Probable Maximum Precipitation

MetStat, Inc. and its partners are a highly qualified team of nationally-recognized experts for conducting Probable Maximum Precipitation (PMP) studies. Since the mid-1990s, MetStat has provided integral pieces of numerous probable maximum precipitation studies and developed the technical framework (storm analyses; dew point and sea surface temperature climatologies; precipitation-frequency analyses for storm transposition; rain/snow assessments; and GIS support) of PMP studies, including the statewide PMP studies for Nebraska (2008), Arizona (2013), Wyoming (2014), Virginia (2015) and Texas (2016). In addition to producing technical elements of PMP studies, MetStat has led several PMP studies from concept to completion. Our PMP studies have supported dam owners, mining operations and nuclear power plants throughout the United States; including FERC-licensed dams with chute-like spillways that are being evaluated for potential erosion damage as a result of lessons learned from Oroville Dam.


30 different storm transpositions across northern Utah of the famous Rattlesnake, ID storm of November 18-25, 1909.

MetStat’s PMP Experience

MetStat provides a complete, cohesive and integrated solution that results in a cost-effective, state-of-the-science site-specific, statewide or regional PMP solution. MetStat is the right choice for PMP studies for the following reasons:

  • MetStat originally conceptualized, developed and implemented the Storm Precipitation Analysis System (SPAS) software in 2002. In 2014-2016, MetStat independently developed a new and improved storm analysis software, MetStorm®, providing the next generation software for storm analyses.
  • The MetStat team has over 100 years of combined experience and consists of Certified Consulting Meteorologists (CCMs), GIS Professionals, Professional Engineers (PEs), and multiple M.S./Ph.D. holders in Meteorology, Civil Engineering, and Watershed Science. In fact, several members have published books and numerous journal/conference papers on extreme precipitation and weather in the western United States.
  • Many of the advances in PMP estimation during the past 20 years have been developed and implemented by MetStat and our strategic partners, including Atmospheric Science Consultants and MGS Engineering Consultants.
  • Similar to NOAA’s Precipitation Frequency Data Server, which was originally designed by MetStat, we provide cost-effective Graphical User Interfaces (GUIs) for accessing, querying, and downloading PMP data.
  • MetStat effectively couples PMP and precipitation-frequency disciplines, thereby offering the benefits of each approach.
  • MetStat has roots from a variety of disciplines, including strong academic, government and private industry backgrounds in weather, climate, hydrology, regulatory, civil engineering, and statistical fields. Our rich blend of backgrounds provides a well-rounded and helpful perspective.
  • Members of MetStat and our strategic partners have been on independent technical review boards for PMP studies, making us familiar with the needs, interests and expectations of a successful PMP study.

Our PMP Approach

Our PMP approach follows methods similar to those used by the National Weather Service in the Hydrometeorological Reports on Probable Maximum Precipitation, and methods prescribed in the World Meteorological Organization’s Manual on Estimation of Probable Maximum Precipitation. We leverage new and accepted improvements to PMP methodologies to address the complexities associated with various meteorological, climatological and topographical settings. The procedural improvements have been reviewed and accepted by numerous peer reviewers including the Federal Energy Regulatory Commission (FERC), the Nuclear Regulatory Commission (NRC), and several state dam regulators as part of other PMP and extreme precipitation studies.

Our probable maximum precipitation development is divided into the following standard-of-practice steps:

  1. Literature Review: A review of HMRs and all other relevant studies.
  2. Storm Search: Leverage MetStat’s in-house storm database, prior PMP studies, findings from the literature review, discussions with State Climatologists, and queries from MetStat’s extensive precipitation gauge database and from the NOAA National Center for Environmental Information.
  3. Storm Typing: Storms are categorized into storm types based on relevant meteorological characteristics of the study area.
  4. Storm Analysis: Potential PMP controlling storms are analyzed with MetStorm® to create the gridded storm analyses output required for transposition and maximization.
  5. Determine Transposition Limits: Transposition limits are defined by regions of similar climatology related to moisture availability, orographic contributions, and storm type. Each storm has a specific transposition region or limit and is restricted to transposition within that domain.
  6. In-Place Maximization: In-Place Maximization Factors (IPMFs) are calculated based on sources of available atmospheric moisture (surface dewpoint or sea surface temperatures) and a climatology of maximum available atmospheric moisture. The HYSPLIT back-trajectory model is used to determine the location of storm representative moisture locations.
  7. Storm Transpositioning: Storm transpositioning provides a critical mechanism to move storms that occurred in one location to estimate the storm characteristics had the storm occurred in different location. Transpositioning storms require similarities in the general meteorological and topographical characteristics of the source and target location, however adjustments are made to account for differences in the local meteorology and topography. The transposition process requires adjustment of storms based on relative changes in available atmospheric moisture, moisture depletion barriers, orographic/topographic effects, and distances from moisture sources. The Enhanced Storm Transposition Procedure (ESTP) is used to “move” the entire storm’s spatial and temporal patterns (hourly precipitation grids) and adjust for differences in orography and moisture-availability using underlying precipitation-frequency reference information. As the name implies, this is a major improvement to the process of adjusting storm depth-area-duration (DAD) tables for moisture and orographics as described in the HMRs.
  8. Quality Control, Sensitivity/Uncertainty, Reasonableness Checks: Quality control and performance assessments are an on-going process throughout a project. Sources of uncertainty in the PMP analysis process are evaluated and explained.
  9. Final Report and Products: MetStat provides a customizable deliverable to meet the needs of the client/project.
The family of depth-area curves using 30 different storm transpositions of 3 different maximized storms, plus the envelopment curve (black line) which represents an initial estimation of PMP.

Past PMP Projects

Below are probable maximum precipitation projects that have previously been completed here at MetStat. Additional projects that are underway may be found on the project portfolios page.

Henderson Mill Drainage Basin Springtime Maximum Rainfall

Henderson Mill is located in the high elevations of the Colorado Rockies where the risk to hydrologic infrastructure may be associated with rain-on-snow events. In this study, MetStat® conducted a storm search for extreme storms to identify rainfall-dominated precipitation patterns during the Spring runoff season for application in a maximum precipitation study. Using traditional methods for developing probable maximum precipitation, storm analyses were performed, which included: the generation of storm temporal and spatial patterns; development of depth-area-duration (DAD) curves; storm maximization and transposition; elevation adjustments; and, calculation of a maximum precipitation value. Storm maximization and transposition requires an assessment of the source and magnitude of moisture inflow into the storm using the HYSPLIT back-trajectory model (see figure). In addition, areal reduction factors were applied to reduce the point maximum precipitation to the area size of the watershed. The output from the springtime maximum precipitation study will be implemented in a hydrologic model with a snowmelt runoff climatology information to generate a rain-on-snow hydrograph for assessment of risk in the Henderson Mill drainage. This project was a collaborative effort between MetStat® and Atmospheric Science Consultants.

Backtrajectory and surface dewpoint analysis locations that were used to determine transposition factors in the Henderson Mill PMP project.