Rain-on-snow events in Alaska, their frequency and distribution from satellite observations

Abstract

Wet snow and the icing events that frequently follow wintertime rain-on-snow (ROS) affect high latitude ecosystems at multiple spatial and temporal scales, including hydrology, carbon cycle, wildlife, and human development. However, the distribution of ROS events and their response to climatic changes are uncertain. In this study, we quantified ROS spatiotemporal variability across Alaska during the cold season (November to March) and clarified the influence of precipitation and temperature variations on these patterns. A satellite-based daily ROS geospatial classification was derived for the region by combining remote sensing information from overlapping MODIS and AMSR sensor records. The ROS record extended over the recent satellite record (water years 2003-2011 and 2013-2016) and was derived at a daily time step and 6 km grid, benefiting from finer (500 m) resolution MODIS snow cover observations and coarser (12.5 km) AMSR microwave brightness temperature-based freeze-thaw retrievals. The classification showed favorable ROS detection accuracy (75%-100%) against in situ climate observations across Alaska. Pixel-wise correlation analysis was used to clarify relationships between the ROS patterns and underlying physiography and climatic influences. Our findings indicate that cold season ROS events are most common during autumn and spring months along the maritime Bering Sea coast and boreal interior regions, but are infrequent on the colder arctic North Slope. The frequency and extent of ROS events coincided with warm temperature anomalies (p < 0.1), but showed a generally weaker relationship with precipitation. The weaker precipitation relationship was attributed to several factors, including large uncertainty in cold season precipitation measurements, and the important contribution of humidity and turbulent energy transfer in driving snowmelt and icing events independent of rainfall. Our results suggest that as high latitude temperatures increase, wet snow and ROS events will also increase in frequency and extent, particularly in the southwestern and interior regions of Alaska.

Tactical departures and strategic arrivals: Divergent effects of climate and weather on caribou spring migrations

“…A better understanding of the factors that influence snow quality with respect to caribou mobility would be gained via improved snow property observations of improved modeling of snow quality from remote sensing (Pan et al. , Boelman et al. ).…”

“…Warmer temperatures and increased winds may also accelerate onset of snow disappearance as wind affects the rate of snow sublimation, leading to easier foraging or new foraging access on late winter ranges, thereby delaying migrations and further decoupling migration from snow phenology. A better understanding of the factors that influence snow quality with respect to caribou mobility would be gained via improved snow property observations of improved modeling of snow quality from remote sensing (Pan et al 2018, Boelman et al 2019.…”

Quantifying the effects of freeze-thaw transitions and snowpack melt on land surface albedo and energy exchange over Alaska and Western Canada

“…The AMSR-E and AMSR2 T integration is summarized in the supplement (text S1 available at stacks.iop.org/ ERL/13/075009/mmedia). The integrated AMSR-E and AMSR2 (hereafter denoted as AMSR) T time series was processed separately for ascending and descending orbital crossings to produce information on morning (AM), afternoon (PM) and composite daily FT conditions using a modified seasonal threshold algorithm (MSTA; Kim et al 2017a, Kim et al 2018). A detailed summary of the MSTA approach, and the resulting FT product accuracy and performance is provided in the supplement (text S2).…”

“…Alternatively, satellite microwave radiometers can detect FT and snow-cover properties with limited impact from these effects, while still providing consistent daily land surface observations, albeit at relatively coarse spatial resolution as compared with optical-IR sensors. Recent studies have utilized satellite multisensor data fusion techniques to provide enhanced information on snow-cover properties with reduced constraints relative to single sensor retrievals (Kim et al 2015, Pan et al 2018, Zhu et al 2017.…”

Role of Surface Melt and Icing Events in Livestock Mortality across Mongolia’s Semi-Arid Landscape

“…Few scientific efforts have examined the role and spatiotemporal heterogeneity of the tumer dzud, defined as a significant snowmelt and subsequent icing event purported to be a major driver of livestock mortality in Mongolia [11]. Much less is known regarding the frequency and regional extent of the tumer dzud due to challenges in detecting such events [14,15]. Moreover, as Mongolia's annual temperatures are warming at roughly twice the global average rate [5] and wintertime temperatures are also increasing [16], wintertime snowmelt events [17] and the tumer dzud may become more common, leading to potentially greater risk of livestock die-offs within Mongolia.…”