In the context of atmospheric models, operational systems are those that dependably provide important, time-critical forecasts for use in decision-support systems. They are characterized by the need for rapid data acquisition and model setup, reliable execution of the model, and post-processing activities that sometimes require delivery of model output timesteps as soon as they are completed. In Alaska, reliable and timely weather forecasts are essential for a variety of commercial, recreational, and simple day-to-day living activities. In addition to routine operational forecasting, Alaskans need to be prepared for surprise events. Volcanic eruptions occur with some regularity in Alaska and Russia, affecting air transport and sometimes shutting down urban areas. Uncontrolled wildfires in unpopulated regions are a fact of life, and Alaskans are sometimes subject to huge smoke emissions during the summer. Additionally, Alaska is affected by non-predictable anthropogenic events such as toxic emissions and nuclear fallout.
In addition to providing the tools for decision support, operational products from Alaska are also useful in a number of "downstream" research endeavors including road weather prediction systems, aviation icing products and greenhouse gas studies.
With a decade of experience in provision of operational products, often for large areas at high resolutions, we have gained a fair amount of experience and wisdom, and still have much to learn. In this presentation we discuss some of the systems we have deployed, lessons learned, and the many exciting ambitions we have.
Don Morton is currently a Research Professor of Computer Science at the University of Alaska Arctic Region Supercomputing Center, and has recently launched a private venture, Boreal Scientific Computing LLC, as a mechanism for contributing operational forecasting expertise to a variety of organisations. With a B.S. in Computer Science from the College of Great Falls, Montana, and a Ph.D. from Louisiana State University, Don has spent his career trying to apply his talents in computer science to his passion for science, especially the environmental sciences.
Simon Phipps is President at the Open Source Initiative (OSI), the non-profit organisation that advocates for open source software, builds bridges between open source communities and maintains the canonical list of open source licenses. Currently an independent consultant on open source policy and practice, he was previously head of open source at Sun Microsystems, CSO of startup Forgerock and a founder of IBM’s Java business unit.
Apart from his pro bono participation at OSI, he is also on the board of the Open Rights Group and the leadership team of The Document Foundation. He has been widely involved in standardisation activities, including as a founding director of the Open Mobile Alliance and as one of the Sun executives sponsoring the donation of resources to OASIS to create Open Document Format (ODF). He is a Fellow of the British Computer Society as well as an Open Forum Fellow.
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It's 1983. A time traveler materializes in front of me. He hesitates a moment, then asks, "You're a UNIX guy, right?"
I say, "Right."
"In another thirty years, the dominant UNIX flavor will be the one running inside phones."
"Well ... okay. Bell is a telephone company. But how will users dial up the printer?"
I will give a 5,000-foot view of that flavor, called Android, to get you excited about developing on it yourself. You did UNIX. You did primitive Linux. Why bail out now and give other developers all the fun?
And when I say "Android development," I don't just mean building apps -- everyone and his mom does that -- I also mean building the underlying platform.
I promise there will be interesting demos.
For the last two years, Jeffrey S. Haemer has been doing source-code management (SCM) at Aircell, in Broomfield, Colorado. A couple of his projects are Android-based smartphones, which Aircell (a telco for the aviation industry) builds from the ground up. In 1983, Dr. Haemer helped make the first, commercial, Intel-based Unix. Between those, he has done many equally bizarre-yet-worthwhile things.
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The Google Earth Engine platform is a system designed to enable petabyte-scale, scientific analysis and visualization of geospatial datasets. Earth Engine provides a consolidated environment including a massive data catalog co-located with thousands of computers for analysis. The user-friendly front-end provides a workbench environment to allow interactive data and algorithm development and exploration and provides a convenient mechanism for scientists to share data, visualizations and analytic algorithms via URLs.
The Earth Engine data catalog contains a wide variety of popular, curated datasets, including the world's largest online collection of Landsat scenes (> 2.0M), numerous MODIS collections, and many vector-based data sets. The platform provides a uniform access mechanism to a variety of data types, independent of their bands, projection, bit-depth, resolution, etc..., facilitating easy multi-sensor analysis. Additionally, a user is able to add and curate their own data and collections.
Using a just-in-time, distributed computation model, Earth Engine can rapidly process enormous quantities of geo-spatial data. All computation is performed lazily; nothing is computed until it's required either for output or as input to another step. This model allows real-time feedback and preview during algorithm development, supporting a rapid algorithm development, test, and improvement cycle that scales seamlessly to large-scale production data processing.
Through integration with a variety of other services, Earth Engine is able to bring to bear considerable analytic and technical firepower in a transparent fashion, including: AI-based classification via integration with Google's machine learning infrastructure, publishing and distribution at Google scale through integration with the Google Maps API, Maps Engine and Google Earth, and support for in-the-field activities such as validation, ground-truthing, crowd-sourcing and citizen science though the Android Open Data Kit. http://earthengine.google.org
Dr. Tyler Erickson is Senior Developer Advocate on the Earth Engine team at Google. In this role he works with scientific organizations to demonstrate the capabilities of Google's geospatial tools for managing, analyzing, and visualizing geospatial datasets, and to guide the development of new features to meet the needs of scientific communities. Prior to joining Google he worked in academia as a research scientist, specializing in applying modern open source geospatial information technologies to the analysis of environmental datasets. Dr. Erickson is a former University of Colorado INSTAAR researcher (Ph.D. 2004), where he worked with Prof. Mark Williams on the geostatistical analysis of snow distribution.