Search NASA⌕ Search

SEARCH · Search NASA

Results for “planetary boundary layer (PBL)”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Vertical column dual-comb spectroscopy to a TBS

Open-path dual-frequency-comb spectroscopy (DCS) is a broadband, high spectral resolution, and high precision method for measuring gas concentrations over kilometer-scale paths. It has been used for detection and quantification of emissions of pollutants, hazardous gasses, and greenhouse gasses (GHGs). DCS has been shown to measure trace-gas mixing ratios with 0.14%-0.4% agreement between instruments. To achieve high signal-to-noise ratios (SNRs) with DCS, comb light is targeted onto a retroreflector at the end of the measurement path, which returns the signal to a detector co-located with the launch signal. Installing the retroreflector on a mobile platform such as a balloon or unmanned aerial vehicle (UAV) extends the capabilities of DCS by enabling variable path lengths, greater mobility, and access to higher altitudes. Mobile-target DCS has many uses in plume and leak detection, emissions modeling, and planetary boundary layer (PBL) studies. It is a promising method for observing vertical distributions of GHGs and mixing processes in the PBL, which are difficult to measure but important for pollution and climate monitoring as well as for understanding transport of gasses through the atmosphere. Tethered balloons are an intriguing platform because they enable longer flight durations and higher altitudes than easily obtainable with a UAV and thus allow for column measurements up to and above the PBL. New measurements completed in October/November 2024 reach the highest altitudes above ground level yet achieved by mobile-target DCS. For these measurements, the retroreflector was mounted on a 7 m diameter tethered helium balloon. An actively tracking gimbal on the ground holds the DCS launch telescope and keeps the 5 cm beam pointed onto the retroreflector while the balloon is lifted, lowered, and moved by wind and turbulence.

atmosphere↗
DOE OSTI2025

Demonstrating Hierarchical System Development With the Common Community Physics Package Single‐Column Model: A Case Study Over the Southern Great Plains

This study demonstrates a specific application of the hierarchical system development (HSD) approach to investigate, analyze, and attribute model issues within the Unified Forecast System (UFS), with a focus on process isolation. By evaluating a non‐precipitating, shallow cumulus case at the Atmospheric Radiation Measurement Southern Great Plains site in the UFS global forecast against the observation, the investigation identifies a warmer and deeper daytime convective planetary boundary layer (PBL) and misrepresented nocturnal PBL transition. Hypothesis testing, which employs the Common Community Physics Package (CCPP) single‐column model (SCM) and uses the same physics as the UFS global model, confirms that these issues are attributed to the model physics and initialization. Specifically, misrepresented PBL processes are linked to problematic surface condition and a lack of cloud formation, which may stem from deficiencies in PBL and cloud microphysics parameterizations and their interactions. The UFS initial condition contributes to an earlier, excessively collapsed daytime convective boundary layer and a lack of decoupling between the stable boundary layer and residual layer late in the afternoon. This work introduces an avenue for the community to engage with the application of HSD, along with the CCPP and CCPP SCM, to understand the interplay of model physics, disentangle the roles of model components, as well as facilitate model and forecast improvement.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

A multi‐variable framework for selecting WRF physics configurations at convection‐permitting scales: An Amazon wet‐season case study

Tropical convection over rainforests modulates atmospheric circulation and the energy and hydrological cycles across multiple scales. However, the scarcity of observations still limits our understanding of these processes. Although numerical models are utilized to investigate atmospheric physical processes, their performance depends on the choice of parameterizations and grid resolution. Here, in this work, we introduce and apply a multi‐variable, multi‐physics framework to evaluate and rank the Advanced Research Weather Research and Forecasting (WRF–ARW) configurations at 1‐km resolution over the central Amazon during the wet season. A 48‐member ensemble combines three land‐surface models (LSMs), four planetary boundary layer (PBL), and four microphysics (MP) schemes. Model performance for seven convection‐related near‐surface and boundary‐layer variables is assessed using Taylor diagrams and the Taylor skill score (TSS), analysis of variance (ANOVA)‐based sensitivity metrics, and non‐parametric rank tests. We then construct a combined, weighted TSS to identify configurations that are comparatively robust across variables. Results showed that most configurations reproduce near‐surface temperature, sensible and latent heat fluxes, and boundary‐layer height reasonably well, whereas humidity and rainfall remain challenging. LSM choice has the strongest impact on the surface fluxes and a secondary influence on near‐surface temperature and humidity, PBL schemes dominate boundary‐layer height, and MP schemes exert the largest control on rainfall. No single configuration is optimal for all variables, but the combination of Noah (LSM), Yonsei University (PBL), and Morrison (MP) emerges as the most robust configuration for this case, with the WRF single‐moment six‐class scheme (WSM6) providing a competitive, computationally cheaper MP alternative. The framework is general and can be applied to other regions, seasons, and convective regimes.

