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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)
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).
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)
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>.
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)
Uncertainties of Climate Projections using Smoothing Splines
These functions use smoothing-splines for the assessment of single-member ensembles of climate projections.
- Cheng, C.-I. and P. L. Speckman (2012)
Evaluation Tools for Assessing Climate Adaptation of Fruit Tree Species
Climate is a critical component limiting growing range of plant species, which
also determines cultivar adaptation to a region. The evaluation of climate influence on
fruit production is critical for decision-making in the design stage of orchards and
vineyards and in the evaluation of the potential consequences of future climate. Bio-
climatic indices and plant phenology are commonly used to describe the suitability of
climate for growing quality fruit and to provide temporal and spatial information about
regarding ongoing and future changes. 'fruclimadapt' streamlines the assessment of
climate adaptation and the identification of potential risks for grapevines and fruit
trees. Procedures in the package allow to i) downscale daily meteorological variables
to hourly values (Forster et al (2016)