CliPick – Climate change web picker. A tool bridging daily climate needs in process based modelling in forestry and agriculture

Joao H. N. Palma


Aim of study: Climate data is a need for different types of modeling assessments, especially those involving process based modeling focusing on climate change impacts. However, there is a scarcity of tools delivering easy access to climate datasets to use in biological related modeling. This study aimed at the development of a tool that could provide an user-friendly interface to facilitate access to climate datasets, that are used to supply climate scenarios for the International Panel on Climate Change.

Area of study: The tool provides daily datasets across Europe, and also parts of northern Africa

Material and Methods: The tool uses climatic datasets generated from third party sources (IPCC related) while a web based interface was developed in JavaScript to ease the access to the datasets

Main Results: The interface delivers daily (or monthly) climate data from a user-defined location in Europe for 7 climate variables: minimum and maximum temperature, precipitation, radiation, minimum and maximum relative humidity and wind speed). The time frame ranges from 1951 to 2100, providing the basis to use the data for climate change impact assessments. The tool is free and publicly available at

Research Highlights: A new and easy-to-use tool is suggested that will promote the use of climate change scenarios across Europe, especially when daily time steps are needed. CliPick eases the communication between climatic and modelling communities such as agriculture and forestry.


AGFORWARD; CORDEX; ENSEMBLES; Forest growth; IPCC; process based modelling

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Fontes L, Bontemps J, Bugmann H, Van Oijen M, Gracia C, Kramer K, Lindner M, Rötzer T, Skovsgaard JP, 2010. Models for supporting forest management in a changing environment. Forest Systems 19(S1): 8–29.

Giorgi F, Jones C, Asrar GR, 2009. Addressing climate information needs at the regional level: the CORDEX framework. Bull. - World Meteorol Organ 58: 175–183.

Hijmans RJ, Cameron SE, Parra JL, Jones PG, Jarvis A, 2005. Very high resolution interpolated climate surfaces for global land areas. Int J Climatol 25: 1965-1978.

Jacob D, Petersen J, Eggert B, Alias A, Christensen OB, Bouwer LM, Braun A, Colette A, Déqué M, Georgievski G, et al., 2014. EURO-CORDEX: New high-resolution climate change projections for European impact research. Reg Environ Chang 14: 563–578.

Katragkou E, García-Díez M, Vautard R, Sobolowski S, Zanis P, Alexandri G, Cardoso RM, Colette A, Fernandez J, Gobiet A, et al., 2015. Regional climate hindcast simulations within EURO-CORDEX: evaluation of a WRF multi-physics ensemble. Geosci Model Dev 8: 603–618.

Kotlarski S, Keuler K, Christensen OB, Colette A, Déqué M, Gobiet A, Goergen K, Jacob D, Lüthi D, Van Meijgaard E, et al., 2014. Regional climate modeling on European scales: A joint standard evaluation of the EURO-CORDEX RCM ensemble. Geosci Model Dev 7: 1297–1333.

Luedeling E, Smethurst PJ, Baudron F, Bayala J, Huth NI, van Noordwijk M, Ong CK, Mulia R, Lusiana B, Muthuri C, Sinclair FL, 2016. Field-scale modeling of tree-crop interactions: Challenges and development needs. Agric Syst 142: 51–69.

Perry M, Hollis D, 2005. The generation of monthly gridded datasets for a range of climatic variables over the UK. Int J Climatol 25: 1041–1054.

Prein AF, Gobiet A, Truhetz H, Keuler K, Goergen K, Teichmann C, Fox Maule C, van Meijgaard E, Déqué M, Nikulin G, et al., 2015. Precipitation in the EURO-CORDEX 0.11 and 0.44 degree simulations: high resolution, high benefits? Clim Dyn 46(1-2): 383-412

Rew R, Davis G, 1990. NetCDF: An Interface for Scientific Data Access. IEEE Comput Graph Appl 10: 76–82.

Talbot G, 2011. L'intégration spatiale et temporelle des compétitions pour l'eau et la lumière dans un système agroforestiers noyers-céréales permet-elle d'en comprendre la productivité? . INRA, Umr Syst Université de Montpellier, Montpellier, France.

van der Werf W, Keesman K, Burgess P, Graves A, Pilbeam D, Incoll LD, Metselaar K, Mayus M, Stappers R, van Keulen H., et al., 2007. Yield-SAFE: A parameter-sparse, process-based dynamic model for predicting resource capture, growth, and production in agroforestry systems. Ecol Eng 29: 419–433.

DOI: 10.5424/fs/2017261-10251