Climate Tools (Series Homogenization and Derived Products)

Functions for the quality control, homogenization and missing data filling of climatological series and to obtain climatological summaries and grids from the results. Also functions to display wind-roses, meteograms, Walter&Lieth diagrams, and more.

Heterogeneous Graphical Model for Non-Negative Data

Graphical model is an informative and powerful tool to explore the conditional dependence relationships among variables. The traditional Gaussian graphical model and its extensions either have a Gaussian assumption on the data distribution or assume the data are homogeneous. However, there are data with complex distributions violating these two assumptions. For example, the air pollutant concentration records are non-negative and, hence, non-Gaussian. Moreover, due to climate changes, distributions of these concentration records in different months of a year can be far different, which means it is uncertain whether datasets from different months are homogeneous. Methods with a Gaussian or homogeneous assumption may incorrectly model the conditional dependence relationships among variables. Therefore, we propose a heterogeneous graphical model for non-negative data (HGMND) to simultaneously cluster multiple datasets and estimate the conditional dependence matrix of variables from a non-Gaussian and non-negative exponential family in each cluster.

Model-Based Clustering for Functional Data with Covariates

Routines for model-based functional cluster analysis for functional data with optional covariates. The idea is to cluster functional subjects (often called functional objects) into homogenous groups by using spline smoothers (for functional data) together with scalar covariates. The spline coefficients and the covariates are modelled as a multivariate Gaussian mixture model, where the number of mixtures corresponds to the number of clusters. The parameters of the model are estimated by maximizing the observed mixture likelihood via an EM algorithm (Arnqvist and Sjöstedt de Luna, 2019) . The clustering method is used to analyze annual lake sediment from lake Kassjön (Northern Sweden) which cover more than 6400 years and can be seen as historical records of weather and climate.

Interface to Download Meteorological (and Hydrological) Datasets

Automatize downloading of meteorological and hydrological data from publicly available repositories: OGIMET (< http://ogimet.com/index.phtml.en>), University of Wyoming - atmospheric vertical profiling data (< http://weather.uwyo.edu/upperair/>), Polish Institute of Meterology and Water Management - National Research Institute (< https://danepubliczne.imgw.pl>), and National Oceanic & Atmospheric Administration (NOAA). This package also allows for searching geographical coordinates for each observation and calculate distances to the nearest stations.

PCIC Implementation of Climdex Routines

PCIC's implementation of Climdex routines for computation of extreme climate indices. Further details on the extreme climate indices can be found at < http://etccdi.pacificclimate.org/list_27_indices.shtml> and in the package manual.

Statistical Transformations for Post-Processing Climate Model Output

Empirical adjustment of the distribution of variables originating from (regional) climate model simulations using quantile mapping.

Set of Tools to Compute Various Climate Indices

Set of tools to compute metrics and indices for climate analysis. The package provides functions to compute extreme indices, evaluate the agreement between models and combine theses models into an ensemble. Multi-model time series of climate indices can be computed either after averaging the 2-D fields from different models provided they share a common grid or by combining time series computed on the model native grid. Indices can be assigned weights and/or combined to construct new indices.

Climate Variability Indices for Ecological Modelling

Supports analysis of trends in climate change, ecological and crop modelling.

Download Geographic Data

Functions for downloading of geographic data for use in spatial analysis and mapping. The package facilitates access to climate, crops, elevation, land use, soil, species occurrence, accessibility, administrative boundaries and other data.

Forecast Verification Routines for Ensemble Forecasts of Weather and Climate

A collection of forecast verification routines developed for the SPECS FP7 project. The emphasis is on comparative verification of ensemble forecasts of weather and climate.