Use-case: seasonal forecasting for agriculture in India

The rural poor, who are economically dependent on agricultural production, face significant risk to their livelihoods from catastrophic weather events that cause widespread crop failure. The concepts of micro-finance and micro-insurance [http://en.wikipedia.org/wiki/Microinsurance] seek to mitigate the economic risks faced.

A provider of micro-insurance services to farmers in rural communities in India aims to reduce impact of weather-related risk to the insured crops and hence lower the associated financial risk underwritten in order to ensure that insurance premiums are as low as possible.

The micro-insurance vendor identifies a package of weather information that will provide value-added information to the rural farming community, thus differentiating the micro-insurance service from peers whilst reducing the underwritten risk. Additionally the vendor seeks to improve the accuracy in settlement of claims by integrating weather information into their loss models. 

The package of information includes:
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1) Seasonal forecasts - providing information on how weather, averaged over the next few months, will vary from normal. Whist seasonal forecasts are indications of an overall picture, it is impossible to forecast individual events so far ahead.

The same computer models of the atmosphere that are used to make daily weather forecasts are used, albeit with some differences:
-- they are run forward in time up to many months ahead, rather than a few days;
-- active oceanic, as well as atmospheric, components are included; and
-- they are run many times, with slight variations to represent uncertainties in the forecast process, in order to establish a probabilistic forecast.

The seasonal forecast has will have a duration of 3- to 6-months and a spatial extent covering the Indian sub-continent. The parameters of primary interest are temperature and precipitation - will the weather be hotter or cooler, wetter or drier?

The value of the forecast to farmers is helping to select crop-types that may more suitable to the season ahead; e.g. planting drought-resistant crops.

Additionally, the information provided can guide the farmers toward better periods for planting, which are often fixed to dates on the religious calendar. The seasonal forecast can indicate whether to plant or earlier or later, perhaps enabling the harvest of two crops in one season.

2) Climate records
In the event of a catastrophic weather event, the micro-insurance vendor will need to verify any claims received. The vendor will use historical observations and analyses from weather prediction models as input to their loss models. Where there is a sparsity of observations, the vendor may require a set of 'synthetic observations' to be provided, using numerical algorithms to downscale the analysis to a local level and thus provide more effective input to the loss model.
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The only mechanism available to communicate between the vendor and farming community is the mobile-phone.