Varmer is an R library for merging satellite-based or model-based gridded images with ground-based observations, using a Variational Merging Approach (Ulloa et al. 2018).

Bugs / comments / questions / collaboration of any kind are very welcomed.


Installing the latest stable version from CRAN:


A simple first application:

Loading required packages:

{r Loading_other_pks, eval = TRUE, message=FALSE} library(zoo) library(sf) library(raster) library(tictoc) library(cluster) library(parallel) library(ggplot2) library(VARMER)

Loading times series and metadata of ground observations:

{r Loading_GroundObservarions, eval = TRUE} data(ecuador.tmax.zoo) data(ecuador.tmax.stations.df) Loading satellite-based/model-based datasets:

{r LoadingSatelliteData, eval = TRUE} data(ecuador.tmax.wrf.out)

Running VARMER

{r, eval = FALSE} varmer.ts(x=ecuador.tmax.zoo, x.metadata=ecuador.tmax.stations.df, v=ecuador.tmax.wrf.out, lat='LAT', lon='LON', drty.out="~/Documentos/dataset_ecuador")

Reporting bugs, requesting new features

If you find an error in some function, or want to report a typo in the documentation, or to request a new feature (and wish it be implemented :) you can do write to


To cite VARMER in publications use:

Ulloa, J., Samaniego, E., Campozano, L., & Ballari, D. (2018). A variational merging approach to the spatial description of environmental variables. Journal of Geophysical Research: Atmospheres, 123.