Thermodynamic Profiles Research Articles

Passive ground-based remote sensing of radiation fog

Abstract. Accurate boundary layer temperature and humidity profiles are crucial for successful forecasting of fog, and accurate retrievals of liquid water path are important for understanding the climatological significance of fog. Passive ground-based remote sensing systems such as microwave radiometers (MWRs) and infrared spectrometers like the Atmospheric Emitted Radiance Interferometer (AERI), which measures spectrally resolved infrared radiation (3.3 to 19.2 µm), can retrieve both thermodynamic profiles and liquid water path. Both instruments are capable of long-term unattended operation and have the potential to support operational forecasting. Here we compare physical retrievals of boundary layer thermodynamic profiles and liquid water path during 12 cases of thin (LWP<40 g m−2) supercooled radiation fog from an MWR and an AERI collocated in central Greenland. We compare both sets of retrievals to in-situ measurements from radiosondes and surface-based temperature and humidity sensors. The retrievals based on AERI observations accurately capture shallow surface-based temperature inversions (0–10 m a.g.l.) with lapse rates of up to −1.2 ∘C m−1, whereas the strength of the surface-based temperature inversions retrieved from MWR observations alone are uncorrelated with in-situ measurements, highlighting the importance of constraining MWR thermodynamic profile retrievals with accurate surface meteorological data. The retrievals based on AERI observations detect fog onset (defined by a threshold in liquid water path) earlier than those based on MWR observations by 25 to 185 min. We propose that, due to the high sensitivity of the AERI instrument to near-surface temperature and small changes in liquid water path, the AERI (or an equivalent infrared spectrometer) could be a useful instrument for improving fog monitoring and nowcasting, particularly for cases of thin radiation fog under otherwise clear skies, which can have important radiative impacts at the surface.

Quantifying the Impact of Precipitation-Type Algorithm Selection on the Representation of Freezing Rain in an Ensemble of Regional Climate Model Simulations

Abstract Given their potentially severe impacts, understanding how freezing rain events may change as the climate changes is of great importance to stakeholders including electrical utility companies and local governments. Identification of freezing rain in climate models requires the use of precipitation-type algorithms, and differences between algorithms may lead to differences in the types of precipitation identified for a given thermodynamic profile. We explore the uncertainty associated with algorithm selection by applying four algorithms (Cantin and Bachand, Baldwin, Ramer, and Bourgouin) offline to an ensemble of simulations of the fifth-generation Canadian Regional Climate Model (CRCM5) at 0.22° grid spacing. First, we examine results for the CRCM5 driven by ERA-Interim reanalysis to analyze how well the algorithms reproduce the recent climatology of freezing rain and how results vary depending on algorithm parameters and the characteristics of available model output. We find that while the Ramer and Baldwin algorithms tend to be better correlated with observations than Cantin and Bachand or Bourgouin, their results are highly sensitive to algorithm parameters and to the number of pressure levels used. We also apply the algorithms to four CRCM5 simulations driven by different global climate models (GCMs) and find that the uncertainty associated with algorithm selection is generally similar to or greater than that associated with choice of driving GCM for the recent past climate. Our results provide guidance for future studies on freezing rain in climate simulations and demonstrate the importance of accounting for uncertainty between algorithms when identifying precipitation type from climate model output. Significance Statement Freezing rain events and ice storms can have major consequences, including power outages and dangerous road conditions. It is therefore important to understand how climate change might affect the frequency and severity of these events. One source of uncertainty in climate studies of these events is related to the choice of algorithm used to detect freezing rain in model output. We compare the frequency of freezing rain identified using four different algorithms and find sometimes large differences depending on the algorithm chosen over some regions. Our findings highlight the importance of taking this source of uncertainty into account and will provide researchers with guidance as to which algorithms are best suited for climate studies of freezing rain.

