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At least 91 records · Page 5

Enhanced Boundary Layer Height Detection Using Ceilometer, Surface Meteorology, and Radiation Products With a Random Forest Ensemble Method

This study develops and evaluates a Random Forest (RF) model for estimating planetary boundary layer height (PBLH) using 9 years of data from the Atmospheric Radiation Measurement Southern Great Plains (ARM SGP) user facility, with potential application in the NOAA Surface Radiation (SURFRAD) Network. The model integrates ceilometer, surface meteorology, and radiation measurements, and is trained using thermodynamic PBLH estimates derived from radiosondes. This approach aims to bridge gaps between aerosol-based and thermodynamic-based PBLH estimates. The RF model outperformed traditional methods during daytime and better captured transition periods, demonstrating improved accuracy and robustness. At ARM SGP, it showed a substantial reduction in both bias and RMSE, with a bias near zero (−4.9 m) compared with traditional Haar Wavelet (HW) (70.9 m) and Vaisala BL-View software (124.1 m), and an RMSE of 303.2 m, lower than both BL-View (566.9 m) and HW (404.6 m). During daytime hours, RF consistently outperformed both alternatives, maintaining lower bias and RMSE across all periods. At a second evaluation site, RF achieved the lowest overall RMSE (323.7 m), similar to HW (326.4 m) and significantly better than BL-View (738.3 m). However, all models showed reduced accuracy under stable nighttime conditions, limiting the reliability of PBLH estimates. Key predictors for the model included the lifting condensation level height (LCLH), aerosol gradients, and month for seasonal variability. The study underscores the potential of integrating machine learning with multiple data sets such as surface energy and thermodynamic data to advance PBLH estimation.

boundary layer height↗

A Novel Machine Learning Algorithm for Planetary Boundary Layer Height Estimation Using AERI Measurement Data

Accurately determining the height of the planetary boundary layer (PBL) is important since it can affect the climate, weather, and air quality. Ground-based infrared hyperspectral remote sensing is an effective way to obtain this parameter. Compared with radiosonde measurements, its temporal resolution is much higher. In this study, a method to retrieve the PBL height (PBLH) from the ground-based infrared hyperspectral radiance data is proposed based on machine learning. In this method, the channels that are sensitive to temperature and humidity profiles are selected as the feature vectors, and the PBLHs derived from radiosonde are taken as the true values. The support vector machine (SVM) is applied to train and test the data set, and the parameters are optimized in the process. The data set collected at the Atmospheric Radiation Measurement (ARM) program Southern Great Plains (SGP) from 2012 to 2015 is analyzed. The instruments used in this letter include Atmospheric Emitted Radiance Interferometer (AERI), Vaisala CL31 ceilometer, and radiosonde. It shows that the root mean square error (RMSE) between the PBLHs calculated by the proposed method using AERI data and those from radiosonde data can be within 370 m, and the square correlation coefficient (SCC) is greater than 0.7. Compared with the PBLHs derived from the ceilometer, it can be found that the new method is more stable and less affected by clouds.

54 ENVIRONMENTAL SCIENCES↗

15-minute Parker River gap-filled tide height and salinity data, PIE LTER, Plum Island Sound, MA (2014–2023), for ELM PFLOTRAN modeling

This dataset contains 15-minute tide height and salinity data from the Typha site along the Parker River, part of the Plum Island Ecosystems Long Term Ecological Research (PIE LTER) site in Plum Island Sound, Massachusetts (MA) 2014-2023. Tide height (in NAVD88) was compiled from measurements conducted at the mouth of Plum Island Sound and corrected for time lags. Gap-filling of missing periods were done by fitting tidal constituents to the time series. Salinity was measured (and is stored on ESS DIVE ) in 2022 and 2023 using HOBO U24-002 conductivity loggers. River discharge is the most important control on tidal river water salinity at the location (Vallino & Hopkinson, 1998). An artificial neural network was trained to predict river water salinity at the location using Parker River discharge (USGS station 01101000, Parker River at Byfield, MA) and gap-filled salinity observations from a long-term monitoring station ca. 3km downstream from the Typha site (LTER station ‘Middle Road’) as input variables to create continuous time series information. The data set was used in the spin up and simulations of a land surface model coupled to a biogeochemical reaction network (ELM PFLOTRAN) assessing impacts of hydrology and salinity input on methane fluxes in 2022 and 2023 (Sulman et al., 2024). Metadata files ELMPFLOTRAN_tide_salinity_dd.csv and ELMPFLOTRAN_tide_salinity_flmd.csv provide details on site location, data variables, and QA/QC methods .

