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.
Highlights
Recognition of the need for climate information that is both useful and usable is developing rapidly alongside a growing literature on dealing with future climate uncertainties (Jones et al, 2015; Jones et al, 2017; Lemos et al, 2012; Nissan et al, 2019)
Station observations of rainfall and temperature provided by the tea estates and the national meteorological departments are critical for bias-correcting the daily global climate model and CP4A data to produce site-specific future climate projections
The explicit representation of convection in pan-Africa simulations represents a step-change in African climate modelling, since the representation of convection is a fundamental limitation for the global climate models: for extremes and their climate change (Jones et al, 2017), for regional climate (Marsham et al, 2013) and for global change (Sherwood et al, 2014)
Summary
Recognition of the need for climate information that is both useful and usable is developing rapidly alongside a growing literature on dealing with future climate uncertainties (Jones et al, 2015; Jones et al, 2017; Lemos et al, 2012; Nissan et al, 2019). Under standing users’ decision-making contexts and tailoring climate information and its communication to their needs is crucial (Lemos et al, 2012). This is relevant in developing countries where the area under perennial cash crops is rapidly expanding, contributing to export earnings, and providing livelihood to millions (Kastner et al, 2014). Improved understanding of climate processes at a local scale, and iterative engagement between users and providers can enable distillation and communication of decision-relevant climate information (Lourenço et al, 2015; Hewitt et al, 2017; Vincent et al, 2018)
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