Amazon rainforest↗
DOE OSTI2020

Assessing the sensitivity of land-atmosphere coupling strength to boundary and surface layer parameters in the WRF model over Amazon

Modeling tools can be used to diagnose regional land-atmosphere (L-A) coupling strength in the absence of sufficient observations, but subject to uncertainties associated with parameters in model physical parameterizations. Different sensitivity analysis (SA) approaches may lead to different conclusions about the underlying sensitivities. In this study, we quantify simulation uncertainties related to parameter perturbations, and use different approaches to conduct parameter SA on the WRF model pertaining to L-A coupling strength for simulations over the Amazon region. A total of twenty parameters from the Yonsei University (YSU) planetary boundary layer (PBL) and the revised MM5 surface layer (SL) schemes were selected in this analysis. Three different SA methods, the Morris One-at-A-Time (MOAT) method, the Multivariate Adaptive Regression Splines (MARS) method, and the Sobol’ method, were employed to analyze seven WRF-simulated variables and five L-A coupling metrics. Results show that 1) parameter perturbations cause large simulation uncertainties which are comparable to those in the observations; 2) three different SA methods give consistent L-A coupling strength outcomes; 3) six out of the twenty parameters contribute 80%–95% of the total variance in the metrics analyzed, and first-order effects dominate over interaction effects; 4) the twelve variables/metrics of interest show similar sensitivity patterns to the selected parameters, which is consistent across all the methods used. Physical mechanisms for how the sensitive parameters act in determining the L-A coupling strength and associated variables also are illustrated. Our results will help quantifying L-A coupling strength and establishing a basis for parameter calibration over the Amazon region.

Wang, Chen↗
DOE OSTI2021

Quantifying physical parameterization uncertainties associated with land-atmosphere interactions in the WRF model over Amazon

The Weather Research and Forecasting (WRF) model can be used to diagnose regional land-atmosphere (L-A) coupling strength in the absence of sufficient observations but subjected to uncertainties associated with model physical parameterizations. In this study, we propose a framework to quantify and reduce model physical parameterization uncertainties associated with surface fluxes and L-A coupling. An ensemble of WRF simulations with different physical schemes is used to simulate surface fluxes and land-atmosphere coupling strength over the Amazon region. The physical parameterizations investigated include cloud microphysics (MP), land surface processes (LSM), planetary boundary layer (PBL), surface layer (SL), and cumulus (CU). We perform 120 ensemble simulations using the WRF model and different combinations of six MPs, three LSMs, six PBLs and SLs and three CUs. The measurements from the GoAMAZON field campaign and satellite data are used to evaluate model performance. A Multi-way analysis of variance (ANOVA) approach is applied to quantify the relative importance of different physics processes on L-A coupling. The Tukey’s test is used to sort schemes that have no significant differences into one group. The suite of physics that result in the best simulations of the corresponding variables are selected based on the Taylor skill score. Results show that the relative importance of processes and their interaction vary with the variables of interest. For example, CU was the most important process in modulating soil moisture, 2 m-humidity, latent heat, and net radiation. LSM showed dominant effects on 2 m-temperature and also has the largest impact on sensible heat and the lifting condensation level. The best physical parameterization ensembles show much narrower ranges of the variables of interest than the priori ensemble. Results of this study show the roles of different physical processes in modulating L-A interactions, quantify model uncertainties from physical processes, and provide insights for improving the model physics parameterizations.

