Machine Learning

Species distribution modelling of Bradypus data for presence of a species

The aim of this practical is to demonstate the utility of R in data manipulation, plotting and statistical analysis of time-series data to detect trends of different type. We will use Daily Mean flow (DMF) data from the Boyne catchment measured at Slane Castle gauging station in Co. Meath from 1941-2010.Data obtained from the Office of Public Works (OPW).

Code for reconstructing Island of Ireland (DJF) rainfall data.

Climate Change Time Series Analysis. This type of data analysis is crucial for flood defences, geographical processes and economic policy’s relating to the climate change.

This example will utilise a file from EUMETSAT CM SAF. We will work with a NetCDF file of monthly sunshine duration over Europe for the single time point of August 2018 from the Interim Climate Data Record. This data file should be provided along with this script and is called SDUms201808010000401UD1000101UD.nc. Put this data file in the same folder as this script is in.

This example will utilise a file from EUMETSAT CM SAF. We will work with a NetCDF file of monthly Direct Normalized Irradiance over Germany for the 30 year period 1983 to 2012 from the Climate Data Record SARAH 2.1. This tutorial will show you how to generate a time series plot for both an area and a point location as well as show how to generate basic statistics from your file.

The 2019-20 class of the MSc Climate Change at Maynooth University were set a group assignment to re-evalaute extreme heat temperature records using Ireland as a proxy. The following script will produce Time series plot, Station Location Map and Frequency Distribution Plots. This script was produced by Ciaran Kelly & Natascha Seifert. All data used in this paper is attached as .csv files in Station_Investigation.zip folder

This script is the data processing and data visualization of the two reanalysis products netcdf files.