The observation of the thin-ice thickness distribution within the Laptev Sea polynya using MODIS data

Polynyas are of high research interest since these features are areas of extensive new ice formation. The calculation of accurate ice-production values requires the knowledge of polynya area and thin-ice thickness distribution. These two variables can be derived by remote sensing data. However, a cross-validation study of various remote sensing data sets indicates that the spatial resolution issue is essential for the retrieval of accurate thin-ice thickness distribution. Thus, high-resolution remote sensing data must be used. MODIS thermal-infrared data with a spatial resolution of 1 km × 1 km is appropriate for the retrieval of thin-ice thickness distribution within the polynya. The algorithm to derive thermal-infrared thin-ice thickness is improved to state-of-the-art parameterizations. The mean absolute error of thin-ice thickness is ±4.7 cm for ice below 20 cm of thickness. The thin-ice thickness maps lack full coverage due to the restriction of the algorithm to cloud-free and nighttime data. Therefore, a compositing method is applied to compute daily thin-ice thickness maps. These maps cover on average 70 % of the Laptev Sea polynya. In order to fill the remaining gaps a combined remote sensing – model approach is developed to provide a consistent time series of high-resolution thin-ice thickness maps. This data set is valuable for the retrieval of accurate ice production within polynyas

The extreme melt across the Greenland ice sheet in 2012

The discovery of the 2012 extreme melt event across almost the entire surface of the Greenland ice sheet is presented. Data from three different satellite sensors – including the Oceansat-2 scatterometer, the Moderate-resolution Imaging Spectroradiometer, and the Special Sensor Microwave Imager/Sounder – are combined to obtain composite melt maps, representing the most complete melt conditions detectable across the ice sheet. Satellite observations reveal that melt occurred at or near the surface of the Greenland ice sheet across 98.6% of its entire extent on 12 July 2012, including the usually cold polar areas at high altitudes like Summit in the dry snow facies of the ice sheet. This melt event coincided with an anomalous ridge of warm air that became stagnant over Greenland. As seen in melt occurrences from multiple ice core records at Summit reported in the published literature, such a melt event is rare with the last significant one occurring in 1889 and the next previous one around seven centuries earlier in the Medieval Warm Period. Given its rarity, the 2012 extreme melt across Greenland provides an exceptional opportunity for new studies in broad interdisciplinary geophysical research

Comparison of Satellite, Thermochron and Air Temperatures at Summit, Greenland, During the Winter of 2008/09

Current trends show rise in Arctic surface and air temperatures, including over the Greenland ice sheet where rising temperatures will contribute to increased sea-level rise through increased melt. We aim to establish the uncertainties in using satellite-derived surface temperature for measuring Arctic surface temperature, as satellite data are increasingly being used to assess temperature trends. To accomplish this, satellite-derived surface temperature, or land-surface temperature (LST), must be validated and limitations of the satellite data must he assessed quantitatively. During the 2008/09 boreal winter at Summit, Greenland, we employed data from standard US National Oceanic and Atmospheric Administration (NOAA) air-temperature instruments, button-sized temperature sensors called thermochrons and the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite instrument to (1) assess the accuracy and utility of thermochrons in an ice-sheet environment and (2) compare MODIS-derived LSTs with thermochron-derived surface and air temperatures. The thermochron-derived air temperatures were very accurate, within 0.1+/-0.3 C of the NOAA-derived air temperature, but thermochron-derived surface temperatures were approx. 3 C higher than MODIS-derived LSTs. Though the surface temperature is largely determined by air temperature, these variables can differ significantly. Furthermore, we show that the winter-time mean air temperature, adjusted to surface temperature was approx. 11 C higher than the winter-time mean MODIS-derived LST. This marked difference occurs largely because of satellite-derived LSTs cannot be measured through cloud cover, so caution must be exercised in using time series of satellite LST data to study seasonal temperature trends

Thin-ice dynamics and ice production in the Storfjorden polynya for winter-seasons 2002/2003–2013/2014 using MODIS thermal infrared imagery

Spatial and temporal characteristics of the Storfjorden polynya, which forms regularly in the proximity of the islands Spitsbergen, Barentsøya and Edgeøya in the Svalbard archipelago under the influence of strong north-easterly winds, have been investigated for the period 2002/2003 to 2013/2014 using thermal infrared satellite imagery. Thin-ice thicknesses were calculated from MODIS ice-surface temperatures, combined with ECMWF ERA-Interim atmospheric reanalysis data in an energy-balance model. Based on calculated thin-ice thicknesses, associated quantities like polynya area and total ice production were derived and compared to previous remote sensing and modeling studies. A basic coverage-correction scheme was applied to account for cloud-gaps in the daily composites. The sea ice in the Storfjorden area experiences a late fall freeze-up in several years over the 12 winter-period, with an increasing frequency of large polynya events until the end of December. During the regarded period, the mean polynya area is 4555.7 ± 1542.9 km2. The average ice production in the fjord is estimated with 28.3 ± 8.5 km3 per winter and therefore lower than in previous studies. Despite this comparatively short record of 12 winter-seasons, a significant positive trend of 20.2 km3 per decade could be detected, which contrasts earlier reports of a slightly negative trend in accumulated ice production prior to 2002. Derived estimates underline the importance of this relatively small coastal polynya system considering its contribution to the cold halocline layer through salt release during ice formation processes

