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GLOBAL SNOWPACK - Global Snow Cover characteristics derived from medium resolution remote sensing data

Dietz, Andreas and Künzer, Claudia (2016) GLOBAL SNOWPACK - Global Snow Cover characteristics derived from medium resolution remote sensing data. Living Planet Symposium 2016, 9.-13. Mai 2016, Prague, Czech Republic.

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Abstract

Global snow cover is an important environmental parameter, as is influences hydrology, vegetation, radiation balance, and the living space of humans and animals. Snow is an essential source for freshwater in many regions of the world and at the same time, snow cover depends on precipitation and temperature during the snow season. As climate and weather varies, also the amount as well as the onset, duration, and offset of snow cover changes throughout the years. It is important to analyze this variability in order to identify possible trends, but also to predict the impact of the snow cover situation on local freshwater availability, floods, or the influences on vegetation. The Global SnowPack is a set of global snow cover parameters that are suited to perform these analyses. It is based on time series of global, daily snow cover information derived from medium resolution remote sensing data. The aim is to include every possible data source available to offer high quality products for the whole globe which range back until the early 80s. Such a long time series is required in order to derive possible trends from the data. AVHRR, MODIS, MERIS, and the upcoming Sentinel-3 data are only some examples for sensors that are/will be included in the Global SnowPack products. These products consist of the overall snow cover duration per hydrological year (different for Northern and Southern Hemisphere), early season snow cover duration and late season snow cover duration. The processing steps that are performed to derive these products include temporal and spatial interpolation to estimate the snow cover status below clouds, during polar darkness, and during data gaps, as well as a snowline detection which is depending on the topography of an area. Landsat data is used to perform accuracy assessment. The presentation will give a quick overview of how the processing steps are implemented before some examples are given on how the Global SnowPack datasets look like and what they can be used for. The locations of these examples will be situated in Central Asia, Western USA, and Europe. In Central Asia, snow cover changes have severe impacts on the local hydrology and the freshwater availability; in the Western USA, California has experienced several snow cover seasons with extraordinary low snow cover durations; in Europe, the snow cover characteristics are highly variable between the years and show no distinct trend in any direction.

Item URL in elib:https://elib.dlr.de/110455/
Document Type:Conference or Workshop Item (Poster)
Title:GLOBAL SNOWPACK - Global Snow Cover characteristics derived from medium resolution remote sensing data
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Dietz, Andreasandreas.dietz (at) dlr.deUNSPECIFIED
Künzer, Claudiaclaudia.kuenzer (at) dlr.deUNSPECIFIED
Date:May 2016
Refereed publication:No
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Page Range:p. 1
Status:Published
Keywords:AVHRR, MODIS, MERIS, Sentinel-3, Landsat, Future Missions
Event Title:Living Planet Symposium 2016
Event Location:Prague, Czech Republic
Event Type:international Conference
Event Dates:9.-13. Mai 2016
Organizer:ESA
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Vorhaben Fernerkundung der Landoberfläche (old)
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center > Land Surface
Deposited By: Dietz, Andreas
Deposited On:11 Jan 2017 10:47
Last Modified:31 Jul 2019 20:07

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