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| {{Keynote-clinics | | {{Keynote-clinics |
| | name = Elowyn Yager | | | name = Elowyn Yager |
| | affiliation = Center for Ecohydraulics, | | | affiliation = Center for Ecohydraulics, University of Idaho |
| | title = Modeling the effects of vegetation on bedload transport | | | title = Modeling the effects of vegetation on bedload transport |
| | abstract = | | | abstract = |
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| ==Clinics== | | ==Clinics== |
| {{Keynote-clinics | | {{Keynote-clinics |
| | name = Peter Burgess & Chris Jenkins | | | name = Fotis Sotiropoulos (confirmed) |
| | affiliation = Royal Holloway, UK & Univ. of Co. | | | affiliation = University of Minnesota |
| | title = Three carbonate sedimentation models for CSDMS | | | title = SAFL Software |
| | abstract = This workshop will showcase three different models of carbonate sedimentation, produced under the CSDMS umbrella: carboCat for facies, carboCell for guilds, carboPop for communities. Participants will be able to download and run (on own or provided machines) these models in Python and Matlab environments, discuss how to select appropriate parameters for them using the various databases being developed in concert with the models, and contribute to plans for further development of models and databases. | | | abstract = |
| }} | | }} |
| {{Keynote-clinics | | {{Keynote-clinics |
| | name = Gary Clow | | | name = Greg Tucker (confirmed) |
| | affiliation = USGS | | | affiliation = CIRES |
| | title = Introduction to the Weather Research & Forecasting (WRF) System, a High-Resolution Atmospheric Model | | | title = Landlab |
| | abstract = WRF is a highly parallel state-of-the-art numerical weather prediction model hosted by the National Center for Atmospheric Research (NCAR). This community model was designed from the onset to be fairly flexible, supporting both operational forecasting and atmospheric research needs at scales ranging from meters to thousands of kilometers. Given the model’s physics implementation and it’s modular design, WRF naturally became the core for a number of more specialized models, including: HWRF (used to forecast the track and intensity of tropical cyclones), WRF-CHEM (simulates the emission, transport, mixing, and chemical transformation of trace gases and aerosols simultaneously with meteorology), Polar WRF (a version of WRF optimized for the polar regions), CWRF and CLWRF (versions of WRF modified to enable regional climate modeling), and planetWRF (a general purpose numerical model for planetary atmospheres used thus far for Mars, Venus, and Titan).<br><br>The goal of this clinic is to provide an overview of the WRF model, including: model architecture, physics options, data required to drive the model, standard model output, model applications, and system requirements. Several examples will be presented. A Basic Model Interface (BMI) is currently being developed for WRF to facilitate the coupling of this atmospheric model with other earth system models. | | | abstract = |
| }} | | }} |
| {{Keynote-clinics | | {{Keynote-clinics |
| | name = Scott Peckham | | | name = Eunseo Choi |
| | affiliation = University of Colorado | | | affiliation = UTIG |
| | title = Introduction to the Basic Model Interface and CSDMS Standard Names | | | title = SNAC |
| | abstract = In order to simplify conversion of an existing model to a reusable, plug-and-play model component, CSDMS has developed a simple interface called the Basic Model Interface or BMI that model developers are asked to implement. In this context, an interface is a named set of functions with prescribed function names, argument types and return types. By design, the BMI functions are straightforward to implement in any of the languages supported by CSDMS, which include C, C++, Fortran (all years), Java and Python. Also by design, the BMI functions are noninvasive. A BMI-compliant model does not make any calls to CSDMS components or tools and is not modified to use CSDMS data structures. BMI therefore introduces no dependencies into a model and the model can still be used in a "stand-alone" manner. Any model that provides the BMI functions can be easily converted to a CSDMS plug-and-play component that has a CSDMS Component Model Interface or CMI.<br><br>Once a BMI-enabled model has been wrapped by CSDMS staff to become a CSDMS component, it automatically gains many new capabilities. This includes the ability to be coupled to other models even if their (1) programming language, (2) variable names, (3) variable units, (4) time-stepping scheme or (5) computational grid is different. It also gains (1) the ability to write output variables to standardized NetCDF files, (2) a "tabbed-dialog" graphical user interface (GUI), (3) a standardized HTML help page and (4) the ability to run within the CSDMS Modeling Tool (CMT).