Difference between revisions of "Snow Extent Variability in Lesotho Derived from MODIS Data"
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'''Abstract''' | '''Abstract''' | ||
| − | In Lesotho, snow cover is not only highly relevant to the climate system, but also affects socio-economic factors such as water storage for | + | In Lesotho, snow cover is not only highly relevant to the climate system, but also affects socio-economic factors such as water storage for irrigation or hydro-electricity. However, while sound knowledge of annual and inter-annual snow dynamics is strongly required by local |
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| − | irrigation or hydro-electricity. However, while sound knowledge of annual and inter-annual snow dynamics is strongly required by local | + | |
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stakeholders, in-situ snow information remains limited. In this study, satellite data are used to generate a time series of snow cover and to | stakeholders, in-situ snow information remains limited. In this study, satellite data are used to generate a time series of snow cover and to | ||
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provide the missing information on a national scale. A snow retrieval method, which is based on MODIS data and considers the concept of a | provide the missing information on a national scale. A snow retrieval method, which is based on MODIS data and considers the concept of a | ||
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normalized difference snow index (NDSI), has been implemented. Monitoring gaps due to cloud cover are filled by temporal and spatial | normalized difference snow index (NDSI), has been implemented. Monitoring gaps due to cloud cover are filled by temporal and spatial | ||
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post-processing. The comparison is based on the use of clear sky reference images from Landsat-TM and ENVISAT-MERIS. While the snow product is | post-processing. The comparison is based on the use of clear sky reference images from Landsat-TM and ENVISAT-MERIS. While the snow product is | ||
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considered to be of good quality (mean accuracy: 68%), a slight bias towards snow underestimation is observed. Based on the daily product, a | considered to be of good quality (mean accuracy: 68%), a slight bias towards snow underestimation is observed. Based on the daily product, a | ||
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consistent time series of snow cover for Lesotho from 2000–2014 was generated for the first time. Analysis of the time series showed that the | consistent time series of snow cover for Lesotho from 2000–2014 was generated for the first time. Analysis of the time series showed that the | ||
| − | + | high annual variability of snow coverage and the short duration of single snow events require daily monitoring with a gap-filling procedure. | |
| − | high annual variability of snow coverage and the short duration of single snow events require daily monitoring with a gap-filling procedure. | + | |
Revision as of 07:22, 2 May 2017
by: Stefan Wunderle, Timm Gross and Fabia Husler
Abstract
In Lesotho, snow cover is not only highly relevant to the climate system, but also affects socio-economic factors such as water storage for irrigation or hydro-electricity. However, while sound knowledge of annual and inter-annual snow dynamics is strongly required by local stakeholders, in-situ snow information remains limited. In this study, satellite data are used to generate a time series of snow cover and to provide the missing information on a national scale. A snow retrieval method, which is based on MODIS data and considers the concept of a normalized difference snow index (NDSI), has been implemented. Monitoring gaps due to cloud cover are filled by temporal and spatial post-processing. The comparison is based on the use of clear sky reference images from Landsat-TM and ENVISAT-MERIS. While the snow product is considered to be of good quality (mean accuracy: 68%), a slight bias towards snow underestimation is observed. Based on the daily product, a consistent time series of snow cover for Lesotho from 2000–2014 was generated for the first time. Analysis of the time series showed that the high annual variability of snow coverage and the short duration of single snow events require daily monitoring with a gap-filling procedure.
Keywords: snow cover; MODIS; NDSI; Lesotho; temporal and spatial gap-filling
Link to website: http://www.mdpi.com/2072-4292/8/6/448
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