Wang, Chen↗
DOE OSTI2023

Developing a 20-year high-resolution wind data set for Puerto Rico

The purpose of this study is to develop a high-resolution wind resource data set for Puerto Rico as part of the wind resource assessment in the Puerto Rico Grid Resilience and Transition to 100 % Renewable Energy Study (PR100) project. The Weather and Research and Forecasting (WRF) is used to model 20-years (2001-2020) of wind resource data on a 3-km grid for the Puerto Rico region. Because accurately representing the planetary boundary layer (PBL)-physics in the WRF is key to accurately model low-level wind speed, 11 different PBL schemes are examined and evaluated to find a WRF configuration that can provide the most accurate wind data. The modeled wind speeds are validated with buoy observations, and the Shin-Hong PBL scheme is selected to generate the final wind data set. Here, the overall results demonstrate that the high-resolution data correctly represents the climate of Puerto Rico (e.g., a dominant easterly trade wind). At 160 m above ground, the southern regions of Puerto Rico show strong offshore wind speed (>8 m/s on average) throughout the daytime and nighttime. For land-based wind, average wind speed ranges from 5 m/s-7 m/s during daytime, whereas notable high wind speeds (>9 m/s) appear in the mountain regions during nighttime.

17 WIND ENERGY↗
DOE OSTI2024

Characterizing model uncertainties in simulated coast-to-offshore wind over the northeast U.S. using multi-platform measurements from the TCAP field campaign

Numerical weather prediction (NWP) models, such as the Weather Research and Forecasting (WRF) model, are widely used to provide estimates of the offshore wind energy resource owing to their large spatial coverage compared to available observations. Nevertheless, spatiotemporal distribution of model biases is highly dependent on factors including model configuration, location, and the interplay of multi-scale physical processes. Here, in this study, we focus on the characterization of model uncertainties in simulated coast-to-offshore winds over the northeast U.S., by varying sea surface temperature (SST) forcings, surface layer (SL) and planetary boundary layer (PBL) parameterizations, as well as identifying biases that may be directly passed from initial and boundary conditions. Multiple measurements, including aircraft data collected during the U.S. Department of Energy's Two-Column Aerosol Project (TCAP) experiment, are used to constrain the model results and facilitate quantitative comparisons. Our analysis indicates while SST forcing has notable impacts on simulated air temperature and moisture within PBL, the modeled winds are in general more sensitive to the choices of SL and PBL physics than to SST. The model’s forcing data not only controls the vertical dependence of wind speed errors, but also alters regional variability in wind speed’s spatial correlation. Bias comparisons between ERA5 reanalysis and ensemble simulations revealed significant similarity, particularly in wind speed biases during winter, underscoring their dependency on initial and boundary conditions. Coastal and offshore near-surface wind speed biases tend to exhibit much higher similarity in winter than in summer due to the presence of much stronger and more persistent synoptic wind conditions. This study highlights the importance of accurate atmospheric forcing and parameterization choices in improving wind forecasts and suggests the potential for extrapolating coastal wind biases to offshore locations, aiding wind energy forecasting and informing the Wind Forecast Improvement Project-3 (WFIP3).

17 WIND ENERGY↗
DOE OSTI2026

Investigating ultrafine aerosol turbulent fluxes during atmospheric new particle formation events

New particle formation (NPF) is an important source of atmospheric aerosols, yet quantitatively predicting its occurrence remains challenging, partly because ground-based measurements cannot capture NPF accurately if they occur in the upper atmosphere. While observations have confirmed the presence of new particles near the top of the planetary boundary layer (PBL), their origins and the direction of their vertical transport have remained ambiguous. Here, we propose and validate an analytical framework using airborne eddy-covariance (EC) and continuous wavelet transform (CWT) to directly quantify the vertical flux of newly formed particles and determine its dominant vertical transportation direction. Analyzing data from a dedicated airborne campaign over the Southern Great Plains, we observed a persistent and strong downward particle flux during NPF events, with a mean value of 133.8 cm?3 m s?¹ downward flux in the entrainment zone, whereas fluxes on non-NPF days were negligible. Our spectral analysis further confirms that these directional fluxes can be reliably captured using standard 1 Hz aerosol instrumentation. These findings suggest that new particle formation, driven by the entrainment of air from the overlying residual/stable layer during PBL growth, is a significant and potentially understudied source of boundary layer aerosols. The framework presented here provides a methodology to correctly attribute NPF events to specific altitudes, thereby improving the mechanistic understanding required for accurate atmospheric models.