54 ENVIRONMENTAL SCIENCES↗

Test of model of equivalence of tree height growth and transpiration rates in percolation-based phenomenology for root-soil interaction

We recently introduced a phenomenological model to represent root-soil interactions that accounts for variability in tree growth on local scales and within species (Hunt et al., 2020). Here, using publicly available datasets, we examine the developed model to provide additional empirical evidence, which also gives novel insight into two particular tree species, Eucalyptus regnans and Eucalyptus sieberri. In particular, we discovered two novel aspects of the model: a power-law time dependence with a different power-law exponent than usually heretofore applied, and apparently a direct equivalence of results for transpiration and growth rates. Also, although our original expectation was that growth and transpiration were merely proportional, comparison of the entire BAAD data set (Falster et al., 2015) for tree height with our model (Hunt et al., 2020; Fig. 1) already suggested approximate equality of these disparate measurements (volume/area, height). In this present manuscript we find further evidence for equivalence of the two measurements and provide additional theoretical basis for a model assumption regarding constancy of sap flow rates.

54 ENVIRONMENTAL SCIENCES↗

Validating simulated mountain wave impacts on hub-height wind speed using SoDAR observations

The ascent of stably stratified air over a mountain barrier can trigger the generation of mountain waves. Mountain waves occur frequently over the Columbia River Gorge in western North America and can impact wind power generation over the area. Therefore, predicting the details of mountain waves events (e.g., dominant wavelength, timing, and duration) can be very valuable for the wind energy community. In this study, the ability of the Weather Research and Forecasting (WRF) model to simulate mountain waves and their impact on hub-height wind speed is investigated. Our results suggest that the WRF model has moderate skill in simulating observed mountain wave. Further, given WRF predictions of wavelength range and wave period, the Fast Fourier Transform can calculate the simulated mountain wave impact on hub-height wind speed. The resulting wind speeds agree well with SoDAR observations in terms of both magnitude and pattern. Finally, for the simulated cases, WRF consistently predicts impacts of significant mountain wave events about an hour earlier than the actual observations. Overall, in this work, the sensitivities as well as uncertainties associated with our methodology are discussed in detail.

17 WIND ENERGY↗

Unconventional Error Cancellation Explains the Success of Hartree–Fock Density Functional Theory for Barrier Heights

Energy barriers, which control the rates of chemical reactions, are seriously underestimated by computationally efficient semilocal approximations for the exchange-correlation energy. The accuracy of a semilocal density functional approximation is strongly boosted for reaction barrier heights by evaluating that approximation non-self-consistently on Hartree–Fock electron densities, which has been known for ~30 years. Here, the conventional explanation is that the Hartree–Fock theory yields the more accurate density. This work presents a benchmark Kohn–Sham inversion of accurate coupled-cluster densities for the reaction H 2 + F → HHF → H + HF and finds a strong, understandable cancellation between positive (excessively overcorrected) density-driven and large negative functional-driven errors (expected from stretched radical bonds in the transition state) within this Hartree–Fock density functional theory. This confirms earlier conclusions (Kaplan, A. D., et al. J. Chem. Theory Comput. 2023, 19, 532–543) based on 76 barrier heights and three less reliable, but less expensive, fully nonlocal density functional proxies for the exact density.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Uncovering the Relationship between Diameter and Height of Electrodeposited Lithium Protrusions in a Rigid Electrolyte

A promising approach for enabling rechargeable batteries with significantly higher energy densities than current lithium-ion batteries is by deploying lithium-metal anodes. However, the growth of lithium protrusions during charging presents significant challenges. Since these protrusions are often branched and filamentous in conventional liquid electrolytes, this problem is referred to in the literature as the “dendrite problem”. While solid electrolytes have the potential to solve this problem, protrusions grow in all electrolytes when the current density exceeds a critical value. Fundamentally understanding the formation is necessary to develop a rational approach for increasing the critical current density, but it is challenging due to the complex interplay between electrochemical and material properties. The diameters and heights of protrusions on lithium-metal anodes stabilized by a rigid block copolymer electrolyte were measured in situ by synchrotron hard X-ray microtomography. The diameter of the shorting protrusions increased linearly with increasing electrolyte thickness. Further, a universal linear relationship between protrusion height and diameter of both shorting and non-shorting protrusions was observed. A model based on the concentrated solution theory was used to establish the electrochemical and mechanical sources for our observations. Here, the computational analysis indicates that elastic and plastic deformation of both the lithium metal and the polymer are important to describe protrusion growth. Both stress-induced current density effects due to the deformation of the electrolyte near the protrusion and plastic deformation of lithium metal combine to give the counterintuitive result: the fastest-growing protrusions have the largest diameter.

