Annual Review of the DoD Center for Geosciences/Atmospheric Research (CG/AR) at Colorado State University
November 15-17, 2005
Hosted by
Army Research Laboratory
Adelphi, MD
Research Theme Presentations by Project Leaders
Prof. Thomas Vonder Haar: Overview and Background of the DoD Center for Geosciences/Atmospheric Research at CSU in 2005
Dr. Pierre Julien and Mark Velleux: Spatially Distributed Watershed Chemical Transport and Fate Model - Development Research Summary
Dr. Andrew Jones, Gary McWilliams, Mike Mungiole, George Mason, Cindy Combs, Dustin Rapp, Phil Stephens, Becky McKeown, John Forsythe, Dr. Tomi Vukicevic, and Prof. Thomas Vonder Haar: 4D Data Assimilation of WindSaT Data to Retrieve Soil Moisture
Prof. Bill Cotton, Cotton, Stephen Saleeby, and David Stokowski: Parameterizing Aerosol and Sub-grid Cloud Properties in a Mesoscale Model
Prof. Sonia Kreidenweis, Kelley Johnson and Laura Sample: Aerosol Observations and Prediction Analyses
Adam Kankiewicz and Dr. Larry Carey, Curtis Seaman, Prof. Thomas Vonder Haar, Prof. Vincent Larson: New Results and Analyses Related to Forecasting Extended Mid- Level Cloud Layers
Prof. Vince Larson, Adam Smith, Michael Falk, Kurt Kotenberg, Chris Golaz: What Determines the Lifetime of Altocumulus Clouds?
Prof. Mahmood Azimi and Gordon Wichern: An Environmentally Adaptive Acoustic Transmission Loss Prediction System
Dr. Milija Zupanski, Dusanka Zupanski, Gustavo Carrio, and William Cotton: Evaluation of Ensemble Data Assimilation for the Army Scale Meteorology
Drs. Tomi Vukicevic, Laura Fowler, Andrew Jones, Manajit Sengupta, and Prof. Thomas Vonder Haar: Assimilation of Geostationary IR Observations for Improved Analysis and Prediction of Cloudy Atmosphere in 4D
Dr. Stan Kidder, Adam Kankiewicz, and Kenneth Eis: Meteosat Second Generation Algorithms for use at AFWA
John Forsythe, Kevin Donofrio, Dr. Andrew Jones, Dr. Stan Kidder, Matthew Nielsen, and Ron Kessler: Water Vapor Profile Retrievals from Satellite Microwave Soundings Over Land and Ocean
Kenneth Eis: Technology Transition Discussion
Poster Session 1
Prof. Jorge Ramirez and Rahul Rajagopal: The Evolution of Landscapes and Hillslopes
Prof. Julien, Do-Hyuk Kang, and Mark Velleux: Distributed Snowmelt Modeling with GIS and CASC2D at California Gulch, CO
Dr. Andrew Jones, P. Shott, John Forsythe, Cindy Combs, Ron Kessler, Matt Nielsen, Phil Stephens, and Prof. Thomas Vonder Haar: Masking Effects of Surface Features – How Global Microwave Emissivities Place Measurable Bounds on the Problem
Drs. Andrew Jones and Phil Stephens: Discrete Backus-Gilbert Method for Reducing RFI Effects
Poster Session 2
David Stowoski, Prof. William Cotton, and Stephen Saleeby: Direct Radiative Effect of Aerosols in a Mesoscale Model
Laura Sample, Profs. Graeme Stephens and Sonia Kreidenweis: Sensitivity of Top-of-the- Atmosphere Reflectances to Aerosol Properties
J. Adam Kankiewicz, Curtis Seaman, Prof. Lawrence Carey, Prof. Thomas Vonder Haar: The Next Cloud Layer Experiment (CLEX-10) Field Campaign
Poster Session 3
Amanda Falcone, Prof. Mahmood Azimi-Sadjadi, Adam Kankiewicz: Multi-Satellite Cloud Product Generation Using Canonical Correlation Analysis
Dr. Dusanka Zupanski, Dr. Milija Zupanski, Scott Denning, Marek Uliasz, and Kenneth Eis: The Role of Model Error in Data Assimilation
Drs. Manajit Sengupta and Tomislava Vukicevic: The Analysis of Forecasting Skill in a Mesoscale Model and the PossibleDetermination of Modeling Error
Maj. Timothy Nobis: RAMS Simulations Incorporating an Urban Boundary Layer Scheme
Giovanni Leoncini and Prof. Roger A. Pielke, Sr.: Nonlinear vs. Linear Mesoscale Dynamics
Drs. Ning Wang and Clifford Matsumoto: A Comparison Study of Data Compression Techniques for the Battle-scale Forecast Model (BFM) Grids
Drs. Laura Fowler, Tomislava Vukicevic and Prof. Thomas Vonder Haar: Analysis of Forecast Errors Due to Cloud Microphysics Using 4DVAR Data Assimilation
Kevin Donofrio, John Forsythe, Matthew Nielsen, Dr. Andrew Jones, Ron Kessler, and Prof. Thomas Vonder Haar: Adding Liquid Clouds to CIRA’s Passive Microwave Profiling Retrieval