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Climate Shifts within Major Agricultural Seasons for +1.5 and +2.0 °C Worlds: HAPPI Projections and AgMIP Modeling Scenarios.

Agricultural and forest meteorology

Ruane AC, Phillips MM, Rosenzweig C.
PMID: 30880854
Agric For Meteorol. 2018 Sep 15;259:329-344. doi: 10.1016/j.agrformet.2018.05.013. Epub 2018 Jun 01.

This study compares climate changes in major agricultural regions and current agricultural seasons associated with global warming of +1.5 or +2.0 °C above pre-industrial conditions. It describes the generation of climate scenarios for agricultural modeling applications conducted as part...

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Ruane AC, Phillips MM, Rosenzweig C. Climate Shifts within Major Agricultural Seasons for +1.5 and +2.0 °C Worlds: HAPPI Projections and AgMIP Modeling Scenarios. Agric For Meteorol. 2018;259:329-344doi: 10.1016/j.agrformet.2018.05.013.
Ruane, A. C., Phillips, M. M., & Rosenzweig, C. (2018). Climate Shifts within Major Agricultural Seasons for +1.5 and +2.0 °C Worlds: HAPPI Projections and AgMIP Modeling Scenarios. Agricultural and forest meteorology, 259329-344. https://doi.org/10.1016/j.agrformet.2018.05.013
Ruane, Alex C, et al. "Climate Shifts within Major Agricultural Seasons for +1.5 and +2.0 °C Worlds: HAPPI Projections and AgMIP Modeling Scenarios." Agricultural and forest meteorology vol. 259 (2018): 329-344. doi: https://doi.org/10.1016/j.agrformet.2018.05.013
Ruane AC, Phillips MM, Rosenzweig C. Climate Shifts within Major Agricultural Seasons for +1.5 and +2.0 °C Worlds: HAPPI Projections and AgMIP Modeling Scenarios. Agric For Meteorol. 2018 Sep 15;259:329-344. doi: 10.1016/j.agrformet.2018.05.013. Epub 2018 Jun 01. PMID: 30880854; PMCID: PMC6415298.
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Coordinating AgMIP data and models across global and regional scales for 1.5°C and 2.0°C assessments.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences

Rosenzweig C, Ruane AC, Antle J, Elliott J, Ashfaq M, Chatta AA, Ewert F, Folberth C, Hathie I, Havlik P, Hoogenboom G, Lotze-Campen H, MacCarthy DS, Mason-D'Croz D, Contreras EM, Müller C, Perez-Dominguez I, Phillips M, Porter C, Raymundo RM, Sands RD, Schleussner CF, Valdivia RO, Valin H, Wiebe K.
PMID: 29610385
Philos Trans A Math Phys Eng Sci. 2018 May 13;376(2119). doi: 10.1098/rsta.2016.0455.

The Agricultural Model Intercomparison and Improvement Project (AgMIP) has developed novel methods for Coordinated Global and Regional Assessments (CGRA) of agriculture and food security in a changing world. The present study aims to perform a proof of concept of...

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Rosenzweig C, Ruane AC, Antle J, et al. Coordinating AgMIP data and models across global and regional scales for 1.5°C and 2.0°C assessments. Philos Trans A Math Phys Eng Sci. 2018;376(2119)doi: 10.1098/rsta.2016.0455.
Rosenzweig, C., Ruane, A. C., Antle, J., Elliott, J., Ashfaq, M., Chatta, A. A., Ewert, F., Folberth, C., Hathie, I., Havlik, P., Hoogenboom, G., Lotze-Campen, H., MacCarthy, D. S., Mason-D'Croz, D., Contreras, E. M., Müller, C., Perez-Dominguez, I., Phillips, M., Porter, C., Raymundo, R. M., Sands, R. D., Schleussner, C. F., Valdivia, R. O., Valin, H., & Wiebe, K. (2018). Coordinating AgMIP data and models across global and regional scales for 1.5°C and 2.0°C assessments. Philosophical transactions. Series A, Mathematical, physical, and engineering sciences, 376(2119), . https://doi.org/10.1098/rsta.2016.0455
Rosenzweig, Cynthia, et al. "Coordinating AgMIP data and models across global and regional scales for 1.5°C and 2.0°C assessments." Philosophical transactions. Series A, Mathematical, physical, and engineering sciences vol. 376,2119 (2018). doi: https://doi.org/10.1098/rsta.2016.0455
Rosenzweig C, Ruane AC, Antle J, Elliott J, Ashfaq M, Chatta AA, Ewert F, Folberth C, Hathie I, Havlik P, Hoogenboom G, Lotze-Campen H, MacCarthy DS, Mason-D'Croz D, Contreras EM, Müller C, Perez-Dominguez I, Phillips M, Porter C, Raymundo RM, Sands RD, Schleussner CF, Valdivia RO, Valin H, Wiebe K. Coordinating AgMIP data and models across global and regional scales for 1.5°C and 2.0°C assessments. Philos Trans A Math Phys Eng Sci. 2018 May 13;376(2119). doi: 10.1098/rsta.2016.0455. PMID: 29610385; PMCID: PMC5897826.
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The Global Gridded Crop Model Intercomparison phase 1 simulation dataset.