Zhang, Ruoyu↗
DOE OSTI2022

The Influence of Dust-Smoke Mixtures on Boundary Layer Processes and Nocturnal Warming in the Sahel

Using a single column model with ground-based, aircraft, and satellite data sets we assess the combined role of smoke and dust aerosols, land degradation/aridization (LDA), and their impact on the planetary boundary layer (PBL) in influencing near-surface air temperature over the Sahel. Our study is unique because it assesses the combined role of smoke and dust aerosols on PBL evolution and near-surface air temperatures during both day and nighttime. More importantly, using a theoretical framework, we provide a careful explanation of the geophysical processes responsible for the changes in PBL and near-surface air temperature. Our results indicate that during northern hemisphere winter months, dust, and smoke over Sahel radiatively combine to impact the PBL. We show that aerosol mixtures dominated by dust modify PBL height in a manner that minimizes/maximizes surface layer cooling/warming at times when daytime maximum/nocturnal minimum temperatures occur. Furthermore, we find that increasing smoke contribution to total column aerosol optical extinction counteracts nighttime warming through daytime cooling. When smoke constitutes half or more of to the total column aerosol optical extinction, the ratio of longwave to shortwave radiative forcing is less than 10%, and nighttime cooling ensues. Minimum temperature is most sensitive to changes in mid-visible aerosol optical depth (AOD) values <1 and doubling of dust AOD within this range during the 1950–1980 Sahelian LDA event is estimated to have a nocturnal warming potential of 0.6°C.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Towards a Unified Setup to Simulate Mid‐Latitude and Tropical Mesoscale Convective Systems at Kilometer‐Scales

Abstract Mesoscale convective systems (MCSs) are the main source of precipitation in the tropics and parts of the mid‐latitudes and are responsible for high‐impact weather worldwide. Studies showed that deficiencies in simulating mid‐latitude MCSs in state‐of‐the‐art climate models can be alleviated by kilometer‐scale models. However, whether these models can also improve tropical MCSs and whether we can find model settings that perform well in both regions is understudied. We take advantage of high‐quality MCS observations collected over the Atmospheric Radiation Measurement (ARM) facilities in the US Southern Great Plains (SGP) and the Amazon basin near Manaus (MAO) to evaluate a perturbed physics ensemble of simulated MCSs with 4 km horizontal grid spacing. A new model evaluation method is developed that enables to distinguish biases stemming from spatiotemporal displacements of MCSs from biases in their reflectivity and cloud shield. Amazon MCSs are similarly well simulated across these evaluation metrics than SGP MCSs despite the challenges anticipated from weaker large‐scale forcing in the tropics. Generally, SGP MCSs are more sensitive to the choice of model microphysics, while Amazon cases are more sensitive to the planetary boundary layer (PBL) scheme. Although our tested model physics combinations had strengths and weaknesses, combinations that performed well for SGP simulations result in worse results in the Amazon basin and vice versa. However, we identified model settings that perform well at both locations, which include the Thompson and Morrison microphysics coupled with the Yonsei University (YSU) PBL scheme and the Thompson scheme coupled with the Mellor‐Yamada‐Janjic PBL scheme.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

The Effect of Surface Heating Heterogeneity on Boundary Layer Height and Its Dependence on Background Wind Speed

The planetary boundary layer height (PBLH) is a fundamental variable of the planetary boundary layer (PBL). The effect of surface heterogeneity is challenging in the PBL parameterization for numerical weather and climate models. Here we use large eddy simulation data to investigate the impact of surface heating heterogeneity on the PBLH spatial variations and mean values over a domain of typical mesoscale model grid size. It is found that this impact depends on background wind condition. Variance decomposition and Fourier spectra both reveal that for the fully developed sheared convective PBL, surface heterogeneity contributes little to the spatial variation of PBLH, except for the case with heterogeneity scale of 14.4 km. This suggests that surface heterogeneity with length scales less than ~10 km, which is typical for mesoscale modeling, does not induce significant subgrid spatial variation of PBLH. The domain-averaged PBLH is found to generally increase as surface heterogeneity scale decreases, until reaching the scale on the order of PBLH. The findings can be used to inform the parameterization development of PBL processes over heterogeneous surface.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Effects of Lower Troposphere Vertical Mixing on Simulated Clouds and Precipitation Over the Amazon During the Wet Season

