties" Module using data from the MILAGRO campaign. Atmos. Chem. 

Phys., 10, 7325-7340.

Barth, M., C., J. Lee, A., Hodzic, G. Pfister, W. C. Skamarock, J. Worden, J. Wong, and 

D. Noone, 2012: Thunderstorms and upper troposphere chemistry during the early 

stages of the 2006 North American Monsoon, Atmos. Chem. Phys. Discuss., 12,

16407-16455, doi:10.5194/acpd-12-16407-2012.

Beck, V., T. Koch, R. Kretschmer, J. Marshall, R. Ahmadov, C. Gerbig, D. Pillai, and M. 

Heimann, 2011: The WRF Greenhouse Gas Model (WRF-GHG) Technical 

Report No. 25, Max Planck Institute for Biogeochemistry, Jena, Germany, 

available online at http://www.bgc-jena.mpg.de/bgc-systems/index.shtml.

Chapman, E.G., W.I. Gustafson Jr., R.C. Easter, J.C. Barnard, S.J. Ghan, M.S. Pekour, 

and J.D. Fast, 2008: Coupling aerosols-cloud-radiative processes in the WRFchem model: Investigating the radiative impact of large point sources. Atmos. 

Chem. Phys., 9, 945-964.

Darby, LS; McKeen, SA; Senff, CJ; White, AB; Banta, RM; Post, MJ; Brewer, WA; 

Marchbanks, R; Alvarez, RJ; Peckham, SE; Mao, H; Talbot, R, 2007: Ozone 

differences between near-coastal and offshore sites in New England: Role of 

meteorology. J. Geophys. Res.-Atmos., 112 ( D16 ), Art No. D16S91, issn: 0148-

0227, ids: 208QX, 31-Aug 2007.

Delle Monache, L., J. Wilczak, S. McKeen, G. Grell, M. Pagowski, S. Peckham, R. Stull, 

J. McHenry, and J. McQueen, 2007: A Kalman-filter bias correction method 

applied to deterministic, ensemble averaged, and probabilistic forecasts of surface 

ozone, Tellus, TeB-07-06-0034.R1, accepted 10/23/07. 

Djalalova, I; Wilczak, J; McKeen, S; Grell, G; Peckham, S; Pagowski, M; 

DelleMonache, L; McQueen, J; Tang, Y; Lee, P; McHenry, J; Gong, W; Bouchet, 

V; Mathur, R, 2010: Ensemble and bias-correction techniques for air quality 

model forecasts of surface O-3 and PM2.5 during the TEXAQS-II experiment of 
52

2006. Atmos. Environ., 44 (4) 455-467, issn: 1352-2310, ids: 556TD, doi: 

10.1016/j.atmosenv.2009.11.007

Eder, B., D. Kang, A. Stein, J. McHenry, G. Grell, and, S. Peckham, 2005: The New 

England Air Quality Forecasting Pilot Program: Development of an Evaluation 

Protocol and Performance Benchmark. Journal of the Air and Waste Management 

Association, 55, 20-27. 

Fast, J. , D., W. I. Gustafson, Jr., R. C. Easter, R. A. Zaveri, J. C. Barnard, E. G. 

Chapman, G. A. Grell, and S. E. Peckham, 2006: Evolution of ozone, particulates, 

and aerosol direct radiative forcing in the vicinity of Houston using a fully 

coupled meteorology-chemistry-aerosol model, J. Geophys. Res., 111, D21305, 

doi:10.1029/2005JD006721.

Fast, J.D., B. de Foy, F. Acevedo Rosas, E. Caetano, G. Carmichael, L.

Emmons, D. McKenna, M. Mena, W. Skamarock, X. Tie, R.L. Coulter, J.C.

Barnard, C. Wiedinmyer, and S. Madronich, 2007: A meteorological overview of

the MILAGRO field campaigns. Atmos. Chem. Phys., 7, 2233-2257.

Fast, J.D., A. Aiken, L.Alexander, T. Campos, M. Canagaratna, E. Chapman, P.

DeCarlo, B. de Foy, J. Gaffney, J.de Gouw, J.C. Doran, L. Emmons, A. Hodzic,

S. Herndon, G. Huey, J. Jayne, J. Jimenez, L. Kleinman, W. Kuster, N.

Marley, Carlos Ochoa, T. Onasch, M. Pekour, C. Song, C. Warneke, D.

Welsh-Bon, C. Wiedinmyer, X.-Y. Yu, and R. Zaveri, 2009: Evaluating

simulated primary anthropogenic and biomass burning organic aerosols during

MILAGRO: Implications for assessing treatments of secondary organic

aerosols. Atmos. Chem. Phys., 9, 6191-6215, doi: 10.5194/acp-9-6191-2009.

