Representation of Model Uncertainty

2018 Haurwitz Lecture

The Robert T. Ryan Symposium will conclude with a cocktail reception welcoming symposium attendees, along with Bob's numerous colleagues and former interns from across the weather enterprise. With a short program hosted by symposium co-chair and AMS Fellow Veronica Johnson of WJLA in Washington, D.C., this casual event will honor Bob for his distinguished career, achievements, and contributions to the American Meteorological Society.

Improving the communication of forecast uncertainty remains a core priority for the weather enterprise as a whole (NAS 2006) and NOAA/NWS in particular (NOAA 2012). For the last 3 years, researchers working in NOAA's Hazardous Weather Testbed and Hydrometeorological Testbed have experimented with a variety of probabilistic tools, in time scales ranging from days to minutes, and explored the ways those tools can be used for forecasting and communication by NWS forecasters, emergency managers, and broadcast meteorologists. This session will report on key findings from these projects, documenting current trajectories of development and outstanding conceptual and technical challenges.

We encourage all attendees to take the opportunity to grab a snack and coffee and spend this extended afternoon break networking with colleagues and viewing the hundreds of posters on display in the poster hall. Poster displays are grouped by conference and change each day.

We encourage all attendees to take the opportunity to grab a snack and coffee and spend this extended afternoon break networking with colleagues and viewing the hundreds of posters on display in the poster hall. Poster displays are grouped by conference and change each day.

The 32nd Conference on Hydrology is hosting a joint session with the 25th Conference Probability and Statistics on probabilistic hydrometeorological forecasting and uncertainty analysis. Over the last several decades, substantial progresses have been achieved in probabilistic hydrometeorological forecasting theories and applications. However, significant challenges still exist in assessing the quality and uncertainty of complex hydrometeorological processes and improving hydrometeorological predictions, especially high-impact hydrometeorological events. This session solicits papers but not limit to that focus on (1) addressing uncertainty in hydrometeorological forecasting from different sources in both offline and couple systems, and (2) hydrometeorological ensemble forecasting methods. The former might include uncertainties in forcing data (quantitative precipitation estimation, meteorological forcing data, and so on), initial conditions (such as soil moisture and heterogeneous geographical conditions), parameters, model structure (physics), calibration, and statistical postprocessing of hydrometeorological model output, and innovative methods for assessing uncertainty information from observations to modeling and postprocessing processes. The latter emphasizes integrated ensemble methods to improve individual hydrologic and atmospheric models, or coupled atmosphere–land–hydrology systems, verification methods to evaluate probabilistic hydrometeorological forecasting, and technologies to process systematic errors of hydrometeorological forecasting at different spatial and temporal scales.

The 32nd Conference on Hydrology is hosting a joint session with the 25th Conference Probability and Statistics on probabilistic hydrometeorological forecasting and uncertainty analysis. Over the last several decades, substantial progresses have been achieved in probabilistic hydrometeorological forecasting theories and applications. However, significant challenges still exist in assessing the quality and uncertainty of complex hydrometeorological processes and improving hydrometeorological predictions, especially high-impact hydrometeorological events. This session solicits papers but not limit to that focus on (1) addressing uncertainty in hydrometeorological forecasting from different sources in both offline and couple systems, and (2) hydrometeorological ensemble forecasting methods. The former might include uncertainties in forcing data (quantitative precipitation estimation, meteorological forcing data, and so on), initial conditions (such as soil moisture and heterogeneous geographical conditions), parameters, model structure (physics), calibration, and statistical postprocessing of hydrometeorological model output, and innovative methods for assessing uncertainty information from observations to modeling and postprocessing processes. The latter emphasizes integrated ensemble methods to improve individual hydrologic and atmospheric models, or coupled atmosphere–land–hydrology systems, verification methods to evaluate probabilistic hydrometeorological forecasting, and technologies to process systematic errors of hydrometeorological forecasting at different spatial and temporal scales.

The 32nd Conference on Hydrology is hosting a joint session with the 25th Conference Probability and Statistics on probabilistic hydrometeorological forecasting and uncertainty analysis. Over the last several decades, substantial progresses have been achieved in probabilistic hydrometeorological forecasting theories and applications. However, significant challenges still exist in assessing the quality and uncertainty of complex hydrometeorological processes and improving hydrometeorological predictions, especially high-impact hydrometeorological events. This session solicits papers that focus on, but are not limited to, (1) addressing uncertainty in hydrometeorological forecasting from different sources in both offline and couple systems, and (2) hydrometeorological ensemble forecasting methods. The former might include uncertainties in forcing data (quantitative precipitation estimation, meteorological forcing data, and so on), initial conditions (such as soil moisture and heterogeneous geographical conditions), parameters, model structure (physics), calibration, and statistical postprocessing of hydrometeorological model output, and innovative methods for assessing uncertainty information from observations to modeling and postprocessing processes. The latter emphasizes integrated ensemble methods to improve individual hydrologic and atmospheric models, or coupled atmosphere–land–hydrology systems, verification methods to evaluate probabilistic hydrometeorological forecasting, and technologies to process systematic errors of hydrometeorological forecasting at different spatial and temporal scales.