Department of Soil Science, Tarbiat Modares University, P.O. Box 14115-336, Tehran, Iran.
Department of Irrigation and Drainage, Tarbiat Modares University, P.O. Box 14115-336, Tehran, Iran.
Int J Biometeorol. 2017 Sep;61(9):1571-1583. doi: 10.1007/s00484-017-1336-y. Epub 2017 Apr 18.
In order to assess the response of wheat and barley to climate variability, the correlation between variations of yields with local and global climate variables was investigated in west and northwest Iran over 1982-2013. The global climate variables were the El Niño-Southern Oscillation (ENSO), Arctic Oscillation (AO), and North Atlantic Oscillation (NAO) signals. Further, minimum (T ), maximum (T ), and mean (T ) temperature, diurnal temperature range (DTR), precipitation, and reference evapotranspiration (ET) was used as local weather factors. Pearson's correlation coefficient was applied to analyze the relationships between climatic variables and yields. Unlike T , T , ET, and T , the yields were significantly associated with the entire growing season (EGS) DTR in most sites. Therefore, considering weather extreme variables such as DTR sheds light on the crop-temperature interactions. It is also found that the April-May-June (AMJ), October-November-December (OND), and EGS rainfall variations markedly influence the yields. Unlike the AO and NAO indices, the Niño-4 and SOI (the ENSO-related signals) were significantly correlated with the OND and EGS precipitation and DTR. Thus, the ENSO anomalies highly impact rainfed yields through influencing the OND and EGS rainfall and DTR in the studied sites. As the correlation coefficient of the OND and July-August-September (JAS) Niño-4 with yields was significant (p < 0.05) for almost all locations, the JAS and OND Niño-4 may be a good proxy for cereal yield forecasting. Further, an insignificant increment and a significant reduction in yields are expected in La Niña and El Niño years, respectively, relative to neutral years.
为了评估小麦和大麦对气候变化的响应,在伊朗西部和西北部,研究了 1982-2013 年期间产量与当地和全球气候变量的变化之间的相关性。全球气候变量为厄尔尼诺-南方涛动(ENSO)、北极涛动(AO)和北大西洋涛动(NAO)信号。此外,还使用了最小(T)、最大(T)和平均(T)温度、日较差(DTR)、降水和参考蒸散量(ET)作为当地天气因素。应用皮尔逊相关系数分析气候变量与产量之间的关系。与 T、T、ET 和 T 不同,在大多数站点,产量与整个生长季节(EGS)DTR 显著相关。因此,考虑天气极端变量,如 DTR,可以更好地了解作物-温度相互作用。还发现,4 月-5 月-6 月(AMJ)、10 月-11 月-12 月(OND)和 EGS 降雨量的变化显著影响产量。与 AO 和 NAO 指数不同,尼诺-4 和 SOI(与 ENSO 相关的信号)与 OND 和 EGS 降水和 DTR 显著相关。因此,ENSO 异常通过影响研究站点的 OND 和 EGS 降水和 DTR,对雨养产量产生重大影响。由于OND 和 JAS 尼诺-4 与产量的相关系数在几乎所有地点都显著(p<0.05),因此 JAS 和 OND 尼诺-4 可能是预测谷物产量的良好指标。此外,与中性年相比,拉尼娜年和厄尔尼诺年的产量预计分别会略有增加和显著减少。