Download and Process INMET Climate Normals

sus_climate_normals() retrieves 30-year climatological normals from the Brazilian National Institute of Meteorology (INMET) for one of three reference periods (1961-1990, 1981-2010, 1991-2020). It loads the variable catalogue from the bundled normal_meta.parquet dictionary—with transparent disk caching and automatic fallback download—then fetches each selected variable's Excel file from the INMET portal, parses the decade-level monthly structure, and returns a tidy long-format climasus_df.

Usage

sus_climate_normals(
  period = "1991-2020",
  target_var = NULL,
  cache_dir = "~/.climasus4r_cache/normals",
  use_cache = TRUE,
  lang = "pt",
  verbose = TRUE
)

Arguments

period: Character. Reference climatological period. One of "1961-1990", "1981-2010", or "1991-2020" (default).
target_var: Character vector of var_code values to download (e.g. c("t_max", "precipitation")). NULL (default) downloads all variables available for the selected period. Run sus_climate_normals_meta() to inspect the catalogue.
cache_dir: Character. Local directory for disk-cached files. Default: "~/.climasus4r_cache/normals".
use_cache: Logical. If TRUE (default), loads from and saves to cache_dir. Set to FALSE to force a fresh download.
lang: Character. Message language: "pt" (default), "en", "es".
verbose: Logical. Print progress messages. Default TRUE.

Value

A climasus_df object at stage "climate" and type "normals", tidy long format with columns:

codigo: Character. INMET station identifier.
nome_estacao: Character. Station name.
uf: Character. Brazilian state abbreviation.
mes: Character. Month name (Portuguese, lower-case ASCII).
decada: Character. Decade within month ("1", "2", "3").
valor: Numeric. Climatological normal value.
var_code: Character. Variable identifier from normal_meta.
variable_pt: Character. Variable label in Portuguese.
variable_en: Character. Variable label in English.
period: Character. Reference period (e.g. "1991-2020").

Public-health and environmental relevance

Climate normals serve as the climatological baseline against which observed exposures are compared in epidemiological studies:

Heat-health: temperature normals reveal chronically hot municipalities for heat-wave attribution and heat-related mortality studies.
Precipitation extremes: wet-day and dry-spell normals support flood and drought exposure assessments linked to diarrhoeal disease, leptospirosis, and waterborne outbreaks.
Vector-borne diseases: humidity and temperature normals define the climatic envelope of Aedes mosquito habitat, informing dengue, chikungunya and Zika risk mapping.
Relative-risk baselines: DLNM models built with sus_mod_dlnm() require a reference exposure; normals provide the station-level climatological mean for that reference.
Vulnerability indices: combined with sus_mod_vulnerability_index(), normals quantify chronic exposure as an IPCC hazard pillar component.

Examples

if (FALSE) { # \dontrun{
# Full 1991-2020 normals (all variables)
normals <- sus_climate_normals(period = "1991-2020")

# Only temperature variables
temp_normals <- sus_climate_normals(
  period     = "1991-2020",
  target_var = c("t_max", "t_min", "t_mean_comp"),
  lang       = "pt"
)

# Browse available variables first
meta <- sus_climate_normals_meta(period = "1991-2020")
} # }

Usage

Arguments

Value

Public-health and environmental relevance

See also

Examples