The latest issue of Scientific Computing World has a nice 3-page article on Scientific Visualization, based on some classes and tutorials at recent events. They start off with a typical SciVis pipeline (Kudos to them for actually including “postprocess” after Render, so many groups stop at Render), and discuss several commercial and freely available package ranging from IDL to VTK.
If you’re already a SciVis guru then you probably won’t get much from it, but it’s a great article for scientists or newcomers to see what’s available.
The NOAA Center for Tsunami Research has released a video of the tsunami propagation in the Pacific Ocean.
Propagation of the March 11, 2011 Honshu tsunami was computed with the NOAA forecast method using MOST model with the tsunami source inferred from DART® data. From the NOAA Center for Tsunami Research, located at NOAA PMEL in Seattle, WA
A star acquires much of its mass by accreting material from a disc. Accretion is probably not continuous but episodic. We have developed a method to include the effects of episodic accretion in simulations of star formation. Episodic accretion results in bursts of radiative feedback, during which a protostar is very luminous, and its surrounding disc is heated and stabilised. These bursts typically last only a few hundred years. In contrast, the lulls between bursts may last a few thousand years; during these lulls the luminosity of the protostar is very low, and its disc cools and fragments. Thus, episodic accretion enables the formation of low-mass stars, brown dwarfs and planetary-mass objects by disc fragmentation. If episodic accretion is a common phenomenon among young protostars, then the frequency and duration of accretion bursts may be critical in determining the low-mass end of the stellar initial mass function.
Phytoplankton are small organisms that live in both fresh and salt water, and many of them are single-celled plants. That makes them too small to be seen individually with the naked eye. However, when there are enough of them in the water, it can give the water a green color. Large enough concentrations can even be seen by satellite.
Phytoplankton are important because they are responsible for half of the total amount of oxygen produced by all plant life. They are eaten by krill, which in turn are eaten by whales. Thus they are also important in the food chain.
NASA has used their MODIS satellite to look at the chlorophyll concentration, as well as the sea surface temperature from the coast of Maine up to Nova Scotia. The images show that more Phytoplankton are growing to the north in the cooler waters, rather than the warmer waters of the Gulf Stream. It is interesting to see that in both images, you can see the eddies formed by the Gulf Stream as it heads towards Europe.
These images show one of those rich mixing basins: the northwest Atlantic Ocean. Based on data collected by the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Aqua satellite, these maps show the concentration of chlorophyll (top) and sea surface temperatures (bottom) in the region from August 29 to September 5, 2010.
After experiencing their warmest year on record, many of the southern and western areas of Greenland also had the longest number of days that snow melted. The snow melt in 2010 lasted lasted 50 days longer than the 1979-2009 average snow melt normally does. In the image to the right, areas in orange and red experienced longer snow melt days while areas in light blue had fewer snow melt days. Good luck finding the light blue areas. Unless you click on the image to make it larger, I doubt that you will be able to see them. Since the light blue areas occur at the very edges of the data, and since they occur right next to some of the highest snow melt days, I suspect that they may be artifacts in the data, and not true values.
Since this is fresh water that is melting, the seas around Greenland have a slight decrease in salinity. The melting of this snow may also increase global sea levels, although scientists do not know to what extent this will occur. Some scientists think that it could increase the global sea level by up to 0.6 meters or about two feet.
This image was assembled from microwave data from the Special Sensor Microwave/Imager (SSM/I) of the Defense Meteorological Satellites Program. Snow and ice emit microwaves, but the signal is different for wet, melting snow than for dry. Marco Tedesco, a professor at the City College of New York, uses this difference to chart the number of days that snow is melting every year. This image above shows 2010 compared to the average number of melt days per year between 1979 and 2009.
Both Wired and the NYTimes have small galleries up of the winning entries in the 2010 International Science & Engineering Visualization Challenge. A bit heavy on the biological visualizations this year (several virus entries and such), the resulting pictures and videos truly are beautiful to behold.