<br><br>This clinic will explain the key concepts of BMI, with step-by-step examples. It will also include an overview of the new CSDMS Standard Names, which provide a standard way to map input and output variable names between component models as part of BMI implementation. Participants are encouraged to read the associated CSDMS wiki pages in advance and bring model code with specific questions. See<br>1) BMI Page: [[BMI_Description]]<br>2) Standard Names Page: [[CSDMS_Standard_Names]] | | | abstract = |
| }} | | }} |
| {{Keynote-clinics | | {{Keynote-clinics |
| | name = Irina Overeem | | | name = Courtney Harris |
| | affiliation = University of Colorado | | | affiliation = VIMS |
| | title = CMT clinic | | | title = ROMS |
| | abstract = This clinic will look at the CSDMS Modeling Tool (CMT). We share the philosophy behind CMT, will demo the functionality of CMT and show what models are incorporated into it. New educational material on several models allows scientists and students to more easily use CSDMS models for classes and simple simulations and we will provide clinic participants with the latest information on these resources. The CMT clinic will be hands-on, we will run a few simple runs and visualize them. Finally, we will spend some time on discussing common problems and strategic solutions. | | | abstract = |
| }} | | }} |
| {{Keynote-clinics | | {{Keynote-clinics |
| | name = Thomas Hauser & Monte Lunacek | | | name = Chris Jenkins (confirmed) |
| | affiliation = University of Colorado | | | affiliation = INSTAAR |
| | title = Python for Matlab users clinic | | | title = Carbonate |
| | abstract = This workshop is a hands-on introduction to using Python for computational science. Python is a powerful open source interpreted language that has been adopted widely in many application areas. The goal of this workshop is to teach participants how to use Python as an open source alternative for MATLAB in their computational workflows. While we will demonstrate how to implement MATLAB-based scientific computing workflows in Python, attendees are not required to have MATLAB or Python experience. The goal of this tutorial is to show how an open source alternative to MATLAB can be used productively for computational science research. In the first part of this workshop we will introduce basic Python concepts and iPython with a focus on migrating from MATLAB to Python. We will show how the Python modules Numpy and Scipy, for scientific computing, and Matplotlib, for plotting, can make Python as capable as MATLAB for computational science research. In the second part of the tutorial we will discuss on how to interface Python with compiled languages like C or Fortran to improve performance of numerical codes. Additionally we will show how to use distributed parallel computing on a supercomputer from interactive python notebooks. <br><br>This tutorial will be hands on, so we would like you to install python on your laptop before you arrive. The easiest way to get everything you need is to download the FREE Enthought distribution:<br>[https://www.enthought.com/products/epd_free.php https://www.enthought.com/products/epd_free.php]<br><br>The installation is fairly straight forward, but if you have any questions, please feel free to email Monte: [mailto:Monte.Lunacek@colorado.edu Monte.Lunacek@colorado.edu]. | | | abstract = |
| }} | | }} |
| {{Keynote-clinics | | {{Keynote-clinics |
| | name = Mary Hill | | | name = Michael Eldred |
| | affiliation = USGS | | | affiliation = Sandia NL |
| | title = Toward Transparent, Refutable Hydrologic Models in Kansas or Oz. | | | title = DAKOTA |
| | abstract = Numerical models are critical to integrating knowledge and data for environmental systems and understanding future consequences of management decisions, weather variability, climate change, and so on. To attain the transparency and refutability needed to understand predictions and uncertainty and use models wisely, this clinic presents a strategy that emphasizes fundamental questions about model adequacy, sensitivity analysis, and uncertainty evaluation, and consistent use of carefully designed metrics. Emphasizing fundamental questions reveals practical similarities in methods with widely varying theoretical foundations and computational demands. In a field where models take seconds to months