Optimization of Aeolus' aerosol optical properties by maximum-likelihood estimation

The European Space Agency (ESA) Earth Explorer Mission Aeolus was launched in August 2018, carrying the first Doppler wind lidar in space. Its primary payload, the Atmospheric LAser Doppler INstrument (ALADIN), is an ultraviolet (UV) high-spectral-resolution lidar (HSRL) measuring atmospheric backscatter from air molecules and particles in two separate channels. The primary mission product is globally distributed line-of-sight wind profile observations in the troposphere and lower stratosphere. Atmospheric optical properties are provided as a spin-off product. Being an HSRL, Aeolus is able to independently measure the particle extinction coefficients, co-polarized particle backscatter coefficients and the co-polarized lidar ratio (the cross-polarized return signal is not measured). This way, the retrieval is independent of a priori lidar ratio information. The optical properties are retrieved using the standard correct algorithm (SCA), which is an algebraic inversion scheme and therefore sensitive to measurement noise. In this work, we reformulate the SCA into a physically constrained maximum-likelihood estimation (MLE) problem and demonstrate a predominantly positive impact and considerable noise suppression capabilities. These improvements originate from the use of all available information by the MLE in conjunction with the expected physical bounds concerning positivity and the expected range of the lidar ratio. To consolidate and to illustrate the improvements, the new MLE algorithm is evaluated against the SCA on end-to-end simulations of two homogeneous scenes and for real Aeolus data collocated with measurements by a ground-based lidar and the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite. The largest improvements were seen in the retrieval precision of the extinction coefficients and lidar ratio ranging up to 1 order of magnitude or more in some cases due to effective noise dampening. In real data cases, the increased precision of MLE with respect to the SCA is demonstrated by increased horizontal homogeneity and better agreement with the ground truth, though proper uncertainty estimation of MLE results is challenged by the constraints, and the accuracy of MLE and SCA retrievals can depend on calibration errors, which have not been considered.

Optical Properties of Cu2O Thin Films Impregnated with Carbon Nanotube (CNT)

This study investigates CNT-doped Cu2O thin film deposited by spray pyrolysis technique at a substrate temperature of 100°C. The samples were annealed at temperatures of 200°C and 230°C for 30 minutes. The effect of CNT doping on certain optical properties, such as extinction and absorption coefficients, a refractive index of doped Cu2O thin films were examined. The absorbance of the doped samples increases within the visible range and decreases in the ultraviolet range of the electromagnetic spectrum (EM). Both absorbance and extinction coefficients increased with temperature making the samples a good candidate for use as absorbance layer in device fabrication. In addition, there was an increase in direct bandgap with the increase in CNT concentration of the thin films. The result of the study revealed that CNT doping has a significant effect on the properties of Cu2O.

Modelling Wind Damage to Southeastern U.S. Trees: Effects of Wind Profile, Gaps, Neighborhood Interactions, and Wind Direction

Tree damage from a variety of types of wind events is widespread and of great ecological and economic importance. In terms of areas impacted, tropical storms have the most widespread effects on tropical and temperate forests, with southeastern U.S. forests particularly prone to tropical storm damage. This impact motivates attempts to understand the tree and forest characteristics that influence levels of damage. This study presents initial findings from a spatially explicit, individual-based mechanistic wind severity model, ForSTORM, parameterized from winching research on trees in southeastern U.S. This model allows independent control of six wind and neighborhood parameters likely to influence the patterns of wind damage, such as gap formation, the shape of the vertical wind profile, indirect damage, and support from neighbors. We arranged the subject trees in two virtual stands orientations with identical positions relative to each other, but with one virtual stand rotated 90 degrees from the other virtual stand – to explore the effect of wind coming from two alternative directions. The model reproduces several trends observed in field damage surveys, as well as analogous CWS models developed for other forests, and reveals unexpected insights. Wind profiles with higher extinction coefficients, or steeper decrease in wind speed from canopy top to lower levels, resulted in significantly higher critical wind speeds, thus reducing level of damage for a given wind speed. Three alternative formulations of wind profiles also led to significant differences in critical wind speed (CWS), although the effect of profile was less than effect of different extinction coefficients. The CWS differed little between the two alternative stand orientations. Support from neighboring trees resulted in significantly higher critical wind speeds, regardless of type of wind profile or spatial arrangement of trees. The presence or absence of gaps caused marginally significant different in CWS, while inclusion of indirect damage along with direct damage did not significantly change CWS from those caused by direct damage alone. Empirical research that could most benefit this modelling approach includes improving crown area measurement, refining drag coefficients, and development of a biomechanical framework for neighbor support.

Snow Depth Retrieval on Arctic Sea Ice Using Under-Ice Hyperspectral Radiation Measurements

Radiation transmitted through sea ice and snow has an important impact on the energy partitioning at the atmosphere-ice-ocean interface. Snow depth and ice thickness are crucial in determining its temporal and spatial variations. Under-ice surveys using autonomous robotic vehicles to measure transmitted radiation often lack coincident snow depth and ice thickness measurements so that direct relationships cannot be investigated. Snow and ice imprint distinct features on the spectral shape of transmitted radiation. Here, we use those features to retrieve snow depth. Transmitted radiance was measured underneath landfast level first-year ice using a remotely operated vehicle in the Lincoln Sea in spring 2018. Colocated measurements of snow depth and ice thickness were acquired. Constant ice thickness, clear water conditions, and low in-ice biomass allowed us to separate the spectral features of snow. We successfully retrieved snow depth using two inverse methods based on under-ice optical spectra with 1) normalized difference indices and 2) an idealized two-layer radiative transfer model including spectral snow and sea ice extinction coefficients. The retrieved extinction coefficients were in agreement with previous studies. We then applied the methods to continuous time series of transmittance and snow depth from the landfast first-year ice and from drifting, melt-pond covered multiyear ice in the Central Arctic in autumn 2018. Both methods allow snow depth retrieval accuracies of approximately 5 cm. Our results show that atmospheric variations and absolute light levels have an influence on the snow depth retrieval.

