rainfall to be _carried over_ between phases, to try to capture the soil moisture at the start of the phase (see Table 6).

# <u>Consecutive Dry Days (CDD) Index</u>

Another approach to capturing adverse rainfall events is to construct an index equal to the maximum consecutive number of _dry days_ within a specified period, where a dry day is defined as a day with total rainfall below a threshold value.

(3) This cover offers protection for long dry spells and can be sold as a standalone product or in conjunction with other indexed cover, particularly rainfall volume based products. For example, Table 7 characterizes a consecutive dry days product where the index uses a daily threshold of 2.5mm, and with claim payment a step function of the index, with claim payment of ₹750 if the index is between 17 and 24 days, ₹1,500 if the index is between 25 and 29 days and ₹2,000 if the index is greater than or equal to 30 days.

Some consecutive dry days products use a trigger of 0mm (see Table 8), although the agronomic merits of such products are unclear; a dry spell of 30 days, with rainfall of 2mm on day 15 would still most likely result in a large crop loss, but would not trigger a claim payment for the product defined in Table 8.

# <u>Excess/Untimely Rainfall Index</u>

Heavy and continuous rainfall within a short period has the potential to cause severe physiological damage to crops, particularly during the maturity and the harvest phases when excess rainfall makes many crops highly susceptible to attacks by pestilence and disease. The indices that have been designed to capture wet spells are similar in nature to those already described for deficit rainfall, dependent on consecutive rainy days, aggregate rainfall over a period of between two and four consecutive days, or a piecewise linear function of rainfall in each phase. For example Hess et al. (2005) report on a rainy days product for Mahabubnagar, Andhra Pradesh for which was 10mm of daily rainfall and a claim was triggered if the rainy day index was four or more. The most recent products seem to be mainly based on aggregate rainfall over a period of two, three, or four consecutive days.

# <u>Low temperature or frost indices</u>

Temperature can have a significant impact on yields (Lobell et al. 2011) and Indian insurers have experimented with indices based on weather station temperature readings, particularly for the Rabi (winter) crop.

Northern parts of India are particularly exposed to the risk of low temperatures or frost which can cause severe crop loss in a short space of time for crops like potato, chick-pea and mustard. Indices have been designed to offer some protection against adversely low temperatures, typically defined as a function of the minimum temperature in the cover period (for example, see Table 11).

# <u>High temperature indices</u>

Complex temperature-based indices have been designed to offer some protection to farmers against adversely high temperatures, particularly for wheat crop. For example, AICI and the Indian Agricultural Research Institute (IARI) designed a phase-based high temperature index for wheat crop in Rajasthan for the Rabi 2007 season, where the claim payment to farmers in respect of each phase was a function of the mean temperature for that phase (Table 9). As another example, ICICI Lombard sold a product for wheat crop in 2010 for which claim payments depended on excess daily temperature, rather than excess average fortnightly temperature (Table 10). However, while it is 7