ESA Web Story – 25/05/2022

For the first time ever recorded, in the late summer of 2021, rain fell on the high central region of the Greenland ice sheet. This extraordinary event was followed by the surface snow and ice melting rapidly. Researchers now understand exactly what went on in those fateful summer days and what we can learn from it.

The never-before-seen rainfall, on 14 August 2021, made headlines around the world. The upper-most parts of Greenland’s enormous ice cap used to be too cold for anything other than snow to fall, but not anymore.

What caused this extreme rainfall and how did it affect the ice?

Researchers from the Department of Glaciology and Climate at the Geological Survey of Denmark and Greenland (GEUS) in collaboration with colleagues from France and Switzerland have scrutinised these questions and come up with the answers.

It didn’t only rain at Summit Camp – rain was measured by new automatic weather stations placed across the ice sheet by GEUS’ ice-sheet monitoring projects PROMICE and GC-Net.

Studying detailed data from these stations alongside measurements of surface reflectivity, or albedo, from the Copernicus Sentinel-3 satellite mission and information on atmospheric circulation patterns, the researchers discovered that the rain had been preceded by a heatwave at a time of year when seasonal melting is usually slowing down.

red more at the ESA Web Story

Box, J.E., D. van As, K. Steffen, 2017. Greenland, Canadian and Icelandic land ice albedo grids (2000-2016), Geological Survey of Denmark and Greenland Bulletin, 38, 53-56. http://www.geus.dk/DK/publications/geol-survey-dk-gl-bull/38/Documents/nr38_p53-56.pdf

Hall, D. K., G. A. Riggs, and V.V. Salomonson (1995). Development of Methods for Mapping Global Snow Cover Using Moderate Resolution Imaging Spectroradiometer Data. Remote Sensing of Environment, 54(2), 127-140.

Hall, D. K., Riggs, G. A., and Salomonson, V. V.: MODIS/Terra Snow Cover Daily L3 Global 500m Grid V004, January to March 2003, Digital media, updated daily. National Snow and Ice Data Center, Boulder, CO, USA, 2011.

Hall, D. K. and G. A. Riggs. 2016. MODIS/Terra Snow Cover Daily L3 Global 500m Grid, Version 6. Greenland coverage. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. doi: http://dx.doi.org/10.5067/MODIS/MOD10A1.006. Accessed December, 2016.

Lyapustin, A., et al. (2014), Science impact of MODIS C5 calibration degradation and C6+ improvements, Atmos. Meas. Tech. Discuss., 7, 7281–7319.

Riggs, G.A. and D.K. Hall. 2015. MODIS Snow Products Collection 6 User Guide, 11 December 2015 https://nsidc.org/sites/nsidc.org/files/files/MODIS-snow-user-guide-C6.pdf

Stroeve, J.: Assessment of Greenland albedo variability from the advanced very high resolution radiometer Polar Pathfinder data set, J. Geophys. Res.-Atmos., 106, 33989–34006, doi:10.1029/2001jd900072, 2001.

Stroeve, J.C., Box, J.E., Haran, T., 2006: Evaluation of the MODIS (MOD10A1) daily snow albedo product over the Greenland ice sheet, Remote Sensing of Environment, 105(2), 155-171 doi:10.1016/j.rse.2006.06.009

Stroeve, J.C., J.E. Box, Z. Wang, C. Schaaf, A. Barrett. 2013. Re-evaluation of MODIS MCD43 Greenland albedo accuracy and trends, Remote Sensing of Environment, 138, 199–214. doi:10.1016/j.rse.2013.07.023

• The workshop starts Wednesday Sep 20 at 12.00, and ends Friday Sep 22 at 12.00.
• A PROMICE 10-year jubilee and reception is planned for the afternoon of Sep 22.

Purpose

• to present and discuss results on modeling of meltwater retention processes in snow and firn on ice sheets and glaciers;
• to plan and coordinate meltwater retention model development;
• to emphasize optical remote sensing snow parameter data comparison and data assimilation;
• to formulate a protocol for a meltwater retention model intercomparison project (RetMIP)

This is workshop two as part of Danish Council for Independent Research (DFF) Natural Sciences program (FNU) project 4002-00234: Understanding and predicting non-linear change in the permeability of Greenland firn and has a special session co-sponsored by the ESA Scientific Exploitation of Operational Missions (SEOM) Sentinel-3 for Science, Land Study 1: SNOW.

1. Snow model development
2. Meltwater retention model validation
3. Meltwater retention model intercomparison project (RetMIP)
4. Optical remote sensing to improve snow models

Session 1 welcomes, for example, model considerations of water availability vs. percolation rate vs. refreezing rate to explore the importance of heterogeneous percolation modelling in polar firn; fine-and-local scale/detailed modeling with possible suggestions to including bulk effects in larger-scale models; inclusion of piping (for instance, by “skipping layers” during percolation) in distributed or single-column models; inclusion of horizontal water motion in snow and firn, i.e. between grid cells.

Session 2 will focus on discussions of useful model validation metrics and aim to compile observational datasets that may be used to validate the above processes.

