Regional assessment of rainfall indices for drought conditions during the monsoon season in Odisha
by Puja Sahu, P K Mohanty, S R Padhi & K C Gouda
Drought in Odisha, India, varies significantly due to its diverse physiographical features, such as orography, river basins, lakes, coastlines, and the Eastern Ghats, which influence rainfall distribution and drought vulnerability. Understanding and interpreting these rainfall patterns is essential for inferring regional rainfall variability for drought conditions, which in turn affects sectors like agriculture, health, energy, and disaster management. This study aims to analyze and quantify regional rainfall variability for drought assessment, focusing on identifying suitable indices for monitoring drought at the block and district levels. Using long-term block-level rainfall data, five key drought indices were evaluated: Precipitation Concentration Index (PCI), Standardized Precipitation Index (SPI), Effective Drought Index (EDI), Deciles Index (DI), and Percentage Departure (PD). Statistical analyses were conducted to assess the performance of these indices in capturing rainfall variability across monthly and daily timescales. The study explored how the indices reflect drought severity in districts with varying geographic conditions. PCI was effective for rainfall distribution, while SPI and EDI were the most reliable for monitoring extreme droughts. In contrast, DI and PD did not align well with observed data. The EDI showed significant drought impacts in the blocks of Jajpur, Khordha, and Koraput, highlighting the need for targeted agricultural interventions. SPI and EDI provide robust tools for assessing drought in Odisha, particularly for disaster management and water resource planning at block, district, and state levels. The study's findings offer critical insights for managing drought in vulnerable regions.
Quantifying CMIP6 models’ performance in simulating marine heatwaves over the Indian Ocean region: A comprehensive analysis of key MHW properties and future projections
by S Swetha & K V Ramesh
This study quantifies CMIP6 models’ performance in simulating marine heatwaves (MHWs) over the Indian Ocean based on MHW properties like frequency, heatdays, and intensity. Spatial and temporal variations were assessed using spatial skill scores (SS score) and M2 scores, with model skills quantified by the performance score (PS), ranging from 0 to 100. The top three qualifying models, CMCC-ESM2, CMCC-CM2-SR5, and GFDL-ESM4, demonstrated notable accuracy in capturing the spatial and temporal features of MHWs close to observations for the period 1981–2014. The models are reliable in simulating the trend in intensity (both mean and maximum intensity) and frequency. However, selected models tended to underestimate MHW properties with a maximum deviation from observations of ~62% for MHW frequency and MHW intensity and the least deviation of only ~28% for MHW heatdays. Surface flux analysis revealed an overestimation of upwelling latent heat flux, longwave flux, and sensible heat flux, leading to a cold bias, particularly in the Southern Indian Ocean region, which could be a possible reason for the model’s underestimation of MHW properties. Future projections for the middle and end century (2041–2100) under SSP585 showed an alarming increase in MHW frequency, heatdays, and intensities, with MHW heatdays reaching a near-permanent state by the end of the century (2100). Over a period of 60 years, the MHW frequency displays an increasing trend of ~0.4 events annually, MHW heatdays increasing at ~1.5 events annually, MHW maximum intensity increasing at ~0.14°C and mean intensity increasing at ~0.1°C annually for the highest emission scenario SSP585.
Multi-Instrument Analysis of Ionospheric Equatorial Plasma Bubbles over the Indian and Southeast Asian Longitudes During the 19–20 April 2024 Geomagnetic Storm
by Sampad Kumar Panda, Siva Sai Kumar Rajana, Chiranjeevi G. Vivek, Jyothi Ravi Kiran Kumar Dabbakuti, Wangshimenla Jamir and Punyawi Jamjareegulgarn
In this study, we explored the occurrence of near-sunrise equatorial plasma bubbles (EPBs) and inhibition of dusk-time EPBs during the geomagnetic storm (SYM-Hmin= −139 nT) of 19–20 April 2024 using multi-instrument observations over the Indian and Southeast Asian longitude sectors. The initial phase of this storm commenced around 0530 UT on 19 April 2024 and did not manifest any visible alterations in the ionospheric electric fields during the main phase of the storm, which corresponded to a period between post-sunset to midnight over the study region. However, during the recovery phase of the storm, the IMF Bz suddenly flipped northward and was associated with an overshielding of the penetrating electric fields, which triggered the formation of near-sunrise EPBs. Interestingly, the persistence of EPBs was also noticed for more than three hours after the sunrise terminator. Initially, sunrise EPBs were developed in the Southeast Asian region and later drifted toward the Indian longitude region, along with the sunrise terminator. Moreover, this study suggested that the occurrence of EPBs was suppressed due to the altered storm time electric fields at the dip equatorial region across the 70–90°E longitude sector in the recovery period. This study highlighted that even moderate geomagnetic storms can generate near-sunrise EPBs in a broader longitude sector due to penetrating electric fields in overshielding conditions, which can significantly affect trans-ionospheric signals.
Source: https://doi.org/10.3390/rs17061100
Modeling near-surface velocity inversion in a sediment sequence using microtremor HVSR
by Dhananjay A. Sant, Gunjankumar K. Makwana, Prabhin Sukumaran, Imtiyaz A. Parvez, Govindan Rangarajan and K. Krishnan
We propose a rapid and cost-effective Horizontal-to-Vertical Spectral Ratio (HVSR) method that uses microtremors (ambient noise) for mapping intercalated sedimentary sequences with lateral heterogeneity for a depth of about 100 m in Lower reaches of Narmada Valley, western India. The elastic parameters for various units/layers at a given site (1D) were derived theoretically based on HVSR inversion, built on the concepts of Diffuse Field Assumption and retrieval of the imaginary part of Green's function. This approach enables efficient forward calculation, delves into the relationship between the HVSR curve and elastic parameters, and accelerates the inversion process. A site-specific priori knowledge gathered during the field visits is further integrated. We successfully derive overall shear wave velocity and density models inferring three sedimentary Units and associated Subunits. The key highlight of this study is successfully distinguishing low-velocity sedimentary Units/Subunits within a sedimentary sequence.
Source: https://doi.org/10.1016/j.soildyn.2025.109235
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