نشریه هواشناسی کشاورزی
سال نهم شماره 2 (پاییز و زمستان 1400)

Awarding half of the 2021 Physics Nobel Prize to climate change scientists, as well as holding the UN Climate Change Conference in Glasgow in October 2021 is the editorial pretext of this issue.a) Syukuro Manabe & Klaus Hasselmann have been able to take a deep look at the nature and quantity of variables that shape and effect the earth's climate system. They laid a solid foundation for the development of physical climate models and increased the level of their reliability and outputs and also confirmed the man-made nature of global warming. Based on climate models, it is now possible to predict the future conditions of the earth and lands under different scenarios of human behaviors with the environment.b) The Glasgow Climate Change Conference (COP26) has confirmed that the global average temperature has increased by 1.1 degrees Celsius since the beginning of the industrial revolution, and 90% of this increase, which is mainly due to greenhouse gas (GHG) emissions, is human-induced. The main motivation of the conference was to coordinate and commit countries to achieve the following goals: 1) Secure global net- zero emissions by the mid-century, and keep warming to 1.5 degrees Celsius to prevent catastrophic events; 2) Agreement and compatibility for protecting communities and natural habitats; 3) Collaborate to mobilize financial resources to implement these objectives; and 4) Finally work together to deliver and implement the goals of the Paris agreement (the detailed rules that make the Paris Agreement operational.c) The quantity and quality of our national researches on climate change is evaluated positive, however it seems necessary to redefine research topics in the agricultural sector towards mitigation of agricultural-induced GHG emissions, and adaptation to climate change.In conclusion, though, the achievements of the conference to save our planet are disappointing, but at the same time, the agreements reached are positive steps in slowing down the global warming.

Temperature is a key variable in climate and agriclutiral studies especially crop models, water requirement estimation and climate change. Despite of ease of measurement and large number of recording stations, data gaps in remote areas and the need for downscaling the grided climate model output has led to development of weather generators. In this study, the skill of Stochastic Harmonic Autoregressive Parametric (SHArP)SHArP weather generator in simulation of the daily maximum and minimum air temperature on a daily scale in 4 weather stations was evaluated. For this purpose, maximum and minimum temperature data as well as CNRM CMIP5 climate model projections were used in four synoptic stations of Kerman, Ahvaz, Karaj and Tabriz during the period of 2000-2015. The results of Pearson correlation coefficient showed that there is a significant correlation between observed data (0.78 to 0.93) and climatic model outputs.Comparing the observed and simulated temperature data generated by the SHArP model showed a good agreement and significant correlation which confirms the skill of this generator. The correlation coefficient in the studied stations varies between 0.80 to 0.95. The highest value of this coefficient belonged to the maximum temperature. The SHArp model also less simulates the temperature. In general, the findings of this study revealed that the SHArP model is capable to generate temperature data and can be used for filling the gaps.

To evaluate the effects of climate change on irrigated wheat yield, Cv. Mehregan, under drought stress condition, a completely randomized block design (CRBD) experiment was carried out during 2019-2020 cropping season in Varamin, Iran. Five treatments of Control (T1), without stress, drought stress in booting stage (T2), flowering stage (T3), milking stage (T4) and doughing stage (T5) were assigned to three replications. In this study, simulation of the future climate, 2025 and 2055 (2010-2039 and 2069-2040), were performed using the outputs of HadGEM general circulation model under RCP4.5 and RCP8.5 climate scenarios. For this purpose outputs of AgMIP model were employed using long-term climatic data of the base period (1980-2009). Based on these findings, under RCP4.5 and RCP8.5 scenarios, the minimum and maximum temperature parameters might increase for the 2025 and 2055 periods. Also, under RCP4.5 scenario rainfall might increase by 9.4% and 21%, for 2025 and 2055 periods, respectively. However, under RCP8.5 scenario, it might decrease by 1.9% and 2.8%, respectively. Drought stress shortened the phonological stages, the number of days after planting to flowering, ripening and the grain filling periods under climate change conditions. The results also showed that under RCP4.5 scenario in 2025 period the highest decrease in dry matter (4 percent) and seed yield (10.2 percent), due to stress condition, occur during booting and flowering stages, respectively.

