To see the other types of publications on this topic, follow the link: Melt ponds.
Journal articles on the topic 'Melt ponds'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 50 journal articles for your research on the topic 'Melt ponds.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.
1
Hohenegger, C., B. Alali, K. R. Steffen, D. K. Perovich, and K. M. Golden. "Transition in the fractal geometry of Arctic melt ponds." Cryosphere 6, no. 5 (October 19, 2012): 1157–62. http://dx.doi.org/10.5194/tc-6-1157-2012.
Full textAbstract:
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.
2
Hohenegger, C., B. Alali, K. R. Steffen, D. K. Perovich, and K. M. Golden. "Transition in the fractal geometry of Arctic melt ponds." Cryosphere Discussions 6, no. 3 (June 15, 2012): 2161–77. http://dx.doi.org/10.5194/tcd-6-2161-2012.
Full textAbstract:
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.
3
Geilfus, N. X., R. J. Galley, O. Crabeck, T. Papakyriakou, J. Landy, J. L. Tison, and S. Rysgaard. "Inorganic carbon dynamics of melt pond-covered first year sea ice in the Canadian Arctic." Biogeosciences Discussions 11, no. 5 (May 23, 2014): 7485–519. http://dx.doi.org/10.5194/bgd-11-7485-2014.
Full textAbstract:
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.
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.
Full textAbstract:
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.
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.
Full textAbstract:
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.
6
Rösel, Anja, and Lars Kaleschke. "Comparison of different retrieval techniques for melt ponds on Arctic sea ice from Landsat and MODIS satellite data." Annals of Glaciology 52, no. 57 (2011): 185–91. http://dx.doi.org/10.3189/172756411795931606.
Full textAbstract:
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.
7
Lin, Ling, Jianfeng He, Fang Zhang, Shunan Cao, and Can Zhang. "Algal bloom in a melt pond on Canada Basin pack ice." Polar Record 52, no. 1 (June 19, 2015): 114–17. http://dx.doi.org/10.1017/s0032247415000510.
Full textAbstract:
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.
8
Gourdal, Margaux, Martine Lizotte, Guillaume Massé, Michel Gosselin, Michel Poulin, Michael Scarratt, Joannie Charette, and Maurice Levasseur. "Dimethyl sulfide dynamics in first-year sea ice melt ponds in the Canadian Arctic Archipelago." Biogeosciences 15, no. 10 (May 29, 2018): 3169–88. http://dx.doi.org/10.5194/bg-15-3169-2018.
Full textAbstract:
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.
9
Li, Qing, Chunxia Zhou, Lei Zheng, Tingting Liu, and 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, no. 82 (July 8, 2020): 154–63. http://dx.doi.org/10.1017/aog.2020.24.
Full textAbstract:
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.
10
Kern, Stefan, Anja Rösel, Leif Toudal Pedersen, Natalia Ivanova, Roberto Saldo, and Rasmus Tage Tonboe. "The impact of melt ponds on summertime microwave brightness temperatures and sea-ice concentrations." Cryosphere 10, no. 5 (September 26, 2016): 2217–39. http://dx.doi.org/10.5194/tc-10-2217-2016.
Full textAbstract:
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.
11
Popović, Predrag, and Dorian Abbot. "A simple model for the evolution of melt pond coverage on permeable Arctic sea ice." Cryosphere 11, no. 3 (May 10, 2017): 1149–72. http://dx.doi.org/10.5194/tc-11-1149-2017.
Full textAbstract:
Abstract. As the melt season progresses, sea ice in the Arctic often becomes permeable enough to allow for nearly complete drainage of meltwater that has collected on the ice surface. Melt ponds that remain after drainage are hydraulically connected to the ocean and correspond to regions of sea ice whose surface is below sea level. We present a simple model for the evolution of melt pond coverage on such permeable sea ice floes in which we allow for spatially varying ice melt rates and assume the whole floe is in hydrostatic balance. The model is represented by two simple ordinary differential equations, where the rate of change of pond coverage depends on the pond coverage. All the physical parameters of the system are summarized by four strengths that control the relative importance of the terms in the equations. The model both fits observations and allows us to understand the behavior of melt ponds in a way that is often not possible with more complex models. Examples of insights we can gain from the model are that (1) the pond growth rate is more sensitive to changes in bare sea ice albedo than changes in pond albedo, (2) ponds grow slower on smoother ice, and (3) ponds respond strongest to freeboard sinking on first-year ice and sidewall melting on multiyear ice. We also show that under a global warming scenario, pond coverage would increase, decreasing the overall ice albedo and leading to ice thinning that is likely comparable to thinning due to direct forcing. Since melt pond coverage is one of the key parameters controlling the albedo of sea ice, understanding the mechanisms that control the distribution of pond coverage will help improve large-scale model parameterizations and sea ice forecasts in a warming climate.
12
Geilfus, N. X., R. J. Galley, O. Crabeck, T. Papakyriakou, J. Landy, J. L. Tison, and S. Rysgaard. "Inorganic carbon dynamics of melt-pond-covered first-year sea ice in the Canadian Arctic." Biogeosciences 12, no. 6 (March 31, 2015): 2047–61. http://dx.doi.org/10.5194/bg-12-2047-2015.
Full textAbstract:
Abstract. Melt pond formation is a common feature of spring and summer Arctic sea ice, but the role and impact of sea ice melt and pond formation on both the direction and size of CO2 fluxes between air and sea is still unknown. Here we report on the CO2–carbonate chemistry of melting sea ice, melt ponds and the underlying seawater as well as CO2 fluxes at the surface of first-year landfast sea ice in the Resolute Passage, Nunavut, in June 2012. Early in the melt season, the increase in ice temperature and the subsequent decrease in 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. As sea ice melt progresses, melt ponds form, mainly from melted snow, leading to a low in situ melt pond pCO2 (36 μatm). The percolation of this low salinity and low pCO2 meltwater into the sea ice matrix decreased the brine salinity, TA and TCO2, and lowered the in situ brine pCO2 (to 20 μatm). This initial low in situ pCO2 observed in brine and melt ponds results in air–ice CO2 fluxes ranging between −0.04 and −5.4 mmol m−2 day−1 (negative sign for fluxes from the atmosphere into the ocean). As melt ponds strive to reach pCO2 equilibrium with the atmosphere, their in situ pCO2 increases (up to 380 μatm) with time and the percolation of this relatively high concentration pCO2 meltwater increases the in situ brine pCO2 within the sea ice matrix as the melt season progresses. As the melt pond pCO2 increases, the uptake of atmospheric CO2 becomes less significant. However, since melt ponds are continuously supplied by meltwater, their in situ pCO2 remains undersaturated with respect to the atmosphere, promoting a continuous but moderate uptake of CO2 (~ −1 mmol m−2 day−1) into the ocean. Considering the Arctic seasonal sea ice extent during the melt period (90 days), we estimate an uptake of atmospheric CO2 of −10.4 Tg of C yr−1. This represents an additional uptake of CO2 associated with Arctic sea ice that needs to be further explored and considered in the estimation of the Arctic Ocean's overall CO2 budget.
13
Jeffries, M. O., K. Schwartz, and S. Li. "Arctic summer sea-ice SAR signatures, melt-season characteristics, and melt-pond fractions." Polar Record 33, no. 185 (April 1997): 101–12. http://dx.doi.org/10.1017/s003224740001442x.
