DOI: 10.5281/zenodo.10089609
title: Future NG-IDF Dataset for CONUS Design Extreme Event Projections

description: Future NG-IDF dataset consists of projections of design extreme events in future climates across the CONUS. Future climates are represented by an ensemble of 10 downscaled CMIP5 global climate models (GCMs) under the RCP8.5 emission scenario. The dataset covers over 200,000 locations at a 1/16th-degree resolution. This dataset extends Sun et al. (2019) by including future projections following the Next-Generation Intensity-Duration-Frequency (NG-IDF) approach (Yan et al., 2018). In contrast to traditional precipitation-based IDF methods such as NOAA Atlas 14, which neglects snow processes, NG-IDF accounts for the total water reaching the land surface (AWR) from rainfall, snowmelt, and rain-on-snow (ROS) events.
Downscaled GCM climate forcing was derived through the Multivariate Adaptive Constructed Analogs (MACA) method for statistical downscaling and were bias-corrected against the Livneh gridded meteorological dataset (Livneh et al., 2013), which is the climate forcing used for the historical CONUS NG-IDF (Sun et al., 2019). The selection of the 10 GCMs was based on their divergence in projecting future changes in temperature and precipitation for the CONUS, as well as their accuracy in representing historical climate conditions. The chosen GCMs are bcc-csm1-1, BNU-ESM, CCSM4, CNRM-CM5, CSIRO-Mk3-6-0, inmcm4, IPSL-CM5A-LR, IPSL-CM5A-MR, MRI-CGCM3, and NorESM1-M. The MACA downscaled GCM projections for future climate forcing are available at: Northwest Knowledge Network.
Driving Mechanism Classification for Extreme AWR Events:
Extreme AWR events at each location are classified by their driving mechanisms as follows:

precip: Sum of snowfall and rain, with the assumption that both contribute instantaneously to runoff
rainfall: Precipitation on snow-free ground.
melt_only: Decreasing SWE, daily rainfall < 10 mm, and the sum of rainfall and snowmelt has < 20% contribution from rainfall.
ROS: Rain-on-snow - Decreasing SWE with at least 10 mm of daily rainfall falling on a snowpack with at least 10 mm daily SWE, and snowmelt contributes at least 20% of the total of rain and snowmelt.
AWR: Amount of water reaching the land surface from rain, snowmelt, and ROS events.
Folder Structure:

historical/matlab_matrix/: baseline period
rcp85/matlab_matrix/: future period
For each GCM, there are 'historical' and 'rcp85' subfolders for baseline and future periods, respectively. Within the subfolder, files list discrete IDF values by event duration (24h, 48h, and 72h) and mechanism (AWR, precip, rainfall, ROS, and melt_only).
File Naming Convention: 

The naming convention is [duration]_[mechanism].mat, e.g., 24hr_AWR.mat
Data Dimension: 

The data is structured in a three-dimensional array of 381 x 921 x 7. The first dimension corresponds to the latitude index, and the second to the longitude index, mapping to specific geographic coordinates. The third dimension represents NG-IDF values for return periods of 2, 5, 10, 25, 50, 100, and 500 years. 'NaN' indicates no runoff generated by a specific mechanism, such as ROS. 

Coordinate Reference:

Each latitude and longitude index is directly mapped to the corresponding row or line number in the 'CONUS_livneh_lat.csv' and 'CONUS_livneh_lon.csv' files, which contain 381 and 921 lines, respectively.
Unit of NG-IDF Values:

millimeter (mm)