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Quantifying and separating different sources of uncertainty helps to improve the understanding of the projected effects of climate change and can inform decision‐making in adaptation planning. This paper (1) evaluated four process‐based crop models; (2) assessed the effects of climate change on maize yield using climate change outputs from seven global climate models (GCMs) under three representative concentration pathways (RCPs); and (3) disaggregated the contributions of multiple crop models, GCMs and RCPs to overall uncertainty. All four models captured more than 80% of the variation in days to silking, maturity and yield, indicating reasonably reproduced observations. Similarly, the root mean square errors were moderate for days to silking and maturity (fewer than 4 days) and yield (0.5–0.7 t/ha). Overall, the results indicate that the models could assess grain yield at the study sites reasonably well. The results of the multiple models ensemble indicate that the maize yield will decrease by 9–11% with a probability of 72–80% on average during the period 2010–2039 relative to the baseline (1976–2005). The uncertainty in the maize‐yield simulations might arise mostly from the GCM models, followed by the crop models and RCPs, the contribution of which could be neglected relative to the other factors. Therefore, the use of a multiple crop model and a GCM ensemble is advisable in order to account properly for uncertainties in crop assessments. The uncertainty in maize‐yield simulations might arise mostly from global climate models (GCMs), followed by crop models and representative concentration pathways (RCPs), the contribution of which could be neglected relative to the other factors. Therefore, the use of a multiple crop model and a GCM ensemble is advisable in order to account properly for uncertainties in crop assessments. [ABSTRACT FROM AUTHOR]

This study assessed the growth of wheat under climate change conditions (increases in CO2 and temperature) in southwestern Iran. Future climate data were projected using long‐term climate data for radiation and minimum and maximum temperatures for the baseline period 1980–2010. The future climate scenarios made use of delta changes from the Coupled Model Intercomparison Project Phase 5 (CMIP5) in the R package of the Agricultural Model Intercomparison and Improvement Project for 2040–2070. After generating the weather data, the Agricultural Production System Simulator wheat model was applied to assess the potential impact of climate change on wheat yield and the relative growth rate, crop growth rate, total dry weight and leaf area index. Averaged across all locations, an increase of 1.6 and 2.3°C in annual temperature was projected under representative concentration pathway 4.5 (RCP4.5) and RCP8.5, respectively. The decrease in the average length of the growing season was 7.5 and 9.3% under RCP4.5 and RCP8.5, respectively, in the mid‐21st century with respect to baseline. The mean cumulative radiation will decrease by 11.6 and 14.3% averaged across all sites for RCP4.5 and RCP8.5, respectively. Grain yield will decrease at all sites for both RCPs. The greatest decrease in wheat yield was projected for Izeh under RCP4.5 and RCP8.5 (7.9 and 9.3%, respectively) for 2040–2070 relative to baseline. A greater grain yield at baseline than for the RCP8.5 and RCP4.5 scenarios was closely related to higher leaf area index, relative growth rate and crop growth rate values during the reproductive phase. Thus, these parameters can be defined as indicators of crop yield. [ABSTRACT FROM AUTHOR]

Many fruit crop failures, including those for peaches, are caused by extremely low winter temperatures or by false springs, which is when a hard freeze occurs in the spring after plants have broken dormancy and started to grow. A decision‐support tool was created to predict major, regional peach yield reductions based on the analysis of significant peach crop loss years between 1934 and 2016 in the Midwest (Illinois, Missouri and Arkansas) and Southeast (Alabama, Georgia, South Carolina and North Carolina) regions of the United States using surface temperature data. The tool was tested using data from high‐yield peach years and was found to function well in all the sample years for the Midwest, but only for 75% of years for the Southeast. The tool was then tested on the 2017 false spring event that occurred over parts of the Eastern United States. The tool correctly indicated that the entire Southeast region would likely experience a major peach crop yield reduction, while many peach‐growing areas in the Midwest were spared as not all Midwest stations had accumulated enough growing degree‐days before experiencing a hard freeze. Composite 500 hPa geopotential height anomalies associated with the "warm" periods of false spring events were 100 m above average for the Midwest, and 100–125 m for the Southeast. Cold period composites of the low‐yield years suggested 500 hPa geopotential height anomalies were 100–200 m below average for the Midwest, and 100–175 m for the Southeast. The decision‐support tool will assist the peach industry to anticipate major, regional yield reductions. A decision‐support tool developed for the Midwest (a) and Southeast (b) regions of the United States will be used to assist the peach‐growing industry to anticipate major, regional yield reductions. [ABSTRACT FROM AUTHOR]

The article discusses the effects of frost in the apple trees of Iran. It states a report from Iran Agricultural Bank that frost in the spring of 2004 caused apple production losses of around 600 million U.S. dollars. The article also includes approximating suitable distribution and possibility of occurrence of last spring frosts, calibration and validation of bud burst prediction model, and frost occurrences due to forecasted bud burst time.