25 ENERGY STORAGE↗

On the Relationship Between the Marine Cold Air Outbreak M Parameter and Low-Level Cloud Heights in the Midlatitudes

Focusing on conditions of subsidence when low clouds are present, ground-based observations in both the North Atlantic and the Southern Ocean reveal strong relationships between cloud boundary (base and top heights) and different measures of lower tropospheric instability. The difference in potential temperature between the surface and 800 hPa (a metric called M) provides a stronger relationship than measures of inversion strength such as the lower tropospheric stability and estimated inversion strength. This is because (1) inversion strength itself does not correlate well with cloud boundaries, and (2) M contains information that appears important for cloud boundaries. These include the surface forcing through the use of sea surface rather than near-surface air temperature and an upper level close to the real cloud top. These results expand upon previous work on the importance of M as a predictor of cloud morphology. However, important differences are found in low-cloud conditions for the North Atlantic as compared to the Southern Ocean (for a given value of M): stronger inversions, deeper boundary layers, and much larger sea level pressures. Therefore, the relationship between cloud boundaries and M differs between the two regions. A general circulation model provides similar relationships as observed between M and both cloud top height and temperature but tends to place clouds higher and at colder temperatures than observed for a given M. This might cause issues with the representation of precipitation, cloud cover and radiation in the Southern Ocean.

54 ENVIRONMENTAL SCIENCES↗

Time Evolution and Diurnal Variability of the Parametric Sensitivity of Turbine-Height Winds in the MYNN-EDMF Parameterization

The Mellor-Yamada-Nakanishi-Niino (MYNN) parameterization applied in the Weather Research and Forecasting (WRF) model has been augmented to include the Eddy-Diffusion Mass-Flux (EDMF) approach to better represent transport by boundary-layer eddies. This change includes the addition of new parameters associated with convective updrafts and boundary-layer clouds. These additions lead to new parametric sensitivities in the hub-height wind speed compared to simulations using the standard MYNN parameterization that were explored previously. This work builds on efforts focused on WRF’s MYNN parameterization by examining the sensitivity of hub-height wind speed to parameters in the MYNN-EDMF parameterization as a function of simulation lead time. Summer and winter periods were selected from the second Wind Forecast Improvement Project (WFIP2). Five sets of simulations were completed for each season, with lead times ranging from 2 to 6 days. The results show that the sensitivity to the new parameters associated with the EDMF scheme is generally small compared to other parameters, with the largest impact in convective boundary layers. The spread in the perturbed parameter ensembles was found to grow quickly over the first 8 to 19 hours in the summer simulations and 17 to 24 hours in the winter simulations with little change after that, regardless of the simulation length. A strong diurnal cycle in the parameter sensitivity was also found associated with changes in the atmospheric stability, as well as an increase in the sensitivity to the entrainment parameter used in the EDMF parameterization that is associated with increasing fractional areas covered by plumes.

54 ENVIRONMENTAL SCIENCES↗

Scaling of Turbulence and Microphysics in a Convection–Cloud Chamber of Varying Height

Abstract The convection–cloud chamber enables measurement of aerosol and cloud microphysics, as well as their interactions, within a turbulent environment under steady‐state conditions. Increasing the size of a convection–cloud chamber, while holding the imposed temperature difference constant, leads to increased Rayleigh, Reynolds and Nusselt numbers. Large–eddy simulation coupled with a bin microphysics model allows the influence of increased velocity, time, and spatial scales on cloud microphysical properties to be explored. Simulations of a convection–cloud chamber, with fixed aspect ratio and increasing heights of H = 1, 2, 4, and (for dry conditions only) 8 m are performed. The key findings are: Velocity fluctuations scale as H 1/3 , consistent with the Deardorff expression for convective velocity, and implying that the turbulence correlation time scales as H 2/3 . Temperature and other scalar fluctuations scale as H −3/7 . Droplet size distributions from chambers of different sizes can be matched by adjusting the total aerosol injection rate as the horizontal cross‐sectional area (i.e., as H 2 for constant aspect ratio). Injection of aerosols at a point versus distributed throughout the volume makes no difference for polluted conditions, but can lead to cloud droplet size distribution broadening in clean conditions. Cloud droplet growth by collision and coalescence leads to a broader right tail of the distribution compared to condensation growth alone, and this tail increases in magnitude and extent monotonically as the increase of chamber height. These results also have implications for scaling within turbulent, cloudy mixed‐layers in the atmosphere, such as fog layers.

