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climate change

2515 record(s)
 
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From 1 - 10 / 2515
  • The dataset describes the data needed for and results produced by the flood risk assessment framework under different development strategies of Luanhe river basin under a changing climate. The Luanhe river basin is located in the northeast of the North China Plain (115°30′ E-119°45′ E, 39°10′ N-42°40′ N) of China, is an essential socio-economic zone on its own in North-Eastern China, and also directly contributes to and influences the socio-economic development of the Beijing-Tianjin-Hebei region. The dataset here used for investigating the flood risk includes (1) uplifts of future climate scenarios to 2030 (2) the validation results of a historical event that happened in 2012; (3) the flood inundation prediction under different development strategies and climate scenarios to 2030; (4) and the spatial resident density map in Luanhe river basin to 2030. Wherein, the uplifts of the future climate change is generated based on the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset and will be applied to the future design rainfall to represent the future climate scenarios; a 2012 event is select to validate the flood model, and the remote sensing data is adopted as real-world observation data; considering the uplifts and future land use data as input, the validated flood model is applied to produce flood inundation prediction under different development strategies and climate scenarios to 2030; and the inundation results are used to overlay the Gridded Population of the World, Version 4 (GPWv4) and then calculate the flood risk map of the local resident. These data are mainly open data or produced by authors. With all these data, the flood risk of the Luanhe river basin in the near future (2030) can be assessed. Full details about this dataset can be found at https://doi.org/10.5285/82055942-386a-4a8b-b2a1-0c3eea12b168

  • The QUEST-GSI WPd1 "Climate scenarios". The aim was to construct climate scenarios representing the effects of uncertainty and different rates of climate forcing. This dataset contains model data which construct climate scenarios. The project requires climate scenarios which (a) characterise the uncertainty in the climate change associated with a given forcing, including changes in climate variability and extreme events, and (b) allow the construction of generalised relationships between climate forcing and impact.

  • QUEST GSI was led by Nigel Arnell (University of Reading) with co-investigators from the Universities of Aberdeen, Leeds, UEA, Edinburgh, Southampton, UCL, London School of Hygiene and Tropical Medicine, CEH and CEFAS. This dataset collection contains model data simulations under various climate, run-off and aquatic scenarios. A central aim of this project was to assess the global-scale impacts of climate change under a range of scenarios, across a number of sectors. A methodology was developed to construct scenarios from a range of climate models, representing changes under different emissions scenarios and fixed amounts of change in global mean temperature. Impacts were estimated across a range of sectors, including water resources, fluvial and coastal flooding, crop productivity and food security, ecosystem productivity and human health, at regional and global scales. The project has provided quantitative information on these impacts and their distribution across the world. The general conclusions are that impacts may be significant at relatively low levels of climate change, that estimates of impact in some sectors are very uncertain due largely to uncertainty in projected changes in rainfall (particularly in south Asia), that there are no obvious thresholds for step changes in impact that are consistent across region and sector, and that socio-economic conditions may amplify or reduce impacts, depending on context. A second project aim was to develop the methodology in such a way that it could be readily applied to estimate impacts under other climate scenarios representing for example specific policy objectives. With additional funding from other sources, the project methodology has been applied successfully to estimate the impacts avoided by a set of feasible emissions policies.

  • Quaternary QUEST was led by Dr Tim Lenton at UEA, with a team of 10 co-investigators at the Universities of Cambridge, Oxford, Reading, Leeds, Bristol, Southampton and at UEA. This dataset contains FAMOUS (FAst Met Office/UK Universities Simulator) glacial cycle model data from 150,000 years ago to present. The project team aimed to compile a synthesis of palaeodata from sediments and ice cores, improve the synchronization of these records with each other, and use this greater understanding of the Earth’s ancient atmosphere to improve Earth system models simulating climate over very long timescales. A combined long-term data synthesis and modelling approach has helped to constrain some key mechanisms responsible for glacial-interglacial CO2 change, and Quaternary QUEST have narrowed the field of ocean processes that could have caused glacial CO2 drawdown.

  • World Climate Research Programme (WCRP) Coupled Model Intercomparison Project Phase 6 (CMIP6): Collection of simulations from the Centro Euro-Mediterraneo per I Cambiamenti Climatici (CMCC) CMCC-CM2-VHR4 model.

  • QUEST Fish was led by Dr Manuel Barange (PML) with 18 co-investigators from POL, PML, CEFAS, University of Plymouth, University of Portsmouth, CSIC (Spain), UEA, WorldFish Centre, IPSL, ICES (Denmark), Met Office, IRD (Paris) and University of North Carolina, as part of QUEST (Quantifying and Understanding the Earth System) This dataset collection contains global fish biomass estimates from the Global Coastal-Ocean Modelling System. QUEST-Fish has delivered a near-global assessment of consequences of climate change for fisheries, demonstrating excellent and innovative bridging of marine biogeochemistry models and socio-economics. QUEST-Fish specifically focused on the added impacts that climate change is likely to cause on global fish production, and on the subsequent additional risks and vulnerabilities to human societies. The team have demonstrated the broad capability of an integrated regional coastal/shelf seas model system. The physical-ecological POLCOMS-ERSEM model that underpinned the research was developed for Europe’s regional seas. Its application to 20 Large Marine Ecosystems (coastal bioregions) worldwide, covering two-thirds of the world’s fish catch, has been critically evaluated and found adequate for most regions (the physical and biogeochemical differences of the upwelling region off Peru presents challenges, with the climate impact likely to be over-expressed in the fisheries projection output).

  • World Climate Research Programme (WCRP) Coupled Model Intercomparison Project Phase 6 (CMIP6): Collection of simulations from the Centro Euro-Mediterraneo per I Cambiamenti Climatici (CMCC) CMCC-CM2-HR4 model.

  • The the NIMS-KMA team team consisted of the following agencies: National Institute of Meteorological Sciences (NIMS) and Korea Meteorological Administration (KMA).World Climate Research Programme (WCRP) Coupled Model Intercomparison Project Phase 6 (CMIP6): Collection of simulations from the the NIMS-KMA team UKESM1-0-LL model.

  • World Climate Research Programme (WCRP) Coupled Model Intercomparison Project Phase 6 (CMIP6): Collection of simulations from the Met Office Hadley Centre (MOHC) HadGEM3-GC31-LM model.

  • Quaternary QUEST was led by Dr Tim Lenton at UEA, with a team of 10 co-investigators at the Universities of Cambridge, Oxford, Reading, Leeds, Bristol, Southampton and at UEA. This dataset collection contains glacial and isotope model data. Over the last million years, the Earth has experienced a sequence of temperature oscillations between glacial and interglacial states, linked to variations in the Earth’s orbit around the sun. These climate oscillations were accompanied by changes in atmospheric CO2, but the fundamental reasons for this relationship are still unresolved. This project team aimed to compile a synthesis of palaeodata from sediments and ice cores, improve the synchronization of these records with each other, and use this greater understanding of the Earth’s ancient atmosphere to improve Earth system models simulating climate over very long timescales. A combined long-term data synthesis and modelling approach has helped to constrain some key mechanisms responsible for glacial-interglacial CO2 change, and Quaternary QUEST narrowed the field of ocean processes that could have caused glacial CO2 drawdown.