Form:CSDMS annual meeting: Difference between revisions

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| abstract = Dakota (https://dakota.sandia.gov) is an open-source software toolkit, designed and developed at Sandia National Laboratories, that provides a library of iterative systems analysis methods, including sensitivity analysis, uncertainty quantification, optimization, and parameter estimation. Dakota can be used to answer questions such as:<br><br>·What are the important parameters in my model?<br>·How safe, robust, and reliable is my model?<br>·What parameter values best match my observational data?<br><br>Dakota has been installed on the CSDMS supercomputer, beach, and is available to all registered users. The full set of Dakota methods can be invoked from the command line on beach; however, this requires detailed knowledge of Dakota, including how to set up a Dakota input file, and how to pass parameters and responses between a model and Dakota. To make Dakota more accessible to the CSDMS community, a subset of its functionality has been configured to run through the CSDMS Web Modeling Tool (WMT; https://csdms.colorado.edu/wmt). WMT provides access to the following Dakota methods:<br><br>·vector, centered, list and multidimensional parameter studies<br>·design and analysis of computer experiments with Monte Carlo and Latin Hypercube sampling methods<br>·uncertainty quantification with sampling, polynomial chaos expansion and stocastic collocation techniques<br><br>In this clinic, we'll provide an overview of Dakota, then, through WMT, set up and perform a series of numerical experiments with Dakota on beach, and evaluate the results.<br>
| abstract = Dakota (https://dakota.sandia.gov) is an open-source software toolkit, designed and developed at Sandia National Laboratories, that provides a library of iterative systems analysis methods, including sensitivity analysis, uncertainty quantification, optimization, and parameter estimation. Dakota can be used to answer questions such as:<br><br>·What are the important parameters in my model?<br>·How safe, robust, and reliable is my model?<br>·What parameter values best match my observational data?<br><br>Dakota has been installed on the CSDMS supercomputer, beach, and is available to all registered users. The full set of Dakota methods can be invoked from the command line on beach; however, this requires detailed knowledge of Dakota, including how to set up a Dakota input file, and how to pass parameters and responses between a model and Dakota. To make Dakota more accessible to the CSDMS community, a subset of its functionality has been configured to run through the CSDMS Web Modeling Tool (WMT; https://csdms.colorado.edu/wmt). WMT provides access to the following Dakota methods:<br><br>·vector, centered, list and multidimensional parameter studies<br>·design and analysis of computer experiments with Monte Carlo and Latin Hypercube sampling methods<br>·uncertainty quantification with sampling, polynomial chaos expansion and stocastic collocation techniques<br><br>In this clinic, we'll provide an overview of Dakota, then, through WMT, set up and perform a series of numerical experiments with Dakota on beach, and evaluate the results.<br>
}}
}}
{{Keynote-clinics
 
