Open AccessIce Particle Mass–Dimensional Relationship Retrieval and Uncertainty Evaluation Using the Optimal Estimation Methodology Applied to the MACPEX Data
Author(s) -
Zhuocan Xu,
Gerald G. Mace
Publication year - 2017
Publication title -
journal of applied meteorology and climatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.079
H-Index - 134
eISSN - 1558-8432
pISSN - 1558-8424
DOI - 10.1175/jamc-d-16-0222.1
Subject(s) - cirrus , ice cloud , environmental science , range (aeronautics) , ice crystals , middle latitudes , particle (ecology) , atmospheric sciences , meteorology , statistics , remote sensing , mathematics , geology , physics , materials science , radiative transfer , optics , oceanography , composite material
A Bayesian optimal estimation methodology is applied to retrieve the time-varying ice particle mass–dimensional (M–D) relationships (i.e., M = a m D b m ) and the associated uncertainties using the in situ data that were collected by the NASA WB-57 during the Midlatitude Airborne Cirrus Properties Experiment (MACPEX) in March and April 2011. The authors utilize the coincident measurements of bulk ice water content and projected cross-sectional area to constrain M–D relationships and estimate the uncertainties. It is demonstrated that the additional information provided by the particle area with respect to size could contribute considerable improvements to the algorithm performance. Extreme variability of M–D properties is found among cases as well as within individual cases, indicating the nondiscrete nature of ice crystal habits within cloud volumes and further suggesting the risk of assuming a constant M–D relationship in different conditions. Relative uncertainties of a m are approximately from 50% to 80%, and relative uncertainties of b m range from 6% to 9.5%, which would cause approximately 2.5-dB uncertainty in forward-modeled radar reflectivity or a factor-of-2 uncertainty in ice water content.