Cloud-driven modulations of Greenland ice sheet surface melt.

Clouds have been recognized to enhance surface melt on the Greenland Ice Sheet (GrIS). However, quantitative estimates of the effects of clouds on the GrIS melt area and ice-sheet-wide surface mass balance are still lacking. Here we assess the effects of clouds with a state-of-the-art regional climate model, conducting a numerical sensitivity test in which adiabatic atmospheric conditions as well as zero cloud water/ice amounts are assumed (i.e., clear-sky conditions), although the precipitation rate is the same as in the control all-sky simulation. By including or excluding clouds, we quantify time-integrated feedbacks for the first time. We find that clouds were responsible for a 3.1%, 0.3%, and 0.7% increase in surface melt extent (of the total GrIS area) in 2012, 2013, and 2014, respectively. During the same periods, clouds reduced solar heating and thus daily runoff by 1.6, 0.8, and 1.0 Gt day-1, respectively: clouds did not enhance surface mass loss. In the ablation areas, the presence of clouds results in a reduction of downward latent heat flux at the snow/ice surface so that much less energy is available for surface melt, which highlights the importance of indirect time-integrated feedbacks of cloud radiative effects.

Bacterial community changes with granule size in cryoconite and their susceptibility to exogenous nutrients on NW Greenland glaciers.

Cryoconite granules are dark-colored biological aggregates on glaciers. Bacterial community varies with granule size, however, community change in space and their susceptibility to environmental factors has not been described yet. Therefore, we focused on bacterial community from four different granule sizes (30-249 µm, 250-750 µm, 750-1599 µm, more than 1600 µm diameter) in 10 glaciers in northwestern Greenland and their susceptibility to exogenous nutrients in cryoconite hole. A filamentous cyanobacterium Phormidesmis priestleyi, which has been frequently reported from glaciers in Arctic was abundant (10%-26%) across any size of granules on most of glaciers. Bacterial community across glaciers became similar with size increase, and whence smallest size fractions contain more unique genera in each glacier. Multivariate analysis revealed that effect of nutrients to beta diversity is larger in smaller granules (30-249 µm and 250-750 µm diameter), suggesting that bacterial susceptibility to nutrients changes with growth of granule (i.e. P. priestleyi was affected by nitrate in early growth stage).

Fast yet accurate computation of radiances in shortwave infrared satellite remote sensing channels.

Accurate radiative transfer simulations of signals received by sensors deployed on satellite platforms for remote sensing purposes can be computationally demanding depending on channel width and the spectral variation of atmospheric and surface optical properties. Therefore, methods that can speed up such simulations are desirable. While it is common practice to use atmospheric "window" channels to minimize the influence of gaseous absorption, the impact of the underlying surface as well as clouds and aerosols has received less attention. To reduce the number of monochromatic computations required to obtain a desired accuracy, one may average the inherent optical properties (IOPs) over a spectral band to generate effective or mean IOP values to be used in "quasi-monochromatic" radiative transfer computations. Comparison of radiances produced by computations based on mean (quasi-monochromatic) IOPs with benchmark results in typical shortwave infrared window channels, revealed that while this approach may be sufficient for gaseous absorption, it led to significant errors in the presence spectrally varying surface IOPs, in general, and snow/ice surfaces, in particular. To solve this problem, a new method was developed in which a satellite channel is represented by a few subbands. This new method significantly reduces the error resulting from IOP averaging to be typically less than 1%. An additional correction was also developed to further reduce the error incurred by use of mean gas IOPs for large solar zenith angles to be less than 0.01%.

Microbial community variation in cryoconite granules on Qaanaaq Glacier, NW Greenland.

Cryoconite granules are aggregations of microorganisms with mineral particles that form on glacier surfaces. To understand the processes by which the granules develop, this study focused on the altitudinal distribution of the granules and photosynthetic microorganisms on the glacier, bacterial community variation with granules size and environmental factors affecting the growth of the granules. Size-sorted cryoconite granules collected from five different sites on Qaanaaq Glacier were analyzed. C and N contents were significantly higher in large (diameter greater than 250 µm) granules than in smaller (diameter 30-249 µm) granules. Bacterial community structures, based on 16S rRNA gene amplicon sequencing, were different between the smaller and larger granules. The filamentous cyanobacterium Phormidesmis priestleyi was the dominant bacterial species in larger granules. Multivariate analysis suggests that the abundance of mineral particles on the glacier surface is the main factor controlling growth of these cyanobacteria. These results show that the supply of mineral particles on the glacier enhances granule development, that P. priestleyi is likely the key species for primary production and the formation of the granules and that the bacterial community in the granules changes over the course of the granule development.

Retrieval of snow physical parameters by neural networks and optimal estimation: case study for ground-based spectral radiometer system.

A new retrieval algorithm for estimation of snow grain size and impurity concentration from spectral radiation data is developed for remote sensing applications. A radiative transfer (RT) model for the coupled atmosphere-snow system is used as a forward model. This model simulates spectral radiant quantities for visible and near-infrared channels. The forward RT calculation is, however, the most time-consuming part of the forward-inverse modeling. Therefore, we replaced it with a neural network (NN) function for fast computation of radiances and Jacobians. The retrieval scheme is based on an optimal estimation method with a priori constraints. The NN function was also employed to obtain an accurate first guess in the retrieval scheme. Validation with simulation data shows that a combination of NN techniques and optimal estimation method can provide more accurate retrievals than by using only NN techniques. In addition, validation with in-situ measurements conducted by using ground-based spectral radiometer system shows that comparison between retrieved snow parameters with in-situ measurements is acceptable with satisfactory accuracy. The algorithm provides simultaneous, accurate and fast retrieval of the snow properties. The algorithm presented here is useful for airborne/satellite remote sensing.

