Low-level Jet Events Research Articles

A model-based study of the dynamics of Arctic low-level jet events for the MOSAiC drift

Low-level jets (LLJs) are studied for the period of the ship-based experiment MOSAiC 2019/2020 using the regional climate model Consortium for Small-scale Model—Climate Limited area Mode (CCLM). The model domain covers the whole Arctic with 14 km resolution. CCLM is run in a forecast mode (nested in ERA5) and with different configurations of sea ice data for the winter. The focus is on the study of LLJs for the MOSAiC site. LLJs are detected using model output every 1 h. We define LLJ events as LLJs that last at least 6 h. Case studies of LLJ events are shown using wind lidar and radiosonde data as well as CCLM simulations. LLJs are not local events but are embedded in large jet structures extending for hundreds of kilometers that are advected toward the MOSAiC site. CCLM simulations are used to study the statistics of LLJs of all profiles and of LLJ events as well as the dynamics. LLJs are found in about 40% of the hourly profiles, but only 26% of the hourly profiles are associated with LLJ events. Strong LLJs (≥15 m/s) are detected in 13% of the hourly profiles, which is about the same fraction as for strong LLJ events. The mean duration of events is about 12 h. The LLJ events are characterized using dynamical criteria for the wind speed profile and the evolution of the jet core. A fraction of 35% of the LLJ events are baroclinic, but more than 40% of the LLJ events show a large contribution of advection to the initial generation as well as for the evolution of the jet core. Only very few events fulfill the criteria of inertial oscillations. LLJ events occur for all months, but strong events have a higher frequency during winter. The turbulent kinetic energy in the lower atmospheric boundary layer (ABL) is twice (4 times) as large for LLJs (strong LLJs) than for situations without LLJs, which underlines the impact of LLJs on turbulent processes in the ABL.

Offshore low-level jet observations and model representation using lidar buoy data off the California coast

Abstract. Low-level jets (LLJs) occur under a variety of atmospheric conditions and influence the available wind resource for wind energy projects. In 2020, lidar-mounted buoys owned by the US Department of Energy (DOE) were deployed off the California coast in two wind energy lease areas administered by the Bureau of Ocean Energy Management: Humboldt and Morro Bay. The wind profile observations from the lidars and collocated near-surface meteorological stations (4–240 m) provide valuable year-long analyses of offshore LLJ characteristics at heights relevant to wind turbines. At Humboldt, LLJs were associated with flow reversals and north-northeasterly winds, directions that are more aligned with terrain influences than the predominant northerly flow. At Morro Bay, coastal LLJs were observed primarily during northerly flow as opposed to the predominant north-northwesterly flow. LLJs were observed more frequently in colder seasons within the lowest 250 m a.s.l. (above sea level), in contrast with the summertime occurrence of the higher-altitude California coastal jet influenced by the North Pacific High, which typically occurs at heights of 300–400 m. The lidar buoy observations also validate LLJ representation in atmospheric models that estimate potential energy yield of offshore wind farms. The European Centre for Medium-Range Weather Forecasts Reanalysis version 5 (ERA5) was unsuccessful at identifying all observed LLJs at both buoy locations within the lowest 200 m. An extension of the National Renewable Energy Laboratory (NREL) 20-year wind resource dataset for the Outer Continental Shelf off the coast of California (CA20-Ext) yielded marginally greater captures of observed LLJs using the Mellor–Yamada–Nakanishi–Niino (MYNN) planetary boundary layer (PBL) scheme than the 2023 National Offshore Wind dataset (NOW-23), which uses the Yonsei University (YSU) scheme. However, CA20-Ext also produced the most LLJ false alarms, which are instances when a model identified an LLJ but no LLJ was observed. CA20-Ext and NOW-23 exhibited a tendency to overestimate the duration of LLJ events and underestimate LLJ core heights.

Effects of negative shear on loads for a 15 MW offshore wind turbine during low-level jet events

Wind turbines are more often interacting with the negative shear region of a low-level jet due to increasing turbine sizes. However, the effects of negative shear on wind turbines are not sufficiently studied, particularly for offshore wind applications. In this paper, we studied the effects of negative shear on wind turbine loading. This was done using user-defined wind profiles and a model chain. The model chain consisted of a turbulence generator and a wake modelling tool coupled to an aero-hydro-servo-elastic engineering tool. We observed significant variations in the structural loading in the case of low-level jets. We also observed changes in the power spectral density estimates. Additionally, we briefly examined the wake recovery distance.

