Creation year

2008

210 record(s)
 
Type of resources
Topics
Keywords
Contact for the resource
Provided by
Years
Formats
Representation types
Update frequencies
Scale
Resolution
From 1 - 10 / 210
  • This dataset comprises characteristics of three-spined stickleback fish including length, weight, sex, condition factor (K-factor), cortisol and glucose concentration, RNA:DNA ratio and ethoxyresorufin-O-deethylase activity normalised to liver homogenate protein concentration. These data were collected by the Centre for Ecology & Hydrology from three-spined sticklebacks (Gasterosteus aculeatus L.) captured in the River Ray (south west England) at sites downstream of an urban waste water treatment works (Rodborne WWTW) prior to (2005-2007), and following (2008), remediation of the WWTW effluent with granular activated carbon (GAC) tertiary treatment. During the same period fish were also sampled from neighbouring reference rivers (R. Ock, Childrey Brook). Full details about this dataset can be found at https://doi.org/10.5285/3322cccd-95fe-4cc9-baf8-48cddd03433d

  • This dataset consists of soil physico-chemical properties (pH, loss on ignition, bulk density, moisture content, carbon stock and concentration, total nitrogen, Olsen phosphorus) from soils sampled from up to 591 1km squares across Great Britain in 2007. The Countryside Survey is a unique study or 'audit' of the natural resources of the UK's countryside. The sample sites are chosen from a stratified random sample, based on a 15 by 15 km grid of GB. Surveys have been carried out in 1978, 1984, 1990, 1998 and 2007 by the Centre for Ecology & Hydrology, with repeated visits to the majority of squares. The countryside is sampled and surveyed using rigorous scientific methods, allowing us to compare new results with those from previous surveys. In this way we can detect the gradual and subtle changes that occur in the UK's countryside over time. In addition to soil data, habitat areas, vegetation species data, linear habitat data, and freshwater habitat data are also gathered by Countryside Survey. Please note: the use of Olsen P data, particularly in relation to acidic soils, is controversial. Please ensure these data are suitable for your requirements and exercise caution in their use. Full details about this dataset can be found at https://doi.org/10.5285/79669141-cde5-49f0-b24d-f3c6a1a52db8

  • "The Circulation, overflow, and deep convection studies in the Nordic Seas using tracers and models" project was a Natural Environment Research Council (NERC) RAPID Climate Change Research Programme project (Round 1 - NER/T/S/2002/00446 - Duration 1 Aug 2003 - 31 Oct 2006 ) led by Prof Andrew Watson of the University of East Anglia, also with co-investigators at the University of East Anglia. Dataset contains sources of water in the Greenland-Scotland overflows: recent tracer release and transient tracer observations, as well as the initiation of convection and its relation to submesoscale hydrodynamics. This dataset collection contains MIT General Circulation Model (MITgcm) ocean model basin and channel experiment outputs. The project investigated two aspects of the Nordic Seas circulation of importance to the North Atlantic meridional overturning circulation (MOC): (1) Sources of water in the Greenland-Scotland overflows: recent tracer release and transient tracer observations were used to constrain inverse models of the sources of Denmark Straits and Faroe-Bank channel overflow waters. (2) The initiation of convection and its relation to submesoscale hydrodynamics: very high-resolution non-hydrostatic models for the Central Greenland Sea were used to model recent observations, which show convection to be intimately related to local sub-mesoscale structure.: The objective was to develop improved descriptions of convection for use in OGCMs, to more accurately describe how the sinking branch of the MOC will be affected by changes in forcing. Rapid Climate Change (RAPID) was a £20 million, six-year (2001-2007) programme for the Natural Environment Research Council. The programme aimed to improve the ability to quantify the probability and magnitude of future rapid change in climate, with a main (but not exclusive) focus on the role of the Atlantic Ocean's Thermohaline Circulation.

