Assimilation of Sentinel-2 Data into a Snowpack Model in the High Atlas of Morocco
The snow melt from the High Atlas is a critical water resource in Morocco. In spite of its importance, monitoring the spatio-temporal evolution of key snow cover properties like the snow water equivalent remains challenging due to the lack of in situ measurements at high elevation. Since 2015, the S...
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doaj-84343bbda81e4744a67e9da4d06fe3c62020-11-24T21:22:39ZengMDPI AGRemote Sensing2072-42922018-12-011012198210.3390/rs10121982rs10121982Assimilation of Sentinel-2 Data into a Snowpack Model in the High Atlas of MoroccoMohamed Wassim Baba0Simon Gascoin1Lahoucine Hanich2Centre d’Etudes Spatiales de la Biosphère, Université de Toulouse, CNRS/CNES/IRD/INRA/UPS, 18 av. E. Belin bpi 2801, 31401 Toulouse, FranceCentre d’Etudes Spatiales de la Biosphère, Université de Toulouse, CNRS/CNES/IRD/INRA/UPS, 18 av. E. Belin bpi 2801, 31401 Toulouse, FranceLaboratoire Géoressources-Département des Sciences de la Terre, Faculté des Sciences et Techniques Guéliz, Université Cadi Ayyad, av. A. Khattabi, BP 549, Marrakech 40000, MoroccoThe snow melt from the High Atlas is a critical water resource in Morocco. In spite of its importance, monitoring the spatio-temporal evolution of key snow cover properties like the snow water equivalent remains challenging due to the lack of in situ measurements at high elevation. Since 2015, the Sentinel-2 mission provides high spatial resolution images with a 5 day revisit time, which offers new opportunities to characterize snow cover distribution in mountain regions. Here we present a new data assimilation scheme to estimate the state of the snowpack without in situ data. The model was forced using MERRA-2 data and a particle filter was developed to dynamically reduce the biases in temperature and precipitation using Sentinel-2 observations of the snow cover area. The assimilation scheme was implemented using SnowModel, a distributed energy-balance snowpack model and tested in a pilot catchment in the High Atlas. The study period covers 2015⁻2016 snow season which corresponds to the first operational year of Sentinel-2A, therefore the full revisit capacity was not yet achieved. Yet, we show that the data assimilation led to a better agreement with independent observations of the snow height at an automatic weather station and the snow cover extent from MODIS. The performance of the data assimilation scheme should benefit from the continuous improvements of MERRA-2 reanalysis and the full revisit capacity of Sentinel-2.https://www.mdpi.com/2072-4292/10/12/1982snowsemi-arid climatedata assimilationparticle filterSWEMERRA-2 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Mohamed Wassim Baba Simon Gascoin Lahoucine Hanich |
spellingShingle |
Mohamed Wassim Baba Simon Gascoin Lahoucine Hanich Assimilation of Sentinel-2 Data into a Snowpack Model in the High Atlas of Morocco Remote Sensing snow semi-arid climate data assimilation particle filter SWE MERRA-2 |
author_facet |
Mohamed Wassim Baba Simon Gascoin Lahoucine Hanich |
author_sort |
Mohamed Wassim Baba |
title |
Assimilation of Sentinel-2 Data into a Snowpack Model in the High Atlas of Morocco |
title_short |
Assimilation of Sentinel-2 Data into a Snowpack Model in the High Atlas of Morocco |
title_full |
Assimilation of Sentinel-2 Data into a Snowpack Model in the High Atlas of Morocco |
title_fullStr |
Assimilation of Sentinel-2 Data into a Snowpack Model in the High Atlas of Morocco |
title_full_unstemmed |
Assimilation of Sentinel-2 Data into a Snowpack Model in the High Atlas of Morocco |
title_sort |
assimilation of sentinel-2 data into a snowpack model in the high atlas of morocco |
publisher |
MDPI AG |
series |
Remote Sensing |
issn |
2072-4292 |
publishDate |
2018-12-01 |
description |
The snow melt from the High Atlas is a critical water resource in Morocco. In spite of its importance, monitoring the spatio-temporal evolution of key snow cover properties like the snow water equivalent remains challenging due to the lack of in situ measurements at high elevation. Since 2015, the Sentinel-2 mission provides high spatial resolution images with a 5 day revisit time, which offers new opportunities to characterize snow cover distribution in mountain regions. Here we present a new data assimilation scheme to estimate the state of the snowpack without in situ data. The model was forced using MERRA-2 data and a particle filter was developed to dynamically reduce the biases in temperature and precipitation using Sentinel-2 observations of the snow cover area. The assimilation scheme was implemented using SnowModel, a distributed energy-balance snowpack model and tested in a pilot catchment in the High Atlas. The study period covers 2015⁻2016 snow season which corresponds to the first operational year of Sentinel-2A, therefore the full revisit capacity was not yet achieved. Yet, we show that the data assimilation led to a better agreement with independent observations of the snow height at an automatic weather station and the snow cover extent from MODIS. The performance of the data assimilation scheme should benefit from the continuous improvements of MERRA-2 reanalysis and the full revisit capacity of Sentinel-2. |
topic |
snow semi-arid climate data assimilation particle filter SWE MERRA-2 |
url |
https://www.mdpi.com/2072-4292/10/12/1982 |
work_keys_str_mv |
AT mohamedwassimbaba assimilationofsentinel2dataintoasnowpackmodelinthehighatlasofmorocco AT simongascoin assimilationofsentinel2dataintoasnowpackmodelinthehighatlasofmorocco AT lahoucinehanich assimilationofsentinel2dataintoasnowpackmodelinthehighatlasofmorocco |
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1725994698126917632 |