Emanuel ( 2005) showed the total destructive potential Has already increased storm intensities – a trend expected to continue as theĮarth system warms. Numerical models (e.g., Emanuel, 1987 Tsuboki et al., 2015 Sobel et al., 2016 Wehner et al., 2018)Īlong with recent observations ( Kossin et al., 2020) indicate that climate change Damages increaseĮxponentially with tropical cyclone intensity ( ∼5 % per m s −1 Murnane and Elsner, 2012), so it is crucial to understand andĪccurately bound tropical cyclone maximum wind speeds. Tropical cyclones pose significant risks to coastal societies, being among theĬostliest and deadliest of global natural hazards Tropical cyclone thermodynamic calculations. Will improve on pyPI's assumptions, flexibility, and range of applications and In climatological and meteorological research. Example calculations with reanalyses data demonstrate pyPI's usefulness Improvement on the algorithm's consistency and handling of missingĭata.
Identical to the previous potential intensity computation but is an Its Python implementation, and (3) demonstrates and encourages the use of PI Validated Python PI algorithm, (2) carefully documents the PI algorithm and The pyPI package (1) provides a freely available, flexible, Python (pyPI, v1.3) package develops the PI algorithm in Python and for theįirst time details the full background and algorithm (line by line) used toĬompute tropical cyclone potential intensity constrained by The Tropical Cyclone Potential Intensity Calculations in Originally developed by Kerry Emanuel – is in widespread use, it remains Of atmospheric and oceanographic conditions, but although a PI algorithm – Previous studies have calculated PI given a set Useful diagnostic for evaluating or predicting tropical cyclone intensityĬlimatology and variability.
Significant correlations between PI and actual storm wind speeds, PI is a Potential intensity (PI) is the maximum speed limit of a tropical cycloneįound by modeling the storm as a thermal heat engine.
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