Spatio-temporal relationships between rainfall and convective clouds during Indian Monsoon through a discrete lens

TL;DR

This work develops a Markov Random Field framework to extract a small set of discrete, spatio-temporally coherent daily patterns for rainfall and Outgoing Longwave Radiation (OLR) over the Indian monsoon region (2004–2010). It identifies eight distinct rainfall patterns, eight OLR patterns, and seven joint patterns, collectively describing over 90% of monsoon days, and reveals a strong general anti-correlation between OLR and rainfall with notable regional nuances. The study further characterizes day-to-day changes via one-day OLR anomaly patterns, uncovering a dominant north–south gradient mechanism that shifts convective activity and rainfall distributions. By comparing with established monsoon classifications (active/break spells and MISO phases), the approach provides a compact, data-driven description that could inform simplified climate models and parameterizations for monsoon dynamics.

Abstract

The Indian monsoon, a multi-variable process causing heavy rains during June-September every year, is very heterogeneous in space and time. We study the relationship between rainfall and Outgoing Longwave Radiation (OLR, convective cloud cover) for monsoon between 2004-2010. To identify, classify and visualize spatial patterns of rainfall and OLR we use a discrete and spatio-temporally coherent representation of the data, created using a statistical model based on Markov Random Field. Our approach clusters the days with similar spatial distributions of rainfall and OLR into a small number of spatial patterns. We find that eight daily spatial patterns each in rainfall and OLR, and seven joint patterns of rainfall and OLR, describe over 90\% of all days. Through these patterns, we find that OLR generally has a strong negative correlation with precipitation, but with significant spatial variations. In particular, peninsular India (except west coast) is under significant convective cloud cover over a majority of days but remains rainless. We also find that much of the monsoon rainfall co-occurs with low OLR, but some amount of rainfall in Eastern and North-western India in June occurs on OLR days, presumably from shallow clouds. To study day-to-day variations of both quantities, we identify spatial patterns in the temporal gradients computed from the observations. We find that changes in convective cloud activity across India most commonly occur due to the establishment of a north-south OLR gradient which persists for 1-2 days and shifts the convective cloud cover from light to deep or vice versa. Such changes are also accompanied by changes in the spatial distribution of precipitation. The present work thus provides a highly reduced description of the complex spatial patterns and their day-to-day variations, and could form a useful tool for future simplified descriptions of this process.

Figures (13)

• Figure 1: Discrete rainfall patterns arranged in increasing order of mean daily rainfall. Orange square markers indicate the Centre of Mass (Def. 2 in the supplementary material) specific to the pattern and the green diamonds are the Centre of Mass (Def. 2 in the supplementary material) across all days. The green diamond is hence a fixed reference point against which we compare the migration of the centre of mass for each pattern of rain.
• Figure 2: Continuous Rainfall patterns corresponding to the discrete rainfall patterns of figure \ref{['fig:Discrete Rainfall']}. Black circles and red squares are the Centre of Mass (Def. 1 in the supplementary material) of each pattern's rainfall over the Indian landmass and the full area respectively. The purple diamond and green crosses are the Centre of Mass (Def. 1 in the supplementary material) of rainfall over the Indian landmass and the full area respectively, across all the days.
• Figure 3: Discrete cloud (OLR) patterns arranged in increasing order of mean daily rainfall. Orange square markers are the Centre of Mass (Def. 2 in the supplementary material) of high cloud cover locations specific to the patterns and the green diamonds are the Centre of Mass (Def. 2 in the supplementary material) of high cloud cover locations across all days.
• Figure 4: Continuous OLR patterns corresponding to the discrete OLR patterns of figure \ref{['fig:Discrete OLR']}. Red squares are Centre of Mass (Def. 1 in the supplementary material) of the full area-weighted with 1/OLR of the pattern. The green diamonds are the Centre of Mass (Def. 1 in the supplementary material) of the full area across all the days sampled.
• Figure 5: The number of days in which each OLR pattern (figure \ref{['fig:Discrete OLR']}) occurs for a given rainfall pattern (figure \ref{['fig:Discrete Rainfall']}). Note the variable vertical axis.