Compact meta-spectral image sensor for mobile applications

We have demonstrated a compact and efficient metasurface-based spectral imager for use in the near-infrared range. The spectral imager was created by fabricating dielectric multilayer filters directly on top of the CMOS image sensor. The transmission wavelength for each spectral channel was selected by embedding a Si nanopost array of appropriate dimensions within the multilayers on the corresponding pixels, and this greatly simplified the fabrication process by avoiding the variation of the multilayer-film thicknesses. The meta-spectral imager shows high efficiency and excellent spectral resolution up to 2.0 nm in the near-infrared region. Using the spectral imager, we were able to measure the broad spectra of LED emission and obtain hyperspectral images from wavelength-mixed images. This approach provides ease of fabrication, miniaturization, low crosstalk, high spectral resolution, and high transmission. Our findings can potentially be used in integrating a compact spectral imager in smartphones for diverse applications.

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.

iSHELL: a 1–5 micron R = 80,000 Immersion Grating Spectrograph for the NASA Infrared Telescope Facility

iSHELL is a 1.06–5.3 μm high spectral resolution spectrograph built for the 3.2 m NASA Infrared Telescope Facility (IRTF) on Maunakea, Hawaii. Dispersion is accomplished with a silicon immersion grating in order to keep the instrument small enough to be mounted at the Cassegrain focus of the telescope. The white pupil spectrograph produces resolving powers of up to about R ≡ λ/δλ = 80,000 (0.″375 slit). Cross-dispersing gratings mounted in a tiltable mechanism allow observers to select different wavelength ranges and, in combination with a slit wheel and Dekker mechanism, slit widths ranging from 0.″375 to 4.″0 and slit lengths ranging from 5″ to 25″. One Teledyne 2048 × 2048 HAWAII-2RG array is used in the spectrograph, and one Raytheon 512 × 512 Aladdin 2 array is used in a 1–5 μm slit viewer for object acquisition, guiding, and scientific imaging. iSHELL has been in productive regular use on IRTF since first light in 2016 September. In this paper we discuss details of the science case, design, construction and astronomical use of iSHELL.

Monitoring the chemical changes in fingermark residue over time using synchrotron infrared spectroscopy

Degradation of fingermark residue has a major impact on the successful forensic detection of latent fingermarks. The time course of degradation has been previously explored with bulk chemical analyses, but little is known about chemical alterations at the micron-scale. Here we report the use of synchrotron-sourced attenuated total reflection-Fourier transform infrared (ATR-FTIR) microscopy to provide spatio-temporal resolution of chemical changes within fingermark droplets, as a function of time since deposition. Eccrine and sebaceous material within natural fingermark droplets were imaged on the micron scales at hourly intervals for the first 6 – 12 hours after deposition, revealing that substantial dehydration occurred within the first 8 hours. Changes to lipid material was more varied, with samples exhibiting an increase or decrease in lipid concentration due to the degradation and redistribution of this material. Across 12 donors, it was noticeable that the initial chemical composition and morphology of the droplet varied greatly, which appeared to influence on the rate of change of the droplet over time. Further, this study attempted to quantify the total water content within fingermark samples. The wide-spread nature and strength of the absorption of Terahertz/Far-infrared (THz/Far-IR) radiation by water vapour molecules were exploited for this purpose, using THz/Far-IR spectroscopy. Upon heating, water confined in natural fingermarks was evaporated and expanded in a vacuum chamber equipped with multipass optics. The amount of water vapour was then quantified by high-spectral resolution analysis, and fingermarks were observed to lose approximately 14 – 20 µg of water. The combination of both ATR-FTIR and Far-IR highlight important implications for experimental design in fingermark research, and operational practices used by law enforcement agencies.

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

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, U.S.A., 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 Modelling 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 is also investigated. We found that while overall all instruments are 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 Modelling Profiling Systems can be constricted to a limited height range in low aerosol conditions.

EVAA – das deutsche Konsortium zur Validierung der Wind- und Aerosolprodukte des ESA Satelliten Aeolus: Fallbeispiele und Langzeitstudien

