ORCID Profile
0000-0002-9222-2107
Current Organisation
University of Western Australia
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Publisher: Frontiers Media SA
Date: 21-04-2020
Publisher: Copernicus GmbH
Date: 04-03-2021
DOI: 10.5194/EGUSPHERE-EGU21-10689
Abstract: & & The lithospheric structure of Greenland is still poorly known due to its thick ice sheet, the sparseness of seismological stations, and the limitation of geological outcrops near coastal areas. As only a few geothermal measurements are available for Greenland, one must rely on geophysical models. Such models of Moho and LAB depths and sub-ice geothermal heat-flow vary largely.& & & & Our approach is to model the lithospheric architecture by geophysical-petrological modelling with LitMod3D. The model is built to reproduce gravity observations, the observed elevation with isostasy assumptions and the velocities from a tomography model. Furthermore, we adjust the thermal parameters and the temperature structure of the model to agree with different geothermal heat flow models. We use three different heat flow models, one from machine learning, one from a spectral analysis of magnetic data and another one which is compiled from a similarity study with tomography data.& & & & For the latter, a new shear wave tomography model of Greenland is used. Vs-depth profiles from Greenland are compared with velocity profiles from the US Array, where a statistical link between Vs profiles and surface heat flow has been established. A similarity function determines the most similar areas in the U.S. and assigns the mean heat-flow from these areas to the corresponding area in Greenland.& & & & The geothermal heat flow models will be further used to discuss the influence on ice sheet dynamics by comparison to friction heat and viscous heat dissipation from surface meltwater.& &
Publisher: Copernicus GmbH
Date: 12-05-2022
DOI: 10.5194/ESSD-14-2209-2022
Abstract: Abstract. We compile and analyze all available geothermal heat flow measurements collected in and around Greenland into a new database of 419 sites and generate an accompanying spatial map. This database includes 290 sites previously reported by the International Heat Flow Commission (IHFC), for which we now standardize measurement and metadata quality. This database also includes 129 new sites, which have not been previously reported by the IHFC. These new sites consist of 88 offshore measurements and 41 onshore measurements, of which 24 are subglacial. We employ machine learning to synthesize these in situ measurements into a gridded geothermal heat flow model that is consistent across both continental and marine areas in and around Greenland. This model has a native horizontal resolution of 55 km. In comparison to five existing Greenland geothermal heat flow models, our model has the lowest mean geothermal heat flow for Greenland onshore areas. Our modeled heat flow in central North Greenland is highly sensitive to whether the NGRIP (North GReenland Ice core Project) elevated heat flow anomaly is included in the training dataset. Our model's most distinctive spatial feature is pronounced low geothermal heat flow ( 40 mW m−2) across the North Atlantic Craton of southern Greenland. Crucially, our model does not show an area of elevated heat flow that might be interpreted as remnant from the Icelandic plume track. Finally, we discuss the substantial influence of paleoclimatic and other corrections on geothermal heat flow measurements in Greenland. The in situ measurement database and gridded heat flow model, as well as other supporting materials, are freely available from the GEUS Dataverse (0.22008/FK2/F9P03L Colgan and Wansing, 2021).
Publisher: American Geophysical Union (AGU)
Date: 06-2021
DOI: 10.1029/2020JB021499
Abstract: We present a machine learning approach to statistically derive geothermal heat flow (GHF) for Antarctica. The adopted approach estimates GHF from multiple geophysical and geological data sets, assuming that GHF is substantially related to the geodynamic setting of the plates. We apply a Gradient Boosted Regression Tree algorithm to find an optimal prediction model relating GHF to the observables. The geophysical and geological features are primarily global data sets, which are often unreliable in polar regions due to limited data coverage. Quality and reliability of the data sets are reviewed and discussed in line with the estimated GHF model. Predictions for Australia, where an extensive database of GHF measurements exists, demonstrate the validity of the approach. In Antarctica, only a sparse number of direct GHF measurements are available. Therefore, we explore the use of regional data sets of Antarctica and its tectonic Gondwana neighbors to refine the predictions. With this, we demonstrate the need for adding reliable data to the machine learning approach. Finally, we present a new geothermal heat flow map, which exhibits intermediate values compared to previous models, ranging from 35 to 156 mW/m 2 , and visible connections to the conjugate margins in Australia, Africa, and India.
