The Role of Mesoscale Cloud Morphology in the Shortwave Cloud Feedback

Abstract

The response of low clouds to global warming is one of the largest uncertainties in projections of climate change. Low clouds strongly affect the amount of shortwave radiation reflected back to space from Earth, but do not affect outgoing longwave radiation substantially (e.g., Hartmann & Short, 1980). How clouds alter reflected shortwave radiation in response to warming is termed the shortwave cloud feedback. It is uncertain how low clouds will respond to changes in the atmosphere in a warming world and contribute to this feedback (e.g., Ceppi et al., 2017;Zelinka et al., 2012aZelinka et al., , 2012bZelinka et al., , 2016Zelinka et al., , 2020. This uncertainty drives spread in the climate sensitivity predicted by global climate models (GCMs) (e.g., Caldwell et al., 2016). Thus, improving our understanding of how low clouds will change in a warming world is critical to predicting 21st century warming (e.g., Bony et al., 2015;Sherwood et al., 2020).At zeroth order, the mean optical thickness and extent of low cloud strongly affect global albedo (Engstrom et al., 2015b). However, low clouds encompass different morphology patterns with regionally varied mesoscale features (e.g., large-scale structures O ∼ 100 km of clouds with typical cell sizes O ∼ 20-80 km, Wood & Hartmann, 2006;Zhou et al., 2021;Stevens et al., 2019). For example, open and closed mesoscale cellular convective (MCC) organization that dominate subtropical stratocumulus (Sc) cloud decks and marine cold-air

Spatial Aggregation of Satellite Observations Leads to an Overestimation of the Radiative Forcing due to Aerosol‐Cloud Interactions

“…Our study also attributes the bias in β to cloud morphology, thus providing a more physically grounded perspective rather than the more generic cloud heterogeneity term. I. L. McCoy et al (2022) have shown that environmentally driven transitions between Sc cloud morphologies coincide with variations in thin cloud features, which as shown here, control the magnitude of the bias in β. Future changes in the frequency of occurrence of Sc cloud morphologies could therefore influence the magnitude of RF aci .…”

“…Future changes in the frequency of occurrence of Sc cloud morphologies could therefore influence the magnitude of RF aci . Such changes could be attributed to various factors, including cloud feedbacks (I. L. McCoy et al, 2022), changes in cloud thickness resulting from rising CO 2 concentrations (Schneider et al, 2019), and changes in aerosol levels that can influence Sc transitions (Goren et al, 2019(Goren et al, , 2022. Our results also show that for a given cloud albedo, β tends to be larger under more heterogeneous conditions.…”

“…However, to the best of our knowledge, no studies have quantified the propagation of this bias in β to the bias in RF aci within the context of the common practice of spatial data aggregation. Moreover, with the growing recognition of the significance of cloud morphology in determining 𝐴𝐴 R (I. L. McCoy et al, 2022), it is crucial to establish the dependence of β on cloud morphology, rather than on the generic term of cloud heterogeneity.…”

The Role of Mesoscale Cloud Morphology in the Shortwave Cloud Feedback

“…Manuscript supporting data is available at https://doi.org/10.5281/zenodo.7311993 (I. L. McCoy & Wood, 2022). CERES Single Scanner Footprint (SSF) daily 1deg product is available at https://asdc.larc.nasa.gov/project/CERES/CER_SSF1deg-Hour_Aqua-MODIS_Edition4A (NASA/LARC/SD/ASDC, 2015).…”