FACCE-JPI Knowledge Hub: MACSUR-Partner 25

FACCE-JPI 知识中心：MACSUR-合作伙伴 25

• 批准号: BB/N004825/1
• 负责人: Mikhail Semenov
• 金额: $ 5.52万
• 依托单位: Rothamsted Research
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2015
• 资助国家: 英国
• 起止时间: 2015 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FN004825%2F1
• 关键词: FACCE; JPI; Knowledge; Hub; MACSUR

The key challenges that CropM have addressed in the first phase of MACSUR were: (i) crop model intercomparison and improvement, (ii) data management, (iii) methods of scaling and model linking, (iv) scenario development and impact uncertainty evaluation, (v) capacity building and (vi) the development of methodological case and integrated pilot studies on impact assessment. Recently, an overview has been completed on the state of the art of crop models to assess climate change risks to food. Progress on the number of simulated crops, uncertainty propagation related to model parameters and structure, adaptations and scaling are less advanced and lagging behind integrated assessment and modelling (IAM) demands. The limitations are considered substantial and apply to all crop models (to a different extent). Overcoming these limitations will require joint efforts, particularly for multi-model ensemble simulations and consideration of novel modelling approaches. The key challenges of CropM in MACSUR2 are to further advance crop modelling for improved assessment of climate change impacts on food security. Particular emphasis will be on cross-cutting activities to advance crop modelling as integrated part of IAM. Like in MACSUR1, the knowledge hub strategy includes the stimulation of excellent science, the support of capacity and network building activities, jointly work on explicit and comprehensive case studies on integrated regional and Europe-wide climate risk assessment in close interaction with stakeholders.

农作物管理局在MACSUR第一阶段处理的主要挑战是：（一）作物模型相互比较和改进，（二）数据管理，（三）定标和模型连接方法，（四）设想发展和影响不确定性评估，（五）能力建设，（六）发展方法案例和影响评估综合试点研究。最近，完成了一项关于评估气候变化对粮食风险的作物模型最新技术水平的综述。在模拟作物的数量、与模型参数和结构有关的不确定性传播、调整和缩放方面的进展不太先进，落后于综合评估和建模的需求。这些限制被认为是巨大的，适用于所有作物模型（在不同程度上）。克服这些限制需要共同努力，特别是在多模型集合模拟方面，并考虑新的建模方法。MACSUR2中CropM的主要挑战是进一步推进作物建模，以改善气候变化对粮食安全影响的评估。将特别强调跨领域活动，以推进作物建模，作为综合管理的组成部分。与MACSUR 1一样，知识中心战略包括激励优秀的科学，支持能力和网络建设活动，与利益攸关方密切互动，共同开展关于综合区域和欧洲范围气候风险评估的明确和全面的案例研究。

项目成果

Monthly-to-seasonal predictions of durum wheat yield over the Mediterranean Basin

• DOI: 10.3354/cr01325
• 发表时间: 2015-09
• 期刊: Climate Research
• 影响因子: 1.1
• 作者: R. Ferrise;P. Toscano;M. Pasqui;M. Moriondo;J. Primicerio;M. Semenov;M. Bindi

Crop model improvement reduces the uncertainty of the response to temperature of multi-model ensembles

• DOI: 10.1016/j.fcr.2016.05.001
• 发表时间: 2017-02-15
• 期刊: FIELD CROPS RESEARCH
• 影响因子: 5.8
• 作者: Maiorano, Andrea;Martre, Pierre;Zhu, Yan
• 通讯作者: Zhu, Yan

Temperature and Precipitation Effects on Wheat Yield Across a European Transect: a Crop Model Ensemble Analysis Using Impact Response Surfaces

• DOI: 10.3354/cr01322
• 发表时间: 2015-09
• 期刊: Climate Research
• 影响因子: 1.1
• 作者: Nina Pirttioja;T. Carter;S. Fronzek;M. Bindi;H. Hoffmann;T. Palosuo;M. Ruíz-Ramos;F. Tao;M. Trnka;M. Acutis;A. Ruane

Multi-wheat-model ensemble responses to interannual climate variability

• DOI: 10.1016/j.envsoft.2016.03.008
• 发表时间: 2016-07-01
• 期刊: ENVIRONMENTAL MODELLING & SOFTWARE
• 影响因子: 4.9
• 作者: Ruane, Alex C.;Hudson, Nicholas I.;Wolf, Joost
• 通讯作者: Wolf, Joost

A Statistical Analysis of Three Ensembles of Crop Model Responses to Temperature and CO2 Concentration

• DOI: 10.1016/j.agrformet.2015.09.013
• 发表时间: 2015-10
• 期刊: Agricultural and Forest Meteorology
• 影响因子: 6.2
• 作者: D. Makowski;S. Asseng;F. Ewert;S. Bassu;J. Durand;Tao Li;P. Martre;M. Adam;P. Aggarwal;Carlos Angulo;C. Baron;B. Basso;P. Bertuzzi;C. Biernath;H. Boogaard;K. Boote;B. Bouman;S. Bregaglio;N. Brisson;Samuel Buis;D. Cammarano;A. Challinor;R. Confalonieri;J. G. Conijn;M. Corbeels;D. Deryng;G. Sanctis;J. Doltra;T. Fumoto;D. Gaydon;S. Gayler;R. Goldberg;R. Grant;P. Grassini;J. Hatfield;T. Hasegawa;L. Heng;S. Hoek;J. Hooker;L. Hunt;J. Ingwersen;R. Izaurralde;R. Jongschaap;James W. Jones;R. A. Kemanian;K. Kersebaum;Soo-Hyung Kim;J. Lizaso;M. Marcaida;C. Müller;H. Nakagawa;S. Kumar;C. Nendel;G. O'Leary;J. Olesen;Philippe Oriol;T. Osborne;T. Palosuo;M. V. Pravia;E. Priesack;D. Ripoche;C. Rosenzweig;A. Ruane;F. Ruget;F. Sau;M. Semenov;I. Shcherbak;Balwinder Singh;U. Singh;H. K. Soo;P. Steduto;C. Stöckle;Pierre Stratonovitch;T. Streck;I. Supit;Liang Tang;F. Tao;E. Teixeira;P. Thorburn;D. Timlin;M. Travasso;R. Rötter;K. Waha;D. Wallach;J. White;P. Wilkens;Jimmy R. Williams;J. Wolf;X. Yin;H. Yoshida;Zi-Yu Zhang;Yan Zhu