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>.

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) ), ii) estimate chilling and forcing heat accumulation (Miranda et al (2019) < https://ec.europa.eu/eip/agriculture/sites/default/files/fg30_mp5_phenology_critical_temperatures.pdf>), iii) estimate plant phenology (Schwartz (2012) ), iv) calculate bioclimatic indices to evaluate fruit tree and grapevine adaptation (e.g. Badr et al (2017) ), v) estimate the incidence of weather-related disorders in fruits (e.g. Snyder and de Melo-Abreu (2005, ISBN:92-5-105328-6) and vi) estimate plant water requirements (Allen et al (1998, ISBN:92-5-104219-5)).

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) .

Dengue Cases and Climate Variables in Colombo Sri Lanka

Weekly notified dengue cases and climate variables in Colombo district Sri Lanka from 2008/ week-52 to 2014/ week-21.

Access Canadian Historical Climate Data

Provides easy access to historical climate data in Canada from R. Search for weather stations and download raw hourly, daily or monthly weather data across Canada from 1840 to present. Implements public API access as detailed at < https://climate.weather.gc.ca>.

Interface to the 'Daymet' Web Services

Programmatic interface to the 'Daymet' web services (< http://daymet.ornl.gov>). Allows for easy downloads of 'Daymet' climate data directly to your R workspace or your computer. Routines for both single pixel data downloads and gridded (netCDF) data are provided.

Interface to 'ECMWF' and 'CDS' Data Web Services

Programmatic interface to the European Centre for Medium-Range Weather Forecasts dataset web services (ECMWF; < https://www.ecmwf.int/>) and Copernicus's Data Stores. Allows for easy downloads of weather forecasts and climate reanalysis data in R. Data stores covered include the Climate Data Store (CDS; < https://cds.climate.copernicus.eu>), Atmosphere Data Store (ADS; < https://ads.atmosphere.copernicus.eu>) and Early Warning Data Store (CEMS; < https://ewds.climate.copernicus.eu>).

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) and Cannon (2018) are implemented -- (i) MBC Pearson correlation (MBCp), (ii) MBC rank correlation (MBCr), and (iii) MBC N-dimensional PDF transform (MBCn) -- as is the Rank Resampling for Distributions and Dependences (R2D2) method. An additional multivariate rescaling method based on the linear Monge-Kantorovich map for Gaussian optimal transport of dependence structure is also included.

Access 'NOAA' Climate and Weather Data

Provides clean, tidy access to climate and weather data from the 'National Oceanic and Atmospheric Administration' ('NOAA') via the 'National Centers for Environmental Information' ('NCEI') Data Service API < https://www.ncei.noaa.gov/access/services/data/v1>. Covers daily weather observations, monthly and annual summaries, and 30-year climate normals from over 100,000 stations across 180 countries. No API key is required. Dedicated functions handle the most common datasets, while a generic fetcher provides access to all 'NCEI' datasets. Station discovery functions help users find stations by location or name. Data is downloaded on first use and cached locally for subsequent calls. This package is not endorsed or certified by 'NOAA'.

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. The package makes use of some of the methods described in: N. Manubens et al. (2018) .