Topic 4c: Snow Cover Monitoring - Cal/Val With Drones
In this video, Dr Yves Bühler from the WSL Institute for Snow and Avalanche Research SLF in Davos shows the difficult conditions that scientists face when they are taking in-situ measurements of snow cover. He shows us how they use drones to calibrate and validate the measurements that are available from satellites.
In the future, scientists at SLF hope that they will be able to use satellite data – but at the moment comparing between satellite data and localised data is useful to verify the accuracy of measurements regarding snow cover, snow water equivalent and snow depth.
Seasonal snow cover is the largest single component of the cryosphere. It covers 50% of the northern hemisphere’s land surface during winter.
Monitoring seasonal snow cover on land is a crucial and challenging research issue in climate analysis and modelling:
- Snow influences energy, moisture and gas fluxes between the land surface and atmosphere
- Snow has a high albedo and provides a significant feedback effect in a warming climate
- Snow is sensitive to precipitation and temperature fluctuations, so it is a fundamental indicator of climate change
- Snow is a major freshwater source in high- and mid-latitude regions
The ESA Snow_cci project is generating consistent, high quality long-term data sets with the aim of better understanding the role that snow plays in the climate system.
For example, researchers at the Finnish Meteorological Institute and Environment and Climate Change Canada have been working using CCI data to reliably estimate the amount of annual snow mass and changes in snow cover in the northern hemisphere between 1980 and 2018. They found that combining these different observations had provided more accurate information about the amount of snow than ever before. The previous considerable uncertainty of 33% in the amount of snow has decreased to 7.4%.
Measuring snow cover extent
Snow cover extent is specified as an Essential Climate Variable (ECV) by the Global Climate Observing System. Snow cover is sensitive to changes in temperature and precipitation and it affects the albedo of the Earth’s surface.
We can measure snow using optical imaging, because it appears brightly on satellite imagery, and has a high reflectance in comparison with areas that are not covered by snow.
Measuring snow cover extent shows the impact that snow albedo can have on the planet.
The Moderate Resolution Imaging Spectroradiometer (MODIS) is a 36-channel visible to thermal-infrared sensor that measures snow cover. MODIS relies on visible light to measure snow cover, to it cannot collect snow cover data during Arctic winter when there is no daylight.
Measuring snow depth
Satellites are a vital method of measuring snow depth in areas that cannot be easily accessed for in-situ measurements, for example on top of mountains.
ESA uses the Sentinel-1 to observe the surface of the Earth. The satellite emits radar waves, and based on the reflection of the waves, snow depth can be calculated. Ice crystals rotate the signal that is reflected from the satellites, and the more rotated that the waves are, the more snow there is.
Sentinel-1 snow depth retrievals allow for near-real-time monitoring of snow depth at 1km-squared resolution.
Measuring snow water equivalent
Snow stores a significant mass of water. Snow water equivalent describes the amount of water contained within the snowpack, or the depth of water that would be produced if the entire snowpack melted instantly.
Snow water equivalent is based on the amount, depth and density of snow. Information about snow water equivalent is needed in applications such as flood forecasting, controlling the water level of power plant reservoirs, planning for forestry and crop irrigation and as a variable in climate change modelling.
Scientists use a combination of satellite and in-situ data to measure snow water equivalent. They use passive microwave radiometers and ground based-weather station data to measure SWE on a daily, weekly and monthly basis.
Featured Educator:
- Dr Yves Bühler
- Andreas Stoffel
Snow Depth
Snow Cover
SENTINEL 1A
Course topics
The core videos of this course are labelled as topic videos.
We have also provided a range of optional further reading, links, and additional resources to help consolidate your learning. Here is a summary of what is available:
Topic links and resources
In each topic, once you have watched the video and read the accompanying text, you will find the following information:
- Optional Further Reading: These are external links to further reading.
- Featured Images and Animations: Below the text on each video page, you’ll find the featured images and featured animations.
- Interactives: On the 'Interactives' tab on relevent topic pages, you will find a satellite tracking application showing the current location of the satellites, a data viewer from the ESA WEkEO platform, as well as a data viewer, specially created for this course, allowing you to explore a selection of data relevant to the themes and topics in this course. (Please note that due to maintenance, the data viewer is currently unavailable).
Quizzes and comments
- Quizzes: At the end of each week there will be a quizz consisting of around five questions. These will help you consolidate your understanding of new topics, but are not scored. The feedback given with each answer also will also provide you with important information.
Weekly interactive exercises
At the end of each week, we have included a guided exercise, using interactive apps available on other websites, to help you become more familiar with looking at and working with EO datasets. You will be guided through the process of searching for, comparing and drawing conclusions from data relevant to some of the topics covered in that week.
©
©
The microwave interferometric radiometer of the European Space Agency’s Soil Moisture and Ocean Salinity (SMOS) mission measures at a frequency of 1.4 GHz in the L-band.
Snow is a major source for freshwater production and a key player in water resources management.