Full textAbstract:
AbstractVariations in multiyear sea-ice backscatter from the synthetic aperture radar (SAR) aboard the ERS-1 satellite are interpreted in terms of melt-season characteristics (onset of melt in spring and of freeze-up in autumn, and the duration of the snow-decay period, the melt season, and the melt-pond season) from late winter to early autumn 1992 in two regions of the Arctic Ocean: the northeastern Beaufort Sea adjacent to the Queen Elizabeth Islands in the Canadian high Arctic and the western Beaufort Sea north of Alaska. In the northeastern Beaufort Sea, the onset of melt occurs later, and the periods of snow-cover decay and the occurrence of melt ponds are shorter than in the western Beaufort Sea. These melt-season characteristics of each area are consistent with previous observations that the northeastern Beaufort Sea has one of the most severe summer climates in the Arctic Ocean. A model, which assumes that the backscatter from multiyear floes is the sum of backscatter from bare ice and melt ponds, is used to derive the melt-pond fraction during the summer. The results show that melt-pond fractions decrease from an early-summer maximum of about 60% to a late-summer minimum around 10%. The magnitude of the melt-pond fractions and their decline during the summer is consistent with previous, more qualitative data. The SAR model, which gives melt-pond fractions with lower variability and less uncertainty than previous data, offers an improved approach to the reliable estimation of the areal extent of water on ice floes. Suggestions for further improvement of the model include accounting for the consequences of wind-speed variations, summer snowfall, and freeze/thaw cycles and their effects on melt-pond and ice-surface roughness.
14
Bates, N. R., R. Garley, K. E. Frey, K. L. Shake, and J. T. Mathis. "Sea-ice melt CO<sub>2</sub>–carbonate chemistry in the western Arctic Ocean: meltwater contributions to air–sea CO<sub>2</sub> gas exchange, mixed-layer properties and rates of net community production under sea ice." Biogeosciences 11, no. 23 (December 8, 2014): 6769–89. http://dx.doi.org/10.5194/bg-11-6769-2014.
Full textAbstract:
Abstract. The carbon dioxide (CO2)-carbonate chemistry of sea-ice melt and co-located, contemporaneous seawater has rarely been studied in sea-ice-covered oceans. Here, we describe the CO2–carbonate chemistry of sea-ice melt (both above sea-ice as "melt ponds" and below sea-ice as "interface waters") and mixed-layer properties in the western Arctic Ocean in the early summer of 2010 and 2011. At 19 stations, the salinity (∼0.5 to <6.5), dissolved inorganic carbon (DIC; ∼20 to <550 μmol kg−1) and total alkalinity (TA; ∼30 to <500 μmol kg−1) of above-ice melt pond water was low compared to the co-located underlying mixed layer. The partial pressure of CO2 (pCO2) in these melt ponds was highly variable (∼<10 to >1500 μatm) with the majority of melt ponds acting as potentially strong sources of CO2 to the atmosphere. The pH of melt pond waters was also highly variable ranging from mildly acidic (6.1 to 7) to slightly more alkaline than underlying seawater (>8.2 to 10.8). All of the observed melt ponds had very low (<0.1) saturation states (Ω) for calcium carbonate (CaCO3) minerals such as aragonite (Ωaragonite). Our data suggest that sea-ice generated alkaline or acidic type melt pond water. This melt water chemistry dictates whether the ponds are sources of CO2 to the atmosphere or CO2 sinks. Below-ice interface water CO2–carbonate chemistry data also indicated substantial generation of alkalinity, presumably owing to dissolution of CaCO3 in sea-ice. The interface waters generally had lower pCO2 and higher pH/Ωaragonite than the co-located mixed layer beneath. Sea-ice melt thus contributed to the suppression of mixed-layer pCO2, thereby enhancing the surface ocean's capacity to uptake CO2 from the atmosphere. Our observations contribute to growing evidence that sea-ice CO2–carbonate chemistry is highly variable and its contribution to the complex factors that influence the balance of CO2 sinks and sources (and thereby ocean acidification) is difficult to predict in an era of rapid warming and sea-ice loss in the Arctic Ocean.
15
Bates, N. R., R. Garley, K. E. Frey, K. L. Shake, and J. T. Mathis. "Sea-ice melt CO<sub>2</sub>-carbonate chemistry in the western Arctic Ocean: meltwater contributions to air-sea CO<sub>2</sub> gas exchange, mixed layer properties and rates of net community production under sea ice." Biogeosciences Discussions 11, no. 1 (January 16, 2014): 1097–145. http://dx.doi.org/10.5194/bgd-11-1097-2014.
Full textAbstract:
Abstract. The carbon dioxide (CO2)-carbonate chemistry of sea-ice melt and co-located, contemporaneous seawater has rarely been studied in sea ice covered oceans. Here, we describe the CO2-carbonate chemistry of sea-ice melt (both above sea ice as "melt ponds" and below sea ice as "interface waters") and mixed layer properties in the western Arctic Ocean in the early summer of 2010 and 2011. At nineteen stations, the salinity (~ 0.5 to < 6.5), dissolved inorganic carbon (DIC; ~ 20 to < 550 μmol kg–1) and total alkalinity (TA; ~ 30 to < 500 μmol kg–1) of above-ice melt pond water was low compared to water in the underlying mixed layer. The partial pressure of CO2 (pCO2) in these melt ponds was highly variable (~ < 10 to > 1500 μatm) with the majority of melt ponds acting as potentially strong sources of CO2 to the atmosphere. The pH of melt pond waters was also highly variable ranging from mildly acidic (6.1 to 7) to slightly more alkaline than underlying seawater (8 to 10.7). All of observed melt ponds had very low (< 0.1) saturation states (Ω) for calcium carbonate (CaCO3) minerals such as aragonite (Ωaragonite). Our data suggests that sea ice generated "alkaline" or "acidic" melt pond water. This melt-water chemistry dictates whether the ponds are sources of CO2 to the atmosphere or CO2 sinks. Below-ice interface water CO2-carbonate chemistry data also indicated substantial generation of alkalinity, presumably owing to dissolution of calcium CaCO3 in sea ice. The interface waters generally had lower pCO2 and higher pH/Ωaragonite than the co-located mixed layer beneath. Sea-ice melt thus contributed to the suppression of mixed layer pCO2 enhancing the surface ocean's capacity to uptake CO2 from the atmosphere. Meltwater contributions to changes in mixed–layer DIC were also used to estimate net community production rates (mean of 46.9 ±29.8 g C m–2 for the early-season period) under sea-ice cover. Although sea-ice melt is a transient seasonal feature, above-ice melt pond coverage can be substantial (10 to > 50%) and under-ice interface melt water is ubiquitous during this spring/summer sea-ice retreat. Our observations contribute to growing evidence that sea-ice CO2-carbonate chemistry is highly variable and its contribution to the complex factors that influence the balance of CO2 sinks and sources (and thereby ocean acidification) is difficult to predict in an era of rapid warming and sea ice loss in the Arctic Ocean.
16
Röhl, Katrin. "Characteristics and evolution of supraglacial ponds on debris-covered Tasman Glacier, New Zealand." Journal of Glaciology 54, no. 188 (2008): 867–80. http://dx.doi.org/10.3189/002214308787779861.
