The GFS Global initial and boundary condition are available in grib format at:

http://nomads.ncep.noaa.gov/pub/data/nccf/com/gfs/prod/

The interested files are files like gfs.t<HOUR>z.pgrb2.0p25.f*, which are in folders like gfs.<YYYYMMDDHH>.

GeraDP software is needed to use these data in BRAMS, because the files need to be converted to BRAMS DP format. Please refer to the GeraDP guide in Documentation page for instructions on how to convert the files.

Download GeraDP at the Downloads page.

In addition to the GFS files, CPTEC produces files on grib format containing the state of the atmosphere on a Gaussian grid. These files have the initial and boundary condition to BRAMS. Bellow are the links to the files with data from South America and Europe/Africa, with the respective PREP_IN file (configuration file to data file converting application).

Resolution T126

http://ftp.cptec.inpe.br/modelos/io/tempo/global/T126L28/

PREP_IN (South America)

PREP_IN (Europe/Africa)

Resolution T213

http://ftp.cptec.inpe.br/modelos/io/tempo/global/T213L42/

PREP_IN

To use these files, grib2dp software is necessary to convert the grib files to the DP format for BRAMS. The grib2dp will be avaiable soon here.

If you have any question, contact us (atende.cptec@inpe.br)

Contains the global landuse data for BRAMS at 30s, or about 1km resolution. Each file contains 5×5 degree blocks, with the filename denoting the southwest corner. The USGS dataset is based on 1-km Advanced Very High Resolution Radiometer (AVHRR). For the Amazonia (Brazilian Rain Forest), the data was updated by PROVEG/INPE

INPE Global Set (28 MB)

To use this files, set the IVEGTFN variable in RAMSIN namelist $MODEL_FILE_INFO, as showed in the following example:

IVEGTFN = '<$BRAMS-DIR>/veget/OGE','<$BRAMS-DIR>/veget/OGE','<$BRAMS-DIR>/veget/OGE',

Where OGE is the file prefix and veg_oge is the directory where the data were saved.

Now, change the variable ISSTFLG, as showed bellow:

IVEGTFG = 1,1,1,1,

Note that the values used in this variable are:

0 – Interpolate from coarser grid

1 – Read from standart LAT/LON data file (default)

2 – Fill data in “leaf3_init”

Each value in the sequence define how the BRAMS will work to each grid. When one grid is used, only the first value works.

If you have any question, contact us (atende.cptec@inpe.br).

The new NHEADER file and NDVI data files for each month:

• NHEADER
• January
• February
• March
• April
• May
• June
• July
• August
• September
• October
• November
• December

To Configure the RAMSIN

To use these datas, set the NDVIFN variable in RAMSIN namelist $MODEL_FILE_INFO, as showed in the following example:

NDVIFN = '<$BRAMS-DIR>/NDVI-MODIS/N','<$BRAMS-DIR>/NDVI-MODIS/N','<$BRAMS-DIR>/NDVI-MODIS/N',

N is the prefix of the files.

Now, change the variable NDVIFLG, as showed bellow::

NDVIFLG = 1,1,1,1,

Note that the values used in this variable are:

0 – Interpolate from coarser grid

1 – Read from standart LAT/LON data file

2 – Fill data in “leaf3_init” (default)

Each value in the sequence define how the BRAMS will work to each grid. When one grid is used, only the first value works.

If you have any question, contact us (atende.cptec@inpe.br).

Contains the global weakly sea surface temperature data for RAMS. The optimum interpolation (OI) sea surface temperature (SST) analysis is produced weekely on a one-degree grid. The analysis uses in situ and satellite SST’s plus SST’s simulated by sea-ice cover. Before the analysis is computed, the satellite data is adjusted for biases using the method of Reynolds (1998) and Reynolds and Mersico (1993).

