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Dr Melody Sandells

Associate Professor

Department: Geography and Environmental Sciences

I am interested in how we can use principles of physics to interpret changes in the cryosphere. My current research uses computer simulations of microwave scattering in snow to understand remote sensing observations, either from ground-based sensors, airborne or satellite. My background is in snowpack modelling though, so I'm always looking for ways to use the outputs from snow evolution models (e.g. temperature, density and snow microstructure) to simulate microwave scattering.

Snow is a fascinating material as it continually evolves - the structure changes depending on the temperature and water vapour conditions around and within it. We can see the changes in the satellite signals too. It's exciting when the models match up with what we expect and possibly even more exciting when they don't!

Melody Sandells

Since 2015 I have been involved in the development and evaluation of the Snow Microwave Radiative Transfer (SMRT) Model (Picard, Sandells and Löwe, 2018). This is a modular model that simulations microwave behaviour in snow, land ice and sea ice can be applied to interpret passive, active and altimetry remote sensing observations. One interesting aspect is how we measure snow microstructure and use that information in SMRT.

Projects I'm currently involved in are:

  • AKROSS: evaluation of SMRT in altimetry mode with fieldwork in Eureka, Canada to understand how snow affects retrievals of sea ice thickness
  • AESOP: potential use of SMRT to remove influence of snow on satellite observations used in numerical weather prediction
  • SCANSAS: dual active-passive evaluation of SMRT with new data from the Swiss Alps.

  • Please visit the Pure Research Information Portal for further information
  • SMRT: an active–passive microwave radiative transfer modelfor snow with multiple microstructure and scatteringformulations (v1.0), Picard, G., Sandells, M., Löwe, H. Jul 2018, In: Geoscientific Model Development
  • Snow Ensemble Uncertainty Project (SEUP): quantification of snow water equivalent uncertainty across North America via ensemble land surface modeling, Kim, R., Kumar, S., Vuyovich, C., Houser, P., Lundquist, J., Mudryk, L., Durand, M., Kim, E., Barros, A., Forman, B., Gutmann, E., Wrzesien, M., Garnaud, C., Sandells, M., Marshall, H., Cristea, N., Pflug, J., Johnston, J., Cao, Y., Mocko, D., Wang, S. 17 Feb 2021, In: The Cryosphere
  • Derivation and Evaluation of a New Extinction Coefficient for use with the n-HUT Snow Emission Model, Maslanka, W., Sandells, M., Gurney, R., Lemmetyinen, J., Leppänen, L., Kontu, A., Matzl, M., Rutter, N., Watts, T., Kelly, R. 1 Oct 2019, In: IEEE Transactions on Geoscience and Remote Sensing
  • Differences Between the HUT Snow Emission Model and MEMLS and Their Effects on Brightness Temperature Simulation, Pan, J., Durand, M., Sandells, M., Lemmetyinen, J., Kim, E., Pulliainen, J., Kontu, A., Derksen, C. Apr 2016, In: IEEE Transactions on Geoscience and Remote Sensing

Harry Clayton 'Remote Sensing of Snow for Improvement of Weather Forecasts' Start Date: 01/10/2021 End Date: 07/08/2022

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