Publisher: Copernicus GmbH
Date: 15-05-2023
DOI: 10.5194/EGUSPHERE-EGU23-368
Abstract: The Wilkes Subglacial Basin hosts potentially the largest unstable sector of the East Antarctica Ice Sheet due to the depth of the ice bed below sea level. Ice covering such basins poses a potentially high, but poorly constrained risk for future sea-level rise, as it is more vulnerable to melting by warming of the surrounding ocean. Such melting could potentially trigger mechanisms of unstable retreat. The neighbouring Transantarctic Mountains are the largest non-contractional mountain range on Earth. Traditionally, the Transantarctic Mountains are viewed as iding the ancient East Antarctic craton from the younger West Antarctic Rift system. However, petrological s les and previous geophysical mapping suggest that the craton boundary is further west, following the western edge of the Wilkes Subglacial Basin. Subglacial geology influences geothermal heat flow and bed roughness, and therefore to better understand the past, present and possible future behaviour of the East Antarctic Ice Sheet improved understanding of the subglacial geology on which it flows, especially in the Wilkes Subglacial Basin and Transantarctic Mountains region, is important.We present a new 3D crustal model of the Wilkes Subglacial Basin and the Transantarctic Mountains based on joint inversion of airborne gravity and magnetic data using the mutual information inversion algorithm incorporated in the software JIF3D. Our model shows a large intrusive body located in the interior of the Wilkes Subglacial Basin and suggests a tectonically complex area west of the Basin, which could potentially indicate the transition zone at the margin of the Terre Ad& #233 lie Craton. Geological units are inferred by clustering of inverted susceptibility and density distribution and are validated against sparse petrological s les from the Transantarctic Mountains region and along the George V Land and Terre Ad& #233 lie coasts. Our inferred crustal properties model can provide crucial insight into the heterogeneity of subglacial geology in terms of thermal conductivity and crustal heat production, which could influence the geothermal heat flow in this area and therefore make the overlying ice sheet more vulnerable than commonly thought.&
Publisher: Copernicus GmbH
Date: 13-09-2021
Abstract: Abstract. We compile, analyse and map all available geothermal heat flow measurements collected in and around Greenland into a new database of 419 sites and generate an accompanying spatial map. This database includes 290 sites previously reported by the International Heat Flow Commission (IHFC), for which we now standardize measurement and metadata quality. This database also includes 129 new sites, which have not been previously reported by the IHFC. These new sites consist of 88 offshore measurements and 41 onshore measurements, of which 24 are subglacial. We employ machine learning to synthesize these in situ measurements into a gridded geothermal heat flow model that is consistent across both continental and marine areas in and around Greenland. This model has a native horizontal resolution of 55 km. In comparison to five existing Greenland geothermal heat flow models, our model has the lowest mean geothermal heat flow for Greenland onshore areas (44 mW m–2). Our model’s most distinctive spatial feature is pronounced low geothermal heat flow ( 40 mW m–2) across the North Atlantic Craton of southern Greenland. Crucially, our model does not show an area of elevated heat flow that might be interpreted as remnant from the Icelandic Plume track. Finally, we discuss the substantial influence of paleoclimatic and other corrections on geothermal heat flow measurements in Greenland. The in-situ measurement database and gridded heat flow model, as well as other supporting materials, are freely available from the GEUS DataVerse (0.22008/FK2/F9P03L Colgan and Wansing, 2021).
Publisher: Frontiers Media SA
Date: 17-08-2022
DOI: 10.3389/FEART.2022.963525
Abstract: Geothermal heat flow is inferred from the gradient of temperature values in boreholes or short-penetration probe measurements. Such measurements are expensive and logistically challenging in remote locations and, therefore, often targeted to regions of economic interest. As a result, measurements are not distributed evenly. Some tectonic, geologic and even topographic settings are overrepresented in global heat flow compilations other settings are underrepresented or completely missing. These limitations in representation have implications for empirical heat flow models that use catalogue data to assign heat flow by the similarity of observables. In this contribution, we analyse the s ling bias in the Global Heat Flow database of the International Heat Flow Commission the most recent and extensive heat flow catalogue, and discuss the implications for accurate prediction and global appraisals. We also suggest correction weights to reduce the bias when the catalogue is used for empirical modelling. From comparison with auxiliary variables, we find that each of the following settings is highly overrepresented for heat flow measurements continental crust, sedimentary rocks, volcanic rocks, and Phanerozoic regions with hydrocarbon exploration. Oceanic crust, cratons, and metamorphic rocks are underrepresented. The findings also suggest a general tendency to measure heat flow in areas where the values are elevated however, this conclusion depends on which auxiliary variable is under consideration to determine the settings. We anticipate that using our correction weights to balance disproportional representation will improve empirical heat flow models for remote regions and assist in the ongoing assessment of the Global Heat Flow database.
Publisher: Authorea, Inc.
Date: 20-07-2023
DOI: 10.22541/ESSOAR.168987130.08453761/V1
Abstract: Direct geological information in Antarctica is limited to ice free regions along the coast, high mountain ranges or isolated nunataks. Therefore, indirect methods are required to reveal subglacial geology and heterogeneities in crustal properties, which are critical steps towards interpreting geological history. We present a 3D crustal model of density and susceptibility distribution in the Wilkes Subglacial Basin and the Transantarctic Mountains (TAM) based on joint inversion of airborne gravity and magnetic data. The applied “variation of information” technique enforces a coupling between gravity and magnetic sources to give an enhanced inversion result. Our model reveals a large-scale body located in the interior of the Wilkes Subglacial Basin interpreted as a batholithic intrusive structure, as well as a linear dense body at the margin of the Terre Adélie Craton. Density and susceptibility relationships are used to inform the interpretation of petrophysical properties and the reconstruction of the origin of those crustal blocks. The petrophysical relationship indicates that the postulated batholitic intrusion is granitic, but independent from the Granite Harbour Igneous Complex previous described in the TAM area. Emplacement of a large volume of intrusive granites can potentially elevate local geothermal heat flow significantly. Finally, we present a tectonic evolution sketch based on the inversion results, which includes development of a passive continental margin with seaward dipping basalt horizons and magmatic underplating followed by two distinct intrusion events in the Wilkes Subglacial Basin with Pan-African ages (700 - 551 Ma) and Ross ages (550 - 450 Ma).