The Impact of Nonzenith Elevation Angles on Ground-Based Infrared Thermodynamic Retrievals

Abstract Observing thermodynamic profiles within the planetary boundary layer is essential to understanding and predicting atmospheric phenomena because of the significant exchange of sensible and latent heat between the land and atmosphere within that layer. The Atmospheric Emitted Radiance Interferometer (AERI) is a ground-based infrared spectrometer used to obtain the vertical profiles of temperature and water vapor mixing ratio. Most AERIs are only capable of zenith views, although the Marine AERI (M-AERI) has a design that allows it to view various elevation angles. In this study, we quantify the improvement in the information content and accuracy of the retrieved profiles when nonzenith angles are included, as is common with microwave radiometer profilers. The impacts of the additional scan angles are quantified through both a synthetic study and with M-AERI observations from the ARM Cloud Aerosol Precipitation Experiment (ACAPEX) campaign. The simulation study shows that low elevation angles contain more information content for temperature whereas high elevation angles have more information content for water vapor. Outside of very humid environments, the addition of low elevation angles also results in lower root-mean-square errors when compared with high angles for both temperature and water vapor mixing ratio, although this is primarily a result of averaging multiple observations together to reduce instrument noise. Real-world results from the ACAPEX dataset indicate similar results as were found for the simulation study, although not all predicted benefits are realized because of the small sample size and observational uncertainties.

Ice Aggregation in Low‐Level Mixed‐Phase Clouds at a High Arctic Site: Enhanced by Dendritic Growth and Absent Close to the Melting Level

AbstractLow‐level mixed‐phase clouds (MPCs) occur extensively in the Arctic, and are known to play a key role for the energy budget. While their characteristic structure is nowadays well understood, the significance of different precipitation‐formation processes, such as aggregation and riming, is still unclear. Using a 3‐year data set of vertically pointing W‐band cloud radar and K‐band Micro Rain Radar (MRR) observations from Ny‐Ålesund, Svalbard, we statistically assess the relevance of aggregation in Arctic low‐level MPCs. Combining radar observations with thermodynamic profiling, we find that larger snowflakes (mass median diameter larger than 1 mm) are predominantly produced in low‐level MPCs whose mixed‐phase layer is at temperatures between −15 and −10°C. This coincides with the temperature regime known for favoring aggregation due to growth and subsequent mechanical entanglement of dendritic crystals. Doppler velocity information confirms that these signatures are likely due to enhanced ice particle growth by aggregation. Signatures indicative of enhanced aggregation are however not distributed uniformly across the cloud deck, and only observed in limited regions, suggesting a link with dynamical effects. Low Doppler velocity values further indicate that significant riming of large particles is unlikely at temperatures colder than −5°C. Surprisingly, we find no evidence of enhanced aggregation at temperatures warmer than −5°C, as is typically observed in deeper cloud systems. Possible reasons are discussed, likely connected to the ice habits that form at temperatures warmer than −10°C, increased riming, and lack of particle populations characterized by broader size distributions precipitating from higher altitudes.

Insight into Thermodynamic and Kinetic Profiles in Small-Molecule Optimization.

Structure-activity relationships (SARs) and structure-property relationships (SPRs) have been considered the most important factors during the drug optimization process. For medicinal chemists, improvements in the potencies and druglike properties of small molecules are regarded as their major goals. Among them, the binding affinity and selectivity of small molecules on their targets are the most important indicators. In recent years, there has been growing interest in using thermodynamic and kinetic profiles to analyze ligand-receptor interactions, which could provide not only binding affinities but also detailed binding parameters for small-molecule optimization. In this perspective, we are trying to provide an insight into thermodynamic and kinetic profiles in small-molecule optimization. Through a highlight of strategies on the small-molecule optimization with specific cases, we aim to put forward the importance of structure-thermodynamic relationships (STRs) and structure-kinetic relationships (SKRs), which could provide more guidance to find safe and effective small-molecule drugs.

