We explore the decoupling physics of a stratocumulus-topped boundary layer (STBL) moving over cooler water, a situation mimicking the warm air advection (WADV). We simulate an initially well-mixed STBL over a doubly periodic domain with the sea surface temperature decreasing linearly over time using the System for Atmospheric Modeling large-eddy model. Due to the surface cooling, the STBL becomes increasingly stably stratified, manifested as a near-surface temperature inversion topped by a well-mixed cloud-containing layer. Unlike the stably stratified STBL in cold air advection (CADV) that is characterized by cumulus coupling, the stratocumulus deck in the WADV is unambiguously decoupled from the sea surface, manifested as weakly negative buoyancy flux throughout the sub-cloud layer. Without the influxes of buoyancy from the surface, the convective circulation in the well-mixed cloud-containing layer is driven by cloud-top radiative cooling. In such a regime, the downdrafts propel the circulation, in contrast to that in CADV regime for which the cumulus updrafts play a more determinant role. Such a contrast in convection regime explains the difference in many aspects of the STBLs including the entrainment rate, cloud homogeneity, vertical exchanges of heat and moisture, and lifetime of the stratocumulus deck, with the last being subject to a more thorough investigation in part 2 of this study. Finally, we investigate under what conditions a secondary stratus near the surface (or fog) can form in the WADV. We found that weaker subsidence favors the formation of fog whereas a more rapid surface cooling rate doesn’t.

Surface latent heat flux (LHF) has been deemed as the determinant driver of the stratocumulus-to-cumulus transition (SCT). The distinct signature of the LHF in driving the SCT, however, has not been found in observations. This motivates us to ask: how determinant the LHF is to SCT? To answer it, we conduct large-eddy simulations in a Lagrangian setup in which the sea-surface temperature increases over time to mimic a low-level cold air advection. To isolate the role of LHF, we conduct a mechanism-denial experiment in which the LHF adjustment is turned off to evaluate the response of SCT. The simulations confirm the indispensable roles of LHF in sustaining (although not initiating) the boundary layer decoupling (first stage of SCT) and driving the cloud regime transition (second stage of SCT). Specifically, we found that decoupling can happen without the need for LHF to increase as long as the capping inversion is weak enough to ensure high entrainment efficiency. The decoupled state, however, cannot sustain without the help of LHF adjustment, leading to the recoupling of the boundary layer. In the coupled boundary layer, the stratocumulus sheet thins over time due to the lack of moisture supply, eventually leading to a cloud-free boundary layer. Interestingly, the stratocumulus sheet sustains longer without LHF adjustment. The mechanisms underlying the findings are explained from the perspectives of cloud-layer budgets of energy (first stage) and liquid water path (second stage). Lastly, we develop a new model diagnostic that offers a physically robust conceptualization of boundary layer decoupling.

A one-year’s worth of global (except poleward of 65 º N/S) marine shallow single-layer cloud-top radiative cooling (CTRC) is derived from a radiative transfer model with inputs from the satellite cloud retrievals and reanalysis sounding. The mean cloud-top radiative flux divergence is 61 Wm-2, decomposed into the longwave and shortwave components of 73 and -11 W m-2, respectively. The CTRC is largely a reflection of free-atmospheric specific humidity distribution: a dry atmosphere enhances CTRC by reducing downward thermal radiation. Consequently, the cooling minimizes in the “wet” tropics and maximizes in the “dry” eastern subtropics. Poleward of 30 º N/S, the CTRC decreases slightly due to the colder clouds that emit less effectively. The CTRC exhibits distinctive seasonal cycles with stronger cooling in the winter and has amplitudes of order 10~20 Wm-2 in stratocumulus-rich regions. The datasets were used to train a machine-learning model that substantially speeds up the retrieval.

Forests play a pivotal role in regulating climate and sustaining the hydrological cycle. The biophysical impacts of forest on clouds, however, remain unclear due to the lack of direct observations. In this first global-scale observational study, we use long-term satellite-derived cloud cover data to show that forests can have opposite effects on summer cloud cover. We find enhanced cloud cover over most temperate and boreal forests, but inhibited cloud cover over Amazon, central Africa, and Southeast US. These cloud effects mainly arise from convection processes associated with forests. The spatial variation in the sign of cloud effects is driven by sensible heating where cloud enhancement (inhibition) is more likely to occur when sensible heat in forest is larger (smaller) than nearby nonforest. Ongoing forest cover loss has led to opposite cloud cover changes, with local cloud increase over forest loss hotspots in the Amazon (+0.78%), Indonesia (+1.19%), and Southeast US (+0.09%), but cloud reduction in East Siberia (-0.20%) from 2002-2018. Our data-driven assessment informs the climate effects of local-scale forest cover change and improves mechanistic understanding of forest-cloud interactions, the latter of which remains uncertain in Earth system models.

Sub-cloud turbulent kinetic energy has been used to parameterize the cloud-base updraft velocity (wb) in cumulus parameterizations. The validity of this idea has never been proved in observations. Instead, it was challenged by recent Doppler lidar observations showing a poor correlation between the two. We argue that the low correlation is likely caused by the difficulty of a fixed-point lidar to measure ensemble properties of cumulus fields. Taking advantage of the stationarity and ergodicity of early-afternoon convection, we developed a lidar sampling methodology to measure wb of a shallow cumulus (ShCu) ensemble (not a single ShCu). By analyzing 128 ShCu ensembles over the Southern Great Plains, we show that the ensemble properties of sub-cloud turbulence explain nearly half of the variability in ensemble-mean wb, demonstrating the ability of sub-cloud turbulence to dictate wb. The derived empirical formulas will be useful for developing cumulus parameterizations and satellite inference of wb.