  • "The Assimilation in ocean and coupled models to determine the thermohaline circulation" project was a Natural Environment Research Council (NERC) RAPID Climate Change Research Programme project (Round 2 - NE/C509058/1 - Duration 1 Sep 2005 - 30 Sep 2009) led by Prof Keith Haines of the University of Reading, with co-investigators at the National Oceanography Centre. This dataset collection contains Atlantic Ocean Thermohaline Circulation (ATOC) model measurements. To make the best use of the historical research ship records as well as new observations from autonomous ocean profiling floats and special observing programs such as Rapid climate change, it was proposed to assimilate all of the available data from the past 40 years into a high quality ocean circulation model that can represent complete fields of ocean properties. In this way derived quantities such as the north-south mass and heat transports which are vital to understanding the oceans role in controlling climate, could be determined. The project also put into context the various timeseries of observations that have been compiled from local regions which suggest that important changes in ocean circulation and transports have been ongoing in the past decades. These timeseries have been put into a basin scale and global scale context of ongoing change. The program determined the relationship between hydrographic signals in different parts of the ocean basins (particularly the N Atlantic). The program provided a method for assimilating data from the thermohaline monitoring arrays into an ocean model that could then be used as part of a coupled climate model for multi-annual climate prediction. Rapid Climate Change (RAPID) was a £20 million, six-year (2001-2007) programme for the Natural Environment Research Council. The programme aimed to improve the ability to quantify the probability and magnitude of future rapid change in climate, with a main (but not exclusive) focus on the role of the Atlantic Ocean's Thermohaline Circulation.

  • Rapid Climate Change (RAPID) was a £20 million, six-year (2001-2007) programme for the Natural Environment Research Council. The programme aimed to improve the ability to quantify the probability and magnitude of future rapid change in climate, with a main (but not exclusive) focus on the role of the Atlantic Ocean's Thermohaline Circulation. This dataset collection contains comparison of high-resolution isotope records from terrestrial archives in NW Europe with model simulations of isotopes in precipitation. The aims of the proposal were to compare high-resolution isotope records from terrestrial archives in NW Europe with model simulations of isotopes in precipitation in order to investigate the role of different forcing factors in rapid climate change during the late glacial and Holocene and to undertake model validation. The proposal constitutes a UK contribution to the PAGES ISOMAP initiative. A water isotope model was developed for the UK Hadley centre model HadCM3. Comparisons have been made between simulations of the isotopic composition of precipitation during periods of rapid climatic change and reconstructions from well-dated and well-calibrated palaeo-archives (lake sediments, peat and speleothem) generated in this study and obtained from the literature, in order to investigate the causes and nature of abrupt climatic events.

  • The main tools that are used for making projections of climate change in the coming century resulting from greenhouse-gas and other emissions are detailed coupled three-dimensional models of the atmosphere and ocean. However, such models give widely different results for some important aspects of climate change, thus limiting our ability to make practically useful projections. One such aspect is changes that may happen in the Atlantic Ocean thermohaline circulation, often referred to as the Gulf Stream. This circulation transports a great deal of heat northwards. If it weakened, future warming in Europe in particular could be reduced or possibly reversed. The spread of model results basically reflects limitations in current understanding of how the large-scale climate system operates. The aim of this project was to identify which are the most important aspects of that uncertainty by making comparisons of the responses simulated by a range of climate models. The results were intended to help improve the models by focusing attention on the aspects which require further theoretical or observational study. This dataset collection contains meteorology and ocean model outputs. Rapid Climate Change (RAPID) was a £20 million, six-year (2001-2007) programme for the Natural Environment Research Council. The programme aimed to improve the ability to quantify the probability and magnitude of future rapid change in climate, with a main (but not exclusive) focus on the role of the Atlantic Ocean's Thermohaline Circulation.