Freitas, S. R., Longo, K. M., Alonso, M. F., Pirre, M., Marecal, V., Grell, G., Stockler, 

R., Mello, R. F., Sanchez Gacita, M., 2011. PREP-CHEM-SRC 1.0: a 

preprocessor of trace gas and aerosol emission fields for regional and global 

atmospheric chemistry models. Geosci. Model Dev., 4, 419-433.

Frost, G. J., S. A. McKeen, M. Trainer, T. B. Ryerson, J. S. Holloway,D. T. Sueper, T. 

Fortin, D. D. Parrish, F. C. Fehsenfeld, S. E. Peckham, G. A. Grell, D. Kowal, J. 

Cartwright, N. Auerbach, and T. Habermann, 2006: Effects of Changing Power 

Plant NOx Emissions on Ozone in the Eastern United States: Proof of concept, J. 

Geophys. Res., 111, D12306. 

Guenther, A., T. Karl, P. Harley, C. Wiedinmyer, P. I. Palmer, C. Geron (2006) Estimates 

of global terrestrial isoprene emissions using MEGAN (Model of Emissions of 

Gases and Aerosols from Nature), Atmos. Chem. Phys., 6, 3181-3210.

Grell G.A., J. D. Fast, W. I. Gustafson Jr, S. E. Peckham, S. A. McKeen, M. Salzmann, 

and S. Freitas. 2010: On-line Chemistry within WRF: Description and Evaluation 

of a State-of-the Art Multiscale Air Quality and Weather Prediction Model. In 
53

press. Integrated Systems of Meso-Meterological and Chemical Transport 

Models.

Grell, G. A., S. R. Freitas, M. Stuefer and J. Fast, 2011: Inclusion of biomass burning in 

WRF-Chem: impact of wildfires on weather forecasts, Atmos. Chem. Phys., 11, , 

5289-5303. doi:10.5194/acp-11-5289-2011.

Grell, G. A., S. E. Peckham, R. Schmitz, S. A. McKeen, G. Frost, W. C. Skamarock and 

B. Eder, 2005: Fully coupled online chemistry within the WRF model, Atmos. 

Environ., 39, 6957-6975.

Gustafson Jr., W.I., E.G. Chapman, S.J. Ghan, and J.D. Fast, 2007: Impact on modeled 

cloud characteristics due to simplified treatment of uniform cloud condensation 

nuclei during NEAQS 2004. Geophys. Res. Lett., 34, L19809.

Kim, S.-W., A. Heckel, S.A. McKeen, G.J. Frost, E.-Y. Hsie, M.K. Trainer, A. Richter, J.

Burrows, S.E. Peckham, and G.A. Grell, 2006: Satellite-Observed US Power 

Plant NOx Emission Reductions and Impact on Air Quality, Geophysical 

Research Letters, 33, L22812, doi:10.1029/2006GL026310, 2006. 

Matsui, H., M. Koike, Y. Kondo, N. Takegawa, K. Kita, J.D. Fast, R. Zaveri,

L. Peng, Y. Wang, G. Song, D. R. Blake, D. G. Streets, and T. Zhu, 2009:

Spatial and temporal variations of aerosols around Beijing in the summer

2006: Model Evaluation and Source Apportionment. J. Geophys. Res., 114,

D00G13, doi: 10.1029/2008JD010906.

McKeen, S., J. Wilczak, G. Grell, I. Djalalova, S. Peckham, E.-Y. Hsie, W. Gong, V. 

Bouchet, S. Menard, R. Moffet, J. McHenry, J. McQueen, Y. Tang, G. R. 

Carmichael, M. Pagowski, A. Chan, T. Dye, 2005: Assessment of an ensemble of 

seven real-time ozone forecasts over Eastern North America during the summer 

of 2004. J. Geophys. Res., 110, D21307.

McKeen, S., J. Wilczak, G. Grell, I. Djalalova, S. Peckham, E.-Y. Hsie, W. Gong, V. 

Bouchet, S. Menard, R. Moffet, J. McHenry, J. McQueen, Y. Tang, G. R. 

Carmichael, M. Pagowski, A. Chan, T. Dye, 2005: Assessment of an ensemble of 

seven real-time ozone forecasts over Eastern North America during the summer 

of 2004. J. Geophys. Res., 110, D21307.

Neu, J. L. and Prather, M. J., 2012: Toward a more physical representation of 

precipitation scavenging in global chemistry models: cloud overlap and ice 

physics and their impact on tropospheric ozone, Atmos. Chem. Phys., 12, 3289-

3310, doi:10.5194/acp-12-3289-2012.

