Estimating Climate Stability from Climate Model Data

Climate stability measures are not formalized in the literature and tools for generating stability metrics from existing data are nascent. This package provides tools for calculating climate stability from raster data encapsulating climate change as a series of time slices. The methods follow Owens and Guralnick Biodiversity Informatics.

Homogenous Segmentation for Spatial Lines Data

Methods of homogenous segmentation for spatial lines data, such as pavement performance indicators and traffic volumes. Three methods are available for homogenous segmentation, including cumulative difference approach, minimization coefficient of variation, and spatial heterogeneity based method.

Climate Change Metrics

A framework that facilitates spatio-temporal analysis of climate dynamics through exploring and measuring different dimensions of climate change in space and time.

Homogenization of GNSS Series

Homogenize GNSS (Global Navigation Satellite System) time-series. The general model is a segmentation in the mean model including a periodic function and considering monthly variances, see Quarello (2020) .

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.

Climate Modeling with Point Data from Climate Stations

An automated and streamlined workflow for predictive climate mapping using climate station data. Works within an environment the user provides a destined path to - otherwise it's tempdir(). Quick and relatively easy creation of resilient and reproducible climate models, predictions and climate maps, shortening the usually long and complicated work of predictive modelling. For more information, please find the provided URL. Many methods in this package are new, but the main method is based on a workflow from Meyer (2019) and Meyer (2022) , however, it was generalized and adjusted in the context of this package.

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>.

Estimating Climate Representativeness

Offers tools to estimate the climate representativeness of reference polygons and quantifies its transformation under future climate change scenarios. Approaches described in Mingarro and Lobo (2018) and Mingarro and Lobo (2022) .

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.