CAMS

Providentia’s download mode supports downloading model output data provided by CAMS from the Atmosphere Data Store:

https://ads.atmosphere.copernicus.eu/datasets

An ECMWF account is required to download the files. For a tutorial on how to create and set up your account, see the Account setup in Atmosphere Data Store section.

Available CAMS datasets

Currently, four CAMS datasets are available for download:

CAMS European Air Quality Forecasts
CAMS Global Atmospheric Composition Forecasts
CAMS European Air Quality Reanalyses
CAMS Global Reanalysis (EAC4)

How to enable Atmosphere Data Store download

To download CAMS data from the Atmosphere Data Store, include one of the following model names along with the domain. For details about available models, streams, and specific resolutions, see the corresponding sections below:

cams_analysis_<model>-regional — CAMS European Air Quality Forecasts
cams_forecast_<model>-regional — CAMS European Air Quality Forecasts
cams_forecast-global — CAMS Global Atmospheric Composition Forecasts
cams_reanalysis_<model>_<stream>-regional — CAMS European Air Quality Reanalyses
cams_reanalysis-global — CAMS Global Reanalysis (EAC4)

Once you have selected the dataset and specified the model and domain, make sure to set:

dl_interpolated = False

or

Answer n to the prompt:

“Model data was detected in the configuration file. Do you want to download the interpolated version? (Otherwise, the non-interpolated model data will be downloaded)”

1. CAMS European Air Quality Forecasts

Dataset Link

Using this dataset you can either download:

Regional Analysis data, or
Regional Forecast data

This dataset contains multi-level data.

Only hourly data is available in this dataset. You must set resolution = hourly in your configuration file; otherwise, the download will not work.

Mandatory fields for regional analysis data

model = cams_analysis_<model>
domain = regional
resolution = hourly

Mandatory fields for regional forecast data

model = cams_forecast_<model>
domain = regional
resolution = hourly

Replace <model> with one of the available model names listed below.

Available models

Use the following model names (same as in the API):

ensemble
chimere
dehm
emep
euradim
gemaq
lotos
match
minni
mocage
monarch
silam

Available variables (Species)

These are the available species:

pm10
pm10du
pm10so4ss
pm2p5
pm2p5ec
pm2p5nh4
pm2p5no3
pm2p5so4
sconcco
sconcglyox
sconchcho
sconcnh3
sconcnmvoc
sconcno
sconcno2
sconco3
sconcso2

Providentia can only read species in GHOST format. If you want to know the mapping from CAMS variables to GHOST species, please refer to the CAMS-GHOST species mapping section.

Assumptions

Providentia assumes the following fixed values when downloading data:

time = 00:00-23:00
leadtime_hour = 0-96
level = 0

All available data in this dataset is multi-level, but Providentia retrieves only the ground level.

Example configuration files and corresponding API requests

Example 1: CAMS Regional Analysis (DEHM Model, sconcno2)

[cams_analysis_dehm-regional] 
start_date = 20250701 
end_date = 20250702
species = sconcno2
model = cams_analysis_dehm
domain = regional
resolution = hourly
dl_interpolated = False

dataset = 'cams-europe-air-quality-forecasts'
request = {
'variable' : 'nitrogen_dioxide',
'leadtime_hour' : '0',
'type' : 'analysis',
'date' : '2025-07-01/2025-07-01',
'model' : 'dehm',
'level' : '0',
'time' : ['00:00', '01:00', '02:00', '03:00', '04:00', '05:00', '06:00', '07:00', '08:00', '09:00', '10:00', '11:00', '12:00', '13:00', '14:00', '15:00', '16:00', '17:00', '18:00', '19:00', '20:00', '21:00', '22:00', '23:00'],
'data_format' : 'netcdf_zip',
}

Example 2: CAMS Regional Forecast (Ensemble Model, sconcno2)

