Session 9B Probabilistic Hydrometeorological Forecasting and Uncertainty Analysis II

Wednesday, 9 January 2019: 10:30 AM-12:00 PM
North 126BC (Phoenix Convention Center - West and North Buildings)
Host: 33rd Conference on Hydrology
Cochairs:
Huiling Yuan, Nanjing Univ., School of Atmospheric Sciences, Nanjing; Kristie J. Franz, Iowa State Univ., Geological and Atmospheric Sciences, Ames, IA and Shugong Wang, NASA GSFC/SAIC, Hydrological Sciences Laboratory, Greenbelt, MD

Over the last several decades, substantial progress has been achieved in probabilistic hydrometeorological forecasting theories and applications. However, significant challenges still exist in assessing the uncertainty of complex hydrometeorological processes and improving the quality of 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 a number of sources in both offline and couple systems, and (2) innovative methods in hydrometeorological ensemble forecasting. The former might include uncertainties in forcing data (e.g., quantitative precipitation estimation, meteorological forcing data), initial conditions (e.g., soil moisture, heterogeneous geographical conditions), parameters, model structure (physics), and calibration.  The latter emphasizes integrated ensemble methods to improve individual hydrologic and atmospheric models, 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. Work on topics of statistical postprocessing of hydrometeorological model output and assessing the uncertainty of postprocessing are also encouraged.

Papers:
10:30 AM
9B.1
10:45 AM
9B.2
Ensemble Streamflow Forecasts Using Spatially Shifted QPF
Kristie J. Franz, Iowa State Univ., Ames, IA; and B. R. Carlberg and W. A. Gallus Jr.
11:00 AM
9B.3A
The Forecast Informed Reservoir Operations Project for Lake Mendocino—Lessons Learned So Far (Invited Presentation)
Michael L. Anderson, California Department of Water Resources, Sacramento, CA; and F. M. Ralph, J. Jasperse, and C. Talbot
11:15 AM
9B.4
11:30 AM
9B.5
Hydrologic Ensemble Forecast at the Russian River Watershed
Ali Hamidi, SIO, La Jolla, CA; and L. Diaz, R. Weihs, F. Cannon, A. Martin, and F. M. Ralph
11:45 AM
9B.6
Probabilistic Urban Flood Forecasting System for Chinese Mega Cities Using Advanced Active Phased Array Radar
Dehua Zhu, Nanjing Univ. of Information Science and Technology, Nanjing, China; and Y. Xuan, X. Bao, Y. Chen, and D. Hu

- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner