Statistical Analysis of the Quantified Relationship between Evaporation Duct and Oceanic Evaporation for Unstable Conditions

Statistical Analysis of the Quantified Relationship between Evaporation Duct and Oceanic... AbstractAn analysis is conducted for the first time to statistically quantify the relationship between the evaporation duct and oceanic evaporation. Through sensitivity analysis, under unstable conditions (air–sea temperature difference less than zero), evaporation duct and evaporation are found to maintain a similar trend with variations in air–sea variables, indicating a possible inherent connection. Furthermore, scatterplots of relevant historical data reveal that the evaporation duct generally increases in a power-law manner with evaporation. Therefore, logarithmic transformation is performed on the data, and then linear regression is adopted to derive the analytical expression of the linear trend. Additionally, based on this analytical expression, a three-parameter empirical model is proposed to estimate the temporal clustering, and the estimated result shows good agreement with the real distribution. The spatial variations of the parameters modeled over different focus areas reflect the influence of geophysical parameters. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Atmospheric and Oceanic Technology American Meteorological Society

Statistical Analysis of the Quantified Relationship between Evaporation Duct and Oceanic Evaporation for Unstable Conditions

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Publisher
American Meteorological Society
Copyright
Copyright © American Meteorological Society
ISSN
1520-0426
D.O.I.
10.1175/JTECH-D-17-0156.1
Publisher site
See Article on Publisher Site

Abstract

AbstractAn analysis is conducted for the first time to statistically quantify the relationship between the evaporation duct and oceanic evaporation. Through sensitivity analysis, under unstable conditions (air–sea temperature difference less than zero), evaporation duct and evaporation are found to maintain a similar trend with variations in air–sea variables, indicating a possible inherent connection. Furthermore, scatterplots of relevant historical data reveal that the evaporation duct generally increases in a power-law manner with evaporation. Therefore, logarithmic transformation is performed on the data, and then linear regression is adopted to derive the analytical expression of the linear trend. Additionally, based on this analytical expression, a three-parameter empirical model is proposed to estimate the temporal clustering, and the estimated result shows good agreement with the real distribution. The spatial variations of the parameters modeled over different focus areas reflect the influence of geophysical parameters.

Journal

Journal of Atmospheric and Oceanic TechnologyAmerican Meteorological Society

Published: Nov 10, 2017

References

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