Bibliografie tematiche / Melt ponds

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Letteratura scientifica selezionata sul tema "Melt ponds"

Autore: Grafiati
Pubblicato: 4 giugno 2021
Ultima modifica: 13 febbraio 2022

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Articoli di riviste sul tema "Melt ponds"

1

Hohenegger, C., B. Alali, K. R. Steffen, D. K. Perovich e K. M. Golden. "Transition in the fractal geometry of Arctic melt ponds". Cryosphere 6, n. 5 (19 ottobre 2012): 1157–62. http://dx.doi.org/10.5194/tc-6-1157-2012.

Testo completo
Abstract (sommario):
Abstract. During the Arctic melt season, the sea ice surface undergoes a remarkable transformation from vast expanses of snow covered ice to complex mosaics of ice and melt ponds. Sea ice albedo, a key parameter in climate modeling, is determined by the complex evolution of melt pond configurations. In fact, ice–albedo feedback has played a major role in the recent declines of the summer Arctic sea ice pack. However, understanding melt pond evolution remains a significant challenge to improving climate projections. By analyzing area–perimeter data from hundreds of thousands of melt ponds, we find here an unexpected separation of scales, where pond fractal dimension D transitions from 1 to 2 around a critical length scale of 100 m2 in area. Pond complexity increases rapidly through the transition as smaller ponds coalesce to form large connected regions, and reaches a maximum for ponds larger than 1000 m2, whose boundaries resemble space-filling curves, with D ≈ 2. These universal features of Arctic melt pond evolution are similar to phase transitions in statistical physics. The results impact sea ice albedo, the transmitted radiation fields under melting sea ice, the heat balance of sea ice and the upper ocean, and biological productivity such as under ice phytoplankton blooms.
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2

Hohenegger, C., B. Alali, K. R. Steffen, D. K. Perovich e K. M. Golden. "Transition in the fractal geometry of Arctic melt ponds". Cryosphere Discussions 6, n. 3 (15 giugno 2012): 2161–77. http://dx.doi.org/10.5194/tcd-6-2161-2012.

Testo completo
Abstract (sommario):
Abstract. During the Arctic melt season, the sea ice surface undergoes a remarkable transformation from vast expanses of snow covered ice to complex mosaics of ice and melt ponds. Sea ice albedo, a key parameter in climate modeling, is determined by the complex evolution of melt pond configurations. In fact, ice-albedo feedback has played a major role in the recent declines of the summer Arctic sea ice pack. However, understanding melt pond evolution remains a significant challenge to improving climate projections. By analyzing area-perimeter data from hundreds of thousands of melt ponds, we find here an unexpected separation of scales, where pond fractal dimension D transitions from 1 to 2 around a critical length scale of 100 m2 in area. Pond complexity increases rapidly through the transition as smaller ponds coalesce to form large connected regions, and reaches a maximum for ponds larger than 1000 m2 whose boundaries resemble space filling curves with D ≈ 2. These universal features of Arctic melt pond evolution are similar to phase transitions in statistical physics. The results impact sea ice albedo, the transmitted radiation fields under melting sea ice, the heat balance of sea ice and the upper ocean, and biological productivity such as under ice phytoplankton blooms.
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3

Geilfus, N. X., R. J. Galley, O. Crabeck, T. Papakyriakou, J. Landy, J. L. Tison e S. Rysgaard. "Inorganic carbon dynamics of melt pond-covered first year sea ice in the Canadian Arctic". Biogeosciences Discussions 11, n. 5 (23 maggio 2014): 7485–519. http://dx.doi.org/10.5194/bgd-11-7485-2014.

Testo completo
Abstract (sommario):
Abstract. Melt pond formation is a common feature of the spring and summer Arctic sea ice. However, the role of the melt ponds formation and the impact of the sea ice melt on both the direction and size of CO2 flux between air and sea is still unknown. Here we describe the CO2-carbonate chemistry of melting sea ice, melt ponds and the underlying seawater associated with measurement of CO2 fluxes across first year landfast sea ice in the Resolute Passage, Nunavut, in June 2012. Early in the melt season, the increase of the ice temperature and the subsequent decrease of the bulk ice salinity promote a strong decrease of the total alkalinity (TA), total dissolved inorganic carbon (TCO2) and partial pressure of CO2 (pCO2) within the bulk sea ice and the brine. Later on, melt pond formation affects both the bulk sea ice and the brine system. As melt ponds are formed from melted snow the in situ melt pond pCO2 is low (36 μatm). The percolation of this low pCO2 melt water into the sea ice matrix dilutes the brine resulting in a strong decrease of the in situ brine pCO2 (to 20 μatm). As melt ponds reach equilibrium with the atmosphere, their in situ pCO2 increase (up to 380 μatm) and the percolation of this high concentration pCO2 melt water increase the in situ brine pCO2 within the sea ice matrix. The low in situ pCO2 observed in brine and melt ponds results in CO2 fluxes of −0.04 to −5.4 mmol m–2 d–1. As melt ponds reach equilibrium with the atmosphere, the uptake becomes less significant. However, since melt ponds are continuously supplied by melt water their in situ pCO2 still remains low, promoting a continuous but moderate uptake of CO2 (~ −1mmol m–2 d–1). The potential uptake of atmospheric CO2 by melting sea ice during the Arctic summer has been estimated from 7 to 16 Tg of C ignoring the role of melt ponds. This additional uptake of CO2 associated to Arctic sea ice needs to be further explored and considered in the estimation of the Arctic Ocean's overall CO2 budget.
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4

