Task 1: Initial data integration and browsing

The main goal of the first task is to provide an opportunity to familiarize yourself with the data. As outlined above, we provide three primary data modalities, MIPAS, AIRS, and CLaMS. In this first task, you should create a basic overview visualization which integrates all three modalities in a common reference frame. This task should provide the basis for the more domain-centric tasks below, i.e. here you will have to establish and explain the fundamental design decisions of your visualization. Questions to be answered include but are not limited to:

Task 2: How can MIPAS detections be linked to eruption events?

In this task, we are interested in associating MIPAS detections to their original eruption events, i.e. for each MIPAS measurement we would like to know from which eruption it is (potentially) coming.

Task 2a: How can the temporal evolution of eruption events be visualized?

The MIPAS data alone will not be sufficient for a visualization of the temporal evolution of the plume, because it only consists of point measurements. In order to fill the gaps between the individual detections you can use the quasi-continuous CLaMS trajectories. This data contain one backward trajectory, going back to the initial eruption time of the respective volcano, and a 5-day long forward trajectory for each MIPAS volcanic ash and sulfate aerosol detection. In order to associate CLaMS and MIPAS data, we suggest to map MIPAS detections to one hour intervals and cross-reference these intervals with the trajectory data. Ultimately, you should demonstrate your methods by creating a continuous visualization of the temporal evolution of the Puyehue-Cordón Caulle volcanic ash plume which only relies on MIPAS and CLaMS data.

Task 2b: How can the Grímsvötn and Nabro eruptions be separated?

The ash cloud from the Puyehue-Cordón Caulle eruption stands out rather prominently, because no other events occurred in that time frame in the southern hemisphere. In contrast, in this task we would like to ask you to separate the sulfate aerosol clouds originating from the Grímsvötn and Nabro eruptions, respectively, which both occured in the northern hemisphere. Hence, detections from both eruptions might overlap. Use the CLaMS trajectories, altitude, and latitude information to separate both clouds. Demonstrate your classification capabilities by masking out the data belonging to the Grímsvötn eruption.

Task 3: What does AIRS add to the overall picture?

As outlined in the data description, MIPAS and AIRS are rather different instruments with individual strengths and weaknesses. In particular, AIRS provides contiguous satellite imagery whereas MIPAS data consists of point measurements; yet MIPAS features solid altitude information, AIRS doesn't. Moreover, MIPAS is more sensitive to lower particle concentrations. Therefore it is able to detect lower ash particle concentrations in contrast to AIRS. For the same reason MIPAS can also detect sulfate aerosol particles, whereas AIRS is sensitive to the particle precursor gas SO2. In this task, we ask you to create a visualization that gives domain experts access to the best of both worlds by integrating the two data modalities.

Based on your design, assess in how far the two instruments agree. Do you observe significant differences between AIRS SO2 and MIPAS sulfate aerosol measurements or between AIRS and MIPAS ash detections, respectively? Can you use the additional information gleaned from MIPAS to eliminate mineral dust clouds identified by AIRS? Finally, can you use the MIPAS altitude data to pinpoint the vertical extent of AIRS detections? Based on this information, can you create a 3D visualization of the respective cloud?

Task 4: How did the eruption of Puyehue-Cordón Caulle affect air traffic?

Please focus on the ash cloud resulting from the Puyehue-Cordón Caulle eruption. Due to this cloud, the airspace in the southern hemisphere was closed in South America, Australia, and New Zealand several times. Can you track the cloud's evolution around the southern ocean? Use the relevant MIPAS, AIRS, and CLaMS data in order to mark potentially dangerous corridors through June 2011, i.e. both their horizontal and vertical extent. You should regard any significant, contigous AIRS ash detection as potentially dangerous. Yet, please note that AIRS is not as sensitive to ash detections as MIPAS and suffers from some data gaps between tracks. Moreover, it does not provide any altitude information. Thus, simply thresholding AIRS clouds is not sufficient to profoundly answer this question.

You might want to compare your findings to the official warnings of the Volcanic Ash Advisory Centres (VAACs).

However, due to the fact that this data is only partially available and tricky to extract, we would like to stress that the VAAC comparison is stricly optional, i.e. we will not downgrade any submissions that do not include it.

Task 5: How did Nabro aerosol enter the stratosphere?

Now let us move on to the Nabro sulfate aerosol. There is an ongoing controversial discussion on how the Nabro sulfate aerosol entered the stratosphere.

In a recent publication the aerosol's upward motion within the Asian Monsoon circulation is presented as the sole pathway into the stratosphere. However, there are several indications (e.g. here and here) that the volcanic emissions were directly injected into the stratosphere. Use the MIPAS detections, the trajectory data, and the given tropopause altitudes to show the position of the aerosol detections with respect to the tropopause. Locate the positions where the trajectories intersect the first (lower) tropopause. What do these locations tell you regarding the aforementioned hypotheses? How do potential vorticity (PV) and potential temperature (theta) of the detection change with time and along the trajectories? Both measurements can be used to discriminate between tropospheric and stratospheric air. By analyzing the temporal evolution of these variables along trajectories one can figure out if there were vertical transport processes involved. For example, if there is no vertical transport, theta remains (almost) constant along a trajectory, although the altitude may change. Actually, if there is vertical transport, it would be interesting to see where the largest gradients in theta can be found.

This is a more open-ended task in which we encourage you to delve deeper into the underlying data and find out anything that might be of significance. It offers you the opportunity to contribute to an ongoing scientific dispute. Make your visualization count!