Disentangling Temporally Lagged Synchronization of Climate Oscillations on Agricultural Droughts across India

Large-scale climate oscillations significantly influence regional agricultural droughts and are crucial for understanding their predictability. However, atmospheric teleconnections linked to these droughts under various climate oscillation regimes are complex and not fully understood, especially when considering temporal delays. This study employs Event-based Coincidence Analysis (ECA) to statistically explore the timing and magnitude of relationships between climate oscillation regimes and the onset of agricultural droughts across different agro-ecological zones of India  , with time lags (τ) ranging from 1 to 1, 3, 6, 9 and 12 months.   ECA is a mathematical framework that quantifies the synchronicity and interdependency between event series such as climate oscillations and agricultural drought events by evaluating the frequency of coinciding occurrences within a defined time window (ΔT) and at specified time lags (τ).  We utilize the Standardized Soil Moisture Index (SSMI) to assess agricultural droughts from 1951 to 2014. The SSMI data are aggregated over three months based on GLDAS VIC model observations. Our analysis includes synchronization between drought events and climate indices, such as the Pacific Decadal Oscillation (PDO), Niño 3.4, Atlantic Multidecadal Oscillation (AMO), and the Dipole Mode Index (DMI). Integrating various time lags allows us to capture both immediate and delayed influences of climate on drought prediction and management strategies. Our results identify significant variations in precursor rates across different time lags and regions, clearly delineating how specific climate indices influence agricultural drought dynamics. Notably, in the northern and central zones of India, Niño 3.4 and the AMO are found to strongly drive drought conditions at longer time lags (τ = 6, 9, 12 months), with a peak coincidence rate of 60% during positive Niño 3.4 episodes. Conversely, in the southern and western regions, significant drought mitigation effects are associated with shorter time lags (τ = 1, 3 months), where the DMI and AMO show high precursor rates of 40 to 60 percent during positive phases.  This study highlights the distinct temporal dynamics of climate indices and emphasizes the role of atmospheric mechanisms, including wind anomalies and vertical velocity at 850 hPa, in modulating these effects. We observe distinct influences on drought patterns, which vary significantly across regions and time lags, highlighting the necessity for region-specific agricultural and water management strategies based on these dynamics to address both drought occurrence and water scarcity challenges effectively.