Podgorny, Igor A. "Calculation of solar-energy inputs into melt ponds". Annals of Glaciology 25 (1997): 188–92. http://dx.doi.org/10.1017/s0260305500014014.

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Abstract (sommario):
The emphasis of this paper is on the partitioning of solar energy in an open plane-parallel melt pond with a Lambertian bottom. Spectral radiative-energy fluxes into the meltwater and underlying ice ocean layers are calculated analytically as a function of pond-bottom spectral albedo, pond depth and illumination condition Albedo of the pond bottom is reconstructed from data on pond albedo and depth. Results of calculations are presented for melt ponds of comparatively high and comparatively low reflectivity for a broad range of pond depths and for various illumination conditions. In the 350–700 nm spectral band, spectrally averaged pond albedo and solar-energy inputs are a function of pond-bottom albedo, pond depth and illumination condition. In the 700–2400 nm spectral band, the partitioning of solar energy in melt ponds depends on pond depth and illumination condition only. The effect of uncertainty in specifying pond-bottom albedo on total energy input into the water layer is relatively small compared to that on spectrally averaged pond albedo and total energy input into the ice-ocean layer.
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5

Podgorny, Igor A. "Calculation of solar-energy inputs into melt ponds". Annals of Glaciology 25 (1997): 188–92. http://dx.doi.org/10.3189/s0260305500014014.

Testo completo
Abstract (sommario):
The emphasis of this paper is on the partitioning of solar energy in an open plane-parallel melt pond with a Lambertian bottom. Spectral radiative-energy fluxes into the meltwater and underlying ice ocean layers are calculated analytically as a function of pond-bottom spectral albedo, pond depth and illumination condition Albedo of the pond bottom is reconstructed from data on pond albedo and depth. Results of calculations are presented for melt ponds of comparatively high and comparatively low reflectivity for a broad range of pond depths and for various illumination conditions. In the 350–700 nm spectral band, spectrally averaged pond albedo and solar-energy inputs are a function of pond-bottom albedo, pond depth and illumination condition. In the 700–2400 nm spectral band, the partitioning of solar energy in melt ponds depends on pond depth and illumination condition only. The effect of uncertainty in specifying pond-bottom albedo on total energy input into the water layer is relatively small compared to that on spectrally averaged pond albedo and total energy input into the ice-ocean layer.
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6

Rösel, Anja, e Lars Kaleschke. "Comparison of different retrieval techniques for melt ponds on Arctic sea ice from Landsat and MODIS satellite data". Annals of Glaciology 52, n. 57 (2011): 185–91. http://dx.doi.org/10.3189/172756411795931606.

Testo completo
Abstract (sommario):
AbstractMelt ponds are regularly observed on the surface of Arctic sea ice in late spring and summer. They strongly reduce the surface albedo and accelerate the decay of Actic sea ice. Until now, only a few studies have looked at the spatial extent of melt ponds on Arctic sea ice. Knowledge of the melt-pond distribution on the entire Arctic sea ice would provide a solid basis for the parameterization of melt ponds in existing sea-ice models. Due to the different spectral properties of snow, ice and water, a multispectral sensor such as Landsat 7 ETM+ is generally applicable for the analysis of distribution. an additional advantage of the ETM+ sensor is the very high spatial resolution (30 m). an algorithm based on a principal component analysis (PCA) of two spectral channels has been developed in order to determine the melt-pond fraction. PCA allows differentiation of melt ponds and other surface types such as snow, ice or water. Spectral bands 1 and 4 with central wavelengths at 480 and 770 nm, respectively, are used as they represent the differences in the spectral albedo of melt ponds. A Landsat 7 ETM+ scene from 19 July 2001 was analysed using PCA. the melt-pond fraction determined by the PCA method yields a different spatial distribution of the ponded areas from that developed by others. A MODIS subset from the same date and area is also analysed. the classification of MODIS data results in a higher melt-pond fraction than both Landsat classifications.
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7

Lin, Ling, Jianfeng He, Fang Zhang, Shunan Cao e Can Zhang. "Algal bloom in a melt pond on Canada Basin pack ice". Polar Record 52, n. 1 (19 giugno 2015): 114–17. http://dx.doi.org/10.1017/s0032247415000510.

