Karthik Balaguru

Biographic Data

ID7992911
NAMEKarthik Balaguru
GIVEN NAMESKarthik
FAMILY NAMEBalaguru
SIGNATUREBALAGURU K
AFFILIATIONSPacific Northwest National Laboratory
ORCID0000-0003-0181-2687
VERIFIEDYes
TOTAL WORKS4
TOTAL CITATIONS0
WORKS AS AUTHOR4
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2013
LATEST PUBLICATION YEAR2025
H-INDEX0

  • Improving tropical cyclone rapid intensification forecasts with satellite measurements of sea surface salinity and calibrated machine learning

    Open AccessRyan Eusebi, Hui Su et al.ARTICLEEnvironmental Research Letters2025

    Forecasting rapid intensification (RI) of tropical cyclones (TC) is a mission known for large errors. One under-researched factor that affects TC intensification is salinity, which is important for density stratification in certain ocean regions and can affect the surface enthalpy flux under a strengthening hurricane. To investigate the impact and efficacy of using salinity information in state-of-the-art forecasting, we use a statistical model c…

  • Projected increases in tropical cyclone-induced U.S. electric power outage risk

    Open AccessJulian Rice, Karthik Balaguru et al.ARTICLEEnvironmental Research Letters2025

    While power outages caused by tropical cyclones (TCs) already pose a great threat to coastal communities, how—and why—these risks will change in a warming climate is poorly understood. To address this need, we develop a robust machine learning model to capture TC-induced power outage risk. When applied to 900 000 synthetic TCs downscaled from simulated historical and future climate conditions under a strong warming scenario, we find outage risk i…

  • Projecting U.S. coastal storm surge risks and impacts with deep learning

    Open AccessJulian Rice, Karthik Balaguru et al.ARTICLEEnvironmental Research Letters2025

    Storm surge is one of the deadliest hazards posed by tropical cyclones (TCs), yet assessing its current and future risk is difficult due to the phenomenon’s rarity and physical complexity. Recent advances in artificial intelligence applications to natural hazard modeling suggest a new avenue for addressing this problem. We develop a deep learning storm surge model to efficiently estimate coastal surge risk in the United States from 900 000 synthe…

  • Oceanic control of Northeast Pacific hurricane activity at interannual timescales

    Open AccessKarthik Balaguru, L Ruby Leung et al.ARTICLEEnvironmental Research Letters2013

    Sea surface temperature (SST) is not the only oceanic parameter that can play a key role in the interannual variability of Northeast Pacific hurricane activity. Using several observational data sets and the statistical technique of multiple linear regression analysis, we show that, along with SST, the thermocline depth (TD) plays an important role in hurricane activity at interannual timescales in this basin. Based on the parameter that dominates…