Accounting for temporal variability for improved precipitation regionalization based on self-organizing map coupled with information theory

Abstract

Precipitation regionalization deals with an investigation of the seasonality and its temporal variability and is useful for a wide variety of applications in hydro-meteorology. The d homogeneous regions can be used as a basis for transforming the information from gauged to ungauged sites and can reduce the uncertainty in estimating the seasonal characteristics of precipitation across India. Despite several studies stressing the importance of seasonality and temporal variability to the environment, there is a lack of studies on accounting for temporal variability in regionalization. Precipitation regionalization must account for both the precipitation magnitude and its temporal variability at multiple time-scales to extract the seasonality of a region representing coherent local and inter-annual variability. Therefore, in this study, we propose a framework for precipitation regionalization, considering both precipitation magnitude and its temporal variability. High resolution (0.25° × 0.25°) gridded daily precipitation time series over the period 1901–2013 from Indian Meteorological Department (IMD) was used for the evaluation of the framework. First, the historical daily time series was transformed into multiple time scales, i.e., annual, seasonal, and monthly time scales. Entropy-based standardized variability index was used to measure the inter-annual variability of precipitation at each time scale. Regionalization of grid points was performed using self-organizing maps, an artificial neural network. Ten distinct regions were identified that can be tied back to two general categories, such as climate characteristics and physical characteristics. Coupling of the self-organizing map with standardized variability index reveals unique seasonal distribution of precipitation for each region. The temporal evolution of clusters unravels a new emerging pattern across Central India. Consideration of temporal variability plays an insignificant role in the shape, size and stability of south-central India, south-eastern coastlines, and Konkan Coast. Intriguingly, separate Rain-belt and Rain-shadow Western Himalayas are formed due to the difference in topography and seasonal characteristics of precipitation. The temporal evolution of clusters unravels a significant change in the occurrence of the 50th percentile monsoon after the 1940s across the north-western region; a significant increase in the 50th percentile monsoon after the 1940s across western India, and decrease in the 50th percentile monsoon after the 1980s in the north-central Region.