Planetary boundary layer (PBL) schemes parameterize unresolved turbulent mixing within the PBL and free troposphere (FT). Previous studies reported that precipitation simulation over the Amazon in South America is quite sensitive to PBL schemes and the exact relationship between the turbulent mixing and precipitation processes is, however, not disentangled. In this study, regional climate simulations over the Amazon in January–February 2019 are examined at process level to understand the precipitation sensitivity to PBL scheme. The focus is on two PBL schemes, the Yonsei University (YSU) scheme, and the asymmetric convective model v2 (ACM2) scheme, which show the largest difference in the simulated precipitation. During daytime, while the FT clouds simulated by YSU dissipate, clouds simulated by ACM2 maintain because of enhanced moisture supply due to the enhanced vertical moisture relay transport process: (a) vertical mixing within PBL transports surface moisture to the PBL top, and (b) FT mixing feeds the moisture into the FT cloud deck. Due to the thick cloud deck over Amazon simulated by ACM2, surface radiative heating is reduced and consequently the convective available potential energy is reduced. As a result, precipitation is weaker from ACM2. Two key parameters dictating the vertical mixing are identified, p , an exponent determining boundary layer mixing and λ , a scale dictating FT mixing. Sensitivity simulations with altered p , λ , and other treatments within YSU and ACM2 confirm the precipitation sensitivity. The FT mixing in the presence of clouds appears most critical to explain the sensitivity between YSU and ACM2.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Airborne Measurements of Scale‐Dependent Latent Heat Flux Impacted by Water Vapor and Vertical Velocity Over Heterogeneous Land Surfaces During the CHEESEHEAD19 Campaign

Abstract The water vapor transport associated with latent heat flux (LE) in the planetary boundary layer (PBL) is critical for the atmospheric hydrological cycle, radiation balance, and cloud formation. The spatiotemporal variability of LE and water vapor mixing ratio ( r v ) are poorly understood due to the scale‐dependent and nonlinear atmospheric transport responses to land surface heterogeneity. Here, airborne in situ measurements with the wavelet technique are utilized to investigate scale‐dependent relationships among LE, vertical velocity ( w ) variance (), and r v variance () over a heterogeneous surface during the Chequamegon Heterogeneous Ecosystem Energy‐balance Study Enabled by a High‐density Extensive Array of Detectors 2019 (CHEESEHEAD19) field campaign. Our findings reveal distinct scale distributions of LE, , and at 100 m height, with a majority scale range of 120 m–4 km in LE, 32 m–2 km in , and 200 m–8 km in . The scales are classified into three scale ranges, the turbulent scale (8–200 m), large‐eddy scale (200 m–2 km), and mesoscale (2–8 km) to evaluate scale‐resolved LE contributed by and . The large‐eddy scale in PBL contributes over 70% of the monthly mean total LE with equal parts (50%) of contributions from and . The monthly temporal variations mainly come from the first two major contributing classified scales in LE, , and . These results confirm the dominant role of the large‐eddy scale in the PBL in the vertical moisture transport from the surface to the PBL, while the mesoscale is shown to contribute an additional ∼20%. This analysis complements published scale‐dependent LE variations, which lack detailed scale‐dependent vertical velocity and moisture information.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Aerosol Vertical Turbulent Mass Flux Retrievals Through Novel Remote Sensing Algorithm

