Christopher A. Hiemstra

Interactive effects of wildfire and climate on permafrost degradation in Alaskan lowland forests

We examined the effects of fire disturbance on permafrost degradation and thaw settlement across a series of wildfires (from ~1930 to 2010) in the forested areas of collapse-scar bog complexes in the Tanana Flats lowland of interior Alaska. Field measurements were combined with numerical modeling of soil thermal dynamics to assess the roles of fire severity and climate history in postfire permafrost dynamics. Field-based calculations of potential thaw settlement following the loss of remaining ice-rich permafrost averaged 0.6 m. This subsidence would cause the surface elevations of forests to drop on average 0.1 m below the surface water level of adjacent collapse-scar features. Up to 0.5 m of thaw settlement was documented after recent fires, causing water impoundment and further thawing along forest margins. Substantial heterogeneity in soil properties (organic layer thickness, texture, moisture, and ice content) was attributed to differing site histories, which resulted in distinct soil thermal regimes by soil type. Model simulations showed increasing vulnerability of permafrost to deep thawing and thaw settlement with increased fire severity (i.e., reduced organic layer thickness). However, the thresholds of fire severity that triggered permafrost destabilization varied temporally in response to climate. Simulated permafrost dynamics underscore the importance of multiyear to multidecadal fluctuations in air temperature and snow depth in mediating the effects of fire on permafrost. Our results suggest that permafrost is becoming increasingly vulnerable to substantial thaw and collapse after moderate to high-severity fire, and the ability of permafrost to recover is diminishing as the climate continues to warm.

Supporting NASA SnowEx remote sensing strategies and requirements for L-band interferometric snow depth and snow water equivalent estimation

The objectives of this research are to (1) address remote sensing strategies and requirements for estimating snow depth and snow water equivalent (SWE) using existing L-Band interferometric data sets in coordination with field-based observations and modeling frameworks and, with this information, (2) inform the Next Generation Cold Land Processes Experiment (SnowEx) toward articulating the appropriate science and research questions for a single motivating science plan. As proposed, SnowEx is a multi-year airborne snow campaign with a primary goal of exploring multimodal sensor observations in coordination with field campaigns to inform the next generation snow remote sensing satellite platform. Based on limitations of satellite-based optical and LiDAR instruments operating in regions of the globe with consistent cloud-cover, the fact that many snow-dominated regions are at more northerly latitudes (limited solar illumination in the middle of winter), and these snow-dominated regions often experience periods of prolonged cloud cover (due to synoptic precipitation events), a microwave remote sensing platform may be the most viable path to space for a dedicated snow remote sensing mission. Specifically, L-Band radar interferometry has shown some unique promise with an archive of historical and contemporary satellite collections from JAXAs PALSAR-1 and PALSAR-2 instruments, respectively. Moreover, with the expected NISAR (NASA-ISRO Synthetic Aperture Radar) mission launch in 2020 and the unprecedented availability of dedicated global interferometric L-Band products every 12-days, as well as what is in essence a NISAR airborne simulator in JPLs UAVSAR platform, the L-Band interferometric approach to estimating snow depth and snow water equivalent (SWE) requires further investigation within the context of in-situ observations and modeling frameworks.