Arctic surface temperatures from Metop AVHRR compared to in situ ocean and land data

The ice surface temperature (IST) is an important boundary condition for both atmospheric and ocean and sea ice models and for coupled systems. An operational ice surface temperature product using satellite Metop AVHRR infra-red data was developed for MyOcean. The IST can be mapped in clear sky regions using a split window algorithm specially tuned for sea ice. Clear sky conditions prevail during spring in the Arctic, while persistent cloud cover limits data coverage during summer. The cloud covered regions are detected using the EUMETSAT cloud mask. The Metop IST compares to 2 m temperature at the Greenland ice cap Summit within STD error of 3.14 °C and to Arctic drifting buoy temperature data within STD error of 3.69 °C. A case study reveals that the in situ radiometer data versus satellite IST STD error can be much lower (0.73 °C) and that the different in situ measurements complicate the validation. Differences and variability between Metop IST and in situ data are analysed and discussed. An inter-comparison of Metop IST, numerical weather prediction temperatures and in situ observation indicates large biases between the different quantities. Because of the scarcity of conventional surface temperature or surface air temperature data in the Arctic, the satellite IST data with its relatively good coverage can potentially add valuable information to model analysis for the Arctic atmosphere

A Supplementary Clear-Sky Snow and Ice Recognition Technique for CERES Level 2 Products

Identification of clear-sky snow and ice is an important step in the production of cryosphere radiation budget products, which are used in the derivation of long-term data series for climate research. In this paper, a new method of clear-sky snow/ice identification for Moderate Resolution Imaging Spectroradiometer (MODIS) is presented. The algorithm's goal is to enhance the identification of snow and ice within the Clouds and the Earth's Radiant Energy System (CERES) data after application of the standard CERES scene identification scheme. The input of the algorithm uses spectral radiances from five MODIS bands and surface skin temperature available in the CERES Single Scanner Footprint (SSF) product. The algorithm produces a cryosphere rating from an aggregated test: a higher rating corresponds to a more certain identification of the clear-sky snow/ice-covered scene. Empirical analysis of regions of interest representing distinctive targets such as snow, ice, ice and water clouds, open waters, and snow-free land selected from a number of MODIS images shows that the cryosphere rating of snow/ice targets falls into 95% confidence intervals lying above the same confidence intervals of all other targets. This enables recognition of clear-sky cryosphere by using a single threshold applied to the rating, which makes this technique different from traditional branching techniques based on multiple thresholds. Limited tests show that the established threshold clearly separates the cryosphere rating values computed for the cryosphere from those computed for noncryosphere scenes, whereas individual tests applied consequently cannot reliably identify the cryosphere for complex scenes

A Model-Based Temperature Adjustment Scheme for Wintertime Sea-Ice Production Retrievals from MODIS

Knowledge of the wintertime sea-ice production in Arctic polynyas is an important requirement for estimations of the dense water formation, which drives vertical mixing in the upper ocean. Satellite-based techniques incorporating relatively high resolution thermal-infrared data from MODIS in combination with atmospheric reanalysis data have proven to be a strong tool to monitor large and regularly forming polynyas and to resolve narrow thin-ice areas (i.e., leads) along the shelf-breaks and across the entire Arctic Ocean. However, the selection of the atmospheric data sets has a large influence on derived polynya characteristics due to their impact on the calculation of the heat loss to the atmosphere, which is determined by the local thin-ice thickness. In order to overcome this methodical ambiguity, we present a MODIS-assisted temperature adjustment (MATA) algorithm that yields corrections of the 2 m air temperature and hence decreases differences between the atmospheric input data sets. The adjustment algorithm is based on atmospheric model simulations. We focus on the Laptev Sea region for detailed case studies on the developed algorithm and present time series of polynya characteristics in the winter season 2019/2020. It shows that the application of the empirically derived correction decreases the difference between different utilized atmospheric products significantly from 49% to 23%. Additional filter strategies are applied that aim at increasing the capability to include leads in the quasi-daily and persistence-filtered thin-ice thickness composites. More generally, the winter of 2019/2020 features high polynya activity in the eastern Arctic and less activity in the Canadian Arctic Archipelago, presumably as a result of the particularly strong polar vortex in early 2020.</jats:p