<p>Der ESA-Satellit Aeolus wurde im August 2018 mit dem Ziel gestartet, durch globale Messungen von Windprofilen die Wettervorhersage zu verbessern. Dazu hat Aeolus das High-Spectral-Resolution (HSR) Doppler-Lidar ALADIN (Atmospheric Laser Doppler Instrument) an Bord, welches es ermöglicht, vertikale Profile einer Windkomponente (West-Ost) aktiv zu messen. Diese Messungen werden inzwischen von mehreren Wetterdiensten assimiliert und es konnte ein positiver Einfluss auf die Vorhersagen gezeigt werden. Zusätzlich zu den Windprofilen können mit diesem Lidar auch Aerosol- und Wolkenprofile als Nebenprodukte gemessen werden. Es ist das erste Mal, dass so eine komplexe Technik vom Weltall aus zum Einsatz kommt und bedarf daher einer ausgiebigen Validierung.</p><p><br>Ein wichtiger Beitrag zur Validierung der Wind- und Aerosolprodukte von Aeolus wurde dabei in dem Kooperationsprojekt EVAA (Experimentelle Validierung und Assimilation von Aeolus-Beobachtungen) zwischen der Ludwig-Maximilians-Universität München, dem deutschen Zentrum für Luft- und Raumfahrt (DLR), dem Deutschen Wetterdienst (DWD) sowie dem Leibniz-Institut für Troposphärenforschung (TROPOS) geleistet. Anhand von bodengebundenen Wind- und Aerosol-Referenzmessungen als auch durch Radiosonden, konnten wichtige Erkenntnisse über den zeitlichen Verlauf sowie die Charakteristik des systematischen und zufälligen Fehlers der Aeolus-Beobachtungen gewonnen werden. Durch die Assimilation der Aeolus-Messungen im Wettermodell ICON des DWD, konnte ihr Einfluss auf die Wettervorhersage quantifiziert werden.</p><p><br>In diesem Beitrag wollen wir die Ergebnisse von unseren Langzeit-Vergleichsmessungen mit Radiosonden in Leipzig, Punta Arenas (Chile) und Radar-Windprofilern über Deutschland präsentieren und das Potential und die Grenzen von Aeolus diskutieren. Um die Verbesserung der Wettervorhersage durch die neuartigen Windbeobachtungen zu quantifizieren, wird ihr Einfluss im Wettermodell ICON demonstriert.</p><p><br>Zusätzlich werden wir einen Einblick in die Möglichkeiten der Aerosolprofilmessungen von Aeolus gegeben. Dazu wird als Beispiel der Transport von Rauchaerosol von den Bränden in Kalifornien im Jahre 2020 bis nach Mitteleuropa diskutiert. Damals waren große Mengen Rauch über Leipzig gemessen wurden, die für eine sichtliche Abschwächung des Sonnenlichts sorgten. Diese Rauchschwaden konnten sowohl von Aeolus als auch mit einem bodengebundenen Forschungslidar, genannt PollyXT, beobachtet werden und sind daher ein hervorragendes Beispiel, um die Potentiale von Aeolus bzgl. Aerosol- und Wolkenmessungen zu diskutieren.</p>

Aeolus L2A aerosol optical properties product: standard correct algorithm and Mie correct algorithm

Aeolus carries the Atmospheric LAser Doppler INstrument (ALADIN), the first high-spectral-resolution lidar (HSRL) in space. Although ALADIN is optimized to measure winds, its two measurement channels can also be used to derive optical properties of atmospheric particles, including a direct retrieval of the lidar ratio. This paper presents the standard correct algorithm and the Mie correct algorithm, the two main algorithms of the optical properties product called the Level-2A product, as they are implemented in version 3.12 of the processor, corresponding to the data labelled Baseline 12. The theoretical basis is the same as in Flamant et al. (2008). Here, we also show the in-orbit performance of these algorithms. We also explain the adaptation of the calibration method, which is needed to cope with unforeseen variations of the instrument radiometric performance due to the in-orbit strain of the primary mirror under varying thermal conditions. Then we discuss the limitations of the algorithms and future improvements. We demonstrate that the L2A product provides valuable information about airborne particles; in particular, we demonstrate the capacity to retrieve a useful lidar ratio from Aeolus observations. This is illustrated using Saharan dust aerosol observed in June 2020.

Vertical structure of biomass burning aerosol transported over the southeast Atlantic Ocean

Biomass burning in southwestern Africa produces smoke plumes that are transported over the Atlantic Ocean and overlie vast regions of stratocumulus clouds. This aerosol layer contributes to direct and indirect radiative forcing of the atmosphere in this region, particularly during the months of August, September and October. There was a multi-year international campaign to study this aerosol and its interactions with clouds. Here we report on the evolution of aerosol distributions and properties as measured by the airborne high spectral resolution lidar (HSRL) during the ORACLES (Observations of Aerosols above Clouds and their intEractionS) campaign in September 2016. The NASA Langley HSRL-2 instrument was flown on the NASA ER-2 aircraft for several days in September 2016. Data were aggregated at two pairs of 2° × 2° grid boxes to examine the evolution of the vertical profile of aerosol properties during transport over the ocean. Results showed that the structure of the profile of aerosol extinction and microphysical properties is maintained over a one to two-day time scale. The fraction of aerosol in the fine mode between 50 and 500 nm remained above 0.95 and the effective radius of this fine mode was 0.16 μm from 3 to 5 km in altitude. This indicates that there is essentially no scavenging or dry deposition at these altitudes. Moreover, there is very little day to day variation in these properties, such that time sampling as happens in such campaigns, may be representative of longer periods such as monthly means. Below 3 km there is considerable mixing with larger aerosol, most likely continental source near land. Furthermore, these measurements indicated that there was a distinct gap between the bottom of the aerosol layer and cloud tops at the selected locations as evidenced by a layer of several hundred meters that contained relatively low aerosol extinction values above the clouds.