The OI.v2 analysis is described in Reynolds, R.W., N.A. Rayner, T.M. Smith, D.C. Stokes, and W. Wang, 2002: An Improved In Situ and Satellite SST Analysis for Climate, J. Climate, vol 15. The paper is available in PDF format in the site:

ftp://ftp.emc.ncep.noaa.gov/cmb/sst/papers/oiv2pap/

Please fill in the date field below with the corresponding year (2000 to current year):

To use this files, set the ISSTFN variable in RAMSIN namelist $MODEL_FILE_INFO, as showed in the following example:

ISSTFN = '<$BRAMS-DIR>/week-sst/W','<$BRAMS-DIR>/week-sst/W','<$BRAMS-DIR>/week-sst/W',

Where W is the file prefix and week-sst is the directory where the data were saved.

Now, change the variable ISSTFLG, as showed bellow:

ISSTFLG = 1,1,1,1,

Note that the values used in this variable are:

0 – Interpolate from coarser grid

1 – Read from standart LAT/LON data file (default)

2 – Fill data in “leaf3_init”

Each value in the sequence define how the BRAMS will work to each grid. When one grid is used, only the first value works.

If you have any question, contact us (atende.cptec@inpe.br).

These files have an estimate of soil moisture for initialization in weather forecast models. The files have the spatial structure in eight soil layers of the soil moisture in terms of wetness. The modelled soil moisture is able to coherently reproduce the expected patterns throughout the seasons over South America, with satisfactory
agreement on time variability. Model description and validation can be found in Gevaerd & Freitas, 2006 (in portuguese).

There are two global soil moisture data available: GPCP and GPNR. The GPCP data uses precipitation estimation from GPCP program (GPCP one-degree daily precipitation data set, provided by the NASA/Goddard Space Flight Center’s Laboratory for Atmospheres) while GPNR uses precipitation from TRMM program (http://trmm.gsfc.nasa.gov). GPCP data is available with some delay 1×1 degree space resolution; data set from 00Z/01/01/1997 to 00Z/31/12/2005 is available. GPNR is available on a daily basis (00Z and 12Z) and its resolution is 0.25 x 0.25 degree (this is data should be used for operational purposes).

Each file has the soil moisture for a specific day. In this way, the files’ names are structured like: GL_SM.GPCP.YYYYMMDD00.vfm or GL_SM.GPNR.YYYYMMDD00.vfm, where: YYYY represents the year, MM represents the month and DD represents the day of the soil moisture data.

Please fill in the date field below with the corresponding year (2000 to current year):

To Configure the RAMSIN

Set the USDATA_IN variable in RAMSIN namelist $MODEL_FILE_INFO, as showed in the following example:

USDATA_IN = '<$BRAMS-DIR>/soil-mosture/GL_SM.GPNR.'

where GL_SM.GPNR. is the file prefix of the soil moisture data.

Now, change the variable SOIL_MOIST, as showed bellow:

 SOIL_MOIST = 'i'

Note that the values used in this variable are:

n – Homogeneous (standard)

i, h, a – Heterogeneous Soil Moisture Initialization from file:

i – INITIAL run type;

h – HISTORY run type;

a – INITIAL or HISTORY run type;

In case of Heterogeneous Soil Moisture, it is possible to define how the BRAMS runs when the files were not found. To do this, set the SOIL_MOISTURE_FAIL variable as showed in this example:

SOIL_MOIST_FAIL = 'h'

The values used to define this variable are:

s – STOP the program;

h – Initialize with Homogeneous Soil Moisture;

l – look for 5 days old files, and if not found again then stop.

If you have any question, contact us (atende.cptec@inpe.br).

Contains the global soil texture data for RAMS. The dataset is originally from the UN FAO. For the Brazilian territory, the data set was updated by INPE.

FAO Global Set (0.75 MB)

To use this files, set the ISOILFN variable in RAMSIN namelist $MODEL_FILE_INFO, as showed in the following example:

ISOILFN = '<$BRAMS-DIR>/soil-fao/W','<$BRAMS-DIR>/soil-fao/W','<$BRAMS-DIR>/soil-fao/W',

Where W is the file prefix and soil-fao is the directory where the data were saved.

Now, change the variable ISOILFLG, as showed bellow:

ISOILFLG = 1,1,1,1,

Note that the values used in this variable are:

0 – Interpolate from coarser grid

1 – Read from standart LAT/LON data file

2 – Fill data in “leaf3_init” (default)

Each value in the sequence define how the BRAMS will work to each grid. When one grid is used, only the first value works.

