Accelerated Springtime Melt of Snow on Tundra Downwind from Northern Alaska River Systems Resulting from Niveo-aeolian Deposition Events

It is well known that light-absorbing particulate matter (PM) enhances absorption of sunlight when deposited on ice and snow. Such increased absorption is due to a reduction in surface albedo, resulting in accelerated melt of frozen surfaces. In isolation, earlier melt enhances Arctic warming since dark surfaces underlying snow and ice are exposed and absorb additional solar energy. Here, we combine various observational tools to demonstrate that aeolian deposition of PM along fluvial features on the North Slope of Alaska resulted in a notable reduction of surface albedo in the spring of 2016, from values typical for snow (~0.8) to around 0.35 on average. This reduction resulted in accelerated snow and ice melt by up to three weeks compared to unaffected areas. This phenomenon was observed to some degree in 12 other years dating back to 2003. Deposition generally was found to occur near particular sections of the rivers, with several areas affected by events in multiple years. In all years, the deposition is attributed to high wind events. The extreme case in 2016 is linked to unusually strong and extraordinarily persistent winds during April. The deposited material is thought to be the natural sediment carried by the rivers, resulting in a seasonally replenished source of PM. These findings indicate a previously unreported impact of both fluvial and atmospheric processes on the seasonal melt of northern Alaska rivers.Il s’agit d’un fait bien connu que la matière particulaire photo-absorbante rehausse l’absorption de la lumière solaire lorsqu’elle est déposée sur la glace et la neige. Cette absorption accrue est attribuable à la réduction de l’albédo de la surface, ce qui se traduit par la fonte accélérée des surfaces glacées. Individuellement, la fonte hâtive augmente le réchauffement de l’Arctique parce que les surfaces sombres se trouvant sous la neige et la glace sont exposées et absorbent l’énergie solaire supplémentaire. Ici, nous recourons à divers outils d’observation pour montrer que le dépôt éolien de matière particulaire le long des caractéristiques fluviales de la North Slope de l’Alaska a entraîné une réduction notable de l’albédo de la surface au printemps de 2016, passant de valeurs typiques pour la neige de (~ 0,8) à environ 0,35 en moyenne. Cette réduction a donné lieu à l’accélération de la fonte de la neige et de la glace dans une mesure de trois semaines comparativement aux endroits qui n’ont pas été touchés par la réduction. Ce phénomène a été observé dans une certaine mesure pendant 12 autres années, remontant en 2003. De manière générale, des dépôts se sont ramassés près de segments particuliers des cours d’eau, et plusieurs des secteurs ont été touchés par des événements au cours de plusieurs années. Dans l’ensemble, les dépôts sont attribués à des vents violents. Le cas extrême de 2016 découle de vents inhabituellement forts et extraordinairement persistants en avril. La matière déposée serait peut-être du sédiment naturel transporté par les cours d’eau, ce qui donne lieu au réapprovisionnement saisonnier de la source de matière particulaire. Ces constatations mènent à une incidence antérieurement non déclarée des processus fluviaux et atmosphériques sur la fonte saisonnière des cours d’eau du nord de l’Alaska

Testing the efficacy of atmospheric boundary layer height detection algorithms using uncrewed aircraft system data from MOSAiC

During the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, meteorological conditions over the lowest 1 km of the atmosphere were sampled with the DataHawk2 (DH2) fixed-wing uncrewed aircraft system (UAS). These in situ observations of the central Arctic atmosphere are some of the most extensive to date and provide unique insight into the atmospheric boundary layer (ABL) structure. The ABL is an important component of the Arctic climate, as it can be closely coupled to cloud properties, surface fluxes, and the atmospheric radiation budget. The high temporal resolution of the UAS observations allows us to manually identify the ABL height (ZABL) for 65 out of the total 89 flights conducted over the central Arctic Ocean between 23 March and 26 July 2020 by visually analyzing profiles of virtual potential temperature, humidity, and bulk Richardson number. Comparing this subjective ZABL with ZABL identified by various previously published automated objective methods allows us to determine which objective methods are most successful at accurately identifying ZABL in the central Arctic environment and how the success of the methods differs based on stability regime. The objective methods we use are the Liu–Liang, Heffter, virtual potential temperature gradient maximum, and bulk Richardson number methods. In the process of testing these objective methods on the DH2 data, numerical thresholds were adapted to work best for the UAS-based sampling. To determine if conclusions are robust across different measurement platforms, the subjective and objective ZABL determination processes were repeated using the radiosonde profile closest in time to each DH2 flight. For both the DH2 and radiosonde data, it is determined that the bulk Richardson number method is the most successful at identifying ZABL, while the Liu–Liang method is least successful. The results of this study are expected to be beneficial for upcoming observational and modeling efforts regarding the central Arctic ABL

