17 May, 2006
Atmospheres and Impact: Mars
Meteoritic impact cratering on planetary bodies has long been used to infer surface ages and geologic processes and histories on planetary bodies. However, the very different appearances of the surfaces of the Earth and Moon attest to the effects atmospheres can have on incoming meteoroid populations. In this talk I will describe how impact cratering can also be used to study the histories atmospheres. I will also show that meteorite accumulation can be used to for all of the same purposes cratering can. Finally I will present what one meteorite has to say aboutMars's atmosphere.
7 June, 2006
Arctic air temperature, precipitation, ground temperature, river runoff, clouds, and radiation are all changing quickly in a warming climate. Interactions and feedbacks between these features are not well understood. In particular, the relative role of local climate processes and large-scale ocean-atmosphere dynamics in driving observed Arctic changes is difficult to ascertain because of the sparsity of observations, inaccuracy of those that do exist, biases in global circulation models and analyses, and fundamental physics of the Arctic region.
This talk will explore four studies of Arctic hydrolimatology:
1.Theanalysis of the Lena river basin hydroclimatology, shows canonical acceleration of the hydrologic cycle and amplification of global warming.
2 & 3. The second two studies describe the development of the Pan-Arctic Snowfall Reconstruction (PASR). This product addresses the problem of cold season precipitation gauge biases for 1940-1999. The NASA Interannual-to-Seasonal Prediction Project Catchment-based Land Surface Model is used to reconstruct solid precipitation from observed snow depth and surface air temperatures.
4. The final work is a case study on hydroclimatological variability driven by a large-scale model of climate, the North Atlantic Oscillation (NAO). The model offers a possible tool for predicting the effects of future NAO variability on hydropower production and energy prices in Scandinavia.
21 June, 2006
5 July, 2006
Ocean Internal Wave Generation by Tidal Forcings
I will describe some elementary theories and concepts of internal waves in stratified fluid. Then I will show some preliminary simulation results (using MITgcm) of ocean internal waves generation by tidal forcings. I will also discuss future research plan and aims of the current work.
Ash Dispersion Modeling of North Pacific Volcanoes
There are over 100 active volcanoes in the North Pacific (NOPAC) Region which includes those on the Aleutian Islands, Alaska Peninsula, Alaska mainland, and the Kamchatka Peninsula and Kurile Islands, Russia. The region is remote and vast but sparsely populated. These volcanoes pose a serious threat to the local communities, and to transcontinental air traffic throughout the Arctic and sub-Arctic region. The Alaska Volcano Observatory (AVO) operationally monitors these volcanoes and is a joint program of the United States Geological Survey (USGS), the Geophysical Institute of the University of Alaska Fairbanks (UAFGI), and the State of Alaska Division of Geological and Geophysical Surveys (ADGGS). Satellite data are used to monitor all of the Alaskan volcanoes and others in the NOPAC. This data is recorded periodically and analysis can be made in real-time (e.g. automated alarms to detect potential activity). The data are analyzed several times a day by the AVO Remote Sensing group to detect hot spots and eruption clouds. During heightened alert, the remote sensing data is analyzed four times a day and during an eruption, 24 hours a day. In addition, to the satellite data, a volcanic ash dispersion model, Puff is used routinely to track the ash clouds from volcanic eruptions. This dispersion model is used by AVO, NWS, AAWU and AFWA. The model uses information on the volcanic eruption such as eruption duration, size of ash plume and start time (from satellite or seismic data) to track the ash cloud released from the eruptive event. Mesoscale meteorological forecast models are used as initialization for the Puff wind fields.
An example of volcano monitoring and analysis will be presented for the eruption of Augustine Volcano, which is an active volcano in the Lower Cook Inlet, 275 km SW of Anchorage, Alaska. Augustine became seismically active with subtle ground inflation starting in May 2005. On 12 December a 75 km long, low level gas plume was observed blowing to the SE. Airborne thermal imaging detected increased surface heating in early January. The volcano erupted multiple times between 11 - 28 January sending ash clouds up to 40,000 feet. The 13th and 14th eruptions consisted of six separate events resulting in 6 simultaneously drifting ash clouds in the Alaska region. From 28 January to 4 February the volcano was in a state of continuous eruption. After this period, activity decreased. Data from three groups of satellites: GOES, AVHRR and MODIS were analyzed using visible and infrared wavelengths from time sequential data sets. Animations showing the dispersion of the ash clouds were simulated using the Puff model. This presentation will focus on (1) providing a description of the Puff model and how it is used operationally, (2) the detection and analysis of volcanic clouds observed on satellite data with attention to the Augustine 2006 event and (3) some of the future developments in Puff (including implementation of model forecasts into Google Earth) looking at its use operationally and as a research tool.
If a Volcano Erupts in Aleutians and it’s covered by cloud, does anyone see it?
The ability to mitigate the human impact of volcanic eruptions is intrinsically linked to how quickly volcanic events can be detected, or preferably how much warning time can be given prior to an eruption. However, the problem in Alaska is that over 100 potentially active volcanoes are spread over almost 3000 km, with many located in remote and inhospitable locations. These conditions mean that less than 1/3 of these volcanoes are monitored using permanent instrumentation, leaving remote sensing using satellites as the only viable method to watch for activity.
Using its own AVHRR and MODIS satellite receiving stations, and GOES data feeds from the Naval research Laboratory, the Alaska Volcano Observatory Remote Sensing Group maintains daily monitoring operations of Alaska’s volcanoes. Of particular interest are thermal anomalies or hotspots, one or more pixels with elevated temperature values relative to surrounding area, that are found coincident with the locations of volcanoes. Hotspots frequently occur as precursors to eruptions. The size, shape, radiant intensity and temporal behavior of a hot spot at an active volcano can provide information on the style of volcanic and/or type of volcanic features (e.g., active lava lake, lava dome growth, effusive lava flow, strombolian explosion). However, hotspots can also result from geothermal or solar heating effects, or can be subdued by intermediate cloud, making the assessment of thermal anomalies a more complex task.
Automated hotspot detection algorithms have been developed by AVO Remote Sensing. Current efforts are concentrated on providing techniques that allow clear and easy visualization of these data. One current area of research uses Google Earth to visualize detected hotspots and other volcanic features (e.g., plumes) relative to the landscape. AVO Remote Sensing, in partnership with ARSC, is at the forefront of developments in this field, as the ability of Google Earth to provide both a scientific monitoring and educational tool is being increasingly recognized by scientists and the public alike.
" Fluid Flow in Sea Ice"
The fluid permeability (aka hydraulic conductivity) of sea ice dictates whether snow melt on the surface of sea ice forms pools or drains to the ocean below. As such, it is key to understanding seasonal changes in the albedo of sea ice, and therefore its heat balance and role in climate feedbacks. The permeability is governed by the temperature-dependent connectivity of the volume of brine that is entrained in sea ice when it forms.
In this talk, I’ll start with an introduction to sea ice formation and properties, and move through to a description of our approach to modeling fluid flow with Lattice Boltzmann methods.