Application of terrestrial‚ 'structure-from-motion' photogrammetry on a medium-size Arctic valley glacier: potential, accuracy and limitations

Terrestrial photogrammetry was the standard method for mapping high mountain terrain in the early days of mountain cartography, until it was replaced by aerial photogrammetry and airborne laser scanning. Modern lowprice digital single-lens reflex (DSLR) cameras and highly automatic and cheap digital computer vision software with automatic image matching and multiview-stereo routines suggest the rebirth of terrestrial photogrammetry, especially in remote regions, where airborne surveying methods are expensive due to high flight costs. Terrestrial photogrammetry and modern automated image matching is widely used in geodesy, however, its application in glaciology is still rare, especially for surveying ice bodies at the scale of some km2, which is typical for valley glaciers. In August 2013 a terrestrial photogrammetric survey was carried out on Freya Glacier, a 6km2 valley glacier next to Zackenberg Research Station in NE-Greenland, where a detailed glacier mass balance monitoring was initiated during the last IPY. Photos with a consumer grade digital camera (Nikon D7100) were taken from the ridges surrounding the glacier. To create a digital elevation model, the photos were processed with the software photoscan. A set of 100 dGPS surveyed ground control points on the glacier surface was used to georeference and validate the final DEM. Aim of this study was to produce a high resolution and high accuracy DEM of the actual surface topography of the Freya glacier catchment with a novel approach and to explore the potential of modern low-cost terrestrial photogrammetry combined with state-of-the-art automated image matching and multiview-stereo routines for glacier monitoring and to communicate this powerful and cheap method within the environmental research and glacier monitoring community

EXPLORING PAST CLIMATE VARIABILITY IN THE GREATER ALPINE REGION

The presentation discusses the potential, the needs and the state of the art of climate variability data quality and analysis in the instrumental period. The greater alpine region is used as an example. Problems and solutions concerning the non climatic noise in time series is discussed (the homogeneity and outlier problem) and some first results based on the new HISTALP datasets are shown

THE NEW CENTENNIAL SNOW INITIATIVE FOR THE GREATER ALPINE REGION (GAR). STATUS REPORT AND FIRST RESULTS

Snow is a significant element in the climate system and has great impact on ecosystem and economy in the Alps, too. Astonishingly there is still a strong gap between the data potential and the data availability. Caused by the existing deficits we started a digitising, quality evaluation, homogenising and analysing initiative for the Alpine region. For the first time we can present a 21-year (1895-1915) daily, high density dataset that was electronically scanned from historic hydro-yearbooks for recent Austria and additional some surrounding regions in Italy, Slovenia, Croatia and Czech Republic. We hope that our snow initiative will grow to a pan-alpine effort to fill the existing lack of information

A Global Cryosphere Watch

There is now an unprecedented demand for authoritative information on the past, present, and future states of the world’s snow and ice resources. The cryosphere is one of the most useful indicators of climate change, yet is one of the most under-sampled domains in the climate system. The Sixteenth World Meteorological Congress (Geneva, 2011) decided to embark on the development of a Global Cryosphere Watch (GCW) as an International Polar Year (IPY) legacy. Through WMO and its partners, GCW is now being implemented for sustained cryosphere observing and monitoring and provision of cryosphere data and information. GCW will ensure a comprehensive, coordinated, and sustainable system of observations and information that will allow for a full understanding of the cryosphere and its changes. It will initiate a surface-based cryosphere observing network called “CryoNet” that will establish best practices and guidelines for cryospheric measurement, data formats, and metadata by building on existing efforts. A complementary task involves developing an inventory of candidate satellite products that are mature and generally accepted by the scientific community. GCW is establishing interoperability between data management systems, and the GCW data portal will provide the ability to exchange data and information with a distributed network of providers.Il existe maintenant une demande sans précédent d’information faisant autorité sur l’état passé, présent et futur des ressources en neige et en glace de la planète. La cryosphère constitue l’un des indicateurs les plus utiles au sujet du changement climatique et pourtant, il s’agit de l’un des domaines du système climatique les plus sous-échantillonnés. Le seizième Congrès météorologique mondial (Genève, 2011) a décidé de mettre au point un système de surveillance mondiale de la cryosphère (Global Cryosphere Watch – GCW) en guise de legs à l’Année polaire internationale. Grâce au concours de l’Organisation météorologique mondiale (OMM) et de ses partenaires, le GCW est en train d’être mis en oeuvre en vue de l’observation et de la surveillance durables de la cryosphère ainsi que de l’obtention de données et d’informations sur la cryosphère. Le GCW donnera lieu à un système exhaustif, coordonné et durable d’observations et d’informations qui permettront de comprendre à fond la cryosphère et les changements qui s’y rapportent. Il comprendra un réseau d’observation de la cryosphère en surface appelé « CryoNet », réseau qui établira les pratiques et les lignes directrices exemplaires en matière de mesure cryosphérique, de formats des données et de métadonnées en s’appuyant sur les efforts actuels. Une tâche complémentaire consiste à dresser l’inventaire des produits satellitaires évolués et généralement acceptés par le monde scientifique. Le GCW établit l’interopérabilité entre les systèmes de gestion des données, et le portail des données du GCW donnera la possibilité d’échanger des données et des informations avec un réseau de fournisseurs interconnectés

Intercomparison Experiment of Water-Insoluble Carbonaceous Particles in Snow in a High-Mountain Environment (1598 m a.s.l.)