Scientific data

Müller C, Elliott J, Kelly D, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Hoek S, Izaurralde RC, Jones CD, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Wang X, de Wit A, Yang H.
PMID: 31068583
Sci Data. 2019 May 08;6(1):50. doi: 10.1038/s41597-019-0023-8.

The Global Gridded Crop Model Intercomparison (GGCMI) phase 1 dataset of the Agricultural Model Intercomparison and Improvement Project (AgMIP) provides an unprecedentedly large dataset of crop model simulations covering the global ice-free land surface. The dataset consists of annual...

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Müller C, Elliott J, Kelly D, et al. The Global Gridded Crop Model Intercomparison phase 1 simulation dataset. Sci Data. 2019;6(1):50doi: 10.1038/s41597-019-0023-8.
Müller, C., Elliott, J., Kelly, D., Arneth, A., Balkovic, J., Ciais, P., Deryng, D., Folberth, C., Hoek, S., Izaurralde, R. C., Jones, C. D., Khabarov, N., Lawrence, P., Liu, W., Olin, S., Pugh, T. A. M., Reddy, A., Rosenzweig, C., Ruane, A. C., Sakurai, G., Schmid, E., Skalsky, R., Wang, X., de Wit, A., & Yang, H. (2019). The Global Gridded Crop Model Intercomparison phase 1 simulation dataset. Scientific data, 6(1), 50. https://doi.org/10.1038/s41597-019-0023-8
Müller, Christoph, et al. "The Global Gridded Crop Model Intercomparison phase 1 simulation dataset." Scientific data vol. 6,1 (2019): 50. doi: https://doi.org/10.1038/s41597-019-0023-8
Müller C, Elliott J, Kelly D, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Hoek S, Izaurralde RC, Jones CD, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Wang X, de Wit A, Yang H. The Global Gridded Crop Model Intercomparison phase 1 simulation dataset. Sci Data. 2019 May 08;6(1):50. doi: 10.1038/s41597-019-0023-8. PMID: 31068583; PMCID: PMC6506552.
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Global wheat production with 1.5 and 2.0°C above pre-industrial warming.

Global change biology

Liu B, Martre P, Ewert F, Porter JR, Challinor AJ, Müller C, Ruane AC, Waha K, Thorburn PJ, Aggarwal PK, Ahmed M, Balkovič J, Basso B, Biernath C, Bindi M, Cammarano D, De Sanctis G, Dumont B, Espadafor M, Eyshi Rezaei E, Ferrise R, Garcia-Vila M, Gayler S, Gao Y, Horan H, Hoogenboom G, Izaurralde RC, Jones CD, Kassie BT, Kersebaum KC, Klein C, Koehler AK, Maiorano A, Minoli S, Montesino San Martin M, Naresh Kumar S, Nendel C, O'Leary GJ, Palosuo T, Priesack E, Ripoche D, Rötter RP, Semenov MA, Stöckle C, Streck T, Supit I, Tao F, Van der Velde M, Wallach D, Wang E, Webber H, Wolf J, Xiao L, Zhang Z, Zhao Z, Zhu Y, Asseng S.
PMID: 30536680
Glob Chang Biol. 2018 Dec 07; doi: 10.1111/gcb.14542. Epub 2018 Dec 07.

Efforts to limit global warming to below 2°C in relation to the pre-industrial level are under way, in accordance with the 2015 Paris Agreement. However, most impact research on agriculture to date has focused on impacts of warming >2°C...

