Working with netCDF for Essential Biodiversity Variables

The concept of Essential Biodiversity Variables (EBV, < https://geobon.org/ebvs/what-are-ebvs/>) comes with a data structure based on the Network Common Data Form (netCDF). The 'ebvcube' 'R' package provides functionality to easily create, access and visualise this data. The EBV netCDFs can be downloaded from the EBV Data Portal: Christian Langer/ iDiv (2020) < https://portal.geobon.org/>.

A Toolbox for CM SAF NetCDF Data

The Satellite Application Facility on Climate Monitoring (CM SAF) is a ground segment of the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) and one of EUMETSATs Satellite Application Facilities. The CM SAF contributes to the sustainable monitoring of the climate system by providing essential climate variables related to the energy and water cycle of the atmosphere (< https://www.cmsaf.eu>). It is a joint cooperation of eight National Meteorological and Hydrological Services. The 'cmsaf' R-package includes a 'shiny' based interface for an easy application of the 'cmsafops' and 'cmsafvis' packages - the CM SAF R Toolbox. The Toolbox offers an easy way to prepare, manipulate, analyse and visualize CM SAF NetCDF formatted data. Other CF conform NetCDF data with time, longitude and latitude dimension should be applicable, but there is no guarantee for an error-free application. CM SAF climate data records are provided for free via (< https://wui.cmsaf.eu/safira>). Detailed information and test data are provided on the CM SAF webpage (< http://www.cmsaf.eu/R_toolbox>).

Reading Data from NetCDF Files for 'REddyProc'

Extension to 'REddyProc' that allows reading data from netCDF files.

Extract Metadata from 'NetCDF' Files as Data Frames

Tools for handling 'NetCDF' metadata in data frames. The metadata is provided as relations in tabular form, to avoid having to scan printed header output or to navigate nested lists of raw metadata.

Generating Rainfall Rasters from IMD NetCDF Data

The developed function is a comprehensive tool for the analysis of India Meteorological Department (IMD) NetCDF rainfall data. Specifically designed to process high-resolution daily gridded rainfall datasets. It provides four key functions to process IMD NetCDF rainfall data and create rasters for various temporal scales, including annual, seasonal, monthly, and weekly rainfall. For method details see, Malik, A. (2019).. It supports different aggregation methods, such as sum, min, max, mean, and standard deviation. These functions are designed for spatio-temporal analysis of rainfall patterns, trend analysis,geostatistical modeling of rainfall variability, identifying rainfall anomalies and extreme events and can be an input for hydrological and agricultural models.

Easy Access to NetCDF Files with CF Metadata Conventions

Network Common Data Form ('netCDF') files are widely used for scientific data. Library-level access in R is provided through packages 'RNetCDF' and 'ncdf4'. Package 'ncdfCF' is built on top of 'RNetCDF' and makes the data and its attributes available as a set of R6 classes that are informed by the Climate and Forecasting Metadata Conventions. Access to the data uses standard R subsetting operators and common function forms.

Makes it Easier to Work with Daily 'netCDF' from EURO-CORDEX RCMs

Daily 'netCDF' data from e.g. regional climate models (RCMs) are not trivial to work with. This package, which relies on 'data.table', makes it easier to deal with large data from RCMs, such as from EURO-CORDEX (< https://www.euro-cordex.net/>, < https://cordex.org/data-access/>). It has functions to extract single grid cells from rotated pole grids as well as the whole array in long format. Can handle non-standard calendars (360, noleap) and interpolate them to a standard one. Potentially works with many CF-conform 'netCDF' files.

General Purpose Client for 'ERDDAP™' Servers

General purpose R client for 'ERDDAP™' servers. Includes functions to search for 'datasets', get summary information on 'datasets', and fetch 'datasets', in either 'csv' or 'netCDF' format. 'ERDDAP™' information: < https://upwell.pfeg.noaa.gov/erddap/information.html>.

Interface to the 'Daymet' Web Services

Programmatic interface to the 'Daymet' web services (< http://daymet.ornl.gov>). Allows for easy downloads of 'Daymet' climate data directly to your R workspace or your computer. Routines for both single pixel data downloads and gridded (netCDF) data are provided.

Earth Observation Data Cubes from Satellite Image Collections

Processing collections of Earth observation images as on-demand multispectral, multitemporal raster data cubes. Users define cubes by spatiotemporal extent, resolution, and spatial reference system and let 'gdalcubes' automatically apply cropping, reprojection, and resampling using the 'Geospatial Data Abstraction Library' ('GDAL'). Implemented functions on data cubes include reduction over space and time, applying arithmetic expressions on pixel band values, moving window aggregates over time, filtering by space, time, bands, and predicates on pixel values, exporting data cubes as 'netCDF' or 'GeoTIFF' files, plotting, and extraction from spatial and or spatiotemporal features. All computational parts are implemented in C++, linking to the 'GDAL', 'netCDF', 'CURL', and 'SQLite' libraries. See Appel and Pebesma (2019) for further details.