• survey and prioritize remotely sensed snow parameter data users’ requirements for global and regional snow information
• discuss how to enhance methods for estimating snow parameters, either from remote sensing or from modeling, and to evaluate advantages and disadvantages of the different approaches
• consult users about the utility/interest in other snow products suitable for studying climate-related issues.

• a protocol for a retention model intercomparison project (RetMIP) including instructions and datasets for validation.
• a list of requirements and minimum accuracy levels for models using optical remotely sensed snow parameter data
• a journal special issue like the 2016 special issue in Frontiers in Earth Science – Melt Water Retention Processes in Snow and Firn on Ice Sheets and Glaciers: Observations and Modeling, papers feeding into the IPCC Special Report on Climate change and the oceans and the cryosphere.

The S3 4Sci Snow research project is gaining momentum, now with scripts that enable batch processing of two important steps: 1.) collocating OLCI and SLSTR imagery, that is, aligning pixels to a common geographic grid and 2.) converting the imagery to top of the atmosphere reflectance.

(above, 22 August 2016 southern Greenland Sentinel-3 scene of TOA reflectance from OLCI band 21, 1020 nm). In this part of the optical spectrum we find strong reflectance differences between fresh snow cover, melting snow and bare ice (dark areas).

The processing chain the project follows is illustrated below. The collocation happens as OLCI and SLSTR radiances are combined.

This project is about monitoring snow properties evolution on the long-term using Sentinel satellite series at global scale. The successful candidates will evaluate and develop retrieval algorithms. The project will more specifically focus on two primary sites, one in Canada and the other one in the French Alps. Secondary sites including Greenland and Antarctica will be exploited for the validation.

Research project

Optical sensors on Sentinel-2 (MSI) and Sentinel-3 (OLCI and SLSTR) provide a new and unique opportunity to investigate the temporal and spatial variability of the snow cover properties at high spatial resolution and on the long-term. The objective of this post-doctoral position is to 1) evaluate global moderate-resolution algorithms for snow cover properties retrieval (snow cover fraction, spectral and broadband albedo, snow specific surface area – SSA and light absorbing impurity content) from S-3 images developed by other parties and 2) develop and evaluate high- resolution algorithms adapted to complex terrains from S-2. The second objective is interesting by itself and will also provide validation data for the first objective on specific sites.

The general evaluation will use data from many sites around the world where in-situ observations are available (Alps, Arctic, EGRIP in Greenland, Dome C in Antarctica, …). The second objective will be especially focused at 2 locations :

• Umijaq area in Canadian Arctic where the interest is on monitoring snow-vegetation interactions in relationship with climate change, greening and permafrost evolution.
• Col du Lautaret in the French Alps which features complex terrain and potential high human impact. The interest is in following the evolution of snow impurities and induced changes in snow physics at the site which is largely impacted by Saharan dust deposition events as well as providing data for snow-vegetation interaction.

These two sites have been equipped with specific instrumentation dedicated to snow monitoring (including in situ spectral reflectance measurements, SSA and light absorbing impurities measurements).

The work plan includes :

• Adapting atmospheric and topographic corrections existing algorithms to S-2 and S-3 images (MODINLAB by Sirguey et al., 2009 ; Dumont et al., 2012)
• Developing snow cover fraction, snow SSA, light absorbing impurities content, snow spectral and broadband albedo based on methodology for S2 proposed in Dumont et al., 2012 ; Kokhanovsky and Zege, 2004, Malinka, 2014 and Picard et al., 2016.
• Participating in field measurements campaigns at Col du Lautaret, Umijaq and possibly EGRIP.
• Evaluate the accuracy of the proposed algorithms at the two sites
• Evaluate the accuracy of available moderate-resolution algorithms at the two sites and at other sites where in-situ data are available.
• Investigate the temporal and spatial variability of the snow cover properties for theses locations in relationship to the specific scientific objectives.

Within this project, special attention will be drawn to the effect of terrain complexity on the accuracy of the surface reflectance and the effect of snow surface roughness on retrieved surface reflectance and snow properties.

Progresses and results shall be documented in project reports. As part of the scientific dissemination it is also expected that the postdoc present results in scientific journals and at international conferences.

This work will contribute to two projects; one funded by the European Space Agency (PI Jason Box, GEUS, Danemark) and the other one by the BNP Paribas fundation (PI Florent Dominé, Takuvik, U. Laval, Canada). The position is based in Grenoble, a place known for its excellence in snow science, but also implies strong international collaborations with colleagues in Canada, Germany and Denmark.

Position summary

Full-time temporary employment. The position is funded for 24 months from January 2017 to December 2018.

Qualifications

To qualify as a candidate for the postdoc position you must have a Ph.D. degree with strength in remote sensing, snow optics and physics or related disciplines and you must have a solid theoretical background in mathematics, physics, statistical analysis and programming. A genuine interest and curiosity in the field measurements campaigns and excellent programming skills (e.g. python) are needed. Experience in processing and analysis of data from satellites, in situ measurements or snow models is regarded as an advantage for the position. The position requires good verbal and written communication skills in English, as most of the work will take place in an international environment. An initial scientific publication record is expected.

Contacts

Ghislain Picard (ghislain.picard@univ-grenoble-alpes.fr)

Marie Dumont (marie.dumont@meteo.fr)

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