scholarly journals Melt pond fraction and spectral sea ice albedo retrieval from MERIS data – Part 2: Case studies and trends of sea ice albedo and melt ponds in the Arctic for years 2002–2011

2015 ◽  
Vol 9 (4) ◽  
pp. 1567-1578 ◽  
Author(s):  
L. Istomina ◽  
G. Heygster ◽  
M. Huntemann ◽  
H. Marks ◽  
C. Melsheimer ◽  
...  
Keyword(s):  
Sea Ice ◽  
Temporal Dynamics ◽  
Surface Air Temperature ◽  
Arctic Region ◽  
The Arctic ◽  
Melt Pond ◽  
Melt Ponds ◽  
Spatial And Temporal Dynamics ◽  
East Siberian Sea ◽  
Resolution Imaging

Abstract. The spatial and temporal dynamics of melt ponds and sea ice albedo contain information on the current state and the trend of the climate of the Arctic region. This publication presents a study on melt pond fraction (MPF) and sea ice albedo spatial and temporal dynamics obtained with the Melt Pond Detection (MPD) retrieval scheme for the Medium Resolution Imaging Spectrometer (MERIS) satellite data. This study compares sea ice albedo and MPF to surface air temperature reanalysis data, compares MPF retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS), and examines albedo and MPF trends. Weekly averages of MPF for 2007 and 2011 showed different MPF dynamics while summer sea ice minimum was similar for both years. The gridded MPF and albedo products compare well to independent reanalysis temperature data and show melt onset when the temperature gets above zero; however MPD shows an offset at low MPFs of about 10 % most probably due to unscreened high clouds. Weekly averaged trends show pronounced dynamics of both, MPF and albedo: a negative MPF trend in the East Siberian Sea and a positive MPF trend around the Queen Elizabeth Islands. The negative MPF trend appears due to a change of the absolute MPF value in its peak, whereas the positive MPF trend is created by the earlier melt onset, with the peak MPF values unchanged. The MPF dynamics in the East Siberian Sea could indicate a temporal change of ice type prevailing in the region, as opposed to the Queen Elizabeth Islands, where MPF dynamics react to an earlier seasonal onset of melt.

scholarly journals Reflective properties of melt ponds on sea ice

2018 ◽  
Vol 12 (6) ◽  
pp. 1921-1937 ◽  
Author(s):  
Aleksey Malinka ◽  
Eleonora Zege ◽  
Larysa Istomina ◽  
Georg Heygster ◽  
Gunnar Spreen ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Sea Ice ◽  
Atmospheric Correction ◽  
Scattering Coefficient ◽  
Spherical Particles ◽  
The Arctic ◽  
Melt Pond ◽  
Melt Ponds ◽  
Bottom Albedo

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.

scholarly journals A mechanism that produces dichotomy in melt pond coverage in sea ice floes

2016 ◽  
Author(s):  
Predrag Popović ◽  
Dorian S. Abbot
Keyword(s):  
Fixed Point ◽  
Sea Ice ◽  
Large Scale ◽  
Bimodal Distribution ◽  
Melting Behavior ◽  
The Arctic ◽  
Scale Model ◽  
Melt Pond ◽  
Melt Ponds ◽  
Ice Floes

Abstract. Late in the melt season, sea ice floes in the Arctic have been observed to exhibit a large range in melt pond coverage, from heavily ponded to almost pond free. Some of these observations are consistent with a bimodal distribution in pond coverage with few intermediately ponded ice floes. We present a model for the evolution of melt ponds on sea ice floes in which conservation of hydrostatic balance in response to melt creates an unstable fixed point in pond coverage: if the initial pond coverage is below a threshold value the floe becomes unponded, and if it is above the threshold the floe becomes heavily ponded. Whether the fixed point is physically realistic depends on the differential melting rates of different points on the ice: ice at the perimeter of ponds needs to melt sufficiently slower than bare ice on average. Interestingly, this shows that the melting behavior of the narrow boundary between bare ice and melt ponds can govern the melt pond evolution of the entire ice floe. 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 us improve large-scale model parameterizations and sea ice forecasts in a warming climate.

scholarly journals Improved cloud detection over sea ice and snow during Arctic summer using MERIS data

