Cloud transition across the daily cycle illuminates model responses of trade cumuli to warming

Abstract

The response of trade cumulus clouds to warming remains a major source of uncertainty for climate sensitivity. Recent studies have highlighted the role of the cloud–convection coupling in explaining this spread in future warming estimates. Here, using observations from an instrumented site and an airborne field campaign, together with high-frequency climate model outputs, we show that i) over the course of the daily cycle, a cloud transition is observed from deeper cumuli during nighttime to shallower cumuli during daytime, ii) the cloud evolution that models predict from night to day reflects the strength of cloud sensitivity to convective mass flux and exhibits many similarities with the cloud evolution they predict under global warming, and iii) those models that simulate a realistic cloud transition over the daily cycle tend to predict weak trade cumulus feedback. Our findings thus show that the daily cycle is a particularly relevant testbed, amenable to process studies and anchored by observations, to assess and improve the model representation of cloud–convection coupling and thus make climate projections more reliable.

What Are the Main Causes of Positive Subtropical Low Cloud Feedbacks in Climate Models?

“…Another important caveat associated with this work is that while we have demonstrated an approach for testing physical hypotheses proposed to explain the causes of positive low cloud feedbacks, we have in this first instance applied it only to a single location in the Californian stratocumulus/trade cumulus transition region for each model. As with other studies focusing on a small number of locations such as Blossey et al (2016) or Vial et al (2023), we should be mindful that our findings might not be robust when applied to other locations or seasons. Clearly it would be of interest to apply this approach to other locations and seasons in these models in future work.…”

“…If it were shown to be the case however, then our present case for ruling out of some mechanisms on the basis of there being no reduction in climatological mean relative humidity in the cloud layer would need to be revisited (e.g., for the surface latent heat flux decoupling, vertical specific humidity gradient convective entrainment and surface upwelling longwave mechanisms in MRI‐ESM2.0 and other models (see Table 9)). This question could be investigated using high frequency model outputs saved from some CFMIP models (e.g., Vial et al., 2023; Vogel et al., 2022; M. J. Webb, Lock, Bodas‐Salcedo, et al., 2015, M. J. Webb et al., 2017).…”

“…Another argument that has been put forward to explain low cloud changes across a range of regimes and timescales (in subtropical trade cumulus in particular) is that changes in cloud radiative cooling affect the stability of the boundary layer, in turn influencing the strength, depth and fractional area of shallow convective clouds (e.g., Vial et al, 2021Vial et al, , 2023Vogel et al, 2022; M. J. Webb & Lock, 2013;Wyant et al, 2009).…”

“…Despite the progress in constraining the magnitudes of subtropical low cloud feedbacks described above, there remain many competing hypotheses to potentially explain the physical mechanisms responsible for them, given that stratocumulus and stratocumulus to trade cumulus transition region feedbacks may well be as important as trade cumulus feedbacks in some models (e.g., Blossey et al., 2013; Bretherton & Blossey, 2014; Bretherton et al., 2013; Brient & Bony, 2012, 2013; Brient et al., 2016; Hirota et al., 2021; Jones et al., 2014; Koshiro et al., 2022; Rieck et al., 2012; S. C. Sherwood et al., 2014; Vial et al., 2016, 2021, 2023; Vogel et al., 2022; M. J. Webb & Lock, 2013; Zhang et al., 2013). This presents a challenge when it comes to improving climate models, as there are multiple parametrizations involved which represent processes such as surface‐atmosphere heat and moisture exchange, atmospheric convection, turbulence, cloud microphysics, and cloud cover.…”

Cloud Botany: Shallow Cumulus Clouds in an Ensemble of Idealized Large‐Domain Large‐Eddy Simulations of the Trades

“…Radiative heating rates are calculated interactively with RRTMG (Iacono et al., 2008; Pincus et al., 2003). As the importance of diurnal, radiative variability in the downstream trades has recently been emphasized (Albright et al., 2021; Narenpitak et al., 2023; Vial et al., 2019, 2021, 2023), we include in the model's shortwave component the diurnal cycle representative for Feb‐01‐2020 at 13.1°N and 52°W (representative of the EUREC 4 A domain and period). Required input profiles for water vapor and temperature above the LES domain were derived from ERA5, averaged over the EUREC 4 A region and period.…”