varunayanR is an R package for downloading and processing ERA5 reanalysis data from Copernicus Climate Data Store and IMD gridded climate data from the Indian Meteorological Department. It provides an easy to use R interface for extracting temperature, precipitation, and other climate variables for any region using bounding boxes, GeoJSON polygons, or point coordinates.

Installation

# Install from GitHub
# install.packages("devtools")
devtools::install_github("saketlab/varunayanR")

Quick Start

ERA5 climate data

library(varunayan)

# Setup CDS credentials (one-time)
# Get your API key from: https://cds.climate.copernicus.eu/how-to-api
setup_cds_credentials(key = "your-cds-api-key")

# Download ERA5 temperature and precipitation for Mumbai
temperature_data <- era5ify_bbox(
  request_id = "mumbai_temp",
  variables = c("2m_temperature", "total_precipitation"),
  start_date = "2023-01-01",
  end_date = "2023-12-31",
  north = 19.2, south = 18.9,
  east = 72.9, west = 72.8,
  frequency = "daily"
)

head(temperature_data)

IMD rainfall data

# Download IMD gridded rainfall data for Maharashtra
rainfall_data <- imd_rainfall_bbox(
  request_id = "maharashtra_rain",
  start_year = 2023,
  end_year = 2024,
  north = 22, south = 16,
  east = 80, west = 73,
  resolution = 0.25,
  frequency = "monthly"
)

GeoJSON regions

# Download data for regions defined by GeoJSON
data <- era5ify_geojson(
  request_id = "indian_states",
  variables = c("2m_temperature", "surface_pressure"),
  start_date = "2024-01-01",
  end_date = "2024-01-31",
  json_file = "path/to/states.geojson",
  frequency = "daily"
)

Use cases

Monsoon analysis

# Download 20 years of rainfall data for monsoon research
rainfall <- imd_rainfall_bbox(
  request_id = "monsoon_study",
  start_year = 2000,
  end_year = 2020,
  north = 28, south = 8,
  east = 92, west = 68,
  resolution = 0.25,
  frequency = "monthly"
)

# Analyze monsoon patterns (June-September)
library(dplyr)
monsoon <- rainfall %>%
  filter(month(date) %in% 6:9) %>%
  group_by(year(date), latitude, longitude) %>%
  summarise(monsoon_total = sum(rainfall))

Atmospheric data at pressure levels

# Download ERA5 data at multiple atmospheric levels
atmos_data <- era5ify_bbox(
  request_id = "atmosphere",
  variables = c("temperature", "geopotential", "u_component_of_wind"),
  start_date = "2024-01-01",
  end_date = "2024-01-05",
  north = 30, south = 20,
  east = 80, west = 70,
  dataset_type = "pressure",
  pressure_levels = c("1000", "850", "500", "200")
)

varunayanR