Remote Sensing of Snow Phenology
Warming of the Arctic Boreal Region (ABR) is occurring at more than twice the global rate, promoting widespread permafrost degradation and substantial changes in hydrologic and ecosystem processes. Influential factors affecting ABR warming include the timing, duration and condition of seasonal snow cover. Snow provides a strong thermal buffer that effectively decouples soil and permafrost from the overlying atmosphere. The higher characteristic snow albedo relative to natural vegetation and the high specific heat capacity of water-ice also reduces surface energy loading, promoting cooler temperatures. However, global warming is promoting a regional reduction in seasonal snow cover especially at higher latitudes and elevations. The snow cover decline is also reinforcing global warming and further snow reductions through a positive snow-ice albedo feedback. The changing snow regime has major consequences for terrestrial ecosystems, including increasing hazards for regional communities from thawing permafrost and unstable snow and ice conditions; alteration of seasonal stream flows and degraded water quality; and degraded wildlife habitats. A key constraint for monitoring snow cover changes in the ABR is the sparse regional weather station network relative to the extreme landscape diversity. The long season of polar darkness combined with persistent cloud cover during the shoulder seasons also strongly restricts monitoring from satellite optical sensors.Here, we developed new capabilities for regional snow cover monitoring by exploiting the global coverage and all-weather capability of existing satellite microwave radiometer records (SSM/I, AMSR). Higher frequency (19-37 GHz) microwave brightness temperatures (Tb) and their vertical and horizontal polarization differences are strongly sensitive to snow cover extent and liquid water content, which we exploited to derive a set of satellite snow phenology metrics. The snow metrics included daily (diurnal) freeze-thaw (FT) dynamics, mean melt onset date (MMOD), snow cover depletion date (SO), and snowmelt duration (SMD) in spring. A similar algorithm was used to classify the occurrence of anomalous rain-on-snow (ROS) and icing events. The continuous daily Tb fidelity of the satellite records allowed for relatively precise characterization of the timing and duration of snow phenology events; albeit at relatively coarse (6-25km) spatial resolution. However, the resolution constraints were partially mitigated by exploiting complimentary finer scale information from optical satellite data (MODIS), including snow cover extent, surface albedo, and land surface temperature. These results are being used to characterize regional trends in critical snow cover properties and the impact of these changes on the ABR seasonal hydrology and ecosystems.
Boelman, N., G. Liston, E. Gurarie, A. Meddens, P. Mahoney, P. Kirchner, G. Bohrer, T. Brinkman, C. Cosgrove, J. Eitel, M. Hebblewhite, J. Kimball, S. LaPoint, A. Nolin, S. Hojlund Pederson, L. Prugh, A. Reinking, L. Vierling, 2018. Integrating snow science and wildlife ecology in Arctic-boreal North America. Environmental Research Letters 14, 010401, https://doi.org/10.1088/1748-9326/aaeec1.
Kim, Y., J.S. Kimball, J. Du, C.L.B. Schaaf, and P.B. Kirchner, 2018. Quantifying the effects of freeze-thaw transitions and snowpack melt on land surface albedo and energy exchange over Alaska and western Canada. Environmental Research Letters 13, 075009, https://doi.org/10/1088/1748-9326/aacf72.
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Kim, Y., J.S. Kimball, X. Xu, R.S. Dunbar, A. Colliander, and C. Derksen, 2019. Global assessment of the SMAP freeze/thaw data record and regional applications for detecting spring onset and frost events. Remote Sensing 11, 11, 1317, https://doi.org/10.3390/rs11111317.
Pan, C.G., P.B. Kirchner, J.S. Kimball, J. Du, and M.A. Rawlins, 2021. Snow phenology and hydrologic timing in the Yukon River basin, AK, USA. Remote Sensing 13, 12, 2284, https://doi.org/10.3390/rs13122284.
Pan, C., P. Kirchner, J.S. Kimball, and J. Du, 2020. A long-term passive microwave snowoff record for the Alaska region, 1988-2016. Remote Sensing, 12, 153, doi:10.3390/rs12010153.
Pan, C.G., P.B. Kirchner, J.S. Kimball, Y. Kim, and J. Du, 2018. Rain-on-snow events in Alaska, and their frequency and distribution from satellite observations. Environmental Research Letters 13, 075004, https://doi.org/10.1088/1748-9327/aac9d3.
Pan, C., J.S. Kimball, M. Munkhjargal, N. Robinson, E. Tijdeman, L. Menzel, and P. Kirchner, 2019. Role of surface melt and icing events in livestock mortality across Mongolia’s semi-arid landscapes. Remote Sensing 11, 2392, doi:10.3390/rs11202392.
Yi, Y., J.S. Kimball, J. Watts, S. Natali, D. Zona, J. Liu, M. Ueyama, H. Kobayashi, and C.E. Miller, 2020. Investigating the sensitivity of soil heterotrophic respiration to recent snow cover changes in Alaska using a satellite-based permafrost carbon model. Biogeosciences 17, 5861-5882, https://doi.org/10.5194/bg-17-5861-2020.
Yi, Y., J.S. Kimball, R.H. Chen, M. Moghaddam, and C.E. Miller, 2019. Sensitivity of active layer freezing process to snow cover in Arctic Alaska. The Cryosphere, 13, 197-218.
Mike Rawlins (UMASS)
Peter Kirchner (USNPS AK)
Yonghong Yi (JPL)
Youngwook Kim (UAE Univ.)
Hotaek Park (JAMSTEC)
Chris Derksen (Environment Canada)