This website provides scientifically based estimates of future values for intensity–duration–frequency (IDF) curves for heavy precipitation events for locations in the United States. These future values incorporate changes due to potential global warming. Two greenhouse gas emissions scenarios are provided, RCP8.5 which is a high emissions scenario with large greenhouse gas increases through the 21st century and RCP4.5 which is a mid-range greenhouse gas emissions scenario where emissions increase to about 2050 then decline thereafter. These estimates were derived using NOAA Atlas 14 values as the basis and then making adjustments based on the scientific findings of this project. This website is the final deliverable for a research project funded by the Strategic Environmental Research and Development Program (SERDP/Department of Defense). The project final report and relevant journal articles are accessible under Downloads.

Photo by Dallas Krentzel. Licensed under CC BY 2.0.


These results are for research use only.

This website is the end result of a research project, whose objective was the incorporation of future climate change into the precipitation frequency values typically used by engineers and infrastructure designers. This project deliverable was produced for the Strategic Environmental Research and Development Program (SERDP/Department of Defense). Given its timeliness and importance, it is being released for use by the public.


Because infrastructure is designed and built for lifetimes of several decades, there is urgency in considering future climate conditions. However, there is currently no national product that provides heavy precipitation design values that take into account climate change. The official source of precipitation frequency estimates used for engineering and design is NOAA Atlas 14, which used statistics based on historical observations. Relying only on Atlas 14 for the design of long-lived infrastructure does not account for future precipitation changes. By combining climate model projections for precipitation in the 21st century with Atlas 14 estimates as the historical baseline, this product aims to assist engineers and infrastructure designers as they plan for a future where extreme rainfall is anticipated to be more frequent and more intense.

This project (“Incorporation of the Effects of Future Anthropogenically Forced Climate Change in Intensity-Duration-Frequency Design Values”) was funded by the U.S. Department of Defense Strategic Environmental Research and Development Program (SERDP). Our proposed work was in response to SERDP’s FY2015 Statement of Need (SON) under the Resource Conservation and Climate Change Program area “Adapting to Changes in the Hydrologic Cycle Under Non-Stationary Climate Conditions.” Our proposal addressed the following SON objective—improve our fundamental and applied understanding of . . . the non-uniform spatial and temporal distribution of potential climate-induced changes in the intensity and variability of heavy precipitation—and the particular SON focus on developing the methodologies for constructing IDF curves, especially under non-stationary conditions. The SON further identifies research needs as developing or improving our understanding of potential stationarity versus non-stationarity of future precipitation relative to a changing climate. As background, the SON notes:

A key focus of the SON is to understand how precipitation (rain and snow) and its variability may change with time and location, and whether localized systems can be considered to operate under stationary or non-stationary conditions. This information is critical for maintaining currency of IDF curves, which have historically been developed using past rainfall patterns. IDF curves are widely used. Therefore, accurately accounting for changing precipitation patterns will be essential for enabling engineering standards and building codes to appropriately adapt and prepare for a changing climate and localized site conditions.

This project was a joint effort of the North Carolina Institute for Climate Studies (NCICS) of North Carolina State University (NCSU) and the NOAA National Centers for Environmental Information (NCEI) . It was led by Dr. Kenneth Kunkel (Lead Principal Investigator), NCSU Research Professor; Dr. David Easterling (co-Principal Investigator), Director of the National Climate Assessment Technical Support Unit; and Dr. Thomas Karl (co-Principal Investigator), retired Director of NOAA NCEI. Scientists from NCICS and NCEI contributing to the project included James Biard, Sarah Champion, Byron Gleason, Dr. Katharine Johnson, Angel Li, Dr. Steven Stegall, Laura Stevens, Scott Stevens, Michael Squires, Dr. Liqiang Sun, and Dr. Xungang Yin.

Methodological Summary

The product uses NOAA Atlas 14 values as a baseline and applies adjustment factors to the NOAA Atlas 14 values. The methodology to compute these adjustment factors blends two approaches. One approach is commonly used by researchers. The second approach is new, specifically developed for this project. For more information on these approaches, see the Technical Approach and Results sections below.

In addition to the estimates for future precipitation frequency, the product provides confidence intervals that include the uncertainty associated with future changes in precipitation. These intervals are larger than what is given in NOAA Atlas 14, reflecting uncertainties in the level of global greenhouse gas emissions and their effects on the climate system through the 21st century.


Numerous scientific assessments have shown that human-induced climate changes are occurring, and more changes are expected as atmospheric composition is altered. This project focused on how these changes affect extreme precipitation rates, specifically the IDF values that are used by engineers and others for planning, design, and operations. The most comprehensive set of existing IDF curves developed over the past two decades—NOAA Atlas 14—is based on the assumption of a stationary climate. The key objective of this work was to transform stationary IDF values into a new set that accounts for a non-stationary climate with varying degrees of climate change.