Publisher: Springer Science and Business Media LLC
Date: 18-11-2022
Publisher: Oxford University Press (OUP)
Date: 27-08-2023
DOI: 10.1093/GJI/GGAC338
Abstract: Volgo–Uralia is the easternmost segment of the East European Craton. It accommodates the Volga–Ural petroleum province where the maturity of source rocks is tightly related to the temperature distribution in the crust. Numerous heat flow and temperature measurements have been reported for this region. However, no consistent geothermal model was presented for the Volgo–Uralian crustal block so far. In this study, we present a novel model of the Volgo–Uralian geothermal field where we aim to reconcile the reported heat flow and temperature data. The main goal of the study is to explore lateral variations of the unknown thermal parameters within Volgo–Uralia. For this purpose, we applied a Bayesian Markov Chain Monte Carlo approach where we used the known surface heat flow, surface temperature, lithosphere–asthenosphere boundary temperature and thicknesses of the Earth's lithospheric and crustal layers as input and investigated the possible lateral variations of crustal and lithospheric mantle thermal conductivities, crustal heat production and mantle heat flow. We implemented this methodology for a single-layer and multilayer crust and validated the obtained geothermal models with existing subsurface temperature measurements for the region. The results show that the Volgo–Uralian subcraton is characterized by significant lateral variations of crustal radiogenic heat production (RHP) and mantle heat flow. The variations of crustal and lithospheric mantle thermal conductivities are less pronounced. According to our model, the surface heat flow distribution is controlled mostly by crustal RHP which accounts for more than half of Volgo–Uralian surface heat flow. Validation of the models shows that single-layer and multilayer crustal models give roughly the same fit of measured and modelled temperatures. This implies that a single-layer crust with constant RHP can be considered a sufficient approximation for regional-scale geothermal modelling.
Publisher: Springer Science and Business Media LLC
Date: 26-10-2022
Publisher: Oxford University Press (OUP)
Date: 23-08-2022
DOI: 10.1093/GJI/GGAC334
Abstract: By combining gravity and magnetic data in a joint inversion approach, 3-D information on the crustal structure of Wilkes Land, East Antarctica, is obtained and possible geological features become evident. Both data sets are combined through a coupling method which decreases the variation of information (VI) so data misfit and model dissimilarity are minimized simultaneously. In this manner, statistically compatible inversion results are obtained. The suitability of the method is demonstrated through a synthetic ex le using magnetic data and pseudo-gravity. Subsequently, we apply the method to gravity residuals and magnetic data and identify matching features of high magnitude density and susceptibility. Prominent structures in NW–SE direction along the edge of the Mawson craton and at the presumed Australo-Antarctic and Indo-Antarctic terrane boundaries are enhanced. Given the structural similarity between inverted susceptibility and density, and a strong indication of a parameter relationship, we suggest a clustering approach in order to differentiate distinct groups with similar parameter properties. The spatial distribution of these clusters reveals possible geological structures that agree with previous 2-D studies and rock measurements from the Indian and Australian continents. This shows that the VI joint inversion is a convenient approach for remote regions like East Antarctica with sparse geological s les.
Publisher: Copernicus GmbH
Date: 04-03-2021
DOI: 10.5194/EGUSPHERE-EGU21-5764
Abstract: & & We established a new Geothermal Heat Flow (GHF) model for Antarctica by using a machine learning approach. GHF is substantially related to the geodynamic setting of the plates, and global geophysical and geological data sets can provide information for remote regions like Antarctica, where only sparse direct measurements exist. We applied a Gradient Boosted Regression Tree algorithm in order to build an optimal prediction model relating GHF to the observables.& br& Employed data sets are reviewed for their reliability and quality in polar regions and we emphasize the need for adding reasonable data to the algorithm. The validity of our approach is indicated by predictions for Australia, where an extensive database of GHF measurements exists. Our new estimated GHF map exhibits rather moderate values compared to previous models, ranging from 35 to 156 mWm& sup& -2& /sup& , and shows visible connections to the conjugate margins in Australia, Africa, and India.& br& Such estimates on the geothermal structure of Antarctica are for ex le needed for studies on ice sheet modeling. The internal thermal structure and the mass balance of the modeled Antarctic ice sheet (AIS) are significantly affected by the prescribed GHF distribution. & Applying a wide range of possible GHF maps within estimated uncertainties to ice-sheet-shelf set-ups, the influence of GHF on the modeled AIS response to a variety of climate scenarios is quantified.& & &
No related grants have been discovered for Mareen Lösing.