54 ENVIRONMENTAL SCIENCES↗

High accuracy barrier heights, enthalpies, and rate coefficients for chemical reactions

Abstract Quantitative chemical reaction data, including activation energies and reaction rates, are crucial for developing detailed kinetic mechanisms and accurately predicting reaction outcomes. However, such data are often difficult to find, and high-quality datasets are especially rare. Here, we use CCSD(T)-F12a/cc-pVDZ-F12// ω B97X-D3/def2-TZVP to obtain high-quality single point calculations for nearly 22,000 unique stable species and transition states. We report the results from these quantum chemistry calculations and extract the barrier heights and reaction enthalpies to create a kinetics dataset of nearly 12,000 gas-phase reactions. These reactions involve H, C, N, and O, contain up to seven heavy atoms, and have cleaned atom-mapped SMILES. Our higher-accuracy coupled-cluster barrier heights differ significantly (RMSE of ∼5 kcal mol −1 ) relative to those calculated at ω B97X-D3/def2-TZVP. We also report accurate transition state theory rate coefficients $${k}_{\infty }(T)$$ k ∞ ( T ) between 300 K and 2000 K and the corresponding Arrhenius parameters for a subset of rigid reactions. We believe this data will accelerate development of automated and reliable methods for quantitative reaction prediction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Estimating viscosity of individual substrate-deposited particles from measurements of their height-to-width ratios

Airborne particles alter the radiative forcing of climate and have further consequences on air visibility, atmospheric chemistry, and human health. Recent studies reported the existence of highly viscous semisolid and even solid amorphous organic aerosol (OA) particles. Particle viscosity has an impact on the heterogeneous chemistry, gas-particle partitioning, and ice nucleation properties. Consequently, variations in particle viscosity must be considered when predicting the atmospheric impact of OA. Here, in this work, we use scanning electron microscopy (SEM) and scanning transmission X-ray microscopy (STXM) to estimate the viscosity of individual particles deposited on substrates based on their characteristic height-to-width ratios, which are affected by changes in morphology upon deposition. The height-to-width ratios obtained from SEM and STXM exhibit a strong correlation, demonstrating that both imaging approaches can be applied separately for viscosity assessment of the substrate-deposited particles. While these metrics are largely qualitative, this method enables rapid assessment of particle viscosity ranges, distinguishing between semisolid (>10 10 Pa·s), viscous (10 4– 10 8 Pa·s), and liquid (10°–10 1 Pa·s) particles within ensembles of ambient particles collected for microscopy studies.

54 ENVIRONMENTAL SCIENCES↗

Genetic mapping and prediction of flowering time and plant height in a maize Stiff Stalk MAGIC population

Abstract The Stiff Stalk heterotic pool is a foundation of US maize seed parent germplasm and has been heavily utilized by both public and private maize breeders since its inception in the 1930s. Flowering time and plant height are critical characteristics for both inbred parents and their test crossed hybrid progeny. To study these traits, a 6-parent multiparent advanced generation intercross population was developed including maize inbred lines B73, B84, PHB47 (B37 type), LH145 (B14 type), PHJ40 (novel early Stiff Stalk), and NKH8431 (B73/B14 type). A set of 779 doubled haploid lines were evaluated for flowering time and plant height in 2 field replicates in 2016 and 2017, and a subset of 689 and 561 doubled haploid lines were crossed to 2 testers, respectively, and evaluated as hybrids in 2 locations in 2018 and 2019 using an incomplete block design. Markers were derived from a practical haplotype graph built from the founder whole genome assemblies and genotype-by-sequencing and exome capture-based sequencing of the population. Genetic mapping utilizing an update to R/qtl2 revealed differing profiles of significant loci for both traits between 635 of the DH lines and 2 sets of 570 and 471 derived hybrids. Genomic prediction was used to test the feasibility of predicting hybrid phenotypes based on the per se data. Predictive abilities were highest on direct models trained using the data they would predict (0.55–0.63), and indirect models trained using per se data to predict hybrid traits had slightly lower predictive abilities (0.49–0.55). Overall, this finding is consistent with the overlapping and nonoverlapping significant quantitative trait loci found within the per se and hybrid populations and suggests that selections for phenology traits can be made effectively on doubled haploid lines before hybrid data is available.

