With Prof. Claude Duguay, we are funded to procure a Ku- and X-Band scatterometer system to measure the backscatter from snow. This work is part of the sceince disocry research for the CoReH2O mission a seasonal snow cover and accumulatio mapping mission designed for unpreceneted spatial resolution observations.
The project has deployed the system in Churchill Manitoba during the 2009-2010 and 2010-2011 winter seasons. We are be observing the seasonal evolution of the snowpack and are conducting detailed scientific experiments of snow and lake ice dynamics.
The equipment for this project forms part of our Cryospheric Remote Sensing Laboratory that we are developing.
This project is concerned with the application of web-based digital technologies to map snow depth through community participation. In other words, we have set up an environment to enable people to 'tweet' snow depth measurements which we map.
Costly snow depth information from environmental agencies has been declining for many years and one way to augment this information is through community involvement in measuring meteorological and hydrological variables. This project aims to do so in a simple way through using widely used web-based services to communicate local measurements of snow depth to our web server. Using the Twitter system, we are able to map 'tweeted' variables in almost ner real time.
If you want to participate, please follow the link to the Snowtweets.org web pages.Funding: NSERC
As the PI for JAXA's standard snow depth and snow accumulation product from the Advanced Microwave Scanning Radiometer - 2 (AMSR2) aboard the GCOM-W1 mission, we are involved with estimating snow water equivalent (SWE) from satellite passive microwave observations at the regional to global scale.
This project aims to investigate the response of pan-Arctic vegetation to recent climate change in Arctic regions (N of 60N). Arctic vegetation contains up to a third of the world's carbon store and is predicted to undergo the greatest changes under global warming.
Current understanding of the Arctic's role in carbon cycling is limited; no studies to date have examined the response of pan-Arctic vegetation to climate change using two established vegetation response variables: productivity (rate of net carbon uptake) and phenology (timing of seasonal biological changes). This project is examining historical (1982-2000) records of productivity and phenology from remote sensing data (MODIS/AVHRR/Landsat) and modelling products (GIMMS and GloPEM).