Mass balance of Icelandic glaciers in variable climate

The mass balance of a glacier is strongly connected to climate. At high latitudes, mass balance is typically controlled by snow accumulation during the winter and the glacier ablation during the summer. In Iceland, direct mass balance observations have been mostly focused on the three largest ice caps (~600 to ~8000 km2), measured in situ for the last 25 years. There are, however, glaciers and ice caps distributed over all quarters of the country that lack mass balance observations. Remote sensing data with the capability to retrieve the glacier surface geometry through Digital Elevation Models (DEMs) are valuable tools to measure mass balance using the geodetic method. For a typical Icelandic glacier (with an area between 1 km2 and hundreds of km2), this can be optimally achieved from optical stereoscopic imagery, emplaced in airborne or spaceborne sensors, and from airborne lidar. This thesis focuses on remote sensing techniques to accurately measure geodetic mass balance from seasonal to decadal time spans and the relationship of mass balance to climate. As an example of seasonal mass balance, the winter mass balance of Drangajökull was measured from satellite sub-meter stereo images at the beginning, middle and end of the 2014–2015 winter using data from the Pléiades and WorldView-2 satellites. The results were complemented with in situ snow density measurements and validated with snow thickness measurements. The study concludes that images from the sensors mentioned above may often be used to monitor seasonal mass balance without tedious field logistics. A vast archive of aerial photographs exists for Iceland extending back to 1945. Since then, most glaciers were surveyed every 5 to 20 years. In addition, a wealth of modern satellite stereo images is available since the early 2000s as well as airborne lidar data in 2008–2013. This creates a unique dataset to construct a 70-year time series of geodetic mass balances. Eyjafjallajökull (~70 km2) was used to develop semi-automated processing chains based on open-source software. The result is a detailed record of glacier changes resulting from climatic and volcanic forcing. Simple linear regression of the annual mass balance of Eyjafjallajökull indicates that most mass balance variations can be related to changes in summer temperature and winter precipitation. It also allows to infer the sensitivities of mass balance to these two climatic variables. The processing chain was then applied to 14 glaciers and ice caps spatially distributed in all quarters of Iceland, resulting in a dense mass-balance record for the last 70 years. The mean and standard deviation (±SD) of mass balances of the target glaciers were –0.44±0.16 m w.e. a–1 in 1945–1960, 0.00±0.21 m w.e. a–1 in 1960–1980, 0.11±0.25 m w.e. a–1 in 1980–1994, –1.01±0.50 m w.e. a–1 in 1994–2004, –1.27±0.56 m w.e. a–1 in 2004–2010 and –0.14±0.51 m w.e. a–1 in 2010–2015. The glaciers located at the south and west coasts revealed the highest decadal variability, in contrast to glaciers located in the north. This study improves the knowledge of Icelandic glaciers prior to the warm 1990s. The obtained glacier DEMs reveals in some cases elevation changes caused by irregularities in ice motion and opens for opportunities of modelling the ice dynamics of some of these glaciers coupled with their mass balance.Afkoma jökla ræðst af veðurfari. Augljós eru tengslin við snjósöfnun vetrar, en einnig hitastig sumars sem vísbending um orku til leysingar. Hefðbundnar reglulegar afkomumælingar með mælingu þykktar vetrarsjós að hausti og sumarleysingu að hausti, á völdum mælistöðvum, hófust á þremur stærstu jöklum Íslands á níunda og tíunda áratug síðustu aldar og hefur verið haldið úti síðan. Á öðrum jöklum Íslands eru beinar afkomumælingar