Land–Atmosphere Coupling at the Southern Great Plains Atmospheric Radiation Measurement (ARM) Field Site and Its Role in Anomalous Afternoon Peak Precipitation

Abstract

The multimodel Global Land-Atmosphere Coupling Experiment (GLACE) identified the semiarid Southern Great Plains (SGP) as a hotspot for land-atmosphere (LA) coupling and, consequently, landderived temperature and precipitation predictability. The area including and surrounding the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) SGP Climate Research Facility has in particular been well studied in the context of LA coupling. Observation-based studies suggest a coupling signal that is much weaker than modeled, if not elusive. Using North American Regional Reanalysis and North American Land Data Assimilation System data, this study provides a 36-yr (1979-2014) climatology of coupling for ARM-SGP that 1) unifies prior interdisciplinary efforts and 2) isolates the origin of the (weak) coupling signal. Specifically, the climatology of a prominent convective triggering potential-low-level humidity index (CTP-HI low ) coupling classification is linked to corresponding synoptic-mesoscale weather and atmospheric moisture budget analyses. The CTP-HI low classification defines a dry-advantage regime for which convective triggering is preferentially favored over drier-than-average soils as well as a wet-advantage regime for which convective triggering is preferentially favored over wetter-than-average soils. This study shows that wet-advantage days are a result of horizontal moisture flux convergence over the region, and conversely, dryadvantage days are a result of zonal and vertical moisture flux divergence. In this context, the role of the land is nominal relative to that of atmospheric forcing. Surface flux partitioning, however, can play an important role in modulating diurnal precipitation cycle phase and amplitude and it is shown that soil moisture and sensible heat flux are significantly correlated with both occurrence and intensity of afternoon peak precipitation.

Does Soil Moisture Affect Warm Season Precipitation Over the Southern Great Plains?

“…Numerous other studies also found no evidence of significant coupling between soil moisture and precipitation over the SGP (Findell et al, ; Phillips & Klein, ; Taylor et al, ). Song et al () indicated a weak positive correlation between SM and peak afternoon precipitation for both “dry‐coupling” and “wet‐coupling” regimes.…”

“…Song et al () found that wet‐coupling days are preceded by an increase in horizontal moisture convergence over the SGP. Wet‐coupling days are characterized by an enhancement of convective initiation likelihood by wetter soils and PBLs with higher relative humidity.…”

“…Tuttle and Salvucci (2016) found that the correlation between precipitation triggering and soil moisture over the U.S. is generally positive in western regions and negative in the east (with no statistically significant feedback over the SGP on seasonal timescales). Numerous recent studies have also addressed the SM-P relationship over the SGP, some of which indicated that coupling is either very weakly positive (Song et al, 2016), negligible (Phillips & Klein, 2014), or dependent on low level jet (Ford et al, 2015a). A comprehensive review of various process-level and statistical metrics utilized to diagnose SM-P and land-atmosphere coupling is presented in Santanello et al (2017).…”

Land–Atmosphere Interactions: The LoCo Perspective

“…As with CoMeT, this is a community resource that can expand to accommodate 448 new metrics, and user input is welcome. L-A coupling strength, in the midst of internal variability (e.g., Song et al 2016, Ford et al 2015, 494 Berg et al 2017. This evolution coincides with, and contributes to, the evolution of Earth…”

Using ARM Observations to Evaluate Climate Model Simulations of Land‐Atmosphere Coupling on the U.S. Southern Great Plains

“…As with free‐running modeling experiments, reanalyses offer an opportunity to study LAC at continental to global scales, but with simulations that are steadily updated by assimilating available observations. Examples of this approach include work by Ruiz‐Barradas and Nigam (), Luo et al (), Wei and Dirmeyer (, ), Findell et al (), Song et al (), and Santanello et al (). In some instances also, LAC in several different reanalyses was compared with that in global or regional models (e.g., Liu et al, ; Zeng et al, ).…”