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Abstract (sommario):
ABSTRACTMelt ponds are common on the surface of ice floes in the Arctic Ocean during spring and summer. Few studies on melt pond algae communities have been accomplished. These studies have shown that these melt ponds were ultra-oligotrophic, and contribute little to overall productivity. However, during the 6th Chinese Arctic Cruise in the Arctic Ocean in summer 2014, a closed coloured melt pond with a chlorophyll a concentration of 15.32 μg/L was observed on Arctic pack ice in the Canada Basin. The bloom was caused by the chlorophyte Carteria lunzensis at an abundance of 15.49×106 cells/L and biomass of 5.07 mg C/L. Primary production within surface melt ponds may need more attention along with Arctic warming.
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8

Gourdal, Margaux, Martine Lizotte, Guillaume Massé, Michel Gosselin, Michel Poulin, Michael Scarratt, Joannie Charette e Maurice Levasseur. "Dimethyl sulfide dynamics in first-year sea ice melt ponds in the Canadian Arctic Archipelago". Biogeosciences 15, n. 10 (29 maggio 2018): 3169–88. http://dx.doi.org/10.5194/bg-15-3169-2018.

Testo completo
Abstract (sommario):
Abstract. Melt pond formation is a seasonal pan-Arctic process. During the thawing season, melt ponds may cover up to 90 % of the Arctic first-year sea ice (FYI) and 15 to 25 % of the multi-year sea ice (MYI). These pools of water lying at the surface of the sea ice cover are habitats for microorganisms and represent a potential source of the biogenic gas dimethyl sulfide (DMS) for the atmosphere. Here we report on the concentrations and dynamics of DMS in nine melt ponds sampled in July 2014 in the Canadian Arctic Archipelago. DMS concentrations were under the detection limit (< 0.01 nmol L−1) in freshwater melt ponds and increased linearly with salinity (rs = 0.84, p ≤ 0.05) from ∼ 3 up to ∼ 6 nmol L−1 (avg. 3.7 ± 1.6 nmol L−1) in brackish melt ponds. This relationship suggests that the intrusion of seawater in melt ponds is a key physical mechanism responsible for the presence of DMS. Experiments were conducted with water from three melt ponds incubated for 24 h with and without the addition of two stable isotope-labelled precursors of DMS (dimethylsulfoniopropionate), (D6-DMSP) and dimethylsulfoxide (13C-DMSO). Results show that de novo biological production of DMS can take place within brackish melt ponds through bacterial DMSP uptake and cleavage. Our data suggest that FYI melt ponds could represent a reservoir of DMS available for potential flux to the atmosphere. The importance of this ice-related source of DMS for the Arctic atmosphere is expected to increase as a response to the thinning of sea ice and the areal and temporal expansion of melt ponds on Arctic FYI.
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9

Li, Qing, Chunxia Zhou, Lei Zheng, Tingting Liu e Xiaotong Yang. "Monitoring evolution of melt ponds on first-year and multiyear sea ice in the Canadian Arctic Archipelago with optical satellite data". Annals of Glaciology 61, n. 82 (8 luglio 2020): 154–63. http://dx.doi.org/10.1017/aog.2020.24.

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Abstract (sommario):
AbstractThe evolution of melt ponds on Arctic sea ice in summer is one of the main factors that affect sea-ice albedo and hence the polar climate system. Due to the different spectral properties of open water, melt pond and sea ice, the melt pond fraction (MPF) can be retrieved using a fully constrained least-squares algorithm, which shows a high accuracy with root mean square error ~0.06 based on the validation experiment using WorldView-2 image. In this study, the evolution of ponds on first-year and multiyear ice in the Canadian Arctic Archipelago was compared based on Sentinel-2 and Landsat 8 images. The relationships of pond coverage with air temperature and albedo were analysed. The results show that the pond coverage on first-year ice changed dramatically with seasonal maximum of 54%, whereas that on multiyear ice changed relatively flat with only 30% during the entire melting period. During the stage of pond formation, the ponds expanded rapidly when the temperature increased to over 0°C for three consecutive days. Sea-ice albedo shows a significantly negative correlation (R = −1) with the MPF in melt season and increases gradually with the refreezing of ponds and sea ice.
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10

Kern, Stefan, Anja Rösel, Leif Toudal Pedersen, Natalia Ivanova, Roberto Saldo e Rasmus Tage Tonboe. "The impact of melt ponds on summertime microwave brightness temperatures and sea-ice concentrations". Cryosphere 10, n. 5 (26 settembre 2016): 2217–39. http://dx.doi.org/10.5194/tc-10-2217-2016.

