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This repository provides weekly US Drought Monitor (USDM) data aggregated to the US Census 2020 county boundaries. This dataset facilitates county-level analysis of drought conditions, supporting research, policy-making, and climate resilience planning.

📂 View the US Drought Monitor Census 2020 county archive listing here.

Federal law and FSA guidance describes a process by which county-level eligibility is determined by the intersection of county boundaries, the United States Drought Monitor weekly drought assessment, and the normal grazing period for each type of grazing land in each county.

📈 About the US Drought Monitor (USDM)

The US Drought Monitor is a weekly map-based product that synthesizes multiple drought indicators into a single national assessment. It is produced by:

  • National Drought Mitigation Center (NDMC)
  • US Department of Agriculture (USDA)
  • National Oceanic and Atmospheric Administration (NOAA)

Each weekly map represents a combination of data analysis and expert interpretation.

The USDM weekly maps depicting drought conditions are categorized into six levels:

  • None: Normal or wet conditions
  • D0: Abnormally Dry
  • D1: Moderate Drought
  • D2: Severe Drought
  • D3: Extreme Drought
  • D4: Exceptional Drought

While USDM drought class boundaries are developed without regard to political boundaries, it is often aggregated by political boundaries to assist in decision-making and for regulatory purposes. This repository focuses on aggregating these data to the county level, enabling more localized analysis and decision-making.

Note: This archive is maintained by the Montana Climate Office, but all analytical authorship of the USDM drought maps belongs to the named USDM authors.

🗂 Directory Structure

  • usdm-counties-census-2020.R: R script that processes and aggregates weekly USDM shapefiles to county boundaries.
  • data/: Directory containing processed county-level USDM data.
  • README.Rmd: This README file, providing an overview and usage instructions.

Data Sources

  • USDM Polygons: Weekly .parquet files from sustainable-fsa/usdm
  • Census 2020 County Boundaries: Downloaded from the U.S. Census TIGER/Line archive for 2020.

USDM Polygons are reprojected to the same coordinate reference system as the Census 2020 County Boundaries, geometrically validated, and saved in .parquet format.

Processing Pipeline

The analysis pipeline is fully contained in usdm-counties-census-2020.R and proceeds as follows:

  1. Install and load dependencies:
  • Uses pak::pak() to ensure fresh, source-built installs of critical geospatial packages.

  1. Fetch the 2020 county boundaries from the census-counties archive, drop the territories, join the state name, and cache as data/census-2020-counties.parquet.

  2. Download and intersect:

  • For each weekly USDM .parquet file:
  • Read county and drought geometries
  • Perform spatial intersection
  • Calculate the percent of each county area affected by each drought class
  • Tabular output is saved to data/usdm/USDM_{YYYY-MM-DD}.parquet
  1. Output Structure: Each output file is a non-spatial .parquet file with the following fields:
  • STATEFP, State, COUNTYFP, County, CountyLSAD
  • usdm_date: The date of the USDM map
  • usdm_class: One of None, D0, D1, D2, D3, D4
  • usdm_percent: Proportion of the county in this drought class (as a decimal between 0 and 1)

🛠️ Dependencies

Key R packages used:

  • sf
  • terra
  • arrow
  • tidyverse
  • curl

The script installs all required packages using the pak package.

📍 Quick Start: Visualize a Weekly County USDM Map in R

This snippet shows how to load a weekly GeoParquet file from the archive and create a simple drought classification map using sf and ggplot2.

