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.
by Bishnupada Sethi, Sarat Chandra Sahu, Krushna Chandra Gouda, Roshan Beuria, Manas Kumar Mallick, Satish Kumar Samal, Amrutanshu Panigrahi & Abhilash Pati
Coastal Odisha, strategically positioned between the Bay of Bengal and a vast inland landmass, is highly susceptible to climate change and variability impacts. This study comprehensively examines interannual temperature variability and its relationship with mean seasonal temperature using 54 years of homogenised surface meteorological data (1969–2022) from seven WMO-standard meteorological stations. To assess inter-annual variability in association with mean seasonal temperature and precipitation, a difference of standard deviations (SD) of two periods (e.g. 1969–1996 and 1995–2022) along with the relation between running 28-year values of SD and means of seasonal temperature for the period from 1969 to 2022, F-ratio test along with slope and correlation values have been conducted. By comparing two distinct periods (1969–1996 and 1995–2022), the analysis reveals significant climatic shifts, including rising mean temperatures and increased interannual variability at most stations, but some of the stations show an increase in mean temperature with decreased or fluctuating variability. These trends are linked to a heightened frequency of extreme weather events, cascading impacts on agriculture, water resources, health, and infrastructure. Notably, the findings identify localised patterns where warming is accompanied by increased or reduced variability, offering nuanced insights into the region’s complex dynamics. Explicitly noted the limitations of prior studies (e.g. low station density, short temporal scales, lack of focus on interannual variability),this study contributes novel insights to climate research in Odisha by employing long-term, high-resolution station-level data and advanced homogenisation techniques. The relationship between temperature and interannual variability is unique and the inverse relationship between the mean temperature and the variance of temperature is disrupted at most of the stations in coastal Odisha. Its findings hold critical implications for future research as a foundation for regional climate modelling, extreme event prediction, and studying climate variability’s socio-economic impacts. Actionable recommendations, including targeted disaster risk reduction measures, adaptive agricultural practices, and resilient infrastructure planning, underscore policy relevance. By addressing gaps in regional climate knowledge, this work provides a roadmap for integrating localised climate insights into state-level and national climate adaptation frameworks, ensuring preparedness for the evolving climate challenges in coastal Odisha.
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
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
by Sridevi Jade & T. S. Shrungeshwara
The 2500 km Himalayan arc spanning Kashmir, Ladakh, in the west to Eastern syntaxis in the east is a tectonically complex and seismically active northern subduction boundary of the Indian plate. Three decades of GPS data give well-constrained surface convergence rates ranging from 10 to 26 mm/yr in the various segments of the Himalayas (Kashmir, Ladakh, Himachal, Garhwal, Kumaun, Nepal, Sikkim, Bhutan, Arunachal and Eastern syntaxis). Arc parallel rates of 3–10 mm/yr is the manifestation of locked curvature of the central Himalayan arc and the E–W extension rate of Tibet. Inverse modelling of surface convergence rates is used to estimate oblique slip rate of 13–20 mm/yr along Main Himalayan Thrust (MHT) at a depth of 15–20 km and locking width of 100–150 km from the frontal Himalayas suggesting that each segment of the Himalaya is unique in nature. Geodetic strain rates derived from the GPS-derived surface convergence rates suggest that the Himalayan region is predominantly under compression with high strain rate coinciding with the northern boundary of sub surface basal decollement (MHT) along which Indian plate subducts below Tibet. Seismic strain rates for each segment of the Himalaya are computed using the instrumental and historical earthquake catalogue. Seismic potential of each segment of the Himalaya is estimated by a combined analysis of geodetic and seismic strain rates and the corresponding moment rates. Further, strain budget and accumulated slip since the last devastating earthquake was used to estimate the recurrence interval and probable magnitude of impending earthquake in the Himalayan segments.
- Relative Impact of Assimilation of Multi-Source Observations using 3D-Var on Simulation of Extreme Rainfall Events over Karnataka, India
- The curious case of a strong relationship between ENSO and Indian summer monsoon in CFSv2 model
- Outer-arc active tectonic deformation off the Nias – Nicobar Trench: Insights from lithospheric stress and seismic slip models
- A comprehensive study of atmospheric dynamics associated with cloudburst events in 2022 over Indian Himalayan Region