2020 ◽  
Vol 13 (12) ◽  
pp. 6459-6472
Author(s):  
Larysa Istomina ◽  
Henrik Marks ◽  
Marcus Huntemann ◽  
Georg Heygster ◽  
Gunnar Spreen
Keyword(s):  
Remote Sensing ◽  
Sea Ice ◽  
Remote Sensing Data ◽  
The Arctic ◽  
Cloud Detection ◽  
High Quality ◽  
Melt Pond ◽  
Resolution Imaging ◽  
Cloud Mask ◽  
Cloud Screening

Abstract. The historic MERIS (Medium Resolution Imaging Spectrometer) sensor on board Envisat (Environmental Satellite, operation 2002–2012) provides valuable remote sensing data for the retrievals of summer sea ice in the Arctic. MERIS data together with the data of recently launched successor OLCI (Ocean and Land Colour Instrument) on board Sentinel 3A and 3B (2016 onwards) can be used to assess the long-term change of the Arctic summer sea ice. An important prerequisite to a high-quality remote sensing dataset is an accurate separation of cloudy and clear pixels to ensure lowest cloud contamination of the resulting product. The presence of 15 visible and near-infrared spectral channels of MERIS allows high-quality retrievals of sea ice albedo and melt pond fraction, but it makes cloud screening a challenge as snow, sea ice and clouds have similar optical features in the available spectral range of 412.5–900 nm. In this paper, we present a new cloud screening method MECOSI (MERIS Cloud Screening Over Sea Ice) for the retrievals of spectral albedo and melt pond fraction (MPF) from MERIS. The method utilizes all 15 MERIS channels, including the oxygen A absorption band. For the latter, a smile effect correction has been developed to ensure high-quality screening throughout the whole swath. A total of 3 years of reference cloud mask from AATSR (Advanced Along-Track Scanning Radiometer) (Istomina et al., 2010) have been used to train the Bayesian cloud screening for the available limited MERIS spectral range. Whiteness and brightness criteria as well as normalized difference thresholds have been used as well. The comparison of the developed cloud mask to the operational AATSR and MODIS (Moderate Resolution Imaging Spectroradiometer) cloud masks shows a considerable improvement in the detection of clouds over snow and sea ice, with about 10 % false clear detections during May–July and less than 5 % false clear detections in the rest of the melting season. This seasonal behavior is expected as the sea ice surface is generally brighter and more challenging for cloud detection in the beginning of the melting season. The effect of the improved cloud screening on the MPF–albedo datasets is demonstrated on both temporal and spatial scales. In the absence of cloud contamination, the time sequence of MPFs displays a greater range of values throughout the whole summer. The daily maps of the MPF now show spatially uniform values without cloud artifacts, which were clearly visible in the previous version of the dataset. The developed cloud screening routine can be applied to address cloud contamination in remote sensing data over sea ice. The resulting cloud mask for the MERIS operating time, as well as the improved MPF–albedo datasets for the Arctic region, is available at https://www.seaice.uni-bremen.de/start/ (Istomina et al., 2017).

scholarly journals Regional melt-pond fraction and albedo of thin Arctic first-year drift ice in late summer

2015 ◽  
Vol 9 (1) ◽  
pp. 255-268 ◽  
Author(s):  
D. V. Divine ◽  
M. A. Granskog ◽  
S. R. Hudson ◽  
C. A. Pedersen ◽  
T. I. Karlsen ◽  
...  
Keyword(s):  
Sea Ice ◽  
Open Water ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
First Year ◽  
Surface Type ◽  
Melt Pond ◽  
Melt Ponds