Enhancing osteogenic differentiation of MC3T3-E1 cells by immobilizing inorganic polyphosphate onto hyaluronic acid hydrogel.

In tissue engineering, precise control of cues in the microenvironment is essential to stimulate cells to undergo bioactivities such as proliferation, differentiation, and matrix production. However, current approaches are inefficient in providing nondepleting cues. In this study, we have developed a novel bioactive hydrogel (HAX-PolyP) capable of enhancing tissue growth by conjugating inorganic polyphosphate chains onto hyaluronic acid macromers. The immobilized polyphosphates provided constant osteoconductive stimulation to the embedded murine osteoblast precursor cells, resulting in up-regulation of osteogenic marker genes and enhanced levels of ALP activity. The osteoconductive activity was significantly higher when compared to those stimulated with free-floating polyphosphates. Even at very low concentrations, immobilization of polyphosphates onto the scaffold allowed sufficient signaling leading to more effective osteoconduction. These results demonstrate the potential of our novel material as an injectable bioactive scaffold, which can be clinically useful for developing bone grafts and bone regeneration applications.

Modeling angular-dependent spectral emissivity of snow and ice in the thermal infrared atmospheric window.

A model of angular-dependent emissivity spectra of snow and ice in the 8-14 µm atmospheric window is constructed. Past field research revealed that snow emissivity varies depending on snow grain size and the exitance angle. Thermography images acquired in this study further revealed that not only welded snow particles such as sun crust, but also disaggregated particles such as granular snow and dendrite crystals exhibit high reflectivity on their crystal facets, even when the bulk snow surface exhibits blackbody-like behavior as a whole. The observed thermal emissive behaviors of snow particles suggest that emissivity of the bulk snow surface can be expressed by a weighted sum of two emissivity components: those of the specular and blackbody surfaces. Based on this assumption, a semi-empirical emissivity model was constructed; it is expressed by a linear combination of specular and blackbody surfaces' emissivities with a weighting parameter characterizing the specularity of the bulk surface. Emissivity spectra calculated using the model succeeded in reproducing the past in situ measured directional spectra of various snow types by employing a specific weighting parameter for each snow type.

Retrieval of snow physical parameters using a ground-based spectral radiometer.

A ground-based spectral radiometer system for albedo and flux (GSAF) was developed to retrieve a mass concentration of snow impurities and effective snow grain size automatically. The GSAF measures spectral albedo and diffuse fraction with a single sensor to omit a radiometric calibration. The deviation from an ideal cosine response of the sensor to insolation is precisely corrected. The snow physical parameters can be retrieved with the GSAF even under cloudy conditions, because the effect of illumination conditions on albedo is considered in a retrieval algorithm. Continuous measurements with the GSAF at two snowfields in Hokkaido, Japan, showed the correlations between the retrieved parameters and in situ measurements (R=0.595 to 0.940).

Monte Carlo simulations of spectral albedo for artificial snowpacks composed of spherical and nonspherical particles.

The optical properties of snowpacks composed of spherical and nonspherical particles artificially prepared in a cold laboratory are investigated by measuring spectral albedos. The measured spectral albedo in the spectral region lambda=0.35-2.5 microm is compared with the theoretically calculated albedo, for which a Monte Carlo radiative transfer model is employed for multiple scattering combined with the Mie theory and the ray-tracing technique for single scattering by snow particles. Since the spherical particles are a little aggregate, the effects of a cluster of the spheres on snow albedo are examined using a generalized multiparticle Mie-solution model [Appl. Opt. 34, 4573 (1995); J. Quant. Spectrosc. Radiat. Transf. 79-80, 1121 (2003)]. The snow albedo of a cluster of the spheres can be represented with that of the singe sphere slightly larger than its component of the cluster in case of small grains. The observed albedos for the spherical snow particles agree with the theoretically calculated ones for the snow grain size measured in the snow pit work. The snow albedos for the nonspherical particles, which were dendrites, are influenced by the branch width and the branch length, based on a comparison of the theoretically calculated albedo by using circular cylindrical snow particles and the observed albedo. The snow albedo in the near-infrared region depends on the branch width only when the branch length is sufficiently greater than the branch width. The comparison between the spherical and nonspherical snow particles indicates that the spectral albedo of the nonspherical particles can be represented by using an equal volume-area ratio sphere.

Efficient use of an improved radiative transfer code to simulate near-global distributions of satellite-measured radiances.

Two new extension modules that give the water-leaving radiance from the ocean and the snow bidirectional reflectance distribution function were implemented in the latest radiative transfer code. In addition, to simulate the near-global distributions of satellite-measured radiances by using the improved radiative transfer code, we tested and applied the look-up table method together with the process-separation technique of the radiative transfer calculation. The computing time was reduced from 1 year to 20 s to simulate one channel, one scene of the Global Imager image by use of an Alpha 21164A-2 (600-MHz) machine. The error analyses showed that the radiances were simulated with less than 1% error for the nonabsorbing visible channels and approximately 2% error for absorbing channels by use of this method.

Path-radiance correction by polarization observation of Sun glint glitter for remote measurements of tropospheric greenhouse gases.

High-accuracy remote measurement of greenhouse gases is hampered by contamination of the field of view by the path radiance of solar radiation scattered from clouds and aerosols. A method is proposed for eliminating the effect of path radiance by differentiating two components of polarized light. The polarization of path radiance is measured directly at the wave-number region of strong water-vapor absorption. Using this measurement, we eliminate the components of path radiance involved in other bands, which are used for greenhouse gas measurements, by differentiating two components of the polarized light. It is shown that the effect of path radiance on retrieving the column amount of gases potentially can be reduced to below 0.1%.