Abstract Integrated measurements of aerosol, radiation, cloud, and turbulent transport in the planetary boundary layer (PBL) are essential for understanding and modeling climate and air quality. Here, we developed a new technique for the identification of convective turbulent regions and deriving the vertical distribution of aerosol turbulent mass fluxes within PBL. The algorithm uses retrievals from coherent Doppler lidars and a high spectral resolution lidar. The technique was applied to study particle mass fluxes over 2 months (November–December 2020) during the campaign conducted at the DOE Atmospheric Radiation Measurement Southern Great Plains (SGP) site in Lamont, Oklahoma. The algorithm developed here is capable of continuously deriving vertically resolved (curtains) aerosol mass fluxes. Our data analysis shows that at the site, the 30‐min averaged fluxes at 135 m above the surface were mainly positive (upward) at ∼1 μg m −2 s −1 , suggesting that the surface is the primary source of the particle mass supplied to the boundary layer at the SGP site. Analyses of the individual case studies have revealed that not all the derived fluxes can be linked to surface emissions. Both positive and negative values in a range of ±5 μg m −2 s −1 can be caused by convective thermals interacting between the residual layer and the mixed layer and by rotation of the horizontal wind with the height. Large erroneous negative fluxes can also be caused by drizzling/precipitating clouds. We anticipate that the application of the current technique will lead to a more realistic representation of aerosol mass budgets and bidirectional mixing rates.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Pivotal Role of Cloud‐Planetary Boundary Layer Coupling to Explain Contrasting Aerosol‐Cloud Relationships

The radiative effect of aerosol on cloud albedo via altering cloud droplet effective radius (r e ) is a major uncertainty in the Earth's climate system. Remote sensing studies have reported either negative or positive relationships between re and aerosol number concentration (N a ) or other aerosol proxies. However, there are much fewer in situ observational evidences and physical explanation remains elusive for the contrasting N a -r e relationships. Here we quantify the N a -r e relationship by using in situ aircraft measurements, together with a re decomposition method. Our analysis reveals that the cloud-planetary boundary layer (PBL) coupling plays a pivotal role on the N a -r e relationship. Quantitative r e decomposition indicates that the contrasting N a -r e relationships in two cloud-PBL coupling regimes result from different balances of four distinct aspects. The widely recognized number effect may be outweighed by the joint effects of the remaining three that have been rarely investigated and largely ignored in N a -r e parameterizations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Improved Representation of Horizontal Variability and Turbulence in Mesoscale Simulations of an Extended Cold-Air Pool Event

Abstract Cold-air pools (CAPs), or stable atmospheric boundary layers that form within topographic basins, are associated with poor air quality, hazardous weather, and low wind energy output. Accurate prediction of CAP dynamics presents a challenge for mesoscale forecast models in part because CAPs occur in regions of complex terrain, where traditional turbulence parameterizations may not be appropriate. This study examines the effects of the planetary boundary layer (PBL) scheme and horizontal diffusion treatment on CAP prediction in the Weather Research and Forecasting (WRF) Model. Model runs with a one-dimensional (1D) PBL scheme and Smagorinsky-like horizontal diffusion are compared with runs that use a new three-dimensional (3D) PBL scheme to calculate turbulent fluxes. Simulations are completed in a nested configuration with 3-km/750-m horizontal grid spacing over a 10-day case study in the Columbia River basin, and results are compared with observations from the Second Wind Forecast Improvement Project. Using event-averaged error metrics, potential temperature and wind speed errors are shown to decrease both with increased horizontal grid resolution and with improved treatment of horizontal diffusion over steep terrain. The 3D PBL scheme further reduces errors relative to a standard 1D PBL approach. Error reduction is accentuated during CAP erosion, when turbulent mixing plays a more dominant role in the dynamics. Last, the 3D PBL scheme is shown to reduce near-surface overestimates of turbulence kinetic energy during the CAP event. The sensitivity of turbulence predictions to the master length-scale formulation in the 3D PBL parameterization is also explored. Significance Statement In this article, we demonstrate how a new framework for modeling atmospheric turbulence improves cold pool predictions, using a case study from January 2017 in the Columbia River basin (U.S. Pacific Northwest). Cold pools are regions of cold, stagnant air that form within valleys or basins, and improved forecasts could help to mitigate the risks they pose to air quality, transportation, and wind energy production. For the chosen case study, our tests show a reduction in temperature and wind speed errors by up to a factor of 2–3 relative to standard model options. These results strongly motivate continued development of the framework as well as its application to other complex weather events.