takmarkaðar; á langflestum hafa engar slíkar mælingar verið gerðar. Upplýsingar um afkomu jökla má einnig meta með því að bera saman hæðarkort af yfirborði þeirra á mismunandi tímum. Í þessu skyni eru fjarkönnunargögn eins og loftmyndir, gervihnattaljósmyndir og leysihæðarskönnun (lidar) sem nýtast við gerð hæðarkorta einkar gagnleg. Viðfangsefni ritgerðarinnar er úrvinnsla slíkra gagna og hvernig má nýta þau til að fá sem nákvæmasta mælinga á afkomu jökla á tímabilum sem spanna allt frá árstíð til áratuga, auk þess sem vensl afkomu og veðurfars eru greind. Til að kanna notagildi fjarkönnunargagna við rannsóknir á árstíðabundinni afkomu jökla voru yfirborðshæðarkort af Drangajökli unnin eftir háupplausnarljósmyndum frá Pléiades og WorldView-2 gervitunglunum við upphaf, miðbik og lok vetursins 2014–2015. Mælingar á eðlismassa vetrarsnjós að vori voru nýttar til að skorða betur vetrarafkomu jökulsins auk þess sem niðurstöðurnar voru bornar saman við mælda snjóþykkt í afkomumælistöðum. Niðurstöður rannsóknarinnar sýna ótvírætt að oft er hægt að nýta myndir frá áðurnefndum gervitunglum við mælingu vetrarákomu jökla í stað þess að leggja í og erfiða mælileiðangra. Gríðarmikið safn loftmynda er til af íslenskum jöklum allt aftur til ársins 1945. Síðan þá hafa þeir flestir verið myndaðir á 5 til 20 ára fresti. Einnig hefur verulegu magni gervihnattaljósmynda sem nýtast til vinnslu hæðarkorta af jöklum verið aflað eftir 2000 auk hæðarkorta eftir leysimælingum úr flugvél af flestum jöklum landsins frá 2008 til 2013. Þessi yfirgripsmiklu gögn gera mögulega vinnslu 70 ára afkomusögu margra jökla. Með slíka vinnslu að markmiði var sett saman hálfsjálfvirk úrvinnslulína (flæðilína úrvinnsluþátta) sem byggist á opnum hugbúnaðarlausnum. Hún var þróuð fyrir og fyrst beitt á öll tiltæk gögn af Eyjafjallajökli (~70 km2 ). Úrvinnslan skilaði ítarlegri sögu um hæðarbreytingar, afkomu og umfang Eyjafjallajökuls sem bæði veðurfar og eldgos hafa stjórnað. Útfrá afkomuröðinni var bestað línulegt fall sem lýsir venslum ársafkomu við sumarhita og vetrarúrkomu auk leiðréttingarliðs vegna breytilegs umfangs jökulsins. Þetta fall sýnir að stór þáttur breytileika afkomu jökulsins má skýra með breytileika í þessum veðurfarsþáttum. Það gerir einnig kleift að meta hversu næm afkoma jökulsins er fyrir breytingum í þeim. Úrvinnslulínan var síðan notuð til að setja saman afkomusögu 14 íslenska jökla á um 70 ára tímabili. Jöklar í öllum landsfjórðungum sem og á miðhálendinu voru rannsakaðir. Meðaltal og staðalfrávik afkomu jöklanna á hverju tímabili fyrir sig var -0.44±0.16 m v.g. ár–1 (metrar vatnsígildis á ári) 1945–1960, 0.00±0.21 m v.g. ár–1 1960–1980, 0.11±0.25 m v.g. ár–1 1980–1994, -1.01±0.50 m v.g. ár–1 1994–2004, -1.27±0.56 m v.g. ár–1 2004–2010 og -0.14±0.51 m v.g. ár–-1 2010–2015. Jöklar við suður og vesturströndina sýna breytilegasta afkomu frá einu tímabili til annars, ólíkt jöklum í norðri þar sem þessi breytileiki er mun minni. Þessi rannsókn eykur mjög við þekkingu okkar á íslenskum jöklum áður en mikil hlýnun varð á tíunda áratug síðustu aldar sem og hvernig afkomu íslenskra jökla breyttist í kjölfarið. Jökla-kortin sem þessi vinna hefur skilað sýna víða hæðarbreytingar sem skýrast af tímabreyti-leika eða óreglu í ísflæði frá afkomu- til leysingasvæðis jöklanna. Þau nýtast einnig sem próf fyrir framtíðarrannsóknir með samtengdum líkönum ísflæðis og afkomu þessara jökla.Le bilan de masse des glaciers est fortement lié au climat. Aux hautes latitudes, l’accumulation de neige pendant l’hiver et la fonte de glace pendant l’été sont les principales composantes du bilan de masse. En Islande, le bilan de masse des trois plus larges calottes glaciaires (~600-~8000 km²) a été suivi régulièrement depuis 25 ans notamment grâce à des mesures in situ. Mais les bilans de masse des autres glaciers et calottes