Full textAbstract:
AbstractSupraglacial ponds on Tasman Glacier, New Zealand, initiated the development of the large Tasman Lake during the 1980s and still play an important role for ice loss and further terminus disintegration. Limnological and glaciological measurements between 2001 and 2003 reveal distinct differences between ponds. The hydraulic connection of a pond to the englacial water level exerts a key control on whether the pond contributes to longer-term terminus disintegration. In the earlier stages of pond development, ice loss occurs predominantly in the horizontal dimension by subaerial melt. Subaqueous calving at later stages plays a major role for ice loss. During the capture of a pond by the lake, substantial limnological changes lead to changes in relative significance and rates of ice loss processes, the most important being the change from melting to predominantly calving. As a result, ice loss accelerated from around 11 m a−1 of melt under partial debris cover to a retreat by calving and melting of 34 m a−1. Ice loss at the ponds accounted for only 10% of the surface loss in the lower terminus area, but is likely to increase in the future with enlargement and coalescence of ponds.
17
Scharien, R. K., J. Landy, and D. G. Barber. "First-year sea ice melt pond fraction estimation from dual-polarisation C-band SAR – Part 1: In situ observations." Cryosphere 8, no. 6 (November 25, 2014): 2147–62. http://dx.doi.org/10.5194/tc-8-2147-2014.
Full textAbstract:
Abstract. Understanding the evolution of melt ponds on Arctic sea ice is important for climate model parameterisations, weather forecast models and process studies involving mass, energy and biogeochemical exchanges across the ocean–sea ice–atmosphere interface. A field campaign was conducted in a region of level first-year sea ice (FYI) in the central Canadian Arctic Archipelago (CAA), during the summer of 2012, to examine the potential for estimating melt pond fraction (fp) from satellite synthetic aperture radar (SAR). In this study, 5.5 GHz (C-band) dual co- (HH + VV – horizontal transmit and horizontal receive + vertical transmit and vertical receive) and cross-polarisation (HV + HH – horizontal transmit and vertical receive + horizontal transmit and horizontal receive) radar scatterometer measurements of melt-pond-covered FYI are combined with ice and pond properties to analyse the effects of in situ physical and morphological changes on backscatter parameters. Surface roughness statistics of ice and ponds are characterised and compared to the validity domains of the Bragg and integral equation model (IEM) scattering models. Experimental and model results are used to outline the potential and limitations of the co-polarisation ratio (VV / HH) for retrieving melt pond information, including fp, at large incidence angles (≥35°). Despite high variability in cross-polarisation ratio (HV / HH) magnitudes, increases at small incidence angles (<30°) are attributed to the formation of ice lids on ponds. Implications of the results for pond information retrievals from satellite C-, L- and P-band SARs are discussed.
18
Malinka, Aleksey, Eleonora Zege, Larysa Istomina, Georg Heygster, Gunnar Spreen, Donald Perovich, and Chris Polashenski. "Reflective properties of melt ponds on sea ice." Cryosphere 12, no. 6 (June 6, 2018): 1921–37. http://dx.doi.org/10.5194/tc-12-1921-2018.
Full textAbstract:
Abstract. Melt ponds occupy a large part of the Arctic sea ice in summer and strongly affect the radiative budget of the atmosphere–ice–ocean system. In this study, the melt pond reflectance is considered in the framework of radiative transfer theory. The melt pond is modeled as a plane-parallel layer of pure water upon a layer of sea ice (the pond bottom). We consider pond reflection as comprising Fresnel reflection by the water surface and multiple reflections between the pond surface and its bottom, which is assumed to be Lambertian. In order to give a description of how to find the pond bottom albedo, we investigate the inherent optical properties of sea ice. Using the Wentzel–Kramers–Brillouin approximation approach to light scattering by non-spherical particles (brine inclusions) and Mie solution for spherical particles (air bubbles), we conclude that the transport scattering coefficient in sea ice is a spectrally independent value. Then, within the two-stream approximation of the radiative transfer theory, we show that the under-pond ice spectral albedo is determined by two independent scalar values: the transport scattering coefficient and ice layer thickness. Given the pond depth and bottom albedo values, the bidirectional reflectance factor (BRF) and albedo of a pond can be calculated with analytical formulas. Thus, the main reflective properties of the melt pond, including their spectral dependence, are determined by only three independent parameters: pond depth z, ice layer thickness H, and transport scattering coefficient of ice σt.The effects of the incident conditions and the atmosphere state are examined. It is clearly shown that atmospheric correction is necessary even for in situ measurements. The atmospheric correction procedure has been used in the model verification. The optical model developed is verified with data from in situ measurements made during three field campaigns performed on landfast and pack ice in the Arctic. The measured pond albedo spectra were fitted with the modeled spectra by varying the pond parameters (z, H, and σt). The coincidence of the measured and fitted spectra demonstrates good performance of the model: it is able to reproduce the albedo spectrum in the visible range with RMSD that does not exceed 1.5 % for a wide variety of melt pond types observed in the Arctic.
19
Rösel, A., L. Kaleschke, and G. Birnbaum. "Melt ponds on Arctic sea ice determined from MODIS satellite data using an artificial neural network." Cryosphere Discussions 5, no. 5 (October 27, 2011): 2991–3024. http://dx.doi.org/10.5194/tcd-5-2991-2011.
Full textAbstract:
Abstract. Melt ponds on sea ice strongly reduce the surface albedo and accelerate the decay of Arctic sea ice. Due to different spectral properties of snow, ice, and water, the fractional coverage of these distinct surface types can be derived from multispectral sensors like MODIS using a spectral unmixing algorithm. The unmixing was implemented using a multilayer perceptron (MLP) to reduce computational costs. Arctic-wide melt pond fractions and sea ice concentrations are derived from the level 3 MODIS surface reflectance product. The validation of the MODIS melt pond data set was conducted with aerial photos from the MELTEX campaign 2008 in the Beaufort Sea, data sets from the National Snow and Ice Data Center (NSIDC) for 2000 and 2001 from four sites spread over the entire Arctic, and with ship observations from the trans-Arctic HOTRAX cruise in 2005. The root-mean-square errors (RMSE) range from 3.8 % for the comparison with HOTRAX data, over 10.7 % for the comparison with NSIDC data, to 10.3 % and 11.4 % for the comparison with MELTEX data, with correlations coefficients ranging from R2 = 0.28 to R2 = 0.45. The mean annual cycle of the melt pond fraction for the entire Arctic shows a strong increase in June, reaching a maximum of 15 % by the end of June. The zonal mean of melt pond fractions indicates a dependence of the temporal development of melt ponds from the geographical latitude, and has its maximum in mid-July in latitudes between 80° and 88° N. Furthermore, the MODIS results are used to estimate the influence of melt ponds on retrievals of sea ice concentrations from passive microwave data. Results from a case study comparing sea ice concentrations from ASI-, NASA Team 2-, and Bootstrap-algorithms with MODIS sea ice concentrations indicate an underestimation of around 40 % for sea ice concentrations retrieved with microwave algorithms.
20
Inoue, Jun, Judith A. Curry, and James A. Maslanik. "Application of Aerosondes to Melt-Pond Observations over Arctic Sea Ice." Journal of Atmospheric and Oceanic Technology 25, no. 2 (February 1, 2008): 327–34. http://dx.doi.org/10.1175/2007jtecha955.1.
