CIRA GOES-R Risk Reduction Project Milestones 2003-2006
Last Updated 9/29/03
I. Database Development
Dec 2003 – Establish project web site and mass storage system for data archival
Mar 2004 - Completion of data collection for severe weather, tropical cyclone and
winter weather case studies (conventional data, satellite data (GOES, AVHRR, MODIS,
AIRS) and specialized in situ datasets such as GPS dropsondes in hurricane
environments, CART site data for severe weather case)
Aug 2004 – Present results of analysis GOES-R simulated data for case studies at the
hyperspectral workshop in Madison, WI
Sep 2004 - Development of processing system for mapping of datasets to common
format
Jan 2005 – Creation of GOES-R imager “subsets”, comparison with in situ data
Sep 2005 – Analysis of AIRS, GOES soundings in tropical storm, severe weather
environments
Dec 2005- Extension of case study analyses to real-time cases
Aug 2006 – Complete research publication describing utility of GOES-R using case study
database
Sept 2006 – Establishment of real-time multi-platform tropical cyclone, severe and winter
weather web site for research, education and training
II. Numerical Modeling Studies
Dec 2003 – Obtain operational eta model analyses, forecasts and operational data input
for case studies
Mar 2003 – Completion of high resolution mesoscale model simulations for case studies
Sep 2004 – Complete development of radiative transfer models for mesoscale model
output, and generate simulated GOES-R data for case studies (this will involve
coordination with JCSDA community radiative transfer model development)
Dec 2004 – Perform time series analysis of case study simulations to help determine time
resolution requirements in storm environments.
March 2005-Complete research publication on estimates of GOES-R sounder timeresolution requirements for tropical cyclones, severe weather and Lake effect snow,
based upon time series analyses of numerical simulations
Sep 2005 – Perform “identical (sub-sample model for input to data assimilation system)
and fraternal (sub-sample different model for input to data assimilation system) twin”
experiments to assess impact of high time resolution input on mesoscale simulations
Dec 2005 – Coordinate with Weather Research and Forecast (WRF) modeling group to
determine if transition from CSU RAMS mesoscale for future studies is possible
March 2006-Complete research publication on potential impact of GOES-R data on
tropical cyclone, severe weather and lake effect snow forecasts, based upon identical and
fraternal twin experiments
Sep 2006 – Data assimilation studies for case studies using real-data input with either
RAMS or WRF model