Quantifying the driving mechanisms and effect on Earth's energy budget, of
mesoscale shallow cloud organisation, remains difficult. Partly because
quantifying the atmosphere's organisational state through objective means
remains challenging. We present the first map of the full continuum of
convective organisation states by extracting the manifold within an
unsupervised neural networks's internal representation. On the manifold
distinct organisational regimes, defined in prior work, sit as waymarkers in
this continuum. Composition of reanalysis and observations onto the manifold,
shows wind-speed and water vapour concentration as key environmental
characteristics varying with organisation. We show, for the first time, that
mesoscale shallow cloud organisation produces ±1.4% variations in albedo
in addition to variations from cloud-fraction changes alone. We further
demonstrate how the manifold's continuum representation captures the temporal
evolution of organisation. By enabling study of states and transitions in
organisation (in simulations and observations) the presented technique paves
the way for better representation of shallow clouds in simulations of Earth's
future climate