17 WIND ENERGY↗
DOE OSTI2021

Evaluating the Lagrangian Evolution of Subtropical Low Clouds in GCMs Using Observations: Mean Evolution, Time Scales, and Responses to Predictors

In this work, a Lagrangian framework is developed to show the daily-scale time evolution of low clouds over the eastern subtropical oceans. An identical framework is applied to two general circulation models (GCMs): the CAM5 and UKMET and a set of satellite observations. This approach follows thousands of parcels as they advect downwind in the subtropical trade winds, comparing cloud evolution in time and space. This study tracks cloud cover, in-cloud liquid water path (CLWP), droplet concentration $N_d$, planetary boundary layer (PBL) depth, and rain rate as clouds transition from regions with predominately stratiform clouds to regions containing mostly trade cumulus. The two models generate fewer clouds with greater $N_d$ relative to observations. Models show stronger Lagrangian cloud cover decline and greater PBL deepening when compared with observations. In comparing frequency distributions of cloud variables over time, it is seen that models generate increasing frequencies of nearly clear conditions at the expense of overcast conditions, whereas observations show transitions from overcast to cloud amounts between 50% and 90%. Lagrangian decorrelation time scales ($\mathcal{e}$-folding time $\tau$) of cloud cover and CLWP are between 11 and 19 h for models and observations, although they are a bit shorter for models. A Lagrangian framework applied here resolves and compares the time evolution of cloud systems as they adjust to environmental perturbations in models and observations. Increasing subsidence in the overlying troposphere leads to declining cloud cover, CLWP, PBL depth, and rain rates in models and observations. Modeled cloud responses to other meteorological variables are less consistent with observations, suggesting a need for continuing mechanical improvements in GCMs.

58 GEOSCIENCES↗
DOE OSTI2023

Observations of Boundary Layer Convergence Lines and Associated Updrafts in the U.S. Southern Great Plains

Abstract Boundary layer convergence lines (CLs) are highly effective at deep-convection initiation (DCI), suggesting that their associated updraft properties differ from those of more widespread turbulent updrafts in the planetary boundary layer (PBL). This study exploits observations at the Atmospheric Radiation Measurement Southern Great Plains (ARM SGP) observatory in Oklahoma from 2011 to 2016 to quantify CL properties and their relation to turbulent PBL eddies preceding CL arrival. Two independent methods for estimating CL properties are developed at two locations in the SGP region, both relying on the assumption of a 2D circulation in the CL-normal plane but using different combinations of instruments. The first (the radar method) relies mainly on scanning radar data and is applied to 61 CLs passing near a high-resolution scanning radar based in Nardin, Oklahoma, while the second (the surface method) relies mainly on surface wind data and is applied to 68 CLs crossing the SGP facility in nearby Lamont, Oklahoma. Mean daytime (1000–1900 LST) CL width (∼2 km) and convergence magnitude (∼0.003 s −1 ) are similar for both methods, and mean daytime CL depth is ∼0.75 km. The two methods disagree at night (0000–1000 and 1900–2400 LST), where the surface method estimates wider and weaker CLs than the radar method. This difference may stem from the radar beam overshooting the shallow, highly stable nocturnal PBL. The largest CL updrafts are slightly wider (∼20%) and stronger (∼40%) than the largest PBL updrafts in the pre-CL period, generating 50%–100% larger updraft mass fluxes over most of the PBL depth. Significance Statement Deep convection is commonly initiated by boundary layer convergence lines (CLs), which are associated with intense surface-based wind convergence and strong updrafts that may lift air to saturation. Although CLs form regularly, they are far less common than ordinary, short-lived turbulent thermals in the daytime boundary layer. To better understand why CLs are so effective at deep-convection initiation, we observationally quantify their morphologies and strengths and compare these properties to those of surrounding turbulent updrafts. Perhaps surprisingly, the CLs are found to exhibit only slightly larger scales and strengths as the turbulent updrafts. Although these marginal increases help to explain the preference for storms to initiate along CLs, they likely are not the whole story.

54 ENVIRONMENTAL SCIENCES↗