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Filhol, Simon; Vasile, Mirela; Sîrbu, Flavius; Onaca, Alexandru; Etzelmüller, Bernd & Westermann, Sebastian
(2023).
Climate Downscaling in the Southern Carpathians for Climate Analysis and Permafrost Conditions Change (1950-2020).
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Filhol, Simon; Larose, Catherine; Hulth, John; Lefeuvre, Pierre-Marie; Czyz, Ceslav & Gallet, Jean-Charles
[Show all 8 contributors for this article]
(2023).
Gruvebadet, a suite of sensors towards completing blowing snow mass balance.
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Filhol, Simon; Lefeuvre, Pierre-Marie; Burkhart, John Faulkner; Schuler, Thomas Vikhamar; Gallet, Jean-Charles & Hulth, John
[Show all 7 contributors for this article]
(2023).
Development and Deployment of Wireless Sensor Networks on Arctic Glaciers.
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Filhol, Simon
(2023).
Finse Research Station.
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Alexander, Andreas; Piermattei, Livia; Assmy, Philipp Kurt Wolf; Popp, Andrea; Valiente, Nicolás & Tallentire, Guy
[Show all 19 contributors for this article]
(2023).
The impact of subglacial drainage system evolution and glacier lake outburst on Arctic fjord macronutrient dynamics: Kongsfjorden, Svalbard.
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Yilmaz, Yeliz A.; Aalstad, Kristoffer; Filhol, Simon; Gascoin, Simon; Pirk, Norbert & Remmers, Janneke
[Show all 8 contributors for this article]
(2022).
Evaluating modeled snow cover dynamics over Fennoscandia using Earth observations and reanalyses
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Yilmaz, Yeliz A.; Aalstad, Kristoffer; Filhol, Simon; Gascoin, Simon; Pirk, Norbert & Remmers, Janneke
[Show all 8 contributors for this article]
(2022).
Evaluating modeled snow cover dynamics over Fennoscandia using Earth observations.
Show summary
The snow cover is an essential part of the climate system in cold regions through its effects on the terrestrial water, energy, and carbon balance. Due to the high spatiotemporal variability of snow, it is challenging to resolve snow cover dynamics in models. Thus, our ability to improve the representation of these dynamics in Earth System Models (ESMs) leans heavily on the accuracy and representativeness of the observational data sets used for model evaluation.
The big picture provided by the long-term climate data record from satellites helps us to monitor changes in land cover over large areas. At the same time, rapidly developing drone and terrestrial imaging technology provides higher resolution information over specific areas. This complimentary information from spaceborne, airborne, and terrestrial Earth observations is invaluable for better understanding the complex processes in the climate system. In our work, we are currently exploiting estimates of snow-covered area from different optical sensors onboard polar orbiting satellites that are imaging the Nordic region. Drone and terrestrial images are being explored as a source of validation and calibration data for the satellite products.
Having representative snow cover maps enables us to better evaluate the terrestrial component of the Norwegian Earth System Model (NorESM), namely the Community Land Model (CLM5). With a focus on snow processes, we are conducting an analysis using satellite-based estimates of snow-covered area (MODIS, Sentinel-2, and Landsat 8), snow simulations from CLM5, snow variables from several climate reanalyses (ERA5, ERA5-Land, and MERRA-2), and in-situ data from eddy covariance stations (LATICE flux sites). Two offline CLM5 simulations are conducted with different atmospheric forcing, namely the default data set (GSWP3) and ERA5. We are investigating trends in the snow cover phenology, which we characterize using snow cover duration, first and last days of the snow cover, and consecutive snow cover days for each snow season over the last two decades. This work illuminates a path to integrate Earth observations with Earth system modeling in cold environments to both identify and constrain sources of uncertainty.
Acknowledgement: This ongoing study is supported by the LATICE (Land-ATmosphere Interactions in Cold Environments) strategic research initiative funded by the University of Oslo, and the project EMERALD (294948) funded by the Research Council of Norway.
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Yilmaz, Yeliz A.; Aalstad, Kristoffer; Filhol, Simon; Gascoin, Simon; Stordal, Frode & Tallaksen, Lena M.
(2021).
Fennoscandian snow cover dynamics in the MODIS era.
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Yilmaz, Yeliz A.; Aalstad, Kristoffer; Filhol, Simon; Gascoin, Simon; Stordal, Frode & Tallaksen, Lena M.
(2021).
Benchmarking CLM5 snow cover dynamics with MODIS and reanalyses over Fennoscandia
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Yilmaz, Yeliz A.; Aalstad, Kristoffer; Filhol, Simon Vincent P; Stordal, Frode & Tallaksen, Lena M.
(2020).
The Representation of the Fennoscandian Snow Cover Phenology in Reanalyses and CLM5 during the MODIS-era.