[cams_forecast_ensemble-regional]
start_date = 20250701
end_date = 20250702
species = sconcno2
model = cams_forecast_ensemble
domain = regional
resolution = hourly
dl_interpolated = False

dataset = 'cams-europe-air-quality-forecasts'
request = {
    'variable': 'nitrogen_dioxide',
    'leadtime_hour': [
        '0', '1', '2', '3', '4', '5', '6', '7', '8', '9', '10', '11', '12',
        '13', '14', '15', '16', '17', '18', '19', '20', '21', '22', '23',
        '24', '25', '26', '27', '28', '29', '30', '31', '32', '33', '34',
        '35', '36', '37', '38', '39', '40', '41', '42', '43', '44', '45',
        '46', '47', '48', '49', '50', '51', '52', '53', '54', '55', '56',
        '57', '58', '59', '60', '61', '62', '63', '64', '65', '66', '67',
        '68', '69', '70', '71', '72', '73', '74', '75', '76', '77', '78',
        '79', '80', '81', '82', '83', '84', '85', '86', '87', '88', '89',
        '90', '91', '92', '93', '94', '95', '96'
    ],
    'type': 'forecast',
    'date': '2025-07-01/2025-07-01',
    'model': 'ensemble',
    'level': '0',
    'time': '00:00',
    'data_format': 'netcdf_zip',
}

2. CAMS Global Atmospheric Composition Forecasts

Dataset Link

Using this dataset you can download Global Forecast data.

This dataset contains both single-level and multi-level data.

hourly and 3hourly data is available in this dataset. In your configuration file, you must set resolution = hourly or resolution = 3hourly, depending on whether the data is single-level or multi-level. Otherwise, the download will fail.

Mandatory fields for global forecast single-level data

model = cams_forecast
domain = global
resolution = hourly

Mandatory fields for global forecast multi-level data

model = cams_forecast
domain = global
resolution = 3hourly

Available variables (Species)

Whether the data is single or multi depends on the selected species. These are the available species:

Single-level:

absod1020aero
absod440aero
absod550aero
acprec
asy1020aero
asy440aero
cldbot
od1020aero
od380aero
od440aero
od500aero
od500aerofine
od550aero
od550du
pm1
pm10
pm2p5
pshltr
rh2
sca1020aero
sca440aero
sca550aero
si
slp
sst
t2
td2
vdist

Multi-level:

cfracmax
lbsco532
sconcc2h4
sconcc2h6
sconcc3h6
sconcc3h8
sconcch4
sconcco
sconcetoh
sconcglyox
sconchcho
sconchcl
sconchf
sconchno3
sconcisop
sconcmsa
sconcnh3
sconcnh4
sconcno
sconcno2
sconcno3
sconco3
sconcpan
sconcpb
sconcso2
sconcso4

Providentia can only read species in GHOST format. If you want to know the mapping from CAMS variables to GHOST species, please refer to the CAMS-GHOST species mapping section.

Assumptions

Providentia assumes the following fixed values when downloading data:

For single-level data:

time = 00:00
leadtime_hour = 0-120 (for every hour)
type = forecast

For multi-level data:

time = 00:00
leadtime_hour = 0-120 (for every three hours)
type = forecast
model_level = 60 (up to and including 2019-07-09) 137 (for data after 2019-07-09, when the levels increased)

For the multi-level data in this dataset, Providentia retrieves only the ground level.

Example configuration files and corresponding API requests

Example 1: CAMS Global Forecast (sst, Single-level, hourly)

[cams_forecast-global-hourly]
start_date = 20171201 
end_date = 20171202
species = sst
model = cams_forecast
domain = global
resolution = hourly
dl_interpolated = False

dataset = 'cams-global-atmospheric-composition-forecasts'
request = {
'variable' : 'sea_surface_temperature',
'leadtime_hour' : ['0', '1', '2', '3', '4', '5', '6', '7', '8', '9', '10', '11', '12', '13', '14', '15', '16', '17', '18', '19', '20', '21', '22', '23', '24', '25', '26', '27', '28', '29', '30', '31', '32', '33', '34', '35', '36', '37', '38', '39', '40', '41', '42', '43', '44', '45', '46', '47', '48', '49', '50', '51', '52', '53', '54', '55', '56', '57', '58', '59', '60', '61', '62', '63', '64', '65', '66', '67', '68', '69', '70', '71', '72', '73', '74', '75', '76', '77', '78', '79', '80', '81', '82', '83', '84', '85', '86', '87', '88', '89', '90', '91', '92', '93', '94', '95', '96', '97', '98', '99', '100', '101', '102', '103', '104', '105', '106', '107', '108', '109', '110', '111', '112', '113', '114', '115', '116', '117', '118', '119', '120'],
'type' : 'forecast',
'date' : '2017-12-01/2017-12-01',
'time' : '00:00',
'data_format' : 'netcdf_zip',
}

Example 2: CAMS Global Forecast (sconcno2, Multi-level, 3hourly)