Understanding the pH Dependence of Supersaturation State—A Case Study of Telmisartan

Creating supersaturating drug delivery systems to overcome the poor aqueous solubility of active ingredients became a frequent choice for formulation scientists. Supersaturation as a solution phenomenon is, however, still challenging to understand, and therefore many recent publications focus on this topic. This work aimed to investigate and better understand the pH dependence of supersaturation of telmisartan (TEL) at a molecular level and find a connection between the physicochemical properties of the active pharmaceutical ingredient (API) and the ability to form supersaturated solutions of the API. Therefore, the main focus of the work was the pH-dependent thermodynamic and kinetic solubility of the model API, TEL. Based on kinetic solubility results, TEL was observed to form a supersaturated solution only in the pH range 3–8. The experimental thermodynamic solubility-pH profile shows a slight deviation from the theoretical Henderson–Hasselbalch curve, which indicates the presence of zwitterionic aggregates in the solution. Based on pKa values and the refined solubility constants and distribution of macrospecies, the pH range where high supersaturation-capacity is observed is the same where the zwitterionic form of TEL is present. The existence of zwitterionic aggregation was confirmed experimentally in the pH range of 3 to 8 by mass spectrometry.

The interplay between AGN feedback and precipitation of the intracluster medium in simulations of galaxy groups and clusters

ABSTRACT Using high-resolution hydrodynamical simulations of idealized galaxy clusters, we study the interaction between the brightest cluster galaxy, its supermassive black hole (BH), and the intracluster medium (ICM). We create initial conditions for which the ICM is in hydrostatic equilibrium within the gravitational potential from the galaxy and an NFW dark matter halo. Two free parameters associated with the thermodynamic profiles determine the cluster gas fraction and the central temperature, where the latter can be used to create cool-core or non-cool-core systems. Our simulations include radiative cooling, star formation, BH accretion, and stellar and active galactic nucleus (AGN) feedback. Even though the energy of AGN feedback is injected thermally and isotropically, it leads to anisotropic outflows and buoyantly rising bubbles. We find that the BH accretion rate (BHAR) is highly variable and only correlates strongly with the star formation rate (SFR) and the ICM when it is averaged over more than $1~\rm Myr$. We generally find good agreement with the theoretical precipitation framework. In $10^{13}~\rm M_\odot$ haloes, AGN feedback quenches the central galaxy and converts cool-core systems into non-cool-core systems. In contrast, higher mass, cool-core clusters evolve cyclically. Episodes of high BHAR raise the entropy of the ICM out to the radius, where the ratio of the cooling time and the local dynamical time tcool/tdyn > 10, thus suppressing condensation and, after a delay, the BHAR. The corresponding reduction in AGN feedback allows the ICM to cool and become unstable to precipitation, thus initiating a new episode of high SFR and BHAR.

Structural aspects of formetanate hydrochloride binding with human serum albumin using spectroscopic and molecular modeling techniques

Formetanate Hydrochloride (FMT), a highly potent chemical, acts as an insecticide, acaricide, and miticide to protect various fruits and vegetables. The widespread use elevates concern about its presence in the ecosystem, impact upon human health via interaction with biological receptors. Spectroscopic and molecular modeling techniques at different temperatures were used to investigate the binding of FMT with Human serum albumin (HSA) at the molecular level. The experimental and computational results have provided the binding affinity, binding mode, conformational flexibility, and thermodynamic profile of FMT-HSA complex. The FMT binding appears to be spontaneous, and entropy driven. Overall binding affinity of FMT falls within −7.29 to −4.67 Kcal M-1. FMT binds in domain I, subdomain IA of HSA and is stabilized by hydrophobic interactions. Molecular dynamics simulations of the FMT-HSA complex over 100 ns at 288 K, 298 K and 308 K indicated that FMT showed minor adjustments in conformation and placement within the binding site. While, MM/PBSA analysis of the complex provided individual contributions of energy terms. Quantum mechanical (QM) calculations were used to calculate absolute energy values of different poses of FMT which in turn showed minor variations in energy suggesting slight conformational variation in the bound form. The computational results are in agreement with experimental findings.