Although global climate models (GCMs) are the backbone of understanding past and future climate, they are known to have deficiencies in simulating the extreme precipitation rates of interest here. A number of methods have been developed to help overcome many of these deficiencies. This work built upon these existing methods to enable robust uncertainty estimates of future IDF values and, most importantly, provide an understanding of why changes in the IDF values are expected for specific locations and future times.

Technical Approach

Two complementary methods were used to provide best estimates for future IDF values. The differing methods provide a basis for assessing uncertainty of future changes. The sources of uncertainty include 1) differing rates of human-caused changes to atmospheric composition, 2) the sensitivity of the climate to changes in atmospheric composition, 3) parameter estimation uncertainty of model coefficients, 4) structural uncertainty related to the approach used, and 5) statistical sampling uncertainty. The first approach to estimate future changes applied a statistical method known as generalized extreme value (GEV) to a statistically downscaled climate model precipitation dataset. The second method made use of changes in well-simulated meteorological factors shown to contribute to extreme precipitation rates. These factors include column-integrated water vapor (i.e., precipitable water [PW]) and the weather systems causing upward vertical velocity responsible for condensing the water vapor into precipitation. Changes in PW, weather fronts, and extratropical cyclones were calculated from GCM simulations of past and future climate, and they were used to transform IDF values from stationary to non-stationary estimates.


Observations show that over the past several decades, the interval between extreme precipitation events is decreasing as they become more frequent across a wide range of durations. This is not evident in all areas, but it is the predominant trend and is strongly linked to increases in PW. Global climate models project widespread increases in PW as the climate warms with various scenarios of human-induced changes of atmospheric composition. As a result, as time evolves, the projected IDF values generally lead to greater frequency of, and shorter intervals between, extreme precipitation events for a wide range of thresholds and duration times. Additionally, the rarer events tend to increase more than less-rare events (e.g., 50-year return period versus 1-year return period), regardless of duration. These projected changes are well beyond standard uncertainty intervals. The projected changes in other factors, such as fronts and extratropical storms, are not ubiquitous, and the magnitude of extreme precipitation is shown to be less sensitive to these changes compared to PW. This is because even when weather systems change in frequency, they still occur often enough to trigger copious precipitation when PW is high. However, the projected weather system changes, combined with varying degrees of increases in water vapor, do add to the spatial and temporal variability of projected IDF values.

The scientific findings were used to develop adjustment factors that were applied to existing IDF values from NOAA Atlas 14. The adjusted IDF values incorporate potential future changes in extreme precipitation from anthropogenic climate change under moderate and high emissions scenarios (RCP4.5 and RCP8.5, respectively). Design values are available for seven future target periods: 30-year periods centered on 2025, 2035, 2045, 2055, 2065, 2075, and 2085.

The major scientific finding is that atmospheric water vapor concentration is the major determining factor for the magnitude of extreme precipitation events. An analysis of historical events showed that extreme precipitation amounts scale closely with precipitable water (vertically integrated water vapor) and that the scaling factor increases with increasing precipitable water. Analysis of global climate model simulations indicates that global warming leads to increases in atmospheric water vapor concentrations at approximately the Clausius–Clapeyron rate (about 7% per °C). Water vapor is the dominant component in the adjustment factors. This is a consequence of the strong relationship in the observational record between extreme precipitation amounts and water vapor combined with the highly confident projections of large increases of future water vapor. This leads to large (>20%) increases in IDF values by the end of the century under the high emissions scenario (RCP8.5).

A complementary method was developed based on GEV methodology. This analysis used the Localized Constructed Analogs dataset, which is a relatively new statistically downscaled dataset for the continental US. This dataset includes daily precipitation data for 32 CMIP5 models covering the period 1950–2100. Spatial resolution is 1/16th degree. We performed GEV analysis on the annual maximum series of 1-day, 5-day, 10-day, 20-day, and 30-day precipitation totals for four 30-year periods (1976–2005, 2006–2035, 2036–2065, and 2070–2099) to estimate future changes in various return period amounts. The following conclusions are derived from this GEV analysis:

  • The future changes in return period threshold values increase with return period, 100-year changes being greater than 5-year changes.
  • The future changes increase substantially with increased greenhouse gas forcing.
  • The future changes are very large by the end of the century under the RCP8.5 scenario.
  • The spatial variability is relatively small compared to the magnitude of the changes by the mid- to late 21st century.
  • Future changes generally decrease slightly with increasing duration.

This separate GEV-derived set of adjustment factors was combined with the adjustment factors derived from the water vapor and weather systems approach, which added to our uncertainty estimates.

It should be noted that other organizations (e.g. Northeast Regional Climate Center) provide similar scientifically based estimates for future values for intensity–duration–frequency (IDF) curves for some regions. Although the estimates were derived using different methods, they are statistically consistent with the values presented here, since they generally fall within the 90% confidence intervals for the estimates for a given location.