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Abstract For predicting surface performance, multiscale topography analysis consistently outperforms standard roughness metrics; however, surface-characterization tools limit the range of sizes that can be measured. Therefore, we evaluate the use of scanning electron microscopy (SEM) to systematically measure small-scale topography. While others have employed SEM for similar purposes, the novelty of this investigation lies in the development and validation of a simple, flexible procedure that can be applied to a wide range of materials and geometries. First, we established four different options that can be used for sample preparation, and we measured quantitative topography of each using the SEM. Then the power spectral density (PSD) was used to compare topography among the four preparations, and against other techniques. A statistical comparison of PSDs demonstrated that SEM topography measurements outperformed AFM measurements at scales below 100 nm and were statistically indistinguishable from (highly labor-intensive) TEM measurements down to 16 nm. The limitations of SEM-based topography are quantified and discussed. Overall, the results show a simple generalizable method for revealing small-scale topography. When combined with traditional stylus profilometry, this technique characterizes surface topography across almost seven orders of magnitude, from 1 cm down to 16 nm, facilitating the use of physical models to predict performance. 

Trace metal cations dissolved in alkaline electrolytes incorporate into nickel hydroxide/oxyhydroxide throughin situcation exchange, creating an interstratified structure near the surface of the material that impacts the electrochemical performance. 

Abstract Geological processes at subduction zones and their associated geohazards (e.g., megathrust earthquakes, submarine landslides, tsunamis, and arc volcanism) are, to a large extent, controlled by the structure, physical properties and fluid content of the subducting plate, the accreted sediments, and the overriding plate. In these settings, modern seismic modeling and imaging techniques based on controlled-source, multicomponent ocean-bottom seismometer (OBS) data are some of the best tools available for determining the subseafloor elastic properties, which can be linked to the aforementioned properties. Here, we present CASIE21-OBS, a controlled-source marine wide-angle OBS data set recently collected across the Cascadia convergent margin as part of the larger CAscadia Seismic Imaging Experiment 2021 (CASIE21). The main component of CASIE21 is a long-offset multichannel seismic (MCS) survey of the Cascadia margin conducted in June–July 2021 onboard R/V M.G. Langseth (cruise MGL2104) aiming to characterize the incoming plate, the plate interface geometry and properties, and the overlying sediment stratigraphy and physical properties. CASIE21-OBS was conducted during R/V M.G. Langseth cruise MGL2103 (May 2021) and R/V Oceanus cruise OC2106A (June–July 2021). It consisted of 63 short-period four-component OBSs deployed at a total 120 stations along 10 across-trench profiles extending from ∼50 km seaward of the deformation front to the continental shelf, and from offshore northern Vancouver Island to offshore southern Oregon. The OBSs recorded the airgun signals of the CASIE21-MCS survey as well as natural seismicity occurring during the deployment period (24 May 2021 19:00 UTC–9 July 2021 09:00 UTC). The OBS data are archived and available at the Incorporated Research Institutions for Seismology Data Management Center under network code YR_2021 for continuous time series (miniSEED) and identifier 21-008 for assembled data set (SEG-Y). 

Abstract. Radiation fogs at Summit Station, Greenland (72.58^∘ N,38.48^∘ W; 3210 m a.s.l.), are frequently reported by observers. Thefogs are often accompanied by fogbows, indicating the particles are composedof liquid; and because of the low temperatures at Summit, this liquid issupercooled. Here we analyze the formation of these fogs as well as theirphysical and radiative properties. In situ observations of particle size anddroplet number concentration were made using scattering spectrometers near 2 and 10 m height from 2012 to 2014. These data are complemented bycolocated observations of meteorology, turbulent and radiative fluxes, andremote sensing. We find that liquid fogs occur in all seasons with thehighest frequency in September and a minimum in April. Due to thecharacteristics of the boundary-layer meteorology, the fogs are elevated,forming between 2 and 10 m, and the particles then fall toward the surface.The diameter of mature particles is typically 20–25 µm in summer.Number concentrations are higher at warmer temperatures and, thus, higher insummer compared to winter. The fogs form at temperatures as warm as −5 ^∘C, while the coldest form at temperatures approaching −40 ^∘C. Facilitated by the elevated condensation, in winter two-thirds offogs occurred within a relatively warm layer above the surface when thenear-surface air was below −40 ^∘C, as cold as −57 ^∘C,which is too cold to support liquid water. This implies that fog particlessettling through this layer of cold air freeze in the air column beforecontacting the surface, thereby accumulating at the surface as ice withoutriming. Liquid fogs observed under otherwise clear skies annually imparted1.5 W m⁻² of cloud radiative forcing (CRF). While this is a smallcontribution to the surface radiation climatology, individual events areinfluential. The mean CRF during liquid fog events was 26 W m⁻², andwas sometimes much higher. An extreme case study was observed toradiatively force 5 ^∘C of surface warming during the coldest partof the day, effectively damping the diurnal cycle. At lower elevations ofthe ice sheet where melting is more common, such damping could signal a rolefor fogs in preconditioning the surface for melting later in the day. 

Abstract 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 (1994–2021). 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 −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.