Physical properties of different sea ice types at ArcticNet, CFL and CASES ice stations, eastern Beaufort Sea

A study of the polarimetric backscattering response of newly formed sea ice types under a large assortment of surface coverage was conducted using a ship-based C-band polarimetric radar system. Polarimetric backscattering results and physical data for 40 stations during the fall freeze-up of 2003, 2006, and 2007 are presented. Analysis of the copolarized correlation coefficient showed its sensitivity to both sea ice thickness and surface coverage and resulted in a statistically significant separation of ice thickness into two regimes: ice less than 6 cm thick and ice greater than 8 cm thick. A case study quantified the backscatter of a layer of snow infiltrated frost flowers on new sea ice, showing that the presence of the old frost flowers can enhance the backscatter by more than 6 dB. Finally, a statistical analysis of a series of temporal-spatial measurements over a visually homogeneous frost-flower-covered ice floe identified temperature as a significant, but not exclusive, factor in the backscattering measurements.

Wetland maps including open water extent dynamics based on ENVISAT ASAR WS for Siberia, 2007 and 2008, links to GeoTIFFs

Wetlands store large amounts of carbon, and depending on their status and type, they release specific amounts of methane gas to the atmosphere. The connection between wetland type and methane emission has been investigated in various studies and utilized in climate change monitoring and modelling. For improved estimation of methane emissions, land surface models require information such as the wetland fraction and its dynamics over large areas. Existing datasets of wetland dynamics present the total amount of wetland (fraction) for each model grid cell, but do not discriminate the different wetland types like permanent lakes, periodically inundated areas or peatlands. Wetland types differently influence methane fluxes and thus their contribution to the total wetland fraction should be quantified. Especially wetlands of permafrost regions are expected to have a strong impact on future climate due to soil thawing. In this study ENIVSAT ASAR Wide Swath data was tested for operational monitoring of the distribution of areas with a long-term SW near 1 (hSW) in northern Russia (SW = degree of saturation with water, 1 = saturated), which is a specific characteristic of peatlands. For the whole northern Russia, areas with hSW were delineated and discriminated from dynamic and open water bodies for the years 2007 and 2008. The area identified with this method amounts to approximately 300,000 km**2 in northern Siberia in 2007. It overlaps with zones of high carbon storage. Comparison with a range of related datasets (static and dynamic) showed that hSW represents not only peatlands but also temporary wetlands associated with post-forest fire conditions in permafrost regions. Annual long-term monitoring of change in boreal and tundra environments is possible with the presented approach. Sentinel-1, the successor of ENVISAT ASAR, will provide data that may allow continuous monitoring of these wetland dynamics in the future complementing global observations of wetland fraction.

Comparisons of observed ice properties and Envisat Advanced Synthetic Aperture Radar (ASAR) data during Nathanial B. Palmer cruise NBP09-01 and Oden cruise OSO08/09

Envisat Advanced Synthetic Aperture Radar (ASAR) Wide Swath Mode (WSM) images are used to derive C-band HH-polarization normalized radar cross sections (NRCS). These are compared with ice-core analysis and visual ship-based observations of snow and ice properties observed according to the Antarctic Sea Ice Processes and Climate (ASPeCt) protocol during two International Polar Year summer cruises (Oden 2008 and Palmer 2009) in West Antarctica. Thick first-year (TFY) and multi-year (MY) ice were the dominant ice types. The NRCS value ranges between -16.3 ± 1.1 and -7.6 ± 1.0 dB for TFY ice, and is -12.6 ± 1.3 dB for MY ice; for TFY ice, NRCS values increase from ~-15 dB to -9 dB from December/January to mid-February. In situ and ASPeCt observations are not, however, detailed enough to interpret the observed NRCS change over time. Co-located Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) vertically polarized 37 GHz brightness temperatures (TB37V), 7 day and 1 day averages as well as the TB37V difference between ascending and descending AMSR-E overpasses suggest the low NRCS values (-15 dB) are associated with snowmelt being still in progress, while the change towards higher NRCS values (-9dB) is caused by commencement of melt-refreeze cycles after about mid-January.

Plume-top altitude time-series during May 2011 volcanic eruption of Grímsvötn, Iceland

Plume-top altitude time series of the volcanic plume during the eruption of Grímsvötn in Iceland 21-28 May 2011. The altitude was estimated from weather radar echo top data from two weather radars, Keflavik and Klaustur. Keflavik radar is a fixed position C-band weather radar close to Keflavik International Airport, at 64°01.583'N, 22°38.150'W. The height of the antenna is 47 m a.s.l. and the distance to Grímsvötn volcano is 257 km. Klaustur radar is a mobile X-band weather radar located close to Kirkjubaejarklaustur, at 63°46.500'N, 17°57.817'W. The height of the antenna is also 47 m a.s.l. and the distance to Grímsvötn volcano is 75 km.

