Snow on Arctic Sea Ice Impacts Climate Data Records from Passive Microwave Satellites

Arctic sea ice is on a rapid decline (Stroeve & Notz, 2018). Sea ice loss has adversely affected the global climate, marine ecosystem and livelihood of coastal communities. Climate Data Records (CDRs) of sea ice concentration from passive microwave satellite measurements show this decline with older, fresher and thicker multi-year sea ice (MYI) replaced by younger, saline and thinner first-year sea ice (FYI). However, it is unclear how fresh snow on MYI and saline snow on FYI (Nandan et al., 2017) affects sea ice concentration uncertainty and stability of CDRs. This is because passive microwave emission signatures from fresher and saline snow and sea ice types are contrasting, but its implication on ice concentration estimates from passive microwave satellites has never been investigated.

In the context of the OSI SAF Visiting Scientist Program, a recent activity led by Drs. Vishnu Nandan (University of Manitoba) and Rasmus Tonboe (Danish Meteorological Institute) simulated the impact of snow salinity on modeled and observed sea ice concentration estimates, derived from AMSR-E passive microwave satellite. They used an advanced Microwave Emission Model of Layered Snowpacks (MEMLS) (Wiesmann and Mätzler, 1999) with a sea ice extension (Tonboe et al., 2006) modeling framework for this purpose. The MEMLS framework assimilated large volumes of in situ measured snow and sea ice property measurements on FYI and MYI, collected since early 90s. Satellite observations consisted of derived brightness temperatures from AMSR-E data, acquired during the winter season of 2015.

Their semi-empirical research demonstrates that saline snow on FYI has a shallower emitting layer than MYI, and is strongly sensitive to changes in snow temperature. The impact is greater when the snow is warm and saline on FYI, where passive microwave energy originates from the air/snow interface, as compared to snow/sea ice interface from colder and fresher snow on MYI. The model simulations also indicate the potential of their approach to explain the geophysical variations along the ice line, as a function of snow salinity and temperature (see Figure on top).

In a warming Arctic, FYI is well-poised to be the dominant ice type with saline and warmer snow. This would lead to different sea ice concentration uncertainties from existing algorithms. It is highly recommended to tune these uncertainty algorithms, accounting for snow salinity/ ice type, in turn improving the CDRs from passive microwave satellite data.

Dr. Vishnu Nandan is working with Prof. Julienne Stroeve (Senior Canada-150 Research Chair) as a postdoctoral researcher at the Centre for Earth Observation Science (CEOS) at the University of Manitoba, Canada.

Dr. Rasmus Tonboe is a senior research scientist, previously at the Danish Meteorological Institute, Copenhagen, now working at the Danish Technical University, Copenhagen.

Report on this study

What happened to sea ice concentration uncertainties and CDR stability when multiyear ice in the Arctic Ocean was replaced by first-year ice in winter?

References

Stroeve, J., & Notz, D. (2018). Changing state of Arctic sea ice across all seasons. Environmental Research Letters, 13(10), 103001.

Nandan, V., Geldsetzer, T., Yackel, J., Mahmud, M., Scharien, R., Howell, S., ... & Else, B. (2017). Effect of snow salinity on CryoSat‐2 Arctic first‐year sea ice freeboard measurements. Geophysical Research Letters, 44(20), 10-419.

Andreas Wiesmann and Christian Mätzler, 1999: Microwave Emission Model of Layered Snowpacks. Remote. Sens. Environ. 70:307-316.

Tonboe, R., S. Andersen, L. Toudal & G. Heygster. Sea ice emission modelling. In: Mätzler, C., P.W. Rosenkranz, A. Battaglia and J.P. Wigneron (eds.), "Thermal Microwave Radiation - Applications for Remote Sensing", IET Electromagnetic Waves Series 52, London, UK, 2006.