| name = Gopal Bhatt
| affiliation = Pennsylvania State University
| participants = People attending: {{#ask: [[Meeting:+]][[CSDMS_meeting_select_clinics1::2) Develop catchment models with PIHM]]|format=count}}
| title = Accessing National Data and Distributed Models for Catchment Simulation
| abstract = Chris Duffy, Gopal Bhatt, Lorne Leonard<br><br>The objective of the clinic is: (1) to introduce the concept of essential terrestrial variables (ETVs) and HydroTerre1 as a continental scale ETV-repository for catchment modeling, and (2) to demonstrate the use of ETV’s with the Penn State Integrated Hydrologic Model (PIHM) for simulating the catchment water cycle. PIHM2 is a multi-process, multi-scale hydrologic model where the hydrologic processes are fully coupled using the semi-discrete finite volume method. PIHMgis3 is an open source, platform independent, and extensible distributed modeling framework for setup, execute, and analyze model simulations. Through the procedural framework of PIHMgis, participants will be introduced to multiple data processing tools, and presented with a live demonstration of (i) accessing HydroTerre ETV service, (ii) ETV geodata translator for PIHM, (iii) automated ingestion of model parameters from national geospatial databases, (iv) conditional domain decomposition of the watershed into quality triangular mesh elements for numerical simulation, (v) performing multi-state distributed hydrologic model simulations on desktop, and (vi) visualization of model results as time-series plots and geo-spatial maps. In the clinic, an application is developed for a small-scale hillslope catchment Susquehanna-Shalehills Critical Zone Observatory (SSHCZO), which serves as a guided example of the desktop workflow, which is readily used to develop your own catchment simulation.<br><br>1 http://www.hydroterre.psu.edu/HydroTerre/Help/Ethos.aspx<br><br>2 http://www.pihm.psu.edu/index.html<br><br>3 http://www.pihm.psu.edu/pihmgis_home.html
}}
{{Keynote-clinics
| name = Phaedra Upton & Sam Roy
| participants = People attending: {{#ask: [[Meeting:+]][[CSDMS_meeting_select_clinics1::3) Influence of faults on Fluvial incision rates and patterns]]|format=count}}
| affiliation = GNS Science & University of Maine
| title = Exploring the influence of fault damage and fault slip on the patterns and rates of fluvial incision using CHILD and Matlab
| abstract = Sam Roy<sup>1</sup>, Phaedra Upton<sup>2</sup>, Peter O. Koons<sup>1</sup> and Greg E. Tucker<sup>3</sup><br><br><small><sup>1</sup> Department of Earth Sciences, University of Maine, Orono, ME, USA<br><sup>2</sup> GNS Science, Lower Hutt, New Zealand<br><sup>3</sup> CIRES and Department of Geological Sciences, University of Colorado, Boulder, CO, USA</small><br><br>The interplay between tectonics and surface processes has long been recognized and explored through field observations, laboratory studies, and analogue and numerical modeling.  However, the dependencies that link tectonics and the surface are complex and often difficult to unravel and visualize with current methods and concepts.  To address these difficulties, it is common to create predictive models with algorithms that simplify these natural processes and limit their dependencies on one another.<br><br>In this clinic, we share some simple methods for isolating two tectonic processes: fault damage and fault slip, and explore how they influence the rates and patterns of surface processes. These tectonic processes are introduced as 3D patterns of rock damage and kinematics in a landscape evolution model using Matlab and CHILD. First, we discuss methods for scaling rock damage to erodibility for use in a stream power model. The erodibility field is based on the generic 3D geometry of planar fault damage zones. Next, we include fault slip by using a 3D kinematic solution for dip-slip, oblique-slip, and strike-slip motion. These models include a single slip plane that divides a block of crust into fixed and mobile components. Finally, we combine the rock damage and kinematic fields to observe their combined influence. In these combined models, rock damage becomes a function of the amount of motion accommodated by the slip plane. Throughout the clinic we will explain our methods, interpret model results, discuss their limitations, and postulate ways to improve upon them. The simple methods we employ in this clinic lay a foundation of understanding that can be broadened by use of dynamic, fully coupled models.
}}
{{Keynote-clinics
| name = Zhen Cheng (Charlie) & Tian-Jian Hsu (Tom)
| affiliation = University of Delaware
| participants = People attending: {{#ask: [[Meeting:+]][[CSDMS_meeting_select_clinics1::4) Modeling Coastal Sediment Transport Using OpenFOAM]]|format=count}}
| title = Modeling Coastal Sediment Transport Using OpenFOAM®
| abstract =During a clinic session in the 2013 CSDMS annual meeting, the OpenFOAM®, an open source computational fluid dynamics (CFD) platform, was first introduced by Dr. Xiaofeng Liu (now at Penn State University) for modeling general earth surface dynamics. OpenFOAM® provides various libraries, solvers and toolboxes for solving various fluid physics via finite volume method. The objective of this clinic is to further discuss its recent development and applications to coastal sediment transport. The clinic will start with an overview of a range of coastal applications using OpenFOAM®. We will then focus on a recently released solver, SedFOAM, for modeling sand transport by using an Eulerian two-phase flow methodology. Specifically, we will focus on applying the model to study wave-driven sheet flows and the occurrence of momentary bed failure. The code can be downloaded via CSDMS code repository and participants will receive a hands-on training of the coding style, available numerical schemes in OpenFOAM®, computational domain setup, input/output and model result analysis. Knowledge of C++, object-oriented programming, and parallel computing is not required but will be helpful.
}}
===Wednesday (2<sup>nd</sup> day)===
===Wednesday (2<sup>nd</sup> day)===
{{Keynote-clinics
 
