  The determination of atmospheric structure and molecular abundances of
planetary atmospheres via spectroscopy involves direct comparisons between
models and data. While varying in sophistication, most model-spectra
comparisons fundamentally assume "1D" model physics. However, knowledge from
general circulation models and of solar system planets suggests that planetary
atmospheres are inherently "3D" in their structure and composition. We explore
the potential biases resulting from standard "1D" assumptions within a Bayesian
atmospheric retrieval framework. Specifically, we show how the assumption of a
single 1-dimensional thermal profile can bias our interpretation of the thermal
emission spectrum of a hot Jupiter atmosphere that is composed of two thermal
profiles. We retrieve upon spectra of unresolved model planets as observed with
a combination of $HST$ WFC3+$Spitzer$ IRAC as well as $JWST$ under varying
differences in the two thermal profiles. For WFC3+IRAC, there is a
significantly biased estimate of CH$_4$ abundance using a 1D model when the
contrast is 80%. For $JWST$, two thermal profiles are required to adequately
interpret the data and estimate the abundances when contrast is greater than
40%. We also apply this preliminary concept to the recent WFC3+IRAC phase curve
data of the hot Jupiter WASP-43b. We see similar behavior as present in our
simulated data: while the H$_2$O abundance determination is robust, CH$_4$ is
artificially well-constrained to incorrect values under the 1D assumption. Our
work demonstrates the need to evaluate model assumptions in order to extract
meaningful constraints from atmospheric spectra and motivates exploration of
optimal observational setups.
