Found 316 packages in 0.09 seconds
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>.
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)
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.
Estimating Climate Representativeness
Offers tools to estimate the climate representativeness of defined areas and quantifies and analyzes its transformation under future climate change scenarios. Approaches described in Mingarro and Lobo (2018)
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.
Visualizing Hypothesis Tests in Multivariate Linear Models
Provides HE plot and other functions for visualizing hypothesis tests in multivariate linear models. HE plots represent sums-of-squares-and-products matrices for linear hypotheses and for error using ellipses (in two dimensions) and ellipsoids (in three dimensions). It also provides other tools for analysis and graphical display of the models such as robust methods and homogeneity of variance covariance matrices. The related 'candisc' package provides visualizations in a reduced-rank canonical discriminant space when there are more than a few response variables.
Climate Window Analysis
Contains functions to detect and visualise periods of climate
sensitivity (climate windows) for a given biological response.
Please see van de Pol et al. (2016)
Koeppen-Geiger Climatic Zones
Aids in identifying the Koeppen-Geiger (KG) climatic zone for
a given location. The Koeppen-Geiger climate zones were first published in 1884, as a system
to classify regions of the earth by their relative heat and humidity through the year, for
the benefit of human health, plant and agriculture and other human activity [1]. This climate
zone classification system, applicable to all of the earths surface, has continued to be
developed by scientists up to the present day. Recently one of use (FZ) has published updated,
higher accuracy KG climate zone definitions [2]. In this package we use these updated
high-resolution maps as the data source [3]. We provide functions that return the KG climate zone
for a given longitude and lattitude, or for a given United States zip code. In addition
the CZUncertainty() function will check climate zones nearby to check if the given location
is near a climate zone boundary. In addition an interactive shiny app is provided to define
the KG climate zone for a given longitude and lattitude, or United States zip code.
Digital data, as well as animated maps, showing the shift of the climate zones are provided
on the following website < http://koeppen-geiger.vu-wien.ac.at>.
This work was supported by the DOE-EERE SunShot award DE-EE-0007140.
[1] W. Koeppen, (2011)
General Purpose Client for 'ERDDAP™' Servers
General purpose R client for 'ERDDAP™' servers. Includes functions to search for 'datasets', get summary information on 'datasets', and fetch 'datasets', in either 'csv' or 'netCDF' format. 'ERDDAP™' information: < https://upwell.pfeg.noaa.gov/erddap/information.html>.
Climate and Ecological Niche Factor Analysis
Tools for climate- and ecological-niche factor analysis of spatial data, including methods for visualization of spatial variability of species sensitivity, exposure, and vulnerability to climate change. Processing of large files and parallel methods are supported. Climate-niche factor analysis is described in Rinnan and Lawler (2019)