Full textAbstract:
Abstract Continuous observation of sea ice using a small robotic aircraft called the Aerosonde was made over the Arctic Ocean from Barrow, Alaska, on 20–21 July 2003. Over a region located 350 km off the coast of Barrow, images obtained from the aircraft were used to characterize the sea ice and to determine the fraction of melt ponds on both multiyear and first-year ice. Analysis of the data indicates that melt-pond fraction increased northward from 20% to 30% as the ice fraction increased. However, the fraction of ponded ice was over 30% in the multiyear ice zone while it was about 25% in the first-year ice zone. A comparison with a satellite microwave product showed that the ice concentration derived from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) has a negative bias of 7% due to melt ponds. These analyses demonstrate the utility of recent advances in unmanned aerial vehicle (UAV) technology for monitoring and interpreting the spatial variations in the sea ice with melt ponds.
21
Scharien, R. K., J. Landy, and D. G. Barber. "Sea ice melt pond fraction estimation from dual-polarisation C-band SAR – Part 1: In situ observations." Cryosphere Discussions 8, no. 1 (January 27, 2014): 805–44. http://dx.doi.org/10.5194/tcd-8-805-2014.
Full textAbstract:
Abstract. An understanding of the evolution of melt ponds on Arctic sea ice is important for climate model parameterizations, weather forecast models, and process studies involving mass, energy and biogeochemical exchanges across the ocean-sea ice–atmosphere interface. A field campaign was conducted on landfast first-year sea ice in the Canadian Arctic Archipelago during the summer of 2012, to examine the potential for estimating melt pond fraction from C-band synthetic aperture radar (SAR). In this study, in situ dual-polarisation radar scatterometer observations of pond covered ice are combined with surface physical measurements to analyse the effects of radar and surface parameters on backscatter. LiDAR measurements of ice surface roughness and ultrasonic wind-wave height profiles of melt ponds are used to quantify the sea ice surface rms-height. Variables contributing to the roughness of wind-generated melt pond surface waves within the fetch-limited pond environment are evaluated, and we show that pond roughness and backscatter cannot be explained by wind speed alone. The utility of the VV / HH polarisation ratio (PR) for retrieving melt pond properties including pond fraction, due to the dielectric contrast between free surface water and sea ice, is demonstrated and explained using Bragg scattering theory. Finally, the PR approach is discussed in the context of retrievals from satellite C-, L-, and P-band dual-polarisation SAR.
22
Lu, Peng, Matti Leppäranta, Bin Cheng, Zhijun Li, Larysa Istomina, and Georg Heygster. "The color of melt ponds on Arctic sea ice." Cryosphere 12, no. 4 (April 13, 2018): 1331–45. http://dx.doi.org/10.5194/tc-12-1331-2018.
Full textAbstract:
Abstract. Pond color, which creates the visual appearance of melt ponds on Arctic sea ice in summer, is quantitatively investigated using a two-stream radiative transfer model for ponded sea ice. The upwelling irradiance from the pond surface is determined and then its spectrum is transformed into RGB (red, green, blue) color space using a colorimetric method. The dependence of pond color on various factors such as water and ice properties and incident solar radiation is investigated. The results reveal that increasing underlying ice thickness Hi enhances both the green and blue intensities of pond color, whereas the red intensity is mostly sensitive to Hi for thin ice (Hi < 1.5 m) and to pond depth Hp for thick ice (Hi > 1.5 m), similar to the behavior of melt-pond albedo. The distribution of the incident solar spectrum F0 with wavelength affects the pond color rather than its intensity. The pond color changes from dark blue to brighter blue with increasing scattering in ice, and the influence of absorption in ice on pond color is limited. The pond color reproduced by the model agrees with field observations for Arctic sea ice in summer, which supports the validity of this study. More importantly, the pond color has been confirmed to contain information about meltwater and underlying ice, and therefore it can be used as an index to retrieve Hi and Hp. Retrievals of Hi for thin ice (Hi < 1 m) agree better with field measurements than retrievals for thick ice, but those of Hp are not good. The analysis of pond color is a new potential method to obtain thin ice thickness in summer, although more validation data and improvements to the radiative transfer model will be needed in future.
23
Perovich, Donald K., and Walter B. Tucker. "Arctic sea-ice conditions and the distribution of solar radiation during summer." Annals of Glaciology 25 (1997): 445–50. http://dx.doi.org/10.1017/s0260305500014439.
Full textAbstract:
Understanding the interaction of solar radiation with the ice cover is critical in determining the heat and mass balance of the Arctic ice pack, and in assessing potential impacts due to climate change. Because of the importance of the ice-albedo feedback mechanism, information on the surface state of the ice cover is needed. Observations of the surface slate of sea ice were obtained from helicopter photography missions made during the 1994 Arctic Ocean Section cruise. Photographs from one flight, taken during the height of the melt season (31 July 1994) at 76° N, 172° W, were analyzed in detail. Bare ice covered 82% of the total area, melt ponds 12%, and open water 6%, There was considerable variability in these area fractions on scales < 1 km2. Sample areas >2 3 km2gave representative values of ice concentration and pond fraction. Melt ponds were numerous, with a number density of 1800 ponds km-2. The melt ponds had a mean area of 62 m2a median area of 14 m2, and a size distribution that was well lit by a cumulative lognormal distribution. While leads make up only a small portion of the total area, they are the source of virtually all of the solar energy input to the ocean.
24
Perovich, Donald K., and Walter B. Tucker. "Arctic sea-ice conditions and the distribution of solar radiation during summer." Annals of Glaciology 25 (1997): 445–50. http://dx.doi.org/10.3189/s0260305500014439.
Full textAbstract:
Understanding the interaction of solar radiation with the ice cover is critical in determining the heat and mass balance of the Arctic ice pack, and in assessing potential impacts due to climate change. Because of the importance of the ice-albedo feedback mechanism, information on the surface state of the ice cover is needed. Observations of the surface slate of sea ice were obtained from helicopter photography missions made during the 1994 Arctic Ocean Section cruise. Photographs from one flight, taken during the height of the melt season (31 July 1994) at 76° N, 172° W, were analyzed in detail. Bare ice covered 82% of the total area, melt ponds 12%, and open water 6%, There was considerable variability in these area fractions on scales < 1 km2. Sample areas >2 3 km2 gave representative values of ice concentration and pond fraction. Melt ponds were numerous, with a number density of 1800 ponds km-2. The melt ponds had a mean area of 62 m2 a median area of 14 m2, and a size distribution that was well lit by a cumulative lognormal distribution. While leads make up only a small portion of the total area, they are the source of virtually all of the solar energy input to the ocean.
25
Barjatia, Meenakshi, Tolga Tasdizen, Boya Song, Christian Sampson, and Kenneth M. Golden. "Network modeling of Arctic melt ponds." Cold Regions Science and Technology 124 (April 2016): 40–53. http://dx.doi.org/10.1016/j.coldregions.2015.11.019.
Full text
26
Miles, Evan S., Francesca Pellicciotti, Ian C. Willis, Jakob F. Steiner, Pascal Buri, and Neil S. Arnold. "Refined energy-balance modelling of a supraglacial pond, Langtang Khola, Nepal." Annals of Glaciology 57, no. 71 (March 2016): 29–40. http://dx.doi.org/10.3189/2016aog71a421.
