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Exploring climate model data

France: Scenarios for adaptation studies to climate change over the Loire Basin

France: Scenarios for adaptation studies to climate change over the Loire Basin

Goal: Providing climate change scenarios for vulnerability studies of human activities and environment to the effects of climate change on flood regimes and droughts in the Loire Basin.
This Use Case is not implemented in the data module yet.

This use-case describes the communication of information on future climate provided by the scientific community, in order to conduct studies on the adaptation of the Loire Basin management plan to the impacts of climate change. The objective of the public managers is to develop a common knowledge on this topic that relies on research results. They have prepared and launched a call of opportunity open to the French scientific community to improve the knowledge of the vulnerabilities of human activities and environments to the effects of climate change over this region. They have appealed French climate research groups for choosing and providing climate change scenarios that could be used by other research groups working in a wide range of fields (hydrology, sociology, etc) to lead their research in response to the call of opportunity.


Serge Planton, Météo-France/CNRM, France
Christian Pagé, CERFACS, France


Climate scientists (Météo-France, CERFACS ), hydrologists (ISTO , Sisyphe , BRGM , …), geographers (CITERES ), Loire Basin managers (Etablissement Public Loire, Agence de l’eau Loire Bretagne, ..), public stake-holders (DGPR ).

Data needs

Two types of data are made available:
  • Regional re-analysis: re-analysis of French meteorological observations (SAFRAN, Météo-France; Quintana-Segui et al, 2008) covering several decades (1970-2007) on a regular grid (grid mesh of 8km) including hourly near surface (2m) temperature and humidity, incoming surface solar and infrared radiations, near surface (10m) wind speed, solid and liquid precipitation. Calculated evapotranspiration from the re-analysed variables is also added.
  • Downscaled scenario: Two ensemble of data from scenario simulations downscaled either with a dynamical method or with a statistical method. The dynamically downscaled ensemble (Météo-France) consists in one present climate simulation over the period 1950-2000 and three climate change scenarios (A1B, A2 and B1) over the period 2001-2100, performed with a variable resolution GCM ((ARPEGE-Climat; Gibelin and Déqué, 2003)) and is given on the model grid (about 50km of resolution over France). The statistically downscaled ensemble (CERFACS) consists in present climate simulations over the period 1961-2000 and climate change scenarios (A1B) over the periods 2046-2065 and 2081-2100, derived by means of a weather typing method from re-analysis (SAFRAN and NCEP) and CMIP3 simulations performed with 15 AOGCMs, and is given over the SAFRAN grid (resolution of 8km). The dynamically downscaled simulation are also statistically downscaled. For the two ensembles, the available variables are the same than those given in the previous section but are given at the daily time step and include the daily maximum and minimum for temperature. The dynamically downscaled variables also include corrected temperature and precipitation using reference daily observations from the French meteorological station network and a quantile-quantile correction method (Déqué, 2007).

Typical course of events

  1. Production by the climate research group of climate scenario datasets within the context of research projects: simulations of climate scenarios using global low resolution atmosphere/ocean/sea-ice climate models, downscaling of climate scenarios using a statistical method and a variable resolution climate model combined with a correction method.
  2. Workshop associating climatologists and Loire Basin managers to exchange knowledge on climate change scenarios and selecting the scenarios and variables that will be provided in the context of the call of opportunity. The importance of uncertainty in the scenarios is re-assessed.
  3. Data extraction (regional re-analysis and downscaled scenario data) over the domain of interest and calculation of complementary variables (evapotranspiration, minimum and maximum daily temperature, relative humidity).
  4. Preparation of a documentation describing the data, the methods for data production, the data access methods, the uncertainty evaluation and recommendations for data use.
  5. Data delivery by the climate research groups in a data repository located in a centre in contact with the selected research teams (provisional before the settlement of a web data portal).
  6. Launch of the call of opportunity including documentation on the available climate change scenarios and selected of variables.
  7. Selection of the research teams by the scientific committee of the program.
  8. Workshop associating the climatologists, the Loire Basin managers and scientists from the selected research teams to present the research project and the data made available for the studies, along with recommendations for data use (uncertainty).
  9. Data recovery by the selected research teams from the data repository with the associated documentation.
  10. Support from the climatologists to the data users during the duration of their projects through e-mails, phone or meetings (practical use, scientific aspects), initiated by means of a unique e-mail contact point.