glaciaires islandaises ont été très peu étudiés. Aujourd’hui, les données de télédétection, notamment via la comparaison des modèles numériques du terrain (MNT), permettent de mesurer le bilan de masse par la méthode géodésique. Pour ces glaciers et calottes de plus petites tailles (de 1 km² et à quelques centaines de km²), les photographies aériennes, l’imagerie satellitaire stéréoscopique sub-métriques, et le lidar aérien sont parfaitement adaptées. Cette thèse se focalise donc sur l’estimation des bilans de masse des « petits » glaciers et calottes islandaises depuis le pas de temps saisonnier jusqu’à pluridécennal et leur relation avec les variations spatiales et temporelles du climat. Le bilan de masse hivernal de la calotte du Drangajökull (NO-Islande) a été mesuré par des images satellitaires stéréoscopiques sub-métriques (données Pléiades et WorldView-2) acquises au début, milieu et à la fin de l’hiver 2014-2015. Les changements de volume ont été convertis en bilan de masse grâce à des mesures in situ de densité de neige, et validés avec des mesures in situ de profondeur de neige. Ce travail permet d’envisager désormais un suivi du bilan de masse saisonnier sans un laborieux travail de terrain. Une importante archive de photographies aériennes est disponible en Islande depuis 1945. Ces données offrent une revisite de 5 à 20 ans pour la majorité des glaciers. De plus, depuis 2000, cette archive est complétée par les données des capteurs satellitaires stéréoscopiques et de lidar aérien acquis entre 2008 et 2013. Cet ensemble de données est exploité pour créer une série temporelle de 70 ans de bilan de masse en Islande. La calotte d’Eyjafjallajökull (~70 km²) sert de zone test pour la création et l’automatisation d’une chaîne de traitement, basée sur des logiciels libres. Le résultat est une série de 70 ans de bilan de masse et changements glaciaires liés au climat et au volcanisme. Les variations décennales du bilan de masse sont mises en relation avec les variations des températures estivales et les précipitations hivernales. Cette relation, quasi linéaire, sert pour le calcul de la sensibilité du bilan de masse au changement de température et précipitation. La chaîne de traitement est alors appliquée à 14 glaciers et calottes glaciaires distribuées aux quatre coins de l’Islande. La moyenne et déviation standard (±DS) du bilan de masse des glaciers sélectionnés est : –0.44±0.16 m w.e. a–1 en 1945–1960, 0.00±0.21 m w.e. a–1 en 1960–1980, 0.11±0.25 m w.e. a–1 en 1980–1994, –1.01±0.50 m w.e. a–1 en 1994–2004, –1.27±0.56 m w.e. a–1 en 2004–2010 et –0.14±0.51 m w.e. a–1 en 2010–2015. Les glaciers maritimes situés près des côtes sud et ouest montrent une plus forte variabilité décennale que les glaciers plus continentaux situés dans le nord et nord-ouest. Notre étude améliore la connaissance des évolutions des glaciers islandais et leur relation avec le climat, en particulier avant les années 1990s et l’augmentation de température. Nos travaux montrent aussi la complexité de la réponse géométrique des glaciers (en lien avec leur dynamique) et offre des données uniques pour la calibration/validation des modèles des glaciers.This work was financially supported by the University of Iceland Research Fund, the Jules Verne Fund and the Katla Kalda project. The lidar mapping of the glaciers in Iceland was funded by the Icelandic Research Fund, the Landsvirkjun research fund, the Icelandic Road Administration, the Reykjavík Energy Environmental and Energy Research Fund, the Klima- og Luftgruppen research fund of the Nordic Council of Ministers, the Vatnajökull National Park, the organization Friends of Vatnajökull, LMÍ, IMO and the UI research fund. Pléiades images were acquired at research price thanks to the CNES ISIS program. WorldView DEMs were obtained through the ArcticDEM project

