Strengthening Drought Monitoring Module by Ensembling Auxiliary Information Based Varying Estimators

Quality of meteorological data such as preciseness and accuracy has substantial importance while making inferences about natural hazards. Among all the natural hazards, drought hazard is a complex natural phenomenon. In this article, we have discussed the procedure of improving time series data of meteorological indicators for analyzing drought. Here, we considered auxiliary information-based sampling estimators to enhance the quality of drought indicators. Since precipitation time series has a key role in drought occurrence and have a strong spatial correlation coherence structure with temperature. Therefore, this study suggests the use of the characteristics of auxiliary information as local weights for improving precipitation records. Consequently, this study presents the proposal of a new drought measure: The Seasonally Transient Weighted Multi-Scaler Standardized Index (STWMSDI). Under varying relationships between time series data of precipitation and temperature, the proposed method is more general than presented in Ali et al. (2019). We applied STWMSDI on ten meteorological stations of Pakistan to compare its performance with the Standardized Precipitation Index (SPI). Experimental results show high significant correlation between the STWMSDI and SPI. From these results, we conclude that the improved data provides much better results in terms of drought indices. Hence, the STWMSDI method of drought index is a good candidate for accurate drought monitoring.