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iceTEA – Tools for Exposure Ages from ice margins

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My guest blogger today is Richard Selwyn Jones from Durham University. He developed iceTEA, a set of MATLAB tools to calculate exposure ages. He kindly accepted my invitation to write here about his software. Thanks!

iceTEA (Tools for Exposure Ages) is a new toolbox for plotting and analysing cosmogenic-nuclide surface-exposure data. The tools were originally intended for data that are used to reconstruct past glacier and ice sheet geometries, but they can potentially be used for many other geochronology and geomorphology applications of cosmogenic nuclides.

The iceTEA tools are available via an online interface (http://ice-tea.org) and as MATLAB code with a ready-to-use front-end script for each tool (https://github.com/iceTEA-code). While the online version performs all primary analysis and plotting functionality, the code provides the user with greater flexibility to apply the tools for specific needs and also includes some additional options.

There are eight tools, which provide the following functionality: 1) calculate exposure ages from 10Be and 26Al data, 2) plot exposure ages as kernel density estimates and as a horizontal or vertical transect, 3) identify and remove outliers within a dataset, 4) plot nuclide concentrations on a two-isotope diagram and as a function of depth, 5) correct exposure ages for cover of the rock surface, 6) correct ages for changes in elevation through time, and estimate 7) average and 8) continuous rates of change (e.g. ice margin retreat or thinning).

Here is an example of how you can use the code to correct data for long-term uplift:

data_name = 'input_data.xlsx';  % File name used for sample data

scaling_model = 'LSD';     % 'DE','DU','LI','ST','LM','LSD','LSDn'
 
% Set elevation correction
correction_type = 'rate';  % Select 'model' or 'rate'
GIA_model = [];            % If 'model', set GIA model to use - 'I5G' or 'I6G'
elev_rate = 2;             % If 'rate', set rate of elevation change (m/ka)

sample_data = get_data(data_name);  % Load sample data
 
% Calculate Elevation-corrected Exposure Ages
if strcmp(correction_type,'model')
    elev_input = GIA_model;
elseif strcmp(correction_type,'rate')
    elev_input = elev_rate;
end
corrected = elev_correct(sample_data,scaling_model,correction_type,elev_input);

The corrected exposure ages can then be plotted as kernel density estimates:

% Plot settings
feature = 1;    % Data from single feature?  yes = 1, no = 0
save_plot = 0;  % Save plot?  1 to save as .png and .eps, otherwise 0
mask = [];      % Select samples to plot (default is all)
time_lim = [];  % Optionally set x-axis limits (in ka)
weighted = [];  % Optionally select weighted (1) or unweighted (0) mean and standard deviation (default is weighted)
 
% Plot figure
plot_kernel(corrected.plot.corr,feature,save_plot,mask,time_lim,weighted);

iceTEA_Concs_anim-1.gif
A two-isotope diagram. Samples that plot inside the “simple exposure region” (marked by black lines) were continuously exposed, whereas samples that plot below this region have been buried in the past with a complex exposure history.
iceTEA_SurfCov_anim-1.gif
A kernel density estimate plot for exposure ages from a moraine. Individual ages are shown in light red, with the summed probability as a dark red line. One of the tools allows the user to evaluate the effects of surface cover on their dataset using different types and depths of surface cover (shown here as green summed probability lines for snow and till).
iceTEA_ContRates_anim.gif
Rates of change can be estimated using linear regression in a Monte Carlo framework, or continuously using Fourier Series analysis or Bayesian penalized spline regression. The latter is shown here. The exposure age constraints (with age and sample position uncertainties) are modelled (upper panel) in order to generate rates of change (lower panel). In this example, ice sheet thinning was most rapid at approx. 8 ka.

The purpose of these tools is to allow users to explore the spatial and temporal patterns in their data in a consistent and inter-comparable way, and also to initiate discussion of further improvements in the application and analysis of surface-exposure data. We welcome suggestions for additional plotting or analysis tools.