| name = Brad Murray & Andrew Ashton
| affiliation = Duke University
| participants = People attending: {{#ask: [[Meeting:+]][[CSDMS_meeting_select_clinics2::1) Coastal Evolution Modeling (CEM)]]|format=count}}
| title = Coastline Evolution Model (CEM)
| abstract =The Coastline Evolution Model (CEM) addresses coastline changes that arise from gradients in the net alongshore transport, over timescales that are long compared to storm cycles, and spatial scales that are larger than the cross-shore extent of the shoreface (kilometers on typical open ocean coasts). In the model, coastline morphodynamic feedbacks arise as coastline shapes determine spatial patterns of sediment flux, and gradients in that flux cause changes in shape. In this model system, waves approach from a wide range of directions, and the influences of the whole ‘wave climate’ combine to determine coastline changes and patterns. Wave shadowing—in which protruding coastline features change the local wave climates affecting other parts of the coastline—also plays a key role in coastline evolution in this model. A number of other processes or influences have been added to the model, including: river sediment input and delta evolution; effects of the composition of underlying rocks; two-way interactions between beach sediment and cliff erosion; and human shoreline stabilization.<br><br>This clinic will combine 1) explanations of model principles, assumptions, and limitations with 2) the opportunity for participants to gain some familiarity with running the model, by conducting their own simple model experiments.
}}
{{Keynote-clinics
{{Keynote-clinics
| name = Eric Hutton & Mark Piper
| name = Eric Hutton & Mark Piper
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| 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 (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 C, C++, Fortran, 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.<br><br>Models that provide a BMI can be incorporated into a modeling framework, such as the CSDMS model coupling framework, where they gain new capabilities provided by the framework. The CSDMS framework allows coupling of models even if they differ in:<br><br>• programming language,<br>• variable names,<br>• variable units,<br>• time-stepping scheme or<br>• computational grid is different.<br><br>Framework models also gain the ability to write output variables to NetCDF files, a graphical user interface, and the ability to run within the CSDMS Web Tool.<br><br>This clinic will explain the key concepts of BMI (and CSDMS Standard Names), and will demonstrate, through example, how to implement a BMI for an existing model. It will also include an overview of the CSDMS Standard Names, which provide a uniform way to map input and output variable names between component models as part of a BMI implementation. Participants are encouraged to read the associated CSDMS wiki pages in advance. See<br><br>• [[BMI_Description|BMI Description]]<br>• [[CSDMS_Standard_Names|CSDMS Standard Names]]
| 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 (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 C, C++, Fortran, 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.<br><br>Models that provide a BMI can be incorporated into a modeling framework, such as the CSDMS model coupling framework, where they gain new capabilities provided by the framework. The CSDMS framework allows coupling of models even if they differ in:<br><br>• programming language,<br>• variable names,<br>• variable units,<br>• time-stepping scheme or<br>• computational grid is different.<br><br>Framework models also gain the ability to write output variables to NetCDF files, a graphical user interface, and the ability to run within the CSDMS Web Tool.<br><br>This clinic will explain the key concepts of BMI (and CSDMS Standard Names), and will demonstrate, through example, how to implement a BMI for an existing model. It will also include an overview of the CSDMS Standard Names, which provide a uniform way to map input and output variable names between component models as part of a BMI implementation. Participants are encouraged to read the associated CSDMS wiki pages in advance. See<br><br>• [[BMI_Description|BMI Description]]<br>• [[CSDMS_Standard_Names|CSDMS Standard Names]]
}}
}}
{{Keynote-clinics
 