# Load required libraries
library(arrow)
library(sf)
library(ggplot2) # For plotting
library(tigris)  # For state boundaries
library(rmapshaper) # For innerlines function

## Get latest USDM data
latest <-
  jsonlite::fromJSON(
    "https://data.sustainable-fsa.com/usdm-counties-census-2020/manifest.json"
  )$path |>
  stringr::str_subset("parquet") |>
  max()
# e.g., [1] "data/usdm/USDM_2025-05-27.parquet"

date <-
  latest |>
  stringr::str_extract("\\d{4}-\\d{2}-\\d{2}") |>
  lubridate::as_date()

# Get the highest (worst) drought class in each county
usdm <-
  paste0("https://data.sustainable-fsa.com/usdm-counties-census-2020/", latest) |>
  arrow::read_parquet() |>
  dplyr::group_by(STATEFP, COUNTYFP) |>
  dplyr::filter(usdm_class == max(usdm_class))

## Load the US Census county data
counties <- 
  # You can read straight from online
  # sf::read_sf("https://data.sustainable-fsa.com/usdm-counties-census-2020/data/census-2020-counties.parquet") |>
  # sf::read_sf("data/census-2020-counties.parquet") |>
  tigris::counties(cb = TRUE,
                   year = 2020,
                   resolution = "5m",
                   progress_bar = FALSE) |>
  dplyr::filter(!(STATEFP %in% c("60", "66", "69", "78"))) |>
  # transform to WGS 84
  sf::st_transform("EPSG:4326") |>
  sf::st_cast("POLYGON", warn = FALSE, do_split = TRUE) |>
  tigris::shift_geometry() |>
  dplyr::group_by(STATEFP, COUNTYFP) |>
  dplyr::summarise(.groups = "drop") |>
  sf::st_cast("MULTIPOLYGON")

usdm_counties <-
  usdm |>
  dplyr::left_join(counties) |>
  sf::st_as_sf()

# Plot the map
ggplot(counties) +
  geom_sf(data = sf::st_union(counties),
          fill = "grey80",
          color = NA) +
  geom_sf(data = usdm_counties,
          aes(fill = usdm_class), 
          color = NA) +
  geom_sf(data = rmapshaper::ms_innerlines(counties),
          fill = NA,
          color = "white",
          linewidth = 0.1) +
  geom_sf(data = counties |>
            dplyr::group_by(STATEFP) |>
            dplyr::summarise() |>
            rmapshaper::ms_innerlines(),
          fill = NA,
          color = "white",
          linewidth = 0.2) +
  scale_fill_manual(
    values = c("grey80",
               "#ffff00",
               "#fcd37f",
               "#ffaa00",
               "#e60000",
               "#730000"),
    drop = FALSE,
    name = "Drought\nClass") +
  labs(title = "US Drought Monitor",
       subtitle = format(date, " %B %d, %Y")) +
  theme_void()

Latest USDM map date: September 01, 2026

📝 Citation

If you use this data in published work, please cite:

National Drought Mitigation Center, USDA, and NOAA. US Drought Monitor Weekly Maps Aggregated to US Census 2020 County Boundaries. Aggregated, curated, and archived by R. Kyle Bocinsky, Montana Climate Office, University of Montana. Sustainable FSA project. Accessed YYYY-MM-DD. https://sustainable-fsa.com/usdm-counties-census-2020/

Machine-readable metadata are in CITATION.cff; GitHub’s Cite this repository button (top right of the repo page) renders it as APA or BibTeX.

Acknowledgment: This work is part of the Enhancing Sustainable Disaster Relief in FSA Programs project, supported by the USDA Office of the Chief Economist, Office of Energy and Environmental Policy, and the USDA Climate Hubs.

📄 License

  • Raw USDM data (NDMC): Public Domain (17 USC § 105)
  • Processed data & scripts: © R. Kyle Bocinsky, released under CC0 and MIT License as applicable

⚠️ Disclaimer

This dataset is archived for research and educational use only. The National Drought Mitigation Center hosts the US Drought Monitor. Please visit https://droughtmonitor.unl.edu.

👏 Acknowledgment

This project is part of:

Enhancing Sustainable Disaster Relief in FSA Programs
Supported by USDA OCE/OEEP and USDA Climate Hubs
Prepared by the Montana Climate Office

📬 Contact

R. Kyle Bocinsky
Director of Climate Extension
Montana Climate Office
📧 kyle.bocinsky@umontana.edu
🌐 https://climate.umt.edu