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GOES USERS’ CONFERENCE III: Discussion Highlights Hydrological/Water Resources Applications

GOES USERS’ CONFERENCE III: Discussion Highlights Hydrological/Water Resources Applications. Increased inclusion of end-users Early and continuous engagement of users (Government, researchers, valu-added private sector and others, i.e. Universities, states and counties Emphasis shift:

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GOES USERS’ CONFERENCE III: Discussion Highlights Hydrological/Water Resources Applications

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  1. GOES USERS’ CONFERENCE III:Discussion HighlightsHydrological/Water Resources Applications

  2. Increased inclusion of end-users Early and continuous engagement of users (Government, researchers, valu-added private sector and others, i.e. Universities, states and counties Emphasis shift: Government & non-government users beyond NOAA Several levels of training Time Tiers Increase lnter-disciplinary & data integration Adaptive processes Cast all factors into 2012 and beyond Themes

  3. Precipitation Skin temperature Snow water equivalent/snow extent Soil moisture Potential evapotranspiration parameters (Solar radiation, wind speed, relative humidity, etc.) Vegetation cover/land use 1) Needs for Data and Product Distribution

  4. When should training start? Earlier in schools, research organizations, universities Closer to launch for operational people. Training methods? Limitations of the data & capabilities Hybrid quantitative/imaging (how to interpret) Information processing/GIS Change in role of human forecaster Early training outreach? Mamma says: butter up the evil people (Budget decision makers) RFPs to universities to demonstrate benefits of GOES-R Target users to deliver value message: Industry users Instrument builders Change in culture- Intro to new tools, need to start early, capacity building now 2) User Community Training

  5. Which ways are most important? Show intercomparisons of products/data between the current GOES and future GOES-R series Developing and validating products Powerpoint files/website for background information Provide test datasets in advance Consult users on specific error info they need and other metadata needs Other venues/forums Participate in other satellite conferences & remote sensing workshops/virtual conferences Academia Water resources conferences Private conferences (i.e. Emergency users) 3) NOAA/NESDIS Preparation for GOES-R

  6. 3) NOAA/NESDIS Preparation for GOES-R (Continued) • Other ways NOAA/Nesdis/Hydrology program can help? • Budget accordingly and addapt to new budget process • Keep hydrologists in the loop (i.e. Don’t let the meteos hijack the process • Continuous interdisciplinary outreach

  7. Operations applications of in current organizations – 3 tiers of users Develop prototype products well in advance for user evaluation and feedback Work closely between developers of products Provide comprehensive scenarios/case studies for various programs Involve academia and science early in algorithm development and evaluation 4) GOES-R Risk Reduction

  8. 4) GOES-R Risk Reduction (Continued) • Feedback mechanism for end users to describe needs • Early definitioin of products and services • More observation systems simulations experiments (OSSEs) • Early development of tools for applicaiton of data • Provide simulated data to test and validate data processing and distribution systems i.e. Data storage, data rates • Validation/verification of algorithms

  9. Use other professional organizations to spread the word AMS, NWR, AWR, AGU, ASCE, IEEE, WMO, IAF User involvement with scenarion based appreciation Fire fighting Storm surge and precipitation-caused flooding Flexible Adjust to new info processing, digital services, GIS New budgets/schedule Coordinate with NPOESS & other programs 5) User Readiness Timeline

  10. Make guest speakers available Particularly, target professional conferencees & academic forums Provide mechanisms for implementing & testing new discoveries into operational product system. Network of ground truth sites Target international organizations Study impact/benefits in the social sciences Data integration across multiple platforms 6) Other Comments

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