for one forward run, a credible strategy must include frugal methods for those in Kansas who can only afford 10s to 100s of highly parallelizable model runs in addition to demanding methods for those in Oz who can afford to do 10,000s to 1,000,000s of model runs. Advanced computing power notwithstanding, people may be in Kansas because they have chosen complex, high-dimensional models, want quick insight into individual models, and/or need systematic comparison of many alternative models. This class will briefly review the fundamental questions, demonstrate relations between existing theoretical approaches, and address challenges and limitations. Students will be able to examine a model constructed using FUSE and compare results from computationally frugal method evaluations conducted in class and demanding methods for which results are provided.<br><br>'''Notice:'''<br>During the clinic you will have the opportunity to run an exercise on your laptop. The exercise uses R, which is freely downloadable. The clinic is only an hour, so it will really be necessary to have downloaded and installed R prior to arriving. Do this as follows<br>go to [http://cran.cnr.berkeley.edu/ http://cran.cnr.berkeley.edu/]<br>Install version 2.15.3<br>Linux, Mac, or Windows versions are available.<br><br>You can install with or without administrative privileges.<br><br>The R scripts you will be working with and the file with results from Sobol' can be downloaded from ftp://ftpext.cr.usgs.gov/pub/cr/co/boulder/mchill, in case you would like to try it out. Here are the rest of the instructions for doing that, but you can wait and do this in class if you like, as long as you have downloaded R.<br><br>2) Open Rgui.exe In the bin subdirectory of the R distribution<br>3) Go to File > Open script "Sensitivities_Global_Local_v02.r"<br>4) Set your current working directory in the R script: setwd("full path") on line 17. This is the directory with the .r files distributed for class. Change any \ to /. There can be spaces in the pathname.<br>5) Run by using the shortcuts Ctrl+a and Ctrl+r.<br><br>PDF files are produced showing plots of results. We will go through what these mean in class.<br><br>The Sobol’ results take 6,000,000 model runs and about 12 hours, so can not be run in class. They are provided in the file:<br>SOBOL_pergridpoint_K_c_9999samplesize_1000bootstrap.txt<br>Each line presents average results for a bootstrapped Sobol’ sample for a portion of the full parameter space. The averages for the entire range of parameters is on the line with grid index=101<br>The R script using this file to create plots; it does not do the runs. | | | abstract = |
| }} | | }} |
| {{Keynote-clinics | | {{Keynote-clinics |
| | name = Xiaofeng Liu | | | name = CSDMS Staff |
| | affiliation = UT San Antonio | | | affiliation = CSDMS |
| | title = Modeling of Earth Surface Dynamics and Related Problems using OpenFOAM®. | | | title = CMTWeb |
| | abstract = This clinic aims to introduce the open source computational fluid dynamics (CFD) platform, OpenFOAM®, to the earth surface dynamics research community and to foster collaborations. OpenFOAM® is essentially a computational toolbox which solves general physical models (differential equations) using finite volume method. This short clinic is tailored to be suitable for an audience at various levels (from beginners to experienced code developers). It will provide an overview of OpenFOAM. We will demonstrate its usage in a variety of applications, including hydrodynamics, sedimentation, groundwater flows, buoyant plumes, etc. Participants can also bring the problems in their fields of interest and explore ways to solve them in OpenFOAM®. Knowledge of C++, object-oriented programming, and parallel computing is not required but will be helpful. | | | abstract = |
| }} | | }} |
| {{Keynote-clinics | | {{Keynote-clinics |
| | name = Eckart Meiburg & students | | | name = Ad Reniers |
| | affiliation = University of California, SB | | | affiliation = University of Miami |
| | title = TURBINS using PETSc | | | title = xBeach |
| | abstract = This clinic will provide information on how laboratory scale flows and field scale flows can be simulated by direct numerical simulations (DNS) and large-eddy simulations (LES) using parallel, high-performance computing facilities. DNS results, from the software TURBINS, of gravity and turbidity currents propagating over complex sea floor topography will be discussed. The use of the PETSc software package within the DNS simulations will be highlighted. LES results of high Reynolds number gravity and turbidity currents, and reversing buoyancy currents over a flat topography will be discussed. Issues relevant to LES such as grid resolution, grid convergence, subgrid models and wall-layer modeling will also be discussed. | | | abstract = |
| }} | | }} |
| {{Keynote-clinics | | {{Keynote-clinics |
| | name = Helena Mitasova | | | name = Michael Barton |
| | affiliation = North Carolina State Univ. | | | affiliation = Arizona State University |
| | title = Modeling and analysis of evolving landscapes in GRASS GIS | | | title = Agent Based Modeling |
| | abstract = This clinic will introduce participants to GRASS6.4.3 with special focus on terrain modeling, geomorphometry, watershed analysis and modeling of landscape processes such as surface water flow and erosion/deposition. The hands-on section will explore lidar-based terrain models, multiple surface visualization, analysis of coastal lidar time series and visualization of terrain evolution using space-time cube. Overview of new capabilities in the GRASS7 development version will also be provided.<br><br>Notice: The participants will be expected to download and install GRASS6.4.3 as well as the practice data sets from the provided web site prior to the clinic. (see below)<br><br>Everything used in the clinic will be available through the following web site: http://courses.ncsu.edu/gis582/common/media/GRASS_clinic2013/GRASS_clinic.html<br>(''I am still working on the material, but the install info is there'').<br><br>Anytime before the clinic (which is on Monday March 25), please:<br>- download the data following the instructions for # 3. Data for the practice<br>- download and install GRASS following # 4. Software<br>- try opening GRASS following [http://courses.ncsu.edu/gis582/common/media/GRASS_clinic2013/IntroGRASS.html the instructions here], especially the video capture [http://courses.ncsu.edu/gis582/common/media/GRASS_clinic2013/gettingstartedGRASS643edit3.mov Getting started with GRASS]<br><br>You don't need to go through the entire video or the instructions - we will do it in Boulder, for now just open GRASS and make sure you can display one of the provided map layers.<br>Please let Helena know if you have any problems: [mailto:hmitaso@ncsu.edu hmitaso@ncsu.edu] | | | abstract = |
| | }} |
| | {{Keynote-clinics |
| | | name = Scott Peckham (confirmed) |
| | | affiliation = University of Colorado |
| | | title = BMI and Standard Names |
| | | abstract = |
| }} | | }} |
| {{Keynote-clinics | | {{Keynote-clinics |
| | name = Ad Reniers | | | name = Chris Duffy |
| | affiliation = University of Miami | | | affiliation = Penn State |
| | title = Dune erosion and overwash with XBeach | | | title = PIHM |
| | abstract = A short tutorial and hands-on workshop to set up and run XBeach to predict the morphodynamic response of dune protected areas under hurricane conditions. We will cover the set up of the computational grid, boundary conditions, model processes and data analysis.<br><br> The XBeach model runs on a windows platform. If you have a Mac, you can still run the model provided you have software (like parallels or vmware) that enables you to run windows programs. To download XBeach, see: [http://oss.deltares.nl/ http://oss.deltares.nl/] | | | abstract = |
| }} | | }} |
| {{Keynote-clinics | | {{Keynote-clinics |
| | name = Hari Rajaram | | | name = Monte Lunacek |
| | affiliation = University of Colorado | | | affiliation = University of Colorado |
| | title = A very basic introduction to numerical methods for scientific computing | | | title = Python |
| | abstract = I will give a overview of the basic foundations of numerical methods for modeling earth systems described by ordinary and partial differential equations. I will discuss the underlying foundations of finite-difference, finite-volume and finite-element methods using diffusion/conduction equations as an example. I will discuss explicit and implicit methods for time-stepping, and stability analysis of time-integration schemes. All numerical methods for ODEs and PDEs in some form arrive at algebraic approximations, translating them into systems of algebraic equations. I will discuss basic algorithms for solving systems of algebraic equations, and how they are incorporated into various software packages, and also emphasize the importance of sparsity | | | abstract = |
| in matrix computations. I will include examples derived from practical problems in reactive transport and glacier dynamics to illustrate how basic concepts apply to real-world problems and make a difference when we want to develop efficient and accurate models.
| |
| }} | | }} |
| <br> | | <br> |
