Tuesday, 9 January 2018: 11:30 AM
Room 6B (ACC) (Austin, Texas)
A weather shock such as a drought or flood often has a disproportionately large effect on the world’s poorest people, impacting food security, triggering conflict and deepening poverty traps. It is therefore unsurprising that the ability to better quantify the historical and existing climate can have enormous benefit for the development community, allowing more timely and effective allocation of funds, or better long term planning. In recent years, climate data has become an integral part of the development toolkit, both indirectly in operational planning and directly in products such as weather based index insurance or Forecast Based Finance (FbF). However, many challenges remain:
- The impact of a weather shock is typically a complex mix of rainfall, temperature, landscape, and human activity, often all acting at different spatio-temporal scales. It is non-trivial to be able to characterise these relationships and to model and communicate uncertainty.
- It is often difficult for non-meteorologists to navigate the maze of available agro-meteorological data products, each of which could be taken from many different data sources (satellites, models, weather stations), and each of which will have their own characteristics and uncertainties. The ‘fitness for purpose’ of a given data source is extremely context specific. The attributes of climate data required for long term planning may look very different to in-season response.
- It is equally non-trivial to develop meaningful climate metrics or triggers. There are many factors behind any operational decision and climate data will generally play only a small role. Yet, particularly in the case of insurance or FbF, a significant decision might be triggered directly off a weather based metric.
Overcoming these challenges requires an iterative co-learning relationship between meteorologists and development decision makers. We explore this process through the lens of two case studies:
- Our experience supporting the index insurance community to scale across Africa; linking probabilistic estimates of satellite rainfall, multiple-source basis risk assessments, index design and participatory farmer validation, to provide insurance to tens of thousands of farmers.
- Our experience working alongside Concern Worldwide to explore and use tailored climate metrics for systematic, operational decision-making in Somalia.
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