Tropical Thermodynamic–Convection Coupling in Observations and Reanalyses

Abstract This study examines thermodynamic–convection coupling in observations and reanalyses, and attempts to establish process-level benchmarks needed to guide model development. Thermodynamic profiles obtained from the NOAA Integrated Global Radiosonde Archive, COSMIC-1 GPS radio occultations, and several reanalyses are examined alongside Tropical Rainfall Measuring Mission precipitation estimates. Cyclical increases and decreases in a bulk measure of lower-tropospheric convective instability are shown to be coupled to the cyclical amplification and decay of convection. This cyclical flow emerges from conditional-mean analysis in a thermodynamic space composed of two components: a measure of “undiluted” instability, which neglects lower-free-tropospheric (LFT) entrainment, and a measure of the reduction of instability by LFT entrainment. The observational and reanalysis products examined share the following qualitatively robust characterization of these convective cycles: increases in undiluted instability tend to occur when the LFT is less saturated, are followed by increases in LFT saturation and precipitation rate, which are then followed by decreases in undiluted instability. Shallow, convective, and stratiform precipitation are coupled to these cycles in a manner consistent with meteorological expectations. In situ and satellite observations differ systematically from reanalyses in their depictions of lower-tropospheric temperature and moisture variations throughout these convective cycles. When using reanalysis thermodynamic fields, these systematic differences cause variations in lower-free-tropospheric saturation deficit to appear less influential in determining the strength of convection than is suggested by observations. Disagreements among reanalyses, as well as between reanalyses and observations, pose significant challenges to process-level assessments of thermodynamic–convection coupling.

Facile Synthesis of a Fluorinated-Squaramide Covalent Organic Framework for the Highly Efficient and Broad-Spectrum Removal of Per- and Polyfluoroalkyl Pollutants.

The escalating contamination by per- and polyfluoroalkyl substances (PFAS) has become an urgent issue in recent years, and the structural diversity of PFAS is the major challenge for effective pollution control. Herein, we take the intrinsic advantages of squaramide and prepare a new two-dimensional covalent organic framework (FSQ-1) that exhibits broad-spectrum PFAS affinity. The tailor-made linker forges hydrogen-bond donors, hydrogen-bond acceptors, and fluorophilic segments into one framework. The obtained material exhibits multipoint and multitype affinity to PFAS with different structures, by which high-efficient and broad-spectrum removal of various PFAS can be simultaneously achieved. Notably, the thermodynamic profiles provided by isothermal titration calorimetry (ITC) experiments further illustrate the underlying mechanism of the broad-spectrum affinity. FSQ-1 can also be applied for efficient PFAS extraction in trace-level PFAS analysis.

Facile Synthesis of a Fluorinated‐Squaramide Covalent Organic Framework for the Highly Efficient and Broad‐Spectrum Removal of Per‐ and Polyfluoroalkyl Pollutants

AbstractThe escalating contamination by per‐ and polyfluoroalkyl substances (PFAS) has become an urgent issue in recent years, and the structural diversity of PFAS is the major challenge for effective pollution control. Herein, we take the intrinsic advantages of squaramide and prepare a new two‐dimensional covalent organic framework (FSQ‐1) that exhibits broad‐spectrum PFAS affinity. The tailor‐made linker forges hydrogen‐bond donors, hydrogen‐bond acceptors, and fluorophilic segments into one framework. The obtained material exhibits multipoint and multitype affinity to PFAS with different structures, by which high‐efficient and broad‐spectrum removal of various PFAS can be simultaneously achieved. Notably, the thermodynamic profiles provided by isothermal titration calorimetry (ITC) experiments further illustrate the underlying mechanism of the broad‐spectrum affinity. FSQ‐1 can also be applied for efficient PFAS extraction in trace‐level PFAS analysis.

