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.

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.

Seasonal to Decadal Verification

An advanced version of package 's2dverification'. Intended for seasonal to decadal (s2d) climate forecast verification, but also applicable to other types of forecasts or general climate analysis. This package is specifically designed for comparing experimental and observational datasets. It provides functionality for data retrieval, post-processing, skill score computation against observations, and visualization. Compared to 's2dverification', 's2dv' is more compatible with the package 'startR', able to use multiple cores for computation and handle multi-dimensional arrays with a higher flexibility. The Climate Data Operators (CDO) version used in development is 1.9.8. Implements methods described in Wilks (2011) , DelSole and Tippett (2016) , Kharin et al. (2012) , Doblas-Reyes et al. (2003) .

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) .

Interior Point Conic Optimization Solver

A versatile interior point solver that solves linear programs (LPs), quadratic programs (QPs), second-order cone programs (SOCPs), semidefinite programs (SDPs), and problems with exponential and power cone constraints (< https://clarabel.org/stable/>). For quadratic objectives, unlike interior point solvers based on the standard homogeneous self-dual embedding (HSDE) model, Clarabel handles quadratic objective without requiring any epigraphical reformulation of its objective function. It can therefore be significantly faster than other HSDE-based solvers for problems with quadratic objective functions. Infeasible problems are detected using using a homogeneous embedding technique.

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.