  • MarQUEST was led by Prof Andrew Watson (UEA), with 15 co-investigators at UEA/BAS, the Universities of Southampton, Essex, and Reading, and from the Plymouth Marine Laboratory and Proudman Oceanographic Laboratory. This dataset collection contains ocean optical, chemical and plankton model measurements from SeaWiFS/SeaStar Level 3 products. MarQUEST developed new methods of validating ocean biogeochemistry models, making use of remote sensing ocean colour data, in situ data sets and ongoing observations from the major European programmes CarboOcean and EUR-OCEANS. In the past, ocean biogeochemical models represented biological processes in very simple or rigid ways (e.g., single nutrient limitation, a single generic primary producer), limiting understanding of the role of ecosystems in the climate system. Increasing the complexity of models has presented new challenges for their validation; it is also not clear what the ‘optimal’ complexity of a model should be for any given real-world problem. QUEST scientists cooperated in comparing various models, and examining more fundamental (physiological) approaches to understanding the planktonic ecoystem. MarQUEST also developed a module to simulate coastal ecosystems usable in global ocean biogeochemical simulations. Finally, the project team generated an accurate physical simulation of the North Atlantic guided by data assimilation, into which ecosystem simulations can be embedded. This allows the variation in air-sea fluxes of gases (CO2, oxygen and dimethyl sulphide) from ocean to atmosphere to be quantified for the contemporary period.

  • Observational data extracted from the Met Office's MetDB system. Data include surface and upper air observations and some satellite data. These data are from a number of different message types covering data from land and ship surface data measurements through to upper air observations from wind profilers, radiosonde ascents and aircraft measurements and also satellite measurements. Data arrive at the Met Office as per standard messages transmitted from source (e.g. SYNOP, METARS, TEMP message types) and are then decoded within the MetDB system. CEDA receives a text output from the MetDB system of these deciphered messages which are then processed into the BADC-CSV format where possible. Messages are split up by observation date at this stage. METARS and CLIMAT data are not decoded by the Met Office and are stored as per the original message. Details about the contents of each message type are given in the links in the 'online resources' section of this record. "Raw" data for all message types are available through the /raw folder within the archive. Each raw file contains messages received within a given period of time at the Met Office and are not sorted by observation date.

  • This dataset consists of metal concentrations (aluminium, arsenic, cadmium, chromium, copper, lead, manganese, mercury, molybdenum, nickel, selenium, titanium and zinc) measured from soils sampled across Great Britain in 2007. The Countryside Survey is a unique study or 'audit' of the natural resources of the UK's countryside. The sample sites are chosen from a stratified random sample, based on a 15 by 15 km grid of GB. Surveys have been carried out in 1978, 1984, 1990, 1998 and 2007 by the Centre for Ecology & Hydrology, with repeated visits to the majority of squares. The countryside is sampled and surveyed using rigorous scientific methods, allowing us to compare new results with those from previous surveys. In this way we can detect the gradual and subtle changes that occur in the UK's countryside over time. In addition to soil data, habitat areas, vegetation species data, linear habitat data, and freshwater habitat data are also gathered by Countryside Survey Full details about this dataset can be found at https://doi.org/10.5285/826b0829-7ab5-4e22-822f-ee3a137896a9

  • This collection contains data from "The Quantitative applications of high-resolution late Holocene proxy data sets: estimating climate sensitivity and thermohaline circulation influences" project, which was a Natural Environment Research Council (NERC) RAPID Climate Change Research Programme project (Round 1 - NER/T/S/2002/00440 - Duration 1 Jul 2003 - 30 Jun 2008) led by Prof Keith Briffa of the University of East Anglia, with co-investigators at the University of East Anglia. This dataset collection contains self-calibrating Palmer Drought Severity Index data. This project analysed the output from state-of-the-art coupled climate models in conjunction with very long instrumental climate data and an extensive archive of annual- and selected decadal-resolution palaeoclimate data to study climate changes during the past millennium. Actual and model-derived synthetic networks of palaeoclimate data have been used to estimate the extent to which (i) variations in Atlantic meridional overturning circulation strength; (ii) variations in the North Atlantic Oscillation; and (iii) the sensitivity of climate to external forcing changes can be reconstructed from different networks of palaeoclimate data, making assumptions about coverage, seasonality of response and reliability of expressed climate signal.