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Flood Risk for Extreme Events (FREE): Historical Rainfall Data and Maps from the Quantifying Flood Risk of Extreme Events using Density Forecasts Based on a New Digital Archive and Weather Ensemble Predictions Project

The Quantifying Flood Risk of Extreme Events using Density Forecasts Based on a New Digital Archive and Weather Ensemble Predictions Project is a Natural Environment Research Council (NERC) Flood...

Flood Risk for Extreme Events (FREE): Historical Rainfall Data and Maps from the Quantifying Flood Risk of Extreme Events using Density Forecasts Based on a New Digital Archive and Weather Ensemble Predictions Project

The Quantifying Flood Risk of Extreme Events using Density Forecasts Based on a New Digital Archive and Weather Ensemble Predictions Project is a Natural Environment Research Council (NERC) Flood...

Pore scale modeling of drainage displacement patterns in association with geological sequestration of CO2

The data include the following: 1. Simulation input files (parameters used in free energy Lattice Boltzmann simulations). 2. Results from these simulations and the corresponding analysis, as...

Prediction of outcrops or subcrops of rock in UK shelf seabed (public)

Prediction of the presence of rock at outcrop or subcrop at the seabed across the UK shelf area. This shapefile was produced through a semi-automated approach, using a Random Forest model combined...

PalaeoQUMP (Quantifying and Understanding the Earth System - Using Palaeodata to Quantify Uncertainties in Model Prediction): Global Charcoal Database

PalaeoQUMP was headed by Prof Sandy Harrison of the University of Bristol, with co-investigators at the University of Southampton and Durham University, as part of QUEST (Quantifying and...

PalaeoQUMP (Quantifying and Understanding the Earth System - Using Palaeodata to Quantify Uncertainties in Model Prediction): Global Charcoal Database

PalaeoQUMP was headed by Prof Sandy Harrison of the University of Bristol, with co-investigators at the University of Southampton and Durham University, as part of QUEST (Quantifying and...

Predicted sedimentation rates data for the Baltic Sea derived from samples from 1992 - 2019

Spatial prediction of the sediment accumulation rate, provided as a .geotif file (as an average linear rate in cm yr-1 since 1986) for the Baltic Sea created using a machine learning approach....

Predicted sedimentation rates data for the Baltic Sea derived from samples from 1992 - 2019

Spatial prediction of the sediment accumulation rate, provided as a .geotif file (as an average linear rate in cm yr-1 since 1986) for the Baltic Sea created using a machine learning approach....

Data associated with 'A 17-year time-series of fungal environmental DNA from a coastal marine ecosystem reveals long-term seasonal-scale and inter-annual diversity patterns'

Dataset associated with the published article: Chrismas Nathan, Allen Ro, Allen Michael J., Bird Kimberley and Cunliffe Michael 2023. A 17-year time-series of fungal environmental DNA from a...

Data associated with 'A 17-year time-series of fungal environmental DNA from a coastal marine ecosystem reveals long-term seasonal-scale and inter-annual diversity patterns'

Dataset associated with the published article: Chrismas Nathan, Allen Ro, Allen Michael J., Bird Kimberley and Cunliffe Michael 2023. A 17-year time-series of fungal environmental DNA from a...

Predicted soil erosion rates, nutrient fluxes and topsoil lifespans, modelled for Kenya at a 30 metre resolution

This dataset presents predicted soil erosion rates (t ha-1 yr-1) and its impact on topsoils, including lifespans (yr) assuming erosion rates remain constant and there is no replacement of soil;...

Predicted outcomes from land use change scenarios in upland Wales catchments

A spatial approach was developed to interpret qualitatively expressed scenarios, and predict the probability and amount of change for 10 land-cover types across 127 sub-catchments in upland Wales....

GCM-based monthly patterns of local meteorological change, per degree of mean land warming, for driving the IMOGEN impacts model

This dataset consists of monthly spatial patterns of meteorological change for 22 Global Circulation Models (GCMs). The patterns are a set of regression coefficients, each representing the change...

Seahorse species predicted habitat distributions and associated environmental data layers covering the shelf seas surrounding the UK

This dataset contains predicted seahorse habitat distributions for two species (*Hippocampus hippocampus *and *H. guttulatus*) and the genus combined (Hippocampus hippocampus MAXENT.asc,...

CMIP5 GCM-based monthly patterns of local meteorological change, per degree of mean land warming, for driving the IMOGEN impacts model

This dataset consists of monthly spatial patterns of meteorological change for 34 Global Circulation Models (GCMs). The patterns are a set of regression coefficients, each representing the change...

Köppen-Geiger climate classification prediction maps for the UK at 1 km resolution, 1901–2080

The data deposited here underlie an assessment of the exposure of UK habitats to climate change, and a linked assessment of how well current UK plant monitoring schemes cover these exposure...

Log file, GSAS data files and diffraction patterns from synchrotron experiments on NaMnF3 (NERC grant NE/J009520/1)

Log file and GSAS data files for synchrotron study of NaMnF3. Diffraction patterns from synchrotron experiments on NaMnF3. NERC grant: Understanding the D' zone: novel fluoride analogues to MgSiO3...

Random Forest model output prediction raster for the occurrence of Fe-Mn in the World Oceans

The raster provide the output of a machine-learning random forest algorithm modelling the occurrence of ferromanganese (Fe-Mn) crust deposits in the world ocean. This raster constitutes a...

A section 75 analysis of mortality patterns in Northern Ireland

An analysis of mortality within Northern Ireland using the NI Mortality Study. Source agency: Health, Social Service and Public Safety (Northern Ireland) Designation: Official Statistics not...

RAPID Improving our Ability to Predict Rapid Changes in the El Nino Southern Oscillation Climatic Phenomenon: HADCM3 model output

"Improving our ability to predict rapid changes in the El Nino Southern Oscillation climatic phenomenon" project, which was a Natural Environment Research Council (NERC) RAPID Climate Change...