Ntelekos, A., J.A. Smith, L. Donner, J.D. Fast, E.G. Chapman, W.I. Gustafson

Jr., and W.F. Krajewski, 2009: Effect of aerosols on intense convective
54

precipitation in the northeastern U.S. Q. J. Roy. Meteor. Soc.,135, 1367-1391. doi: 

10.1002/qj.476.

Pagowski, M; Grell, GA; McKeen, SA; Peckham, SE; Devenyi, D., 2010: Threedimensional variational data assimilation of ozone and fine particulate matter 

observations: some results using the Weather Research and Forecasting -

Chemistry model and Grid-point Statistical Interpolation. Q. J. R. Meteorol.

Soc., 136 Part B (653) 2013-2024, issn: 0035-9009, ids: 694QO, doi: 

10.1002/qj.700. 

Pagowski, M., G. A. Grell, S. A. McKeen, D. Devenyi, J. M. Wilczak, V. Bouchet, W. 

Gong, J. McHenry, S. Peckham, J. McQueen, R. Moffet and Y. Tang, 2005: A 

Simple method to improve ensemble-based ozone forecasts, Geophys. Res. 

Letters, 32, L07814.

Pagowski, M; Grell, GA, 2006: Ensemble-based ozone forecasts: Skill and economic 

value. J. Geophys. Res.-Atmos.: Vol. 111

Pagowski, M., G.A. Grell, D. Devenyi, S.E. Peckham, S.A. McKeen, W. Gong, L. Delle 

Monache, J.N. McHenry, J. McQueen and P. Lee, 2006: Application of dynamic 

linear regression to improve the skill of ensemble-based deterministic ozone 

forecasts, Atmos. Environ., 40, 3240-3250.

Pfister,G. G., D. D. Parrish, H. Worden, L. K. Emmons, D. P. Edwards, C. Wiedinmyer, 

G. S. Diskin, G. Huey, S. J. Oltmans, V. Thouret, A. Weinheimer, and A. 

Wisthaler, 2011: Characterizing summertime chemical boundary conditions for 

airmasses entering the US West Coast, Atmos. Chem. Phys., 11, 1769-1790.

Pfister, G.G., J. Avise, C. Wiedinmyer, D. P. Edwards, L. K. Emmons, G. D. Diskin, J. 

Podolske, and A. Wisthaler, 2011: CO source contribution analysis for California 

during ARCTAS-CARB, Atmos. Chem. Phys., 11, 7515-7532, doi:10.5194/acp11-7515-2011.

Sakulyanontvittaya, T., T. Duhl, C. Wiedinmyer, D. Helmig, S. Matsunaga, M. Potosnak, 

J. Milford, A. Guenther, 2008: Monoterpene and Sesquiterpene Emission 

Estimates for the United States. Environmental Science & Technology, 42 (5),

1623–1629.

Shrivastava, M., Fast, J., Easter, R., Gustafson Jr., W. I., Zaveri, R. A., Jimenez, J. L.,

Saide, P., and Hodzic, A., 2011: Modeling organic aerosols in a megacity: 

comparison of simple and complex representations of the volatility basis set 

approach, Atmos. Chem. Phys., 11, 6639-6662, doi:10.5194/acp-11-6639-2011.

Wiedinmyer, C., Akagi, S. K., Yokelson, R. J., Emmons, L. K., Al-Saadi, J. A., 

Orlando, J. J., and Soja, A. J.: The Fire INventory from NCAR (FINN): a high 
55

resolution global model to estimate the emissions from open burning, Geosci. 

Model Dev., 4, 625-641, doi:10.5194/gmd-4-625-2011, 2011. 

Wilczak, J., S. McKeen, I. Djalalova, G. Grell, , S. Peckham, W. Gong, V. Bouchet, R. 

Moffet, J. McHenry, J. McQueen, P. Lee, Y. Tang, G. R. Carmichael: Biascorrected ensemble and probabilistic forecasts of surface ozone over eastern 

North America during the summer of 2004, J. Geophys. Res.-Atmos., Vol. 111, 

D23, D23S28, doi:10.1029/2006JD007598, 2006. 

Yang, Q., W.I. Gustafson Jr., J.D. Fast, H. Wang, R.C. Easter, H. Morrison Y.-N. Lee, 

E.G. Chapman, S.N. Spak, and M.A. Mena-Carrasco, 2011: Assessing regional 

scale predictions of aerosols, marine stratocumulus, and their interactions during 

VOCALS-REx using WRF-Chem. Atmos. Chem. Phys., 11, 11951-11975.