Supersonic–subsonic transition region in radiative heat flow via self-similar solutions

We study the radiative hydrodynamics flow of radiation-driven heat waves in hot dense plasmas, using approximate self-similar solutions. Specifically, we have focused on the intermediate regime between the pure radiative supersonic flow and the pure subsonic regime. These two regimes were investigated using both exact self-similar solutions and numerical simulations; however, most of the study used numerical simulations, mainly because the radiative heat wave and the shock regions are not self-similar altogether. In a milestone work [Garnier et al., “Self-similar solutions for a nonlinear radiation diffusion equation,” Phys. Plasmas 13, 092703 (2006)], it was found that for a specific power law dependency temperature profile, a unique exact self-similar solution exists that is valid for all physical regimes. In this work, we approximate Garnier's exact solution for a general power-law temperature-dependency, using simple analytical considerations. This approximate solution yields a good agreement compared to numerical simulations for the different thermodynamic profiles within the expected range of validity. In addition, we offer an approximate solution for the energies absorbed in the matter, again, for a general power-law temperature profile. Our approximate self-similar solution for the energy yields very good results compared to exact numerical simulations for both gold and Ta2O5. We also set a comparison of our self-similar solutions with the results of an experiment for radiation temperature measurement in a Hohlraum in low-density foams that is addressed directly to the intermediate regime, yielding a good agreement and similar trends. The different models as well as the numerical simulations are powerful tools to analyze the supersonic–subsonic transition region.

High and temperature-insensitive piezoelectric performance in the lead-free Sm-doped BiFeO3–BaTiO3 ceramics with high Curie temperature

Large sensor piezoelectric constant (d33 = 334 pC/N) and superior actuator piezoelectric constant (d33* = 552 pm/V) as well as a high Curie temperature (TC = 454 °C) were obtained simultaneously in the lead-free 0.67Bi1.03FeO3-0.33Ba1-xSmxTiO3 ceramics. Such an excellent and temperature-insensitive piezoelectric performance with only 10% temperature variation of piezoelectric strain at the range of 25–125 °C is highly desirable for real applications. The structural origin of the enhanced piezoelectric performance is mainly attributed to the morphotropic phase boundary and the highest known tetragonality (cT/aT = 1.02) in such materials. Transmission electron microscopy and electro-mechanical phenomenological theory demonstrate that the superior d33 and d33* are associated with the hybrids nanodomains (60–90 nm) and flattened thermodynamic energy profile owing to the local structure heterogeneity. These results are superior as the piezoelectric properties are temperature-independent and the material has large d33*, and high TC compared to other lead-free piezoelectric ceramics.

A Novel Machine Learning Algorithm for Cloud Detection Using AERI Measurement Data

Infrared hyperspectral remote sensing has been widely used in the field of meteorology. Many scientists have carried out research on inversion methods of meteorological elements such as thermodynamic profile, boundary layer height, cloud base height, etc. In this study, a method based on machine learning for cloud detection using ground-based infrared hyperspectral radiation data is proposed. The features of outliers, the cloudy and cloud-free data of Atmospheric Emitted Radiance Interferometer (AERI) radiation are extracted. The “reference values” of cloudy and cloud-free are determined based on the observation data of Vaisala CL31 ceilometer within the time range of 8 min before the corresponding time of AERI. A support vector machine (SVM) algorithm is used for training. The dataset comes from the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site and North Slope Alaska (NSA) site from 2015 to 2017, and the ARM West Antarctic Radiation Experiment (AWARE) site in 2016 is also analyzed. The instruments used in this paper include AERI, ceilometer, etc. The experimental results reveal that the agreement of cloud detection results between the proposed algorithm and ceilometer is about 93% at each site. However, for high clouds or optically thin clouds, the agreement will decrease.

Mechanistic Studies Yield Improved Protocols for Base-Catalyzed Anti-Markovnikov Alcohol Addition Reactions.

The catalytic anti-Markovnikov addition of alcohols to simple alkenes is a longstanding synthetic challenge. We recently disclosed the use of organic superbase catalysis for the nucleophilic addition of alcohols to activated styrene derivatives. This article describes mechanistic studies on this reversible reaction, including thermodynamic and kinetic profiling as well as computational modeling. Our findings show the negative entropy of addition is counterbalanced by an enthalpy that is most favored in nonpolar solvents. However, a large negative alcohol rate order under these conditions indicates excess alcohol sequesters the active alkoxide ion pairs, slowing the reaction rate. These observations led to an unexpected solution to a thermodynamically challenging reaction: use of less alcohol enables faster addition, which in turn allows for lower reaction temperatures to counteract Le Chatelier's principle. Thus, our original method has been improved with new protocols that do not require excess alcohol stoichiometry, enable an expanded alkene substrate scope, and allow for the use of more practical catalyst systems. The generality of this insight for other challenging hydroetherification reactions is also demonstrated through new alkenol cyclization and oxa-Michael addition reactions.