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Liu B, Martre P, Ewert F, et al. Global wheat production with 1.5 and 2.0°C above pre-industrial warming. Glob Chang Biol. 2018;doi: 10.1111/gcb.14542.
Liu, B., Martre, P., Ewert, F., Porter, J. R., Challinor, A. J., Müller, C., Ruane, A. C., Waha, K., Thorburn, P. J., Aggarwal, P. K., Ahmed, M., Balkovič, J., Basso, B., Biernath, C., Bindi, M., Cammarano, D., De Sanctis, G., Dumont, B., Espadafor, M., Eyshi Rezaei, E., Ferrise, R., Garcia-Vila, M., Gayler, S., Gao, Y., Horan, H., Hoogenboom, G., Izaurralde, R. C., Jones, C. D., Kassie, B. T., Kersebaum, K. C., Klein, C., Koehler, A. K., Maiorano, A., Minoli, S., Montesino San Martin, M., Naresh Kumar, S., Nendel, C., O'Leary, G. J., Palosuo, T., Priesack, E., Ripoche, D., Rötter, R. P., Semenov, M. A., Stöckle, C., Streck, T., Supit, I., Tao, F., Van der Velde, M., Wallach, D., Wang, E., Webber, H., Wolf, J., Xiao, L., Zhang, Z., Zhao, Z., Zhu, Y., & Asseng, S. (2018). Global wheat production with 1.5 and 2.0°C above pre-industrial warming. Global change biology, . https://doi.org/10.1111/gcb.14542
Liu, Bing, et al. "Global wheat production with 1.5 and 2.0°C above pre-industrial warming." Global change biology vol. (2018). doi: https://doi.org/10.1111/gcb.14542
Liu B, Martre P, Ewert F, Porter JR, Challinor AJ, Müller C, Ruane AC, Waha K, Thorburn PJ, Aggarwal PK, Ahmed M, Balkovič J, Basso B, Biernath C, Bindi M, Cammarano D, De Sanctis G, Dumont B, Espadafor M, Eyshi Rezaei E, Ferrise R, Garcia-Vila M, Gayler S, Gao Y, Horan H, Hoogenboom G, Izaurralde RC, Jones CD, Kassie BT, Kersebaum KC, Klein C, Koehler AK, Maiorano A, Minoli S, Montesino San Martin M, Naresh Kumar S, Nendel C, O'Leary GJ, Palosuo T, Priesack E, Ripoche D, Rötter RP, Semenov MA, Stöckle C, Streck T, Supit I, Tao F, Van der Velde M, Wallach D, Wang E, Webber H, Wolf J, Xiao L, Zhang Z, Zhao Z, Zhu Y, Asseng S. Global wheat production with 1.5 and 2.0°C above pre-industrial warming. Glob Chang Biol. 2018 Dec 07; doi: 10.1111/gcb.14542. Epub 2018 Dec 07. PMID: 30536680.
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Biophysical and economic implications for agriculture of +1.5° and +2.0°C global warming using AgMIP Coordinated Global and Regional Assessments.

Climate research

Ruane AC, Antle J, Elliott J, Folberth C, Hoogenboom G, Mason-D'Croz D, Müller C, Porter C, Phillips MM, Raymundo RM, Sands R, Valdivia RO, White JW, Wiebe K, Rosenzweig C.
PMID: 33154611
Clim Res. 2018;76(1):17-39. doi: 10.3354/cr01520. Epub 2018 Sep 04.

This study presents results of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Coordinated Global and Regional Assessments (CGRA) of +1.5° and +2.0°C global warming above pre-industrial conditions. This first CGRA application provides multi-discipline, multi-scale, and multi-model perspectives to...

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Ruane AC, Antle J, Elliott J, et al. Biophysical and economic implications for agriculture of +1.5° and +2.0°C global warming using AgMIP Coordinated Global and Regional Assessments. Clim Res. 2018;76(1):17-39doi: 10.3354/cr01520.
Ruane, A. C., Antle, J., Elliott, J., Folberth, C., Hoogenboom, G., Mason-D'Croz, D., Müller, C., Porter, C., Phillips, M. M., Raymundo, R. M., Sands, R., Valdivia, R. O., White, J. W., Wiebe, K., & Rosenzweig, C. (2018). Biophysical and economic implications for agriculture of +1.5° and +2.0°C global warming using AgMIP Coordinated Global and Regional Assessments. Climate research, 76(1), 17-39. https://doi.org/10.3354/cr01520
Ruane, Alex C, et al. "Biophysical and economic implications for agriculture of +1.5° and +2.0°C global warming using AgMIP Coordinated Global and Regional Assessments." Climate research vol. 76,1 (2018): 17-39. doi: https://doi.org/10.3354/cr01520
Ruane AC, Antle J, Elliott J, Folberth C, Hoogenboom G, Mason-D'Croz D, Müller C, Porter C, Phillips MM, Raymundo RM, Sands R, Valdivia RO, White JW, Wiebe K, Rosenzweig C. Biophysical and economic implications for agriculture of +1.5° and +2.0°C global warming using AgMIP Coordinated Global and Regional Assessments. Clim Res. 2018;76(1):17-39. doi: 10.3354/cr01520. Epub 2018 Sep 04. PMID: 33154611; PMCID: PMC7641099.
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Future climate change could reduce irrigated and rainfed wheat water footprint in arid environments.

