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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.
Search Download and Handle Data from Copernicus Climate Data Service
Subset and download data from EU Copernicus Climate Data Service: < https://cds.climate.copernicus.eu/>. Import information about the Earth's past, present and future climate from Copernicus into R without the need of external software.
Climate Classification According to Several Indices
Classification of climate according to Koeppen - Geiger, of aridity indices, of continentality indices, of water balance after Thornthwaite, of viticultural bioclimatic indices. Drawing climographs: Thornthwaite, Peguy, Bagnouls-Gaussen.
Zhang + Yue-Pilon Trends Package
An efficient implementation of the slope method described by Sen (1968)
Non-Homogeneous Markov and Hidden Markov Multistate Models
Fits non-homogeneous Markov multistate models and misclassification-type hidden Markov models in continuous time to intermittently observed data. Implements the methods in Titman (2011)
Dataset for Climate Analysis with Data from the Nordic Region
The Nordklim dataset 1.0 is a unique and useful achievement for climate analysis. It includes observations of twelve different climate elements from more than 100 stations in the Nordic region, in time span over 100 years. The project contractors were NORDKLIM/NORDMET on behalf of the National meteorological services in Denmark (DMI), Finland (FMI), Iceland (VI), Norway (DNMI) and Sweden (SMHI).
Tests of Homogeneity of Variances
Most common exact, asymptotic and resample based tests are provided for testing the
homogeneity of variances of k normal distributions under normality.
These tests are Barlett, Bhandary & Dai, Brown & Forsythe, Chang et al., Gokpinar & Gokpinar, Levene, Liu and Xu, Gokpinar.
Also, a data generation function from multiple normal distribution is provided using any multiple normal parameters.
Bartlett, M. S. (1937)
Multivariate Bias Correction of Climate Model Outputs
Calibrate and apply multivariate bias correction algorithms
for climate model simulations of multiple climate variables. Three methods
described by Cannon (2016)
Statistical Downscaling of Climate Predictions
Statistical downscaling and bias correction of climate predictions.
It includes implementations of commonly used methods such as Analogs,
Linear Regression, Logistic Regression, and Bias Correction techniques,
as well as interpolation functions for regridding and point-based applications.
It facilitates the production of high-resolution and local-scale climate
information from coarse-scale predictions, which is essential for impact analyses.
The package can be applied in a wide range of sectors and studies,
including agriculture, water management, energy, heatwaves, and other
climate-sensitive applications. The package was developed within the framework of
the European Union Horizon Europe projects Impetus4Change (101081555) and ASPECT (101081460),
the Wellcome Trust supported HARMONIZE project (224694/Z/21/Z), and the Spanish national project
BOREAS (PID2022-140673OA-I00). Implements the methods described in
'Ramon et al. (2021)
Agro-Climatic Data by County
The functions are designed to calculate the most widely-used county-level variables in agricultural production or agricultural-climatic and weather analyses. To operate some functions in this package needs download of the bulk PRISM raster. See the examples, testing versions and more details from: < https://github.com/ysd2004/acdcR>.