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At least 163 records · Page 9

The stochastic variability of asteroidal regolith depths

Modeling the depth of regolith on asteroids is approached from a statistical point of view. It is demonstrated that average values are not good descriptors of regolith depth on asteroids. Large deviations from the average can be expected to occur due to both large variations in depth over the surface of a body and to the fact that each asteroid has a unique regolith. The utility of the average depth is not significantly increased by excluding the parts of a surface which are occupied by large craters; a procedure adopted in existing regolith models. Although an asteroid's surface may be 'smoothed out' by movement of debris into gravitationally low spots, the regolith depth retains its variability because of variations in topography at the bottom of the regolith layer. The large variability associated with regolith depth severely limits the power of regolith models in predicting parent body size for the brecciated meteorites.

Housen, K. R.↗

Mechanisms and depths of atlantic transform earthquakes

Mechanisms and depths of 40 earthquakes on major transforms along the Mid-Atlantic Ridge are studied in order to identify events that deviate from the transform-parallel strike-slip motion. Long and short period waves and Rayleigh wave spectral amplitudes are used to analyze focal mechanisms, depths, source time functions, and seismic moments of earthquakes. The relationship between centroid depths and transform thermal structures is examined. The data reveal that transform earthquake centroid depths occur above the predicted 400 C isotherms and the oceanic intraplate depths extend to the 750 C isotherm. Slip rates inferred from seismic moment releases are compared to those predicted by plate motions and good correlation is detected. The difference in the centroid depths of transform and interplate seismicity indicates transforms are either weaker or higher temperatures than expected.

Engeln, J. F.↗

How to reinforce perception of depth in single two-dimensional pictures

The physical conditions of the display of single 2-D pictures, which produce images realistically, were studied by using the characteristics of the intake of the information for visual depth perception. Depth sensitivity, which is defined as the ratio of viewing distance to depth discrimination threshold, was introduced in order to evaluate the availability of various cues for depth perception: binocular parallax, motion parallax, accommodation, convergence, size, texture, brightness, and air-perspective contrast. The effects of binocular parallax in different conditions, the depth sensitivity of which is greatest at a distance of up to about 10 m, were studied with the new versatile stereoscopic display. From these results, four conditions to reinforce the perception of depth in single pictures were proposed, and these conditions are met by the old viewing devices and the new high-definition and wide television displays.

S. Nagata↗

Determination of depth-viewing volumes for stereo three-dimensional graphic displays

Real-world, 3-D, pictorial displays incorporating true depth cues via stereopsis techniques offer a potential means of displaying complex information in a natural way to prevent loss of situational awareness and provide increases in pilot/vehicle performance in advanced flight display concepts. Optimal use of stereopsis requires an understanding of the depth viewing volume available to the display designer. Suggested guidelines are presented for the depth viewing volume from an empirical determination of the effective region of stereopsis cueing (at several viewer-CRT screen distances) for a time multiplexed stereopsis display system. The results provide the display designer with information that will allow more effective placement of depth information to enable the full exploitation of stereopsis cueing. Increasing viewer-CRT screen distances provides increasing amounts of usable depth, but with decreasing fields-of-view. A stereopsis hardware system that permits an increased viewer-screen distance by incorporating larger screen sizes or collimation optics to maintain the field-of-view at required levels would provide a much larger stereo depth-viewing volume.

Parrish, Russell V.↗

Model based estimation of image depth and displacement

Passive depth and displacement map determinations have become an important part of computer vision processing. Applications that make use of this type of information include autonomous navigation, robotic assembly, image sequence compression, structure identification, and 3-D motion estimation. With the reliance of such systems on visual image characteristics, a need to overcome image degradations, such as random image-capture noise, motion, and quantization effects, is clearly necessary. Many depth and displacement estimation algorithms also introduce additional distortions due to the gradient operations performed on the noisy intensity images. These degradations can limit the accuracy and reliability of the displacement or depth information extracted from such sequences. Recognizing the previously stated conditions, a new method to model and estimate a restored depth or displacement field is presented. Once a model has been established, the field can be filtered using currently established multidimensional algorithms. In particular, the reduced order model Kalman filter (ROMKF), which has been shown to be an effective tool in the reduction of image intensity distortions, was applied to the computed displacement fields. Results of the application of this model show significant improvements on the restored field. Previous attempts at restoring the depth or displacement fields assumed homogeneous characteristics which resulted in the smoothing of discontinuities. In these situations, edges were lost. An adaptive model parameter selection method is provided that maintains sharp edge boundaries in the restored field. This has been successfully applied to images representative of robotic scenarios. In order to accommodate image sequences, the standard 2-D ROMKF model is extended into 3-D by the incorporation of a deterministic component based on previously restored fields. The inclusion of past depth and displacement fields allows a means of incorporating the temporal information into the restoration process. A summary on the conditions that indicate which type of filtering should be applied to a field is provided.

