Application of Orthogonal Polynomial Fitting Method to Extract Gravity
Wave Signals from AIRS Data Related to Typhoon Deep Convection
Abstract
Gravity waves can influence weather and climate patterns on various
temporal and spatial scales in atmosphere. Despite their recognized
importance, there are clearly a lack of sufficient and accurate
observations from currently available satellite observing systems to
satisfy the requirements of many satellite users. Common method to
detect gravity waves is to measure bright temperature (BT) anomalies,
which rely on an initial efficient background removal method. Before
gravity waves can be extracted from Atmospheric Infrared Sounder (AIRS)
raw radiances, Hoffmann and Alexander (2010) used a fourth-order
polynomial fitting (4PF) method to remove the background variations. In
this study, we propose a new strategy, an optimal orthogonal polynomial
fitting (OPF) method using Chebyshev Polynomials as basis functions, to
remove the background variations and estimate BT perturbations. By
extending the classic 4PF method to the fifth-order polynomial fitting
(5PF) method, and combining the Cressman interpolation (CI) method, some
experiments are designed to validate the feasibility and superiority of
OPF method. The results show that OPF is the optimal method to remove
the limb-brightening effect in the extraction of gravity wave signals
generated by typhoons. In addition, what we noticed is that an
appropriate fitting orders have to be selected to get more accurate BT
anomalies signals in the experiments to extract gravity wave signals.