  New-generation spectrographs dedicated to the study of exoplanetary
atmospheres require a high accuracy in the atmospheric models to better
interpret the input spectra. Thanks to space missions, the observed spectra
will cover a large wavelength range from visible to mid-infrared with an higher
precision compared to the old-generation instrumentation, revealing complex
features coming from different regions of the atmosphere. For hot and ultra hot
Jupiters (HJs and UHJs), the main source of complexity in the spectra comes
from thermal and chemical differences between the day and the night sides. In
this context, one-dimensional plane parallel retrieval models of atmospheres
may not be suitable to extract the complexity of such spectra. In addition,
Bayesian frameworks are computationally intensive and prevent us from using
complete three-dimensional self-consistent models to retrieve exoplanetary
atmospheres. We propose the TauREx 2D retrieval code, which uses
two-dimensional atmospheric models as a good compromise between computational
cost and model accuracy to better infer exoplanetary atmospheric
characteristics for the hottest planets. TauREx 2D uses a 2D parametrization
across the limb which computes the transmission spectrum from an exoplanetary
atmosphere assuming azimuthal symmetry. It also includes a thermal dissociation
model of various species. We demonstrate that, given an input observation,
TauREx 2D mitigates the biases between the retrieved atmospheric parameters and
the real atmospheric parameters. We also show that having a prior knowledge on
the link between local temperature and composition is instrumental in inferring
the temperature structure of the atmosphere. Finally, we apply such a model on
a synthetic spectrum computed from a GCM simulation of WASP-121b and show how
parameter biases can be removed when using two-dimensional forward models
across the limb.
