Unraveling Intricacies of Monsoon Attributes in Homogenous Monsoon Regions of India

Abstract

India observes the summer monsoon in June–July–August–September (JJAS) season, and the livelihood security of a huge population depends on it. The impact of the monsoon onset timing, length of monsoon season, rainfall amount, and related extreme events is huge on the Indian economy. Therefore, understanding the inherent intricacies needed a detailed investigation. In five homogenous monsoon regions of India, the trend of monsoon onset and the length of monsoon season are examined. The association between 1) monsoon onset ∼ rainfall amount, 2) length of monsoon season ∼ rainfall amount, and 3) monsoon onset ∼ length of monsoon season is investigated. Subsequently, the behavior of rainfall and extreme excess days in the ±1 standard deviation (SD) length of monsoon season is also examined in detail. The trend for monsoon onset shows late onset in all the homogenous monsoon regions except the northeast region. The length of monsoon season is found increasing significantly with high magnitude in west central and northwest regions. A significantly strong negative correlation (∼−0.6) for monsoon onset timing ∼ length of monsoon season is observed. Therefore, the change in rainfall anomaly, extreme excess days, and rainy days is done concerning the length of the monsoon season. In the cases of the −1 SD (+1 SD) length of monsoon season, rainfall anomaly and extreme excess days are low (high) in most parts of the homogenous monsoon regions. Extreme excess days showed a significant association with rainy days, which indicates a high possibility of rainy days converting into extreme excess days. However, the increase in extreme excess days in the +1 SD length of monsoon season is limited to a great extent in JJAS and June only. Morlet wavelet power spectrum shows the delay (advance) of power in −1SD (+1 SD) length of monsoon season.

Determination of Grid-Wise Monsoon Onset and Its Spatial Analysis for India (1901–2019)

“…Therefore, the policy and planningrelated institutions should consider these regions as vulnerable districts, and a highly refined framework must be prepared to mitigate the impacts in the long term. While investigating the intricacies of the monsoon onset, Saini et al (2022) found its relation with the length of the monsoon season and the amount of rainfall [1]. Therefore, in the long term, changing patterns and timing of the monsoon onset can influence the regime of agriculture, disease proliferation, river regime, etc.…”

“…Monsoon onset is generally viewed with the isochrones passing through different regions, and it has been observed that those isochrones are not dense enough to provide the monsoon onset date at a finer spatial scale [1]. Various methodologies for the determination have been introduced, and in most cases, each one of them uses different criteria [2].…”

Assessment of Rainfall And Temperature Trends in The Yellow River Basin, China from 2023 to 2100

“…In this study, we use 5 different interpolation methods to obtain high-resolution values and compare them. These include Spline (Saini et al, 2022), Kriging (Yang et al, 2014), Inverse Distance Weighted (IDW) (Zhu et al, 2004), Natural Neighbor Interpolation (NNI) (Habib et al, 2021), Bilinear Interpolation (BI) (Meng et al, 2022).…”

Risk Assessment of Waterlogging in Major Winter Wheat-Producing Areas in China in the Last 20 Years

“…The Pearson correlations conducted to compare y r and ten-day sunshine time, ten-day precipitation, and Q s , as shown in Figure 2d,e,f, Figure 3d,e,f, Figure 4d,e,f, Figure 5d,e,f and Figure 6d,e,f, were derived using Origin 2022b software (OriginLab Corporation, Northampton, MA, USA). The extracted event years were determined by the behavior of y r and ten-day sunshine time, ten-day precipitation, and Q s excess the mean value ± 1 standard deviation (hereafter SD) [30], and the results are shown in Tables 1-5. Table 1.…”