Full textAbstract:
AbstractSupraglacial ponds on debris-covered glaciers present a mechanism of atmosphere/glacier energy transfer that is poorly studied, and only conceptually included in mass-balance studies of debris-covered glaciers. This research advances previous efforts to develop a model of mass and energy balance for supraglacial ponds by applying a free-convection approach to account for energy exchanges at the subaqueous bare-ice surfaces. We develop the model using field data from a pond on Lirung Glacier, Nepal, that was monitored during the 2013 and 2014 monsoon periods. Sensitivity testing is performed for several key parameters, and alternative melt algorithms are compared with the model. The pond acts as a significant recipient of energy for the glacier system, and actively participates in the glacier’s hydrologic system during the monsoon. Melt rates are 2-4 cm d-1 (total of 98.5 m3 over the study period) for bare ice in contact with the pond, and <1 mmd-1 (total of 10.6m3) for the saturated debris zone. The majority of absorbed atmospheric energy leaves the pond system through englacial conduits, delivering sufficient energy to melt 2612 m3 additional ice over the study period (38.4 m3 d-1). Such melting might be expected to lead to subsidence of the glacier surface. Supraglacial ponds efficiently convey atmospheric energy to the glacier’s interior and rapidly promote the downwasting process.
27
Huang, W., P. Lu, R. Lei, H. Xie, and Z. Li. "Melt pond distribution and geometry in high Arctic sea ice derived from aerial investigations." Annals of Glaciology 57, no. 73 (September 2016): 105–18. http://dx.doi.org/10.1017/aog.2016.30.
Full textAbstract:
ABSTRACTAerial photography was conducted in the high Arctic Ocean during a Chinese research expedition in summer 2010. By partitioning the images into three distinct surface categories (sea ice/snow, water and melt ponds), the areal fraction of each category, ice concentration and the size and geometry of individual melt ponds, are determined with high-spatial resolution. The ice concentration and melt pond coverage have large spatial deviations between flights and even between images from the marginal ice zone to the pack ice zone in the central Arctic. Ice concentration and pond coverage over high Arctic (from 84°N to north) was ~75% and ~6.8%, respectively, providing ‘ground truth’ for the unusual transpolar reduction strip of ice indicated concurrently by AMSR-E data and for the regions (north of 88°N) where no passive microwave sensors can cover. Melt pond size and shape distributions are examined in terms of pond area (S), perimeter (P), mean caliper dimension (MCD) (L), roundness (R), convex degree (C), the ratio of P/S and fractal dimension (D). Power-law relationships are developed between pond size and number. Some general trends in geometric metrics are identified as a function of pond area including R, C, P/S and D. The scale separation of pond complexity is demonstrated by analyzing area-perimeter data. The results will potentially help the modelling of melt pond evolution and the determination of heterogeneity of under-ice transmitted light fields.
28
Rösel, A., L. Kaleschke, and G. Birnbaum. "Melt ponds on Arctic sea ice determined from MODIS satellite data using an artificial neural network." Cryosphere 6, no. 2 (April 3, 2012): 431–46. http://dx.doi.org/10.5194/tc-6-431-2012.
Full textAbstract:
Abstract. Melt ponds on sea ice strongly reduce the surface albedo and accelerate the decay of Arctic sea ice. Due to different spectral properties of snow, ice, and water, the fractional coverage of these distinct surface types can be derived from multispectral sensors like the Moderate Resolution Image Spectroradiometer (MODIS) using a spectral unmixing algorithm. The unmixing was implemented using a multilayer perceptron to reduce computational costs. Arctic-wide melt pond fractions and sea ice concentrations are derived from the level 3 MODIS surface reflectance product. The validation of the MODIS melt pond data set was conducted with aerial photos from the MELTEX campaign 2008 in the Beaufort Sea, data sets from the National Snow and Ice Data Center (NSIDC) for 2000 and 2001 from four sites spread over the entire Arctic, and with ship observations from the trans-Arctic HOTRAX cruise in 2005. The root-mean-square errors range from 3.8 % for the comparison with HOTRAX data, over 10.7 % for the comparison with NSIDC data, to 10.3 % and 11.4 % for the comparison with MELTEX data, with coefficient of determination ranging from R2=0.28 to R2=0.45. The mean annual cycle of the melt pond fraction per grid cell for the entire Arctic shows a strong increase in June, reaching a maximum of 15 % by the end of June. The zonal mean of melt pond fractions indicates a dependence of the temporal development of melt ponds on the geographical latitude, and has its maximum in mid-July at latitudes between 80° and 88° N. Furthermore, the MODIS results are used to estimate the influence of melt ponds on retrievals of sea ice concentrations from passive microwave data. Results from a case study comparing sea ice concentrations from ARTIST Sea Ice-, NASA Team 2-, and Bootstrap-algorithms with MODIS sea ice concentrations indicate an underestimation of around 40 % for sea ice concentrations retrieved with microwave algorithms.
29
Fors, Ane S., Dmitry V. Divine, Anthony P. Doulgeris, Angelika H. H. Renner, and Sebastian Gerland. "Signature of Arctic first-year ice melt pond fraction in X-band SAR imagery." Cryosphere 11, no. 2 (March 23, 2017): 755–71. http://dx.doi.org/10.5194/tc-11-755-2017.
Full textAbstract:
Abstract. In this paper we investigate the potential of melt pond fraction retrieval from X-band polarimetric synthetic aperture radar (SAR) on drifting first-year sea ice. Melt pond fractions retrieved from a helicopter-borne camera system were compared to polarimetric features extracted from four dual-polarimetric X-band SAR scenes, revealing significant relationships. The correlations were strongly dependent on wind speed and SAR incidence angle. Co-polarisation ratio was found to be the most promising SAR feature for melt pond fraction estimation at intermediate wind speeds (6. 2 m s−1), with a Spearman's correlation coefficient of 0. 46. At low wind speeds (0. 6 m s−1), this relation disappeared due to low backscatter from the melt ponds, and backscatter VV-polarisation intensity had the strongest relationship to melt pond fraction with a correlation coefficient of −0. 53. To further investigate these relations, regression fits were made both for the intermediate (R2fit = 0. 21) and low (R2fit = 0. 26) wind case, and the fits were tested on the satellite scenes in the study. The regression fits gave good estimates of mean melt pond fraction for the full satellite scenes, with less than 4 % from a similar statistics derived from analysis of low-altitude imagery captured during helicopter ice-survey flights in the study area. A smoothing window of 51 × 51 pixels gave the best reproduction of the width of the melt pond fraction distribution. A considerable part of the backscatter signal was below the noise floor at SAR incidence angles above ∼ 40°, restricting the information gain from polarimetric features above this threshold. Compared to previous studies in C-band, limitations concerning wind speed and noise floor set stricter constraints on melt pond fraction retrieval in X-band. Despite this, our findings suggest new possibilities in melt pond fraction estimation from X-band SAR, opening for expanded monitoring of melt ponds during melt season in the future.
30
Lu, Peng, and Zhijun Li. "Uncertainties in retrieved ice thickness from freeboard measurements due to surface melting." Annals of Glaciology 55, no. 66 (2014): 205–12. http://dx.doi.org/10.3189/2014aog66a188.
