Calibration, the estimation of model parameters based on fitting the model to experimental data, is among the first steps in many applications of process-based models and has an important impact on simulated values. We propose a novel method of developing guidelines for calibration of process-based models, based on development of recommendations for calibration of the phenology component of crop models. The approach was based on a multi-model study, where all teams were provided with the same data and asked to return simulations for the same conditions. All teams were asked to document in detail their calibration approach, including choices with respect to criteria for best parameters, choice of parameters to estimate and software. Based on an analysis of the advantages and disadvantages of the various choices, we propose calibration recommendations that cover a comprehensive list of decisions and that are based on actual practices.

校准，即基于将模型与实验数据拟合来估计模型参数，是基于过程的模型的许多应用中的第一步，对模拟值具有重要影响。基于对作物模型物候成分校准的建议的制定，我们提出了一种为基于过程的模型校准制定指南的新方法。该方法基于多模型研究，向所有团队提供相同的数据，并要求返回相同条件下的模拟。所有团队都被要求详细记录他们的校准方法，包括关于最佳参数标准的选择、估计参数的选择和软件。基于对各种选择的优缺点的分析，