| name = Jon Goodall
| affiliation = University of Virginia
| participants = People attending:  {{#ask: [[Meeting:+]][[CSDMS_meeting_select_clinics2::3) Integrated Modeling Concepts]]|format=count}}
| title = Integrated Modeling Concepts
| abstract = This clinic is intended for early career researchers interested in gaining an understanding of basic integrated modeling concepts as they relate to modeling earth science systems. The class will present key literature in the field, core concepts and terminology, and different integrated modeling systems. Past, present, and future trends for designing integrating modeling systems will be discussed. Participants will also gain experience applying integrated modeling concepts using CSDMS for simplified integrated modeling examples.
}}
===Thursday (3<sup>rd</sup> day)===
===Thursday (3<sup>rd</sup> day)===
{{Keynote-clinics
{{Keynote-clinics
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| abstract = Gregory E. Tucker <sup>1</sup>, Daniel E.J. Hobley <sup>1</sup>, Jordan M. Adams <sup>2</sup>, Sai S. Nudurupati <sup>3</sup>, Eric Hutton <sup>4</sup>, Nicole M. Gasparini <sup>2</sup>, and Erkan Istanbulluoglu <sup>3</sup><br><br><small><sup>1</sup> CIRES and Department of Geological Sciences, University of Colorado at Boulder<br><sup>2</sup> Department of Earth and Environmental Sciences, Tulane University<br><sup>3</sup> Department of Civil and Environmental Engineering, University of Washington<br><sup>4</sup> CSDMS, University of Colorado at Boulder</small><br><br>Writing the software to implement a two-dimensional numerical model can be a daunting exercise, even when the underlying discretization and numerical schemes are relatively simple. The challenge is even greater when the desired model includes ``advanced'' features such as an unstructured grid, a staggered-grid numerical solver, or input/output operations on gridded data. Landlab is a Python-language programming library that makes the process of 2D model-building simpler and more efficient. Landlab's core features include: (1) a gridding engine that lets you create and configure a structured or unstructured grid in just a few lines of code, and to attach data directly to the grid; (2) a library of pre-built process components that saves you from having to re-invent the wheel with common geoscience algorithms (such as flow routing on gridded terrain, linear and nonlinear diffusion, and elastic plate flexure); (3) a mechanism for coupling components together to create integrated model; and (4) a suite of tools for input/output and other common operations. Although Landlab's components are primarily related to earth-surface dynamics (including geomorphology and hydrology), its basic framework is applicable to many types of geophysical system. This clinic provides a hands-on tutorial introduction to Landlab. Participants will learn about Landlab's capabilities, and how to use it to build and run simple 2D models. Familiarity with the Python language and the Numpy library is helpful but not critical.
| abstract = Gregory E. Tucker <sup>1</sup>, Daniel E.J. Hobley <sup>1</sup>, Jordan M. Adams <sup>2</sup>, Sai S. Nudurupati <sup>3</sup>, Eric Hutton <sup>4</sup>, Nicole M. Gasparini <sup>2</sup>, and Erkan Istanbulluoglu <sup>3</sup><br><br><small><sup>1</sup> CIRES and Department of Geological Sciences, University of Colorado at Boulder<br><sup>2</sup> Department of Earth and Environmental Sciences, Tulane University<br><sup>3</sup> Department of Civil and Environmental Engineering, University of Washington<br><sup>4</sup> CSDMS, University of Colorado at Boulder</small><br><br>Writing the software to implement a two-dimensional numerical model can be a daunting exercise, even when the underlying discretization and numerical schemes are relatively simple. The challenge is even greater when the desired model includes ``advanced'' features such as an unstructured grid, a staggered-grid numerical solver, or input/output operations on gridded data. Landlab is a Python-language programming library that makes the process of 2D model-building simpler and more efficient. Landlab's core features include: (1) a gridding engine that lets you create and configure a structured or unstructured grid in just a few lines of code, and to attach data directly to the grid; (2) a library of pre-built process components that saves you from having to re-invent the wheel with common geoscience algorithms (such as flow routing on gridded terrain, linear and nonlinear diffusion, and elastic plate flexure); (3) a mechanism for coupling components together to create integrated model; and (4) a suite of tools for input/output and other common operations. Although Landlab's components are primarily related to earth-surface dynamics (including geomorphology and hydrology), its basic framework is applicable to many types of geophysical system. This clinic provides a hands-on tutorial introduction to Landlab. Participants will learn about Landlab's capabilities, and how to use it to build and run simple 2D models. Familiarity with the Python language and the Numpy library is helpful but not critical.
}}
}}
{{Keynote-clinics
 
| name = Jon Pollak & Jon Goodall
| affiliation = CUASHI
| participants = People attending:  {{#ask: [[Meeting:+]][[CSDMS_meeting_select_clinics3::3) CUASHI Water Data Center]]|format=count}}
| title = Data Access and Publication with the CUAHSI Water Data Center
| abstract = The CUAHSI Water Data Center (WDC) is community governed, NSF funded facility that enables data access and publication through a web services oriented architecture. The WDC maintains the largest catalog of time series water data in the world, which includes data sources that range from global to local coverage and include data sets that describe climate, streams, and soil. This session will touch upon a number of functions of the WDC including:<br><br>• How can I use WDC services to fulfill NSF Data Management requirements?<br><br>• What data are available through the WDC?<br><br>• How can I access data?<br><br>• How can I write custom software that accesses data published with the WDC?<br><br>Participants should anticipate this information to be presented through slides and should expect to leave with a comprehensive understanding of the research support services offered by the WDC. 
}}
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Revision as of 17:32, 13 January 2016

The joint 2016 CSDMS - SEN* Annual Meeting
Capturing Climate Change

May 17 -19th 2016, Boulder Colorado, USA



Optional: May 16th 2016, pre-conference bootcamp


Registration

Registration will open Mid January


Objectives and general description

The joint CSDMS - SEN* 2016 annual meeting will focus on “advances in simulating the imprint of climate change on the land and seascapes, including the processes that influence them”. We would like presentations to either focus on the impacts of present and future climate change, or how climate change has impacted the earth in the past. Topics of interests also include modeling research that integrate different disciplines, different scales, and the synergy between models and experimental data. As in past meetings, keynote speakers are by invitation only, and poster presentations are the general media. The meeting will include:

  1. State-of-the art keynote presentations in earth-surface dynamics and modeling
  2. Hands-on clinics related to community models, tools and approaches
  3. Transformative software products and approaches designed to be accessible, easy to use, and relevant
  4. Breakout sessions for Working, Focus Research Groups and the Initiatives
  5. Poster Sessions

and more!

