This opportunity invites highly motivated individuals to work with a team of dedicated meteorologists, hydrologists, and engineers to conduct cutting edge research in hydrometeorology, supporting NOAA’s mission of science, service, and stewardship. The Hydrometeorology Modeling and Applications (HMA) and the Hydrometeorology Observations and Processes (HOP) teams in NOAA’s Physical Sciences Laboratory focus on advancing hydrometeorology methods, models, observations, and applications to address water resource management concerns, especially as they relate to water extremes (both too wet and too dry). This information is used to provide guidance on observing network design, modeling assimilation and analysis, and predictions that can be applied in NOAA operations, as well as informing local, regional, and national communities, planners, and decision makers. Examples of research activities include (1) analyzing observations, model simulations, and reanalysis datasets to better understand key physical processes responsible for atmospheric or hydrologic model performance; (2) developing methods to evaluate hydrologic forecasts, including disentangling errors between forcing inputs and model physics ; (3) improving process understanding of the drivers, trends, and impacts of drought; (4) contributing to NOAA’s Hydrometeorology Testbed (HMT) through analysis of data from field experiments and atmospheric and hydrologic models and/or developing prototype tools for use in forecast operations; and (5) using radar, satellite, or in-situ observations to advance precipitation process understanding and improve precipitation estimates and forecasts, especially in areas of complex terrain.
Cifelli R, et al: High Resolution Radar Quantitative Precipitation Estimation in the San Francisco Bay Area: Rainfall Monitoring for the Urban Environment. Journal of the Meteorological Society of Japan 96A: 141-155, 2018
Matrosov SY, et al: Hydrometeor Shape Variability in Snowfall as Retrieved from Polarimetric Radar Measurements. Journal of Applied Meteorology and Climatology 59: 1503-1517, 2020
White AB, et al: Winter Storm Conditions Leading to Excessive Runoff above California’s Oroville Dam during January and February 2017. Bulletin of the American Meteorological Society 100: 55-70, 2019
Precipitation; Hydrology; Hydrometeorology; Quantitative precipitation estimation; Quantitative precipitation forecasting; Hydrologic forecasting; Process understanding; Radar meteorology; Hydrologic modeling