A new classification of satellite-derived liquid water cloud regimes at cloud scale

Abstract

Clouds are highly variable in time and space, affecting climate sensitivity and climate change. To study and distinguish the different influences of clouds on the climate system, it is useful to separate clouds into individual cloud regimes. In this work we present a new cloud classification for liquid water clouds at cloud scale defined using cloud parameters retrieved from combined satellite measurements from CloudSat and CALIPSO. The idea is that cloud heterogeneity is a measure that allows us to distinguish cumuliform and stratiform clouds, and cloud-base height is a measure to distinguish cloud altitude. The approach makes use of a newly developed cloud-base height retrieval. Using three cloud-base height intervals and two intervals of cloud-top variability as an inhomogeneity parameter provides six new liquid cloud classes. The results show a smooth transition between marine and continental clouds as well as between stratiform and cumuliform clouds in different latitudes at the high spatial resolution of about 20 km. Analysing the micro-and macrophysical cloud parameters from collocated combined MODIS, CloudSat and CALIPSO retrievals shows distinct characteristics for each cloud regime that are in agreement with expectation and literature. This demonstrates the usefulness of the classification.

Examining cloud vertical structure and radiative effects from satellite retrievals and evaluation of CMIP6 scenarios

“…For the eight infrequent CVSs (average cloud fraction <5%), their spatial patterns resemble the feature of H×M×L, excluding the high values of H×M over the Tibet Plateau and Antarctica caused by high terrain. In conclusion, the spatial patterns of these 12 CVSs reveal consistent distributions with well-known cloud top height/pressure characteristics (Marchand et al, 2010;King et al, 2013) and, for the single-layer clouds, documented cloud regimes from 220 approaches (Tselioudis et al, 2013;2021;Unglaub et al, 2020). However, the quantitative cloud fractions of the various CVS types provided here is previously not achievable with passive satellite sensors.…”

Decomposing Effective Radiative Forcing due to Aerosol Cloud Interactions by Global Cloud Regimes

“…This regime methodology has the key limitation of only being available on daylit points due to technical limitations of COSP, however, this has the advantage that the results can be easily compared with satellite data as a result of the design goal of COSP. Other regime classification methods exist, however, for instance Unglaub et al (2020), which uses cloud base From this analysis it can be concluded that a large majority of forcing in the HadGEM3 GA7.1 comes from changes to the thick stratocumulus and thick midlevel cloud regimes (amounting to a of −0.51 E and −0.23 E Wm −2 , respectively). These two sets of regimes have a similar geographical distribution and there may be some crossover between the two regimes, owing to the simplicity of the regime assignment method.…”

Decomposing Effective Radiative Forcing Due to Aerosol Cloud Interactions by Global Cloud Regimes

“…This regime methodology has the key limitation of only being available on daylit points due to technical limitations of COSP, however, this has the advantage that the results can be easily compared with satellite data as a result of the design goal of COSP. Other regime classification methods exist, however, for instance Unglaub et al (2020), which uses cloud base From this analysis it can be concluded that a large majority of forcing in the HadGEM3 GA7.1 comes from changes to the thick stratocumulus and thick midlevel cloud regimes (amounting to a total of −0.51 E and −0.23 Wm −2 , respectively). These two sets of regimes have a similar geographical distribution and there may be some crossover between the two regimes, owing to the simplicity of the regime assignment method.…”