Homogeneous soil moisture fields suppress Sahelian MCS frequency

TL;DR

This study addresses how the scale of soil moisture variability controls mesoscale convective systems (MCSs) in the Sahel. Using 78 high-resolution, convection-permitting simulations with scale-filtered soil moisture fields, the authors compare a homogeneous-SM state (SM_LargeOnly) to a partially heterogeneous state (SM_Large+Small). They find that homogenising SM below ~1000 km reduces peak MCS counts by about 23%, driven by the loss of mesoscale dry patches that foster boundary-layer deepening and convergence; reintroducing small-scale SM variability lessens this drop to ~13%. Wet patches suppress favorable convective environments, while insolation in cloud-free slots can substitute for dry SM as a driver of favorable conditions when SM is uniform, with implications for predictability and the representation of land–atmosphere interactions in Sahel rainfall forecasting.

Abstract

Understanding controls on Mesoscale Convective Systems (MCSs) is critical for predicting rainfall extremes across scales. Spatial variability of soil moisture (SM) presents such a control, with ~200km dry patches in the Sahel observed to intensify mature MCSs. Here we test MCS sensitivity to spatial scales of surface heterogeneity using a framework of 78 Unified Model experiments initialised from scale-filtered SM. We demonstrate the control of SM heterogeneity on MCS populations, and the mechanistic chain via which spatial variability propagates through surface fluxes to convective boundary layer development and storm environments. When all sub-synoptic SM variability is homogenised, peak MCS counts drop by 23%, whereas maintaining small-scale variability maintains primary initiation rates, reducing the drop in MCS totals. In sensitivity experiments, boundary layer development prior to MCSs is similar to that over mesoscale dry SM anomalies, but driven by cloud-free slots of increased shortwave radiation. This reduces storm numbers and potential predictability.

Figures (4)

• Figure 1: (a-c) Representative 06UTC surface-layer SM content for each simulation; boxes show Sahel domain. (d-f) Composite evolution about MesoDRY locations of difference between Control and SM(Large+Small) (d) sensible heat flux and 925hPa temperature; (e) PBL height and 925hPa divergence; and (f) TCW and 925hPa humidity. Control mean ITD (bold 925hPa 13$^\circ$C dewpoint contour) shown in (e). (g-i) Area--averaged evolution of same field differences about MesoDRY and MesoWET locations, also with (g) SM and (h) 925hPa meridional wind. All averages taken over 150km slices.
• Figure 2: (a) Hourly total counts of tracked Sahel MCS snapshots (solid lines) and regional mean rainfall (dashed) across all 39 members of each simulation. (b) Mean MCS snapshot areas (solid) and minimum $T_b$ (dashed) between 12 UTC D1 and 00 UTC D2. (c) Mean hourly MCS maximum (solid) and total (dashed) rainfall rates over same period.
• Figure 3: Violin and box plots of 1$^\circ$ mean (a) sensible heat flux and (b) 925hPa temperature anomalies; (c) 925hPa divergence; (d) latent heat flux and (e) TCW anomalies; and (f) integrated CAPE. Distributions centred on D1 09UTC MesoDRY/WET and 17UTC MCS core locations, with sensitivity experiment MCS (MCS$_{\rm Exp}$) conditions aggregated from both experiments. All 12UTC fields unless stated otherwise , legend specifies sample sizes. SM patches sampled in Control, horizontal red lines show MesoDRY means.
• Figure 4: (a-c) Zonal sections, for each simulation, of composite mean 09--12UTC flux anomalies at D2 locations of 17UTC Sahel MCS cores ; titles specify sample sizes. (d-f) Composite Hovmoellers of evolution prior to Control D2 core locations of anomalous (d) shortwave radiation and total cloud cover (TCC); (e) PBL height and 925hPa temperature; and (f) 925hPa humidity and equivalent potential temperature ($\theta_e$). (g-i) Repeated for SM(Large+Small) D2. 150km longitudinal slices used throughout ; vertical lines denote start of D2.