Regionalisation of heat waves in southern South America

This study describes the climatological characteristics of regional heat waves (HWs) over southern South America (SSA) for the warm seasons (October–March) of 1979–2018 based on daily maximum temperature series from 131 weather stations. Clustering of stations with high co-occurrence of simultaneous HW days is employed to identify regional HW events over five homogeneous regions: northern, central-eastern and southern SSA regions, central Argentina, and central Chile. When all regions are considered, we find a mean frequency of ∼4 HWs per year. Transitional regions (northern SSA, central-eastern SSA and central Argentina) are characterised by longer, albeit less intense, HWs than the southernmost region (southern SSA), whereas central Chile events display the lowest duration, intensity and extension. By aggregating these single HW attributes into a combined severity index, a ranking of historical HWs has been obtained, with the March 1980 event standing as the most severe one of SSA. The assessment of long-term changes reveals significant increases in the frequency of regional HW days over central Argentina and central Chile only. Trends in HW characteristics are also region dependent, and the southernmost region is the only one where HW severity has increased significantly.We report similarities and differences in the synoptic circulation patterns associated with regional HW events. Southern SSA HWs have the most distinctive signatures, related to extratropical high-pressure systems blocking the westerly flow. In the remaining regions, HWs are associated with anomalies in the South Atlantic (northern SSA, central-eastern SSA and central Argentina) or South Pacific (central Chile) High, and the intensification of the northerly low-level flow by regional thermal lows and South American Low Level Jet events. Regional HWs often migrate from northern to central-eastern SSA and central Argentina, following the displacement/intensification of the South Atlantic High, which partially explains the similarity of their associated patterns.

Effects of atmospheric low-level jets on the mixing process of a large tropical reservoir.

Changes in the physical and biogeochemical properties of water columns are frequently associated with cold fronts and mesoscale convective systems due to increased cloud cover. The effects of low-level jet (LLJ) events on thermal stratification and water quality, however, remain undescribed, particularly for tropical reservoirs. Here, water temperature time series are combined with meteorological data, LIDAR observations, ERA5 reanalysis data, and hydrodynamical modeling to investigate the impact of an event of LLJ over the Furnas hydropower reservoir in Brazil. The LLJ event was characterized by dry, intense, and persistent winds (~10 m s-1) blowing for more than 12 hours over the main fetch of the reservoir. In the downwind side of the lake, the surface mixed layer depth increased by 50% during the LLJ event. The changes to the water column were produced by a combination of wind-induced upwelling, shear-driven mixing, and nocturnal convective overturning, different from the heat balance expected during passing cold fronts and mesoscale convective systems. The results suggest that both momentum and heat fluxes during LLJ events need to be accounted for in lake modelings to reproduce the vertical mixing process.

Evaluation of low-level jets in the southern Baltic Sea: a comparison between ship-based lidar observational data and numerical models

Abstract. In contrast to fixed measuring devices, ship-based lidar systems provide highly reliable wind observations within extensive regions. Therefore, this kind of reference dataset provides a great potential for evaluating the performance of mesoscale numerical models in resembling mesoscale flow phenomena such as low-level jets – essential for an optimal development and operation of wind turbines. This paper presents a comparison between numerical output data from two state-of-the-art numerical datasets (ERA5 and NEWA) and the ship-mounted lidar measurements from the NEWA Ferry Lidar Experiment. The comparison was performed along the route covered by the vessel, as well as in specific locations within this route, to better understand the capabilities and limitations of the numerical models to precisely resemble the occurrence and main properties of low-level jets (LLJs) in different locations. The findings of this study show that the non-stationary nature of ship-based lidar measurements allows evaluating the accuracy of the models when retrieving jets' characteristics and occurrence under different temporal and spatial effects. Numerical models underestimate the occurrence of LLJs, and they struggle to accurately describe their main characteristics, with a particularly large underestimation of the falloff. The found results are to be seen in relation to the characteristics of the observations, such as the data availability, the time–position relation of the selected vessel's route, or the profile height limitation, as well as the features of the jets, with a particular relevance of core height and falloff. Additionally, the results illustrate the temporal and spatial shift between the LLJ events detected by the measurements and the models and the potential benefit of considering such deviations when studying LLJs' climatology through numerical modes.

