nonCciKeyword

climate

6 record(s)

 

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From 1 - 6 / 6
  • This dataset includes six sets of model output from JULES/IMOGEN simulations. Each set includes output from JULES (the Joint UK Land Environment Simulator) run with 34 climate change patterns from 2000-2099. The outputs provide carbon stocks and variables related to the surface energy budget to understand the implications of land-based climate mitigation. Full details about this dataset can be found at https://doi.org/10.5285/333eb066-be07-4209-9dfe-2d9d18560de6

  • These data contain 408 instances of annual model output from JULES/IMOGEN simulations, covering the period between 1850-2100. Each simulation (which corresponds to one netcdf file) provides annual average of carbon stocks of the land, atmosphere and ocean store required to calculate the anthropogenic fossil fuel emissions as the residual of the yearly changes. Also included are the global warming variables, fractional land-cover, natural wetland extent and methane (CH4) flux and the soil temperature and moisture content for additional analysis. The spatial coverage is global with spatial resolution of the data is 2.5 degrees latitude, 3.75 degrees longitude. This dataset is the model output that was used in Comyn-Platt et al (2018) [ Comyn-Platt, E. et al. (2018). Carbon budgets for 1.5 and 2C targets lowered by natural wetland and permafrost feedbacks. Nature Geoscience. https://doi.org/10.1038/s41561-018-0174-9] Full details about this dataset can be found at https://doi.org/10.5285/1cebd79c-02e7-475a-a1da-1f26a963d41e

  • Mosquito trap data from Kilombero Valley in Tanzania - a global hotspot for malaria. Since 2007, field entomologists working at Ifakara Health Institue (IHI) and at the University of Glasgow have been trapping and collecting primary malaria vectors for four villages in the Kilombero Valley: Lupiro, Kidugalo, Minepa and Sagamaganga. Trapped mosquitoes were identified to species level (Anopheles gambiae and A funestus), their sex recorded (male or female) and their abdominal status (fed or unfed) noted. When available, the daily mosquito data was consistently linked to micro climate data logger data (weather conditions on site, including averaged, minimum and maximum daytime and night time values for temperature, humidity and vapour pressure deficit). This long record allows exploring the relationship between malaria vector dynamics and related environmental conditions. Full details about this dataset can be found at https://doi.org/10.5285/89406b06-d0aa-4120-84db-a5f91b616053

  • Data comprise soil methane oxidation results from a group of 30 forested islands in northern Sweden sampled in 2006 and 2007. The islands have different fire histories and represent a retrogressive chronosequence spanning 5000 years. Full details about this dataset can be found at https://doi.org/10.5285/66cc8fd4-e722-44c4-9363-5930b8373b2c

  • Eddy covariance (EC) observations of surface-atmosphere exchanges of sensible heat and latent heat, momentum and net ecosystem carbon dioxide exchange were measured at thirty minute resolution at three Land Surface Stations in India. The dataset includes ancillary weather and soil physics observations, as well as variables describing atmospheric turbulence and the quality of the turbulent flux observations. Meteorological observations include: the net radiation and its incoming and outgoing short- and long-wave components, air temperature, barometric pressure, relative humidity, wind speed and direction, and rainfall. Soil physics observations include: Soil heat fluxes, soil temperatures and soil volumetric water content. Observations were collected under the Interaction of Convective Organization and Monsoon Precipitation, Atmosphere, Surface and Sea (INCOMPASS) Project between January 2016 and January 2018. Full details about this dataset can be found at https://doi.org/10.5285/78c64025-1f8d-431c-bdeb-e69a5877d2ed

  • The dataset contains time series observations of meteorological and soil physics variables logged at one minute time resolution at three Land Surface Stations in India. The three INCOMPASS Land Surface Stations were located at: (1) agricultural land in Southern Karnataka (Berambadi); (2) the University of Agricultural Sciences in Dharwad in northern Karnataka; and (3) a semi-natural grassland at the Indian Institute of Technology in Kanpur (IITK), Uttar Pradesh. Observations were collected under the Interaction of Convective Organization and Monsoon Precipitation, Atmosphere, Surface and Sea (INCOMPASS) Project between January 2016 and January 2019. Full details about this dataset can be found at https://doi.org/10.5285/c5e72461-c61f-4800-8bbf-95c85f74c416