Numerical Study of the Influence of Coupling Interface Emissivity on Aerogel Metal Thermal Protection Performance

For aerogels in metal thermal protection system (MTPS), radiative heat transfer will participate in the thermal transport process. Therefore, the influence of the emissivity of the coupling interface between metal and aerogels on thermal insulation performance is considered an important research focus. In this paper, CFD numerical simulation is performed to study the influence of emissivity on the performance with different extinction coefficients at different boundary temperatures. The finite volume method and the discrete ordinate method are used to solve the govern equations. The results show that when the boundary temperatures are 600 K and 2100 K, the extinction coefficient is 50 m−1, and the reduction percentage of the effective thermal conductivity with an emissivity of 0.2 can be up to 47.5% and 69.8%, compared to the system with an emissivity of 1. Thus, the reduction in emissivity has a good effect on the thermal insulation performance of the MTPS at a higher boundary temperature for materials with small extinction coefficients.

Assessment of NAAPS-RA performance in Maritime Southeast Asia during CAMP²Ex

Monitoring and modeling aerosol particle lifecycle in Southeast Asia (SEA) is challenged by high cloud cover, complex meteorology, and the wide range of aerosol species, sources, and transformations found throughout the region. Satellite observations are limited, and there are few in situ observations of aerosol extinction profiles, aerosol properties, and environmental conditions. Therefore, accurate aerosol model outputs are crucial for the region. This work evaluates the Navy Aerosol Analysis and Prediction System Reanalysis (NAAPS-RA) aerosol optical thickness (AOT) and light extinction products using airborne aerosol and meteorological measurements from the Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP2Ex) in SEA. Modeled AOTs and extinction coefficients were compared to those retrieved with a High Spectral Resolution Lidar (HSRL-2). Correlations were highest for AOT in the mixed layer (AOTML; R2 = 0.83, bias = 0.00, root mean square error [RMSE] = 0.03) compared to total AOT (R2 = 0.68, bias = 0.01, RMSE = 0.14), although the correlations between the observations and 1° × 1° degree NAAPS-RA outputs were weaker in regions with strong gradients in aerosol properties, such as near areas of active convection. Correlations between simulated and retrieved aerosol extinction coefficients were highest from 145–500 m (R2 = 0.75, bias = 0.01 km−1, RMSE = 0.08 km−1) and decreased with increasing altitude (R2 = 0.69 and 0.26, bias = 0.00 and 0.00 km−1, RMSE = 0.09 and 0.00 km−1 for 500–1500 m and > 1500 m, respectively), which was likely a result of the use of bulk cloud mixing parameterizations. We also investigated the role of possible relative humidity (RH) errors in extinction simulations. Despite negative biases in modeled RH (−4.9, −7.7, and −2.3 % for altitudes < 500 m, 500–1500 m, and > 1500 m, respectively), AOT and extinction agreement with the HSRL-2 did not change significantly at any altitude when RHs from dropsondes were substituted into the model. Improvements may have been stunted due to errors in how NAAPS-RA modeled physics of particle hygroscopic growth, dry particle mass concentrations, and/or dry mass extinction efficiencies, especially when combined with AOT corrections from data assimilation. Specifically, the model overestimated the hygroscopicity of (i) smoke particles from biomass burning in the Maritime Continent (MC), and (ii) anthropogenic emissions transported from East Asia. This work provides insight into how certain environmental and microphysical properties influence AOT and extinction simulations, which can then be interpreted in the context of modeling global concentrations of particle mass and cloud condensation nuclei (CCN).

Simple method to determine the concentration and incorporation ratio of ruthenium-labeled antibodies

Aim: Ruthenium-labeled antibodies are commonly used detection reagents in bioanalysis assays and must be characterized to ensure quality. The aim of this work was to develop a method to determine the concentration and incorporation ratio (the degree of labeling [DOL]) of ruthenium-labeled antibodies by UV/VIS spectroscopy. Materials & methods: Free SULFO-TAG compound was scanned using UV/VIS and showed an absorbance peak at 292 nm. In contrast, antibodies demonstrate UV absorbance at 280 nm. After experimentally determining the extinction coefficients at 280 and 292 nm of free ruthenium and antibody, we generated a formula based on the Beer–Lambert law that calculates both concentration and DOL of these ruthenium-labeled antibodies. Conclusion: The concentration and DOL values determined by our method were comparable to those determined from bicinchoninic acid and LC/MS for the same reagents. This method creates a faster and more accessible reagent characterization process that uses far less reagent than the more traditional alternatives.

Reduced ice number concentrations in contrails from low-aromatic biofuel blends

Sustainable aviation fuels can reduce contrail ice numbers and radiative forcing by contrail cirrus. We measured apparent ice emission indices for fuels with varying aromatic content at altitude ranges of 9.1–9.8 and 11.4–11.6 km. Measurement data were collected during the ECLIF II/NDMAX flight experiment in January 2018. The fuels varied in both aromatic quantity and type. Between a sustainable aviation fuel blend and a reference fuel Jet A-1, a maximum reduction in apparent ice emission indices of 40 % was found. We show vertical ice number and extinction distributions for three different fuels and calculate representative contrail optical depths. Optical depths of contrails (0.5–3 min in age) were reduced by 40 % to 52 % for a sustainable aviation fuel compared to the reference fuel. Our measurements suggest that sustainable aviation fuels result in reduced ice particle numbers, extinction coefficients, optical depth and climate impact from contrails.