Vegetation type is an important predictor of the arctic summer land surface energy budget

Despite the importance of high-latitude surface energy budgets (SEBs) for land-climate interactions in the rapidly changing Arctic, uncertainties in their prediction persist. Here, we harmonize SEB observations across a network of vegetated and glaciated sites at circumpolar scale (1994&ndash;2021). Our variance-partitioning analysis identifies vegetation type as an important predictor for SEB-components during Arctic summer (June-August), compared to other SEB-drivers including climate, latitude and permafrost characteristics. Differences among vegetation types can be of similar magnitude as between vegetation and glacier surfaces and are especially high for summer sensible and latent heat fluxes. The timing of SEB-flux summer-regimes (when daily mean values exceed 0 Wm&minus;2) relative to snow-free and -onset dates varies substantially depending on vegetation type, implying vegetation controls on snow-cover and SEB-flux seasonality. Our results indicate complex shifts in surface energy fluxes with land-cover transitions and a lengthening summer season, and highlight the potential for improving future Earth system models via a refined representation of Arctic vegetation types. &nbsp;</p

Observed aerosol suppression of cloud ice in low-level Arctic mixed-phase clouds

The interactions that occur between aerosols and a mixed-phase cloud system, and the subsequent alteration of the microphysical state of such clouds, are a problem that has yet to be well constrained. Advancing our understanding of aerosol–ice processes is necessary to determine the impact of natural and anthropogenic emissions on Earth's climate and to improve our capability to predict future climate states. This paper deals specifically with how aerosols influence ice mass production in low-level Arctic mixed-phase clouds. In this study, a 9-year record of aerosol, cloud and atmospheric state properties is used to quantify aerosol influence on ice production in mixed-phase clouds. It is found that mixed-phase clouds present in a clean aerosol state have higher ice water content (IWC) by a factor of 1.22 to 1.63 at cloud base than do similar clouds in cases with higher aerosol loading. We additionally analyze radar-derived mean Doppler velocities to better understand the drivers behind this relationship, and we conclude that aerosol induced reduction of the ice crystal nucleation rate, together with decreased riming rates in polluted clouds, are likely influences on the observed reductions in IWC

Design and fabrication of a planar three-DOFs MEMS-based manipulator

This paper presents the design, modeling, and fabrication of a planar three-degrees-of-freedom parallel kinematic manipulator, fabricated with a simple two-mask process in conventional highly doped single-crystalline silicon (SCS) wafers (100). The manipulator’s purpose is to provide accurate and stable positioning of a small sample (10 × 20 × 0.2 μm3), e.g., within a transmission electron microscope. The manipulator design is based on the principles of exact constraint design, resulting in a high actuation-compliance combined with a relatively high suspension stiffness. A modal analysis shows that the fourth vibration mode frequency is at least a factor 11 higher than the first three actuation-related mode frequencies. The comb-drive actuators are modeled in combination with the shuttle suspensions gaining insight into the side and rotational pull-in stability conditions. The two-mask fabrication process enables high-aspect-ratio structures, combined with electrical trench insulation. Trench insulation allows structures in conventional wafers to be mechanically connected while being electrically insulated from each other. Device characterization shows high linearity of displacement wrt voltage squared over ±10 μm stroke in the x- and y-directions and ±2◦ rotation at a maximum of 50 V driving voltage. Out-of-plane displacement crosstalk due to in-plane actuation in resonance is measured to be less than 20 pm. The hysteresis in SCS, measured using white light interferometry, is shown to be extremely small

