Friday, June 6, 2014
High, Dry, and Free of Snow…
Two years ago the NGEE Arctic team established our research sites on the Barrow Environmental Observatory (BEO). We designed our studies around geomorphological features including thaw lakes, drained thaw lake basins, and polygons of which there are three types; low-, flat-, and high-centered polygons. The various types of polygons are of interest to our team because they have what we believe to be marked differences in CO2 and CH4 flux, temperature, and hydrology. Scientists on our team are gathering data and developing models to test this possibility and will then use those models to examine what a change from low- to high-centered polygons due to permafrost thaw might mean to carbon cycle and energy balance processes over the next century.
We have already made great strides in addressing how landscape evolution and the thaw lake cycle will potentially impact CO2 and CH4 fluxes, with an eye towards getting this information into high-resolution climate models. It has been interesting this week to walk the BEO and, when time permits, to consider how snowmelt and associated processes might differ across the polygons that we are studying. What I have observed is that the tops of the high-centered polygons do not have very deep layers of snow and the snow that accumulates on them during the long winter seems to melt first before melting on any of the other features in the landscape.
Scientists including Margaret Torn, Bryan Curtis, Melanie Hahn, and others have not yet summarized all of their chamber-based measurements of CO2 and CH4 flux from previous years at this point, so I cannot be overly quantitative about this observation. However, looking at our field sites, especially those in and among high-centered polygons, I can imagine that the growing season is longer, soils are warmer, albeit possibly dryer, and thus environmental conditions may result in different rates and seasonal magnitudes of CO2 and CH4 flux from these features. If so, then we need to incorporate this fine-scale information into our models.