Exploring Glycan Binding Specificity of Odorranalectin by Alanine Scanning Library.

Fluorescently labelled alanine scan analogues of odorranalectin (OL), a cyclic peptide that exhibits lectin like properties, were screened for binding BSA-conjugated monosaccharides using an enzyme-linked lectin assay (ELLA). Results revealed that Lys5, Phe7, Tyr9, Gly12, Leu14, and Thr17 were crucial for binding BSA-L-fucose, BSA-D-galactose and BSA-N-acetyl-D-galactosamine. Notably, Ala substitution of Ser3, Pro4, and Val13 resulted in higher binding affinities compared to the native OL. The obtained data also indicated that Arg8 plays an important role in differentiation of binding for BSA-L-fucose/D-galactose from BSA-N-acetyl-D-galactosamine. The thermodynamics of binding of the selected alanine analogues was evaluated by isothermal titration calorimetry. Low to moderate binding affinities were determined for the tetravalent MUC1 glycopeptide and asialofetuin, respectively, and high for the fucose rich polysaccharide, fucoidan. The thermodynamic profile of interactions with asialofetuin exhibits shift to an entropy-driven mechanism compared to the fucoidan, which displayed an enthalpyentropy compensation, typically associated with the carbohydratelectin recognition process.

PO-615-08 SINGLE SENSOR VERSUS MULTI-SENSOR ESOPHAGEAL MONITORING: WHAT ARE WE MISSING?

Esophageal temperature monitors are often used to decrease risk of esophageal injury during atrial fibrillation ablation. Multi-sensor monitors have been shown to have a superior thermodynamic profile in radiofrequency ablation, but there is limited data on single versus multi-electrode temperature discrepancies in cryoballoon ablation. We aim to evaluate temperature differences in the Circa S-Cath, a multi-sensor esophageal probe, to investigate its potential benefits over a single sensor probe in cryoablation. A total of 15 patients underwent cryoballoon ablation for atrial fibrillation under general anesthesia. A Circa probe was placed oropharyngeally after intubation. The Circa Esophageal Temperature Monitor has 12 sensors total located 8mm apart. Each sensor has a radiopaque marker and collects a temperature to the nearest 10th of a degree every half second. Position of the Crica probe could be adjusted under fluoroscopy. In the total of 15 patients, a minimum esophageal temperature below 25 °C was recorded in 8 cases during cryoablation. The lowest esophageal temperature did not occur in the same sensor for all cases or even freezes in the same patient. Sensor 7 recorded the coldest temperature in 7/15 of these freezes, Sensor 8 recorded 3/15, Sensor 10 recorded 2/15, and Sensors 4, 5, and 10 recorded one each. When compared to neighboring sensors, the largest difference between neighboring sensors was 13.14 degrees, with a range of 5.6 to 19.9 degrees. The disparity between neighboring temperature sensors suggest that single sensor probes are insufficient to detect the lowest temperature of the esophagus. Continuation of cryoablation to very low temperatures could increase risk of collateral injury to the esophagus. Use of multi-sensor temperature probes helps in accurately reflecting the coldest temperature point of the esophagus during cryoablation. Similar discrepancy may also be seen in radiofrequency ablation.

