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Climate and climate change

76 record(s)
 
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From 1 - 10 / 76
  • This dataset represents the hydro-meteorological monitoring activities undertaken in Ouagadougou, Burkina Faso, during 2016-2018, as part of the DFID funded AMMA-2050 (African Monsoon Multidisciplinary Analysis) project (amma2050.org). The data comprises time series of rainfall, water level and river flow recorded at locations across Ouagadougou city for the purposes of building an understanding of hydrological function and hydrological model development. In-situ data were collected using tipping bucket raingauges and pressure level sensors, with spot gauging of river flows used to develop rating curves used to derive flow from level measurements in channels. The network was designed and set-up by the UK Centre for Ecology and Hydrology (UKCEH) and maintained by the Burkina Faso Institut International d’Ingenierie de l’Eau et de l’Environment (2iE) and processing was undertaken by UKCEH. Full details about this dataset can be found at https://doi.org/10.5285/30ae0230-e352-4a82-901d-ac1d42449044

  • 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 contains in situ CO2 efflux, root production and fungal hyphae production from plots distributed across a subarctic landscape in Northern Sweden. 6 paired plots were established in mountain birch forest and 5 paired plots were established in tall shrub tundra where one of each pair was 'girdled' and one acted as a non girdled 'control'. Efflux measurements were made during six sampling campaigns over 2017 and 2018 at an approximate frequency of once per week during each campaign, constituting a time series of measurements. Production measurements integrated root or hyphae production over the whole growing season (June-September) and therefore there is one datapoint per plot per year. Full details about this dataset can be found at https://doi.org/10.5285/4418c631-c39c-467c-b3b8-c75142fcae0a

  • 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 DATASET HAS BEEN WITHDRAWN]. 1 km gridded estimates of daily and monthly rainfall for Great-Britain and Northern Ireland (together with approximately 3000 km2 of catchment in the Republic of Ireland) from 1890 to 2015. The rainfall estimates are derived from the Met Office national database of observed precipitation. To derive the estimates, monthly and daily (when complete month available) precipitation totals from the UK rain gauge network are used. The natural neighbour interpolation methodology, including a normalisation step based on average annual rainfall, was used to generate the daily and monthly estimates. The estimated rainfall on a given day refers to the rainfall amount precipitated in 24 hours between 9am on that day until 9am on the following day. The CEH-GEAR dataset has been developed according to the guidance provided in BS 7843-4:2012. Full details about this dataset can be found at https://doi.org/10.5285/33604ea0-c238-4488-813d-0ad9ab7c51ca

  • 1 km gridded estimates of daily and monthly rainfall for Great-Britain and Northern Ireland (together with approximately 3000 km2 of catchment in the Republic of Ireland) from 1890 to 2017. The rainfall estimates are derived from the Met Office national database of observed precipitation. To derive the estimates, monthly and daily (when complete month available) precipitation totals from the UK rain gauge network are used. The natural neighbour interpolation methodology, including a normalisation step based on average annual rainfall, was used to generate the daily and monthly estimates. The estimated rainfall on a given day refers to the rainfall amount precipitated in 24 hours between 9am on that day until 9am on the following day. The CEH-GEAR dataset has been developed according to the guidance provided in BS 7843-4:2012. Full details about this dataset can be found at https://doi.org/10.5285/ee9ab43d-a4fe-4e73-afd5-cd4fc4c82556

  • 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 DATASET HAS BEEN WITHDRAWN]. This dataset includes manual measurements of water table depth at the Climoor fieldsite in the Clocaenog Forest, north-east Wales. Water table depth was collected via water permeable tubes installed through the soil profile down to bedrock. Measurements were taken, usually every two weeks, using a tape measure and head torch to assist in seeing the water level in the tube. Data are available from May 2009 to January 2014. Full details about this dataset can be found at https://doi.org/10.5285/5ba28b53-6b20-4e31-9c0f-ba234ddc55ef

  • [THIS DATASET HAS BEEN WITHDRAWN]. This dataset contains hourly micro-meteorological data from the experimental plots at the Climoor field site in Clocaenog forest, NE Wales. It runs from 11/9/2008 until 31/12/2013, and contains air temperature, soil temperature at two depths (5cm and 20cm) as well as soil moisture. Climoor is a climate change experiment which investigates the possible impact of increased temperatures and repeated summer drought on an Atlantic upland moorland. The experiment uses automatic roof technology to warm experimental plots by 0.5 - 1 degC and reproduces drought conditions in other experimental plots (July to September annually). In 2014, the Climoor experiment was the second longest running climate change experiment in the UK and data from the experiment has been used in several modelling exercises. The site was originally established under a EU consortium project - called CLIMOOR - where replica manipulation experiments were built in six European countries. As well as our site in North-East Wales (United Kingdom), there are identical sites in Denmark, the Netherlands, Sardinia (Italy) and Hungary. There was also a site in Catalonia (Spain). Full details about this dataset can be found at https://doi.org/10.5285/124ae988-41d3-4555-b704-5acc85633a05

  • 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