Zhao, C., X. Liu, L.R. Leung, B. Johnson, S. McFarlane, W.I. Gustafson Jr., J.D. Fast, 

and R. Easter, 2010: The spatial distribution of dust and its short wave radiative 

impact over North Africa: Modeling sensitivity to dust emissions and aerosol size 

treatments. Atmos Chem. Phys., 10, 8821-8838.

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applications. Atmos. Environ., 32 (17), 2981–2999.

Ahmadov, R., C. et al., 2009: Comparing high resolution WRF-VPRM simulations and

two global CO2 transport models with coastal tower measurements of CO2. 

Biogeosciences, 6(5), 807-817.

Beck V., T. Koch, R. Kretschmer, J. Marshall, R. Ahmadov, C. Gerbig, D. Pillai, and M. 

Heimann (2011): The WRF Greenhouse Gas Model (WRF-GHG), Technical 

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Binkowski, F.S., U. Shankar, 1995: The regional particulate matter model, 1. Mode 

description and preliminary results. J. Geophys. Res., 100, 26191–26209. 

Boucher, O., and U. Lohmann, 1995: The sulfate-CCN-cloud albedo effect, A sensitivity

study with two general circulation models. Tellus, 47B, 281-300.

Carey, S. N., and H. Sigurdsson (1982), Influence of particle aggregation on deposition 

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61

Appendix A: WRF-Chem Quick Start Guide

1. Compiling WRF-Chem

a. Download the WRF and then the WRF-Chem from the NCAR web site 

http://www2.mmm.ucar.edu/wrf/users/download/get_sources.htm

b. Set the environmental variables

i. setenv WRF_CHEM 1

ii. setenv EM_CORE 1

iii. setenv FLEX_LIB_DIR /usr/lib (optional)

iv. setenv WRF_KPP 1 (optional)

v. setenv YACC ‘/usr/bin/yacc –d’ (optional)

c. Compile WRF-Chem using the command: 

compile em_real >& compile.log

2. Running WRF-Chem with the chemistry turned off

a. Decide which emissions preprocessor you will need to run (step 3 or step 

6, see also section 2 in the WRF-Chem User’s Guide). This is important, 

since step 6 requires the user to select a polar stereographic projection for 

the forecast domain.

b. Produce meteorological input files (wrfinput_d01 and wrfbdy_d01) for the 

domain of your choice (save these, they will be needed later). Use the 

WPS to do this. Be sure to choose the map projection based upon your 

desired emissions data set.

c. First run a meteorology-only simulation to verify the domain you want is 

functioning correctly, the code has compiled properly, and no issues exist 

from the meteorological part of the model (set chem_opt=0 in the name 

list).

i. Modify the namlist.input file (to fit your needs and be sure to set 

chem_opt=0)

ii. Run real.exe to produce a wrfinput and wrfbdy file

iii. Run wrf.exe to produce a forecast

iv. Check the resulting output files to verify your forecast results
62

3. Producing an emissions-input file for your forecast domain using 

the global RETRO/EDGAR emissions data set and 

prep_chem_sources

a. Get the latest version of the prep_chem_sources tar files from the ESRL 

web site, including the documentation 

ftp://aftp.fsl.noaa.gov/divisions/taq/global_emissions

b. Compile prep_chem_sources following the instructions in the README 

file 

c. Modify the prep_sources_chem.inp file for correct domain, and choice of 

input data

d. Run prep_sources_chem to generate emissions data file

e. From your WRF-Chem run directory, link output files (e.g., WRF-2008-

07-15 files) from prep_sources_chem_cptec_wrf

i. ln –sf ../../../Prep_sources_chem_cptec_wrf/WRF-2008-07-15-

000000-g1-gocartBG.bin wrf_gocart_backg

ii. ln –sf ../../../Prep_sources_chem_cptec_wrf/WRF-2008-07-15-

000000-g1-ab.bin emissopt3_d01

iii. ln –sf ../../../Prep_sources_chem_cptec_wrf/WRF-2008-07-15-

000000-g1-bb.bin emissfire_d01

iv. ln –sf ../../../Prep_sources_chem_cptec_wrf/WRF-2008-07-15-

000000-g1-volc.bin volc_d01

f. Edit your name list.input to reflect the switch to global-emissions data and 

run convert_emiss.exe. Typically this will require a change to the update 

interval, the emissions option and possibly the vertical dimension for the 

emissions. For example, the global data is updated on a monthly basis and 

is surface data only. So for a typical simulation of a couple of days the 

emissions data will not be updated (auxiliary input port time intervals are 

set to a very large number of seconds) and the name list modified for 

surface only emissions (kemit =1). In addition, the RETRO/EDGAR 

emissions are for just a few emitted species and the emiss_opt=5 is most 

often used for this data set.

g. Run the convert_emiss program. It is acceptable if the program was 

compiled with the distributed memory (dmpar only) as it will run with one 

or multiple processors. The WRF input files that should be generated are: 

wrfinput_d01 (2a), the files from set (e.) above, and your WRF name 

list.input. 
63

h. Check whether the program successfully produced the emissions input 

(wrfchemi_d01 or wrfchemv_d01, wrffirechemi_d01 and 

wrfchemi_gocart_bg_d01). These should all be netcdf files if you 

specified that I/O form in your name list.input file and so you can check 

the data with utilities like ncview or ncbrowse.

