Manipulating Large-Scale Qualitative Meteorological Information for Drought Outlook

Abstract

Despite many strides made in the development of global circulation models as well as the expansive understanding of meteorological phenomena, many countries still lack sufficient meteorological information that can be conveniently utilized for a hydrologic outlook. This paper suggests a technique of processing the meteorological information, which is not only difficult to differentiate by reducing to a specific basin because of extensive data, but is also impossible to be led to a quantitative drought outlook because of its presentation in qualitative forms. To assess the drought conditions, two indices were selected—the standardized precipitation index (SPI), which is a meteorological index, and the soil moisture index (SMI), an agricultural index. The long-range forecasts, provided by the Korea Meteorological Administration (KMA) to target the Korean peninsula, were used to predict these indices. As a means to convert the qualitative interval forecast into a quantitative probability forecast, previous data on temperature and precipitation were used to create a compatible probability distribution that was then divided into three intervals. Based on the interval forecast provided by the KMA, the forecast probability of corresponding intervals were differentiated and optimized for each study basin by modifying the probability adjustment coefficient. The quantified probability forecast established in this manner was applied to three basins in Korea, and was verified by applying the ranked probability skill score (RPSS). The results proved that accuracy was ensured in both SPI and SMI.