Abstract:
Extreme climatic events are increasing because of climate change and thus likely to influence
global agricultural production. Regional assessments on various abiotic factors and its influences
on biological entities in diverse geographic locations are needed for understanding
uncertainties. Most climate impact studies rely on changes in means of meteorological variables,
such as temperature, to estimate potential climate impacts, including effects on agricultural
production. However, extreme meteorological events such as a short period of abnormally high
temperatures, can have a significant harmful effect on crop growth and final yield. The
characteristics of daily temperature time series, specifically mean, variance and autocorrelation,
are analyzed to determine possible ranges of probabilities of certain extreme temperature
events with changes in mean temperature of the time series. The extreme temperature events
considered are motivated primarily by agricultural concerns, particularly, the effects of high
temperatures on rice production in Anuradhapura district in North Central Province of Sri
Lanka. Trends in extreme daily temperature were analyzed for thirty years from 1975 to 2005
for Anuradhapura district for two major seasons for paddy production, Yala and Maha. Daily
average temperatures were calculated using daily minimum and daily maximum temperatures
and separated into two seasons. The 90th percentile was used as the reference value as an
extreme temporal value. Number of occurrences above the 90th percentile was cumulated yearly
and analyzed for a pattern from 1975 to 2005. These trends in extreme temperatures showed
considerable consistency across the study area. The study reveals a positive correlation between
the years and the occurrences of extreme temperature events for both Yala season and Maha
seasons with p values of 0.03 and 0.04, respectively. From a statistical point of view, the
occurrences have been increasing throughout the time series in Anuradhapura district and will
detrimentally affect the crop production specially for rice production in the area.
