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- Published by:
- Centre for Environmental Data Analysis
- Last updated:
- 19 June 2018
How feasible is it to predict Arctic climate at seasonal-to-interannual timescales? As part of the APPOSITE project a multi-model ensemble prediction experiment was conducted in order to answer...
- Published by:
- Marine Environmental Data & Information Network
- Last updated:
- 10 July 2024
Spatial predictions of substrate composition for the UK shelf and North Sea.
Compositional fractions of mud, sand and gravel were modelled for an area of
the UK and North Sea using a statistical...
- Published by:
- Marine Environmental Data & Information Network
- Last updated:
- 21 September 2024
Spatial predictions of substrate composition for the UK shelf and North Sea.
Compositional fractions of mud, sand and gravel were modelled for an area of
the UK and North Sea using a statistical...
- Published by:
- Cambridgeshire Insight
- Last updated:
- 12 April 2020
This dataset contains both the national prediction score for the prevalence of Loneliness across all LSOA's in England and Wales and also has this broken down to just Cambridgeshire and...
- Published by:
- Environmental Information Data Centre
- Last updated:
- 29 June 2024
Prediction of Caesium-137 (Cs-137) deposition from atmospheric nuclear weapons tests. The methodology uses a ratio of Cs-137 deposition and precipitation measured at Milford Haven by the Atomic...
- Published by:
- City of York Council
- Last updated:
- 08 September 2024
Total population aged 65 and over predicted to have dementia
- Published by:
- Marine Environmental Data & Information Network
- Last updated:
- 10 September 2024
Spatial predictions of the fractions of mud, sand and gravel as continuous
response variables for the north-west European continental shelf. Mud, sand
and gravel fractions range from 0-1 (i.e....
- Published by:
- Marine Environmental Data & Information Network
- Last updated:
- 10 July 2024
Spatial predictions of the fractions of mud, sand and gravel as continuous
response variables for the north-west European continental shelf. Mud, sand
and gravel fractions range from 0-1 (i.e....
- Published by:
- Centre for Environmental Data Analysis
- Last updated:
- 19 June 2018
The Antarctic Mesoscale Prediction System (AMPS) is an experimental, real-time numerical weather prediction capability that provides support for the United States Antarctic Program, Antarctic...
- Published by:
- Centre for Environmental Data Analysis
- Last updated:
- 17 July 2017
The Antarctic Mesoscale Prediction System (AMPS) is an experimental, real-time numerical weather prediction capability that provides support for the United States Antarctic Program, Antarctic...
- Published by:
- Scottish Government SpatialData.gov.scot
- Last updated:
- 19 June 2024
These layers are the outputs of research which developed a national river temperature model for Scotland capable of predicting both daily maximum river temperature and sensitivity to climate...
- Published by:
- Joint Nature Conservation Committee
- Last updated:
- 01 July 2019
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...
- Published by:
- Centre for Environmental Data Analysis
- Last updated:
- 19 June 2018
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...
- Published by:
- Centre for Environmental Data Analysis
- Last updated:
- 17 July 2017
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...
- Published by:
- Marine Environmental Data & Information Network
- Last updated:
- 10 September 2024
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....
- Published by:
- Marine Environmental Data & Information Network
- Last updated:
- 10 July 2024
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....
- Published by:
- Environmental Information Data Centre
- Last updated:
- 29 June 2024
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;...
- Published by:
- Environmental Information Data Centre
- Last updated:
- 29 June 2024
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....
- Published by:
- Marine Environmental Data & Information Network
- Last updated:
- 10 September 2024
This dataset contains predicted seahorse habitat distributions for two species
(*Hippocampus hippocampus *and *H. guttulatus*) and the genus combined
(Hippocampus hippocampus MAXENT.asc,...
- Published by:
- Environmental Information Data Centre
- Last updated:
- 29 June 2024
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...