4. Running WRF-Chem (multiple processors may be necessary due 

to large memory requirements, depending on your domain size)

a. Modify the name list to suit your needs (check Chapter 3 of the User’s 

Guide to select your name list options, and Chapter 4 as guidance for some 

typical setups)

b. Run real.exe to produce the wrfinput file that includes chemistry. Check 

the output using ncview or ncbrowse or similar programs

c. Confirm that you have the emissions files for the simulation in the run 

directory. If necessary, rename your emissions files (or link them) to the 

files wrfchemi_00z_d01 and/or wrfchemi_12z_d01 (for 

io_style_emissions=1)

d. Run wrf.exe.

e. Inspect the model results to make sure your name list.input settings were 

correct

5. Visualizing the output can be done with various packages, 

including ncview, NCL, RIP, ncbrowse, GrADS

The output from the WRF-Chem model is a standard WRF output netCDF data 

file. Therefore, your favorite netCDF data file viewer can be used to examine 

results. For example, the ncview program will allow the users to quickly view the 

model output.
64

Additional Options

6. Using the NEI data set for domains located over the USA

a. Download the emiss_v03.F program and the emission data from the ESRL 

anonymous ftp site, or through your web browser by setting the URL to: 

ftp://aftp.fsl.noaa.gov/divisions/taq/emissions_data_2011

b. Modify the emiss_v03.F program file to correspond to your domain setup 

(see also chapter of the WRF-Chem Emissions Guide).

c. Compile emiss_v03.F

i. There are examples provided at the beginning of the program like 

for the case when using pgi, the suggested compile commands 

would be 

> pgf90 –w –byteswapio –Mfree –Mlfs –o emiss_v03.exe emiss_v03.F

d. Run emiss_v03.exe to produce an emissions file for a domain located over 

the contiguous states. Two binary data files will be produced called 

wrfem_00to12Z and wrfem_12to24Z. You can re-name them after the 

simulation run, or edit the emiss_v03.F to have the program produce a 

name that suits your liking.

e. Move the binary output files with the prefix “wrfem” from where you 

have run the program to WRFV3/run for use later on by the 

convert_emiss.exe program.

f. Go to the test/em_real directory and link the binary emissions files from 

(3e) to the files that are used by the WRF-Chem code

i. ln –sf wrfem_00to12Z wrfem_00to12z_d01

ii. ln –sf wrfem_12to24Z wrfem_12to24z_d01

g. Modify the name list.input file to have the correct update time interval 

(auxinput5_interval_m for anthropogenic emissions.) for each auxiliary 

input. Default output time interval from emiss_v03 is 3600 seconds. You 

should also set the correct emission input option (emiss_opt=3 for NEI 

emissions, or emiss_opt=5 for RETRO/EDGAR) for the anthropogenic 

emissions and your choice of chem_opt (see chapter 2 of the WRF-Chem 

Emissions Guide). In addition, the NEI emissions include smoke stack 

emissions so the input data will have a vertical dimension set with the 

kemit option.

h. Run the convert_emiss program. Run this program with one processor 

only. It is acceptable if the program was compiled with the distributed 
65

memory option, but do not run it with more than 1 processor. Required 

input files are: wrfinput_d01 (2a), wrfem_00to12z_d01 and/or 

wrfem_12to24z_d01 (3f), and name list.input. 

i. Check whether the program successfully produced the emissions input 

(wrfchemi_d01_xxz or wrfchemi_d<domain>_<date>). These are netcdf 

files, you can check them with ncview or ncbrowse.

7. Special biogenic emissions files

There are four choices in the model for biogenic emissions.

