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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Abstract Low-level jets (LLJ) around the world critically support the food, water, and energy security in regions that they traverse. For the purposes of development planning and weather and climate prediction, it is important to improve understanding of how LLJs interact with the land surface and upper-atmospheric flow, and collectively, how LLJs have and may change over time. This study details the development and application of a new automated, dynamical objective classification of upper-atmospheric jet stream coupling based on a merging of the Bonner–Whiteman vertical wind shear classification and the finite-amplitude local wave activity diagnostic. The classification approach is transferable globally, but applied here only for the Great Plains (GP) LLJ (GPLLJ). The analysis spans the period from 1901 to 2010, enabled by the ECMWF climate-quality, coupled Earth reanalysis of the twentieth century. Overall, statistically significant declines in total GPLLJ event frequency over the twentieth century are detected across the entire GP corridor and attributed to declines in uncoupled GPLLJ frequency. Composites of lower- and upper-atmospheric flow are shown to capture major differences in the climatological, coupled GPLLJ, and uncoupled GPLLJ synoptic environments. Detailed analyses for southern, central, and northern GP subregions further highlight synoptic differences between weak and strong GPLLJs and provide quantification of correlations between total, coupled, and uncoupled GPLLJ frequencies and relevant atmospheric anomalies. Because uncoupled GPLLJs tend to be associated with decreased precipitation and low-level wind speed and enhanced U.S. ridge strength, this finding may suggest that support for drought over the twentieth century has waned.
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null (Ed.)Abstract The Great Plains (GP) southerly nocturnal low-level jet (GPLLJ) is a dominant contributor to the region’s warm-season (May–September) mean and extreme precipitation, wind energy generation, and severe weather outbreaks—including mesoscale convective systems. The spatiotemporal structure, variability, and impact of individual GPLLJ events are closely related to their degree of upper-level synoptic coupling, which varies from strong coupling in synoptic trough–ridge environments to weak coupling in quiescent, synoptic ridge environments. Here, we apply an objective dynamic classification of GPLLJ upper-level coupling and fully characterize strongly coupled (C) and relatively uncoupled (UC) GPLLJs from the perspective of the ground-based observer. Through composite analyses of C and UC GPLLJ event samples taken from the European Centre for Medium-Range Weather Forecasts’ Coupled Earth Reanalysis of the twentieth century (CERA-20C), we address how the frequency of these jet types, as well as their inherent weather- and climate-relevant characteristics—including wind speed, direction, and shear; atmospheric stability; and precipitation—vary on diurnal and monthly time scales across the southern, central, and northern subregions of the GP. It is shown that C and UC GPLLJ events have similar diurnal phasing, but the diurnal amplitude is much greater for UC GPLLJs. C GPLLJs tend to have a faster and more elevated jet nose, less low-level wind shear, and enhanced CAPE and precipitation. UC GPLLJs undergo a larger inertial oscillation (Blackadar mechanism) for all subregions, and C GPLLJs have greater geostrophic forcing (Holton mechanism) in the southern and northern GP. The results underscore the need to differentiate between C and UC GPLLJs in future seasonal forecast and climate prediction activities.more » « less
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Abstract The U.S. Great Plains warm season climate is inextricably linked to the frequency and structure of the region's southerly low‐level jet. In the present‐day climate (1977–2009), low‐level jets are shown to occur on 26%, 46%, and 62% of May–September days in the northern (NGP), central (CGP) and southern (SGP) Great Plains, respectively, and account for at least 26%, 25%, and 36% of those region's precipitation during the same period. A shortcoming of previous research has been a failure to treat upper‐level dynamically coupled, or cyclone‐induced jets, separately from jets that are relatively uncoupled from synoptic flow. Differentiating between jet types is essential to proper mechanistic diagnosis and attribution of jet‐related wind, precipitation, and temperature changes to their local land or remote oceanic forcing. Using a new CERA‐20C objective dynamical jet classification dataset, this study achieves the first quantitative assessment of changes in coupled and uncoupled jets between 1901 and 2010 for NGP, CGP, and SGP. Declines in warm season jet frequency are pinpointed to July–September jets. In the NGP and CGP, both jet types have undergone significant increases in speed and height with concomitant decreases in CAPE and precipitation. NGP uncoupled jet and CGP coupled jet precipitation has decreased by 0.5 and 0.8 mm day−1, respectively, which accounts for 41%–44% of total May–September precipitation decreases between 1905–1937 and 1977–2009. A dynamic situation in which synoptic and local soil moisture changes drive opposite jet responses is discussed.
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null (Ed.)Abstract Soil moisture (SM) and evapotranspiration (ET) are key variables of the terrestrial water cycle with a strong relationship. This study examines remotely sensed soil moisture and evapotranspiration data assimilation (DA) with the aim of improving drought monitoring. Although numerous efforts have gone into assimilating satellite soil moisture observations into land surface models to improve their predictive skills, little attention has been given to the combined use of soil moisture and evapotranspiration to better characterize hydrologic fluxes. In this study, we assimilate two remotely sensed datasets, namely, Soil Moisture Operational Product System (SMOPS) and MODIS evapotranspiration (MODIS16 ET), at 1-km spatial resolution, into the VIC land surface model by means of an evolutionary particle filter method. To achieve this, a fully parallelized framework based on model and domain decomposition using a parallel divide-and-conquer algorithm was implemented. The findings show improvement in soil moisture predictions by multivariate assimilation of both ET and SM as compared to univariate scenarios. In addition, monthly and weekly drought maps are produced using the updated root-zone soil moisture percentiles over the Apalachicola–Chattahoochee–Flint basin in the southeastern United States. The model-based estimates are then compared against the corresponding U.S. Drought Monitor (USDM) archive maps. The results are consistent with the USDM maps during the winter and spring season considering the drought extents; however, the drought severity was found to be slightly higher according to DA method. Comparing different assimilation scenarios showed that ET assimilation results in wetter conditions comparing to open-loop and univariate SM DA. The multivariate DA then combines the effects of the two variables and provides an in-between condition.more » « less
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1175/MWR-D-20-0185.1
