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The rapid change of wind speed and direction on 21 August 2017 is studied using Doppler lidar measurements at five sites of the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) facility in north-central Oklahoma. The Doppler lidar data were investigated along with meteorological variables such as temperature, humidity, and turbulence available from the large suite of instrumentation deployed at the SGP Central Facility (C1) during the Land-Atmosphere Feedback Experiment in August 2017. Lidar measurements at five sites, separated by 55–70 km, allowed us to document the development and evolution of the wind flow over the SGP area, examine synoptic conditions to understand the mechanism that leads to the ramp event, and estimate the ability of the High-Resolution Rapid Refresh model to reproduce this event. The flow feature in question is an atmospheric bore, a small-scale phenomenon that is challenging to represent in models, that was generated by a thunderstorm outflow northwest of the ARM SGP area. The small-scale nature of bores, its impact on power generation, and the modeling challenges associated with representing bores are discussed in this paper. The results also provide information about model errors between sites of different surface and vegetation types. [ABSTRACT FROM AUTHOR]

Low-level jets (LLJs) are an important nocturnal source of wind energy in the U.S. Great Plains. An August 2017 lidar-based field-measurement campaign [the Land--Atmosphere Feedback Experiment (LAFE)] studied LLJs over the central SGP site in Oklahoma and found nearly equal occurrences of the usual southerly jets and postfrontal northeasterly jets--typically rare during this season--for an opportunity to compare the two types of LLJs during this month. Southerly winds were stronger than the northeasterlies by more than 4 m ss-1 on average, reflecting a significantly higher frequency of winds stronger than 12 m s-1. The analysis of this dataset has been expanded to other SGP Dopplerlidar sites to quantify the variability of winds and LLJ properties between sites of different land use. Geographic variations of winds over the study area were noted: on southerly wind nights, the winds blew stronger at the highest, westernmost sites by 2 m s-1, whereas on the northeasterly flow nights, the easternmost sites had the strongest wind speeds. Lidar measurements at 5 sites during August 2017, contrasted to the 2016-21 summertime data, revealed unusual wind and LLJ conditions. Temporal hodographs using hourly averaged winds at multiple heights revealed unorganized behavior in the turbulent stable boundary layer (SBL) below the jet nose. Above the nose, some nights showed veering qualitatively similar to inertial oscillation (IO) behavior, but at amplitudes much smaller than expected for an IO, whereas other nights showed little veering. Vertical hodographs had a linear shape in the SBL, indicating little directional shear there, and veering above, resulting in a hook-shaped hodograph with height. [ABSTRACT FROM AUTHOR]

Low-powered commercially available coherent Doppler lidar (CDL) wind profilers provide continuous measurement of vertical profiles of wind in the lower troposphere, usually close to or up to the top of the planetary boundary layer. The vertical extent of these wind profiles is limited by the availability of scatterers and thus varies substantially throughout the day and from one day to the next. This makes it challenging to develop continuous products that rely on CDL-observed wind profiles. In order to overcome this problem, we have developed a new method for wind profile retrievals from CDL that combines the traditional velocity-azimuth display (VAD) technique with optimal estimation (OE) to provide continuous wind profiles up to 3 km. The new method exploits the level-to-level covariance present in the wind profile to fill in the gaps where the signal-to-noise ratio of the CDL return is too low to provide reliable results using the traditional VAD method. Another advantage of the new method is that it provides the full error covariance matrix of the solution and profiles of information content, which more easily facilitates the assimilation of the observed wind profiles into numerical weather prediction models. This method was tested using yearlong CDL measurements at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) Central Facility in 2019. Comparison with the ARM operational CDL wind profile product and collocated radiosonde wind measurements shows excellent agreement (R2>0.99) with no degradation in results where the traditional VAD provided a valid solution. In the region where traditional VAD does not provide results, the OE wind speed and wind vector have uncertainties of 3.44 and 4.33 m s -1 , respectively. As a result, the new method provides additional information over the standard technique and increases the effective range of existing CDL systems without the need for additional hardware. [ABSTRACT FROM AUTHOR]

Low-powered commercially-available coherent Doppler lidar (CDL) provides continuous measurement of vertical profiles of wind in the lower troposphere, usually close to or up to the top of the planetary boundary layer. The vertical extent of these wind profiles is limited by the availability of scatterers, and thus varies substantially throughout the day and from one day to the next. This makes it challenging to develop continuous products that rely on CDL-observed wind profiles. In order to overcome this problem, we have developed a new method for wind profile retrievals from CDL that combines the traditional velocity-azimuth display (VAD) technique with optimal estimation (OE) to provide continuous wind profiles up to 3 km. The new method exploits the level-to-level covariance present in the wind profile to fill in the gaps where the signal to noise ratio of the CDL return is too low to provide reliable results using the traditional VAD method. Another advantage of the new method is that it provides the full error covariance matrix of the solution and profiles of information content, which more easily facilitates the assimilation of the observed wind profiles into numerical weather prediction models. This method was tested using CDL measurements at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) Central Facility. Comparison with the ARM operational CDL wind profile product and collocated radiosonde wind measurements shows excellent agreement (R² > 0.99) with no degradation in results where the traditional VAD provided a valid solution. In the region where traditional VAD do not provide results, the OE wind speed has uncertainty of 4.5 m/s. As a result, the new method provides additional information over the standard technique and increases the effective range of existing CDL systems without the need for additional hardware. [ABSTRACT FROM AUTHOR]

Previous studies of the low-level jet (LLJ) over the central Great Plains of the United States have been unable to determine the role that mesoscale and smaller circulations play in the transport of moisture. To address this issue, two aircraft missions during the International H2O Project (IHOP_2002) were designed to observe closely a well-developed LLJ over the Great Plains (primarily Oklahoma and Kansas) with multiple observation platforms. In addition to standard operational platforms (most important, radiosondes and profilers) to provide the large-scale setting, dropsondes released from the aircraft at 55-km intervals and a pair of onboard lidar instruments—High Resolution Doppler Lidar (HRDL) for wind and differential absorption lidar (DIAL) for moisture—observed the moisture transport in the LLJ at greater resolution. Using these observations, the authors describe the multiscalar structure of the LLJ and then focus attention on the bulk properties and effects of scales of motion by computing moisture fluxes through cross sections that bracket the LLJ. From these computations, the Reynolds averages within the cross sections can be computed. This allow an estimate to be made of the bulk effect of integrated estimates of the contribution of small-scale (mesoscale to convective scale) circulations to the overall transport. The performance of the Weather Research and Forecasting (WRF) Model in forecasting the intensity and evolution of the LLJ for this case is briefly examined. [ABSTRACT FROM AUTHOR]