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.

Manipulate Time Series of Climate Reconstructions

Methods to easily extract and manipulate climate reconstructions for ecological and anthropological analyses, as described in Leonardi et al. (2023) . The package includes datasets of palaeoclimate reconstructions, present observations, and future projections from multiple climate models.

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) .

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.

Simulating Homogenous & Non-Homogenous Poisson Processes

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

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.

Interface to 'ECMWF' and 'CDS' Data Web Services

Programmatic interface to the European Centre for Medium-Range Weather Forecasts dataset web services (ECMWF; < https://www.ecmwf.int/>) and Copernicus's Data Stores. Allows for easy downloads of weather forecasts and climate reanalysis data in R. Data stores covered include the Climate Data Store (CDS; < https://cds.climate.copernicus.eu>), Atmosphere Data Store (ADS; < https://ads.atmosphere.copernicus.eu>) and Early Warning Data Store (CEMS; < https://ewds.climate.copernicus.eu>).

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.

Tools for AEMET Climate Data

Download meteorological and climate data from the Spanish Meteorological Agency (AEMET) directly in R using the AEMET API. Create scientific visualizations, including climate charts, climate time series trend analyses, temperature and precipitation anomaly maps, warming stripes and climatograms.