The aim of this study was to determine the appropriate time for supplementary irrigation rainfed fig trees in Estahban region, Fars province south of Iran using canopy and meteorological data. In a 2-year experiment, different water stresse levels were applied to rainfed Fig trees and soil moisture was measured at different time intervals. For determination of supplementary irrigation timing based on crop water stress index, soil moisture, the air and plant canopy temperature, were measured. The experiment treatments consisted of a control (without irrigation) and supplementary irrigation at water stress index of 0, 0.2, 0.4, 0.6, 0.8. In each treatment, irrigation was applied at a time when the water stress was just above the selected threshold. Trees were irrigated by tanker as the concentional method in this region. The results of the study showed that the maximum stress occurred in stress index of 0.6 in late July when the soil moisture was about 12%. In spring, the beginning of water stress period, was observed at soil moisture of 14%. Simple equations for predicting the onset of water stress with respect to rainfall and evaporation are presented, which can be used to determine the time of supplementary irrigation. A set of the water–yield relationships were also proposed.

Rising greenhouse gases and the resulting increase temperature have disrupted the balance of the earth climate system. Combined increase in temperature and humidity above a certain threshold causes stress in livestock like dairy cows, which reduces milk production. To assess the effect of heat stress on livestock, a so-called temperature-humidity index (THI) is used. The aim of this study is to investigate the possible effects of climate change on THI in two stations located in north of Iran namely, Babolsar and Ramsar For this purpose, the projected values of THI under three climate change scenarios i.e. RCP2.6, RCP4.5, RCP8.5 were downscaled using SDSM weather generator. The results showed that there exist a significant positive trend in THI time series in both baseline (1961-2005) and future periods. According to results of this study, it is projected that number of days with heat stress would increase and more severe classes of THI will occur. The findings also indicated that the stress conditions in Babolsar have been more severe than Ramsar, such that, during the baseline period, Ramsar and Babolsar stations had 4 and 5 months of a year with heat stress , respectively, while it is projected that by the end of the century, these figures will increase to 6 and 7 months, respectively. Besides, the results showed that in the baseline period days with severe stress class (risk of mortality of dairy cattle) were not recorded in any of the studied stations, but for the far future period (2071-2100) in Ramsar and Babolsar stations, severe condition is projected to occur in two and six days of the year, respectively, which is a serious warning for the province's livestock industry.

From March 1 to April 4, 2019, three flash-flood events occurred across different areas of Iran. The purpose of this study is to select the optimum configuration of RegCM4. 7 regional climate model for weekly precipitation prediction several days ahead of these extreme events. For this purpose, the RegCM4. 7 climate model was run using the CFSv. 2 general circulation model boundary layer conditions and cumulus convection scheme. The results were compared with the ERA5 reanalysis using Taylor diagram and Kling Gupta (KGE) index. Accumulated precipitation of each of the three selected weeks was predicted in 6 different lead times. To select the best convection schemes, six of them namely. Tiedtke, Emanuel, Grell, Kian, Kou and MM5 shallow water were evaluated under the conditions of extreme events. In the first stage, the Tiedtke, Emanuel and Grell schemes showed better performance compared to other schemes. In the second stage, the effect of different boundary layer schemes was investigated. It was found that Tiedtke -Holtslag, Tiedtke -UW and Grell-UW are the most appropriate configuration of RegCM4. 7 model in predicting heavy rainfall in the study period, respectively. Although good KGE values was only obtained for one week ahead, but the correlation coefficients were relatively good for hindcast with lead time of 2-4 weeks. Despite of low KGE values for the weeks beyond second week, acceptable correlations coefficients confirms that the RegCM4. 7 model under the Tiedtke -Holtlag configuration is capable of weekly cumulative prediction precipitation well in advance, although it has weak capability in predicting precipitation spatial pattern.

Due to the spatial variations of evapotranspiration, and lack of adequate point estimations using interpolation methods for spatial analysis is necessary. The aim of this study was to estimate the regional values of reference evapotranspiration (ETo) in Kermanshah province, west of Iran and comparison with Iran National Water Document. For this purpose, daily weather data of 38 meteorological stations of Kermanshah and neighboring provinces were obtained from the Iran Meteorological Organization. Three methods were used for calculation and zoning of ETo, based on Penman and Penman-Monteith equations. In the first and second methods, the meteorological data were interpolated and then ETo was calculated using the interpolated data, while in the third method the point estimation of ETo (weather stations) were interpolated. For the purpose of interpolation, the CGMS software was used in a gridded network of 366 cells with 10 × 10 km size. The results showed that there exist a significant spatial variations ETo across the province. In general, in the western regions of the province, with higher temperature and lower altitude, higher values of ETo was observed. The ETo estimations based on Penman-Monteith method were higher than Penman method. Although the ETo values presented in the Iran National Water Document are calculated by the Penman-Monteith equation, but obtained amount for plain regions of the province are more consistent with Penman- equation estimations.