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The Great Plains (GP) low-level jet (GPLLJ) contributes to GP warm season water resources (precipitation), wind resources, and severe weather outbreaks. Past research has shown that synoptic and local mesoscale physical mechanisms (Holton and Blackadar mechanisms) are required to explain GPLLJ variability. Although soil moisture–PBL interactions are central to local mechanistic theories, the diurnal effect of regional soil moisture anomalies on GPLLJ speed, northward penetration, and propensity for severe weather is not well known. In this study, two 31-member WRF-ARW stochastic kinetic energy backscatter scheme ensembles simulate a typical warm season GPLLJ case under CONUS-wide wet and dry soil moisture scenarios. In the GP (24°–48°N, 103°–90°W), ensemble mean differences in sensible heating and PBL height of 25–150 W m −2 and 100–700 m, respectively, at 2100 UTC (afternoon) culminate in GPLLJ 850-hPa wind speed differences of 1–4 m s −1 12 hours later (0900 UTC; early morning). Greater heat accumulation in the daytime PBL over dry soil impacts the east–west geopotential height gradient in the GP (synoptic conditions and Holton mechanism) resulting in a deeper thermal low in the northern GP, causing increases in the geostrophic wind. Enhanced daytime turbulent mixing over dry soil impacts the PBL structure (Blackadar mechanism), leading to increased ageostrophic wind. Overnight geostrophic and ageostrophic winds constructively interact, leading to a faster nocturnal GPLLJ over dry soil. Ensemble differences in CIN (~50–150 J kg −1 ) and CAPE (~500–1000 J kg −1 ) have implications for severe weather predictability.
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Assimilation of Satellite-Derived Soil Moisture for Improved Forecasts of the Great Plains Low-Level Jet
Abstract In the context of forecasting societally impactful Great Plains low-level jets (GPLLJs), the potential added value of satellite soil moisture (SM) data assimilation (DA) is high. GPLLJs are both sensitive to regional soil moisture gradients and frequent drivers of severe weather, including mesoscale convective systems. An untested hypothesis is that SM DA is more effective in forecasts of weakly synoptically forced, or uncoupled GPLLJs, than in forecasts of cyclone-induced coupled GPLLJs. Using the NASA Unified Weather Research and Forecasting (NU-WRF) Model, 75 GPLLJs are simulated at 9-km resolution both with and without NASA Soil Moisture Active Passive SM DA. Differences in modeled SM, surface sensible (SH) and latent heat (LH) fluxes, 2-m temperature (T2), 2-m humidity (Q2), PBL height (PBLH), and 850-hPa wind speed (W850) are quantified for individual jets and jet-type event subsets over the south-central Great Plains, as well as separately for each GPLLJ sector (entrance, core, and exit). At the GPLLJ core, DA-related changes of up to 5.4 kg m −2 in SM can result in T2, Q2, LH, SH, PBLH, and W850 differences of 0.68°C, 0.71 g kg −2 , 59.9 W m −2 , 52.4 W m −2 , 240 m, and 4 m s −1 , respectively. W850 differences focus along the jet axis and tend to increase from south to north. Jet-type differences are most evident at the GPLLJ exit where DA increases and decreases W850 in uncoupled and coupled GPLLJs, respectively. Data assimilation marginally reduces negative wind speed bias for all jets, but the correction is greater for uncoupled GPLLJs, as hypothesized.
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- Award ID(s):
- 1638936
- PAR ID:
- 10216768
- Date Published:
- Journal Name:
- Monthly Weather Review
- Volume:
- 148
- Issue:
- 11
- ISSN:
- 0027-0644
- Page Range / eLocation ID:
- 4607 to 4627
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1175/MWR-D-20-0185.1