Geodetic mass balance record with rigorous uncertainty estimates deduced from aerial photographs and lidar data – Case study from Drangajökull ice cap, NW Iceland

In this paper we describe how recent high-resolution digital elevation models (DEMs) can be used to extract glacier surface DEMs from old aerial photographs and to evaluate the uncertainty of the mass balance record derived from the DEMs. We present a case study for Drangajokull ice cap, NW Iceland. This ice cap covered an area of 144 km(2) when it was surveyed with airborne lidar in 2011. Aerial photographs spanning all or most of the ice cap are available from survey flights in 1946, 1960, 1975, 1985, 1994 and 2005. All ground control points used to constrain the orientation of the aerial photographs were obtained from the high-resolution lidar DEM. The lidar DEM was also used to estimate errors of the extracted photogrammetric DEMs in ice-and snow-free areas, at nunataks and outside the glacier margin. The derived errors of each DEM were used to constrain a spherical semivariogram model, which along with the derived errors in ice-and snow-free areas were used as inputs into 1000 sequential Gaussian simulations (SGSims). The simulations were used to estimate the possible bias in the entire glaciated part of the DEM and the 95% confidence level of this bias. This results in bias correction varying in magnitude between 0.03m (in 1975) and 1.66m (in 1946) and uncertainty values between +/- 0.21m (in 2005) and +/- 1.58m (in 1946). Error estimation methods based on more simple proxies would typically yield 2-4 times larger error estimates. The aerial photographs used were acquired between late June and early October. An additional seasonal bias correction was therefore estimated using a degree-day model to obtain the volume change between the start of 2 glaciological years (1 October). This correction was largest for the 1960 DEM, corresponding to an average elevation change of -3.5m or approx. three-quarters of the volume change between the 1960 and the 1975 DEMs. The total uncertainty of the derived mass balance record is dominated by uncertainty in the volume changes caused by uncertainties of the SGSim bias correction, the seasonal bias correction and the interpolation of glacier surface where data are lacking. The record shows a glacier-wide mass balance rate of (B) over dot = -0.26 +/- 0.04m w.e.a(-1) for the entire study period (1946-2011). We observe significant decadal variability including periods of mass gain, peaking in 1985-1994 with (B) over dot = -0.27 +/- 0.11m w.e.a(-1). There is a striking difference when (B) over dot is calculated separately for the western and eastern halves of Drangajokull, with a reduction of eastern part on average similar to 3 times faster than the western part. Our study emphasizes the need for applying rigorous geostatistical methods for obtaining uncertainty estimates of geodetic mass balance, the importance of seasonal corrections of DEMs from glaciers with high mass turnover and the risk of extrapolating mass balance record from one glacier to another even over short distances.This work was carried out within SVALI funded by the Nordic Top-level Research Initiative (TRI) and is SVALI publication number 70. It was also financially supported by alpS GmbH. This work is a contribution to the Rannis grant of excellence project, ANATILS. We thank the National Land Survey of Iceland and Loftmyndir ehf. for acquisition and scanning of the aerial photographs. This study used the recent lidar mapping of the glaciers in Iceland that was funded by the Icelandic Research Fund, the Landsvirkjun Research Fund, the Icelandic Road Administration, the Reykjavik Energy Environmental and Energy Research Fund, the Klima- og Luftgruppen (KoL) research fund of the Nordic Council of Ministers, the Vatnajokull National Park, the organization Friends of Vatnajokull, the National Land Survey of Iceland and the Icelandic Meteorological Office.Peer Reviewe

The geodetic mass balance of Eyjafjallajökull ice cap for 1945–2014: processing guidelines and relation to climate