Testo completo
Abstract (sommario):
Abstract. Sea-ice concentrations derived from satellite microwave brightness temperatures are less accurate during summer. In the Arctic Ocean the lack of accuracy is primarily caused by melt ponds, but also by changes in the properties of snow and the sea-ice surface itself. We investigate the sensitivity of eight sea-ice concentration retrieval algorithms to melt ponds by comparing sea-ice concentration with the melt-pond fraction. We derive gridded daily sea-ice concentrations from microwave brightness temperatures of summer 2009. We derive the daily fraction of melt ponds, open water between ice floes, and the ice-surface fraction from contemporary Moderate Resolution Spectroradiometer (MODIS) reflectance data. We only use grid cells where the MODIS sea-ice concentration, which is the melt-pond fraction plus the ice-surface fraction, exceeds 90 %. For one group of algorithms, e.g., Bristol and Comiso bootstrap frequency mode (Bootstrap_f), sea-ice concentrations are linearly related to the MODIS melt-pond fraction quite clearly after June. For other algorithms, e.g., Near90GHz and Comiso bootstrap polarization mode (Bootstrap_p), this relationship is weaker and develops later in summer. We attribute the variation of the sensitivity to the melt-pond fraction across the algorithms to a different sensitivity of the brightness temperatures to snow-property variations. We find an underestimation of the sea-ice concentration by between 14 % (Bootstrap_f) and 26 % (Bootstrap_p) for 100 % sea ice with a melt-pond fraction of 40 %. The underestimation reduces to 0 % for a melt-pond fraction of 20 %. In presence of real open water between ice floes, the sea-ice concentration is overestimated by between 26 % (Bootstrap_f) and 14 % (Bootstrap_p) at 60 % sea-ice concentration and by 20 % across all algorithms at 80 % sea-ice concentration. None of the algorithms investigated performs best based on our investigation of data from summer 2009. We suggest that those algorithms which are more sensitive to melt ponds could be optimized more easily because the influence of unknown snow and sea-ice surface property variations is less pronounced.
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Più fonti

Tesi sul tema "Melt ponds"

1

Scott, F. "Modelling the evolution of Arctic melt ponds". Thesis, University College London (University of London), 2009. http://discovery.ucl.ac.uk/16333/.

Testo completo
Abstract (sommario):
During winter the ocean surface at the poles freezes over to form sea ice. Sea ice floats on the ocean surface and has a matrix structure caused by the rejection of salts during freezing. In the summer sea ice melts at its surface creating melt ponds. An accurate estimate of the fraction of the upper sea ice surface covered in melt ponds during the summer melt season is essential for a realistic estimate of the albedo for global climate models. I will present a melt-pond{sea-ice model that simulates the twodimensional (areal) evolution of melt ponds on an Arctic sea-ice surface. This advancements of this model compared to previous models are the inclusion of snow topography, a realistic hydraulic balance and calculation of drainage rates and the incorporation of a detailed one-dimensional thermodynamic model. Water transport across and through the sea-ice surface is described by the major hydraulic processes believed to be present. Thermodynamic processes are modelled using the mushy-layer equations in sea ice, heat diffusion equations in snow and using assumptions of turbulent heat flux in melt ponds, along with a three-layer two-stream radiation model. The model simulates a section of a sea ice floe considered to be in hydrostatic equilibrium, where edge effects such as the presence of leads are neglected and consists of a grid of cells, each of which can be in one of four possible configurations: snow covered ice; bare ice; melt pond covered ice or open water. Eventually, a cluster of adjacent cells each containing melt water may be considered to have formed a melt pond. Lateral and vertical melt water transport is described by Darcy's Law. The model is initialised with ice topographies that represent either first-year or multiyear sea ice, which are reconstructed from SHEBA ice thickness data using standard statistical methods. The roughness and thickness of the ice and snow surfaces were altered and the sensitivity of the model to the initial data was tested. First-year ice and multiyear ice simulations confirmed observed differences in individual pond size and depth. Sensitivity studies showed that pond fraction is most sensitive to mean initial snow depth in first-year ice simulations and reduction of ice permeability in all cases.
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2

Taylor, Paul Duncan. "Mathematical modelling the formation and evolution of melt ponds on sea ice". Thesis, University College London (University of London), 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.406901.

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3

Nasonova, Sasha. "Estimating Arctic sea ice melt pond fraction and assessing ice type separability during advanced melt". Thesis, Remote Sensing, 2017. https://dspace.library.uvic.ca//handle/1828/9313.