Damour, Kevin T.↗

Uncertainty in cloud optical depth estimates made from satellite radiance measurements

The uncertainty in optical depths retrieved from satellite measurements of visible wavelength radiance at the top of the atmosphere is quantified. Techniques are briefly reviewed for the estimation of optical depth from measurements of radiance, and it is noted that these estimates are always more uncertain at greater optical depths and larger solar zenith angles. The lack of radiometric calibration for visible wavelength imagers on operational satellites dominates the uncertainty retrievals of optical depth. This is true for both single-pixel retrievals and for statistics calculated from a population of individual retrievals. For individual estimates or small samples, sensor discretization can also be significant, but the sensitivity of the retrieval to the specification of the model atmosphere is less important. The relative uncertainty in calibration affects the accuracy with which optical depth distributions measured by different sensors may be quantitatively compared, while the absolute calibration uncertainty, acting through the nonlinear mapping of radiance to optical depth, limits the degree to which distributions measured by the same sensor may be distinguished.

Pincus, Robert↗

Aerosol Optical Depth Determinations for BOREAS

Automated tracking sun photometers were deployed by NASA/Ames Research Center aboard the NASA C-130 aircraft and at a ground site for all three Intensive Field Campaigns (IFCs) of the Boreal Ecosystem-Atmosphere Study (BOREAS) in central Saskatchewan, Canada during the summer of 1994. The sun photometer data were used to derive aerosol optical depths for the total atmospheric column above each instrument. The airborne tracking sun photometer obtained data in both the southern and northern study areas at the surface prior to takeoff, along low altitude runs near the ground tracking sun photometer, during ascents to 6-8 km msl, along remote sensing flightlines at altitude, during descents to the surface, and at the surface after landing. The ground sun photometer obtained data from the shore of Candle Lake in the southern area for all cloud-free times. During the first IFC in May-June ascents and descents of the airborne tracking sun photometer indicated the aerosol optical depths decreased steadily from the surface to 3.5 kni where they leveled out at approximately 0.05 (at 525 nm), well below levels caused by the eruption of Mt. Pinatubo. On a very clear day, May 31st, surface optical depths measured by either the airborne or ground sun photometers approached those levels (0.06-0.08 at 525 nm), but surface optical depths were often several times higher. On June 4th they increased from 0.12 in the morning to 0.20 in the afternoon with some evidence of brief episodes of pollen bursts. During the second IFC surface aerosol optical depths were variable in the extreme due to smoke from western forest fires. On July 20th the aerosol optical depth at 525 nm decreased from 0.5 in the morning to 0.2 in the afternoon; they decreased still further the next day to 0.05 and remained consistently low throughout the day to provide excellent conditions for several remote sensing missions flown that day. Smoke was heavy for the early morning of July 24th but cleared partially by 10:30 local time and cleared fully by 11:30. Heavy smoke characterized the rest of the IFC in both study areas.

Wrigley, R. C.↗

Comparison of the Atomic Oxygen Erosion Depth and Cone Height of Various Materials at Hyperthermal Energy

