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Tailored climate projections to assess site-specific vulnerability of tea production

Neha Mittal, David P. Rowell, Andrew J. Dougill and 7 more

Climate Risk Management · 2021

doi:10.1016/j.crm.2021.100367 (opens in a new tab)

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Abstract

Tailored climate change information is essential to understand future climate risks and identify relevant adaptation strategies. However, distilling and effectively communicating decision-relevant information from climate science remains challenging. In this paper, we develop and apply an iterative stakeholder engagement approach and a Site Specific Synthesis of Projected Range (SPR), to co-produce future climate information for Africa’s largest tea producing nations - Kenya and Malawi - for the mid-and late-21st century. SPR provides a novel analysis approach, which combines long-term station observations with projections from 29 global climate models and the first convection-permitting high-resolution climate projection for Africa (CP4A). This addresses the mismatch between spatial scales of projections, large-scale modelling uncertainties and stakeholder need for site-specific information. Iterative stakeholder engagement and communication helped to build trust, allowed use of new observation data and improved visualisations of climate information for stakeholders. SPR demonstrates site-specificity in changes in all metrics, showing risks of large changes in tea crop sensitive metrics. All nine locations analysed show substantial (up to four times) increases in heatwave days and large decreases in cold nights by 2050s compared to the current climate. While tea producers are already witnessing changing climatic conditions, potential future changes will greatly affect the resilience of tea production, thereby affecting the sustainability and quality of tea production in the region. Site specific climate information iteratively co-produced with stakeholders helps them to identify location-specific adaptation strategies and investment priorities, potentially safeguarding supply-chains and millions of livelihoods.

Abstract licence: CC BY-NC

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