Project Instance

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{
    "ob_id": 37834,
    "uuid": "f1bfceeff4e045a588d143fdb9097f2b",
    "title": "Impacts of climate change in the troposphere, stratosphere and mesosphere on the thermosphere and ionosphere",
    "abstract": "The data were produced as part of a Natural Environment Research Council (NERC) Independent Research Fellowship (NE/R015651/1) awarded to Ingrid Cnossen, entitled 'Impacts of climate change in the troposphere, stratosphere and mesosphere on the thermosphere and ionosphere'. \r\n\r\nThe project as a whole aims to quantify the importance of man-made climate change in the lower and middle atmosphere in causing long-term changes in the upper atmosphere, both in the past (1950s-2010s) and projected into the future (2050s) according to established emission scenarios. Computer simulations with WACCM-X, a state-of-the-art, global, 3-dimensional climate model, extending from the surface up to ~500 km altitude, are being used to do this. Results from these simulations will be compared to observed long-term changes in the upper atmosphere (e.g., in temperature, density) and to contributions made by other known factors. These include the increase in greenhouse gas concentration within the upper atmosphere itself, which has a cooling effect, and changes in the Earth's magnetic field, which cause more complicated patterns of long-term change. Interactions of changes in the Earth's magnetic field and changes in atmospheric tides due to climate change will also be investigated. This will focus at least initially again on the period of the 1950s to 2050s, but this may be broadened to a larger timespan from 850 to the present-day. \r\n\r\nThe current data set covers the period 1950-2015 and comes from the first long-term transient simulation with WACCM-X. The data set was used by Cnossen (2020) to quantify past climate change in the upper atmosphere, using the same multi-linear regression analysis technique that is often used to extract trends from observational data sets. The data set is also highly suitable for comparisons with observed long-term trends in the upper atmosphere, as the timeframes covered by observational data sets can be matched by selecting the relevant time window from the simulation data and all known drivers of climate change are included.  NE/R015651/1",
    "keywords": "",
    "status": "completed",
    "publicationState": "published",
    "identifier_set": [],
    "observationCollection": [],
    "parentProject": null,
    "subProject": [],
    "responsiblepartyinfo_set": [
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        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/180527/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/180528/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/180529/?format=api"
    ]
}