Jon Harbor

Towards a GIS assessment of numerical ice-sheet model performance using geomorphological data

A major difficulty in assimilating geomorphological information with ice-sheet models is the lack of a consistent methodology to systematically compare model output and field data. As an initial step in establishing a quantitative comparison methodology, automated proximity and conformity analysis (APCA) and automated flow direction analysis (AFDA) have been developed to assess the level of correspondence between modelled ice extent and ice-marginal features such as end moraines, as well as between modelled basal flow directions and palaeo-flow direction indicators, such as glacial lineations. To illustrate the potential of such an approach, an ensemble suite of 40 numerical simulations of the Fennoscandian ice sheet were compared to end moraines of the Last Glacial Maximum and the Younger Dryas and to glacial lineations in northern Sweden using APCA and AFDA. Model experiments evaluated in this manner were ranked according to level of correspondence. Such an approach holds considerable promise for optimizing the parameter space and coherence of ice-flow models by automated, quantitative assessment of multiple ensemble experiments against a database of geological or glaciological evidence.

Water Transformation and Storage in the Mountains and at the Coast: Midwest Students' Disconnected Conceptions of the Hydrologic Cycle.

The purpose of the present study was to investigate students’ conceptions of the hydrologic cycle and to examine whether these conceptions vary by grade level and community setting. This study was descriptive in nature and reflected a cross‐age design involving the collection of qualitative data from 1,298 students from the Midwest, USA. These data were analysed for content in an inductive manner to identify student’s conceptions, and statistical analysis was used to determine the significance in the frequency of these student conceptions. Four categories emerged that reflected different degrees of sophistication of students’ conceptions of water transformation, movement, and storage. These Midwest students often portrayed the hydrologic cycle in the context of mountain or coastal landscapes that are common in textbooks but that are not representative of the environments where students live and where many of these students might apply their understanding of environmental systems as adults. Based on these findings, we make curricular recommendations that build on the students’ conceptions, the hydrologic concept, and the National Research Council science education standards.

Identifying patterns of correspondence between modeled flow directions and field evidence: An automated flow direction analysis

Comparison of numerical model output that predicts spatial flow patterns against field observations is a necessity within several areas of the geosciences. However in many cases these comparisons are qualitative or relative in nature. Automated flow direction analysis (AFDA) is a new method designed to provide a systematic comparison between modeled flow patterns and field observations, with particular focus on two-dimensional linear features representing flow directions of natural phenomena. By subtracting vector output of time-dependent models from field-observed directions, the resultant mean residual and variance of the offset between these data sets can be used to identify patterns of correspondence and variation between model-predicted directions and field observations. The technique is demonstrated by comparison of modeled basal ice flow directions of the Fennoscandian Ice Sheet with observed lineations mapped in Northern Sweden. In this example, the analysis provides an effective means to quantitatively validate the modeled basal thermal and flow regime with observed glacial lineations. The technique has potential applications in a wide range of flow vector direction comparisons in the geosciences, for example lava flow, landslides, aeolian and fluvial processes.