A global meta-analysis of climate services and decision-making in agriculture

Lorna Born,Steven Prager,Julian Ramirez-Villegas,Pablo Imbach

doi:10.1016/j.cliser.2021.100231

Lorna Born, Steven Prager + Show 2 more

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https://doi.org/10.1016/j.cliser.2021.100231

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Abstract

Harmonizing the supply of climate information with the type of information needed by next-users is crucial for effective weather and climate services (CS). Understanding of information demand could help reshape supply-side based CS that have dominated the field over the last few decades. Most CS have been developed using a ‘loading dock’ model, whereby products are designed by information suppliers with little input from or consultation with users of climate services. Notably, a focus on climate modelling and prediction has largely resulted in a lack of consideration of the demand-side when producing climate services. Here, we contribute to understanding of CS demand by presenting a global meta-analysis – a ‘decision matrix’ - of farmers’ climate-influenced decisions. We identify 41 studies that encompass 186 decisions, three forecast timescales (weather, dekadal, seasonal), and five forecast variables (precipitation, temperature, wind, soil moisture and soil temperature). Several insights were offered by this literature review into the value of climate services and the way forward in considering users’ needs. We find that the seasonal precipitation is the most frequently used forecast variable for decision-making, particularly of crop sowing date. Forecasts such as temperature, soil moisture and soil temperature appeared to be less used by farmers, according to the decision matrix. It is apparent that more investigation is necessary into how farmers use climate information in their decision-making to better establish the value of CS. We suggest that different sectors should make their respective decision matrices to explore decision spaces and engage with users of climate information in various sectors.

Highlights

This paper aims to address a persistent opportunity associated with efforts for better understanding the demand for climate services (CS) in an agricultural context
We delve into understanding how agricul tural users may leverage climate information for agricultural decision making by constructing a ‘decision matrix’ that systematically charac terizes the decision space that CS literature currently addresses
The literature sourced in this analysis came from several different fields of study, some not focusing on climate services them selves but rather on farming calendars or household adaptation strate gies

Summary

Introduction

This paper aims to address a persistent opportunity associated with efforts for better understanding the demand for climate services (CS) in an agricultural context. We see an opportunity in terms of the general characterization and comparison of the decision space in which CS are applied, and need for CS related decision making in agriculture. We delve into understanding how agricul tural users may leverage climate information for agricultural decision making by constructing a ‘decision matrix’ that systematically charac terizes the decision space that CS literature currently addresses. Through better understanding of users’ needs and the demand side perspective, we offer a decision matrix to contribute to the understanding of the patterns of forecast use for the support of continued development of more demand driven and user-oriented ap proaches. For the purposes of clarity in this paper, both agro-climatic services and climate services as well as weather services fall under the umbrella of “climate services (CS)”

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