presents three main recommendations for responding to these challenges.
Prioritize Core Capabilities
The NWS needs to prioritize the core capabilities that only the NWS can provide so as to deliver the products and services upon which the public and the entire weather, water, and climate enterprise depend. These core capabilities include creating foundational datasets, performing essential functions such as issuing forecasts, watches, and warnings, and conducting operationally-related research. Because the quality of NWS core capabilities underlies the relationship of trust and reliance among the NWS, the public, and the rest of the enterprise, and consistent with Lessons 1, 2, 3, and 5 from NRC (2012a), the Committee makes the following overarching recommendation.
Recommendation I: Prioritize Core Capabilities
The National Weather Service (NWS) should
1. Evaluate all aspects of its work that contribute to its foundational datasets, with the explicit goal of ensuring that those foundational datasets are of the highest quality and that improvements are driven by user needs and scientific advances. As part of this initial and ongoing evaluation effort, clear quality and performance metrics should be established. Such metrics would address the technical components of NWS operations, as well as the efficiency and effectiveness of the flow of weather information to end users.
2. Ensure that a similarly high priority is given to (a) product generation and dissemination, (b) the brokering and provision of data services, and (c) development and enhancement of analysis tools for maintaining a common operating picture (COP).
3. Engage the entire enterprise to develop and implement a national strategy for a systematic approach to research-to-operations and operations-to-research.
To aid the NWS in implementing Recommendation I, the Committee makes the following supporting recommendations:
Recommendation I.a: Technology Infusion
The National Weather Service (NWS) should continue technology infusion programs that have been effective subsequent to the Modernization and Associated Restructuring. Parallel support from the National Environmental Satellite, Data, and Information (NESDIS) is needed to continually upgrade satellite capabilities. Such infusion programs should include both hardware and software development.
Recommendation I.b: Numerical Weather Prediction
The National Weather Service (NWS) global and regional numerical weather prediction systems should be of the highest quality and accuracy, with improvements driven by user needs and scientific advances. To achieve this goal, the NWS should give priority to upgrading its data assimilation system and increasing the resolution of its deterministic and ensemble modeling systems. The product development process can be improved by developing a systematic approach to research-to-operations through collaboration with users and partners in the entire weather, water, and climate enterprise, both in the United States and around the world.
Recommendation I.c: Observational Data Metrics
To increase the capability of its numerical weather prediction systems to keep up with technological advances and prioritize investments in data assimilation and observations systems, the National Weather (NWS) should develop and advance software tools to monitor the impact of observations on numerical weather prediction and downstream forecast systems.
Recommendation I.d: Probabilistic Forecasts
The National Weather Service (NWS) should take the lead in a community effort to provide products that effectively communicate forecast uncertainty information. The format for communicating probabilistic forecasts requires careful design using cognitive research. Calibrated probabilistic forecasts would be produced by statistical post-processing of forecast ensembles, and improvement efforts should focus on increasing the resolution and accuracy of the ensemble forecasts.
Recommendation I.e: Hydrologic Prediction Metrics
The National Weather Service (NWS) hydrologic prediction services should coordinate with other entities