Poster Information: The poster boards are configured for 4' wide by 6' tall (portrait orientation) posters. The deadline to submit abstracts is April 15, 2016.

Agenda

Click here to view the draft agenda of 12/29/2015.

Participants

Interested to see who registered for the meeting as of 06/18/2025?


Reimbursement

Within its budget, CSDMS intends to support member applicants to attend the annual meeting. Towards this goal, we encourage members to fully or partially cover their expenses if capable. We additionally thank those in the industry and agency fields for understanding that 1) we cannot compensate federal agency participants since our own funding is from NSF, and 2) we request that our industrial/ corporate participants cover their own costs thereby allowing more academic participants to attend.

To the extent possible, CSDMS intends to reimburse the registration fee, lodging (shared rooms at 100% and single rooms at 50% at conference hotels), and a limited amount of travel expenses for qualified registrants - those members who will attend all three days of the meeting and are not industry or federal employees.

Important for foreign travelers requesting reimbursement: If you need a visa to travel to USA, select a business visa. If you need an invitation letter, please email csdms@colorado.edu as soon as possible. Also indicate whether specific wording is required in the letter. Second, we will need to copy the entry stamp in your passport sometime during the meeting as proof that you were here on business as required by US tax laws for reimbursement (especially when dealing with airfare.) We are only able to provide reimbursement for airfare within the U.S. All airfare that is being reimbursed must be for airlines that are U.S. flag carriers.

Travel, Lodging and Conference Center Information

The meeting will be held at SEEC
Hotels: Millennium Harvest House Hotel and the Boulder Inn by Best Western
Transportation: You can book transportation between DIA and Boulder here: Green Ride Boulder. And information on how to find Green Ride Boulder at DIA.
We will provide a bus between the hotels and the meeting venue each day. We will also provide transportation to the banquet.

Pre-conference one-day Software Carpentry bootcamp

CSDMS will host a Pre-conference one-day Software Carpentry bootcamp on Monday May 16th, 2016. The objective is to teach basic programming skills that will be useful for scientific computing and model development. This is an intensive, hands-on workshop, during which certified instructors will cover basic elements of:

  1. the Unix bash shell,
  2. Python programming and NumPy, and
  3. Github for version control.

Our instructors are earth scientists and have familiarity with the CSDMS framework, such that lessons and examples will be targeted toward relevant problems in your field. The bootcamp intentionally precedes the CSDMS meeting, so the skills participants develop should be useful in the clinics during the meeting.

Note:

  • Registration is open till April 1st (or until program fill) and is handled through the 2016 meeting site.
  • The bootcamp is capped at 30 participants (first paid first serve), and it has a $25 registration fee.
  • Participant will be responsible for cost / organization of their extra day of hotel accommodation and dinner. Costs will not be reimbursed.
  • We will cover coffee and lunch during the bootcamp.



Student Scholarships

This year CSDMS is offering a limited number of scholarships (up to 12) for graduate students to attend the CSDMS annual meeting. Three scholarships will be offered for the purpose of increasing participation of underrepresented students. To be eligible, graduate students need to meet the following requirements:

  • Attend the whole meeting (May 17-19, 2016)
  • Submit an abstract
  • Be enrolled as a graduate student at the time of the meeting (bring proof)
  • Submit a letter of motivation that states why you wish to participate in the meeting, and explain how your participation would enhance diversity in the field of surface dynamics modeling.


The CSDMS scholarships will cover:

  • Registration costs
  • Travel (air fare ONLY within the United States and local transport)
  • Per diem to help reimburse the cost of meals from 17-19 May 2016 not offered in the conference schedule



Important dates

  • January 15th: Registration opens
  • March 1st: Deadline for student scholarship applications
  • April 1st: Deadline for abstract submission & registration
  • May 16th: Optional: pre-conference bootcamp
  • May 17-19th: CSDMS annual meeting
  • May 20th: CSDMS Executive and Steering committees meeting (by invitation only)

* The Sediment Experimentalist Network (SEN) integrates the efforts of sediment experimentalists to build a knowledge base for guidance on best practices for data collection and management. The network facilitates cross-institutional collaborative experiments and communicates with the research community about data and metadata guidelines for sediment-based experiments. This effort aims to improve the efficiency and transparency of sedimentary research for field geologists and modelers as well as experimentalists.

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