Spatio-temporal variation of hydro-climatic variables and extreme indices over Iran based on reanalysis data

Malaekeh, SayedMorteza; Safaie, Ammar; Shiva, Layla; Tabari, Hossein

doi:10.1007/s00477-022-02223-0

Cited by 15 publications

(16 citation statements)

References 102 publications

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“…Similar to growing season lengths, extreme cold events can have both positive and negative impacts on agriculture, depending on the crop types and specific regions (Vogel et al, 2019). Malaekeh et al (2022) highlighted two consequences of climate change that could benefit agriculture in Iran: an increase in growing season length and a decrease in the occurrence of cold extreme events. By incorporating these factors into our econometric analysis, we shed light on their significance in shaping agricultural outcomes and caution against overestimating the adverse impacts of climate change on agriculture.…”

Section: Resultsmentioning

confidence: 99%

“…We take advantage of the highresolution meteorological dataset to tackle the sparse distribution of weather stations in Iran. Malaekeh et al (2022) elaborated on the rationales behind using this gridded dataset instead of land-based observations over Iran in more detail. AgERA5 was corrected towards a finer topography at 0.1 o (compared to ERA5 at 0.25 o ), and it was modified and bias-corrected for the presence of cloud cover, seasonal amendments, and mountainous and coastal areas.…”

Section: Data and Variablesmentioning

confidence: 99%

“…Malaekeh et al. (2022) elaborated on the rationales behind using this gridded dataset instead of land‐based observations over Iran in more detail. AgERA5 was corrected towards a finer topography at

{0.1^{\mathrm{o}}}

(compared to ERA5 at

{0.25^{\mathrm{o}}}

), and it was modified and bias‐corrected for the presence of cloud cover, seasonal amendments, and mountainous and coastal areas.…”

Section: Data and Variablesmentioning

confidence: 99%

“…Malaekeh et al (2022) validated AgERA5's temperature, precipitation, and other hydro-climatic variables (e.g., extreme indices) through a comparison with weather stations in different climate zones and geographical locations across Iran. They also provided a county-level dataset for several hydro-climatic variables and extreme indices by aggregating the gridded dataset from 1986 to 2015.…”

mentioning

confidence: 99%

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Investigating the economic impact of climate change on agriculture in Iran: Spatial spillovers matter

Malaekeh,

Shiva,

Safaie

2024

Agricultural Economics

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In this study, we enhance our understanding of the economic impacts of climate change on agriculture in Iran to provide further information for moving Iran's climate policy forward by linking farmland net revenue to novel climatic and non‐climatic variables. We take advantage of spatial panel econometrics to better circumvent omitted factors extraneous to the agricultural sector and to develop a more reliable and consistent model when data are inherently spatial. In contrast to conventional panel studies which relied on year‐to‐year weather observations, we exploit a hybrid approach to compromise between the disadvantages and advantages of longer‐term cross‐sectional analysis and shorter‐term panel models. We estimate the potential impacts of climate change on agriculture under several global warming scenarios based on the Sixth Phase of the Coupled Model Intercomparison Project (CMIP6). We find that (I) farmlands’ net revenues are projected to decline by 8%–19% and 14%–51% by 2050 and 2080; (II) the distributional impacts of climate change would highly depend on climate zones and geographical locations; (III) a few counties might benefit from climate changes; (IV) finally, failing to account for spatial spillovers when they are present leads to a misspecified model.

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Section: Resultsmentioning

confidence: 99%

Section: Data and Variablesmentioning

confidence: 99%

{0.1^{\mathrm{o}}}

(compared to ERA5 at

{0.25^{\mathrm{o}}}

), and it was modified and bias‐corrected for the presence of cloud cover, seasonal amendments, and mountainous and coastal areas.…”

Section: Data and Variablesmentioning

confidence: 99%

mentioning

confidence: 99%

See 2 more Smart Citations

Investigating the economic impact of climate change on agriculture in Iran: Spatial spillovers matter

