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<p>Understanding rainfall variability and its relationship with the ENSO (El Niño Southern Oscillation) and IOD (Indian Ocean Dipole) is crucial for enhancing regional climate predictions and agricultural planning. ENSO is driven by unusual Sea Surface Temperature (SST) anomalies in the equatorial zone of the Pacific Ocean, while IOD arises due to the discrepancy in temperature in the western and eastern Indian Ocean. Both phenomena exert significant influence on the Indian monsoon system. However, their effects on rainfall vary across regions and seasons, making it challenging to establish straightforward correlations. Hence, the Partial Correlation co-efficient is used to assess the influence of ENSO and IOD on Indian rainfall. The findings reveal that ENSO and IOD collectively modulate the Indian monsoon. For instance, El Niño events typically weaken monsoon rainfall, while La Niña events tend to enhance it. Similarly, a positive IOD phase strengthens the monsoon, whereas a negative IOD phase reduces rainfall. To explore the characteristics of Indian rainfall, various methodologies such as Innovative Trend Analysis (ITA), Mann–Kendall (MK), modified Mann–Kendall (mMK), Percent Bias (P<sub><i>BIAS</i></sub>), Sen’s slope estimator (<InlineEquation ID="IEq1"> <EquationSource Format="TEX">\({Q}_{ij}\)</EquationSource> <EquationSource Format="MATHML"><math> <msub> <mi>Q</mi> <mrow> <mi mathvariant="italic">ij</mi> </mrow> </msub> </math></EquationSource> </InlineEquation>), Precipitation Concentration Index (PCI), and Rainfall Seasonality Index (RSI) are employed. These tools offer a comprehensive insight into rainfall trends and variability. The teleconnection between ENSO, IOD, and Indian rainfall has significant implications for agriculture, disaster management and efforts to mitigate the negative impacts of climate variability on water resources and food security. Improved predictions of rainfall variability, concerning ENSO and IOD, can help formulate strategies to cope with water stress and enhance food production, especially in regions heavily dependent on monsoon rains.</p>

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Understanding the Teleconnections of ENSO and IOD with Rainfall Variation in India

  • 期刊论文

  • 发表日期：

    2025年9月3日

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  • Tapash Mandal,
  • Jayanta Das,
  • A. T. M. Sakiur Rahman,
  • Piu Saha,
  • Snehasish Saha

摘要

Understanding rainfall variability and its relationship with the ENSO (El Niño Southern Oscillation) and IOD (Indian Ocean Dipole) is crucial for enhancing regional climate predictions and agricultural planning. ENSO is driven by unusual Sea Surface Temperature (SST) anomalies in the equatorial zone of the Pacific Ocean, while IOD arises due to the discrepancy in temperature in the western and eastern Indian Ocean. Both phenomena exert significant influence on the Indian monsoon system. However, their effects on rainfall vary across regions and seasons, making it challenging to establish straightforward correlations. Hence, the Partial Correlation co-efficient is used to assess the influence of ENSO and IOD on Indian rainfall. The findings reveal that ENSO and IOD collectively modulate the Indian monsoon. For instance, El Niño events typically weaken monsoon rainfall, while La Niña events tend to enhance it. Similarly, a positive IOD phase strengthens the monsoon, whereas a negative IOD phase reduces rainfall. To explore the characteristics of Indian rainfall, various methodologies such as Innovative Trend Analysis (ITA), Mann–Kendall (MK), modified Mann–Kendall (mMK), Percent Bias (PBIAS), Sen’s slope estimator ( \({Q}_{ij}\) Q ij ), Precipitation Concentration Index (PCI), and Rainfall Seasonality Index (RSI) are employed. These tools offer a comprehensive insight into rainfall trends and variability. The teleconnection between ENSO, IOD, and Indian rainfall has significant implications for agriculture, disaster management and efforts to mitigate the negative impacts of climate variability on water resources and food security. Improved predictions of rainfall variability, concerning ENSO and IOD, can help formulate strategies to cope with water stress and enhance food production, especially in regions heavily dependent on monsoon rains.