The Cryosphere / Circumpolar patterns of potential mean annual ground temperature based on surface state obtained from microwave satellite data

Gap filling is required for temporally and spatially consistent records of land surface temperature from satellite data due to clouds or snow cover. Land surface state, frozen versus unfrozen conditions, can be, however, captured globally with satellite data obtained by microwave sensors. The number of frozen days per year has been previously proposed to be used for permafrost extent determination. This suggests an underlying relationship between number of frozen days and mean annual ground temperature (MAGT). We tested this hypothesis for the Northern Hemisphere north of 50N using coarse-spatial-resolution microwave satellite data (Metop Advanced SCATterometer ASCAT and Special Sensor Microwave Imager SSM/I; 12.5 and 25km nominal resolution; 20072012), which provide the necessary temporal sampling. The MAGT from GTN-P (Global TerrestrialNetworkfor Permafrost) borehole records at the coldest sensor depth was tested for validity in order to build a comprehensive in situ data set for calibration and validation and was eventually applied. Results are discussed with respect to snow water equivalent, soil properties, land cover and permafrost type. The obtained temperature maps were classified for permafrost extent and compared to alternative approaches.An R2 of 0.99 was found for correlation between and MAGT at zero annual amplitude provided in GTN-P metadata and MAGT at the coldest sensor depth. The latter could be obtained with an RMSE of 2.2C from ASCAT and 2.5C from SSM/I surface state records using a linear model. The average deviation within the validation period is less than 1C at locations without glaciers and coastlines within the resolution cell in the case of ASCAT. The exclusion of snow melt days (available for ASCAT) led to better results. This suggests that soil warming under wet snow cover needs to be accounted for in this context. Specifically Scandinavia and western Russia are affected. In addition, MAGT at the coldest sensor depth was overestimated in areas with a certain amount of organic material and in areas of cold permafrost. The derived permafrost extent differed between the used data sets and methods. Deviations are high in central Siberia, for example. We show that microwave-satellite-derived surface state records can provide an estimation of not only permafrost extent but also MAGT without the need for gap filling. This applies specifically to ASCAT. The deviations among the tested data sets, their spatial patterns as well as in relation to environmental conditions, revealed areas which need special attention for modelling of MAGT.(VLID)278661

TerraSAR-X Time Series Fill a Gap in Spaceborne Snowmelt Monitoring of Small Arctic Catchments—A Case Study on Qikiqtaruk(Herschel Island), Canada

The timing of snowmelt is an important turning point in the seasonal cycle of small Arctic catchments. The TerraSAR-X (TSX) satellite mission is a synthetic aperture radar system (SAR) with high potential to measure the high spatiotemporal variability of snow cover extent (SCE) and fractional snow cover (FSC) on the small catchment scale. We investigate the performance of multi-polarized and multi-pass TSX X-Band SAR data in monitoring SCE and FSC in small Arctic tundra catchments of Qikiqtaruk (Herschel Island) off the Yukon Coast in the Western Canadian Arctic. We applied a threshold based segmentation on ratio images between TSX images with wet snow and a dry snow reference, and tested the performance of two different thresholds. We quantitatively compared TSX- and Landsat 8-derived SCE maps using confusion matrices and analyzed the spatiotemporal dynamics of snowmelt from 2015 to 2017 using TSX, Landsat 8 and in situ time lapse data. Our data showed that the quality of SCE maps from TSX X-Band data is strongly influenced by polarization and to a lesser degree by incidence angle. VH polarized TSX data performed best in deriving SCE when compared to Landsat 8. TSX derived SCE maps from VH polarization detected late lying snow patches that were not detected by Landsat 8. Results of a local assessment of TSX FSC against the in situ data showed that TSX FSC accurately captured the temporal dynamics of different snow melt regimes that were related to topographic characteristics of the studied catchments. Both in situ and TSX FSC showed a longer snowmelt period in a catchment with higher contributions of steep valleys and a shorter snowmelt period in a catchment with higher contributions of upland terrain. Landsat 8 had fundamental data gaps during the snowmelt period in all 3 years due to cloud cover. The results also revealed that by choosing a positive threshold of 1 dB, detection of ice layers due to diurnal temperature variations resulted in a more accurate estimation of snow cover than a negative threshold that detects wet snow alone. We find that TSX X-Band data in VH polarization performs at a comparable quality to Landsat 8 in deriving SCE maps when a positive threshold is used. We conclude that TSX data polarization can be used to accurately monitor snowmelt events at high temporal and spatial resolution, overcoming limitations of Landsat 8, which due to cloud related data gaps generally only indicated the onset and end of snowmelt

Ten Years of SeaWinds on QuikSCAT for Snow Applications

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

Ten Years of SeaWinds on QuikSCAT for Snow Applications

Abstract: 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

The seasonal dynamics of Arctic surface hydrology in permafrost environments

Climate-induced landscape evolution is resulting in changes to biogeochemical and hydrologi- cal cycling. In the Arctic and sub-Arctic permafrost zones, rising air temperatures are warming, and in some regions even thawing, the frozen ground. Permafrost is a carbon sink. The thermal state of the ground therefore has important implications on carbon exchange with the atmo- sphere. Permafrost thaw mobilises previously sequestered carbon stocks, potentially turning these high latitude regions into a net carbon source. Borehole temperature and active layer depth measurements are the traditional means for monitoring permafrost, however these point measurements cannot easily be extrapolated to the landscape-scale; Earth Observation (EO) data may be used for such purposes. It is widely recognised that changes in the thermal state of permafrost may be associated with longterm changes in surface hydrology. As the ground shifts from a frozen to a thawed state, Arctic lakes display changes in surface extent. Therefore, it has become common practice to explore lake dynamics, using these as indicators of permafrost change; dynamics being the keyword. Surface hydrology is a dynamic process. Discharge studies in the Arctic and sub-Arctic regions are associated with flashy hydrographs. Currently, however, remote sensing of permafrost lake change is done on the scale of decades without explicitly taking seasonality and rapid hydrolog- ical phenology into consideration. To examine the seasonal changes in Arctic surface hydrology on the landscape scale high temporal resolution data are necessary. Synthetic aperture radar instruments are exemplary for such a task. The PhD research focuses on establishing operational techniques for mapping open surface water using synthetic aperture radar data, investigating straightforward raster classification methods and exploring their feasibility by undertaking map accuracy and sensitivity studies (chapter 3). The results are then used to justify error propagation when developing an auto- mated procedure that creates temporal composites of water body extent. These temporal water body classifications are the main EO product used to identify and image seasonal surface water change in Arctic permafrost environments (chapter 4). Furthermore, a terrain-based hydrolog- ical study is undertaken to explore the context of the detected changes and possible links to relief and stream channel network (chapter 5). The aim of this PhD is to demonstrate a new method of dynamic monitoring using the Euro- pean Space Agency’s Envisat Advanced Synthetic Aperture Radar, recommending its incorpo- ration in longterm lake change studies. Technical feasibility is explored, the inherent trade-off vii between spatial and temporal resolution discussed. An automated surface water change de- tection algorithm is developed and its applicability to monitoring spring floods is assessed; noting possible modifications to the drainage system given present-day land-use and land- cover changes that are taking place in the study area, the hydrocarbon-rich Yamalo-Nenets Autonomous District in the North of West Siberia (chapter 6). The key significance of this research is to improve the current knowledge of Arctic lake change by including spring flood events and seasonality in the equation. Therefore, it is strongly believed that this research is of benefit to the entire permafrost community.AM Trofaier was a recipient of a DOC-fFORTE Fellowship [Women in Research and Technology] of the Austrian Academy of Sciences