Publisher's version (útgefin grein)Mass-balance measurements of Icelandic glaciers are sparse through the 20th century. However, the large archive of stereo images available allows estimates of glacier-wide mass balance in decadal time steps since 1945. Combined with climate records, they provide further insight into glacier-climate relationship. This study presents a workflow to process aerial photographs (1945-1995), spy satellite imagery (1977-1980) and modern satellite stereo images (since 2000) using photogrammetric techniques and robust statistics in a highly automated, open-source pipeline to retrieve seasonally corrected, decadal glacier-wide geodetic mass balances. In our test area, Eyjafjallajökull (S-Iceland, ~70 km2), we obtain a mass balance of <![CDATA[$, with a maximum and minimum of and , respectively, attributed to climatic forcing, and , mostly caused by the April 2010 eruption. The reference-surface mass balances correlate with summer temperature and winter precipitation, and linear regression accounts for 80% of the mass-balance variability, yielding a static sensitivity of mass balance to summer temperature and winter precipitation of-2.1 ± 0.4 m w.e.a-1K-1 and 0.5 ± 0.3 m w.e.a-1 (10%)-1, respectively. This study serves as a template that can be used to estimate the mass-balance changes and glaciers' response to climate.This study was funded by the University of Iceland (UI) Research Fund. Collaboration and travels between IES and LEGOS were funded by the Jules Verne research fund. We thank David Shean and two anonymous reviewers for their valuable comments, which greatly improved the manuscript. We thank Carsten Kristinsson at LMÍ for scanning the aerial photographs, Oleg Alexandrov for his helpful tips and advice on ASP, Luc Girod for his help in the MicMac forum and Deirdre Clark and Ken Moxham for the Englishlanguage editing of the manuscript. Pléiades images were acquired at research price thanks to the CNES ISIS program (http://www.isis-cnes.fr). This study uses the lidar mapping of the glaciers in Iceland, funded by the Icelandic Research Fund, the Landsvirkjun research fund, the Icelandic Road Administration, the Reykjavík Energy Environmental and Energy Research Fund, the Klima-og Luftgruppen research fund of the Nordic Council of Ministers, the Vatnajökull National Park, the organization Friends of Vatnajökull, LMÍ, IMO and the UI research fund. This study uses the GLIMS database of the outlines of Icelandic glaciers. E.B. acknowledges support from the French Space Agency (CNES) through the TOSCA program.Peer Reviewe

Non-surface mass balance of glaciers in Iceland

Publisher's version (útgefin grein)Non-surface mass balance is non-negligible for glaciers in Iceland. Several Icelandic glaciers are in the neo-volcanic zone where a combination of geothermal activity, volcanic eruptions and geothermal heat flux much higher than the global average lead to basal melting close to 150 mm w.e. a−1 for the Mýrdalsjökull ice cap and 75 mm w.e. a−1 for the largest ice cap, Vatnajökull. Energy dissipation in the flow of water and ice is also rather large for the high-precipitation, temperate glaciers of Iceland resulting in internal and basal melting of 20–150 mm w.e. a−1. The total non-surface melting of glaciers in Iceland in 1995–2019 was 45–375 mm w.e. a−1 on average for the main ice caps, and was largest for Mýrdalsjökull, the south side of Vatnajökull and Eyjafjallajökull. Geothermal melting, volcanic eruptions and the energy dissipation in the flow of water and ice, as well as calving, all contribute, and thus these components should be considered in mass-balance studies. For comparison, the average mass balance of glaciers in Iceland since 1995 is −500 to −1500 mm w.e. a−1. The non-surface mass balance corresponds to a total runoff contribution of 2.1 km3 a−1 of water from Iceland.Financial support for lidar mapping of glaciers in Iceland in 2008–2012 was provided by the Icelandic Research Fund (163391-052), the Landsvirkjun (National Power Company of Iceland) Research Fund, the Icelandic Road Administration, the Reykjavík Energy Environmental and Energy Research Fund, the National Land Survey of Iceland, the Klima- og Luftgruppen (KoL) research fund of the Nordic Council of Ministers, and the Vatnajökull National Park. The acquisition of the Hofsjökull 2013 DEM was funded by AlpS GmbH and the University of Innsbruck. The acquisition of the Langjökull 2013 DEM was funded by NERC grant IG 13/12 and the DEM was provided by Ian Willis at the Scott Polar Research Institute. The work on estimating geothermal and volcanic power is based on funding from many sources, including the Research Fund of the University of Iceland, ISAVIA (the Icelandic Aviation Service), the Icelandic Road Administration and Landsvirkjun; logistical support has been provided by the Iceland Glaciological Society.Peer Reviewe

Of mosses and men: Plant succession, soil development and soil carbon accretion in the sub-Arctic volcanic landscape of Hekla, Iceland