Genetics & Heredity↗

Self-calibrating the look-elsewhere effect: fast evaluation of the statistical significance using peak heights

In experiments where one searches a large parameter space for an anomaly, one often finds many spurious noise-induced peaks in the likelihood. This is known as the look-elsewhere effect, and must be corrected for when performing statistical analysis. Here, this paper introduces a method to calibrate the false alarm probability (FAP), or p-value, for a given dataset by considering the heights of the highest peaks in the likelihood. Specifically, we derive an equation relating the global p-value to the rank and height of local maxima. In the simplest form of self-calibration, the look-elsewhere-corrected $\chi^2$ of a physical peak is approximated by the $\chi^2$ of the peak minus the $\chi^2$ of the highest noise-induced peak, with accuracy improved by considering lower peaks. In contrast to alternative methods, this approach has negligible computational cost as peaks in the likelihood are a byproduct of every peak-search analysis. We apply to examples from astronomy, including planet detection, periodograms, and cosmology.

79 ASTRONOMY AND ASTROPHYSICS↗

Heavy-ion fusion cross section formula and barrier height distribution

Methods for obtaining fusion cross section formulas are discussed, especially for those that take on an empirical form. A new expression starting with σ( E) = $\frac{1}{E}$ $\int ^{E}_{E_0}$ $(\int^{E'}_{E_0} B (E^\shortparallel) dE^\shortparallel)dE'$ has been explored. Here, B(E) is a reasonable, assumed function of the barrier height distribution, $\frac{d^2 (\sigma E)}{dE^2}$. Further, the resulting analytic cross section formula reproduces very well the excitation functions for many light and heavy fusion systems across wide energy ranges, when B(E) is assumed to be a multi-Gaussian function. This study offers an improved determination of the fusion barrier height distribution over other numerical techniques.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

The impact of the charge barrier height on Germanium (Ge) detectors with amorphous-Ge contacts for light dark matter searches

Germanium (Ge) detectors with ability of measuring a single electron–hole (e–h) pair are needed in searching for light dark matter (LDM) down to the MeV scale. We investigate the feasibility of Ge detectors with amorphous-Ge (a-Ge) contacts to achieve the sensitivity of measuring a single e-h pair, which requires extremely low leakage current. Three Ge detectors with a-Ge contacts are used to study the charge barrier height for blocking electrons and holes. Using the measured bulk leakage current and the Döhler–Brodsky model, we obtain the values for charge barrier height and the density of localized energy states near the Fermi energy level for the top and bottom contacts, respectively. We predict that the bulk leakage current is extremely small and can be neglected at helium temperature ( $$\sim $$ ~ 4 K). Thus, Ge detectors with a-Ge contacts possess the potential to measure a single e–h pair for detecting LDM particles.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

CHM-MS-net-Canopy-Height-Model

The CHM-MS-net Canopy Height Model is a MS-net neural network applied to high resolution satellite imagery to estimate tree height, tree location, and crown radius.

Atchley, Adam↗

Theoretical Understanding of the Linear Relationship between Convective Updrafts and Cloud-Base Height for Shallow Cumulus Clouds. Part II: Continental Conditions

This is the Part II of a two-part study that seeks a theoretical understanding of an empirical relationship for shallow cumulus clouds: subcloud updraft velocity covaries linearly with the cloud-base height. This work focuses on continental cumulus clouds that are more strongly forced by surface fluxes and more deviated from equilibrium than those over oceans (Part I). We use a simple analytical model for shallow cumulus that is well tested against a high-resolution (25 m in the horizontal) large-eddy simulation model. Consistent with a conventional idea, we find that surface Bowen ratio is the key variable that regulates the covariability of both parameters: under the same solar insolation, a drier surface allows for stronger buoyancy flux, triggering stronger convection that deepens the subcloud layer. We find that the slope of the Bowen-ratio-regulated relationship between the two parameters (defined as λ) is dependent on both the local time and the stability of the lower free atmosphere. The value of λ decreases with time exponentially from sunrise to early afternoon and linearly from early afternoon to sunset. The value of λ is larger in a more stable atmosphere. In addition, continental λ in the early afternoon more than doubles the oceanic λ. Validation of the theoretical results against ground observations over the Southern Great Plains shows a reasonable agreement. Physical mechanisms underlying the findings are explained from the perspective of different time scales at which updrafts and cloud-base height respond to a surface flux forcing.

54 ENVIRONMENTAL SCIENCES↗