Simple Short-Term Probabilistic Drought Prediction Using Mediterranean Teleconnection Information

Abstract

Timely forecasts of the onset or possible evolution of droughts is an important contribution to 9 mitigate their manifold negative effects; therefore, in this paper, we propose a mathematically-10 simple drought forecasting framework gaining Mediterranean Sea temperature information (SST-11 M) to predict droughts. Agro-metrological drought index addressing seasonality and 12 autocorrelation (AMDI-SA) was used in a Markov model in Urmia lake basin, North West of Iran. 13 Markov chain is adopted to model drought for joint occurrence of different classes of drought 14 severity and sea surface temperature of Mediterranean Sea, which is called 2D Markov chain 15 model. The proposed model, which benefits suitability of Markov chain models for modeling 16 droughts, showed improvement results in prediction scores relative to classic Markov chain model 17 not including SST-M information, additionally.

A New Weighting Scheme in Weighted Markov Model for Predicting the Probability of Drought Episodes

“…A Markov chain is a discrete time stochastic process, which has the property that the future state of the process is independent from the past state, given the present state [8]. Furthermore, Markov chain models can be useful for forecasting future drought classes due to their multifaceted nature to enumerate uncertainties associated with these hydrometeorological variables [9][10][11]. However, it is difficult to adjust the transition probability matrix of Markov chain for the precise forecasting of succeeding events at short time scale.…”