README FrEDI: The Framework for Evaluating Damages and Impacts
Source:R/FrEDI-package.R
FrEDI-package.RdFrEDI is an R package that is developed and maintained by the U.S. Environmental Protection Agency (EPA). The functions and data provided in this package can be used to project impacts of climate change within the contiguous United States (CONUS), under any custom temperature or socioeconomic trajectory, using the Framework for Evaluating Damages and Impacts (FrEDI) that was developed as part of EPA's Climate Change Impacts and Risk Analysis (CIRA) project. The FrEDI package contains R code that implements FrEDI and allows users to project annual impacts from climate change and sea level rise across over 20 impact sectors, geographic regions, and populations through the end of the 21st century (and optionally through 2300). While this framework does not currently account for all ways in which the American public may be impacted by future climate change, this type of detailed information helps EPA to better understand and communicate the types of potential impacts and risks from future climate change in the United States, as well as the potential benefits of greenhouse gas mitigation and adaptation.
Details
See the FrEDI Technical Documentation for additional information about the underlying theory, design, structure, components, and capabilities of FrEDI, as well as examples of some of its intended uses and applications. For help getting started with FrEDI, visit https://usepa.github.io/FrEDI/articles/manual.html. For additional package documentation, see https://usepa.github.io/FrEDI/index.html.
Overview of Functions
The function run_fredi() provided in this package is the primary function implementing the Framework for Evaluating Damages and Impacts (FrEDI), developed by the U.S. EPA for projecting annual climate impacts. The main inputs to run_fredi() are climate scenarios (temperature in degrees Celsius, global mean sea level rise in centimeters) and socioeconomic scenarios (U.S. gross domestic product, state population).
FrEDI also contains functions to assist in the pre-processing of input scenarios and the post-processing of outputs.
Pre-processing functions include
get_sectorInfo(),import_inputs(),convertTemps(),temps2slr().get_sectorInfo()allows users to access a list of sectors withinFrEDIand related sector information.import_inputs()helps users in importing custom scenarios from user-specified comma-separated value (CSV) files.convertTemps()helps users to convert between global mean temperature and temperatures for the contiguous United States (CONUS) (both in degrees Celsius).temps2slr()helps users to estimate global mean sea level rise (GMSL, in centimeters) from global mean temperature in degrees Celsius.
aggregate_impacts() is a post-processing helper function that helps users to aggregate and summarize the outputs of FrEDI. aggregate_impacts() can be used to calculate national totals, model averages, sum over impact types, and interpolate between multiple impact years (note that run_fredi() will automatically run aggregate_impacts() before returning outputs if the aggLevels argument is not "none").
Versions 2.3.0 and above include the FrEDI Social Vulnerability (SV) module for estimating impacts on socially vulnerable populations for select sectors. get_sv_sectorInfo() allows users to access a list of sectors within the FrEDI SV module and related sector information. The function run_fredi_sv() is the main function for the FrEDI SV module. run_fredi_sv() is designed to calculate impacts for a single sector at a time for a custom population scenario or one or more custom temperature or sea level rise scenarios. For more information on the data underlying the FrEDI SV module, see https://www.epa.gov/cira/social-vulnerability-report/.
Overview of Package Contents
FrEDI consists of files in the following directories:
R. Contains function definitions (files ending in
".R") and configuration files (ending in".rda").data. Contains R Data files ending in
".rdb",".rds", and".rdx", containing data included with the package.help and html. Contain documentation for functions available to the user, including function descriptions, lists of arguments and outputs, and examples. See
"html/00Index.html"or the individual R help functions for more information about individual functions.Meta. Contains RDS files (ending in
".rds") with information about the package contents.extdata. extdata/scenarios Contains four CSV files for users to test the function for importing data. For more information on importing scenarios for use with
run_fredi(), refer to documentation for the functionimport_inputs()."GCAM_scenario.csv"contains a set of temperature scenarios that can be used with FrEDI, including the default temperature scenario used by bothrun_fredi()andrun_fredi_sv(). Also see documentation for the gcamScenarios dataset for more information."State ICLUS Population.csv"contains the default state population scenario used byrun_fredi()(see popScenario and popScenario_sv)."slr_from_GCAM.csv"contains global mean sea level rise heights in centimeters (created from the reference temperature scenario).
extdata/sv Contains files used by the
FrEDISV module to calculate impacts.
The FrEDI package contains a loadable dataset with default results defaultResults, which contains annual impacts produced by run_fredi() for the with the default options and default scenarios (i.e., default temperature, GDP, and state population trajectories). Other loadable datasets provided by FrEDI are a set of driver scenarios (gcamScenarios) and a state population scenario (popScenario) for use with run_fredi() or run_fredi_sv(), which can be loaded into the workspace using the data() function (e.g., data(gcamScenarios)).
Typical use will involve library(FrEDI) or require(FrEDI).
Status
Disclaimer: All code in this repository is being provided in a "draft" state and has not been reviewed or cleared by U.S. EPA. This status will be updated as models are reviewed.
Dependencies
FrEDI requires R (>= 4.2.0).
FrEDI depends on:
tidyverse (Easily Install and Load the 'Tidyverse'). The official documentation for tidyverse can be found here. tidyverse can be installed using
install.packages("tidyverse"), or see link for more information.ggpubr ('ggplot2' Based Publication Ready Plots). The official documentation for ggpubr can be found here. ggpubr can be installed using
install.packages("ggpubr"), or see link for more information.openxlsx (Read, Write and Edit
xlsxFiles). The official documentation for openxlsx can be found here. openxlsx can be installed usinginstall.packages("openxlsx").
EPA Disclaimer
The United States Environmental Protection Agency (EPA) GitHub project code is provided on an "as is" basis and the user assumes responsibility for its use. EPA has relinquished control of the information and no longer has responsibility to protect the integrity, confidentiality, or availability of the information. Any reference to specific commercial products, processes, or services by service mark, trademark, manufacturer, or otherwise, does not constitute or imply their endorsement, recommendation or favoring by EPA. The EPA seal and logo shall not be used in any manner to imply endorsement of any commercial product or activity by EPA or the United States Government.
By submitting a pull request to the GitHub and/or by installing this package, you make an agreement with EPA that you will not submit a claim of compensation for services rendered to EPA or any other federal agency. Further, you agree not to charge the time you spend developing software code related to this project to any federal grant or cooperative agreement.
Author
Maintainer: Corinne Hartin hartin.corinne@epa.gov (ORCID) (cahartin)
Authors:
Erin McDuffie mcduffie.erin.e@epa.gov (ORCID) (emcduffie) [contributor]
Marcus Sarofim mcduffie.erin.e@epa.gov (ORCID) (emcduffie) [contributor]
Karen Noiva (ORCID) (knoiva-indecon) [contributor]
Other contributors: