News

Nov 07
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Reading and discussion group:  Data science in understanding and addressing climate change 

By | Educational, Events, General Interest, Happenings

CSCAR announces a reading and discussion group Data science in understanding and addressing climate change that will meet on the third or fourth (depending on the preferences of participants) Friday of every month between 3 and 5 pm. We will discuss reports and significant papers that illuminate fundamental issues in climate change science, policy, and management. The suggested format at this stage is that we discuss one science and one policy (or management) paper or chapter. The focus will be on the spatial (and temporal) dimensions of the issue and we will concentrate more on methods and techniques keeping the requirement for domain knowledge relatively low. We will lay emphasis on the conceptual part of the tools and techniques so that it is accessible to a wider set of participants, but will also get into the technical details.

This is an effort to bring people involved in climate change together from a data science perspective. The idea is to learn together in a fun environment and foster dialogue with a focus on how data science can provide the common ground for mutual learning and understanding.

 We will meet in Rackham, but we will be open to rotating the location. You will be able to participate remotely, if you choose to.

 If you are interested send an email to Manish Verma at manishve@umich.edu

 If you have any suggestion for discussion and reading let us know.  We will include chapters from the IPCC and US global change science programs in our discussion.

Oct 10
0

Research highlights: Running climate models in the cloud

By | General Interest, News, Research

Xianglei Huang

Can cloud computing systems help make climate models easier to run? Assistant research scientist Xiuhong Chen and MICDE affiliated faculty Xianglei Huang, from Climate and Space Sciences and Engineering (CLASP), provide some answers to this question in an upcoming issue of Computers & Geoscience (Vol. 98, Jan. 2017, online publication link: http://dx.doi.org/10.1016/j.cageo.2016.09.014).

Teaming up with co-authors Dr. Chaoyi Jiao and Prof. Mark Flanner, also in CLASP, as well as Brock Palen and Todd Raeker from U-M’s Advanced Research Computing – Technology Services (ARC-TS), they compared the reliability and efficiency of Amazon’s Web Service – Elastic Compute 2 (AWS EC2) with U-M’s Flux high performance computing (HPC) cluster in running the Community Earth System Model (CESM), a flagship climate model in the U.S. developed by the National Center for Atmospheric Research.

The team was able to run the CESM in parallel on an AWS EC2 virtual cluster with minimal packaging and code compiling effort, finding that the AWS EC2 can render a parallelization efficiency comparable to Flux, the U-M HPC cluster, when using up to 64 cores. When using more than 64 cores, the communication time between virtual EC2 nodes exceeded the communication time in Flux.

Until now, climate and earth systems simulations had relied on numerical model suites that run on thousands of dedicated HPC cores for hours, days or weeks, depending on the size and scale of each model. Although these HPC resources have the advantage of being supported and maintained by trained IT support staff, making them easier to use them, they are expensive and not readily available to every investigator that needs them.

Furthermore, the systems within reach are sometimes not large enough to run simulations at the desired scales. Commercial cloud systems, on the other hand, are cheaper and accessible to everyone, and have grown significantly in the last few years. One potential drawback of cloud systems is that the user needs to provide and install all the software and the IT expertise needed to run the simulations’ packages.

Chen and Huang’s work represents an important firstxiangleihuangpost2016 step in the use of cloud computing in large-scale climate simulations. Now, cloud computing systems can be considered a viable alternate option to traditional HPC clusters for computational research, potentially allowing researchers to leverage the computational power offered by a cloud environment.

This study was sponsored by the Amazon Climate Initiative through a grant awarded to Prof. Huang. The local simulation in U-M was made possible by a DoE grant awarded to Prof. Huang.

Top image: http://www.cesm.ucar.edu/

May 12
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Seminar: Monitoring and Modeling Great Lakes Water, Drew Gronewold, NOAA-GLERL — May 21

By | Educational, Events

SPEAKER: Drew Gronewold, NOAA-GLERL

TITLE : Monitoring and modeling the water budget and water levels of Earth’s largest lake system

TIME: 10 – 11 am ET on Thursday, May 21

LOCATION: School of Natural Resources and Environment, Dana Building Room 1040

ABSTRACT: The North American Great Lakes constitute the largest surface of fresh water on Earth (Lakes Superior and Michigan-Huron alone are the two largest lakes on Earth by surface area).  Monitoring and modeling the major components of the Great Lakes water budget, including over-lake precipitation, over-lake evaporation, and runoff, involves an international, multi-institution partnership that leverages a complex combination of sensor networks and modeling platforms.  In this presentation, we provide an overview of the drivers behind long-term changes in Great Lakes water levels, including findings from recent research focused on explaining the abrupt water level decline on Lakes Superior and Michigan-Huron in the late 1990s, and the recent record-setting water level surge.  Insights from this research underscore the sensitivity of large freshwater systems to regional climate perturbations, and the need for improved understanding of how the future of these systems will be dictated by a combination of climate change, human intervention, and changes in consumptive use.​

Apr 27
0

Tutorial: Learning to use the Community Earth System Model on Flux — May 6

By | Educational, Events

If you are interested in learning how to operate the Community Earth System Model (CESM) global climate modeling system using U-M computing resources, please consider attending an upcoming interactive tutorial:

Time/Date/Location: 1:30 – 3:30 p.m., Wednesday, May 6, Space Research Building Auditorium (Room 2246).

Presenter: Mark Flanner, Assistant Professor, AOSS

Topics:

  • Compile CESM on the U of M computing cluster Flux
  • Run a basic configuration of CESM
  • Visualize model output and compute global averages of key model states.
  • Learn how to implement a simple source code change
  • Explore some of the numerous configurations of CESM

RSVP: Contact Prof. Flanner at flanner@umich.edu.