 

a. The first option is not to use an additional biogenic-emissions input data 

file (bio_emi_opt= 0). The user could add the biogenic emission to the 

anthropogenic-emissions data if it is desired. Be sure to do this for every 

time period in the emissions input data and not just the first time.

b. For the second option (bio_emi_opt= 1), the model calculates the biogenic 

emissions online using the USGS land-use classification, which is 

generated by WRF WPS and available for the meteorological and 

chemical model. 

c. For the third option, the user-specifies reference fields for the biogenic 

emissions, which are then modified online by a subroutine from the 

Biogenic Emissions Inventory System (BEIS) version 3.14. The land-use 

for this emissions inventory is obtained from the Biogenic Emissions 

Landuse Database version 3 (BELD3). The reference fields need to be 

provided as an additional input data file (wrfbiochemi_d01) for the 

real.exe program. 

d. The final option is the use of MEGAN, which again requires the 

preparation of reference fields (Chapter 3 of the WRF-Chem Emissions

Guide)

8. Nesting

a. Produce wrfinput files for both domains following Chapter 4 of WRF 

User’s Guide

b. Like the single domain WRF-Chem simulations, it is probably best to 

make a nested domain weather forecast (Chapter 5 of WRF User’s Guide) 

c. Generate the emissions files for both domains using the emiss_v03.F 

program (section 3 of Quick Step Guide, Chapter 2 of the WRF-Chem
66

Emissions Guide). File names will need to differentiate between the 

domains (e.g., wrfem_00to12z_d01 and wrfem_00to12z_d02)

d. The convert_emiss.exe program is not currently designed to read the name 

list.input file and generate the nested domain emissions files. Therefore, 

run the conversion program treating the nested domain as if it was actually 

the mother domain 

i. Follow 3f – 3i to generate wrfchemi_d01 for the coarse domain, 

move it to a safe place so that they will not be overwritten

ii. Change the name list.input file. Moving the nested information to 

the mother domain column

iii. Move the met wrfinput_d02 to wrfinput_d01

iv. Link the output from emisv03 (for the nested domain) to the 

required filenames (see 3h)

v. Run convert_emiss.exe

vi. Move the resulting wrfchemi_d01 to wrfchemi_d02

e. Modify the name list.input file to set the chemistry name list variables for 

the nested domain 

9. Boundary conditions from larger scale models

At this time, tools are still under development to provide larger scale data from 

models other than WRF as boundary and initial conditions to the WRF-Chem

simulations. One such utility program that is available from NOAA/ESRL is 

called wrfchembc. This program currently works with data from the MPIMATCH and RAQMS global chemistry models. 

a. Download the latest version of the code from the ESRL ftp site. For 

example, the latest code might be named

ftp://aftp.fsl.noaa.gov/divisions/taq/broken_experimental/wrfchemv2.2

_bcond_code_09Apr07.tar

b. Modify the Makefile to use your desired compile options and compile 

to generate the wrfchembc executable

c. Modify the wrfchembc_name list.input file to have the correct data 

directories and species added to the boundary data file (wrfbdy_d01)
67

d. Run the wrfchembc program after real.exe and before wrf.exe to add 

the global model data to the lateral boundary data file (wrfbdy_d01)

e. Before running wrf.exe, modify the name list.input to set 

have_bcs_chem = .true

f. Make a forecast using wrf.exe and inspect the model results to make 

sure your name list.input settings were correct

Another tool for generating chemica lateral boundary conditions is available from 

NCAR/ACD and is called mozbc. The mozbc utility and is provided to the 

community at the NCAR/ACD website http://www.acd.ucar.edu/wrf-chem and 

along with the code the user can obtain MOZART model data for the dates and 

location of interest. The user is directed to the NCAR/ACD web site for the 

latest information regarding this utility.
68

Appendix B: Using MOZART with WRF-Chem

Introduction

The National Center for Atmospheric Research (NCAR) provides Fortran source code to 

prepare additional data files to support the MOZART (Model for OZone And Related 

chemical Tracers) gas-phase chemistry scheme in WRF-Chem. These files are needed to 

update WRF-Chem parameters suitable for MOZART. MOZART gas-phase chemistry 

can be combined with GOCART aerosol treatment – known as MOZCART in this 

manual.

When setting up WRF-Chem to use MOZART/MOZCART, the user should select the 

FTUV photolysis option (phot_opt=3) in the name list.input file. NCAR advises the 

FTUV code has been updated to read in O3 and O2 climatological atmospheric column 

values rather than fixed values. This requires an additional input file for each domain –

exo_coldens_d<nn> (nn = domain number). The exo_colden utility (for single CPU) 

reads WRF-and MOZART-input files and produces netCDF files for each WRF domain.

When using dry deposition in WRF-Chem (gas_drydep_opt=1) combined with 

MOZART (and MOZCART) scheme in WRF-Chem, NCAR advises that an additional 

file for each domain is required – wrf_season_wes_usgs_d<nn> (nn = domain number). 

The wesely utility (for single CPU) reads WRF and MOZART input files and produces 

netCDF files for each WRF domain.