Unravelling functions of halogen substituents in the enantioseparation of halogenated planar chiral ferrocenes on polysaccharide-based chiral stationary phases: experimental and electrostatic potential analyses

Planar chiral halogenated ferrocenes have come in useful as synthetic intermediates over the years, allowing for the preparation of functionalized derivatives for catalysis, material science, optoelectronics, and medicinal chemistry. Despite their chemical interest, few halogenated planar chiral ferrocenes have been prepared in enantiopure form by asymmetric synthesis so far. Enantioselective HPLC on polysaccharide-based chiral stationary phases (CSPs) has been used for resolving planar chiral ferrocenes making both enantiomers available. However, the enantioseparation of derivatives containing halogens or alkyl groups exclusively remains rather challenging. Given this context, in this study the enantioseparation of eleven dihalogenated planar chiral ferrocenes was systematically explored by using five polysaccharide-based CSPs under multimodal elution conditions. Baseline enantioseparations were achieved for nine analytes with separation factors (α) ranging from 1.15 to 1.66. Thermodynamic quantities associated with the enantioseparations were derived from van't Hoff plots, and for 1-halo-2-(iodoethynyl)ferrocenes (1-halogen=F, Cl, Br) halogen-dependent thermodynamic profiles were identified on a cellulose tris(3,5-dimethylphenylcarbamate)-based column. The impact of CSP structure and mobile phase (MP) polarity on the enantioseparation was evaluated. In addition, with the aim to unravel the functions of halogen substituents in mechanisms and noncovalent interactions underlying selector-selectand complex formation at molecular level, local electron charge density of specific molecular regions of the interacting partners were evaluated in terms of calculated electrostatic potential (V) and related source function (SF) contributions. On this basis, the impact of halogen type and position on the enantioseparation was investigated by correlating theoretical and experimental data.

Evaluating convective planetary boundary layer height estimations resolved by both active and passive remote sensing instruments during the CHEESEHEAD19 field campaign

Abstract. During the Chequamegon Heterogeneous Ecosystem Energy-balance Study Enabled by a High-density Extensive Array of Detectors 2019 (CHEESEHEAD19) field campaign, held in the summer of 2019 in northern Wisconsin, USA, active and passive ground-based remote sensing instruments were deployed to understand the response of the planetary boundary layer to heterogeneous land surface forcing. These instruments include radar wind profilers, microwave radiometers, atmospheric emitted radiance interferometers, ceilometers, high spectral resolution lidars, Doppler lidars, and collaborative lower-atmospheric mobile profiling systems that combine several of these instruments. In this study, these ground-based remote sensing instruments are used to estimate the height of the daytime planetary boundary layer, and their performance is compared against independent boundary layer depth estimates obtained from radiosondes launched as part of the field campaign. The impact of clouds (in particular boundary layer clouds) on boundary layer depth estimations is also investigated. We found that while all instruments are overall able to provide reasonable boundary layer depth estimates, each of them shows strengths and weaknesses under certain conditions. For example, radar wind profilers perform well during cloud-free conditions, and microwave radiometers and atmospheric emitted radiance interferometers have a very good agreement during all conditions but are limited by the smoothness of the retrieved thermodynamic profiles. The estimates from ceilometers and high spectral resolution lidars can be hindered by the presence of elevated aerosol layers or clouds, and the multi-instrument retrieval from the collaborative lower atmospheric mobile profiling systems can be constricted to a limited height range in low-aerosol conditions.

Planetary boundary layer height retrieval from a diode-laser-based high spectral resolution lidar

The planetary boundary layer height (PBLH) is an essential parameter for weather forecasting and climate modeling. The primary methods for obtaining the PBLH include radiosonde measurements of atmospheric parameters and lidar measurements, which track aerosol layers in the lower atmosphere. Radiosondes provide the parameters to determine the PBLH but cannot monitor changes over a diurnal cycle. Lidar instruments can track the temporal variability of the PBLH and account for spatial variability when operated in a network configuration. The networkable micropulse DIAL (MPD) instruments for thermodynamic profiling are based on diode-laser technology that is eye-safe and cost-effective and has demonstrated long-term autonomous operation. We present a retrieval algorithm for determining the PBLH from the quantitative aerosol profiling capability of the high spectral resolution channel of the MPD. The PBLH is determined using a Haar wavelet transform (HWT) method that tracks aerosol layers in the lower atmosphere. The PBLH from the lidar is compared with the PBLH determined from potential temperature profiles from radiosondes. In many cases, good agreement among the PBLH retrievals was seen. However, the radiosonde retrieval often missed the lowest inversion layer when several layers were present, while the HWT could track the lowest layer.