Wes Bethel (Lawrence Berkeley National Laboratory) , Kelly Gaither (TACC), Hank Childs (Lawrence Livermore National Laboratory), and Sean Ahern (Oak Ridge National Laboratory) are among the leaders today in the visualization community. They, along with John van Rosendale, Dale Southard, and Eric Brugger, have published a whitepaper titled: Visualization From the Skinny Guys at Big Supercomputer Centers. The report takes a look at the importance of the role of data analysis, or scientific visualization, in understanding the results that come from high performance computing systems. Some of the questions that they cover are of particular interest. For example, one question that they ask is whether or not data analysis hardware needs to be separate from the HPC systems, or integrated into the HPC systems. Another question they examine is how large should the data analysis staff be at a Supercomputing Center. Here’s a hat tip to InsideHPC for bringing this whitepaper to our attention.
Supercomputing Centers are unique resources that aim to enable scientic knowledge discovery through the use of large computational resources, the Big Iron. Design, acquisition, installation, and management of the Big Iron are activities that are carefully planned and monitored. Since these Big Iron systems produce a tsunami of data, it is natural to co-locate visualization and analysis infrastructure as part of the same facility. This infrastructure consists of hardware (Big Iron) and staff (Skinny Guys). Our collective experience suggests that design, acquisition, installation, and management of the Little Iron and Skinny Guys does not receive the same level of treatment as that of the Big Iron.
Earlier this year we told you that a La Niña event was starting to occur. A La Niña event is when the water is cool across the equatorial Pacific Ocean. An El Niño event is when the water is warm across the equatorial Pacific Ocean, and is the opposite of a La Niña. These two events are important because both the La Niña and El Niño can affect weather systems across the Pacific Rim and beyond. Both events are commonly called the El Niño/La Niña-Southern Oscillation, or ENSO.
In the image to the right, we can see where cool water (shown in blue), stretches across the equatorial region of the Pacific Ocean. Earlier this year it is not a uniform deep blue, and instead had pockets of warm water contained within it. Now the image shows a strong, uniform deep blue indicating a strong La Niña event.
La Niña’s cold water signal is strong in the top two images. The left image shows ocean surface temperatures on December 15, 2010, as measured by the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) on NASA’s Aqua satellite. In December 2010, sea surface temperatures were colder than average across the equatorial Pacific.
Winter-like weather has arrived in the northern hemisphere. But is this winter colder than past ones, or warmer? That is the question NASA seeks to answer with this latest visualization. They have taken temperature measurements using the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Aqua satellite. Then they compared the week of December 3-10, 2010 to the average of the same week from 2002 to 2009. Red indicates areas that are warmer than the average, and blues represent areas that are colder than the average. What caused Greenland and parts of Canada to be warmer than average, while northern Europe was cooler than normal? In short, it was the Arctic Oscillation.
The Arctic Oscillation is a climate pattern that influences winter weather in the northern hemisphere. It describes the relationship between high pressure in the mid-latitudes and low pressure over the Arctic. When the pressure systems are weak, the difference between them is small, and air from the Arctic flows south, while warmer air seeps north. This is referred to as a negative Arctic Oscillation. Like December 2009, the Arctic Oscillation was negative in early December 2010. Cold air from the Arctic channeled south around a blocking system over Greenland, while Greenland and northern Canada heated up.
NASA’s Image of the Day shows how our reliance on plants is increasing. From 1995 to 2005, human’s reliance on plants increased from 20.3 percent to 25.6 percent. This is due in part to population growth, as well as people using more plant products.
This map shows the comparison for 2005. The colors represent the ratio between the amount of carbon people require and the amount of carbon Earth produced. At the top of the scale (dark red), the population needs at least ten times more plants than are grown locally. At the lower end of the scale (dark green), the land produces more vegetation that the local population needs. Gray areas are places where people in the area use less than 10 percent of the vegetation growing there. In the center of the scale (pale yellow) people use most of the vegetation.
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