Testo completo
Abstract (sommario):
Arctic sea ice is rapidly declining in extent, thickness, volume and age, with the majority of the decline in extent observed at the end of the melt season. Advanced melt is a thermodynamic regime and is characterized by the formation of melt ponds on the sea ice surface, which have a lower surface albedo (0.2-0.4) than the surrounding ice (0.5-0.7) allowing more shortwave radiation to enter the system. The loss of multiyear ice (MYI) may have a profound impact on the energy balance of the system because melt ponds on first-year ice (FYI) comprise up to 70% of the ice surface during advanced melt, compared to 40% on MYI. Despite the importance of advanced melt to the ocean-sea ice-atmosphere system, advanced melt and the extent to which winter conditions influence it remain poorly understood due to the highly dynamic nature of melt pond formation and evolution, and a lack of reliable observations during this time. In order to establish quantitative links between winter and subsequent advanced melt conditions, and assess the effects of scale and choice of aggregation features on the relationships, three data aggregation approaches at varied spatial scales were used to compare high resolution satellite GeoEye-1 optical images of melt pond covered sea ice to winter airborne laser scanner surface roughness and electromagnetic induction sea ice thickness measurements. The findings indicate that winter sea ice thickness has a strong association with melt pond fraction (fp) for FYI and MYI. FYI winter surface roughness is correlated with fp, whereas for MYI no association with fp was found. Satellite-borne synthetic aperture radar (SAR) data are heavily relied upon for sea ice observation; however, during advanced melt the reliability of observations is reduced. In preparation for the upcoming launch of the RADARSAT Constellation Mission (RCM), the Kolmogorov-Smirnov (KS) statistical test was used to assess the ability of simulated RCM parameters and grey level co-occurrence matrix (GLCM) derived texture features to discriminate between major ice types during winter and advanced melt, with a focus on advanced melt. RCM parameters with highest discrimination ability in conjunction with optimal GLCM texture features were used as input parameters for Support Vector Machine (SVM) supervised classifications. The results indicate that steep incidence angle RCM parameters show promise for distinguishing between FYI and MYI during advanced melt with an overall classification accuracy of 77.06%. The addition of GLCM texture parameters improved accuracy to 85.91%. This thesis provides valuable contributions to the growing body of literature on fp parameterization and SAR ice type discrimination during advanced melt.
Graduate
2019-03-21
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4

König, Marcel [Verfasser], Natascha [Akademischer Betreuer] Oppelt e Peter [Gutachter] Gege. "Mapping Melt Pond Bathymetry on Arctic Sea Ice by Means of Optical Remote Sensing / Marcel König ; Gutachter: Peter Gege ; Betreuer: Natascha Oppelt". Kiel : Universitätsbibliothek Kiel, 2021. http://d-nb.info/1234451379/34.

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5

Kirk, Robert B. "The optical and microwave properties of melt ponds over first year Arctic sea ice". 2005. http://hdl.handle.net/1993/20148.

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6

"Ponds, Flows, and Ejecta of Impact Cratering and Volcanism: A Remote Sensing Perspective of a Dynamic Moon". Doctoral diss., 2016. http://hdl.handle.net/2286/R.I.38376.

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Abstract (sommario):
abstract: Both volcanism and impact cratering produce ejecta and associated deposits incorporating a molten rock component. While the heat sources are different (exogenous vs. endogenous), the end results are landforms with similar morphologies including ponds and flows of impact melt and lava around the central crater. Ejecta from both impact and volcanic craters can also include a high percentage of melted rock. Using Lunar Reconnaissance Orbiter Camera Narrow Angle Camera (LROC NAC) images, crucial details of these landforms are finally revealed, suggesting a much more dynamic Moon than is generally appreciated. Impact melt ponds and flows at craters as small as several hundred meters in diameter provide empirical evidence of abundant melting during the impact cratering process (much more than was previously thought), and this melt is mobile on the lunar surface for a significant time before solidifying. Enhanced melt deposit occurrences in the lunar highlands (compared to the mare) suggest that porosity, target composition, and pre-existing topography influence melt production and distribution. Comparatively deep impact craters formed in young melt deposits connote a relatively rapid evolution of materials on the lunar surface. On the other end of the spectrum, volcanic eruptions have produced the vast, plains-style mare basalts. However, little was previously known about the details of small-area eruptions and proximal volcanic deposits due to a lack of resolution. High-resolution images reveal key insights into small volcanic cones (0.5-3 km in diameter) that resemble terrestrial cinder cones. The cones comprise inter-layered materials, spatter deposits, and lava flow breaches. The widespread occurrence of the cones in most nearside mare suggests that basaltic eruptions occur from multiple sources in each basin and/or that rootless eruptions are relatively common. Morphologies of small-area volcanic deposits indicate diversity in eruption behavior of lunar basaltic eruptions driven by magmatic volatiles. Finally, models of polar volatile behavior during impact-heating suggest that chemical alteration of minerals in the presence of liquid water is one possible outcome that was previously not thought possible on the Moon.
Dissertation/Thesis
Doctoral Dissertation Geological Sciences 2016
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7

Jungblut, Anne Dorothee Biotechnology &amp Biomolecular Sciences Faculty of Science UNSW. "Characterisation of microbial Mat communities in meltwater ponds of the McMurdo ice shelf, Antarctica". 2007. http://handle.unsw.edu.au/1959.4/40496.