Atomic oxygen readily reacts with most spacecraft polymer materials exposed to the low Earth orbital (LEO) environment. If the atomic oxygen arrival comes from a fixed angle of impact, the resulting erosion will foster the development of a change in surface morphology as material thickness decreases. Hydrocarbon and halopolymer materials, as well as graphite, are easily oxidized and textured by directed atomic oxygen in LEO at energies of approx.4.5 eV. What has been curious is that the ratio of cone height to erosion depth is quite different for different materials. The formation of cones under fixed direction atomic oxygen attack may contribute to a reduction in material tensile strength in excess of that which would occur if the cone height to erosion depth ratio was very low because of greater opportunities for crack initiation. In an effort to understand how material composition affects the ratio of cone height to erosion depth, an experimental investigation was conducted on 18 different materials exposed to a hyperthermal energy directed atomic oxygen source (approx.70 eV). The materials were first salt-sprayed to provide microscopic local areas that would be protected from atomic oxygen. This allowed erosion depth measurements to be made by scanning microscopy inspection. The polymers were then exposed to atomic oxygen produced by an end Hall ion source that was operated on pure oxygen. Samples were exposed to an atomic oxygen effective fluence of 1.0x10(exp 20) atoms/sq cm based on Kapton H polyimide erosion. The average erosion depth and average cone height were determined using field emission scanning electron microscopy (FESEM). The experimental ratio of average cone height to erosion depth is compared to polymer composition and other properties.

Waters, Deborah L.↗

Snow Depth and Ice Thickness Measurements From the Beaufort and Chukchi Seas Collected During the AMSR-Ice03 Campaign

In March 2003, a field validation campaign was conducted on the sea ice near Barrow, AK. The goal of this campaign was to produce an extensive dataset of sea ice thickness and snow properties (depth and stratigraphy) against which remote sensing products collected by aircraft and satellite could be compared. Chief among these were products from the Polarimetric Scanning Radiometer (PSR) flown aboard a NASA P-3B aircraft and the Aqua Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E). The data were collected in four field areas: three on the coastal sea ice near Barrow, AK, and the fourth out on the open ice pack 175 km northeast of Barrow. The snow depth ranged from 9.4-20.8 cm in coastal areas (n = 9881 for three areas) with the thinnest snow on ice that had formed late in the winter. Out in the main pack ice, the snow was 20.6 cm deep (n = 1906). The ice in all four areas ranged from 138-219 cm thick (n = 1952), with the lower value again where the ice had formed late in the winter. Snow layer and grain characteristics observed in 118 snow pits indicated that 44% of observed snow layers were depth hoar; 46% were wind slab. Snow and ice measurements were keyed to photomosaics produced from low-altitude vertical aerial photographs. Using these, and a distinctive three-way relationship between ice roughness, snow surface characteristics, and snow depth, strip maps of snow depth, each about 2 km wide, were produced bracketing the traverse lines. These maps contain an unprecedented level of snow depth detail against which to compare remote sensing products. The maps are used in other papers in this special issue to examine the retrieval of snow properties from the PSR and AMSR-E sensors.

Sturm, M.↗

Retrievals of Thick Cloud Optical Depth from the Geoscience Laser Altimeter System (GLAS) by Calibration of Solar Background Signal

Laser beams emitted from the Geoscience Laser Altimeter System (GLAS), as well as other space-borne laser instruments, can only penetrate clouds to a limit of a few optical depths. As a result, only optical depths of thinner clouds (< about 3 for GLAS) are retrieved from the reflected lidar signal. This paper presents a comprehensive study of possible retrievals of optical depth of thick clouds using solar background light and treating GLAS as a solar radiometer. To do so we first calibrate the reflected solar radiation received by the photon-counting detectors of GLAS' 532 nm channel, which is the primary channel for atmospheric products. The solar background radiation is regarded as a noise to be subtracted in the retrieval process of the lidar products. However, once calibrated, it becomes a signal that can be used in studying the properties of optically thick clouds. In this paper, three calibration methods are presented: (I) calibration with coincident airborne and GLAS observations; (2) calibration with coincident Geostationary Operational Environmental Satellite (GOES) and GLAS observations of deep convective clouds; (3) calibration from the first principles using optical depth of thin water clouds over ocean retrieved by GLAS active remote sensing. Results from the three methods agree well with each other. Cloud optical depth (COD) is retrieved from the calibrated solar background signal using a one-channel retrieval. Comparison with COD retrieved from GOES during GLAS overpasses shows that the average difference between the two retrievals is 24%. As an example, the COD values retrieved from GLAS solar background are illustrated for a marine stratocumulus cloud field that is too thick to be penetrated by the GLAS laser. Based on this study, optical depths for thick clouds will be provided as a supplementary product to the existing operational GLAS cloud products in future GLAS data releases.

