On the assessment of the moisture transport by the Great Plains low-level jet

Abstract

Low-level jets (LLJs) can be defined as wind corridors of anomalously high wind speed values located within the first kilometre of the troposphere. These structures are one of the major meteorological systems in the meridional transport of moisture on a global scale. In this work, we focus on the southerly Great Plains low-level jet, which plays an important role in the moisture transport balance over the central United States. The Gulf of Mexico is the main moisture source for the Great Plains low-level jet (GPLLJ), which has been identified as a key factor for rainfall modulation over the eastern and central US.

The relationship between moisture transport from the Gulf of Mexico to the Great Plains and precipitation has been well documented in previous studies. Nevertheless, a large uncertainty still remains in the quantification of the moisture amount actually carried by the GPLLJ. The main goal of this work is to address this question. For this purpose, a relatively new tool, the regional atmospheric Weather Research and Forecasting Model with 3-D water vapour tracers (WRF-WVT; Insua-Costa and Miguez-Macho, 2018) is used together with the Lagrangian model FLEXPART to estimate the load of precipitable water advected within the GPLLJ. Both models were fed with data from ERA Interim. From a climatology of jet intensity over a 37-year period, which follows a Gaussian distribution, we select five cases for study, representing the mean and 1 and 2 standard deviations above and below it. Results show that the jet is responsible for roughly 70 %–80 % of the moisture transport occurring in the southern Great Plains when a jet event occurs. Furthermore, moisture transport by the GPLLJ extends to the north-east US, accounting for 50 % of the total in areas near the Great Lakes. Vertical distributions show the maximum of moisture advected by the GPLLJ at surface levels and maximum values of moisture flux about 500 m above, in coincidence with the wind speed profile.