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Abstract (sommario):
The investigation presented in this thesis examined the microbial and functional diversity of the meltwater ponds Fresh, Orange and Salt Ponds on the McMurdo Ice Shelf, near Bratina Island, Antarctica. These sites were chosen because of the ecological importance and absence of detailed characterisations of their diversity and function as part of Antarctica?s largest wetland. Particular focus was on cyanobacterial diversity, nitrogen fixation and secondary metabolite production. Using 16S rRNA gene and morphological analysis a large diversity of cyanobacteria (more than 22 phylotypes) was identified with high phylogenetic similarities (up to 99% sequence identity) to cyanobacteria from mats in other regions of Antarctica. In addition biogeographical distributions were identified including potentially endemic and cosmopolitan cyanobacteria. High salinities were also connected to the change and reduction of diversity. Lipid marker analyses were performed targeting hydrocarbons, ether-linked hydrocarbons, methylated fatty acid esters (FAME), wax esters, hopanols and sterols. Lipid biomarker profiles were similar to typical cyanobacteria dominated mats with major input from microorganisms including oxygenic and anoxygenic phototrophs, obligate aerobic and anaerobic heterotrophs that conduct the metabolic processes of fermentation, sulphate reduction, sulphate and iron-oxidation, methanogeneses. Signature lipids indicative of Chloroflexus and archaea, as well as branched aliphatic alkanes with quaternary substituted carbon atoms (BAQCs), were identified for the first time in Fresh, Orange and Salt Ponds. Based on nifH gene analysis, the nitrogen fixing diversity characterised in Orange Pond consisted of cyanobacterial Nostoc sp. as well as firmicutes, beta-, gamma- and delta-proteobacteria. Acetylene reduction assays and nifH gene RNA transcript diversity identified Nostoc sp. as a main contributor of nitrogenase activity in these ponds. Furthermore, analytical methods were used to identify the cyanobacterial secondary metabolites microcystins, although the genetic basis for this production and the toxin producer could not been identified. However non-ribosomal peptide synthetases (NRPS) and polyketide synthases (PKS) genes were identified which could be the genetic basis for novel bioactives. The use of a multi-disciplinary approach synthesis and subsequent results significantly increased our understanding of the diversity and function of microbial mat communities in the unique meltwater ponds of the McMurdo Ice shelf, Antarctica.
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8

Chang, Yueh-Cheng, e 張越程. "Investigating the spatiotemporal variation of crevasses, melt ponds and ice floes during the 2008 Ward Hunt Ice Shelf calving event- evidence from Formosat-2 remote sensing imagery". Thesis, 2009. http://ndltd.ncl.edu.tw/handle/20035598868631267847.

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Abstract (sommario):
碩士
國立成功大學
衛星資訊暨地球環境研究所
97
Ice shelves are vulnerable and sensitive to climate change. Their collapses indirectly lead to sea-level rising and further climate change. Typically speaking, causes for ice island calving in the Arctic include change of wind, sea ice retreat and fracture propagation. Although melt pond has been regarded as a precursor of the collapse of ice shelves, large numbers of melt ponds have been existed for at least a century in some of the ice shelves in the Canadian High Arctic (Jeffries, 2002). But the relationship between melt pond and ice island calving has not been well investigated yet due to lack of proper tool. This research aims to provide a preliminary insight in the relationship between ice-island calving and variations of features on the surface of ice shelf and sea from high spatiotemporal imagery. The case study is the three calving events during 2008 melt season in Ward Hunt Ice Shelf (WHIS), Ellesmere, in the Canadian High Arctic. WHIS has lost 90% of its area since the beginning of the 20th century after its 3000+ years of existence, which has been regarded as very sensitive but vulnerable to climate change. In 2007 (2 scenes) and 2008 (15 scenes), high-spatiotemporal optical images of Formosat-2 were acquired successfully in Polar Image Campaign (PIC) by National Space Organization (NSPO) from June to August. Surface features, such as melt pond, crevasse and sea ice, are extracted from these images for spatiotemporal analysis. MODIS imagery of WHIS is also employed to provide additional spatiotemporal information for the third calving event. There are several findings. Firstly, the areal reduction of melt pond is highly correlated with the increase of crevasse length statistically. Furthermore, crevasse and rift tend to propagate through ponds and troughs, implying the effect of weakening due to hydro-fracture mechanism. However, the trend slowed down during July 17th and 28th, which reveals some systematical change in the drainage system. Secondly, new troughs are also observed during 2007-2008 winter, and then became melt ponds; some of these further propagated as rifts, and then resulted in calving, developed into new ice front along with the ex-fracture in some area at last, which supports Holdsworth’s propose (1987) related the formation of the unique land feature (with hummocks and troughs) to pack ice pressure, plate buckling and creep formation as a result. The above mentioned two phenomena altogether not only indicate that melt water does weaken the ice shelf, but also align with the theories of hydro-fracture mechanism on ice-berg calving in the Antarctica (Rist et al., 2002; Scambos et al., 2009a). Thirdly, this set of time-sequential imagery also shows that sea ice concentration over ice front has high correlation with calving events. Lastly, intrusive flow of pack ice to marginal ice zone, eastward flow along the ice front and formation of new fast-ice near to the east of the new calving bay (18 August 2008), combined with the distribution of thin areas in the map of thickness, altogether suggests that there is seasonal outflow from Disraeli Fiord through the central crack, found in 2002, which is consistent to previous studies about the existence of the flow and the drainage of the freshwater (Jeffries et al., 1990; Mueller et al., 2003). The bottom flows probably contribute to differential thinning (especially bottom melting) and formation of cracks both found in 2002 and 2008. These findings imply that bottom flow is one of the potential mechanisms indirectly contributing to ice-island calving and ice-shelf disintegration, in addition to traditional factors, such as overall thinning, off-shore wind, sea ice retreat and wave propagation. This is to be simulated in calving model furthermore in addition to refinement and verification with more field data and analyses.
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Rossnagel, Andrea L. "Spatial and temporal changes of photosynthetically available radiation, temperature and salinity beneath a variable sea ice cover". 2012. http://hdl.handle.net/1993/5090.