Observational Investigation of the Low‐Level Jets in the Metropolitan Region of São Paulo, Brazil

AbstractThe main features of low‐level jet (LLJ) in the metropolitan region of São Paulo (MRSP), Brazil, are assessed using rawinsondes carried out: (a) every 3‐hr during 10‐consecutive days in summer and winter field campaigns of the MCITY BRAZIL Project in 2013, (b) at 0900 and 2100 local time, from September 2009 to August 2013. These observations indicate that the LLJ is a typical feature of the MRSP, observed in 85% of the 20 days of the field‐campaigns and 77.6% of the 1,446 days of regular rawinsonde period. The fine temporal and spatial resolution soundings indicate that most of the LLJs occur during nighttime and early in the morning, with mean intensity of 8.5 ± 0.3 m s−1, height of 539 ± 26 m, and mostly (52.5%) from east and north. The coarse resolution soundings indicate the LLJ display a seasonal variation with maximum intensity in October (8.6 ± 0.3 m s−1) and a minimum in February (7.1 ± 0.2 m s−1), a maximum height in March (703 ± 151 m) and a minimum in June (577 ± 151 m). During MCITY campaigns about 76.4% of LLJ events show inertial oscillation and 35.3% of them are combined with sea breeze. Only 17.6% of LLJ events are associated with cold fronts and post‐frontal high pressure system. The urban heat island intensity, surface inversion layer strength, particulate matter 2.5 and carbon monoxide concentrations are negatively correlated with the LLJ intensity, suggesting the jet‐induced turbulent mixing may contribute to reduce them.

Evaluation of a forest parameterization to improve boundary layer flow simulations over complex terrain. A case study using WRF-LES V4.0.1

Abstract. We evaluate the influence of a forest parametrization on the simulation of the boundary layer flow over moderate complex terrain in the context of the Perdigão 2017 field campaign. The numerical simulations are performed using the Weather Research and Forecasting model in large eddy simulation mode (WRF-LES). The short-term, high-resolution (40 m horizontal grid spacing) and long-term (200 m horizontal grid spacing) WRF-LES are evaluated for an integration time of 12 h and 1.5 months, respectively, with and without forest parameterization. The short-term simulations focus on low-level jet events over the valley, while the long-term simulations cover the whole intensive observation period (IOP) of the field campaign. The results are validated using lidar and meteorological tower observations. The mean diurnal cycle during the IOP shows a significant improvement of the along-valley wind speed and the wind direction when using the forest parametrization. However, the drag imposed by the parametrization results in an underestimation of the cross-valley wind speed, which can be attributed to a poor representation of the land surface characteristics. The evaluation of the high-resolution WRF-LES shows a positive influence of the forest parametrization on the simulated winds in the first 500 m above the surface.

Wind Lidar and Radiosonde Measurements of Low-Level Jets in Coastal Areas of the German Bight

For wind energy, the knowledge of the available wind resource is essential. Therefore, specific wind phenomena at the altitude range of wind turbines are currently the focus of investigations. One such specific feature is the low-level jet (LLJ). The article analyses LLJ properties at two locations in the German Bight: A wind lidar system for measuring wind profiles at heights from 50 m to 500 m a.g.l. (above ground level) was first installed at the offshore island of Heligoland, Germany, and then at the coastal island of Norderney, Germany, for one year. The LLJ is defined here as a maximum horizontal wind speed in the vertical profile of horizontal wind speed followed by a minimum wind speed, independent of the mechanism or origin of the phenomenon. The two sites showed a similar annual and diurnal distribution of LLJ events with a maximum occurrence in spring and summer and during the night, and a most frequent jet core height of around 120 m a.g.l. Based on radiosondes launched from Norderney at midnight and noon, it is shown that LLJ events at noon are most frequent when atmospheric conditions are stable. A case study shows the horizontal extent of an LLJ event over at least 100 km by simultaneous wind lidar measurements at four sites in the German Bight and mesoscale simulations with the weather research and forecast (WRF) model.

