Peculiarities of weather forecast for agriculture

No doubt weather is the most important factor determining whether an agricultural enterprise is successful or not. Changes in the weather greatly affect growth, state and amount of crops, its disease incidence, its need for water and fertilizers. Not only plants, but also a whole agricultural market highly depends on weather. Directly and due to some sideway reasons, weather is guilty of loss of the annual world crop in the amount of its three out of four! A mistake in weather forecast can result in crop loss.
Generally, as science and modern technologies evolve, the dependence of crop on weather seems to decrease but of course there is still some correlation of yield amount and weather conditions. Nevertheless, crop loss can be reduced significantly by adjusting taken measures that are based on well-timed and accurate weather forecast. Such weather forecast allows developing recommendations for long-term and seasonal planning and for selection of crops best suitable for expected climatic conditions.
Here one needs to take into consideration some specific features of weather forecast for agriculture which are quite different from those of weather forecast for daily living needs. Efficiency of weather forecasts is higher when attention of forecasters is emphasized on requests of farmers, and farmers know how to use these forecasts and what steps to take. The case is complicated by the fact that the reaction of various agricultural plants to type and intensity of peculiar weather phenomena is different; and this reaction also varies at different stages while plants grow. Furthermore, due to differences in climatic conditions, ways of cultivation of agricultural plants vary at certain world locations, even during the same season.

Thus forecasts for short and long periods of time are of the same great importance. For instance, making decisions based on forecast for late start of the season of growing plants requires significant alterations of ways of cultivation compared with ordinary start.
Organization and implementation of such strategies are considered as decisions of high cost, and usually they require quite a lot of time. That is why preliminary seasonal forecasts should be valid for at least 10 days and be received not less than a week beforehand.
Also measures of diminishing consequences of dangerous meteorological phenomena, of hazardous pests and diseases should be conducted properly in time and as they require some considerable time, so current seasonal forecasts should be received 5 days (at least not later than 3 days!) beforehand preferably.
One should mention here, as weather forecasts are processed for agricultural users, they should be distributed as soon as possible.
Since the season of growing plants starts, the only way to affect the situation is to minimize the impact of severe weather conditions by a timely adoption of preventive measures; the factor of time can be crucial here.
For example, crop loss due to night frosts can be prevented by irrigation, mulching or using smoke bombs.
The main weather phenomena timely information about which can significantly reduce commercial risks are:

• Precipitation, its amount and intensity. Warning of hail should be distributed in advance as there are agricultural plants that are to be protected (e.g., leafy and salad vegetables), and it takes additional expenses to have staff in the fields on constant basis.
• Temperature. In regions with temperate climate slight frosts represent a significant threat to crop, however lowering the temperature below zero has different impact on various kinds of agricultural plants: potato can perish while radish can withstand a drop in temperature up to -4C.
  In any cases current forecasts and chronological forecast data of previous seasons are both important.

So far as while making forecasts for agriculture, information on abnormal weather phenomena and its possibility for specific location should be emphasized; particular performance standards of weather regime and plant growth should be stated. Otherwise how abnormal weather phenomena can be recognized when a performance standard is not fixed. Thus chronological forecast data of previous seasons for this specific location represent particular interest; by scrutinizing which one can create a performance standard of ordinary weather conditions and can trace prevalence and frequency of abnormal weather phenomena.
In view of the above OpenWeatherMap company plans launching of new products designed for agriculture. Let’s see what we have in stores for our users: weather forecast for a specific region up to 10 days, temperature defining for any point worldwide (current and historical data), time, amount and location of precipitation (history and forecast), weather warnings of hail, frosts, storms and other abnormal weather phenomena.