| 1. |
- Griffiths, PG, et al.
(författare)
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Spatial precipitation frequency of an extreme event: the July 2006 mesoscale convective complexes and floods in southeastern Arizona
- 2009
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Ingår i: Water resources research. - 0043-1397 .- 1944-7973. ; 45:W07419
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Tidskriftsartikel (refereegranskat)abstract
- An extreme, multiday rainfall event over southeastern Arizona during 27–31 July 2006 caused record flooding and a historically unprecedented number of slope failures and debris flows in the Santa Catalina Mountains north of Tucson. An unusual synoptic weather pattern induced repeated nocturnal mesoscale convective systems over southeastern Arizona for five continuous days, generating multiday rainfall totals up to 360 mm. Analysis of point rainfall and weather radar data yielded storm totals for the southern Santa Catalina Mountains at 754 grid cells approximately 1 km 1 km in size. Precipitation intensity for the 31 July storms was not unusual for typical monsoonal precipitation in this region (recurrence interval (RI) < 1 year), but multiday rainfall where slope failures occurred had RI > 50 years and individual grid cells had RI exceeding 1000 years. The 31 July storms caused the watersheds to be essentially saturated following 4 days of rainfall.
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| 2. |
- Juter, Kristina
(författare)
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University students linking limits, derivatives, integrals and continuity
- 2011
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Ingår i: Proceedings of the seventh congress of the European Society for Research in Mathematics Education (CERME 7). ; , s. 2043-2052
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Bokkapitel (populärvet., debatt m.m.)abstract
- Mathematical concepts are mentally represented differently depending on individual, context and existing conceptions of related concepts among other things. The present paper reports on a study of students‘ representations in analysis with an emphasis on the types of representations and the links they have between their representations. The data collection was designed to evoke different parts of the students‘ concept images and also to return to the concepts several times over time at every data collection session. The results show that formal and intuitive representations in combination are rare. The number of links between concepts is not in itself a measure of the quality of the concept image, as there is a vast number of erroneous links misleading the students to think they understand the concepts.
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| 3. |
- Lyon, Steve, et al.
(författare)
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Combining radar and rain gauges to capture the space-time variability of monsoon rainfall during an extreme flood event
- 2008
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Ingår i: EGU General Assembly.
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Konferensbidrag (refereegranskat)abstract
- Monsoon rainfall events are typified by high spatial and temporal variability in both rainfall amount and intensity. Monsoon rainfall events occurring in Tucson, AZ, USA over seven consecutive days in July, 2006 lead to the highest ever recorded stream flows in Sabino Canyon Creek and resulted in flash flooding that caused large-scale property damage. Concurrent to these monsoon events, a network of 40 tipping bucket rain gauges were in place throughout the Sabino Canyon Creek watershed. In addition to this rain gauge network, radar data (NEXRAD) was collected during this monsoon period and used to derive rainfall accumulation maps with at 15-minute temporal resolution and 1 km2 spatial resolution. An event based, kinematic-wave overland flow runoff model (KINEROS) was used to model stream flow in Sabino Canyon Creek for the largest of the flooding events using rainfall data from both rain gauge observations and radar estimation. While the modeling results based solely on rain gauge observations agreed well with observed flow, the results were highly reliant on the extent of the spatial coverage of the rain gauge network. To overcome the reliance, geostatistics (kriging with external drift) were used to combine the rain gauge data with the radar data. By combining these two datasets, we could compensate for restricted spatial coverage in the rain gauge network. This allowed for high quality modeling of the flood event even with a great reduction in the spatial extent of the observational rain gauge network. Techniques to combine data from rain gauge networks and radar estimates are quite valuable as the development of real-time rain gauge network with good spatial extent and high spatial density is difficult and costly.
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