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SIM2 (Safran-Isba)

🌍 Access data

Description

Daily data from the SIM (Safran-Isba-Modcou) surface scheme simulation are made available by Météo-France on meteo.data.gouv.fr. These datasets contain atmospheric surface parameters and soil water balances obtained from the analysis of a model simulating surface water and energy fluxes.

Data are distributed as space-time tabular CSV files projected on a regular grid of 8 km × 8 km, in the CRS EPSG:27572 (NTF Lambert II étendu), and packaged as one decade per file. Files are openly accessible (no API key required), and recent decades and the running year are republished as the data become available.

Key characteristics:

• Temporal coverage: 1958-08-01 to present

• Temporal resolution: daily

• Spatial resolution: 8 km × 8 km (SAFRAN grid)

• Spatial coverage: France (metropolitan)

• Native CRS: EPSG:27572 (NTF Lambert II étendu)

• Source: Météo-France (meteo.data.gouv.fr)

GEOP4TH workflows

SIM2 data can be:

• downloaded in an automatic and simpler way with download_sim2 (or its underlying SIM2Downloader class),

• standardized (CRS embedded, conversion to geospatial formats such as netCDF, standard units, axes and attributes, optional reprojection to WGS84…) with standardize_sim2,

• formatted as inputs for specific applications, such as for the CWatM hydrological model with cwatm_meteo.

The downloader fetches the relevant decadal archives from data.gouv.fr, extracts only the requested variables and the requested period, optionally clips the data to a user mask, and produces one output file per variable. Existing files in the destination folder are detected and only the missing time periods are downloaded.

Standardization renames short column names to their canonical *_Q form, embeds the CRS, fills the SAFRAN grid to a continuous raster, converts units to UDUNITS-2 form (e.g. mm → m, J/cm² → W m-2), reprojects to WGS84 by default to align with ERA5-Land and other lat/lon datasets, and computes the secondary variable PRETOT_Q (total precipitation) from its components when requested.

Basic example

import geop4th as geo

# 1. Download (no API key required)
files = geo.download_sim2(
    dst_folder='./sim2_raw',
    variables=['PRELIQ', 'PRENEI', 'T', 'ETP', 'SWI'],
    start_date='2015',
    end_date='2024',
    mask='./catchment.gpkg',     # optional, clips to a sub-extent
)

# 2. Standardize already happens inline when extension='.nc' (default).
#    To re-run standardization on an existing folder of CSVs:
geo.standardize_sim2(
    data='./sim2_raw',
    output_path='./sim2_std',
    target_crs=4326,             # default; pass 27572 to keep the native grid
)

Available variables

SIM2 exposes about 25 variables organized by physical category. All variable names internally carry a _Q suffix (e.g. PRELIQ_Q); the corresponding short names (e.g. PRELIQ) are accepted as input and resolved automatically. Each variable carries an aggregation hint (sum / mean / min / max) used by the standardizer if the temporal frequency is changed.

The columns Native units and Standard units reflect respectively the units in the source CSV files and the units after standardization (UDUNITS-2 form).

Precipitation (2 variables)

Short	Variable	Native units	Standard units	Aggregation	Description
PRELIQ	PRELIQ_Q	mm	m	sum	Liquid precipitation (daily, 06–06 UTC)
PRENEI	PRENEI_Q	mm	m	sum	Solid precipitation (daily, 06–06 UTC)

Temperature (3 variables)

Short	Variable	Native units	Standard units	Aggregation	Description
T	T_Q	°C	°C	mean	Daily mean temperature
TINF_H	TINF_H_Q	°C	°C	min	Min of the 24 hourly temperatures
TSUP_H	TSUP_H_Q	°C	°C	max	Max of the 24 hourly temperatures

Wind & humidity (3 variables)

Short	Variable	Native units	Standard units	Aggregation	Description
FF	FF_Q	m/s	m s-1	mean	Wind speed (daily mean)
Q	Q_Q	g/kg	g kg-1	mean	Specific humidity (daily mean)
HU	HU_Q	%	%	mean	Relative humidity (daily mean)

