Müller, C. (2013). Multi-sector interaction in climate change impact analysis..
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Ruane, A. C., Hudson, N. I., Asseng, S., Camarrano, D., Ewert, F., Martre, P., et al. (2016). Multi-wheat-model ensemble responses to interannual climate variability. Env. Model. Softw., 81, 86–101.
Abstract: We compare 27 wheat models’ yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981-2010 grain yield, and we evaluate results against the interannual variability of growing season temperature, precipitation, and solar radiation. The amount of information used for calibration has only a minor effect on most models’ climate response, and even small multi-model ensembles prove beneficial. Wheat model clusters reveal common characteristics of yield response to climate; however models rarely share the same cluster at all four sites indicating substantial independence. Only a weak relationship (R-2 <= 0.24) was found between the models’ sensitivities to interannual temperature variability and their response to long-term warming, suggesting that additional processes differentiate climate change impacts from observed climate variability analogs and motivating continuing analysis and model development efforts. Published by Elsevier Ltd.
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Piotr, B., Jaromir Krzyszczak, Cezary Slawinski. (2014). Multifractal analysis of chosen meteorological time series to assess climate impact in field level..
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Baranowski, P., Krzyszczak, J., & Slawinski, C. (2014). Multifractal analysis of chosen meteorological time series to assess climate impact in field level..
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Yin, X., Olesen, J. E., Wang, M., Öztürk, I., & Chen, F. Observed and anticipated impacts and adaptation of crop production systems to climate change in the northeast farming region of China.
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