Post-print (lokagerð höfundar)Lava flows pose a hazard in volcanic environments and reset ecosystem development. A succession of dated lava flows provides the possibility to estimate the direction and rates of ecosystem development and can be used to predict future development. We examine plant succession, soil development and soil carbon (C) accretion on the historical (post 874 AD) lava flows formed by the Hekla volcano in south Iceland. Vegetation and soil measurements were conducted all around the volcano reflecting the diverse vegetation communities on the lavas, climatic conditions around Hekla mountain and various intensities in deposition of loose material. Multivariate analysis was used to identify groups with similar vegetation composition and patterns in the vegetation. The association of vegetation and soil parameters with lava age, mean annual temperature, mean annual precipitation and soil accumulation rate (SAR) was analysed. Soil carbon concentration increased with increasing lava age becoming comparable to concentrations found on the prehistoric lavas. The combination of a sub-Arctic climate, gradual soil thickening due to input of loose material and the specific properties of volcanic soils allow for continuing accumulation of soil carbon in the soil profile. Four successional stages were identified: initial colonization and cover coalescence (ICC) of Racomitrium lanuginosum and Stereocaulon spp. (lavas 600 years); and highland conditions/retrogression (H/R) by tephra deposition (70−860 years). The long time span of the SC stage indicates arrested development by the thick R. lanuginosum moss mat. The progression from SC into VPD was linked to age of the lava flows and soil depth, which was significantly deeper within the VPD stage. Birch was growing on lavas over 600 years old indicating the development towards birch woodland, the climax ecosystem in Iceland.The Icelandic Research Fund, Rannís, Grant of Excellence no. 152266-052 (Project: EMMIRS).Peer Reviewe

Hekla Volcano, Iceland, in the 20th Century: Lava Volumes, Production Rates, and Effusion Rates

Publisher's version (útgefin grein)Lava flow thicknesses, volumes, and effusion rates provide essential information for understanding the behavior of eruptions and their associated deformation signals. Preeruption and posteruption elevation models were generated from historical stereo photographs to produce the lava flow thickness maps for the last five eruptions at Hekla volcano, Iceland. These results provide precise estimation of lava bulk volumes: V1947–1948 = 0.742 ± 0.138 km3, V1970 = 0.205 ± 0.012 km3, V1980–1981 = 0.169 ± 0.016 km3, V1991 = 0.241 ± 0.019 km3, and V2000 = 0.095 ± 0.005 km3 and reveal variable production rate through the 20th century. These new volumes improve the linear correlation between erupted volume and coeruption tilt change, indicating that tilt may be used to determine eruption volume. During eruptions the active vents migrate 325–480 m downhill, suggesting rough excess pressures of 8–12 MPa and that the gradient of this excess pressure increases from 0.4 to 11 Pa s−1 during the 20th century. We suggest that this is related to increased resistance along the eruptive conduit.Icelandic Research Fund. Grant Number: 152266‐052Peer Reviewe

