nonCciKeyword

Climate and climate change

73 record(s)

 

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From 1 - 10 / 73
  • This dataset provides UK maps of baseline prior uncertainty (UQ) in fluxes of Greenhouse Gases (GHGs) carbon dioxide, CO2 (2014-15) and methane, CH4 (2015). Spatial maps of these GHG emissions are produced annually in the National Atmospheric Emissions Inventory (NAEI) but it is important to quantify uncertainty in these maps. These uncertainty estimates come from sectoral uncertainty data provided by the NAEI. Here, we propagate the uncertainty in the maps for each of the sectors contributing to the emissions using a Monte Carlo method, in order to quantify the uncertainty in the total emissions spatially. The Monte Carlo method employed here uses a novel approach (Nearest Neighbour Gaussian Process) to make calculations computationally affordable. These estimate the influence on the overall uncertainty of unknown errors in the model structure. Further details of the methodology used here can be found in the supporting documentation included with this data. In the near term, this methodology will be used and developed further in the NERC-funded project, DARE-UK (NE/S003614/1), to update UQ in maps of CO2 and CH4 for the UK. For that work and in general, it is useful to have a baseline prior uncertainty quantification against which future UK maps of uncertainty in CO2 and CH4 fluxes can be compared. Full details about this dataset can be found at https://doi.org/10.5285/739c65a5-12c0-439b-bbcd-1252a4086e87

  • Regular temperature, rainfall and other weather data, as collected between February 1999 and September 2002 from an on-site Automatic Weather Station, located on experimental plots at Sourhope, Scotland. Data were collected as part of the NERC Soil Biodiversity Thematic Programme, which was established in 1999 and was centred upon the intensive study of a large field experiment located at the Macaulay Land Use Research Institute (now the James Hutton Institute) farm at Sourhope in the Scottish Borders (Grid reference: NT8545019630). During this time, the site was monitored to assess changes in above-ground biomass production (productivity), species composition and relative abundance (diversity). Full details about this dataset can be found at https://doi.org/10.5285/e6e835ae-99e6-445e-b0dc-0d0db44e310a

  • This data set includes longitudinal occurrence of bird species at 36 forest plots – half of which burned during the 2015-16 El Niño drought – distributed across a gradient of prior human disturbance in the Brazilian Amazon. Data was collected in 2010 and 2016 (around 6 years before, and one year after the 2015-16 El Niño, respectively) as part of the projects ‘Assessing ENSO-induced Fire Impacts in tropical Rainforest Ecosystems’ (AFIRE) and ‘Biodiversity and Ecosystem Functioning in degraded and recovering Amazonian and Atlantic Forests’ (ECOFOR), within the NERC Human-Modified Tropical Forest (HTMF) programme. Full details about this dataset can be found at https://doi.org/10.5285/4b05caee-a3c8-46a7-b675-e5a94554bd9f

  • [This application is embargoed until March 31, 2022]. This dataset contains a water resource systems model for the Sutlej-Beas system in western Himalayas. It includes all the files required to run the model for the historical period 1989-2008 and climate change scenarios for the middle (2032-2050) and end of the century (2082-2100) considering the uncertainty associated to different Representative Concentration Pathways and Global Climate Models. The WEAP model was built within the “Sustaining Himalayan Water Resources in a Changing Climate” (SusHi-Wat) project (NE/N015541/1), funded by the UK Natural Environment Research Council and the Indian Ministry of Earth Sciences through the Newton-Bhabha Fund. Full details about this application can be found at https://doi.org/10.5285/715db0b2-1d63-4842-ab80-f0f33b39e5e0

