arXiv subjects

Raghu Murtugudde

Publications and source records attributed to Raghu Murtugudde.

4 recordsLinked to original sources

arXiv2026

Unexpected limitation of tropical cyclone genesis by subsurface tropical central-north Pacific during El Ni\~no

The vast tropical Pacific is home to the majority of tropical cyclones (TCs) which threaten the rim countries every year. The TC genesis is nourished by warm sea surface temperatures (SSTs). During El Ni\~no, the western Pacific warm pool extends eastward. However, the number of TCs does not increase significantly with the expanding warm pool and it remains comparable between El Ni\~no and La Ni\~na. Here, we show that the subsurface heat content change counteracts the favorable SSTs in the tropical central-north Pacific. Due to the anomalous positive wind stress curl, the 26 {\deg}C isotherm shoals during El Ni\~no over this region and the heat content diminishes in the tropical central-north Pacific, even though warm SST anomalies prevail. This negative correlation between SST and 26 {\deg}C isotherm depth anomalies is opposite to the positive correlation in the tropical eastern and western Pacific. This is critical because quantifying the dynamics of the subsurface ocean provides insight into TC genesis. The trend in TC genesis continues to be debated. Future projections must account for the net effect of the surface-subsurface dynamics on TCs, especially given the expected El Ni\~no-like pattern over the tropical Pacific under global warming.

physics.ao-ph↗

arXiv2026

Crucial role of subsurface ocean variability in tropical cyclone genesis

The upper ocean provides thermal energy to tropical cyclones. However, the impacts of the subsurface ocean on tropical cyclogenesis have been largely overlooked. Here, we show that the subsurface variabilities associated with the variation in the 26 {\deg}C isothermal depth have pronounced impacts on tropical cyclogenesis over global oceans. The sea surface wind stress and its curl before tropical cyclogenesis are large enough to perturb the ocean interior down to more than one hundred meters due to entrainment and upwelling. The 26 {\deg}C isothermal depth can fluctuate by tens of meters to significantly modify the upper ocean heat content. Consequently, sea surface temperature anomalies under nascent tropical cyclones are induced, and tropical cyclogenesis is modulated. Our results substantiate an unexpected relation between ocean interior variations and tropical cyclogenesis.

physics.ao-ph↗

arXiv2023

Analysis of Mumbai Floods in recent Years with Crowdsourced Data

Mumbai, a densely populated city, experiences frequent extreme rainfall events leading to floods and waterlogging. However, the lack of real-time flood monitoring and detailed past flooding data limits the scientific analysis to extreme rainfall assessment. To address this, we explore the usability of crowdsourced data for identifying flood hotspots and extracting reliable flood information from the past. Through an automated program, we filter and retrieve flood-related data from Twitter, using location information to generate flood maps for past heavy rainfall events. The validity of the retrieved data is confirmed by comparing it with volunteered geographic information (VGI) which is more accurate but less abundant. In the absence of direct flood information, Twitter data is cross-verified with the Height above the Nearest Drainage (HAND) map, which serves as a proxy for elevation. Interestingly, while extreme rainfall events are increasing in frequency, recent Twitter-based information shows a decrease in flood reporting, attributed to effective mitigation measures implemented at various flood hotspots. Local surveys support this finding and highlight measures such as underground storage tanks and pumping stations that have reduced flood severity. Our study demonstrates the value of crowdsourced data in identifying urban flood hotspots and its potential for real-time flood monitoring and forecasting. This approach can be adapted for data-sparse urban regions to generate location-specific warnings, contributing to improved early warnings and mitigating the impact on lives and property.

physics.ao-ph↗

arXiv2014

Preconditioned Krylov solvers for kernel regression

A primary computational problem in kernel regression is solution of a dense linear system with the $N\times N$ kernel matrix. Because a direct solution has an O($N^3$) cost, iterative Krylov methods are often used with fast matrix-vector products. For poorly conditioned problems, convergence of the iteration is slow and preconditioning becomes necessary. We investigate preconditioning from the viewpoint of scalability and efficiency. The problems that conventional preconditioners face when applied to kernel methods are demonstrated. A \emph{novel flexible preconditioner }that not only improves convergence but also allows utilization of fast kernel matrix-vector products is introduced. The performance of this preconditioner is first illustrated on synthetic data, and subsequently on a suite of test problems in kernel regression and geostatistical kriging.

math.NA↗