A potato model intercomparison across varying climates and productivity levels

Area of Science:

• Agricultural Science
• Climate Modeling
• Crop Physiology

Background:

• Potato crop modeling is crucial for understanding climate change impacts.
• Quantifying model uncertainty is essential for reliable predictions.
• Previous assessments have not focused on tuber/root crops.

Purpose of the Study:

• To quantify variation among potato crop models.
• To evaluate model responses to climate change.
• To assess the effectiveness of an ensemble modeling approach.

Main Methods:

• Nine modeling groups simulated potato agronomic and climatic responses.
• Two calibration stages (partial and full) were used.
• Simulations were conducted at low- and high-input management sites globally.

Main Results:

• The median model ensemble outperformed single models in yield prediction.
• Uncertainty in simulated yield decreased from 38% to 20% with full calibration.
• Model variation increased with temperature and rainfall changes, with temperature sensitivity being a major unknown.

Conclusions:

• An ensemble approach is recommended for improved potato climate change impact assessments.
• Model calibration significantly reduces uncertainty.
• Future research should focus on improving temperature sensitivity parameters in crop models.