The tar file from NCAR includes a helpful readme file which expands on the instructions 

below. NCAR provides some information at http://www.acd.ucar.edu/wrfchem/MOZCART_UsersGuide.pdf which provides a table mapping MOZART emissions 

species to EPA/NEI species as well as contact details at NCAR for further support.

Compiling

1) Download the MOZART preprocessor Fortran source code from 

http://www.acd.ucar.edu/wrf-chem/. You will be asked to register some contact details 

– subsequently click the “preprocessor” button on the user registration page to 

download the MOZART Fortran source code, makefile, and MOZART-data input 

files. The files can be downloaded to a directory of your choice – note that the process 

of using MOZART needs to access the WRF run directory and the wrfinput_d01 file 

during MOZART data preprocessing.

2) Un-tar the files downloaded in a directory of your choice by issuing the commands:

>tar –xvf wes_coldens.tar

3) Compile the MOZART source code by issuing the commands:
69

>make_util wesely

>make_util exo_coldens

This will create the executable files – wesely and exo_coldens.

Preprocessing

4) The wesely program reads WRF wrfinput_d<nn> files and a MOZART-data file 

containing dry emission parameters - season_wes_usgs.nc (found in the tar file above). 

Adjust the text file wesely.inp for:

1. domains – the number of domains used in your WRF model

2. pft_flnm – season_wes_usgs.nc

3. wrf_dir – the directory where the associated wrfinput_d<nn> resides, and

4. pft_dir – the directory in which the MOZART data file exists 

5) To create the wesely data files for MOZART, issue the command:

>wesely < wesely.inp > wesely.out

This creates a file for each domain wrf_season_wes_usgs_d<nn> which should be 

copied to the WRF run directory for use in WRF-Chem MOZART/MOZCART model 

runs.

6) The exo_colden program reads WRF wrfinput_d<nn> files and a MOZART data file 

exo_coldens.nc (found in the tar file above). Adjust the text file exo_coldens.inp for:

A. domains – the number of domains used in your WRF model

B. exo_flnm – exo_coldens.nc

C. wrf_dir – the directory where the associated wrfinput_d<nn> resides, and

D. exo_dir – the directory in which the MOZART data file exists 

7) To create the exo_coldens data files for MOZART, issue the command:

>exo_coldens < exo_coldens.inp > exo_coldens.out

This creates a file for each domain exo_coldens_d<nn> which should be copied to the 

WRF run directory for use in WRF-Chem MOZART/MOZCART model runs.

Running WRF-Chem with MOZART (MOZCART)

8) Selecting the MOZART/MOZCART settings in the name list.input of the WRF-Chem 

run directory (chem_opt and emiss_opt) will switch on the ingestion of the files noted 

above into WRF-Chem.
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Appendix C: Using the Lightning-NOx 

Parameterization in WRF-Chem

The WRF-Chem model has a parameterization able to provide an estimate of the 

lightning-generated nitrogen oxides production (LNOx). The LNOx parameterization is 

based on the Price and Rind (1992, hereafter PR92) schemes with modifications based on 

Barth et al. (2012) and Wong et al. (2013). To determine LNOx, the lightning flash rate, 

the location (both horizontally and vertically), and the amount of NO produced per flash 

must be estimated. The lightning flash rate parameterization is located in the physics 

directory using module_lightning_driver.F, which is called from dyn_em/solve_em.F. 

The location and production of NO per flash parameterization is located in the chem 

directory using module_lightning_nox_driver.F, which is called from emissions_driver.F. 

The parameterization of lightning-generated NOx is valid for both parameterized 

convection and resolved convection, but different parameters may be used. Details on the 

parameters used in the namelist.input file are explained next.

Physics section:

To turn on the lightning flash rate parameterization in WRF, set the physics name 

list option lightning option to one of the following values:

lightning_option Description

1

PR92 based on maximum w; distributes flashes within dBZ > 20

For convection-resolved resolutions with microphysics turned on for 

reflectivity calculations.

2

PR92 based on 20 dBZ cloud top; distributes flashes within dBZ > 20

For convection-resolved resolutions with microphysics turned on for 

reflectivity calculations.

11

PR92 based on level of neutral buoyancy obtained from convective 

parameterization

For convection-parameterized resolution using either GD or G3 cu 

physics options. Adjusted by areal ratio relative to dx=36 km (Wong 

et al., 2013), intended for use at 10 < dx < 50 km.