The Science of the total environment

Deihimfard R, Rahimi-Moghaddam S, Collins B, Azizi K.
PMID: 34656577
Sci Total Environ. 2022 Feb 10;807:150991. doi: 10.1016/j.scitotenv.2021.150991. Epub 2021 Oct 15.

The concept of water footprint (WF) has been used to manage freshwater resources for the past two decades and is considered as indicator of the sustainability of agricultural systems. Accordingly, the current study aimed to quantify WF and its...

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Deihimfard R, Rahimi-Moghaddam S, Collins B, et al. Future climate change could reduce irrigated and rainfed wheat water footprint in arid environments. Sci Total Environ. 2021;807:150991doi: 10.1016/j.scitotenv.2021.150991.
Deihimfard, R., Rahimi-Moghaddam, S., Collins, B., & Azizi, K. (2022). Future climate change could reduce irrigated and rainfed wheat water footprint in arid environments. The Science of the total environment, 807150991. https://doi.org/10.1016/j.scitotenv.2021.150991
Deihimfard, Reza, et al. "Future climate change could reduce irrigated and rainfed wheat water footprint in arid environments." The Science of the total environment vol. 807 (2022): 150991. doi: https://doi.org/10.1016/j.scitotenv.2021.150991
Deihimfard R, Rahimi-Moghaddam S, Collins B, Azizi K. Future climate change could reduce irrigated and rainfed wheat water footprint in arid environments. Sci Total Environ. 2022 Feb 10;807:150991. doi: 10.1016/j.scitotenv.2021.150991. Epub 2021 Oct 15. PMID: 34656577.
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Future climate change could reduce irrigated and rainfed wheat water footprint in arid environments.

The Science of the total environment

Deihimfard R, Rahimi-Moghaddam S, Collins B, Azizi K.
PMID: 34656577
Sci Total Environ. 2021 Oct 15;150991. doi: 10.1016/j.scitotenv.2021.150991. Epub 2021 Oct 15.

The concept of water footprint (WF) has been used to manage freshwater resources for the past two decades and is considered as indicator of the sustainability of agricultural systems. Accordingly, the current study aimed to quantify WF and its...

Cite
Deihimfard R, Rahimi-Moghaddam S, Collins B, et al. Future climate change could reduce irrigated and rainfed wheat water footprint in arid environments. Sci Total Environ. 2021;150991doi: 10.1016/j.scitotenv.2021.150991.
Deihimfard, R., Rahimi-Moghaddam, S., Collins, B., & Azizi, K. (2021). Future climate change could reduce irrigated and rainfed wheat water footprint in arid environments. The Science of the total environment, 150991. https://doi.org/10.1016/j.scitotenv.2021.150991
Deihimfard, Reza, et al. "Future climate change could reduce irrigated and rainfed wheat water footprint in arid environments." The Science of the total environment vol. (2021): 150991. doi: https://doi.org/10.1016/j.scitotenv.2021.150991
Deihimfard R, Rahimi-Moghaddam S, Collins B, Azizi K. Future climate change could reduce irrigated and rainfed wheat water footprint in arid environments. Sci Total Environ. 2021 Oct 15;150991. doi: 10.1016/j.scitotenv.2021.150991. Epub 2021 Oct 15. PMID: 34656577.
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An AgMIP framework for improved agricultural representation in IAMs.

Environmental research letters : ERL [Web site]

Ruane AC, Rosenzweig C, Asseng S, Boote KJ, Elliott J, Ewert F, Jones JW, Martre P, McDermid SP, Müller C, Snyder A, Thorburn PJ.
PMID: 30881482
Environ Res Lett. 2017 Dec;12(12). doi: 10.1088/1748-9326/aa8da6. Epub 2017 Nov 24.