Predictive Capability of WRF Cycling 3DVAR: LiDAR Assimilation at FINO1

In this study, we assess tentatively the predictive capability of the Weather Research and Forecasting (WRF) model and its Three-Dimensional Variational (3DVAR) system. We study the impact of LiDAR data assimilation on predictions of wind speed and direction. The simulation domain covers the German wind energy research platform FINO1 in the Southern North Sea, at which the LiDAR data were recorded. The results demonstrate the significance of applying the LiDAR Data Assimilation (DA) with a short assimilation interval (1-hour) to improve the wind prediction and the temporal and spatial representation of low level jet events, compared with an experiment without DA. Furthermore, we briefly examine the impacts of data assimilation cycle length on predictive performance of the DA system, and spatial variability of wind speed over the study area at a height of 250 m.

Recent Changes in the Low-Level Jet along the Subtropical West Coast of South America

Surface winds along the subtropical west coast of South America are characterized by the quasi-weekly occurrences of low-level jet events. These short lived but intense wind events impact the coastal ocean environment. Hence, identifying long-term trends in the coastal low-level jet (CLLJ) is essential for understanding changes in marine ecosystems. Here we use ERA5 reanalysis (1979–2019) and an objective algorithm to track anticyclones to investigate recent changes in CLLJ events off central Chile (25–43 °S). Results present evidence that the number of days with intense wind (≥10 ms−1), and the number and duration of CLLJ events have significantly changed off central Chile in recent decades. There is an increase in the number of CLLJ events in the whole study area during winter (June-July-August; JJA), while during summer (December–January–February; DJF) a decrease is observed at lower latitudes (29–34 °S), and an increase is found at the southern boundary of the Humboldt system. We suggest that changes in the central pressures and frequency of extratropical, migratory anticyclones that reach the coast of South America, which force CLLJs, have played an important role in the recent CLLJ changes observed in this region.

Observations of Wintertime Low-Level Jets in the Coastal Region of the Laptev Sea in the Siberian Arctic Using SODAR/RASS

In 2014/2015 a one-year field campaign at the Tiksi observatory in the Laptev Sea area was carried out using Sound Detection and Ranging/Radio Acoustic Sounding System (SODAR/RASS) measurements to investigate the atmospheric boundary layer (ABL) with a focus on low-level jets (LLJ) during the winter season. In addition to SODAR/RASS-derived vertical profiles of temperature, wind speed and direction, a suite of complementary measurements at the Tiksi observatory was available. Data of a regional atmospheric model were used to put the local data into the synoptic context. Two case studies of LLJ events are presented. The statistics of LLJs for six months show that in about 23% of all profiles LLJs were present with a mean jet speed and height of about 7 m/s and 240 m, respectively. In 3.4% of all profiles LLJs exceeding 10 m/s occurred. The main driving mechanism for LLJs seems to be the baroclinicity, since no inertial oscillations were found. LLJs with heights below 200 m are likely influenced by local topography.

Potential Associations between Low-Level Jets and Intraseasonal and Semi-Diurnal Variations in Coastal Chlorophyll—A over the Beibuwan Gulf, South China Sea

Low-level jet (LLJ) significantly affects the synoptic-scale hydrometeorological conditions in the South China Sea, although the impact of LLJs on the marine ecological environment is still unclear. We used multi-satellite observation data and meteorological reanalysis datasets to study the potential impact of LLJs on the marine biophysical environment over the Beibuwan Gulf (BBG) in summer during 2015–2019. In terms of the summer average, the sea surface wind vectors on LLJ days became stronger in the southwesterly direction relative to those on non-LLJ days, resulting in enhanced Ekman pumping (the maximum upwelling exceeds 10 × 10−6 m s−1) in most areas of the BBG, accompanied by stronger photosynthetically active radiation (increased by about 20 μmol m−2 s−1) and less precipitation (decreased by about 3 mm day−1). These LLJ-induced hydrometeorological changes led to an increase of about 0.3 °C in the nearshore sea surface temperature and an increase of 0.1–0.5 mg m−3 (decrease of 0.1–0.3 mg m−3) in the chlorophyll-a (chl-a) concentrations in nearshore (offshore) regions. Intraseasonal and diurnal changes in the incidence and intensity of LLJs potentially resulted in changes in the biophysical ocean environment in nearshore regions on intraseasonal and semi-diurnal timescales. The semi-diurnal peak and amplitude of chl-a concentrations on LLJ days increased with respect to those on non-LLJ days. Relative to the southern BBG, LLJ events exhibit greater impacts on the northern BBG, causing increases of the semi-diurnal peak and amplitude with 1.5 mg m−3 and 0.7 mg m−3, respectively. This work provides scientific evidence for understanding the potential mechanism of synoptic-scale changes in the marine ecological environment in marginal seas with frequent LLJ days.

