  We present a novel retrieval technique that attempts to model phase curve
observations of exoplanets more realistically and reliably, which we call the
2.5-dimension (2.5-D) approach. In our 2.5-D approach we retrieve the vertical
temperature profile and mean gaseous abundance of a planet at all longitudes
and latitudes \textbf{simultaneously}, assuming that the temperature or
composition, $x$, at a particular longitude and latitude $(\Lambda,\Phi)$ is
given by $x(\Lambda,\Phi) = \bar{x} + (x(\Lambda,0) - \bar{x})\cos^n\Phi$,
where $\bar{x}$ is the mean of the morning and evening terminator values of
$x(\Lambda,0)$, and $n$ is an assumed coefficient. We compare our new 2.5-D
scheme with the more traditional 1-D approach, which assumes the same
temperature profile and gaseous abundances at all points on the visible disc of
a planet for each individual phase observation, using a set of synthetic phase
curves generated from a GCM-based simulation. We find that our 2.5-D model fits
these data more realistically than the 1-D approach, confining the hotter
regions of the planet more closely to the dayside. We then apply both models to
WASP-43b phase curve observations of HST/WFC3 and Spitzer/IRAC. We find that
the dayside of WASP-43b is apparently much hotter than the nightside and show
that this could be explained by the presence of a thick cloud on the nightside
with a cloud top at pressure $< 0.2$ bar. We further show that while the mole
fraction of water vapour is reasonably well constrained to
$(1-10)\times10^{-4}$, the abundance of CO is very difficult to constrain with
these data since it is degenerate with temperature and prone to possible
systematic radiometric differences between the HST/WFC3 and Spitzer/IRAC
observations. Hence, it is difficult to reliably constrain C/O.
