Calibration and Uncertainty Quantification of Gravity Wave
Parameterization in an Intermediate Complexity Climate Model
Abstract
The drag due to breaking atmospheric gravity waves plays a leading order
role in driving the middle atmosphere circulation, but as their
horizontal wavelength ranges from tens to thousands of kilometers, part
of their spectrum must be parameterized in climate models. Gravity wave
parameterizations prescribe a source spectrum of waves in the lower
atmosphere and allow these to propagate upwards until they either
dissipate or break, where they deposit drag on the large-scale flow.
These parameterizations are a source of uncertainty in climate modeling
which is generally not quantified. Here, we explore the uncertainty
associated with a non-orographic gravity wave parameterization in a
global climate model of intermediate complexity, using the Calibrate,
Emulate and Sample (CES) method. We first calibrate the uncertain
parameters that define the gravity wave source spectrum in the tropics,
to obtain climate model settings that are consistent with properties of
the primary mode of tropical stratospheric variability, the
Quasi-Biennial Oscillation (QBO). Then we use a Gaussian process
emulator to sample the calibrated distribution of parameters and
quantify the uncertainty of these parameter choices. We find that the
resulting parametric uncertainties on the QBO period and amplitude are
of a similar magnitude to the internal variability under a 2xCO2
forcing.