[cams_forecast-global-3hourly]
start_date = 20200601  
end_date = 20200602
species = sconcno2
model = cams_forecast
domain = global
resolution = 3hourly
dl_interpolated = False

dataset = 'cams-global-atmospheric-composition-forecasts'
request = {
'variable' : 'nitrogen_dioxide',
'leadtime_hour' : ['0', '3', '6', '9', '12', '15', '18', '21', '24', '27', '30', '33', '36', '39', '42', '45', '48', '51', '54', '57', '60', '63', '66', '69', '72', '75', '78', '81', '84', '87', '90', '93', '96', '99', '102', '105', '108', '111', '114', '117', '120'],
'type' : 'forecast',
'date' : '2020-06-01/2020-06-01',
'model_level' : '137',
'time' : '00:00',
'data_format' : 'netcdf_zip',
}

3. CAMS European Air Quality Reanalyses

Dataset Link

Using this dataset you can download Regional Reanalysis data.

This dataset contains multi-level data.

Only hourly data is available in this dataset. You must set resolution = hourly in your configuration file; otherwise, the download will not work.

Mandatory fields for regional reanalysis data

model = cams_reanalysis_<model>_<stream>
domain = regional
resolution = hourly

Replace <model> and <stream> with one of the available model names and streams listed below.

Available models

Use the following model names (same as in the API):

ensemble
chimere
emep
lotos
match
minni
mocage
monarch
silam
euradim
dehm
gemaq

Available streams

There is two available streams for the regional reanalysis dataset:

validated available for the period 2014–2021 (inclusive)
interim available for the period 2021–2024 (inclusive)

Available variables (Species)

These are the available species:

pm10
pm10du
pm10so4ss
pm2p5
pm2p5ec
sconcco
sconcglyox
sconchcho
sconcnh3
sconcnmvoc
sconcno
sconcno2
sconco3
sconcso2

Providentia can only read species in GHOST format. If you want to know the mapping from CAMS variables to GHOST species, please refer to the CAMS-GHOST species mapping section.

Assumptions

Providentia assumes the following fixed values when downloading data:

level = 0

All available data in this dataset is multi-level, but Providentia retrieves only the ground level.

Example configuration files and corresponding API requests

Example 1: CAMS Regional Reanalysis (Ensemble Model, sconcno2, Interim Reanalysis)

[cams_reanalysis_ensemble_interim-regional]
start_date = 20240101
end_date = 20240201
species = sconcno2
model = cams_reanalysis_ensemble_interim
domain = regional
resolution = hourly
dl_interpolated = False

dataset = 'cams-europe-air-quality-reanalyses'
request = {
'variable' : 'nitrogen_dioxide',
'year' : '2024',
'month' : '01',
'type' : 'interim_reanalysis',
'model' : 'ensemble',
'level' : '0',
}

Example 2: CAMS Regional Reanalysis (Ensemble Model, sconcno2, Validated Reanalysis)

[cams_reanalysis_ensemble_validated-regional] 
start_date = 20200101 
end_date = 20200301
species = sconcno2
model = cams_reanalysis_ensemble_validated
domain = regional
resolution = hourly
dl_interpolated = False

dataset = 'cams-europe-air-quality-reanalyses'
request = {
'variable' : 'nitrogen_dioxide',
'year' : '2020',
'month' : '01',
'type' : 'validated_reanalysis',
'model' : 'ensemble',
'level' : '0',
}

4. CAMS Global Reanalysis (EAC4)

Dataset Link

Using this dataset you can download Global Reanalysis data.

This dataset contains both single-level and multi-level data.

Only 3hourly data is available in this dataset. You must set resolution = 3hourly in your configuration file; otherwise, the download will not work.

Mandatory fields for regional reanalysis data

model = cams_reanalysis
domain = global
resolution = 3hourly

Available variables (Species)

Whether the data is single or multi depends on the selected species. These are the available species:

Single-level:

2m_dewpoint_temperature
2m_temperature
dust_aerosol_optical_depth_550nm
mean_sea_level_pressure
particulate_matter_10um
particulate_matter_1um
particulate_matter_2.5um
relative_humidity
sea_surface_temperature
snow_depth
surface_pressure
total_aerosol_optical_depth_550nm

Multi-level:

cfracmax
sconcc2h4
sconcc2h6
sconcc3h6
sconcc3h8
sconcco
sconcetoh
sconchcho
sconchno3
sconcisop
sconcmsa
sconcnh3
sconcnh4
sconcno
sconcno2
sconcno3
sconco3
sconcpan
sconcpb
sconcso2
sconcso4

Providentia can only read species in GHOST format. If you want to know the mapping from CAMS variables to GHOST species, please refer to the CAMS-GHOST species mapping section.