Reference

Jones, R.S., Small, D., Cahill, N., Bentley, M.J. and Whitehouse, P.L., 2019. iceTEA: Tools for plotting and analysing cosmogenic-nuclide surface-exposure data from former ice margins. Quaternary Geochronology, 51, 72-86. [DOI: 10.1016/j.quageo.2019.01.001]

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Two PhD positions “Elevated Low Relief Landscapes in Mountain Belts: Active Tectonics or Glacial Reshaping? A Case Study in the Eastern Alps”

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Two PhD positions within the FWFproject “Elevated Low Relief Landscapes in Mountain Belts: Active Tectonics or Glacial Reshaping? A Case Study in the Eastern Alps

This project will focus on the evolution of elevated low relief landscapes (plateaus) in active mountain ranges. The project is funded by the Austrian Science Fund (FWF) and the government of Salzburg for a period of three years and will commence in March 2019. Details of the research project are available under: www.geodynamics.at.

Duration of the employment

The two PhD positions will be fully financed for 36 months. In accordance with the Collective Labour Agreement for Austrian Universities in Austrian (§ 26 “Kollektivvertrag für die ArbeitnehmerInnen der Universitäten“ Verwendungsgruppe B1), a salary of € 2,096,00 gross per month (14 x) for a 30-h / week employment.

Desired skills and experience

The successful candidate should have:

Obligatory:

  • Master’s degree (or equivalent) in Geology, Geomorphology, Geophysics, Geochemistry, Computational Science

Excellent skills and practical experience in one or more of the following research areas:

  • experience in numerical simulationtools and programming skills (e.g. C++, Fortran, Python, R, Matlab…)
  • ability to work in rugged alpine terrain and caves
  • experience with lab-work and chemical preparation of rock samples
  • knowledge of the principles of earthsurface dynamics (in particular the interaction of processes driven by climate and tectonics)
  • autonomous and proactive working
  • written and spoken English proficiency
  • skills in dissemination of scientific results (e.g. writing scientific publications)
  • flexibility and the ability to workin a team

Specification of the main focus of the two PhD positions:

  • PhD-candidate A will work at the University of Salzburg under the supervision of Jörg Robl.She/He will focus on morphometry and landscape evolution modelling (glacialerosion). A stay abroad at Aarhus University (David Egholm) is planned. For this position we seek for an ambitious young scientist with a strong affinity to numerical modeling. Experience with field work in alpine environments is an advantage.
  • PhD-candidate B is based in Graz and will work under the supervision of Kurt Stüwe. She/He willfocus on cosmogenic nuclide dating of cave sediments. A stay abroad at the SUERC Glasgow (Derek Fabel, Fin Stuart) is planned. For this position we seek for a motivated researcher with a strong affinity to lab work and caves. The ability to work in rugged alpine terrain and caves is a prerequisite.

A tight cooperation between all team members is expected. Amongst others this will include joint field work in the Eastern Alps, meetings in Salzburg and Graz, GIS and modelling workshops, conference visits, and paper writing.

The Application should include:

  • letter of motivation for the desired position (PhD-A: Salzburg or PhD-B: Graz)
  • CV (academic career, scientific publications, research interests, skills)

The applications can be submitted until December 31 to the following Email address: joerg.robl@sbg.ac.at

Open Ph.D. position at the University of Roma

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Here is an advertisement for an open PhD position at the University of Roma for a project led by Paolo Ballato and Claudio Faccenna. I am collaborating in the project.

Ph.D. position at the Department of Science (Section Geology) of the University of Roma

Deciphering the Mantle Contribution on Surface uplift in the Atlas-Meseta system (Morocco).