Integrated assessment models (IAMs) hold great potential to assess how future agricultural systems will be shaped by socioeconomic development, technological innovation, and changing climate conditions. By coupling with climate and crop model emulators, IAMs have the potential to resolve...

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Ruane AC, Rosenzweig C, Asseng S, et al. An AgMIP framework for improved agricultural representation in IAMs. Environ Res Lett. 2017;12(12)doi: 10.1088/1748-9326/aa8da6.
Ruane, A. C., Rosenzweig, C., Asseng, S., Boote, K. J., Elliott, J., Ewert, F., Jones, J. W., Martre, P., McDermid, S. P., Müller, C., Snyder, A., & Thorburn, P. J. (2017). An AgMIP framework for improved agricultural representation in IAMs. Environmental research letters : ERL [Web site], 12(12), . https://doi.org/10.1088/1748-9326/aa8da6
Ruane, Alex C, et al. "An AgMIP framework for improved agricultural representation in IAMs." Environmental research letters : ERL [Web site] vol. 12,12 (2017). doi: https://doi.org/10.1088/1748-9326/aa8da6
Ruane AC, Rosenzweig C, Asseng S, Boote KJ, Elliott J, Ewert F, Jones JW, Martre P, McDermid SP, Müller C, Snyder A, Thorburn PJ. An AgMIP framework for improved agricultural representation in IAMs. Environ Res Lett. 2017 Dec;12(12). doi: 10.1088/1748-9326/aa8da6. Epub 2017 Nov 24. PMID: 30881482; PMCID: PMC6417889.
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Next generation agricultural system data, models and knowledge products: Introduction.

Agricultural systems

Antle JM, Jones JW, Rosenzweig CE.
PMID: 28701811
Agric Syst. 2017 Jul;155:186-190. doi: 10.1016/j.agsy.2016.09.003.

Agricultural system models have become important tools to provide predictive and assessment capability to a growing array of decision-makers in the private and public sectors. Despite ongoing research and model improvements, many of the agricultural models today are direct...

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Antle JM, Jones JW, Rosenzweig CE. Next generation agricultural system data, models and knowledge products: Introduction. Agric Syst. 2017;155:186-190doi: 10.1016/j.agsy.2016.09.003.
Antle, J. M., Jones, J. W., & Rosenzweig, C. E. (2017). Next generation agricultural system data, models and knowledge products: Introduction. Agricultural systems, 155186-190. https://doi.org/10.1016/j.agsy.2016.09.003
Antle, John M, et al. "Next generation agricultural system data, models and knowledge products: Introduction." Agricultural systems vol. 155 (2017): 186-190. doi: https://doi.org/10.1016/j.agsy.2016.09.003
Antle JM, Jones JW, Rosenzweig CE. Next generation agricultural system data, models and knowledge products: Introduction. Agric Syst. 2017 Jul;155:186-190. doi: 10.1016/j.agsy.2016.09.003. PMID: 28701811; PMCID: PMC5485643.
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Importance of the description of light interception in crop growth models.

Plant physiology

Liu S, Baret F, Abichou M, Manceau L, Andrieu B, Weiss M, Martre P.
PMID: 33710303
Plant Physiol. 2021 Jun 11;186(2):977-997. doi: 10.1093/plphys/kiab113.

Canopy light interception determines the amount of energy captured by a crop, and is thus critical to modeling crop growth and yield, and may substantially contribute to the prediction uncertainty of crop growth models (CGMs). We thus analyzed the...

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Liu S, Baret F, Abichou M, et al. Importance of the description of light interception in crop growth models. Plant Physiol. 2021;186(2):977-997doi: 10.1093/plphys/kiab113.
Liu, S., Baret, F., Abichou, M., Manceau, L., Andrieu, B., Weiss, M., & Martre, P. (2021). Importance of the description of light interception in crop growth models. Plant physiology, 186(2), 977-997. https://doi.org/10.1093/plphys/kiab113
Liu, Shouyang, et al. "Importance of the description of light interception in crop growth models." Plant physiology vol. 186,2 (2021): 977-997. doi: https://doi.org/10.1093/plphys/kiab113
Liu S, Baret F, Abichou M, Manceau L, Andrieu B, Weiss M, Martre P. Importance of the description of light interception in crop growth models. Plant Physiol. 2021 Jun 11;186(2):977-997. doi: 10.1093/plphys/kiab113. PMID: 33710303; PMCID: PMC8253170.
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