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imdR

imdR is an R package for downloading, processing, and visualizing India Meteorological Department (IMD) gridded daily meteorological data. It provides a complete pipeline from raw binary data to climate indices, trend analysis, and publication-quality maps — all within R.

What makes imdR different

SOI-approved boundaries bundled — state and district level maps with Survey of India shapefiles, ready to use with no extra downloads
State and district extraction — mask any IMD raster to any of 36 states or 808 districts in one line
Complete pipeline — download → extract → indices → trends → maps
No Python required — pure R implementation with additional capabilities beyond existing tools

Data coverage

Variable	Resolution	Period
Rainfall	0.25 degree	1901 to present
Maximum temperature	1.0 degree	1951 to present
Minimum temperature	1.0 degree	1951 to present

Installation

# Install from CRAN
install.packages("imdR")

# Or install the development version from GitHub
install.packages("remotes")
remotes::install_github("Subhradip25/imdR")

Quick start

library(imdR)

file_dir <- tempdir()

# Download 2020 rainfall data
rain2020 <- get_data("rain", 2020, 2020, file_dir)

# Plot a single day — full India map with SOI boundaries
plot_imd(rain2020, "2020-06-28", "rain")

# Zoom to Kerala
plot_imd(rain2020, "2020-06-28", "rain",
         level = "state", name = "Kerala")

# Extract daily time series at Panaji, Goa
goa_ts <- get_point(lat = 15.5, lon = 73.8,
                    variable = "rain",
                    start_yr = 2020, end_yr = 2020,
                    file_dir = file_dir)

# Plot time series with 30-day rolling mean
plot_timeseries(goa_ts, variable = "rain",
                title = "Goa Daily Rainfall 2020")

# Compute rainfall indices for Goa
goa_idx <- compute_rainfall_indices(rain2020,
                                    level    = "state",
                                    name     = "Goa",
                                    file_dir = file_dir)
print(goa_idx)

Functions

Function	Description
`get_data()`	Download and read IMD binary data
`open_data()`	Read cached IMD data from disk
`get_point()`	Extract daily time series at a point
`get_point_all()`	Extract all variables at a point
`get_bbox()`	Extract data within a bounding box
`extract_by_boundary()`	Mask data to a state or district
`list_states()`	List all 36 states and UTs
`list_districts()`	List districts, optionally by state
`get_boundary()`	Get sf boundary for a state or district
`plot_imd()`	Publication-quality daily map
`plot_timeseries()`	Daily time series with rolling mean
`compute_rainfall_indices()`	11 rainfall climate indices
`compute_temp_indices()`	13 temperature climate indices
`trend_analysis()`	Mann-Kendall test and Sen’s slope

Climate indices

Rainfall (11): dr, d64, d115, rx1day, rx5day, rtwd, sdii, total, cwd, cdd, pci

Temperature (13): mean_tmax, mean_tmin, mean_dtr, txx, txn, tnx, tnn, su35, su40, tr10, tr25, wsdi, csdi

Bundled boundaries

imdR includes Survey of India (SOI) approved administrative boundaries for all 36 Indian states and union territories and 808 districts, ready to use with no additional downloads.

# List all states
list_states()

# List districts in any state
list_districts("Kerala")

# Get sf boundary object
goa <- get_boundary("state", "Goa")

Data source

IMD gridded data: India Meteorological Department, Pune. https://imdpune.gov.in (accessed periodically; server may be temporarily unavailable)

Boundaries: Survey of India (SOI)

Citation

citation("imdR")

Authors

Subhradip Bhattacharjee (maintainer)
Amitava Panja
Ankita Chakraborty
Basavareddy

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.