Abstract. The paper presents a case study of the regional (≈150 km) morphological and optical properties of a relatively thin, 70–90 cm modal thickness, first-year Arctic sea ice pack in an advanced stage of melt. The study combines in situ broadband albedo measurements representative of the four main surface types (bare ice, dark melt ponds, bright melt ponds and open water) and images acquired by a helicopter-borne camera system during ice-survey flights. The data were collected during the 8-day ICE12 drift experiment carried out by the Norwegian Polar Institute in the Arctic, north of Svalbard at 82.3° N, from 26 July to 3 August 2012. A set of > 10 000 classified images covering about 28 km2 revealed a homogeneous melt across the study area with melt-pond coverage of ≈ 0.29 and open-water fraction of ≈ 0.11. A decrease in pond fractions observed in the 30 km marginal ice zone (MIZ) occurred in parallel with an increase in open-water coverage. The moving block bootstrap technique applied to sequences of classified sea-ice images and albedo of the four surface types yielded a regional albedo estimate of 0.37 (0.35; 0.40) and regional sea-ice albedo of 0.44 (0.42; 0.46). Random sampling from the set of classified images allowed assessment of the aggregate scale of at least 0.7 km2 for the study area. For the current setup configuration it implies a minimum set of 300 images to process in order to gain adequate statistics on the state of the ice cover. Variance analysis also emphasized the importance of longer series of in situ albedo measurements conducted for each surface type when performing regional upscaling. The uncertainty in the mean estimates of surface type albedo from in situ measurements contributed up to 95% of the variance of the estimated regional albedo, with the remaining variance resulting from the spatial inhomogeneity of sea-ice cover.

Modelling melt ponds in Global Circulation Models

2020 ◽  
Author(s):  
Jean Sterlin ◽  
Thierry Fichefet ◽  
François Massonnet ◽  
Olivier Lecomte ◽  
Martin Vancoppenolle
Keyword(s):  
Aspect Ratio ◽  
Sea Ice ◽  
Climate Models ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Global Circulation ◽  
Melt Pond ◽  
Global Circulation Models ◽  
Melt Ponds ◽  
The Impact

<p>Melt ponds appear during the Arctic summer on the sea ice cover when meltwater and liquid precipitation collect in the depressions of the ice surface. The albedo of the melt ponds is lower than that of surrounding ice and snow areas. Consequently, the melt ponds are an important factor for the ice-albedo feedback, a mechanism whereby a decrease in albedo results in greater absorption of solar radiation, further ice melt, and lower albedos </p><p>To account for the effect of melt ponds on the climate, several numerical schemes have been introduced for Global Circulation Models. They can be classified into two groups. The first group makes use of an explicit relation to define the aspect ratio of the melt ponds. The scheme of Holland et al. (2012) uses a constant ratio of the melt pond depth to the fraction of sea ice covered by melt ponds. The second group relies on theoretical considerations to deduce the area and volume of the melt ponds. The scheme of Flocco et al. (2012) uses the ice thickness distribution to share the meltwater between the ice categories and determine the melt ponds characteristics.</p><p>Despite their complexity, current melt pond schemes fail to agree on the trends in melt pond fraction of sea ice area during the last decades. The disagreement casts doubts on the projected melt pond changes. It also raises questions on the definition of the physical processes governing the melt ponds in the schemes and their sensitivity to atmospheric surface conditions.</p><p>In this study, we aim at identifying 1) the conceptual difference of the aspect ratio definition in melt pond schemes; 2) the role of refreezing for melt ponds; 3) the impact of the uncertainties in the atmospheric reanalyses. To address these points, we have run the Louvain-la-Neuve Ice Model (LIM), part of the Nucleus for European Modelling of the Ocean (NEMO) version 3.6 along with two different atmospheric reanalyses as surface forcing sets. We used the reanalyses in association with Holland et al. (2012) and Flocco et al. (2012) melt pond schemes. We selected Holland et al. (2012) pond refreezing formulation for both schemes and tested two different threshold temperatures for refreezing. </p><p>From the experiments, we describe the impact on Arctic sea ice and state the importance of including melt ponds in climate models. We attempt at disentangling the separate effects of the type of melt pond scheme, the refreezing mechanism, and the atmospheric surface forcing method, on the climate. We finally formulate a recommendation on the use of melt ponds in climate models. </p>

scholarly journals Applying high-resolution visible imagery to satellite melt pond fraction retrieval: A neural network approach

2018 ◽  
Vol 3 (3) ◽  
Author(s):  
Qi Liu 1 ◽  
Yawen Zhang 1
Keyword(s):  
Neural Network ◽  
Sea Ice ◽  
Satellite Data ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Neural Network Approach ◽  
Melt Pond ◽  
Melt Ponds ◽  
Arctic Sea ◽  
Visible Imagery

