Accessing NOAA Climate Data Online

Fetch data from the National Oceanic and Atmospheric Administration Climate Data Online (NOAA CDO) < https://www.ncdc.noaa.gov/cdo-web/webservices/v2> API including daily, monthly, and yearly climate summaries, radar data, climatological averages, precipitation data, annual summaries, storm events, and agricultural meteorology.

Ordered Homogeneity Pursuit Lasso for Group Variable Selection

Ordered homogeneity pursuit lasso (OHPL) algorithm for group variable selection proposed in Lin et al. (2017) . The OHPL method exploits the homogeneity structure in high-dimensional data and enjoys the grouping effect to select groups of important variables automatically. This feature makes it particularly useful for high-dimensional datasets with strongly correlated variables, such as spectroscopic data.

Climate Indices

Computes 138 standard climate indices at monthly, seasonal and annual resolution. These indices were selected, based on their direct and significant impacts on target sectors, after a thorough review of the literature in the field of extreme weather events and natural hazards. Overall, the selected indices characterize different aspects of the frequency, intensity and duration of extreme events, and are derived from a broad set of climatic variables, including surface air temperature, precipitation, relative humidity, wind speed, cloudiness, solar radiation, and snow cover. The 138 indices have been classified as follow: Temperature based indices (42), Precipitation based indices (22), Bioclimatic indices (21), Wind-based indices (5), Aridity/ continentality indices (10), Snow-based indices (13), Cloud/radiation based indices (6), Drought indices (8), Fire indices (5), Tourism indices (5).

Test the Homogeneity of Kappa Statistics

Tests the homogeneity of intraclass kappa statistics obtained from independent studies or a stratified study with binary results. It is desired to compare the kappa statistics obtained in multi-center studies or in a single stratified study to give a common or summary kappa using all available information. If the homogeneity test of these kappa statistics is not rejected, then it is possible to make inferences over a single kappa statistic that summarizes all the studies. Muammer Albayrak, Kemal Turhan, Yasemin Yavuz, Zeliha Aydin Kasap (2019) Jun-mo Nam (2003) Jun-mo Nam (2005) Mousumi Banerjee, Michelle Capozzoli, Laura McSweeney,Debajyoti Sinha (1999) Allan Donner, Michael Eliasziw, Neil Klar (1996) .

Analyze biotic homogenization of landscapes

Tools for assessing exotic species' contributions to landscape homogeneity using average pairwise Jaccard similarity and an analytical approximation derived in Harris et al. (2011, "Occupancy is nine-tenths of the law," The American Naturalist). Also includes a randomization method for assessing sources of model error.

PaleoPhyloGeographic Modeling of Climate Niches and Species Distributions

Reconstruction of paleoclimate niches using phylogenetic comparative methods and projection reconstructed niches onto paleoclimate maps. The user can specify various models of trait evolution or estimate the best fit model, include fossils, use one or multiple phylogenies for inference, and make animations of shifting suitable habitat through time. This model was first used in Lawing and Polly (2011), and further implemented in Lawing et al (2016) and Rivera et al (2020). Lawing and Polly (2011) "Pleistocene climate, phylogeny and climate envelope models: An integrative approach to better understand species' response to climate change" Lawing et al (2016) "Including fossils in phylogenetic climate reconstructions: A deep time perspective on the climatic niche evolution and diversification of spiny lizards (Sceloporus)" Rivera et al (2020) "Reconstructing historical shifts in suitable habitat of Sceloporus lineages using phylogenetic niche modelling.".

Integrating Phylogenetics and Climatic Niche Modeling

Implements some methods in phyloclimatic modeling: estimation of ancestral climatic niches, age-range-correlation, niche equivalency test and background-similarity test.

Climate Crop Zoning Based in Air Temperature for Brazil

Climate crop zoning based in minimum and maximum air temperature. The data used in the package are from 'TerraClimate' dataset (< https://www.climatologylab.org/terraclimate.html>), but, it have been calibrated with automatic weather stations of National Meteorological Institute of Brazil. The climate crop zoning of this package can be run for all the Brazilian territory.

Non-Homogeneous Markov Switching Autoregressive Models

Calibration, simulation, validation of (non-)homogeneous Markov switching autoregressive models with Gaussian or von Mises innovations. Penalization methods are implemented for Markov Switching Vector Autoregressive Models of order 1 only. Most functions of the package handle missing values.

Hydrology and Climate Forecasting

Focuses on data processing and visualization in hydrology and climate forecasting. Main function includes data extraction, data downscaling, data resampling, gap filler of precipitation, bias correction of forecasting data, flexible time series plot, and spatial map generation. It is a good pre- processing and post-processing tool for hydrological and hydraulic modellers.