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Melt ponds greatly increase the transmission of solar radiation through sea ice relative to snow covered or bare ice. This rise in transmittance has the potential to enhance water column heating and primary production. I examine how spatially variable sea ice surfaces control the under-ice salinity, temperature and photosynthetically active radiation (PAR) and provide estimates of solar heating and primary production during melt. Conductivity, temperature and PAR profiles were measured in the Canadian Arctic under snow covered ice, leads, bare ice and melt ponds. The under-ice light field to a depth of 10 to 13 m was highly variable, controlled by increased transmission under melt ponds and shading by bare ice. Below, the light field became relatively homogeneous showing the depth the surface heterogeneity had an effect on transmitted PAR. Furthermore, one water column profile is not representative of the PAR, salinity or temperature under a spatially heterogeneous surface.
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Libri sul tema "Melt ponds"

1

Rösel, Anja. Detection of Melt Ponds on Arctic Sea Ice with Optical Satellite Data. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37033-5.

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Haeberli, Wilfried. Neue Seen als Folge des Gletscherschwundes im Hochgebirge: Chancen und Risiken : Forschungsbericht NFP 61, Projekt NELAK = Formation des nouveaux lacs suite au recul des glaciers en haute montagne : chances et risques. Zürich: VDF Hochschulverlag AG an der ETH Zürich, 2013.

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3

The diabetes DTOUR diet cookbook: 200 undeniably delicious recipes to balance your blood sugar and melt away pounds. [Emmaus, Pa.]: Rodale, 2009.

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4

Quinn, Barbara. The diabetes DTOUR diet cookbook: 200 undeniably delicious recipes to balance your blood sugar and melt away pounds. Emmaus, Pa: Rodale, 2009.

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5

Chilton, Floyd H. The gene smart diet: The revolutionary eating plan that will rewrite your genetic destiny--and melt away the pounds. Emmaus, Pa: Rodale, 2009.

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6

Aziz, Michael. The perfect 10 diet: The breakthrough diet solution : 10 key hormones you must balance to melt away the pounds and stay healthy for life. Naperville, Ill: Sourcebooks, 2010.

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Commons, Canada Parliament House of. Bill: An act to incorporate the Holiness Mov[e]ment (or Church) in Canada. Ottawa: S.E. Dawson, 2003.

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8

Rösel, Anja. Detection of Melt Ponds on Arctic Sea Ice with Optical Satellite Data. Springer, 2013.

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9

undifferentiated, Ian K. Smith. Fast Burn!: Melt the Fat, Drop the Pounds. St. Martin's Press, 2021.

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(Editor), Ron Kenner, a cura di. THE SMART DIETER'S CHEATING GUIDE: Eat and Watch Pounds Melt Away. Outskirts Press, 2007.

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Capitoli di libri sul tema "Melt ponds"

1

Rösel, Anja. "Melt Pond Determination from MODIS Data". In Detection of Melt Ponds on Arctic Sea Ice with Optical Satellite Data, 37–64. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37033-5_5.

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2

Rösel, Anja. "Melt Pond Determination from Landsat Satellite Data". In Detection of Melt Ponds on Arctic Sea Ice with Optical Satellite Data, 27–36. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37033-5_4.

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3

Scagliarini, Andrea, Enrico Calzavarini, Daniela Mansutti e Federico Toschi. "Modelling Sea Ice and Melt Ponds Evolution: Sensitivity to Microscale Heat Transfer Mechanisms". In Mathematical Approach to Climate Change and its Impacts, 179–98. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-38669-6_6.

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4

Rösel, Anja. "Introduction". In Detection of Melt Ponds on Arctic Sea Ice with Optical Satellite Data, 1–5. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37033-5_1.

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5

Rösel, Anja. "Physical Characteristics of Sea Ice". In Detection of Melt Ponds on Arctic Sea Ice with Optical Satellite Data, 7–16. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37033-5_2.