During summer, melt ponds have a significant influence on Arctic sea-ice albedo. The melt pond fraction (MPF) also has the ability to forecast the Arctic sea-ice in a certain period. It is important to retrieve accurate melt pond fraction (MPF) from satellite data for Arctic research. This paper proposes a satellite MPF retrieval model based on the multi-layer neural network, named MPF-NN. Our model uses multi-spectral satellite data as model input and MPF information from multi-site and multi-period visible imagery as prior knowledge for modeling. It can effectively model melt ponds evolution of different regions and periods over the Arctic. Evaluation results show that the MPF retrieved from MODIS data using the proposed model has an RMSE of 3.91% and a correlation coefficient of 0.73. The seasonal distribution of MPF is also consistent with previous results.

scholarly journals Dimethylsulfide dynamics in first-year sea ice melt ponds in the Canadian Arctic Archipelago

2017 ◽  
Author(s):  
Margaux Gourdal ◽  
Martine Lizotte ◽  
Guillaume Massé ◽  
Michel Gosselin ◽  
Michael Scarratt ◽  
...  
Keyword(s):  
Sea Ice ◽  
Canadian Arctic ◽  
The Arctic ◽  
First Year ◽  
Canadian Arctic Archipelago ◽  
Ice Melt ◽  
Melt Pond ◽  
Potential Source ◽  
Melt Ponds ◽  
Cover Up

Abstract. Melt pond formation is a natural 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 dimethylsulfide (DMS) for the atmosphere. Here we report on the concentrations and dynamics of DMS in nine melt ponds sampled in July 2014 in the Eastern Canadian Arctic. DMS concentrations were under the detection limit (

scholarly journals Inorganic carbon dynamics of melt pond-covered first year sea ice in the Canadian Arctic

2014 ◽  
Vol 11 (5) ◽  
pp. 7485-7519 ◽  
Author(s):  
N.-X. Geilfus ◽  
R. J. Galley ◽  
O. Crabeck ◽  
T. Papakyriakou ◽  
J. Landy ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
First Year ◽  
Ice Melt ◽  
Melt Pond ◽  
Melt Ponds ◽  
Arctic Sea ◽  
Melt Water

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.

Arctic summer sea-ice SAR signatures, melt-season characteristics, and melt-pond fractions

Polar Record ◽  
1997 ◽  
Vol 33 (185) ◽  
pp. 101-112 ◽  
Author(s):  
M. O. Jeffries ◽  
K. Schwartz ◽  
S. Li
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Late Summer ◽  
Beaufort Sea ◽  
Early Summer ◽  
The Arctic ◽  
Late Winter ◽  
Melt Pond ◽  
Melt Ponds ◽  
The Arctic Ocean

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.

scholarly journals Prediction of Arctic temperature and sea ice using a high-resolution coupled model

2021 ◽  
pp. 1-62
Author(s):  
Le Chang ◽  
Jing-Jia Luo ◽  
Jiaqing Xue ◽  
Haiming Xu ◽  
Nick Dunstone
Keyword(s):  
High Resolution ◽  
Sea Ice ◽  
Air Temperature ◽  
Southern Oscillation ◽  
Coupled Model ◽  
Surface Air Temperature ◽  
Arctic Region ◽  
Warming Trend ◽  
Lower Atmosphere ◽  
The Arctic

AbstractUnder global warming, surface air temperature has risen rapidly and sea ice decreased markedly in the Arctic. These drastic climate changes have brought about various severe impacts on the vulnerable environment and ecosystem there. Thus, accurate prediction of Arctic climate becomes more important than before. Here we examine the seasonal to interannual predictive skills of 2-meter air temperature (2-m T) and sea ice cover (SIC) over the Arctic region (70°∼90°N) during 1980–2014 with a high-resolution global coupled model called the Met Office Decadal Prediction System version 3 (DePreSys3). The model captures well both the climatology and interannual variability of the Arctic 2-m T and SIC. Moreover, the anomaly correlation coefficient (ACC) of Arctic-averaged 2-m T and SIC shows statistically significant skills at lead times up to 16 months. This is mainly due to the contribution of strong decadal trends. In addition, it is found that the peak warming trend of Arctic 2-m T lags the maximum decrease trend of SIC by one month, in association with the heat flux forcing from the ocean surface to lower atmosphere. While the predictive skill is generally much lower for the detrended variations, we find a close relationship between the tropical Pacific El Niño–Southern Oscillation and the Arctic detrended 2-m T anomalies. This indicates potential seasonal to interannual predictability of the Arctic natural variations.

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