WRF-Simulated Springtime Low-Level Jets over Iowa: Implications for Wind Energy

High-resolution simulations with the Weather Research and Forecasting (WRF) model are analyzed to characterize the frequency, intensity, height, and duration of springtime low-level jets (LLJ) and their implications for wind energy resource assessment and planning in Iowa. The time evolution of short-duration LLJ is analyzed to understand wind behavior around LLJ events and to illustrate their importance for high-frequency (few hours) variability in wind speeds and rotor plane turbulent kinetic energy (TKE). During spring, the LLJ core height has a spatiotemporal mean value of 217 m, but the LLJ depth means it frequently intersects typical wind turbine rotor planes. Nearly one-quarter of LLJ exhibit a maximum within the height interval 50-150 m AGL. LLJ profiles are found to have higher mean wind speeds across typical wind turbine rotor planes than non-LLJ profiles and to exhibit lower values of TKE. LLJ occur under stable stratification (i.e. positive Richardson numbers) and are associated with low TKE and the occurrence of high vertical wind shear. The frequency and duration of LLJ exhibit geospatial variability across Iowa with highest values in the northeast of the state. Analyses of daytime and night-time LLJ indicate topographic variability is an important factor in the development of LLJ.

How accurate is a machine learning-based wind speed extrapolation under a round-robin approach?

As the size of commercial wind turbines keeps increasing, having accurate ways to vertically extrapolate wind speed is essential to obtain a precise characterization of the wind resource for wind energy production. Recently, machine learning has been proposed and applied to extrapolate wind speed to hub heights. However, previous studies trained and tested the machine learning methods at the same site, giving them an unfair advantage over the conventional extrapolation techniques, which are instead more universal. Here, we use data from four sites in Oklahoma to test a round-robin validation approach for machine learning, under which we train a random forest at a site, and test it at a different site, where the model has no prior knowledge of the wind resource. We quantify how the accuracy of this technique varies with distance from the training site, and we find that it outperforms conventional techniques for wind extrapolation at all the considered spatial separations. We then assess how the accuracy of the machine-learning based approach varies when it is used to predict wind speed in a wind farm far wake. Finally, we explore as case study the performance of the random forest in extrapolating winds during a low-level jet event.

Estimation of turbulence dissipation rate and its variability from sonic anemometer and wind Doppler lidar during the XPIA field campaign

Abstract. Despite turbulence being a fundamental transport process in the boundary layer, the capability of current numerical models to represent it is undermined by the limits of the adopted assumptions, notably that of local equilibrium. Here we leverage the potential of extensive observations in determining the variability in turbulence dissipation rate (ϵ). These observations can provide insights towards the understanding of the scales at which the major assumption of local equilibrium between generation and dissipation of turbulence is invalid. Typically, observations of ϵ require time- and labor-intensive measurements from sonic and/or hot-wire anemometers. We explore the capability of wind Doppler lidars to provide measurements of ϵ. We refine and extend an existing method to accommodate different atmospheric stability conditions. To validate our approach, we estimate ϵ from four wind Doppler lidars during the 3-month XPIA campaign at the Boulder Atmospheric Observatory (Colorado), and we assess the uncertainty of the proposed method by data intercomparison with sonic anemometer measurements of ϵ. Our analysis of this extensive dataset provides understanding of the climatology of turbulence dissipation over the course of the campaign. Further, the variability in ϵ with atmospheric stability, height, and wind speed is also assessed. Finally, we present how ϵ increases as nocturnal turbulence is generated during low-level jet events.

