'GAMS' Modularization Support Package

A collection of tools to create, use and maintain modularized model code written in the modeling language 'GAMS' (< https://www.gams.com/>). Out-of-the-box 'GAMS' does not come with support for modularized model code. This package provides the tools necessary to convert a standard 'GAMS' model to a modularized one by introducing a modularized code structure together with a naming convention which emulates local environments. In addition, this package provides tools to monitor the compliance of the model code with modular coding guidelines.

May All Data be Reproducible and Transparent (MADRaT) *

Provides a framework which should improve reproducibility and transparency in data processing. It provides functionality such as automatic meta data creation and management, rudimentary quality management, data caching, work-flow management and data aggregation. * The title is a wish not a promise. By no means we expect this package to deliver everything what is needed to achieve full reproducibility and transparency, but we believe that it supports efforts in this direction.

Visualize the Climate Scenario Alignment of a Financial Portfolio

Create plots to visualize the alignment of a corporate lending financial portfolio to climate change scenarios based on climate indicators (production and emission intensities) across key climate relevant sectors of the 'PACTA' methodology (Paris Agreement Capital Transition Assessment; < https://www.transitionmonitor.com/>). Financial institutions use 'PACTA' to study how their capital allocation decisions align with climate change mitigation goals.

Simulating Homogenous & Non-Homogenous Poisson Processes

Contains functions and classes for simulating, plotting and analysing homogenous and non-homogenous Poisson processes.

Hierarchical Climate Regionalization

A tool for Hierarchical Climate Regionalization applicable to any correlation-based clustering. It adds several features and a new clustering method (called, 'regional' linkage) to hierarchical clustering in R ('hclust' function in 'stats' library): data regridding, coarsening spatial resolution, geographic masking, contiguity-constrained clustering, data filtering by mean and/or variance thresholds, data preprocessing (detrending, standardization, and PCA), faster correlation function with preliminary big data support, different clustering methods, hybrid hierarchical clustering, multivariate clustering (MVC), cluster validation, visualization of regionalization results, and exporting region map and mean timeseries into NetCDF-4 file. The technical details are described in Badr et al. (2015) .

An API Wrapper for 'DAWA' - 'The Danish Address Web API'

Functions for interacting with all sections of the official 'Danish Address Web API' (also known as 'DAWA') < https://api.dataforsyningen.dk>. The development of this package is completely independent from the government agency, Klimadatastyrelsen, who maintains the API.

Flood Frequency Analysis Framework

Tools to support systematic and reproducible workflows for both stationary and nonstationary flood frequency analysis, with applications extending to other hydroclimate extremes, such as precipitation frequency analysis. This package implements the FFA framework proposed by Vidrio- Sahagún et al. (2024) , originally developed in 'MATLAB', now adapted for the 'R' environment. This work was funded by the Flood Hazard Identification and Mapping Program of Environment and Climate Change Canada, as well as the Canada Research Chair (Tier 1) awarded to Dr. Pietroniro.

Climate AEMET Tools

Tools to download the climatic data of the Spanish Meteorological Agency (AEMET) directly from R using their API and create scientific graphs (climate charts, trend analysis of climate time series, temperature and precipitation anomalies maps, warming stripes graphics, climatograms, etc.).

Standard Normal Homogeneity Test

Implementation of robust and non-robust Standard Normal Homogeneity Test (SNHT) for changepoint detection. This test statistic is equal sided, as proposed in "Homogenization of Radiosonde Temperature Time Series Using Innovation Statistics" by Haimberger, L., 2007. However, the statistic contains an estimate of sigma^2 in the denominator instead of sigma, which seems to be a more appropriate value (based on the paper "Homogenization of Swedish temperature data. Part I: Homogeneity test for linear trends." by Alexandersson, H., and A. Moberg, 1997).

Tests for Variance Homogeneity

Performs 20 omnibus tests for testing the composite hypothesis of variance homogeneity.