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General consensus: Lots of good work going on in the PG. Workshop proves it! What is data integration? The level of processing (L1/2/3) What level is used / needed in operations The combination of different types of data, including international Role of models (SA vs models) In large areas or areas with limited obs, combine obs to come up with single state of atmosphere View integration in terms of the future forecast process Bits of data (products) won’t be used as they are now Strategic plan Extrapolation of observations for now/nearcasting and potential role in future operations Breakout Group 2: Overview
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Data integrity is critical – using mutlisensor data to assess confidence in observation Understanding the basis of the product is essential for forecasters to act on guidance Recommendation: Training about products, how they’re made, strengths/weaknesses, and when to use them Sufficient metadata is needed to trace back source of information Error characterization needed for models What’s needed to specify data & product reliability and quality for users?
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Precip algorithm (MW, GLM, GPM, ABI, model) Severe WX nearcasting (grid of vertical thetaE over time) Next gen CI (combines model, satellite, and potentially radar) TC rapid intensification (sat/models/altimetry data) Orographic rain index (model winds / satellite TPW) Lightning jump algorithm Volcanic Ash (fusion product b/c obs are a source for plume models) Recommendation: Fusion products are gap fillers AND/OR principle sources of observations PG interaction and NWS guidance will inform future R3 activities Identify GOES-R Risk Reduction Projects for fused products with early successful demonstrations
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Recommendation: Central or local - Situation dependent NextGen as schedule driver (SOA) Initial focus is aviation, but need to expand to all forecast elements When & where will fused operational decision-making products be created?
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NWS currently upgrading IT infrastructure based on data increase projections from GOES-R, JPSS, NPP, models and dual-pole radar Dependencies on AWIPPS II Recommendation: Further analysis of level of data delivery needed Service delivery should be science driven, not IT driven Initial IT infrastructure needs to get smarter about what’s sent How can Integrated Decision Support Services be delivered at national, regional, & local scales in the GOES-R era given current & planned communications (data flow) limitations ?
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