(Table 1) Accumulation and ice discharge of West Antarctic glaciers draining into the Amundsen Sea between 1974 and 2007

The Advanced Land Observation System (ALOS) Phased-Array Synthetic-Aperture Radar (PALSAR) is an L-band frequency (1.27 GHz) radar capable of continental-scale interferometric observations of ice sheet motion. Here, we show that PALSAR data yield excellent measurements of ice motion compared to C-band (5.6 GHz) radar data because of greater temporal coherence over snow and firn. We compare PALSAR velocities from year 2006 in Pine Island Bay, West Antarctica with those spanning years 1974 to 2007. Between 1996 and 2007, Pine Island Glacier sped up 42% and ungrounded over most of its ice plain. Smith Glacier accelerated 83% and ungrounded as well. Their largest speed up are recorded in 2007. Thwaites Glacier is not accelerating but widening with time and its eastern ice shelf doubled its speed. Total ice discharge from these glaciers increased 30% in 12 yr and the net mass loss increased 170% from 39 ± 15 Gt/yr to 105 ± 27 Gt/yr. Longer-term velocity changes suggest only a moderate loss in the 1970s. As the glaciers unground into the deeper, smoother beds inland, the mass loss from this region will grow considerably larger in years to come.

Plume-top altitude time-series during 2010 volcanic eruption of Eyjafjallajökull

The eruption of Eyjafjallajökull volcano in 2010 lasted for 39 days, 14 April-23 May. The eruption had two explosive phases separated by a phase with lava formation and reduced explosive activity. The height of the plume was monitored every 5 min with a C-band weather radar located in Keflavík International Airport, 155 km distance from the volcano. Furthermore, several web cameras were mounted with a view of the volcano, and their images saved every five seconds. Time series of the plume-top altitude were constructed from the radar observations and images from a web camera located in the village Hvolsvöllur at 34 km distance from the volcano. This paper presents the independent radar and web camera time series and performs cross validation.

Circumarctic wetland dataset based on ENVISAT ASAR Global Monitoring Mode with links to geotiff image and NetCDF files (2005-01 to 2011-12)

A circumpolar representative and consistent wetland map is required for a range of applications ranging from upscaling of carbon fluxes and pools to climate modelling and wildlife habitat assessment. Currently available data sets lack sufficient accuracy and/or thematic detail in many regions of the Arctic. Synthetic aperture radar (SAR) data from satellites have already been shown to be suitable for wetland mapping. Envisat Advanced SAR (ASAR) provides global medium-resolution data which are examined with particular focus on spatial wetness patterns in this study. It was found that winter minimum backscatter values as well as their differences to summer minimum values reflect vegetation physiognomy units of certain wetness regimes. Low winter backscatter values are mostly found in areas vegetated by plant communities typically for wet regions in the tundra biome, due to low roughness and low volume scattering caused by the predominant vegetation. Summer to winter difference backscatter values, which in contrast to the winter values depend almost solely on soil moisture content, show expected higher values for wet regions. While the approach using difference values would seem more reasonable in order to delineate wetness patterns considering its direct link to soil moisture, it was found that a classification of winter minimum backscatter values is more applicable in tundra regions due to its better separability into wetness classes. Previous approaches for wetland detection have investigated the impact of liquid water in the soil on backscatter conditions. In this study the absence of liquid water is utilized. Owing to a lack of comparable regional to circumpolar data with respect to thematic detail, a potential wetland map cannot directly be validated; however, one might claim the validity of such a product by comparison with vegetation maps, which hold some information on the wetness status of certain classes. It was shown that the Envisat ASAR-derived classes are related to wetland classes of conventional vegetation maps, indicating its applicability; 30% of the land area north of the treeline was identified as wetland while conventional maps recorded 1-7%.

Circumpolar dataset of Soil Organic Carbon north of treeline derived from ENVISAT ASAR GM, link to GeoTIFF

A new approach for the estimation of soil organic carbon (SOC) pools north of the tree line has been developed based on synthetic aperture radar (SAR; ENVISAT Advanced SAR Global Monitoring mode) data. SOC values are directly determined from backscatter values instead of upscaling using land cover or soil classes. The multi-mode capability of SAR allows application across scales. It can be shown that measurements in C band under frozen conditions represent vegetation and surface structure properties which relate to soil properties, specifically SOC. It is estimated that at least 29 Pg C is stored in the upper 30 cm of soils north of the tree line. This is approximately 25 % less than stocks derived from the soil-map-based Northern Circumpolar Soil Carbon Database (NCSCD). The total stored carbon is underestimated since the established empirical relationship is not valid for peatlands or strongly cryoturbated soils. The approach does, however, provide the first spatially consistent account of soil organic carbon across the Arctic. Furthermore, it could be shown that values obtained from 1 km resolution SAR correspond to accounts based on a high spatial resolution (2 m) land cover map over a study area of about 7 × 7 km in NE Siberia. The approach can be also potentially transferred to medium-resolution C-band SAR data such as ENVISAT ASAR Wide Swath with ~120 m resolution but it is in general limited to regions without woody vegetation. Global Monitoring-mode-derived SOC increases with unfrozen period length. This indicates the importance of this parameter for modelling of the spatial distribution of soil organic carbon storage.

Spring snowmelt and midwinter thaw and refreeze north of 60°N based on Seawinds QuikScat 2000-2009

The scatterometer SeaWinds on QuikSCAT provided regular measurements at Ku-band from 1999 to 2009. Although it was designed for ocean applications, it has been frequently used for the assessment of seasonal snowmelt patterns aside from other terrestrial applications such as ice cap monitoring, phenology and urban mapping. This paper discusses general data characteristics of SeaWinds and reviews relevant change detection algorithms. Depending on the complexity of the method, parameters such as long-term noise and multiple event analyses were incorporated. Temporal averaging is a commonly accepted preprocessing step with consideration of diurnal, multi-day or seasonal averages.