Observed Subcloud-Layer Moisture and Heat Budgets in the Trades

Abstract

The trade-wind subcloud layer is an important structural component of the atmosphere. Its thermodynamic variability has long been characterized using simple frameworks, of which mixed layer theory is the simplest kind. Past studies qualitatively support such a description, yet the adequacy of mixed layer theory as a quantitative description has not been tested. Here we use observations collected during the EUREC4A (Elucidating the role of clouds–circulation coupling in climate) field campaign to test this framework and evaluate our understanding of the trade-wind subcloud layer. We find evidence for a transition layer separating the mixed layer and subcloud layer tops. The presence of such a finitely-thick transition layer with vertical gradients complicates the application of mixed layer theory, which assumes an abrupt gradient, or ‘jump’ at the subcloud layer top. This ambiguity introduces effective parameters and motivates their estimation through a Bayesian methodology. Results from this Bayesian inversion further reflect a finite-depth entrainment zone. We find that subcloud layer moisture and heat budgets close for synoptic variability and a monthly campaign-mean, yielding a campaign-mean residual of 3.6 Wm−2 for moisture and 2.9 Wm−2 for heat. Surface wind speed variability influences the subcloud layer depth and fluxes, yet thermodynamic variability above the subcloud layer top emerges as the primary control on subcloud layer moisture and heat variability. Given that this simple theoretical framework can explain observed variability, it offers an appealing framework for evaluating larger-scale models that must parameterize the processes regulating this fundamental part of the atmosphere.

Strong cloud–circulation coupling explains weak trade cumulus feedback

“…A typical flight day of HALO consisted of two sets of three consecutive circles lasting about 3 h and comprising 30-36 sondes (sometimes defined as circling 9,22,29 ). The 3-h circle sets are separated by a 1.5-h break to refuel the ATR.…”

“…Vogel et al 20 developed a method to estimate the shallow-convective mass flux at the sub-cloud-layer top as a residual of the sub-cloud-layer mass budget and tested it in real-case large-eddy simulations over the tropical Atlantic. Here the method is applied to EUREC 4 A observations, in parallel with Albright et al 22 , who close the sub-cloud-layer moisture and heat budgets and provide an independent constraint on the entrainment rate E. Except for the surface buoyancy flux estimate (see the previous section), all data for the budgets come entirely from the dropsondes. Equation ( 1) expresses the budget of the sub-cloud-layer height h per unit area and constant density.…”

“…As noted above, E describes the net effect of local processes and must be inferred from the statistics of other quantities (that is, the mean sub-cloud-layer growth rate or the dilution of sub-cloud-layer properties). This raises the question whether the E estimate itself might depend on the mesoscale environment and therefore introduce spurious co-variabilities between M, W and C. The Bayesian estimation of the uncertain parameter estimates A e , C q and C θ is a priori independent of M and W. Also, the synoptic variability during EUREC 4 A can be well explained by keeping them constant 22 . Reference 22 also explored to what extent other factors correlated with residuals in their Bayesian fits and found no evidence of a systematic effect of other factors, including wind speed and shear 64 .…”

“…The same chain of arguments holds for increasing and decreasing the threshold ϵ in the h definition by ±0.05 K. With ϵ = 0.25 K instead of 0.2 K (case 'h.eps = 0.25'), h increases by 31 m and, through the larger Δθ v , decreases E and M by about 3.3 mm s −1 . Owing to the presence of a thin transition layer 22 , the response to ϵ ± 0.05 K is nonlinear and a reduction of ϵ to 0.15 K ('h.eps = 0.15') leads to a disproportionately smaller Δθ v and roughly 6 mm s −1 larger E and M. The 35 m shallower mean h with ϵ = 0.15 K also strongly increases σ E , which increases the correlation between E and M at the expense of a decreased correlation between the unaffected W and M (Extended Data Fig. 2c).…”

Non-precipitating shallow cumulus convection is intrinsically unstable to length-scale growth

“…The first mode spans the so-called transition layer, which we loosely interpret as the layer where q t is no-longer well-mixed, while θ lv is. Observations both old (Augstein et al, 1973) and very recent (Albright et al, 2022a) 16: Development of the vertical relation between θ lv and q t over four time samples, superimposed by their tendency at the last point in time, at several altitudes. Circles indicate the inversion base, squares the cloud base, and triangles cloup top, as they vary with time.…”