Yang, Yuekui↗

Estimation of Sea Ice Thickness Distributions through the Combination of Snow Depth and Satellite Laser Altimetry Data

Combinations of sea ice freeboard and snow depth measurements from satellite data have the potential to provide a means to derive global sea ice thickness values. However, large differences in spatial coverage and resolution between the measurements lead to uncertainties when combining the data. High resolution airborne laser altimeter retrievals of snow-ice freeboard and passive microwave retrievals of snow depth taken in March 2006 provide insight into the spatial variability of these quantities as well as optimal methods for combining high resolution satellite altimeter measurements with low resolution snow depth data. The aircraft measurements show a relationship between freeboard and snow depth for thin ice allowing the development of a method for estimating sea ice thickness from satellite laser altimetry data at their full spatial resolution. This method is used to estimate snow and ice thicknesses for the Arctic basin through the combination of freeboard data from ICESat, snow depth data over first-year ice from AMSR-E, and snow depth over multiyear ice from climatological data. Due to the non-linear dependence of heat flux on ice thickness, the impact on heat flux calculations when maintaining the full resolution of the ICESat data for ice thickness estimates is explored for typical winter conditions. Calculations of the basin-wide mean heat flux and ice growth rate using snow and ice thickness values at the 70 m spatial resolution of ICESat are found to be approximately one-third higher than those calculated from 25 km mean ice thickness values.

Kurtz, Nathan T.↗

Freeboard, Snow Depth and Sea-Ice Roughness in East Antarctica from In Situ and Multiple Satellite Data

In October 2003 a campaign on board the Australian icebreaker Aurora Australis had the objective to validate standard Aqua Advanced Microwave Scanning Radiometer (AMSR-E) sea-ice products. Additionally, the satellite laser altimeter on the Ice, Cloud and land Elevation Satellite (ICESat) was in operation. To capture the large-scale information on the sea-ice conditions necessary for satellite validation, the measurement strategy was to obtain large-scale sea-ice statistics using extensive sea-ice measurements in a Lagrangian approach. A drifting buoy array, spanning initially 50 km 100 km, was surveyed during the campaign. In situ measurements consisted of 12 transects, 50 500 m, with detailed snow and ice measurements as well as random snow depth sampling of floes within the buoy array using helicopters. In order to increase the amount of coincident in situ and satellite data an approach has been developed to extrapolate measurements in time and in space. Assuming no change in snow depth and freeboard occurred during the period of the campaign on the floes surveyed, we use buoy ice-drift information as well as daily estimates of thin-ice fraction and rough-ice vs smooth-ice fractions from AMSR-E and QuikSCAT, respectively, to estimate kilometer-scale snow depth and freeboard for other days. The results show that ICESat freeboard estimates have a mean difference of 1.8 cm when compared with the in situ data and a correlation coefficient of 0.6. Furthermore, incorporating ICESat roughness information into the AMSR-E snow depth algorithm significantly improves snow depth retrievals. Snow depth retrievals using a combination of AMSR-E and ICESat data agree with in situ data with a mean difference of 2.3 cm and a correlation coefficient of 0.84 with a negligible bias.

Markus, Thorsten↗

The Use of Satellite-Measured Aerosol Optical Depth to Constrain Biomass Burning Emissions Source Strength in a Global Model GOCART

