AgMIP Regional Integrated Assessments: High-level Findings, Methods, Tools, and Studies (2012–2017)

Rosenzweig, Cynthia; Mutter, Carolyn Z.; Ruane, Alex C.; Contreras, Erik Mencos; Boote, Kenneth J.; Valdivia, Roberto O.; Houtkamp, J.M.; MacCarthy, Dilys S.; Claessens, Lieven; Adhikari, Roshan; Durand, Wiltrud; Kee-Tui, Sabine Homann; Ahmad, Ashfaq; Subash, N.; Geethalakshmi, V.; Nedumaran, Swamikannu

doi:10.1142/9781786348791_0005

Cited by 3 publications

(2 citation statements)

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“…Downscaled future climate data as shown in Table 1 derived from five ensemble representative GCMs, namely, CSIRO-Mk3.6.0, HadGEM2-ES, IPSL.CM5A-MR, MIROC5 and MRI.GCM3 were selected out of the 20 GCMs that are available in the AgMIP climate scenario (Hudson and Ruane, 2015;Rosenzweig et al, 2015) ensembled for two RCP's (RCP 4.5 and RCP 8.5) and two time periods; 2050s (2040-2069) and 2080s (2070-2099) including the baseline scenario . These five GCMs were selected due to their long history of development and evaluation, a preference for higher resolution, and established performance in monsoon regions (Rosenzweig et al, 2013b).…”

Section: Historical Meteorological Data and Future Climate Scenarios ...mentioning

confidence: 99%

Analysis of projected climate change in sorghum growing semi-arid rift valley of Ethiopia

Lupi Edao,

Dechassa,

Merga

et al. 2024

IJAm

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Global warming projected to have a significant impact on agricultural water availability for crops in Africa in particularly in Ethiopia. Therefore, the study was conducted to analyze the projected change of temperature and rainfall in sorghum growing semi-arid rift valley of Ethiopia. The weather data for 11 stations were generated using AgiMP5 technique for RCP 4.5 and 8.5 and for the period of 2050s and 2080s. MAKESENS employed for the detection of trend of extreme indices. InStat v3.37 were used for the analysis of start, end, and length of growth season. Under RCP 4.5, the projected mean annual minimum air temperatures in CRV, ERVE and NRVE could increase respectively by 1.9 °C (2050s) and 2.6 °C (2080s), 1.8 °C (2050s) and 2.5 °C (2080s) and 1.88 °C (2050s) and 2.69 °C (2080s). Under RCP 8.5, however, with same location it will projected to increase in both time frames (2050s and 2080s) in all studied sites. The mean annual maximum air temperature, projected under RCP 4.5 in the CRV, ERV and NRVE will increase by 1.59 °C (2050s) and 2.18°C (2080s),1.42 °C (2050s) and 2.08 °C (2080s) and 1.46 °C (2050s) and 2.09 °C (2080s) respectively. However, under the RCP 8.5, at same regions it projected to rise in both periods (2050s and 2080s). This will be convoy with increase of the hot and cold extremes’ indices in regions. The mean percentage change of annual rainfall is projected to decrease insignificantly in (0.6-5.5% and 2.6%) and increase (0.85-12.3% and 22.3%) in half of the stations located in CRV and ERVE, whereas, in NRVE it will projected to increase (6.1-14.6%) under RCP 4.5 in all stations in 2050s. Though the annual projected rainfall under RCP 4.5 in 2080s will decline in range of 2.1-10.1%, 3.12-4.5% and 0.9-4.6% at CRV, ERVE and NRVE respectively. In most of the location in CRV and ERVE stations growing season rainfall will projected to decline from 1.45% to 53.8% and 0.8 to 8.8%, whereas, in NRVE it will projected to increase in 9.2 to 19% under RCP 4.5 in period of 2050. The projected SOS will be changed in mixed pattern, whereas and LGP will prolonged in most locations. The findings indicated that there has been a change of projected climate change in semi-arid RV, which will be alter the agricultural practices in depletion of soil moisture. Therefore, in adjusting planting timing and using early/medium maturation sorghum varieties, may be necessary for farmers in the region. Soil and water management needs attention.

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Section: Historical Meteorological Data and Future Climate Scenarios ...mentioning

confidence: 99%

Analysis of projected climate change in sorghum growing semi-arid rift valley of Ethiopia

Lupi Edao,

Dechassa,

Merga

et al. 2024

IJAm

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“…An applied GLG interactions approach reveals unanticipated consequences of a U.S. climate policy-both in terms of local and global environmental quality as well as food security. Regional and national-scale crop modeling applications add information on more diverse farming systems and can connect to household-level socioeconomic information for regional integrated assessment (Freduah et al 2019, Rosenzweig et al 2021. This requires additional details on agricultural conditions and further bias-adjustment and downscaling of climate information to represent household conditions Ruane et al 2015.…”

Section: How Can Glg Perspectives Improve Our Modeling Approach?mentioning

confidence: 99%

Global-to-local-to-global interactions and climate change

Baldos

Chepeliev

Cultice

et al. 2023

Environ. Res. Lett.

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Climate change by its very nature epitomizes the necessity and usefulness of the globalto-local-to-global (GLG) paradigm. It is a global problem with the potential to affect localcommunities and ecosystems. Accumulation of local impacts and responses to climate changefeeds back to regional and global systems creating feedback loops. Understanding these compleximpacts and interactions is key to developing more resilient adaptation measures anddesigning more efficient mitigation policies. To this date, however, GLG interactions havenot yet been an integrative part of the decision-support toolkit. The typical approach eithertraces the impacts of global action on the local level or estimates the implications of localpolicies at the global scale. The first approach misses cumulative feedback of local responsesthat can have regional, national or global impacts. In the second case, one undermines aglobal context of the local actions most likely misrepresenting the complexity of the localdecision-making process. Potential interactions across scales are further complicated by thepresence of cascading impacts, connected risks and tipping points. Capturing these dimensionsis not always a straightforward task and often requires a departure from conventionalmodeling approaches. In this paper, we review the state-of-the-art approaches to modelingGLG interactions in the context of climate change. We further identify key limitationsthat drive the lack of GLG coupling cases and discuss what could be done to address thesechallenges.

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Application of CSM-CANEGRO Model for Climate Change Impact Assessment and Adaptation for Sugarcane in Semi-arid Environment of Southern Punjab, Pakistan

Nadeem

Khan

Abbas

et al. 2022

Int. J. Plant Prod.

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AgMIP Regional Integrated Assessments: High-level Findings, Methods, Tools, and Studies (2012–2017)

Cited by 3 publications

References 0 publications

Analysis of projected climate change in sorghum growing semi-arid rift valley of Ethiopia

Analysis of projected climate change in sorghum growing semi-arid rift valley of Ethiopia

Global-to-local-to-global interactions and climate change

Application of CSM-CANEGRO Model for Climate Change Impact Assessment and Adaptation for Sugarcane in Semi-arid Environment of Southern Punjab, Pakistan

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