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Improving cyclone prediction, saving lives

The tracks of all tropical cyclones in the North Indian Ocean during the 2013 season. The points show the location of each storm at six-hour intervals. The colors represent the storm's maximum sustained wind speeds as classified by the Saffir-Simpson Hurricane Scale, and the shapes represent the nature of the storm. Image courtesy Wikimedia Commons.

Tropical cyclones (TCs) are the costliest and often deadliest natural hazards on the planet. Research published in the journal Nature Climate Changereveals that by 2100, damage caused by TCs will increase from the current $26 billion to a projected $56 billion globally.

Because every weather model is prone to at least minor errors, predicting the direction and intensity of cyclones remains a challenge. In the past few decades, researchers have made significant progress in predicting the direction a cyclone will take, but few improvements in forecasting its strength and destructive potential.

An international team of scientists, led by researchers at Pacific Northwest National Laboratory (PNNL) in Richland, Washington, US, is investigating how model errors grow. Simulating Indian Ocean TCs and using very high-resolution models, their research reveals that in TC environments, model errors begin to grow in calculations over small regions with strong convection and condensation, and continue to build from local to regional scales.

The scientists and their collaborators at the Indian Institute of Tropical Meteorology and Pennsylvania State University, US, used the Weather Research & Forecasting Model (WRF v3.4) to simulate conditions in the Indian Ocean, with only small differences among the initial scenarios. The team computed how quickly errors doubled and conducted a number of experiments to determine how the errors compounded as spatial scales widened.

Comparing results from simulations of TCs at 10-kilometer resolution with parameterized convection, the scientists found that moist convection plays a major role in error growth that limits TC predictability. Model errors start to accrue from convection regions and ultimately affect larger scale simulations. The scientists also discovered that errors at small scales grow faster than those at larger scales, even in sophisticated models that explicitly simulate processes involving clouds and rain.

"The sorts of errors we found ultimately limit the ability to predict Indian Ocean tropical cyclones," says PNNL atmospheric researcher and study lead Dr. Sourav Taraphdar."Solving those errors will improve our ability to forecast cyclone direction and intensity." The scientists used cyclone track and intensity information from the India Meteorological Department to evaluate and compare model performance to real storms.

Reliably predicting the track and intensity of such storms may not have an immediate impact on property damage, but lower fatalities are a direct result of more accurate predictions. The reduction of model errors like the ones Taraphdar and his colleagues are studying could ultimately result in thousands of lives saved.