Assessment of the impacts of climate change on agro-climatic indices in Iran

Kamyar, Asghar; Yazdanpanah, H; Movahedi, Saeed; Morimoto, David

doi:10.1007/s00704-020-03385-z

Cited by 3 publications

(2 citation statements)

References 37 publications

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“…The assessment of how the current (and future) climate is suitable for agriculture is essential for many users in the agricultural community (planners, land managers, farmers, plant breeders, etc.). For this purpose, Agro-climatic Indicators (AgcIs) have been developed [7][8][9][10][11][12]. Derived from climate variables, AgcIs characterize plant-climate interactions, such as the impact of temperature on plant growth and productivity, and the response of plants to water stress and drought conditions.…”

Section: Introductionmentioning

confidence: 99%

“…They provide synthetic information regarding climate influence on crop functioning. Over the last years, AgcIs were extensively used to better understand and manage climate-related risks in agriculture [7][8][9][10]. In addition to being understandable to the agricultural users, AgcIs are effective in encouraging stakeholders to consider the potential impacts of climate change on their land-use systems and in adapting to this issue [13].…”

Section: Introductionmentioning

confidence: 99%

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Evaluation of Five Reanalysis Products over France: Implications for Agro-Climatic Studies

Er-Rondi,

Troin,

Coly

et al. 2024

Applied Sciences

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Agro-climatic indicators (AgcIs) provide a suitable tool to evaluate the implications of climate change on agriculture by simplifying plant–climate interactions. However, developing reliable AgcIs requires high-quality historical climate datasets. Consequently, reanalysis products (RPs) are frequently used as a potential reference dataset for observed climate in agricultural studies. This study aims to compare five RPs (ERA5, ERA5-Land, SCOPE Climate, FYRE Climate, and RFHR) at reproducing observed AgcIs over France. The RPs are evaluated against the SYNOP meteorological data over the 1996–2012 period, focusing on six AgcIs specific to apple, maize, and vine crops. The findings show that RPs perform well in reproducing temperature-based AgcIs, with some slight discrepancies in areas with complex topography. However, all RPs tend to overestimate precipitation amounts and to underestimate dry days, leading to a poor performance in reproducing precipitation-based AgcIs. This study emphasizes the need for a thorough evaluation of the RPs in developing both temperature-based and precipitation-based AgcIs, especially if findings are intended to support operational agricultural decision-making.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Evaluation of Five Reanalysis Products over France: Implications for Agro-Climatic Studies

Er-Rondi,

Troin,

Coly

et al. 2024

Applied Sciences

View full text Add to dashboard Cite

show abstract

Historical variability and future changes in seasonal extreme temperature over Iran

Zarrin

Dadashi-Roudbari

Hassani

2021

Theor Appl Climatol

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The extreme temperature indices (ETI) are an important indicator of climate change, the detection of their changes over the next years can play an important role in the Climate Action Plan (CAP). In this study, four temperature indices (Mean of daily minimum temperature (TN), Mean of daily maximum temperature (TX), Cold-spell duration index (CSDI), and Warm-spell duration index (WSDI)) were de ned by ETCCDI and two new indices of the Maximum number of consecutive frost days (CFD) and the Maximum number of consecutive summer days (CSU) were calculated to examine ETIs in Iran under climate change conditions. We used minimum and maximum daily temperature of ve General circulation models (GCMs) including HadGEM2-ES, IPSL-CM5A-LR, GFDL-ESM2M, MIROC-ESM-CHEM, and NorESM1-M from the set of CMIP5 Bias-Correction models. We investigated Two Representative Concentration Pathway (RCP) scenarios of RCP4.5 and RCP8.5 -during the historical and future (2021-2060 and 2061-2100) periods. The performance of each model was evaluated using the Taylor diagram on a seasonal scale. Among models, GFDL-ESM2M and HadGEM2-ES models showed the highest, and NorESM1-M and IPSL-CM5A-LR models showed the lowest performance in Iran. Then an ensemble model was generated using Independence Weighted Mean (IWM) method. The results of multimodel ensembles (MME) showed a higher performance compared to individual CMIP5 models in all seasons. Also, the uncertainty value was signi cantly reduced, and the correlation value of the MME model reached 0.95 in all seasons. Additionally, it is found that WSDI and CSU indices showed positive anomalies in future periods and CSDI and CFD showed negative anomalies throughout Iran. Also, at the end of the 21 st century, no cold spells are projected in almost every part of Iran. The CSU index showed that Iran's summer days are increasing sharply, according to the results of the RCP8.5 scenario in spring (MAM) and autumn (SON), the CSU will increase by 18.79 and 20.51 days, respectively at the end of the 21 st century. It is projected that in the future, the spring and autumn seasons will be shorter and, summers, will be much longer than before.

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Trends of freezing period and its main cause on the Qinghai-Tibetan Plateau from 1961 to 2018

Zhao

Gao

Yang

2021

Theor Appl Climatol

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The ecosystems of Qinghai-Tibetan Plateau (QTP) are very sensitive to climate change because of their unique structure and function. However, little attention has been paid to variations in cold non-growing season. In this study, based on daily mean temperature from 63 meteorological stations throughout the QTP during the period 1961−2018, the spatial and temporal variations in the freezing period (FP) were investigated. The FP was de ned as the period between the date of the rst autumn freeze and the date of the rst spring thaw in the second year. Understanding how the FP changes are imperative in predicting future climate change and decision-making for implementing ecological conservation on the plateau. The results showed that the start of freezing period (SFP) exhibited a pronounced increasing trend with a rate of 0.0704 days year −1 and the end of freezing period (EFP) showed an obviously decreasing trend with a rate of −0.2537 days year −1 at the regional scale. The length of freezing period (LFP) presented a signi cant negative trend at a rate of −0.3256 days year −1 for regional scale, which was mainly attributed to the earlier EFP. Spatially, earlier EFP and shorter LFP mainly occurred in the south and north of the QTP. Furthermore, this study found that the variations in the SFP, EFP, and LFP were highly dependent on the elevation with EFP and LFP are positively correlated with elevation, while SFP is negatively correlated with elevation.

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Assessment of the impacts of climate change on agro-climatic indices in Iran

Cited by 3 publications

References 37 publications

Evaluation of Five Reanalysis Products over France: Implications for Agro-Climatic Studies

Evaluation of Five Reanalysis Products over France: Implications for Agro-Climatic Studies

Historical variability and future changes in seasonal extreme temperature over Iran

Trends of freezing period and its main cause on the Qinghai-Tibetan Plateau from 1961 to 2018

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