Full textAbstract:
AbstractAirborne and spaceborne remote sensing of ice freeboard offers a good method of retrieving ice thickness in the polar oceans. However, its accuracy is highly limited by the factors altering the hydrostatic equilibrium of ice floes, such as snow cover and melt ponds which change the surface loading on the ice volume. In contrast to the abundant studies on snow loads, little attention has been paid to the role of melt ponds, partly owing to the difficulties of freeboard measurements during the melt season. To help fill this gap and provide a basis for possible instruments and algorithms being able to access ice freeboard with melting surface in future, a theoretical model was developed to investigate the uncertainty in ice thickness retrieval due to surface melting. First, the ice thickness was related to the freeboard, snow depth, melt pond size and densities of snow, ice and water, and then a sensitivity analysis was carried out to study the influence of melt pond morphology. The results show that melting ice has a much lower mean thickness than ice without a melting surface, although with the same freeboard because of a loss of floe weight due to melting. During pond evolution, a floe gains weight when ponds deepen on the vertical scale, but loses weight when they widen on the horizontal scale, resulting in increasing mean ice thickness with decreasing pond depth and fraction. Freeboard is found to be the major source of uncertainty in the retrieved thickness of first-year ice (FYI), while it is ice density in the case of multi-year ice (MYI). The ratio of ice draft to freeboard ranges from 3.0 to 6.2 for FYI and 2.0 to 4.1 for MYI, agreeing with field observations during melting seasons.
31
Luckman, Adrian, Andrew Elvidge, Daniela Jansen, Bernd Kulessa, Peter Kuipers Munneke, John King, and Nicholas E. Barrand. "Surface melt and ponding on Larsen C Ice Shelf and the impact of föhn winds." Antarctic Science 26, no. 6 (November 13, 2014): 625–35. http://dx.doi.org/10.1017/s0954102014000339.
Full textAbstract:
AbstractA common precursor to ice shelf disintegration, most notably that of Larsen B Ice Shelf, is unusually intense or prolonged surface melt and the presence of surface standing water. However, there has been little research into detailed patterns of melt on ice shelves or the nature of summer melt ponds. We investigated surface melt on Larsen C Ice Shelf at high resolution using Envisat advanced synthetic aperture radar (ASAR) data and explored melt ponds in a range of satellite images. The improved spatial resolution of SAR over alternative approaches revealed anomalously long melt duration in western inlets. Meteorological modelling explained this pattern by föhn winds which were common in this region. Melt ponds are difficult to detect using optical imagery because cloud-free conditions are rare in this region and ponds quickly freeze over, but can be monitored using SAR in all weather conditions. Melt ponds up to tens of kilometres in length were common in Cabinet Inlet, where melt duration was most prolonged. The pattern of melt explains the previously observed distribution of ice shelf densification, which in parts had reached levels that preceded the collapse of Larsen B Ice Shelf, suggesting a potential role for föhn winds in promoting unstable conditions on ice shelves.
32
Healy, M., J. G. Webster-Brown, K. L. Brown, and V. Lane. "Chemistry and stratification of Antarctic meltwater ponds II: Inland ponds in the McMurdo Dry Valleys, Victoria Land." Antarctic Science 18, no. 4 (November 14, 2006): 525–33. http://dx.doi.org/10.1017/s0954102006000575.
Full textAbstract:
Meltwater ponds in the Victoria Valley and in the Labyrinth at the head of the Wright Valley of Victoria Land were sampled in January (summer) and October (late winter) of 2004 to establish their geochemistry and stratification, and to compare this with that of coastal meltwater ponds at a similar latitude near Bratina Island. In summer, vertical profiles were measured in 14 ponds; 10 were thermally stratified (maximum ΔT = 11.5°C) and 12 demonstrated a conductivity increase (∼25x) in the lowest 10–20 cm of the water column. When 11 of these ponds were resampled in October, the ice columns were stratified with respect to conductivity and five ponds had highly saline (up to 148 mS cm−1), oxygenated basal brines present under the ice. Basal brines and summer melt waters were Na-Cl dominated, and Victoria Valley pond meltwaters were enriched in Ca relative to the Labyrinth ponds. Early gypsum precipitation directs the chemical evolution of residual brine during freezing. These ponds were enriched in NO3 relative to the coastal ponds at Bratina Island, due to dissolution of nitrate-bearing soil salts, and the reduced influence of marine aerosols and biological productivity on pond chemistry.
33
Lyons, W. Berry, Kathleen A. Welch, Christopher B. Gardner, Chris Jaros, Daryl L. Moorhead, Jennifer L. Knoepfle, and Peter T. Doran. "The geochemistry of upland ponds, Taylor Valley, Antarctica." Antarctic Science 24, no. 1 (September 23, 2011): 3–14. http://dx.doi.org/10.1017/s0954102011000617.
Full textAbstract:
AbstractThe McMurdo Dry Valleys of Antarctica are the largest ice-free region on the continent. These valleys contain numerous water bodies that receive seasonal melt from glaciers. For forty years, research emphasis has been placed on the larger water bodies, the permanent ice-covered lakes. We present results from the first study describing the geochemistry of ponds in the higher elevations of Taylor Valley. Unlike the lakes at lower elevations, the landscape on which these ponds lie is among the oldest in Taylor Valley. These upland ponds wax and wane in size depending on the local climatic conditions, and their ionic concentrations and isotopic composition vary annually depending on the amount of meltwater generated and their hydrologic connectivity. This study evaluates the impact of changes in summer climate on the chemistry of these ponds. Although pond chemistry reflects the initial meltwater chemistry, dissolution and chemical weathering within the stream channels, and possibly permafrost fluid input, the primary control is the dilution effect of glacier melt during warmer summers. These processes lead to differences in solute concentrations and ionic ratios between ponds, despite their nearby proximity. The change in size of these ponds over time has important consequences on their geochemical behaviour and potential to provide water and solutes to the subsurface.
34
König, Marcel, and Natascha Oppelt. "A linear model to derive melt pond depth on Arctic sea ice from hyperspectral data." Cryosphere 14, no. 8 (August 12, 2020): 2567–79. http://dx.doi.org/10.5194/tc-14-2567-2020.
Full textAbstract:
Abstract. Melt ponds are key elements in the energy balance of Arctic sea ice. Observing their temporal evolution is crucial for understanding melt processes and predicting sea ice evolution. Remote sensing is the only technique that enables large-scale observations of Arctic sea ice. However, monitoring melt pond deepening in this way is challenging because most of the optical signal reflected by a pond is defined by the scattering characteristics of the underlying ice. Without knowing the influence of meltwater on the reflected signal, the water depth cannot be determined. To solve the problem, we simulated the way meltwater changes the reflected spectra of bare ice. We developed a model based on the slope of the log-scaled remote sensing reflectance at 710 nm as a function of depth that is widely independent from the bottom albedo and accounts for the influence of varying solar zenith angles. We validated the model using 49 in situ melt pond spectra and corresponding depths from shallow ponds on dark and bright ice. Retrieved pond depths are accurate (root mean square error, RMSE=2.81 cm; nRMSE=16 %) and highly correlated with in situ measurements (r=0.89; p=4.34×10-17). The model further explains a large portion of the variation in pond depth (R2=0.74). Our results indicate that our model enables the accurate retrieval of pond depth on Arctic sea ice from optical data under clear sky conditions without having to consider pond bottom albedo. This technique is potentially transferrable to hyperspectral remote sensors on unmanned aerial vehicles, aircraft and satellites.
35
Salerno, Franco, Sudeep Thakuri, Nicolas Guyennon, Gaetano Viviano, and Gianni Tartari. "Glacier melting and precipitation trends detected by surface area changes in Himalayan ponds." Cryosphere 10, no. 4 (July 11, 2016): 1433–48. http://dx.doi.org/10.5194/tc-10-1433-2016.
