Unfreezing the confidence in the future

Chart. Example of different temperature distribution on vineyard. Data source

For example, temperature differences in hilly terrain are quite common on cold nights. As air near the surface is cooled on radiational frost nights, it becomes denser and flows downhill to lower areas where it collects.

Within a given area of a farming region, the most elevated sites tend to be the warmest during freeze events. The trees on northern slopes are much more and severely damaged by the extremely cold and dry winds during advective winter/spring freeze events. Soil characteristics can exert a microclimate effect.

Moreover, the experience has clearly shown that orchards may become active a little earlier in late winter on heavier, clay type soils and/or darker coloured soils (such as reds and blacks) than on lighter coloured, sandy soils. Although the latter tends to warm up faster, but they reflect more heat during the day (trap less heat) and lose it faster during the night.

Human-induced impacts can also be significant. For example, large areas of paved roads, such as interstate highways release substantial heat on cold nights, and this combined with heat released by vehicles and air currents created by traffic, can sometimes provide a beneficial effect to several rows of trees located close to such highways.

Chart. Trend, that witnesses the second half of December is getting warmer and warmer in the South-Eastern part of Poland. Data source: GrECo Group analysis

After resumption of the vegetation temperature at which ground frosts lead to partial damage to apple trees is much higher, e.g. at full blossom stage is -2.9 ⁰C leading to partial loss and -4.7 leading to full loss.

Generally, the crop sensitivity to freezing temperature increases from first bloom to small-fruit stages, and this is when a crop is most likely to be damaged. Sensitivity is also higher when warm weather has preceded a freeze night than if the cold temperatures preceded the freeze.

As long as such a minimal temperature condition occurs, the farmer gets the specified amount of insurance indemnity depending on the value of the actual temperature.

Despite advantages of parametric solutions, such as transparency, less paperwork and simplicity of insurance compensations, the insurance market faces the big challenges of basis risk and availability of suitable weather data to insure frosts.

Basis risk in parametric (index) insurance means when the index measurements do not match an individual insured’s actual losses. There are two major sources of basis risk in index insurance. One source of basis risk stems from a poorly designed model and the other from geographical elements.

The good frost parametric model should be based on accurate on-site weather data and consider at least, the fruit/berry development stage and the right frost tolerance parameters for specific types and varieties of crops. Additional factors like windspeed, temperature dewpoint and warm preceding days can be also considered in order to enforce the model. However, regardless of the final perfect model, the basis risk cannot be eliminated.