Assumptions

Providentia assumes the following fixed values when downloading data:

For single-level data:

time = 00:00-21:00 (for every three hours)

For multi-level data:

time = 00:00-21:00 (for every three hours)
model_level = 60

For the multi-level data in this dataset, Providentia retrieves only the ground level.

Example configuration files and corresponding API requests

Example 1: CAMS Global Reanalysis (sst, Single-level)

[cams_reanalysis-global-single]
start_date = 20181101
end_date = 20181130
species = sst
model = cams_reanalysis
domain = global
resolution = 3hourly
dl_interpolated = False

dataset = 'cams-global-reanalysis-eac4'
request = {
'variable' : 'sea_surface_temperature',
'date' : '2018-11-01/2018-11-29',
'time' : ['00:00', '03:00', '06:00', '09:00', '12:00', '15:00', '18:00', '21:00'],
'data_format' : 'netcdf_zip',
}

Example 2: CAMS Global Reanalysis (sconcno2, Multi-level)

[cams_reanalysis-global-multi]
start_date = 20181101
end_date = 20181130
species = sconcno2
model = cams_reanalysis
domain = global
resolution = 3hourly
dl_interpolated = False

dataset = 'cams-global-reanalysis-eac4'
request = {
'variable' : 'nitrogen_dioxide',
'date' : '2018-11-01/2018-11-29',
'model_level' : '60',
'time' : ['00:00', '03:00', '06:00', '09:00', '12:00', '15:00', '18:00', '21:00'],
'data_format' : 'netcdf_zip',
}

CAMS-GHOST species mapping

Here is the mapping between CAMS variables and GHOST species names:

2m_dewpoint_temperature: td2
2m_temperature: t2
ammonia: sconcnh3
ammonium: sconcnh4
asymmetry_factor_1020nm: asy1020aero
asymmetry_factor_440nm: asy440aero
attenuated_backscatter_due_to_aerosol_532nm_from_ground: lbsco532
carbon_monoxide: sconcco
cloud_base_height: cldbot
dust: pm10du
dust_aerosol_optical_depth_550nm: od550du
ethane: sconcc2h6
ethanol: sconcetoh
ethene: sconcc2h4
formaldehyde: sconchcho
fraction_of_cloud_cover: cfracmax
glyoxal: sconcglyox
hydrogen_chloride: sconchcl
hydrogen_fluoride: sconchf
isoprene: sconcisop
lead: sconcpb
mean_sea_level_pressure: slp
methane: sconcch4
methane_sulfonic_acid: sconcmsa
nitrate: sconcno3
nitric_acid: sconchno3
nitrogen_dioxide: sconcno2
nitrogen_monoxide: sconcno
non_methane_vocs: sconcnmvoc
ozone: sconco3
particulate_matter_10um: pm10
particulate_matter_1um: pm1
particulate_matter_2.5um: pm2p5
peroxyacetyl_nitrate: sconcpan
pm10_sea_salt_dry: pm10so4ss
pm2.5_ammonium: pm2p5nh4
pm2.5_nitrate: pm2p5no3
pm2.5_sulphate: pm2p5so4
propane: sconcc3h8
propene: sconcc3h6
relative_humidity: rh2
sea_surface_temperature: sst
single_scattering_albedo_1020nm: sca1020aero
single_scattering_albedo_440nm: sca440aero
single_scattering_albedo_550nm: sca550aero
snow_depth: si
sulphate_aerosol_mixing_ratio: sconcso4
sulphur_dioxide: sconcso2
surface_pressure: pshltr
total_absorption_aerosol_optical_depth_1020nm: absod1020aero
total_absorption_aerosol_optical_depth_440nm: absod440aero
total_absorption_aerosol_optical_depth_550nm: absod550aero
total_aerosol_optical_depth_1020nm: od1020aero
total_aerosol_optical_depth_380nm: od380aero
total_aerosol_optical_depth_440nm: od440aero
total_aerosol_optical_depth_500nm: od500aero
total_aerosol_optical_depth_550nm: od550aero
total_elementary_carbon: pm2p5ec
total_fine_mode_aerosol_optical_depth_500nm: od500aerofine
total_precipitation: acprec
visibility: vdist