If you have any question, contact us (atende.cptec@inpe.br).

Contains the global USGS topography dataset for BRAMS with different resolutions:

10 km (0.4 MB)

01 km (247 MB)

To use this files, set the ITOPTFN variable in RAMSIN namelist $MODEL_FILE_INFO, as showed in the following example:

ITOPTFN = '<$BRAMS-DIR>/topo/H','<$BRAMS-DIR>/topo/EL','<$BRAMS-DIR>/topo/EL',

Where H is the file prefix to 10 km resolution files, EL is the file prefix to 1 km resolution files and topo is the directory where the data were saved.

Change the variable ISSTFLG, as showed bellow:

ITOPTFLG = 1,1,1,1,

Note that the values used in this variable are:

0 – Interpolate from coarser grid

1 – Read from standart LAT/LON data file (default)

2 – Fill data in “leaf3_init”

Each value in the sequence define how the BRAMS will work to each grid. When one grid is used, only the first value works.

If you have any question, contact us (atende.cptec@inpe.br).

PREP-CHEM-SRC is a pollutant emissions numerical too developed at CPTEC/INPE whose function is to create data of atmospheric pollutant emissions from biomass burning, photosynthesis or other forest transformation processes, combustion of oil-based products by vehicles or industry, charcoal production, and many other processes.

The system is maintained and developed at CPTEC/INPE by the GMAI group, which not only updates versions of data such as EDGAR, RETRO, MEGAN, etc., but also implements new functionalities such as volcanic emissions which is present now in this version.

The purpose of PREP-CHEM guide  is to present how to install, compile and run the pre-processor. Finally, the steps for utilizing the emissions data in the BRAMS, WRF-Chem and FIM-Chem models are presented.

We recommend that you read the article “PREP-CHEM-SRC – 1.0: a preprocessor of trace gas and aerossol emission fields for regional and global atmospheric chemistry models” (Freitas et al., 2010 – here).

Download documentation for PREP-CHEM in the Documentation page.

Download PREP-CHEM software at Downloads page.

Download PREP-CHEM surface data:

GL_IGBP_MODIS_INPE
GL_OGE_INPE

Download PREP-CHEM Emission files of your interest:

EDGAR
EDGAR-HTAP
SEAC4RS
RETRO
OLSON2
GOCART
GFEDv2-8days
Emissions_Yevich_Logan
Biogenic Emissions
Carbon density
Carbon density Saatchi
Megan
Streets
Volcanic SO2

Some Fire Spots data of some places in past dates.
Fire spots data

Biomass data. 3bbem emissions biomass data are composed by MODIS, DSA and GOES(WF_ABBA). You can also can find more data at these sites:

Fire spots files from ABBA/GOES 15 – North and Central America (only the last 7 days):
ftp://128.104.108.86/pub/abba/v65/goes-15/text/

GOES-16 officially replaced GOES-13 as GOES-EAST on December 19, 2017.

Fire spots files from DSA – South America (only the last 7 days):
http://ftp.cptec.inpe.br/modelos/io/tempo/regional/BRAMS20km/datain/focos/DSA/

MODIS Global data from the site below must be treated in one software that will be turned avaiable in brams site in the future. If you need some MODIS data, you may request to us for some specific period.

ftp://fire:burnt@fuoco.geog.umd.edu

After generating the data of atmospheric pollutant emissions by the PREP-CHEM software, it’s necessary to include chemical species to initial conditions and atmospheric boundary.
For that purpose, DPREP-CHEM software must be used to include the chemical species to initial conditions and atmospheric boundary in the format required by the model.

The boundary and initial condition atmospheric files are converted files from Global GFS to the required format for DPREP-CHEM. The conversion of files is done by GeraDP program, which is also available at the Atmospheric section in this page. Please refer to the Atmospheric section for more information.

Download documentation for DPREP-CHEM in the Documentation page.

Download DPREP-CHEM software at Downloads page.