Support to users

A documentation describing the data, the methods for data production, the data access methods, the uncertainty evaluation and recommendations for data use, is provided to the users. Support from the climatologists is provided to the data users during the duration of their projects through e-mails, phone or meetings (practical use, scientific aspects), initiated by means of a unique e-mail contact point.

References for the Use Case

  • Call of opportunity of « Plan-Loire »: « Appel à projets de recherche sur la connaissance des vulnérabilités des activités humaines et des milieux du bassin de la Loire par rapport aux effets du changement climatique sur les régimes d’inondation et de sécheresse », June 2008, available at:
  • Boé, J., L. Terray, F. Habets, and E. Martin, 2006: A simple statistical-dynamical downscaling scheme based on weather types and conditional resampling. J. Geophys. Res., 111 :D21106, 2006.
  • Déqué, M., 2007 : Frequency of precipitation and temperature extremes over France in an anthropogenic scenario: model results and statistical correction according to observed values. Global and Planetary Change 57, 16-26.
  • Gibelin, A.L., and M. Déqué, 2003 : Anthropogenic climate change over the Mediterranean region simulated by a global variable resolution model. Climate Dyn., 20, 327-339.
  • Pagé, C., L. Terray et J. Boé, 2009: dsclim: A software package to downscale climate scenarios at regional scale using a weather-typing based statistical methodology. Technical Report TR/CMGC/09/21, CERFACS, Toulouse, France.
  • Pagé, C., J. Boé, et L. Terray, 2008 : Projections climatiques à échelle fine sur la France pour le 21ème siècle : les scénarii SCRATCH08. Technical Report TR/CMGC/08/64, CERFACS, Toulouse, France.
  • Russell, K. R., E. J. Hartnett, and J. Caron, 2006: NetCDF-4: Software Implementing an Enhanced Data Model for the Geosciences. 22nd International Conference on Interactive Information Processing Systems for Meteorology, Oceanography, and Hydrology.
  • Quintana-Segui, P., Le Moigne, P., Durand, Y., Martin, E., Habets, F., Baillon, M., Canellas, C., Franchisteguy, L. and Morel, S., 2008: Analysis of Near-Surface Atmospheric Variables: Validation of the SAFRAN Analysis over France. J. Appl. Meteor. Climatol. 47, 92–107. udunits-1: Convention CF-1.0 NetCDF:

Software used

  1. CERFACS dsclim: downscaling software and library
  2. CERFACS extract_ds: data-extraction software
  3. ARPEGE-Climat (variable resolution version): Météo-France regional climate model
  4. Météo-France correctmod: software to correct simulated variables from regional climate scenarios using available observations of these variables
  5. NetCDF-4 library
  6. udunits-1 library

File format(s)

  • The provided files containing the data (regional re-analysis and downscaled scenario) are in ASCII format
  • The native format for CERFACS statistical downscaling data is in the NetCDF format using the CF-1 convention

Miscellaneous Notes

Only one research team selected after the first call of opportunity needed the data but, due to direct interaction with the climatologists in the context of a previous research project, the data was already at their disposal. The facility of the data repository was thus not used within the context of the first call of opportunity.

Sources and cascade of Uncertainty

The sources of uncertainty of the downscaled scenarios are the internal climate variability, the choice of the emission scenario, the choice of the climate model and the choice of the downscaling method. The first one is generally addressed by using ensemble of simulations for each climate model and each emission scenario. It is not here taken into account. The uncertainty from the scenario is accounted for by using 3 different emission scenarios (B1, A1B and A2). The uncertainty of the model choice is taken into account by selecting 15 different GCMs and one regional climate model to calculate the statistically downscaled scenarios. The uncertainty from the downscaling method is addressed by using two different methods: statistically downscaled scenarios from GCMs simulations and dynamically downscaled scenarios (regional climate model) with corrected precipitation and temperature to reproduce observed spectra of variability under present climate conditions.
>> Read more on uncertainties


The ENES3 project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 824084.