PROBABLE MAXIMUM PRECIPITATION
PROJECT // NRC Carolinas
Probable Maximum Precipitation (PMP) estimates were last updated for the eastern half of the United States by the federal government in 1978. Due to the many nuclear infrastructure projects along rivers and reservoirs in the eastern United States, the Nuclear Regulatory Commission (NRC) provided funding to the Bureau of Reclamation Flood Hydrology, Meteorology, and Consequences Group to investigate multiple facets of the historical PMP process and to explore modernization through use of quantitative precipitation estimates (QPE; i.e., radar-gage blended rainfall).
After completing a review of the Hydrometeorological Reports (HMRs) series, the project focused on analysis of major tropical storms (e.g., Floyd and Fran) that impacted the Carolinas - which was the initial testbed for automated QPE projects at the then National Climatic Data Center, now NCEI. Results indicated that PMP had been exceeded at short-durations and area sizes during Fran and for larger area sizes and durations during Floyd over portions of North Carolina. These results were presented at the NRC's Probabilistic Flood Hazard Workshop multiple times by Dr. Caldwell of Weather & Water. The practice of applying these methods to PMP, precipitation frequency, and hydrologic hazards studies continues today based on this important work!
PROJECT // Entergy Arkansas
In 2014, while establishing a Hydrometeorology & Climate Change program at Leonard Rice Engineers, Jason led a significant project under subcontract to GZA for Entergy Corporation for a nuclear plant in northwestern Arkansas (followed by another smaller project in the New Orleans area). This project evaluated the estimated return period with uncertainty bounds for the Probable Maximum Precipitation in the Arkansas River Basin. In conjuction with MGS Engineering, he developed novel methods for extrapolation of NOAA Atlas 14 frequency estimates coupled with stochastic storm transposition approaches to constrain extrapolation and reduce uncertainty in the tails of the distribution through space-for-time substitution and using actual observations over a wide range of climate regimes.
Modelers at GZA ingested the inputs to evaluate hydrologic uncertainty - though Jason lef a statistical approach using the Australian Rainfall Runoff (ARR) method and PEAK-FQ software applied at federal agencies like Reclamation. Weather & Water continues to utilize similar methodologies, but has advanced the methods through use of reanalysis products and resampling techniques to produce a superior nationally consistent gridded frequency dataset. Look to the original implementation folks who continue to advance the science for your PMP and probabilistic PMP needs.