The idea that mantle flow dynamics may contribute to the topographic development of orogens has changed our vision on mountain building processes and inspired an increasing number of modelling studies. Isolating and documenting such a contribution however, has been proved to be difficult, especially in continental settings where the paleontological record is not as determinant as in marine systems. This research proposal aims to decipher the influence of mantle flow on the topographic growth of the Atlas-Meseta system of Morocco. There, the occurrence of several hundred of meters of mantle driven uplift, offers the possibility to investigate magnitude, timing and rates of surface uplift, by means of a multidisciplinary approach involving recent advancements on stratigraphy, geomorphology, geochronology, and low-temperature thermochronology. The outcome of this field- and laboratory-based approach will be finally integrated for developing an analogue geodynamic model and gain more insights into the mechanisms of mantle flow. Specifically, the candidate student will quantify longitudinal and latitudinal spatio-temporal patterns of surface uplift and regional tilting induced by mantle flow along two transects across the Atlas-Meseta system. In addition, the expected results will provide geological information that will be used for calibrating a final geodynamic analogue model, which will be of general interest for unravelling the evolution of mountain belts that are not supported by orogenic roots.

Supervisors

Paolo Ballato and Claudio Faccenna (University of Roma Tre)

Collaborators

Taylor Schildgen (GFZ Poytsdam), Wolfgang Schwanghart (University of Potsdam), Giuditta Fellin (ETH Zurich), Francesca Funiciello and Federico Rossetti (University of Roma Tre)

Requirements

The successful candidate must have high motivation, a MSc degree in Geology, Earth Sciences or equivalent, solid basic knowledge in field geology, geomorphology, stratigraphy and tectonics. Basic knowledge in ArcGIS and MATLAB are also required. Applicants must be also proficient in spoken and written English and have teamwork skills.

Information and application

To apply, please send a cover letter clarifying your overall motivation together with your curriculum vitae and names, telephone numbers, and e-mail addresses of two referees to Paolo Ballato (paolo.ballato@uniroma3.it), before June 18th.

Conditions of employment

The project will start on November 1st as part of the University of Roma Tre Ph.D. programme (34th cycle) and will last 3 years. The scholarship has an annual amount of 13.638,47 Euro (social security fee included) and is increased (+50%) for periods of study or research abroad.

If you have any questions regarding this offer please feel free to contact Paolo Ballato (paolo.ballato@uniroma3.it) and/or Claudio Faccenna (claudio.faccenna@uniroma3.it).

TopoToolbox 2.2 released

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The last weeks had been quite busy to finish version 2.2 which was available as a prerelease for a long while. TopoToolbox users who keep their software constantly updated (for example by using GIT) won’t see much changes.  For those that do not keep pace with the frequent commits to our repository, we encourage them to do so now. There are a lot of new functions and modifications. Benjamin Campforts added TTLEM, the TopoToolbox Landscape Evolution Model. The scope of functions for working with river networks (STREAMobj) has tremendously increased with new plotting functions, low-level chi analysis tools, and tools for geometric modifications. We added new functions to hydrologically correct and smooth river networks and values measured along them (e.g. constrained regularized smoothing (CRS)). TopoToolbox now supports multiple flow directions and there are several new functions for working with grids (GRIDobj). In addition, we consolidated the help sections in each function and increased compatibility with older MATLAB versions. Please see the readme-file for a complete overview of changes.

With version 2.2, we offer TopoToolbox as a MATLAB® toolbox file (mltbx-file). This file will make installation very easy. Simply download it, double-click, and follow the instructions.

Dirk and I met this morning in the train (here we are!) …

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Dirk (left) and I taking a selfie…

… and discussed possible directions for a next version. The number of functions has increased a lot which entails the threat that TopoToolbox might become confusing and even deterrent in particular for new users. Simply adding new functionalities is thus not the way forward. Instead, we decided that a new version should have a better documentation that should be integrated in MATLABs documentation browser. To quote John D’Errico, a long-time and excellent contributor of MATLAB code: Your job as a programmer does not stop when you write the last line of code. If you think so, then you should be fired. You should document your code. Provide help. Otherwise, that code is just a bunch of random bits, useful to nobody else in the world.

With this in mind, let’s go for 2.3.

Geomorphometry Short Course at the EGU 2017, Vienna

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Only few days left until the EGU begins, the largest European annual geoscience meeting in Vienna. In case you attend you should consider to participate the short course in geomorphometry: Getting the most out of DEMs of Difference. The course is organized by Tobias Heckmann, Paolo Tarolli and me and will be on Wednesday, 26 April, 13:30-15:00 in Room N1.

