相关论文: Spatio-temporal relationships between rainfall and…
We propose a representation of the Indian summer monsoon rainfall in terms of a probabilistic model based on a Markov Random Field, consisting of discrete state variables representing low and high rainfall at grid-scale and daily rainfall…
The primary objective of this paper is to analyze a set of canonical spatial patterns that approximate the daily rainfall across the Indian region, as identified in the companion paper where we developed a discrete representation of the…
Traditionally, during the monsoon season, more rainfall is received along the Western Ghats, the Northern Gangetic plains, the central belt, and northeast India. However, recently, there has been a shift in this canonical monsoon rainfall…
The Indian monsoon brings around 80% of the annual rainfall over the summer months June--September to the Indian subcontinent. The timing of the monsoon onset and the associated rainfall has a large impact on agriculture, thus impacting the…
Forecasts of monsoon rainfall for India are made at national scale. But there is spatial coherence and heterogeneity that is relevant to forecasting. This paper considers year-to-year rainfall change and annual extremes at sub-national…
An unresolved problem of present generation coupled climate models is the realistic distribution of rainfall over Indian monsoon region, which is also related to the persistent dry bias over Indian land mass. Therefore, quantitative…
Precipitation is a large-scale, spatio-temporally heterogeneous phenomenon, with frequent anomalies exhibiting unusually high or low values. We use Markov Random Fields (MRFs) to detect spatio-temporally coherent anomalies in gridded annual…
Extreme rainfall over the Indian monsoon region poses severe societal and infrastructural risks but remains difficult to predict at daily time scales due to stochastic convective triggering and multiscale atmospheric interactions. While…
A region under rainfall is a contiguous spatial area receiving positive precipitation at a particular time. The probabilistic behavior of such a region is an issue of interest in meteorological studies. A region under rainfall can be viewed…
Simulation of rainfall over a region for long time-sequences can be very useful for planning and policy-making, especially in India where the economy is heavily reliant on monsoon rainfall. However, such simulations should be able to…
Global attention has been focused on extreme climatic changes. This paper investigates the relationship between different phases of solar activity and extreme precipitation events in Kerala, India. Sunspot number and rainfall data were…
Rainfall forecasting plays a critical role in climate adaptation, agriculture, and water resource management. This study develops long-term forecasts of monthly rainfall across 19 districts of West Bengal using a century-scale dataset…
The challenge in predicting sub-regional climate within the Indian monsoon region is exacerbated by its increasing variability in a warming world. While exploring the seasonal predictability of rainfall over the state of Tamil Nadu in…
Many physical processes involve spatio-temporal observations, which can be studied at different spatial and temporal scales. For example, rainfall data measured daily by rain gauges can be considered at daily, monthly or annual temporal…
Accurate short range weather forecasting has significant implications for various sectors. Machine learning based approaches, e.g., deep learning, have gained popularity in this domain where the existing numerical weather prediction (NWP)…
Deep learning models for precipitation forecasting often function as black boxes, limiting their adoption in real-world weather prediction. To enhance transparency while maintaining accuracy, we developed an interpretable deep learning…
The sub-seasonal and synoptic-scale variability of the Indian summer monsoon rainfall are controlled primarily by monsoon intra-seasonal oscillations (MISO) and low pressure systems (LPS), respectively. The positive and negative phases of…
We study the role of galactic cosmic ray (GCR) variability in influencing the rainfall variability in Indian Summer Monsoon Rainfall (ISMR) season. We find that on an average during 'drought' (low ISMR) periods in India, GCR flux is…
Downscaling is necessary to generate high-resolution observation data to validate the climate model forecast or monitor rainfall at the micro-regional level operationally. Dynamical and statistical downscaling models are often used to get…
The Indian Summer Monsoon (ISM) is a critical climate phenomenon, fundamentally impacting the agriculture, economy, and water security of over a billion people. Traditional long-range forecasting, whether statistical or dynamical, has…