Historical lava flow fields at Hekla volcano, South Iceland

Publisher's version (útgefin grein)Hekla volcano is known to have erupted at least 23 times in historical time (last 1100 years); often producing mixed eruptions of tephra and lava. The lava flow volumes from the 20th century have amounted 80% to almost 100% of the entire erupted volume. Therefore, evaluating the extent and volume of individual lava flows is very important when assessing the historical productivity of Hekla volcano. Here we present new maps of the historical lava flow fields at Hekla in a digital format. The maps were produced at a scale of 1:2000–10000 using a catalogue of orthophotos since 1945, acquired before and after each of the last five eruptions, combined with field observation of stratigraphy, soil profiles, tephra layers and vegetation cover. The new lava flow maps significantly improve the historical eruptive history of Hekla, prior to the 1947 eruption. The historical lava flow fields from Hekla cover 233 km2 and the lavas reach up to 16 km from Hekla volcano. Flow lengths up to 20 km are known, though lava flows only travelled up to 8–9 km from Hekla in the last 250 years. Identified historical vents are distributed between 0 and 16 km from Hekla volcano and vents are known to have migrated up to 5 km away from Hekla during eruptions. We have remapped the lava flow fields around Hekla and assigned the identified flow fields to 16 eruptions. In addition, ca. 60 unidentified lava units, which may be of historical age, have been mapped. It is expected that some of these units are from known historical Hekla eruptions such as the 1222, 1341, 1510, 1597, 1636 and potentially even from the previously excluded eruptions such as 1436/1439.Hekla hefur gosið 23 sinnum svo vitað sé síðan land byggðist. Oftast hafa gosin verið blandgos og framleitt bæði gjósku og hraun. Í gosum 20. aldar var hlutfall hrauns á milli 80–100% af gosefnunum svo þau skipta verulegu máli þegar framleiðni eldstöðvarkerfisins er metin. Í þessari grein eru birtar niðurstöður stafrænnar kortlagningar á Hekluhraunum frá sögulegum tíma eins langt aftur í tímann og unnt er. Þetta er engan veginn auðvelt viðfangsefni á svo virku eldfjalli sem Hekla er, því ný hraun hylja þau sem fyrir eru. Hraunakortin eru gerð í mælikvarða 1:2000–10000 og styðjast við uppréttaðar loftmyndir sem teknar hafa verið síðan 1945, bæði fyrir og eftir síðustu fimm eldgos. Einnig er stuðst við innbyrðis afstöðu hraunanna, landslagsform, jarðvegssnið, gjóskulög og gróðurþekju. Tekist hefur að bæta talsvert hraunakort Heklu og gert hefur verið kort af hraunum sem runnu fyrir gosið mikla 1947. Hraun frá eldstöðvarkerfi Heklu á sögulegum tíma þekja u.þ.b. 233 km2 lands. Hraun hafa runnið allt að 16 km vegalengd frá megineldstöðinni og hraunstraumar hafa náð 20 km lengd. Á síðustu 250 árum hafa hraun þó aðeins runnið 8–9 km frá megineldstöðinni. Eldvörp á sögulegum tíma dreifast allt að 16 km út frá megineldstöðinni. Í sumum gosum hefur eldvirknin færst um allt að 5 km út frá eldstöðinni þega leið á gosið. Borin hafa verið kennsl á hraun frá 16 gosum og að auki hafa um 60 hraunflákar verið kortlagðir sem gætu verið frá gosum á sögulegum tíma. Þessi hraun eru líklega frá þekktum gosum, s.s. 1222, 1341, 1510, 1597 og 1636 en þau gætu líka verið að einhverju leyti frá gosum sem þótt hafa vafasöm, á árunum 1436–1439.Icelandic Research fund, Grant of Excellence No. 152266-052 (Project EMMIRS)Peer Reviewe

Observing glacier elevation changes from spaceborne optical and radar sensors – an inter-comparison experiment using ASTER and TanDEM-X data

Observations of glacier mass changes are key to understanding the response of glaciers to climate change and related impacts, such as regional runoff, ecosystem changes, and global sea-level rise. Spaceborne optical and radar sensors make it possible to quantify glacier elevation changes, and thus multi-annual mass changes, on a regional and global scale. However, estimates from a growing number of studies show a wide range of results with differences often beyond uncertainty bounds. Here, we present the outcome of a community-based inter-comparison experiment using spaceborne optical stereo (ASTER) and synthetic aperture radar interferometry (TanDEM-X) data to estimate elevation changes for defined glaciers and target periods that pose different assessment challenges. Using provided or self-processed digital elevation models (DEMs) for five test sites, 12 research groups provided a total of 97 spaceborne elevation-change datasets using various processing strategies. Validation with airborne data showed that using an ensemble estimate is promising to reduce random errors from different instruments and processing methods, but still requires a more comprehensive investigation and correction of systematic errors. We found that scene selection, DEM processing, and co-registration have the biggest impact on the results. Other processing steps, such as treating spatial data voids, differences in survey periods, or radar penetration, can still be important for individual cases. Future research should focus on testing different implementations of individual processing steps (e.g. co-registration) and addressing issues related to temporal corrections, radar penetration, glacier area changes, and density conversion. Finally, there is a clear need for our community to develop best practices, use open, reproducible software, and assess overall uncertainty in order to enhance inter-comparison and empower physical process insights across glacier elevation-change studies