The DataHawk2 uncrewed aircraft system for atmospheric research

The DataHawk2 (DH2) is a small, fixed-wing, uncrewed aircraft system, or UAS, developed at the University of Colorado (CU) primarily for taking detailed thermodynamic measurements of the atmospheric boundary layer. The DH2 weighs 1.7&thinsp;kg and has a wingspan of 1.3&thinsp;m, with a flight endurance of approximately 60&thinsp;min, depending on configuration. In the DH2's most modern form, the aircraft carries a Vaisala RSS-421 sensor for pressure, temperature, and relative humidity measurements, two CU-developed infrared temperature sensors, and a CU-developed fine-wire array, in addition to sensors required to support autopilot function (pitot tube with pressure sensor, GPS receiver, inertial measurement unit), from which wind speed and direction can also be estimated. This paper presents a description of the DH2, including information on its design and development work, and puts the DH2 into context with respect to other contemporary UASs. Data from recent field work (MOSAiC, the Multidisciplinary drifting Observatory for the Study of Arctic Climate) is presented and compared with radiosondes deployed during that campaign to provide an overview of sensor and system performance. These data show good agreement across pressure, temperature, and relative humidity as well as across wind speed and direction. Additional examples of measurements provided by the DH2 are given from a variety of previous campaigns in locations ranging from the continental United States to Japan and northern Alaska. Finally, a look toward future system improvements and upcoming research campaign participation is given. &nbsp;</p

Intercomparison of Small Unmanned Aircraft System (sUAS) Measurements for Atmospheric Science during the LAPSE-RATE Campaign

Small unmanned aircraft systems (sUAS) are rapidly transforming atmospheric research. With the advancement of the development and application of these systems, improving knowledge of best practices for accurate measurement is critical for achieving scientific goals. We present results from an intercomparison of atmospheric measurement data from the Lower Atmospheric Process Studies at Elevation&mdash;a Remotely piloted Aircraft Team Experiment (LAPSE-RATE) field campaign. We evaluate a total of 38 individual sUAS with 23 unique sensor and platform configurations using a meteorological tower for reference measurements. We assess precision, bias, and time response of sUAS measurements of temperature, humidity, pressure, wind speed, and wind direction. Most sUAS measurements show broad agreement with the reference, particularly temperature and wind speed, with mean value differences of 1.6 &plusmn;2.6∘ C and 0.22 &plusmn;0.59 m/s for all sUAS, respectively. sUAS platform and sensor configurations were found to contribute significantly to measurement accuracy. Sensor configurations, which included proper aspiration and radiation shielding of sensors, were found to provide the most accurate thermodynamic measurements (temperature and relative humidity), whereas sonic anemometers on multirotor platforms provided the most accurate wind measurements (horizontal speed and direction). We contribute both a characterization and assessment of sUAS for measuring atmospheric parameters, and identify important challenges and opportunities for improving scientific measurements with sUAS.</p

Clutter mitigation, multiple peaks, and high-order spectral moments in 35 GHz vertically pointing radar velocity spectra

This study presents and applies three separate processing methods to improve high-order moments estimated from 35GHz (Ka band) vertically pointing radar Doppler velocity spectra. The first processing method removes Doppler-shifted ground clutter from spectra collected by a US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program Ka-band zenith pointing radar (KAZR) deployed at Oliktok Point (OLI), Alaska. Ground clutter resulted from multiple pathways through antenna side lobes and reflections off a rotating scanning radar antenna located 2m away from KAZR, which caused Doppler shifts in ground clutter returns from stationary targets 2.5km away. After removing clutter in the recorded velocity spectra, the second processing method identifies multiple separate and sub-peaks in the spectra and estimates high-order moments for each peak. Multiple peaks and high-order moments were estimated for both original 2 and 15s averaged spectra. The third processing step improves the spectrum variance, skewness, and kurtosis estimates by removing velocity variability due to turbulent broadening during 15s averaging intervals. Applying the multiple peak processing to Doppler velocity spectra during liquid-only clouds can identify cloud and drizzle particles and during mixed-phase clouds can identify liquid cloud and frozen hydrometeors. Consistent with previous studies, this work found that spectrum skewness assuming only a single spectral peak was a good indicator of two hydrometeor populations (for example, cloud and drizzle particles) being present in the radar pulse volume. Yet, after dividing the spectrum into multiple peaks, velocity spectrum skewness for individual peaks is near zero, indicating nearly symmetric peaks. This suggests that future studies should use velocity skewness of single-peak spectra as an indicator of possible multiple hydrometeor populations and then use multiple-peak moments for quantitative studies. Three future activities will continue this work. First, KAZR spectra from several ARM sites have been processed and are available in the ARM archive as a principal investigator (PI) product. ARM programmers are evaluating these processing methods as part of future multiple-peak products generated by ARM. Third, MATLAB code generating the Oliktok Point products has been uploaded as supplemental material for public dissemination