Please see here for further details on the course’s aims and scope.

Short courses on the analysis of elevation data at the University of Potsdam

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Two short courses are scheduled for mid June at Potsdam University. The short courses are independent of each other; however, the topics are related and probably address a similar audience.

Geoscience investigations of point clouds, June 7-9, 2017. Instructors B. Bookhagen, R. Arrowsmith, M. Isenburg, C. Crosby.

This course will explore the acquisition, post-processing, and classification of point clouds derived from airborne and terrestrial lidar scanners and structure from motion (SfM) photogrammetry from drones. The course will take place at campus Golm (UP) and includes one day of field-data collection and two days of data post-processing and analysis.
The application is here: https://goo.gl/forms/NrRAcaASXPuseRs62. The course is sponsored by Geo-X.
Here is the flyer: PDF for more details.

Advancing understanding of geomorphology with topographic analysis emphasizing high resolution topography, June 12-15, 2017. Instructors R. Arrowsmith, W. Schwanghart, C. Crosby, B. Bookhagen.

This course will focus on advanced understanding of geomorphology with topographic analysis emphasizing high-resolution topography. The course will take place at campus Golm (UP) and includes theoretical background and analysis of digital topography using TopoToolbox in a Matlab environment. The course is sponsored by StRATEGy.
Here is the flyer: PDF for more details.

I’d be glad to see you in Potsdam!

Chimaps in a few lines of code (5)

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Having prepared a stream network and equipped with a reasonable value of the m/n ratio, we are now ready to plot a chimap that visualizes the planform patterns of chi. The main interest in these maps lies in chi values near catchment divides as large differences between adjacent catchment would indicate a transient behavior of drainage basin reorganization.

Some of you might have already experimented with TopoToolbox to create chimaps. Perhaps you became exasperated with the function chiplot that is restricted to calculations with only one drainage basin and has a bewildering structure array as output. The reason for the confusing output of chiplot is that it is fairly old. At this time, I hadn’t implemented node-attribute lists that are now more common with STREAMobj methods.

Realizing this shortcoming of chiplot, I wrote the function chitransform. chitransform is what I’d refer to as a low-level function that solves the chi-equation using upstream cumulative trapezoidal integration (see the function cumtrapz). chitransform requires a STREAMobj and a flow accumulation grid as input and optionally a mn-ratio (default is 0.45) and a reference area (default is 1 sqkm). It returns a node-attribute list, i.e., a vector with chi values for each node in the STREAMobj. Node-attribute lists are intrinsically tied to the STREAMobj from which they were derived. Yet, they can be used together with several other TopoToolbox functions to produce output.

Ok, let’s derive chi values for our stream network:

A = flowacc(FD); % calculate flow accumulation
c = chitransform(S,A,'mn',0.4776);

In the next step, we will plot a color stream network on a grayscale hillshade:

imageschs(DEM,[],'colormap',[1 1 1],'colorbar',false,'ticklabel','nice');
hold on
plotc(S,c)
colormap(jet)
colorbar
hold off

chimap_07_chimap
Chimap of the Mendocino Triple Junction.

Interestingly, there seem to be some locations with quite some differences in chi values on either side of the divide. “Victims” seem to be rather elongated catchments draining northwest. Let’s zoom into one of these locations.

chimap_08_detail
Detail of the chimap with arrow indicating the expected direction of divide migration.

Are these significant differences? Well, it seems by just looking at the range of values. However, to my knowledge no approach exists that provides a more objective way of evaluating the significance of contrasting chi values and their implications about rates of divide migration. Still, we now have a nice map that can aid our geomorphic assessment together with the tectonic and geodynamic interpretation of the Mendocino Triple Junction.

Unfortunately, I must leave the discussion to you since I am quite unfamiliar with the region. If anyone wants to share his or her interpretation, I’d be more than happy to provide space here. So far, I hope that these few posts on chimaps were useful to you and sufficiently informative to enable you to compute chimaps by yourself. In my next post, I will give a short summary and show with another example that eventually chimaps can be derived really in a few lines of code.