Full textAbstract:
Abstract. Climatic time series for high-elevation Himalayan regions are decidedly scarce. Although glacier shrinkage is now sufficiently well described, the changes in precipitation and temperature at these elevations are less clear. This contribution shows that the surface area variations of unconnected glacial ponds, i.e. ponds not directly connected to glacier ice, but that may have a glacier located in their hydrological basin, can be considered as suitable proxies for detecting past changes in the main hydrological components of the water balance. On the south side of Mt Everest, glacier melt and precipitation have been found to be the main drivers of unconnected pond surface area changes (detected mainly with Landsat imagery). In general, unconnected ponds have decreased significantly by approximately 10 &pm; 5 % in terms of surface area over the last 50 years (1963–2013 period) in the study region. Here, an increase in precipitation occurred until the mid-1990s followed by a decrease until recent years. Until the 1990s, glacier melt was constant. An increase occurred in the early 2000s, while a declining trend in maximum temperature has caused a reduction in the glacier melt during recent years.
36
Markus, Thorsten, Donald J. Cavalieri, and Alvaro Ivanoff. "The potential of using Landsat 7 ETM+ for the classification of sea-ice surface conditions during summer." Annals of Glaciology 34 (2002): 415–19. http://dx.doi.org/10.3189/172756402781817536.
Full textAbstract:
AbstractDuring spring and summer, the surface of the Arctic sea-ice cover undergoes rapid changes that greatly affect the surface albedo and significantly impact the further decay of the sea ice. These changes are primarily the development of a wet snow cover and the development of melt ponds. As melt ponds generally do not exceed a couple of meters in diameter, the spatial resolutions of sensors like the Advanced Very High Resolution Radiometer and Moderate Resolution Imaging Spectroradiometer are too coarse for their identification. Landsat 7, on the other hand, has a spatial resolution of 30 m (15 m for the panchromatic band) and thus offers the best chance to map the distribution of melt ponds from space. The different wavelengths (bands) from blue to near-infrared offer the potential to distinguish among different surface conditions. Landsat 7 data for the Baffin Bay region for June 2000 have been analyzed. The analysis shows that different surface conditions, such as wet snow and melt-ponded areas, have different signatures in the individual Landsat bands. Consistent with in situ albedo measurements, melt ponds show up as blueish, whereas dry and wet ice have a white to gray appearance in the Landsat true-color image. These spectral differences enable areas with high fractions of melt ponds to be distinguished.
37
Hu, Yang, Xin Yao, Yuanyuan Wu, Wei Han, Yongqiang Zhou, Xiangming Tang, Keqiang Shao, and Guang Gao. "Contrasting Patterns of the Bacterial Communities in Melting Ponds and Periglacial Rivers of the Zhuxi glacier in the Tibet Plateau." Microorganisms 8, no. 4 (April 2, 2020): 509. http://dx.doi.org/10.3390/microorganisms8040509.
Full textAbstract:
Since the early 21st century, global climate change has been inducing rapid glacier retreat at an unprecedented rate. In this context, the melt ponds impart increasing unique footprints on the periglacial rivers due to their hydrodynamic connection. Given that bacterial communities control numerous ecosystem processes in the glacial ecosystem, exploring the fate of bacterial communities from melt ponds to periglacial rivers yields key knowledge of the biodiversity and biogeochemistry of glacial ecosystems. Here, we analyzed the bacterial community structure, diversity, and co-occurrence network to reveal the community organization in the Zhuxi glacier in the Tibet Plateau. The results showed that the bacterial communities in melt ponds were significantly lower in alpha-diversity but were significantly higher in beta-diversity than those in periglacial rivers. The rare sub-communities significantly contributed to the stability of the bacterial communities in both habitats. The co-occurrence network inferred that the mutually beneficial relationships predominated in the two networks. Nevertheless, the lower ratio of positive to negative edges in melt ponds than periglacial rivers implicated fiercer competition in the former habitat. Based on the significantly higher value of degree, betweenness, and modules, as well as shorter average path length in melt ponds, we speculated that their bacterial communities are less resilient than those of periglacial rivers.
38
Schmidt, S., W. Moskal, S. J. De Mora, C. Howard-Williams, and W. F. Vincent. "Limnological properties of Antarctic ponds during winter freezing." Antarctic Science 3, no. 4 (December 1991): 379–88. http://dx.doi.org/10.1017/s0954102091000482.
Full textAbstract:
Two shallow ponds at Cape Evans, Ross Island, were sampled at 1–2 week intervals, during winter freezing throughout the winter and during the subsequent melt period, to examine the physical and chemical conditions imposed on the biota during the year. Liquid water was first detected at the base of the ponds in late December. During the main summer melt period conductivities were less than 10 mS cm−1 with maximum daily temperatures around 5°C. The bottom waters became increasingly saline during freezing and water temperatures decreased below 0°C; by June the remaining water overlying the sediments had conductivities >150 mS cm−1 and temperatures of −13°C. Calcium carbonate, then sodium sulphate precipitated out of solution during early freezing. The dominant nitrogen species was dissolved organic-N which reached 12 g m−3 in Pond 1 just prior to final freeze up. The organic and inorganic forms of nitrogen and dissolved reactive phosphorus increased with increasing conductivity in the ponds. The behaviour of particulate-N and particulate-P mirrored that of chlorophyll a with a peak in March-April and a second higher peak just before final freeze-up. This study provides clear evidence that organisms which persist throughout the year in Antarctic coastal ponds must be capable of surviving much more severe osmotic, pH, temperature and redox conditions than those measured during the summer melt. Deoxygenation, pH decline and H2S production, however, point to continued respiratory activity well into the dark winter months.
39
Tschudi, Mark A., Judith A. Curry, and James A. Maslanik. "Determination of areal surface-feature coverage in the Beaufort Sea using aircraft video data." Annals of Glaciology 25 (1997): 434–38. http://dx.doi.org/10.1017/s0260305500014415.
Full textAbstract:
The surface-energy budget of the Arctic Ocean depends on the distribution of various sea-ice features that form by both mechanical and thermodynamic processes. Melt ponds, new ice and open water greatly affect the determination of surface albedo. However, even basic measurements of some surface-feature characteristics, such as areal extent of melt ponds, remain rare.A method has been developed to assess the areal coverage of melt ponds, new ice and open water using video data from the Beaufort and Arctic Storms Experiment (BASE). A downward-looking video camera mounted on the underside of a Hercules C-130 aircraft provided clear images of the surface. Images acquired over multi-year ice on 21 September 1994 were analyzed using a spectral technique to determine the areal coverage of melt ponds, new ice and open water. Statistics from this analysis were then compared to previous field studies and to the Schramm and others (in press) sea-ice model.
40
Tschudi, Mark A., Judith A. Curry, and James A. Maslanik. "Determination of areal surface-feature coverage in the Beaufort Sea using aircraft video data." Annals of Glaciology 25 (1997): 434–38. http://dx.doi.org/10.3189/s0260305500014415.
Full textAbstract:
The surface-energy budget of the Arctic Ocean depends on the distribution of various sea-ice features that form by both mechanical and thermodynamic processes. Melt ponds, new ice and open water greatly affect the determination of surface albedo. However, even basic measurements of some surface-feature characteristics, such as areal extent of melt ponds, remain rare.A method has been developed to assess the areal coverage of melt ponds, new ice and open water using video data from the Beaufort and Arctic Storms Experiment (BASE). A downward-looking video camera mounted on the underside of a Hercules C-130 aircraft provided clear images of the surface. Images acquired over multi-year ice on 21 September 1994 were analyzed using a spectral technique to determine the areal coverage of melt ponds, new ice and open water. Statistics from this analysis were then compared to previous field studies and to the Schramm and others (in press) sea-ice model.