A New Look at the Identification of Low-Level Jets in South America

Abstract Criteria currently employed in algorithms that identify low-level jets (LLJs) in South America utilizing rawinsonde and gridded model data fail to detect an important number of LLJ events. This study discusses shortcomings in the existing approaches for LLJ identification in South America and proposes modifications to the criteria regarding layer depth for LLJ identification and wind direction. Episodes of southerly LLJs, which have received less attention in the La Plata basin, are also included in the investigation. A sensitivity analysis of LLJ detection in South America upon the choice of the criteria applied to a sample period of 15 years (1996–2010) of gridded numerical data from the National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (CFSR), and to a 20-yr dataset (1996–2015) of actual rawinsondes for the La Plata basin, reveals the benefits of revising the criteria. The modified criteria allow for the characterization of a wider spectrum of LLJs over key regions of South America, such as over the Bolivian–Paraguayan border, Sierras de Córdoba in Argentina, and southern-southeastern Brazil. This wider range of events includes elevated LLJs, mostly with strong zonal components, that account for approximately 20% of the full sample of LLJs identified in the rawinsonde dataset investigated here. The revised criteria have the advantage of retaining the identification of episodes that meet the consecrated definition of the South American LLJ, while at the same time providing an augmented sample of such wind systems. Our results provide further insights into the forcing mechanisms of distinct types of LLJs in South America, ranging from topographic to baroclinic effects.

Mixed layer depths via Doppler lidar during low-level jet events

A low-level jet (LLJ) is a prominent wind speed peak in the lower troposphere. Nocturnal LLJs have been shown to transport and mix atmospheric constituents from the residual layer down to the surface, breaching quiescent nocturnal conditions due to high wind shear. A new fuzzy logic algorithm combining turbulence and aerosol information from Doppler lidar scans can resolve the strength and depth of this mixing below the jet. Conclusions will be drawn about LLJ relations to turbulence and mixing.

WRF Forecasts of Great Plains Nocturnal Low-Level Jet-Driven MCSs. Part II: Differences between Strongly and Weakly Forced Low-Level Jet Environments

Abstract The classic Great Plains southerly low-level jet (LLJ) is a primary factor in sustaining nocturnal convection. This study compares convection-allowing WRF forecasts of LLJ events associated with MCSs in strongly and weakly forced synoptic environments. The depth of the LLJs and magnitude, altitude, and times of the LLJ peak wind were evaluated in observations and WRF forecasts for 31 cases as well as for case subsets of strongly and weakly forced synoptic regimes. LLJs in strongly forced regimes were stronger, deeper, and peaked at higher altitudes and at earlier times compared to weakly forced cases. Mean error MCS-centered composites of WRF forecasts versus RUC analyses were derived at MCS initiation time for the LLJ atmospheric water vapor mixing ratio, LLJ total wind magnitude, convergence, most unstable convective available potential energy (MUCAPE), and most unstable convective inhibition (MUCIN). In most configurations, simulated MCSs in strongly and weakly forced regimes initiated to the north and east of observations, generally in a region where LLJ moisture, MUCAPE, and MUCIN fields were forecast well, with larger errors outside this region. However, WSM6 simulations for strongly forced cases showed a southward displacement in MCS initiation, where a combination of ambient environmental factors and microphysics impacts may simultaneously play a role in the location of forecast MCS initiation. Strongly forced observed and simulated MCSs initiated west of the LLJ axis and moved eastward into the LLJ, while observed and simulated MCSs in weakly forced environments traversed the termini of the LLJ. A northward bias existed for simulated MCS initiation and LLJ termini for weakly forced regimes.

The South American Water Balance: The Influence of Low-Level Jets

Abstract To study the climatology of the water balance over South America and analyze the influence of low-level jets (LLJs), a climate study of the water balance and its main components was performed, specifically in the Amazon and La Plata basin (LPB) region, from 1979 to 2008. The results showed that on average for the analysis period, the Amazon basin and LPB performed as a sink of moisture (ET < P) and as a moisture convergence for the regions, which accounted for approximately 62% and 43% of the precipitation, respectively. During the study period, 884 days with an occurrence of LLJs were observed, occurring most frequently during the winter and around 0000 and 0600 UTC. When considering the water balance for the days with LLJs, it was observed that the Amazon acts as a source of moisture, especially in the dry season, and that the LPB behaves as a sink during all months. The influence of the LLJ as a modulator for precipitation on the LPB is clear, as the precipitation is 32% higher during the LLJ events compared with days without LLJs. This main pattern shows that the moisture convergence trough of the LLJs is crucial for the water balance on the LPB, whereas evapotranspiration is a more important variable of the water balance on the Amazon basin with or without the LLJs.