Malaekeh,

Shiva,

Safaie

2024

Agricultural Economics

View full text Add to dashboard Cite

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“…This study used 20 precipitation and temperature indices recommended by the Expert Team on Climate Change Detection and Indices (ETCCDI) and described in (Table 1). In dry places where climate change is having an effect, these indices have been used extensively to evaluate the severity and frequency of extreme weather occurrences (Hamed et al, 2022; Hu et al, 2023; Kumar et al, 2020; Malaekeh et al, 2022; Pervin & Khan, 2022).…”

Section: Methodsmentioning

confidence: 99%

A novel approach for evaluation of CMIP6 GCMs in simulating temperature and precipitation extremes of Pakistan

Ali,

Hamed,

Muhammad

et al. 2024

Intl Journal of Climatology

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The study used a hybrid approach to evaluate the performance of 20 global climate models (GCMs) from CMIP6 in reproducing 20 extreme temperature and precipitation indices over Pakistan. This study first analysed the future simulations of extremes and discarded the GCMs whose projections fell outside the 95% confidence interval. The remaining GCMs' performance was evaluated using the Kling Gupta Efficiency‐based criteria. The changes in extreme climatic events in Pakistan were projected using the multi‐model ensemble (MME) median of the selected GCMs for four shared socioeconomic pathways (SSPs) in two future periods, 2020–2059 and 2060–2099. Four GCMs' showed inconsistency in projecting future climatic extremes and were discarded initially. The past performance of the remaining GCMs revealed EC‐Earth3‐Veg‐LR, GFDL‐ESM4, MRI‐ESM2‐0 and NOR‐ESM2‐MM to be effective in reproducing extreme indices for the historical period. The MME median of the selected GCMs showed a gradual increase in most of the temperature and precipitation extreme indices in the future periods for all SSPs across the country. Specifically, it showed a higher increase in daily maximum temperature (TXx) by 4.5–5°C, daily minimum temperature (TNn) by more than 4.5°C, consecutive days with a temperature higher than the 95th percentile (WSDI) by >160 days, one‐day maximum rainfall by 9–15 mm and days with precipitation above the 95th percentile by >50 mm in northern high‐elevated areas during 2060–2099 for SSP585. Similarly, a higher increase in TXx by 4.5–5°C, TNn by >4.5°C, WSDI by 140 days and tropical nights by 40–60 days was also found in the western arid region during 2060–2099 for SSP585. The study highlights that northern high‐elevated and western arid regions are at a higher risk of extreme temperatures and precipitation due to climate change.

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Changes in extreme precipitation indices across Algeria climate zones

Hamitouche,

Zeroual,

Meddi

et al. 2024

Intl Journal of Climatology

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Extreme precipitation events can have a significant impact on the environment, agriculture, economy and safety, making close monitoring of their short‐ and long‐term trends essential for the development of effective mitigation and adaptation strategies. In this study, we analysed 16 in situ observation datasets from four different climate zones in Algeria, spanning from 1969 to 2021. The trend analysis was conducted using the original Mann–Kendall test and seven modified tests to eliminate the effects of short‐term persistence. Our findings reveal a significant increasing trend of extreme precipitation variability for most stations in the Warm Mediterranean climate zone, except for the Consecutive dry days index, which showed a negative trend for the same zone, while stations in the Cold/Warm semi‐arid climate and Cold desert climate (Bwk) zones showed a decreasing trend. Additionally, all index series with significant long‐term trends were affected by a significant shift in their means, which was confirmed by both the Lombard and Pettitt tests. However, when we used the modified MPT and the test eliminating the effects of long‐term persistence, the significance of the shifts and the trend decreased. Our results suggest that while extreme precipitation events have been increasing in some parts of Algeria; the trend may not be statistically significant in the long‐run, indicating the necessity of revisiting and refreshing the findings of previous studies for a more current perspective.

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Spatio-temporal variation of hydro-climatic variables and extreme indices over Iran based on reanalysis data

Cited by 15 publications

References 102 publications

Investigating the economic impact of climate change on agriculture in Iran: Spatial spillovers matter

Investigating the economic impact of climate change on agriculture in Iran: Spatial spillovers matter

A novel approach for evaluation of CMIP6 GCMs in simulating temperature and precipitation extremes of Pakistan

Changes in extreme precipitation indices across Algeria climate zones

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