PT  - JOURNAL ARTICLE
AU  - Daniel Wallach
AU  - Taru Palosuo
AU  - Peter Thorburn
AU  - Zvi Hochman
AU  - Emmanuelle Gourdain
AU  - Fety Andrianasolo
AU  - Senthold Asseng
AU  - Bruno Basso
AU  - Samuel Buis
AU  - Neil Crout
AU  - Camilla Dibari
AU  - Benjamin Dumont
AU  - Roberto Ferrise
AU  - Thomas Gaiser
AU  - Cecile Garcia
AU  - Sebastian Gayler
AU  - Afshin Ghahramani
AU  - Santosh Hiremath
AU  - Steven Hoek
AU  - Heidi Horan
AU  - Gerrit Hoogenboom
AU  - Mingxia Huang
AU  - Mohamed Jabloun
AU  - Per-Erik Jansson
AU  - Qi Jing
AU  - Eric Justes
AU  - Kurt Christian Kersebaum
AU  - Anne Klosterhalfen
AU  - Marie Launay
AU  - Elisabet Lewan
AU  - Qunying Luo
AU  - Bernardo Maestrini
AU  - Henrike Mielenz
AU  - Marco Moriondo
AU  - Hasti Nariman Zadeh
AU  - Gloria Padovan
AU  - Jørgen Eivind Olesen
AU  - Arne Poyda
AU  - Eckart Priesack
AU  - Johannes Wilhelmus Maria Pullens
AU  - Budong Qian
AU  - Niels Schütze
AU  - Vakhtang Shelia
AU  - Amir Souissi
AU  - Xenia Specka
AU  - Amit Kumar Srivastava
AU  - Tommaso Stella
AU  - Thilo Streck
AU  - Giacomo Trombi
AU  - Evelyn Wallor
AU  - Jing Wang
AU  - Tobias K.D. Weber
AU  - Lutz Weihermüller
AU  - Allard de Wit
AU  - Thomas Wöhling
AU  - Liujun Xiao
AU  - Chuang Zhao
AU  - Yan Zhu
AU  - Sabine J. Seidel
TI  - The chaos in calibrating crop models
AID  - 10.1101/2020.09.12.294744
DP  - 2020 Jan 01
TA  - bioRxiv
PG  - 2020.09.12.294744
4099  - http://biorxiv.org/content/early/2020/09/14/2020.09.12.294744.short
4100  - http://biorxiv.org/content/early/2020/09/14/2020.09.12.294744.full
AB  - Calibration, the estimation of model parameters based on fitting the model to experimental data, is among the first steps in essentially every application of crop models and process models in other fields and has an important impact on simulated values. The goal of this study is to develop a comprehensive list of the decisions involved in calibration and to identify the range of choices made in practice, as groundwork for developing guidelines for crop model calibration starting with phenology. Three groups of decisions are identified; the criterion for choosing the parameter values, the choice of parameters to estimate and numerical aspects of parameter estimation. It is found that in practice there is a large diversity of choices for every decision, even among modeling groups using the same model structure. These findings are relevant to process models in other fields.HighlightsWe documented calibration procedures in two multi-model studiesGroups differ in criteria for best parameters, parameters to estimate and softwareThere are important differences even between groups using the same model structureCompeting Interest StatementThe authors have declared no competing interest.