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Rösel, Anja. "Optical Remote Sensing". In Detection of Melt Ponds on Arctic Sea Ice with Optical Satellite Data, 17–25. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37033-5_3.

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Rösel, Anja. "Summary and Outlook". In Detection of Melt Ponds on Arctic Sea Ice with Optical Satellite Data, 65–94. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37033-5_6.

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Stopar, Julie D., e Carolyn H. van der Bogert. "Impact Melt Pond". In Encyclopedia of Planetary Landforms, 1–13. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4614-9213-9_236-1.

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Stopar, Julie D., e Carolyn H. van der Bogert. "Impact Melt Pond". In Encyclopedia of Planetary Landforms, 978–88. New York, NY: Springer New York, 2015. http://dx.doi.org/10.1007/978-1-4614-3134-3_236.

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"“Pounds, Ounces, Meat”". In I Love Dollars and Other Stories of China, 215–28. Columbia University Press, 2007. http://dx.doi.org/10.7312/zhu-13694-009.

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Atti di convegni sul tema "Melt ponds"

1

Sudakov, Ivan. "Arctic melt ponds and energy balance in the climate system". In RADIATION PROCESSES IN THE ATMOSPHERE AND OCEAN (IRS2016): Proceedings of the International Radiation Symposium (IRC/IAMAS). Author(s), 2017. http://dx.doi.org/10.1063/1.4975549.

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2

Rosel, Anja, e Lars Kaleschke. "Influence of melt ponds on microwave sensors' sea ice concentration retrieval algorithms". In IGARSS 2012 - 2012 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2012. http://dx.doi.org/10.1109/igarss.2012.6350608.

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3

Evans, T. W., M. J. Kalambokidis, I. Hawes e R. E. Summons. "Biomarker Signals from Microbial Mats in Melt Water Ponds from Bratina Island on the Mcmurdo Ice Shelf, Antarctica". In 29th International Meeting on Organic Geochemistry. European Association of Geoscientists & Engineers, 2019. http://dx.doi.org/10.3997/2214-4609.201903034.

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4

Fetterer, F., e N. Untersteiner. "Melt pond coverage statistics from classified satellite data". In IGARSS '98. Sensing and Managing the Environment. 1998 IEEE International Geoscience and Remote Sensing. Symposium Proceedings. (Cat. No.98CH36174). IEEE, 1998. http://dx.doi.org/10.1109/igarss.1998.703706.

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Marks, Henrik, Georg Heygster e Larysa Istomina. "Cloud filtering with MERIS and AATSR for melt pond detection on Arctic sea ice". In IGARSS 2016 - 2016 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2016. http://dx.doi.org/10.1109/igarss.2016.7731000.

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6

Libkin, Leonid. "Certain Answers Meet Zero-One Laws". In SIGMOD/PODS '18: International Conference on Management of Data. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3196959.3196983.

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7

Tziavelis, Nikolaos, Wolfgang Gatterbauer e Mirek Riedewald. "Optimal Join Algorithms Meet Top-k". In SIGMOD/PODS '20: International Conference on Management of Data. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3318464.3383132.

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8

Fors, Ane S., Anthony P. Doulgeris, Angelika H. H. Renner, Camilla Brekke e Sebastian Gerland. "On the relation between polarimetric synthetic aperture radar (SAR) features and sea ice melt pond fraction". In IGARSS 2015 - 2015 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2015. http://dx.doi.org/10.1109/igarss.2015.7326559.

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9

Shen, He, Salvador Rojas, Eduardo Molina, Francisco Moxo Galicia e Ni Li. "Development and Analysis of Robotic Arms for Humanoid Melo". In ASME 2018 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/imece2018-87987.

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Abstract (sommario):
A robotic arm is one of the most sophisticated components of a humanoid, due to its complexity in multi-degree-of-freedom actuation and sensing, size and weight constraints, and requirement for object manipulation. This paper talks about the design, development, and verification of a low-cost, light-weight robotic manipulator that can achieve anthropomorphic movements. The 5 degree-of-freedom robotic arm has a fully extended length of 31 – inches and weight of 7 - pounds. The joints of the arm were fabricated using mainly 3D printed parts using Polylactic Acid and Nylon and linked with carbon fiber tubing. The arm is actuated by 2 servo motors at the distal joint and 3 brushless DC motors at the proximal joints. All joints of the arm perform at zero backlash through harmonic gear boxes, which are also assembled mainly from 3D printed parts. The robotic arm has demonstrated a comparable performance to similar robotic arms on the market with significantly reduced cost.
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Nghiem, Son V., Jiyue Zhu, Shurun Tan, Donald K. Perovich, Christopher Polashenski, Stephen T. Lowe, Rashmi Shah et al. "Polar Sea Ice Thickness and Melt Pond Fraction Measurements with Multi-Frequency Bistatic Radar Polarimetric and Interferometric Reflectometry". In IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2019. http://dx.doi.org/10.1109/igarss.2019.8900079.

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