Providing future climate projections using multiple models and methods: insights from the Philippines

To meet the growing demand for climate change information to guide national and local adaptation decision-making in the Philippines, the climate science and services community is producing an increasing volume of future climate data using a range of modelling approaches. However, there is a signific...

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Veröffentlicht in:Climatic change 2018-05, Vol.148 (1-2), p.187-203
Hauptverfasser: Daron, Joseph, Macadam, Ian, Kanamaru, Hideki, Cinco, Thelma, Katzfey, Jack, Scannell, Claire, Jones, Richard, Villafuerte, Marcelino, Cruz, Faye, Narisma, Gemma, Delfino, Rafaela Jane, Lasco, Rodel, Manalo, John, Ares, Emma, Solis, Ana Liza, de Guzman, Rosalina, Basconcillo, Joseph, Tangang, Fredolin
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Sprache:eng
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Zusammenfassung:To meet the growing demand for climate change information to guide national and local adaptation decision-making in the Philippines, the climate science and services community is producing an increasing volume of future climate data using a range of modelling approaches. However, there is a significant methodological challenge in how to best compare and combine information produced using different models and methods. In this paper, we present the landscape of climate model data available in the Philippines and show how multi-model, multi-method climate projections are being used and communicated to inform climate change policy and planning, focusing on the agriculture sector. We highlight the importance of examining and communicating methodological strengths and weaknesses as well as understanding the needs and capabilities of different user communities. We discuss the assessment of projections from different methods, including global and regional downscaled simulations, and discuss ways to summarise and communicate this information to stakeholders using co-production approaches. The paper concludes with perspectives on how to best use an “ensemble of opportunity” to construct defensible, plausible and usable climate projections.
ISSN:0165-0009
1573-1480
DOI:10.1007/s10584-018-2183-5