Setting the lightning option will produce four new 2D arrays: ic_flashrate, cg_flashrate 

both with units number per second, and ic_flashcount, cg_flashcount with units number 

of flashes, where ic and cg represent intra-cloud and cloud-to-ground, respectively. The 

ic_flashrate and cg_flashrate arrays are instantaneous output that can be used to diagnose 

the lightning flashrate and LNOx parameterizations. The arrays ic_flashcount, 

cg_flashcount accumulate the number of flashes during the simulation. To find the 

number of flashes between output times, simply subtract the flashcount array from the 

previous output time from the current output time to get number of flashes per dt (where 
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dt = time between output files).

Set the physics name list option iccg_method to control the IC:CG ratio:

iccg_method Description

0 Default method depending on lightning_option, currently all options 

use iccg_method=2 by default.

1

Constant everywhere, set with name list options 

iccg_prescribed_num (numerator) and iccg_prescribed_den 

(denominator). 

2 Coarsely prescribed 1995–1999 NLDN/OTD climatology based on 

Boccippio et al. (2001).

3 Parameterization by Price and Rind (1993) based on cold-cloud 

depth.

4 Gridded input via arrays iccg_in_num (numerator) and iccg_in_den 

(denominator) from wrfinput for monthly mapped ratios. 

Additional name list settings in the physics section are available for more detailed control 

of the parameterization: 

Name list Option Description

iccg_prescribed_num Prescribes numerator of IC:CG ratio. Used by iccg method=1,4 

Default = 0

iccg_prescribed_den Prescribes denominator of IC:CG ratio. Used by iccg 

method=1,4 Default = 1

iccg_in_num

Gridded array from the wrfinput file for monthly mapped 

IC:CG ratios. iccg_in_num is the numerator of the ratio. 

Gridpoints with iccg_in_num=0 and iccg_in_den=0 values use 

ratio defined by iccg_prescribed_num and 

iccg_prescribed_den. See more information below.

iccg_in_den

Gridded array from the wrfinput file for monthly mapped 

IC:CG ratios. iccg_in_den is the denominator of the ratio. 

Gridpoints with iccg_in_num=0 and iccg_in_den=0 values use 

ratio defined by iccg_prescribed_num and 

iccg_prescribed_den. See more information below.

lightning dt Time interval (seconds) for calling lightning parameterization. 

Default uses model time step.

lightning start seconds Start time for calling lightning parameterization. Recommend 
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at least 10 minutes for spin-up.

flashrate factor

Factor to adjust the predicted number of flashes. Recommend 

1.0 for lightning option=11 between dx=10 and 50 km. Manual 

tuning recommended for all other options independent for each 

nest.

cellcount method

Method for counting storm cells. Used by CRM options 

(lightning options=1,2). 

0 = model determines method used.

1 = tile-wide, appropriate for large domains

2 = domain-wide, appropriate for single-storm domains

cldtop_adjustment Adjustment from LNB in km. Used by lightning option =11. 

Default is 0, but recommends 2 km.

Gridded data of the IC:CG ratios written in the form of a ratio numerator and 

denominator (iccg_in_num and iccg_in_den) can be read from the wrfinput file to 

prescribe the IC to CG flash ratio. To get the gridded data into the wrfinput file, the user 

needs to interpolate the IC:CG ratio dataset to the WRF grid as a pre-processing step. The 

user also needs to provide his/her own dataset.

Chemistry section:

To emit LNOx, in the form of nitrogen oxide (NO), set the chem name list option 

lnox_opt to one of the following values:

lnox_option Description

1 Combined IC+CG single-mode vertical distributions (Ott et al., 

2010). Outputs passive tracer array in addition to the NO source.

2

Separate IC, CG vertical distributions following DeCaria et al. 

(2000). In addition to providing a source to NO, outputs two passive 

tracer arrays lnox_ic and lnox_cg.

Additional chem name list settings are available for more detailed control of the 

parameterizations:

Name list Option Description

N_IC

Moles of NO emitted per IC flash. For lnox opt=1, the total 

number of moles NO per flash is the weighted average based on 

the calculated IC:CG ratio of N_IC and N_CG. Default is 500 

moles. 
73

N_CG

Moles of NO emitted per CG flash. For lnox opt=1, the total 

number of moles NO per flash is the weighted average based on 

the calculated IC:CG ratio of N_IC and N_CG. Default is 500 

moles. 

lnox_passive Set to .true. to emit passive tracers only.

Set to .false. to emit both NO and passive tracer. 

Default = .false.

ltng_temp_upper Temperature (C) of upper peak of LNOx vertical distribution for 

IC lightning (used by lnox opt=2).

ltng_temp_lower Temperatures (C) of lower peak of LNOx vertical distribution 

for both IC and CG lightning (used by lnox opt=2).

For further information, please contact Mary Barth (barthm@ucar.edu) or John Wong 

(jwong.colorado@mac.com).