Small particles in the atmosphere, called "atmospheric aerosol" have a direct effect on Earth climate through scattering and absorbing sunlight, and also an indirect effect by changing the properties of clouds, as they interact with solar radiation as well. Aerosol typically stays in the atmosphere for several days, and can be transported long distances, affecting air quality, visibility, and human health not only near the source, but also far downwind. Smoke from vegetation fires is one of the main sources of atmospheric aerosol; other sources include anthropogenic pollution, dust, and sea salt. Chemistry transport models (CTMs) are among the major tools for studying the atmospheric and climate effects of aerosol. Due to the considerable variation of aerosol concentrations and properties on many temporal and spatial scales, and the complexity of the processes involved, the uncertainties in aerosol effects on climate are large, as is featured in the latest report of Intergovernmental Panel on Climate Change (IPCC) in 2007. Reducing this uncertainty in the models is very important both for predicting future climate scenarios and for regional air quality forecasting and mitigation. During vegetation fires, also called biomass burning (BB) events, complex mixture of gases and particles is emitted. The amount of BB emissions is usually estimated taking into account the intensity and size of the fire and the properties of burning vegetation. These estimates are input into CTMs to simulate BB aerosol. Unfortunately, due to large variability of fire and vegetation properties, the quantity of BB emissions is very difficult to estimate and BB emission inventories provide numbers that can differ by up to the order of magnitude in some regions. Larger uncertainties in data input make uncertainties in model output larger as well. A powerful way to narrow the range of possible model estimates is to compare model output to observations. We use satellite observations of aerosol properties, specifically aerosol optical depth, which is directly proportional to the amount of aerosol in the atmosphere, and compare it to the model output. Assuming the model represents aerosol transport and particle properties correctly, the amount of BB emissions determines the simulated aerosol optical depth. In this study, we explore the regional performance of 13 commonly used emission estimates. These are each input to global Goddard Chemistry Aerosol Radiation and Transport (GOCART) model. We then evaluate how well each emission estimate reproduces the smoke aerosol optical depth measured by the MODIS instrument. We compared GOCART-simulate aerosol optical depth with that measured from the satellite for 124 fire cases around the world during 2006 and 2007. We summarize the regional performance of each emission inventory and discuss reasons for their differences by considering the assumptions made during their development. We also show that because stronger wind disperses smoke plumes more readily, in cases with stronger wind, a larger increase in emission amount is needed to increase aerosol optical depth. In quiet, low-wind-speed environments, BB emissions produce a more significant increase in aerosol optical depth, other things being equal. Using the region-specific, quantitative relationships derived in our paper, together with the wind speed obtained from another source for a given fire case, we can constrain the amount of emission required in the model to reproduce the observations. The results of this paper are useful to the developers of BB emission inventories, as they show the strengths and weaknesses of individual emission inventories in different regions of the globe, and also for modelers who use these inventories and wish to improve their model results.

Petrenko, Mariya↗

Global Estimates of PBL Depth from Space-Borne LIDAR

The planetary boundary layer (PBL) is responsible for communicating the exchange of energy, moisture, momentum, pollutants, and aerosols between the surface and the free atmosphere and is therefore crucial to many studies of the atmosphere. Unfortunately, there have historically been few observations of this important layer due to the complexity involved in its measurement. However, with the advent of more advanced satellites, global measurements of the PBL are now becoming possible. The PBL is often characterized by a high concentration of aerosols within the layer and low level clouds capping it and these are observable from space. The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite was launched in 2006 with the intention of observing aerosols and clouds and was the first space-based LIDAR optimized for this purpose. CALIPSO observations are therefore well suited to observing the depth of the PBL. Since it was launched, CALIPSO has been making nearly continuous measurements enabling a global picture of PBL depth. We plan to present a global PBL depth product and how it evolves throughout the year. The product is able to identify deeper PBL depths in the summer hemisphere over land and deeper depths along the northern hemisphere oceanic storm tracks in winter associated with cold air traveling over warm water. Large seasonal cycles are also evident in the subtropical desert locations among other features. In addition, comparisons will be made between several estimates of PBL depth based on turbulent intensity, meteorology profiles, and aerosol profiles from the GEOS5 model.

McGrath-Spangler, Erica lynn↗

Effect of Thin Cirrus Clouds on Dust Optical Depth Retrievals From MODIS Observations

The effect of thin cirrus clouds in retrieving the dust optical depth from MODIS observations is investigated by using a simplified aerosol retrieval algorithm based on the principles of the Deep Blue aerosol property retrieval method. Specifically, the errors of the retrieved dust optical depth due to thin cirrus contamination are quantified through the comparison of two retrievals by assuming dust-only atmospheres and the counterparts with overlapping mineral dust and thin cirrus clouds. To account for the effect of the polarization state of radiation field on radiance simulation, a vector radiative transfer model is used to generate the lookup tables. In the forward radiative transfer simulations involved in generating the lookup tables, the Rayleigh scattering by atmospheric gaseous molecules and the reflection of the surface assumed to be Lambertian are fully taken into account. Additionally, the spheroid model is utilized to account for the nonsphericity of dust particles In computing their optical properties. For simplicity, the single-scattering albedo, scattering phase matrix, and optical depth are specified a priori for thin cirrus clouds assumed to consist of droxtal ice crystals. The present results indicate that the errors in the retrieved dust optical depths due to the contamination of thin cirrus clouds depend on the scattering angle, underlying surface reflectance, and dust optical depth. Under heavy dusty conditions, the absolute errors are comparable to the predescribed optical depths of thin cirrus clouds.

