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R Interface to the TELEMAC Model Suite
An R interface to the TELEMAC suite for modelling of free surface flow. This includes methods for model initialisation, simulation, and visualisation. So far only the TELEMAC-2D module for 2-dimensional hydrodynamic modelling is implemented.
Actuarial Climate Index
Computes the Actuarial Climate Index (ACI) and its components (temperature, precipitation, drought, wind, sea level) from gridded climate data ('NetCDF') and tide gauge records. Implements the methodology described in Garrido, Milhaud & Olympio (2025) < https://hal.science/hal-04491982v2> for a French/European actuarial climate index, building on the American Academy of Actuaries framework, to any country in the world.
Climate Futures Toolbox
Developed as a collaboration between Earth lab and the North Central Climate Adaptation Science Center to help users gain insights from available climate data. Includes tools and instructions for downloading climate data via a 'USGS' API and then organizing those data for visualization and analysis that drive insight. Web interface for 'USGS' API can be found at < http://thredds.northwestknowledge.net:8080/thredds/reacch_climate_CMIP5_aggregated_macav2_catalog.html>.
Community Climate Statistics
Computes community climate statistics for volume and mismatch using species' climate niches either unscaled or scaled relative to a regional species pool. These statistics can be used to describe biogeographic patterns and infer community assembly processes. Includes a vignette outlining usage.
Wegener Center Climate Uncertainty Explorer
Methods to calculate and interpret climate change signals and time series from climate multi-model ensembles. Climate model output in binary 'NetCDF' format is read in and aggregated over a specified region to a data.frame for statistical analysis. Global Circulation Models, as the 'CMIP5' simulations, can be read in the same way as Regional Climate Models, as e.g. the 'CORDEX' or 'ENSEMBLES' simulations. The package has been developed at the 'Wegener Center for Climate and Global Change' at the University of Graz, Austria.
Climate Window Analysis
Contains functions to detect and visualise periods of climate
sensitivity (climate windows) for a given biological response.
Please see van de Pol et al. (2016)
Visualizing Hypothesis Tests in Multivariate Linear Models
Provides HE plot and other functions for visualizing hypothesis tests in multivariate linear models. HE plots represent sums-of-squares-and-products matrices for linear hypotheses and for error using ellipses (in two dimensions) and ellipsoids (in three dimensions). It also provides other tools for analysis and graphical display of the models such as robust methods and homogeneity of variance covariance matrices. The related 'candisc' package provides visualizations in a reduced-rank canonical discriminant space when there are more than a few response variables.
Post-Processing of Climate Data for Health Applications
Obtain, transform and export climate data including reanalyses,
(seasonal) forecasts and hindcasts, and weather stations for their use
in epidemiological analyses. It is organised in three sequential blocks,
input (download and load data), transform (downscaling, verification,
spatiotemporal aggregation and threshold-based indicators) and output
(visualising and exporting data). Downscaling methods include those
described in Duzenli et al. (2026)
Koeppen-Geiger Climatic Zones
Aids in identifying the Koeppen-Geiger (KG) climatic zone for
a given location. The Koeppen-Geiger climate zones were first published in 1884, as a system
to classify regions of the earth by their relative heat and humidity through the year, for
the benefit of human health, plant and agriculture and other human activity [1]. This climate
zone classification system, applicable to all of the earths surface, has continued to be
developed by scientists up to the present day. Recently one of use (FZ) has published updated,
higher accuracy KG climate zone definitions [2]. In this package we use these updated
high-resolution maps as the data source [3]. We provide functions that return the KG climate zone
for a given longitude and lattitude, or for a given United States zip code. In addition
the CZUncertainty() function will check climate zones nearby to check if the given location
is near a climate zone boundary. In addition an interactive shiny app is provided to define
the KG climate zone for a given longitude and lattitude, or United States zip code.
Digital data, as well as animated maps, showing the shift of the climate zones are provided
on the following website < http://koeppen-geiger.vu-wien.ac.at>.
This work was supported by the DOE-EERE SunShot award DE-EE-0007140.
[1] W. Koeppen, (2011)
Maximum Homogeneity Clustering for Univariate Data
Maximum homogeneity clustering algorithm for one-dimensional data
described in W. D. Fisher (1958)