  • The dataset contains annual soil greenhouse gas emissions following sheep urine (real and artificial) applications to a semi-improved upland grassland in North Wales, UK, across two seasons (spring and autumn) within the year 2016-2017. Soil greenhouse gas data were collected using a combination of automated chambers and manually sampled chambers, both analysed via gas chromatography. Supporting data include meteorological data, soil chemistry and above ground biomass data collected on a time-series throughout the study, following urine application. The data were used to calculate sheep urine patch nitrous oxide emission factors from an upland environment, to improve estimates of greenhouse gas emissions from extensively grazed agroecosystems. Full details about this dataset can be found at https://doi.org/10.5285/0434c74c-4a8e-45b8-a187-13e422c0ed0f

  • [THIS DATASET HAS BEEN WITHDRAWN]. This dataset includes rainfall data from a ground level rain gauge as well as from basic storage rain gauges within the experimental plots in the Climoor field site in the Clocaenog Forest. Data includes volume of rainfall at both site and plot level, and rainfall chemistry (site level) from 1999-2012. Determinands include: Sodium (Na), Potassium (K), Calcium (Ca), Magnesium (Mg), Aluminium (Al), PO4-P, Chlorine (Cl), Phosphorus (P), Nitogen (N), Ammonium Nitrogen (NH4-N), Nitrate Nitrogen (NO3-N), Sulphate (SO4), dissolved organic Carbon (DOC) and pH for 1999-2002; and NH4-N, NO3-N, SO4, DOC and pH for 2002-2012. Full details about this dataset can be found at https://doi.org/10.5285/7b0da62f-14fc-4636-abb0-4dd9a668a6eb

  • [THIS DATASET HAS BEEN WITHDRAWN]. This dataset includes all measurements of roots from the Climoor fieldsite in the Clocaenog Forest. The data spans three periods: 2003-2004, 2008 and 2011. In 2003 and 2004, 5cm x 15cm plastic root cores were measured, and roots manually picked out the soil. In 2008, root biomass was determined by sieving and washing. In 2011, root biomass, density and length was also determined using sieving and washing. However, the methods used in each of the periods differs so significantly the data should not be directly compared, only differences between experimental plots should be considered. Full details about this dataset can be found at https://doi.org/10.5285/36eeb185-cdf7-44cc-ab69-4bacde9ca50b

  • [This dataset is embargoed until January 31, 2022]. This dataset contains time series observations of surface-atmosphere exchanges of net ecosystem carbon dioxide exchange (NEE), sensible heat (H) and latent heat (LE), and momentum (τ) measured at two managed lowland peatland environments in the East Anglian Fens, England, UK. One site is managed for the production of horticultural salad crops, the other is an area of managed grassland. Turbulent flux densities were monitored using the micrometeorological eddy covariance (EC) technique between 10th November 2016 and 25th September 2018 at the cropland site, and between 27th April 2017 and 31st March 2019 at the grassland. The dataset includes ancillary weather and soil physics observations, as well as variables describing atmospheric turbulence and the quality of the turbulent flux observations. Full details about this dataset can be found at https://doi.org/10.5285/2fe84b80-117a-4b19-a1f5-71bbd1dba9c9

  • Projections of global changes in water scarcity with the current extent of croplands were combined to identify the potential country level vulnerabilities of cropland land to water scarcity in 2050. The data relate to an analysis of the impact changes in water availability will have on cropland availability in 2050. Full details about this dataset can be found at https://doi.org/10.5285/1011037f-4f41-41db-ac7a-0d8e9b8bc933

  • This dataset contains time series observations of surface-atmosphere exchanges of net ecosystem carbon dioxide exchange (NEE), sensible heat (H) and latent heat (LE), and momentum (τ) measured at an area of organically managed grassland located on the Berkshire Downs, UK. Turbulent flux densities were monitored using the micrometeorological eddy covariance (EC) technique between 1st January 2017 and 31st July 2019. The dataset includes ancillary weather and soil physics observations, as well as variables describing atmospheric turbulence and the quality of the turbulent flux observations. This work was supported by the Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability. Full details about this dataset can be found at https://doi.org/10.5285/5a93161f-0124-4650-a2c9-7e8aaea7e6bb