41
Fetterer, Florence, and Norbert Untersteiner. "Observations of melt ponds on Arctic sea ice." Journal of Geophysical Research: Oceans 103, no. C11 (October 15, 1998): 24821–35. http://dx.doi.org/10.1029/98jc02034.
Full text
42
König, Marcel, Gerit Birnbaum, and Natascha Oppelt. "Mapping the Bathymetry of Melt Ponds on Arctic Sea Ice Using Hyperspectral Imagery." Remote Sensing 12, no. 16 (August 14, 2020): 2623. http://dx.doi.org/10.3390/rs12162623.
Full textAbstract:
Hyperspectral remote-sensing instruments on unmanned aerial vehicles (UAVs), aircraft and satellites offer new opportunities for sea ice observations. We present the first study using airborne hyperspectral imagery of Arctic sea ice and evaluate two atmospheric correction approaches (ATCOR-4 (Atmospheric and Topographic Correction version 4; v7.0.0) and empirical line calibration). We apply an existing, field data-based model to derive the depth of melt ponds, to airborne hyperspectral AisaEAGLE imagery and validate results with in situ measurements. ATCOR-4 results roughly match the shape of field spectra but overestimate reflectance resulting in high root-mean-square error (RMSE) (between 0.08 and 0.16). Noisy reflectance spectra may be attributed to the low flight altitude of 200 ft and Arctic atmospheric conditions. Empirical line calibration resulted in smooth, accurate spectra (RMSE < 0.05) that enabled the assessment of melt pond bathymetry. Measured and modeled pond bathymetry are highly correlated (r = 0.86) and accurate (RMSE = 4.04 cm), and the model explains a large portion of the variability (R2 = 0.74). We conclude that an accurate assessment of melt pond bathymetry using airborne hyperspectral data is possible subject to accurate atmospheric correction. Furthermore, we see the necessity to improve existing approaches with Arctic-specific atmospheric profiles and aerosol models and/or by using multiple reference targets on the ground.
43
Wright, Nicholas C., Chris M. Polashenski, Scott T. McMichael, and Ross A. Beyer. "Observations of sea ice melt from Operation IceBridge imagery." Cryosphere 14, no. 10 (October 26, 2020): 3523–36. http://dx.doi.org/10.5194/tc-14-3523-2020.
Full textAbstract:
Abstract. The summer albedo of Arctic sea ice is heavily dependent on the fraction and color of melt ponds that form on the ice surface. This work presents a new dataset of sea ice surface fractions along Operation IceBridge (OIB) flight tracks derived from the Digital Mapping System optical imagery set. This dataset was created by deploying version 2 of the Open Source Sea-ice Processing (OSSP) algorithm to NASA's Advanced Supercomputing Pleiades System. These new surface fraction results are then analyzed to investigate the behavior of meltwater on first-year ice in comparison to multiyear ice. Observations herein show that first-year ice does not ubiquitously have a higher melt pond fraction than multiyear ice under the same forcing conditions, contrary to established knowledge in the sea ice community. We discover and document a larger possible spread of pond fractions on first-year ice leading to both high and low pond coverage, in contrast to the uniform melt evolution that has been previously observed on multiyear ice floes. We also present a selection of optical images that capture both the typical and atypical ice types, as observed from the OIB dataset. The derived OIB data presented here will be key to explore the behavior of melt pond formation Arctic sea ice.
44
Podgorny, Igor A., and Thomas C. Grenfell. "Partitioning of solar energy in melt ponds from measurements of pond albedo and depth." Journal of Geophysical Research: Oceans 101, no. C10 (October 15, 1996): 22737–48. http://dx.doi.org/10.1029/96jc02123.
Full text
45
De Mora, S. J., P. A. Lee, A. Grout, C. Schall, and K. G. Heumann. "Aspects of the biogeochemistry of sulphur in glacial melt water ponds on the McMurdo Ice Shelf, Antarctica." Antarctic Science 8, no. 1 (March 1996): 15–22. http://dx.doi.org/10.1017/s0954102096000041.
Full textAbstract:
The distribution of dimethylsulphide (DMS), together with the precursor dimethylsulphonio-propionate (DMSP) and the oxidation product dimethylsulphoxide (DMSO), was measured in melt waters on the McMurdo Ice Shelf in the immediate vicinity of Bratina Island. Conductivity in these sulphate dominated ponds was extremely variable, ranging from 0.106–52.3 mS cm−1. Similarly, chlorophyll a concentrations in the pond waters (1–150 μg 1−1) and mats (1.4–33 μg cm−2) differed considerably. The biomass was dominated by benthic felts of phototrophic cyanobacteria, which might act as a source of biogenic sulphur compounds in the ponds. The mean (and ranges) of concentrations of dissolved sulphur compounds (nmol 1−1) were: CS2 0.16 (<0.04–1.29); DMSPd 0.6 (<0.07–8.4); DMS 3.5 (<0.07–183); DMSO 27.9 (15.5–184.5). Very high concentrations of DMSO were ubiquitous in the ponds in the ice-cored moraine region of the ice shelf, with dissolved concentrations having been 1–2 orders of magnitude greater than those of DMS or DMSPd. It is difficult to ascribe the formation of DMSO solely to the conventionally accepted pathways of DMS oxidation by either bacterial activity or photochemical reactions. A direct biosynthetic production from phytoplankton or bacteria might be involved which means that DMSO in aquatic environments could act as a significant source of DMS rather than as a sink as generally supposed.
46
Ma, Yi-Ping, Ivan Sudakov, Courtenay Strong, and Kenneth M. Golden. "Ising model for melt ponds on Arctic sea ice." New Journal of Physics 21, no. 6 (June 21, 2019): 063029. http://dx.doi.org/10.1088/1367-2630/ab26db.
Full text
47
Flocco, Daniela, Daniel L. Feltham, Eleanor Bailey, and David Schroeder. "The refreezing of melt ponds on Arctic sea ice." Journal of Geophysical Research: Oceans 120, no. 2 (February 2015): 647–59. http://dx.doi.org/10.1002/2014jc010140.
Full text
48
MORASSUTTI, M. P., and E. F. LEDREW. "ALBEDO AND DEPTH OF MELT PONDS ON SEA-ICE." International Journal of Climatology 16, no. 7 (July 1996): 817–38. http://dx.doi.org/10.1002/(sici)1097-0088(199607)16:7<817::aid-joc44>3.0.co;2-5.
Full text
49
Webster, Melinda A., Ignatius G. Rigor, Donald K. Perovich, Jacqueline A. Richter‐Menge, Christopher M. Polashenski, and Bonnie Light. "Seasonal evolution of melt ponds on Arctic sea ice." Journal of Geophysical Research: Oceans 120, no. 9 (September 2015): 5968–82. http://dx.doi.org/10.1002/2015jc011030.
Full text
50
Sudakov, I., S. A. Vakulenko, and K. M. Golden. "Arctic melt ponds and bifurcations in the climate system." Communications in Nonlinear Science and Numerical Simulation 22, no. 1-3 (May 2015): 70–81. http://dx.doi.org/10.1016/j.cnsns.2014.09.003.
Full text