Joint Poster Session 7 Probabilistic Hydrometeorological Forecasting and Uncertainty Analysis

Wednesday, 10 January 2018: 3:45 PM-5:30 PM
Exhibit Hall 3 (ACC) (Austin, Texas)
Hosts: (Joint between the 32nd Conference on Hydrology; and the 25th Conference on Probability and Statistics )
Huiling Yuan, Nanjing Univ., School of Atmospheric Sciences, Nanjing; Qingyun Duan, Beijing Normal Univ., College of Global Change and Earth System Science, Beijing and Kristie J. Franz, Iowa State Univ., Geological and Atmospheric Sciences, Ames, IA

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.

Impact of Downscaling on Forcing Engine for Operational Water Prediction System of National Water Center
Linlin Pan, NCAR, Boulder, CO; and D. Gochis, W. Yu, A. Dugger, J. Grim, Y. Zhang, A. Rafieeinasab, L. Karsten, Y. Liu, and B. Cosgrove

Improving Hydrologic Forecasting Using Ensemble Conditional Bias-Penalized Kalman Filter
Haksu Lee, Len Technologies, Inc., Oak Hill, VA; and D. J. Seo, Y. Zhang, S. Kim, and S. Noh

High-Resolution, Multi-Model Hydrological Seasonal Forecasting for Water Resources Management over Europe
Ming Pan, Princeton Univ., Princeton, NJ; and N. Wanders, E. F. Wood, J. Sheffield, L. Samaniego, S. Thober, R. Kumar, C. Prudhomme, and H. Houghton-Carr

Simulation and Test of Flood Routing Based on GIS Rainstorm Flood Inundation Model
Limei Ye, Institute of Heavy Rain, China Meteorological Administration, Wuhan, China; and T. Peng and Y. Zhou

NWP Forecast Performance for Significant Precipitation Events over Southwest British Columbia
Anthony Di Stefano, Univ. of British Columbia, Vancouver, BC, Canada; and D. M. Siuta, G. L. West, and R. B. Stull

Calibration of QPF Using the Optimal Percentile Method
Kan Dai, National Meteorological Center of China Meteorological Administration, Beijing, China; and Y. Zhu

Evaluation and Statistical Analysis of Short-Term WRF QPFs for Santa Clara Valley in Winter 2016/17
Arthur Eiserloh, San Jose State Univ., San Jose, CA; and C. Keene and S. Chiao

An Investigation of the Forecast Performance for Precipitation in the Extended Global Ensemble Forecast System (GEFS) Reforecast
Eric Sinsky, NOAA/NCEP/EMC and IMSG, College Park, MD; and Y. Zhu, H. Guan, C. Melhauser, Y. Luo, and W. Li

Evaluation of GRAPES Global Ensemble Prediction System (GRAPES-GEPS) of CMA
Yinglin LI, National Meteorological Center of the China Meteorological Administration, Beijing, China

Jiangsu Moisture Characteristics Analysis in Different Weather Background of Plum Flood Season
Mei Liu, Jiangsu Meteorology Observation, Nanjing, China; and J. Yu, L. Wang, and M. Yang

Sensitivity of Orographic Precipitation to Microphysics Parameter and Process Perturbations
Annareli Morales, Univ. of Michigan, Ann Arbor, MI; and D. J. Posselt and H. Morrison

Stochastic Parameter Perturbation in Grell-Freitas Convective Parameterization
Isidora Jankov, CIRA/Colorado State Univ., Boulder, CO; and G. Grell and J. Berner

Analysis on the Key Factors in Causing Heavy Rain and Precipitation Forecast Deviation in a Regional Persistent Heavy Rainfall
Jianwei Yu, Jiangsu Meteorology Observation, Nanjing, China; and M. Liu, M. Yang, and S. Chen

Analysis for Cold Water Lenses off the Jiangsu Coast Based on Observation and Simulation
Wenjing Zhang, National Univ. of Defense Technology, Nanjing, China; and S. Zhu and X. Z. Wang

On the Detection of Statistical Heterogeneity in Rain Measurement
A. R. Jameson, RJH Scientific, Inc., Arlington, VA; and M. L. Larsen and A. B. Kostinski

Handout (85.0 kB) Handout (85.7 kB)

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