TY - JOUR
T1 - Statistical analysis of the quantified relationship between evaporation duct and oceanic evaporation for unstable conditions
AU - Zhang, Qi
AU - Yang, Kunde
AU - Yang, Qiulong
N1 - Publisher Copyright:
© 2017 American Meteorological Society.
PY - 2017/11/1
Y1 - 2017/11/1
N2 - An 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.
AB - An 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.
KW - Air-sea interaction
KW - Evaporation
KW - Numerical analysis/modeling
KW - Sensitivity studies
KW - Statistical techniques
KW - Water vapor
UR - http://www.scopus.com/inward/record.url?scp=85036460858&partnerID=8YFLogxK
U2 - 10.1175/JTECH-D-17-0156.1
DO - 10.1175/JTECH-D-17-0156.1
M3 - 文章
AN - SCOPUS:85036460858
SN - 0739-0572
VL - 34
SP - 2489
EP - 2497
JO - Journal of Atmospheric and Oceanic Technology
JF - Journal of Atmospheric and Oceanic Technology
IS - 11
ER -