The TropD software package (v1): standardized methods for calculating tropical-width diagnostics

Observational and modeling studies suggest that Earth's tropical belt has widened over the late 20th century and will continue to widen throughout the 21st century. Yet, estimates of tropical-width variations differ significantly across studies. This uncertainty, to an unknown degree, is partly...

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Bibliographic Details
Published in:Geoscientific Model Development 2018-10, Vol.11 (10), p.4339-4357
Main Authors: Adam, Ori, Grise, Kevin M, Staten, Paul, Simpson, Isla R, Davis, Sean M, Davis, Nicholas A, Waugh, Darryn W, Birner, Thomas, Ming, Alison
Format: Article
Language:English
Subjects:
Climate change
Computer software
Datasets
Dependence
Earth
Forecasts and trends
Latitude
Meteorological research
Methods
Modelling
Noise
Noise sensitivity
Noise threshold
Observations
Programming languages
Sensitivity analysis
Software
Syntax
Tropical climate
Tropical climates
Uncertainty
Width
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Summary:Observational and modeling studies suggest that Earth's tropical belt has widened over the late 20th century and will continue to widen throughout the 21st century. Yet, estimates of tropical-width variations differ significantly across studies. This uncertainty, to an unknown degree, is partly due to the large variety of methods used in studies of the tropical width. Here, methods for eight commonly used metrics of the tropical width are implemented in the Tropical-width Diagnostics (TropD) code package in the MATLAB programming language. To consolidate the various methods, the operations used in each of the implemented methods are reduced to two basic calculations: finding the latitude of a zero crossing and finding the latitude of a maximum. A detailed description of the methods implemented in the code and of the code syntax is provided, followed by a method sensitivity analysis for each of the metrics. The analysis provides information on how to reduce the methodological component of the uncertainty associated with fundamental aspects of the calculations, such as monthly vs. seasonal averaging biases, grid dependence, sensitivity to noise, and sensitivity to threshold criteria.
ISSN:1991-9603
1991-959X
1991-962X
1991-9603
1991-962X
DOI:10.5194/gmd-11-4339-2018