The harmonization of sampling, sample preparation and laboratory analysis methods to detect carbon compounds in snow requires detailed documentation of those methods and their uncertainties. Moreover, intercomparison experiments are needed to reveal differences and quantify the uncertainties further. Here, we document our sampling, filtering, and analysis protocols used in the intercomparison experiment from three laboratories to detect water-insoluble carbon in seasonal surface snow in the high-mountain environment at Kolm Saigurn (47.067842° N, 12.98394° E, alt 1598 m a.s.l.), Austria. The participating laboratories were TU Wien (Austria), the University of Florence (Italy), and the Finnish Meteorological Institute (Finland). For the carbon analysis, the NIOSH5040 and EUSAAR2 protocols of the OCEC thermal-optical method were used. The median of the measured concentrations of total carbon (TC) was 323 ppb, organic carbon (OC) 308 ppb, and elemental carbon (EC) 16 ppb. The methods and protocols used in this experiment did not reveal large differences between the laboratories, and the TC, OC, and EC values of four inter-comparison locations, five meters apart, did not show meter-scale horizontal variability in surface snow. The results suggest that the presented methods are applicable for future research and monitoring of carbonaceous particles in snow. Moreover, a recommendation on the key parameters that an intercomparison experiment participant should be asked for is presented to help future investigations on carbonaceous particles in snow. The work contributes to the harmonization of the methods for measuring the snow chemistry of seasonal snow deposited on the ground

A three-pillar approach to assessing climate impacts on low flows

The objective of this paper is to present a framework for assessing climate impacts on future low flows that combines different sources of information, termed pillars. To illustrate the framework three pillars are chosen: (a) extrapolation of observed low-flow trends into the future, (b) rainfall–runoff projections based on climate scenarios and (c) extrapolation of changing stochastic rainfall characteristics into the future combined with rainfall–runoff modelling. Alternative pillars could be included in the overall framework. The three pillars are combined by expert judgement based on a synoptic view of data, model outputs and process reasoning. The consistency/inconsistency between the pillars is considered an indicator of the certainty/uncertainty of the projections. The viability of the framework is illustrated for four example catchments from Austria that represent typical climate conditions in central Europe. In the Alpine region where winter low flows dominate, trend projections and climate scenarios yield consistently increasing low flows, although of different magnitudes. In the region north of the Alps, consistently small changes are projected by all methods. In the regions in the south and south-east, more pronounced and mostly decreasing trends are projected but there is disagreement in the magnitudes of the projected changes. The process reasons for the consistencies/inconsistencies are discussed. For an Alpine region such as Austria the key to understanding low flows is whether they are controlled by freezing and snowmelt processes, or by the summer moisture deficit associated with evaporation. It is argued that the three-pillar approach offers a systematic framework of combining different sources of information aimed at more robust projections than that obtained from each pillar alone

A NEW HIGH-RESOLUTION BI-CENTENNIAL (1800–2003) PRECIPITATION DATASET FOR THE GREATER ALPINE REGION

A new precipitation dataset for the Greater Alpine Region (GAR; 4°E–19°E, 43°N–49°N) has been developed. It provides monthly precipitation totals for the 1800–2003 period on a 10-min resolution grid. The new ‘HISTALP 10-min-grid’ dataset is based on long-term homogenized precipitation series from meteorological stations across the study domain and a high-resolution precipitation climatology dataset for the 1971–1990 period. The effective coverage of the dataset depends on the observations available in the station network which progressively decline back to the early 19th Century (from 192 to 5 stations). To aid the use of these data in other studies, an accompanying dataset has also been developed, which provides a measure of quality of each monthly precipitation estimate over the grid: the explained variance, relative to the 1931–2000 (maximum data availability) period. The computed quality score illustrates the comparatively poorer accuracy of the dataset for regions and months with less coherent precipitation fields (i.e., over the Alps and in summer) and when the number of stations is reduced, particularly before 1840. The derived gridded field has been compared with other independently-developed datasets and is found to provide a similar description of the precipitation in the GAR for places and periods of common coverage