Studying the dynamics of cloudburst events over Indian Himalayan region using model simulation
by Payoshni Samantray & Krushna Chandra Gouda
Cloudbursts are brief, intense rainfall occurrences that present significant risks to human life, infrastructure, and ecosystems, especially in the Indian Himalayan Region (IHR). Despite their damaging characteristics, predicting these events remains challenging due to their localized nature, the influence of complex terrain, and a lack of high-resolution observational data. Therefore, enhancing the simulation and comprehension of such occurrences is crucial for improved forecasting and disaster readiness. This research introduces a high-resolution computational modeling technique utilizing the Weather Research and Forecasting (WRF) model to replicate cloudburst events in the Indian Himalayan Region (IHR) during the monsoon season of 2022. These extreme weather phenomena, marked by intense and localized rainfall, are hard to forecast because of the region's complex terrain and convective dynamics. In this study six representative cloudburst events from Himachal Pradesh, Uttarakhand, and Jammu & Kashmir were simulated at a resolution of 3 km using six-hourly NCEP-FNL reanalysis data. The analysis concentrated on critical atmospheric mechanisms such as vorticity, convective instability (CAPE, CINE), moisture availability, and orographic lifting. The model outputs were validated against daily rainfall data from the India Meteorological Department (IMD), Global Precipitation Measurement Mission (GPM), and the CPC MORPHing technique (CMORPH). The model demonstrated a strong correlation with IMD data (correlation coefficient of 0.84 and RMSE of 45.07 mm), although performance varied with satellite-based datasets. This study contributes to understanding the simulation of cloudburst events using high-resolution regional modeling and multiple observational validations.
Source: https://doi.org/10.1007/s40808-025-02680-w
Seismo-ionospheric anomalies associated with the 2025 Mw 7.7 Myanmar earthquake: a case study
by Siva Sai Kumar Rajana, Sambit Prasanajit Naik, Sampad Kumar Panda, Chiranjeevi G. Vivek, Sridevi Jade
Quantifying weather-rice crop production relationships across different physiographical zones in Odisha, India
by Puja Sahu, P. K. Mohanty & Krushna Chandra Gouda
Climate change has direct effect on rice crop production, resulting in an impact on food security in tropical countries like India. The coastal state of Odisha, situated in the country's eastern region, also suffered from crop production/yield due to the regional climate change. In this research work, the multi-source long term data analysis is being carried out to quantify the climate-crop relation in the state of Odisha. The analysis of rainfall, temperature, Kharif crop (rice) yield and production for the past three decades in Odisha at district scale is carried out. The study based on the cluster analysis of different physiographical regions i.e. coastal plain (CP), river catchment (RC) and mountainous zone (MZ). The region wise climatology, interannual variability, and trend analysis of both rainfall and temperature and the rain/temperature days are computed using the data over 30 (1993–2022) years. The variability of annual and monsoon rainfall is comparatively higher in the CP and RC than in MZ. The monsoon rainfall trend seems to be decreasing in the CP region, increasing in the MZ and no trend over RC. The analysis infers a negligible (0.01 °C/year) temperature trend in the state. The correlation result suggested that the Kharif rice crop yield & production well correlated with the summer monsoon rainfall over RC and MZ at 90% confidence levels. The rice production in the state shows increasing trend in RC as compared to other two regions. The results suggest a good correlation between the rainfall and rice crop production observed in RC and MZ regions. Similarly, temperature also correlates better with the Kharif crop production and yield in CP as compared to other regions. The district scale analysis also indicated that strong correlation (95%) of rice crop yield with temperature is observed in 10 districts and the relation of crop production and rainfall is strong in 12 districts. The impact of large-scale process like ENSO on the district scale Kharif yield/production also assessed. The analysis signifies the global, local, and direct impact of climate patterns on rice production at district and regional scales. This study opens a scope for the potential use of the integrated approach to address the impact of climate change on a state's agriculture and food sector.
Impact of the Gannon Superstorm on the Equatorial Ionization Anomaly Dynamics During Its Recovery Phase on 11 May 2024
by K. Shimna, R. K. Archana, C. Vineeth, Gang Lu, T. K. Pant and M. S. M. Vijayan
During the recovery phase of the Gannon Superstorm on 11 May 2024, the thermosphere-ionosphere system experienced dramatic changes marked by an unusual redistribution of plasma density. The peak electron density (Nmax) from Global-scale Observations of the Limb and Disk (GOLD), ground-based Vertical Total Electron Content (VTEC), and topside VTEC from Swarm C satellite revealed an enhanced electron density at the equator and a complete disappearance of the Equatorial Ionization Anomaly (EIA) crests. This absence of EIA crests was linked to a strong daytime Counter Electrojet (CEJ) caused by disturbance dynamo effects observed in ground magnetic data. The unusually strong CEJ suppressed the ExB vertical drift, thereby eliminating the fountain effect. Thermosphere-Ionosphere-Electrodynamics General Circulation Model (TIEGCM) simulations further indicated the presence of equatorward converging meridional winds from both hemispheres. This converging wind hindered the diffusion of plasma from the dip equatorial rΣO/N2 ratio along the equator was observed during the recovery phase, further contributing to this phenomenon. The present study, therefore, for the first time, demonstrates the combined effects of storm-induced changes in equatorial electrodynamics, meridional winds, and significant compositional changes during the recovery phase of a superstorm, and their influence on plasma distributions. The corroborative evidence from model simulations further strengthened these observational findings.
Assessing the dynamics and thermodynamics of Monsoon onset: The impact of ENSO
by Smrutishree Lenka, K. C. Gouda, MOHAN T. S., Rani Devi and V. S. Prasad
This study examines the mechanisms involved in the onset and progression of the monsoon over the Indian subcontinent by analyzing key dynamical and thermodynamical processes. Additionally, it investigates the characteristics of monsoon onset during various ENSO phases. To achieve this, we utilized long-term observations and ERA5 reanalysis data to conduct a comprehensive study on the onset and related characteristics.
Results indicate that, a robust connection between the thermal gradient in both zonal and meridional directions and the corresponding vertical wind shear both across the active monsoon shear domain (MSD) and Kerala domain (KD). It is found that, this relationship varies across different time scales i.e., annual, seasonal (ISM-length), and onset pentad (p0), underscoring that the intensity of monsoon convection hinges on the thermal gradient and wind shear. The analysis concludes that presence of weak vertical wind shear, creates a stable state and the presence of a significant thermal gradient, characterized by minimal variations in wind speed and direction at different altitudes, are critical factors that facilitate the monsoon onset. Further, El Niño tends to increase wind shear over the Indian subcontinent and leads to a delayed monsoon onset. Elevated geopotential height during an El Niño year indicates the existence of a high-pressure region, which is an unfavorable condition for the onset of the monsoon. Analysis of temperature tendency equation exhibit a robust diabatic heating which is linked to a Gill-like Rossby wave response, initiating thermodynamic interactions with midlatitude westerly jet. Furthermore, this study also gives an indication of the influence of central pacific (CP) warming events and its influence on monsoon onset characteristics, which needs further exploration.
- Leaf area index estimation over the Kosi watershed in central Himalaya from remote sensing data using machine/deep learning models and validation against in situ measurements
- Impact of assimilating GNSS ground-based and Space-based observations on Extreme rainfall prediction over Karnataka, India
- Multi-Instrument Observations of Unseasonal Post-Sunset Equatorial Plasma Bubbles During Two Moderate Geomagnetic Storms in May and June 2024 Over East/Southeast Asia
- Identification of malaria vulnerable zones in North East Region of India: Spatiotemporal assessment through geographical information system and self-organizing maps
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