The 2019 Mississippi and Missouri River Flooding and Its Impact on Atmospheric Boundary Layer Dynamics

Abstract

In spring 2019, a catastrophic flood occurred along the Missouri and Mississippi River basins in the United States, which was characterized as the longest lasting flood since the Great Flood of 1927. The 2019 flooding resulted in extremely wet soils for 3–4 months over the Great Plains. Using rawinsonde‐derived atmospheric boundary layer depths (BLDs) and in situ soil moisture (SM) data sets at 10 sites located meridionally across the two river‐valleys, we investigated the SM controls on regional‐scale BLDs during spring 2019. The impact of spring flooding on atmospheric boundary layer dynamics is reported via regression analyses between daily SM and BLDs yielding statistically significant negative r (p < 0.0012) with substantial spatial variability (r: −0.25 to −0.70). Results suggest (1) the strengthening of the negative SM‐BLD relationship in the wake of extreme flooding and (2) positive SM anomalies of 0.05–0.12 m3 m−3 resulted in negative BLD anomalies (−100 to −400 m) compared to 8‐year means, confirming the impact of perturbed land atmosphere feedback processes (LAFP). These results offer a test bed for developing better numerical models with advanced representations of LAFP.

The Impact of Height-Independent Errors in State Variables on the Determination of the Daytime Atmospheric Boundary Layer Depth Using the Bulk Richardson Approach

“…Knowledge of the potential impacts of errors in these fields is especially important for highly sheared ABLs (e.g., Conzemius and Fedorovich 2006;Fedorovich and Conzemius 2008;Liu et al 2018). Additionally, it has been found that frontal environments pose additional challenges characterizing BLD variability when temperature, moisture and wind change drastically before and after frontal passages (e.g., Boulte et al 2010;Clark et al 2020). We found nontrivial BLD errors across all stations when introducing perturbations to the u and y wind components as compared with the thermodynamic quantities.…”

“…For example, shallow and deep BLDs can occur both in the cold and warm seasons (e.g., Liu and Liang 2010;Seidel et al 2012;Lee and Pal 2017), spatial BLD variability exists for terrain-following versus terrainindependent ABL regimes (e.g., Kalthoff et al 1998;Kossmann et al 1998;Lee and De Wekker 2016;Pal et al 2016), and both shallow and deep BLD regimes can be present during the early-morning (e.g., Lenschow et al 1979) and early-evening (e.g., Acevedo and Fitzjarrald 2001) transition periods. Furthermore, there are different ABL regimes in which deep versus shallow BLDs prevail, i.e., stable ABLs versus convective ABLs (e.g., Stull 1988), sheared versus nonsheared ABLs (e.g., Fedorovich and Conzemius 2008), cloud-topped versus cloud-free ABLs (e.g., Garratt 1994), moist ABLs versus entrainment-drying ABLs (e.g., Stull 1988), quasi-stationary versus growing ABLs (e.g., Pal and Haeffelin 2015;Muppa et al 2016), ABLs over land versus ABLs over water (e.g., Garratt 1994), and rural versus urban ABLs (e.g., Pal et al 2012).…”

“…In future work, similar sensitivity analyses as those presented in the present study should be applied to other approaches that can be used for determining BLDs from rawinsondes (e.g., the parcel method, height of the elevated inversion), as well as from other surface-based and remote sensing instruments (water vapor and temperature lidars, microwave radiometers) used to determine the BLD (e.g., Behrendt et al 2005;Cimini et al 2013;Dupont et al 2020). Other future research avenues include the exploration of BLD errors for 1) different atmospheric stability regimes, 2) seasonal changes in surface forcing, 3) complex ABL regimes (e.g., coastal regions, complex terrain, interface of urban-rural regions), and 4) diverse advection regimes (e.g., Pal and Lee 2019a,b;Pal et al 2020).…”

Contrasting Effect of Soil Moisture on the Daytime Boundary Layer Under Different Thermodynamic Conditions in Summer Over China

“…In particular, reduced SM (i.e., dry soil) was closely linked to less surface evaporation, which allowed for more transfer of sensible heat flux (SHF), thereby promoting the growth of PBL (Guo et al., 2019; Mccumber & Pielke, 1981; Pal & Haeffelin, 2016; Pan & Mahrt, 1987; Rihani et al., 2015). Conversely, enhanced SM was found to dramatically inhibit the development of PBL in the wake of extreme flooding (Pal et al., 2020).…”

Patterns and drivers of evapotranspiration in South American wetlands

“…Evapotranspiration (ET), a key ux linking surface and atmospheric energy budgets, is also the main consumer of incoming energy and water in wetlands. At the regional landscape level (i.e., the wetlandscape 18 ), the existence of large wet surfaces has the potential to affect the partition of available energy into sensible and latent heat, in uencing not only local temperature and water quality but also the regional atmospheric boundary layer 19 , the vertical transport of heat and water vapor in the atmosphere, and local-to-regional atmospheric circulation [20][21][22] . The river or wetland breeze effect, observed, for instance, in the Central Amazon 23,24 , has been suggested to suppress precipitation over ooded areas and initiate convection over wetland edges 21,25 .…”