Unlocking Growth Opportunities Through Saturation Evaluation Behind Complex Completion by Applying State-of-Art Pulsed Neutron Technology

Perseverance in quantifying the remaining hydrocarbon saturation, in cased boreholes, remains critical to take business decisions and prioritize operations in brownfield waterflood development. Challenges with cased hole saturation evaluation acquired in certain complex completions such as those completed in multiple casing-tubing strings, slotted-liners and sand-screens require advanced tool technology. Pulsed Neutron Logging (PNL) is one such technology used successfully to analyze behind casing saturation evaluation. The PNL device provide accurate and precise measurement, and with robust processing and environmental compensation corrections, the saturation uncertainty can be delineated. A robust cased hole hydrocarbon saturation and uncertainty estimation enables informed decision making and value driven workover prioritization. The new generation PNL tool features a high-output electronic neutron source and four signal detectors. Near and far Gamma Ray (GR) detectors are made of Cerium-doped Lanthanum Bromide (LaBr3: Ce) featuring high-count rate efficiency and high-spectral resolution (largely insensitive to temperatures variations). A deep-reading GR detector made of Yttrium Aluminum Perovskite (YAP) in combination with a compact fast neutron monitor placed adjacent to the neutron source, enables a new measurement of the fast neutron cross section (FNXS) which provides sensitivity to gas-filled porosity. A newly devised pulsing scheme allows simultaneous measurement in both time and energy domains. The time-domain measurement aid in analyzing the self-compensated capture cross section (SIGM), neutron porosity (TPHI), and FNXS. The energy-domain measurement provides a detailed insight for high-precision mineralogy, total organic carbon (TOC), and carbon/oxygen ratio (COR). The high statistical precision energy-domain capture and inelastic spectral yield data are interpreted using an oxide-closure model which when combined with an extensive tool characterization database provide lithology and saturation measurements compensated for wellbore and completion contributions. This paper shares the advanced features of the new multi-detector PNL tool run in a horizontal well targeting the aeolian Mahwis Formation, consisting of unconsolidated sands and the glacial Al Khlata Formation (Porosity ranges 0.25 – 0.29 p.u.). In this case-study, the well was completed with uncemented sand screens and production tubing to mitigate sanding related risk. The absence of cement behind casing and the presence of screens adds considerable complexity to the saturation analysis. Furthermore, due to low water salinity (∼7000 ppm NaCl equivalent), saturation must be determined using carbon spectroscopy-based techniques - namely the COR and TOC. Logging conventional PNL tools in horizontal wells can lead to lengthy acquisition times, thus adding considerable operational complexity and cost. With the new PNL technology advancements, the time required to acquire high-quality data can be halved. Saturation outputs computed independently from COR and TOC methods showed close agreement and allowed for the direct compensation of changes in borehole oil hold-up without which the computed saturation would have been overestimated. The remaining oil saturation estimation behind cased hole and uncertainty quantification enable a proper understanding of well production performance and uncovered further opportunities. In addition, decision based strategic data acquisition to quantify remaining hydrocarbon saturation enables unlocking growth and ‘no further action’ (NFA) opportunities, impacting production recovery and meeting bottom-line targets in brownfield assets.

Adaptive Data Screening for Multi-Angle Polarimetric Aerosol and Ocean Color Remote Sensing Accelerated by Deep Learning

Remote sensing measurements from multi-angle polarimeters (MAPs) contain rich aerosol microphysical property information, and these sensors have been used to perform retrievals in optically complex atmosphere and ocean systems. Previous studies have concluded that, generally, five moderately separated viewing angles in each spectral band provide sufficient accuracy for aerosol property retrievals, with performance gradually saturating as angles are added above that threshold. The Hyper-Angular Rainbow Polarimeter (HARP) instruments provide high angular sampling with a total of 90–120 unique angles across four bands, a capability developed mainly for liquid cloud retrievals. In practice, not all view angles are optimal for aerosol retrievals due to impacts of clouds, sunglint, and other impediments. The many viewing angles of HARP can provide resilience to these effects, if the impacted views are screened from the dataset, as the remaining views may be sufficient for successful analysis. In this study, we discuss how the number of available viewing angles impacts aerosol and ocean color retrieval uncertainties, as applied to two versions of the HARP instrument. AirHARP is an airborne prototype that was deployed in the ACEPOL field campaign, while HARP2 is an instrument in development for the upcoming NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission. Based on synthetic data, we find that a total of 20–30 angles across all bands (i.e., five to eight viewing angles per band) are sufficient to achieve good retrieval performance. Following from this result, we develop an adaptive multi-angle polarimetric data screening (MAPDS) approach to evaluate data quality by comparing measurements with their best-fitted forward model. The FastMAPOL retrieval algorithm is used to retrieve scene geophysical values, by matching an efficient, deep learning-based, radiative transfer emulator to observations. The data screening method effectively identifies and removes viewing angles affected by thin cirrus clouds and other anomalies, improving retrieval performance. This was tested with AirHARP data, and we found agreement with the High Spectral Resolution Lidar-2 (HSRL-2) aerosol data. The data screening approach can be applied to modern satellite remote sensing missions, such as PACE, where a large amount of multi-angle, hyperspectral, polarimetric measurements will be collected.