Radiation (2 variables)

Short	Variable	Native units	Standard units	Aggregation	Description
DLI	DLI_Q	J/cm²	W m-2	sum	Atmospheric (longwave) radiation
SSI	SSI_Q	J/cm²	W m-2	sum	Visible (shortwave) radiation

Evapotranspiration (3 variables)

Short	Variable	Native units	Standard units	Aggregation	Description
EVAP	EVAP_Q	mm	m	sum	Actual evapotranspiration (06–06 UTC)
ETP	ETP_Q	mm	m	sum	Potential evapotranspiration (Penman-Monteith)
PE	PE_Q	mm	m	sum	Effective rainfall

Soil water (6 variables)

Short	Variable	Native units	Standard units	Aggregation	Description
SWI	SWI_Q	%	%	mean	Soil wetness index (06–06 UTC)
DRAINC	DRAINC_Q	mm	m	sum	Drainage (06–06 UTC)
RUNC	RUNC_Q	mm	m	sum	Runoff (06–06 UTC)
WG_RACINE	WG_RACINE_Q	mm	m	mean	Liquid water content of the root layer (at 06 UTC)
WGI_RACINE	WGI_RACINE_Q	mm	m	mean	Frozen water content of the root layer (at 06 UTC)
ECOULEMENT	ECOULEMENT_Q	mm	m	sum	Outflow at the base of the snowpack

Snow (6 variables)

Short	Variable	Native units	Standard units	Aggregation	Description
RESR_NEIGE	RESR_NEIGE_Q	mm	m	mean	Snow water equivalent (06–06 UTC)
RESR_NEIGE6	RESR_NEIGE6_Q	mm	m	mean	Snow water equivalent at 06 UTC
HTEURNEIGE	HTEURNEIGE_Q	m	m	mean	Snowpack thickness (06–06 UTC)
HTEURNEIGE6	HTEURNEIGE6_Q	m	m	mean	Snowpack thickness at 06 UTC
HTEURNEIGEX	HTEURNEIGEX_Q	m	m	max	Daily maximum snowpack thickness
SNOW_FRAC	SNOW_FRAC_Q	%	%	mean	Cell fraction covered by snow (06–06 UTC)

Secondary (derived) variables (1 variable)

Recomputed from primary variables when requested.

Variable	Computed from	Units	Notes
PRETOT_Q	PRELIQ_Q, PRENEI_Q	m	Total precipitation (sum of liquid + solid)

Variable profiles

Predefined bundles can be passed directly as variables=:

• 'hydrology' (10 variables): PRELIQ_Q, PRENEI_Q, T_Q, ETP_Q, EVAP_Q, PE_Q, DRAINC_Q, RUNC_Q, SWI_Q, PRETOT_Q.

• 'complete': every variable.

Source archives

The download workflow fetches one or several decadal archives from data.gouv.fr, each weighing about 1 GB compressed. Only the archives that intersect the requested period are downloaded.

Archive	Period	Compressed size
QUOT_SIM2_1958-1959	1958-08-01 to 1959-12-31	~0.16 GB
QUOT_SIM2_1960-1969	1960 to 1969	~1.1 GB
QUOT_SIM2_1970-1979	1970 to 1979	~1.1 GB
QUOT_SIM2_1980-1989	1980 to 1989	~1.1 GB
QUOT_SIM2_1990-1999	1990 to 1999	~1.1 GB
QUOT_SIM2_2000-2009	2000 to 2009	~1.1 GB
QUOT_SIM2_2010-2019	2010 to 2019	~1.1 GB
QUOT_SIM2_latest_period	2020 to last full month	~1.1 GB
QUOT_SIM2_latest_days	current month to yesterday	~0.1 GB

Examples

Coming soon…

Illustrative figures and notebook outputs.