Feng, Qian↗

Estimating Alpine Snow Depth by Combining Multi-Frequency Passive Radiance Observations with Ensemble Snowpack Modeling

This paper presents a physically-based snow depth retrieval algorithm adapted for deep mountainous snowpack and airborne multifrequency (10.7, 18.7, 37.0 and 89.0 GHz) passive microwave (PM) radiance observations from a single flight. The algorithm employs a single forecast-analysis cycle of a traditional sequential assimilation scheme. It uses an ensemble of multi-layer snowpack model runs to resolve snow microstructure and melt-refreeze crusts, andmicrowave radiative transfer models to relate snow properties to microwave measurements.Snow depth was retrieved at a 120 m spatial resolution over three 1 km2 Intensive Study Area (ISA) within the Rabbit Ears Meso-Cell Study Area (MSA) from the NASA Cold Land Processes Experiment (CLPX) in Colorado (United States) for one date in February 2003. When evaluated against in situ observations, root mean square error (RMSE) of the snow depth from the assimilation was 13.3 cm for areas with low (<5 %) forest cover, which was a reduction of 48 % in the RMSE compared with the modeled snow depth when the PM observations were not assimilated; indicating a ~5% relative error of the posterior snow depth with respect to the average snow depth (200 cm) measured at these pixels. For pixels with forest cover ranging from 5-15% and 15-30%, results were improved (R2 increased from 0.65 to 0.71 and from 0 to 0.38, respectively) by introducing a forest radiative transfer model during the assimilation.

Airborne Multifrequency↗

ICESat-2 Meltwater Depth Estimates: Application to Surface Melt on Amery Ice Shelf, East Antarctica

Surface melting occurs during summer on the Antarctic and Greenland ice sheets, but the volume of meltwater stored has been difficult to quantify due to a lack of accurate depth estimates. NASA’s ICESat-2 laser altimeter brings a new capability: photons penetrate water and are reflected from both the water and the underlying ice; the difference provides a depth estimate. ICESat-2 sampled Amery Ice Shelf on 2 January 2019 and showed double returns from surface depressions, indicating meltwater. For four melt features, we compared depth estimates from eight algorithms: six based on ICESat-2 and two from coincident Landsat-8 and Sentinel-2 imagery. All algorithms successfully identified surface water at the same locations. Algorithms based on ICESat-2 produced the most accurate depths; the image-based algorithms underestimated depths (by 30-70%). This implies that ICESat-2 depths can be used to tune image-based algorithms, moving us closer to quantifying stored meltwater volumes across Antarctica and Greenland.

ICESat-2↗

Inter-comparison of snow depth over Arctic sea ice from reanalysis reconstructions and satellite retrieval

In this study, we compare eight recently developed snow depth products over Arctic sea ice, which use satellite observations, modeling, or a combination of satellite and modeling approaches. These products are further compared against various ground-truth observations, including those from ice mass balance observations and airborne measurements. Large mean snow depth discrepancies are observed over the Atlantic and Canadian Arctic sectors. The differences between climatology and the snow products early in winter could be in part a result of the delaying in Arctic ice formation that reduces early snow accumulation, leading to shallower snowpacks at the start of the freeze-up season. These differences persist through spring despite overall more winter snow accumulation in the reanalysis-based products than in the climatologies. Among the products evaluated, the University of Washington (UW) snow depth product produces the deepest spring (March–April) snowpacks, while the snow product from the Danish Meteorological Institute (DMI) provides the shallowest spring snow depths. Most snow products show significant correlation with snow depths retrieved from Operational IceBridge (OIB) while correlations are quite low against buoy measurements, with no correlation and very low variability from University of Bremen and DMI products. Inconsistencies in reconstructed snow depth among the products, as well as differences between these products and in situ and airborne observations, can be partially attributed to differences in effective footprint and spatial–temporal coverage, as well as insufficient observations for validation/bias adjustments. Our results highlight the need for more targeted Arctic surveys over different spatial and temporal scales to allow for a more systematic comparison and fusion of airborne, in situ and remote sensing observations.

Lu Zhou↗