Show summary
Snow plays an important role in cold regions through its effect on the terrestrial exchange of energy, water, and carbon. Accurately simulating snow processes is therefore important in capturing various climate feedbacks in Earth system models. The representation of the subgrid heterogeneity of snow properties (e.g. coverage, depth, density, albedo) are, in addition to accumulation and snowmelt, major sources of uncertainty in the snow modules of land surface schemes. Using multiple data sources is essential to address these uncertainties and to evaluate overall model performance. Unlike in-situ observations, satellite remote sensing products provide unique representative information at the scale of Earth system models. The Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard the Aqua and Terra satellites provide a continuous long-term climate record for the last two decades.
In this study, two daily snow cover data sets from MODIS (MOD10A1 and MYD10A1) were used to retrieve fractional snow-covered area (fSCA) and several snow cover metrics (e.g. snow cover duration, first and last day of snow) over Fennoscandia for the 2001-2020 water years. We use these retrievals to evaluate the fSCA outputs from multiple reanalyses (ERA5-Land, ERA5, and MERRA-2) and the latest version of the Community Land Model (CLM5) which is the land component of the Community Earth System Model (CESM) and the Norwegian Earth System Model (NorESM). In order to test the accuracy of the MODIS data, we employed Sentinel-2 and Landsat 8 satellite retrievals as well as local‐scale measurements around the Finse Eco-Hydrological Observatory (Finse EcHO), a low-alpine site in central Norway. Lastly, we compared the trends in snow cover metrics with terrestrial water storage anomalies obtained from the Gravity Recovery and Climate Experiment (GRACE) to better understand the regional water cycle dynamics over this region. This study provides a useful starting point for integrating Earth observations into Earth system modeling in cold regions to help identify and constrain sources of uncertainty.
Acknowledgement : This study is conducted under the LATICE strategic research initiative funded by the Faculty of Mathematics and Natural Sciences at the University of Oslo, and the EMERALD (project #294948) funded by the Research Council of Norway.
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Yilmaz, Yeliz A.; Aalstad, Kristoffer; Filhol, Simon Vincent P; Stordal, Frode & Tallaksen, Lena M.
(2020).
Fennoscandian snow cover phenology from MODIS, CLM5, and climate reanalyses.
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Filhol, Simon Vincent P
(2019).
In-situ Sensing of Seasonal Snow in High Temporal and High Spatial Resolution with Time-lapse Photogrammetry and Wireless Sensor Network.
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Filhol, Simon Vincent P
(2019).
New Technology for High Spatial and Temporal Resolution in-situ Characterization of Snow and Atmospheric processes.
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Filhol, Simon Vincent P
(2019).
Snow measurements in Svalbard.
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Filhol, Simon Vincent P
(2019).
A Wireless Sensor Network: Status, development, and future.
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Filhol, Simon
(2018).
Snow Science Activities and Instrumentation Development at Finse.
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Filhol, Simon
(2018).
Snow distribution at Finse.
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Filhol, Simon; Thomas, Schuler & Burkhart, John
(2017).
The Morphological evolution of a wind-shaped snow surface during a storm event at Finse, NO.
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Filhol, Simon; Pirk, Norbert; Schuler, Thomas & Burkhart, John
(2017).
The Evolution of a Snow Dune Field.
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Burkhart, John; Decker, Sven; Filhol, Simon; Hulth, John; Nesje, Atle & Schuler, Thomas
[Show all 8 contributors for this article]
(2017).
Development of the Finse Alpine Research Station towards a platform for multi-disciplinary research on Land-Atmosphere Interaction in Cold Environments (LATICE).
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Filhol, Simon; Schuler, Thomas; Burkhart, John; Hulth, John & Decker, Sven
(2017).
A network of instrumentation to keep track of snow distribution at Finse, Norway.
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Filhol, Simon; Pirk, Norbert; Schuler, Thomas & Burkhart, John
(2017).
The morphological evolution of a wind-shaped snow surface during a storm event at Finse, Norway.
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Schuler, Thomas; Tweldebrahn, Aynom Tesfay; Filhol, Simon & Burkhart, John
(2017).
ESCYMO activities and linkage to SnowHow.
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Burkhart, John; Schuler, Thomas; Tallaksen, Lena M.; Filhol, Simon; Hulth, John & Decker, Sven
(2016).
Snow model validation in Norway at the Land
Atmosphere Interaction in Cold Environments
(LATICE) Finse site.
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Filhol, Simon; Burkhart, John; Schuler, Thomas & Hulth, John
(2016).
Capturing snow depth distribution with a low cost and wireless weather station network.
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Filhol, Simon; Burkhart, John; Schuler, Thomas & Hulth, John
(2016).
Weather stations for wind-blown snow at Finse, Norway: A distributed and real-time wireless network of.
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Filhol, Simon; Burkhart, John; Schuler, Thomas & Hulth, John
(2016).
A distributed and real-time wireless network of weather stations for wind-blown snow at Finse, Norway.
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