Correlation Structures between Satellite All-Sky Infrared Brightness
Temperatures and the Atmospheric State at Storm Scales
Abstract
This study explores the structures of the correlations between infrared
(IR) brightness temperatures (BTs) from the three water vapor channels
of the Advanced Baseline Imager (ABI) onboard the GOES-16 satellite and
the atmospheric state. Ensemble-based data assimilation techniques such
as the ensemble Kalman filter (EnKF) rely on correlations to propagate
innovations of BTs to increments of model state variables. Because the
three water vapor channels are sensitive to moisture in different layers
of the troposphere, the heights of the strongest correlations between
these channels and moisture in clear-sky regions are closely related to
the peaks of their respective weighting functions. In cloudy regions,
the strongest correlations appear at the cloud tops of deep clouds, and
ice hydrometeors generally have stronger correlations with BT than
liquid hydrometeors. The magnitudes of the correlations decrease from
the peak value in a column with both vertical and horizontal distance.
Just how the correlations decrease depend on both the cloud scenes and
the cloud structures, as well as the model variables. Horizontal
correlations between BTs and moisture, as well as hydrometeors, in fully
cloudy regions decrease to almost 0 at about 30 km. The horizontal
correlations with atmospheric state variables in clear-sky regions are
broader, maintaining non-zero values out to ~100 km. The
results in this study provide information on the proper choice of cutoff
radii in horizontal and vertical localization schemes for the
assimilation of BTs. They also provide insights on the most efficient
and effective use of the different water vapor channels.