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  • 1
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    In:  XXVIII General Assembly of the International Union of Geodesy and Geophysics (IUGG)
    Publication Date: 2023-08-02
    Description: An unresolved problem of present generation coupled climate models is realistic distribution of rainfall over Indian monsoon region. This outstanding deficiency is also related to the persistent dry bias over Indian land mass. Therefore, quantitative prediction of the intensity of rainfall (light/moderate/heavy) events has remained a challenge in any climate models. Guided by the observation, it is hypothesized that insufficient growth of cloud droplets and processes responsible for the cloud to rain water conversion are key components to distinguish between shallow to convective clouds. The Eulerian-Lagrangian particle-by-particle based small-scale model can only provide required information and provide a pathway to revisit the parameterizations in climate models for monsoon clouds. This can be done using in situ airborne measurement data of Cloud Aerosol Interaction and Precipitation Enhancement Experiment (CAIPEEX) during monsoon over Indian sub-continent. The new diffusional growth rates (Cm) is varied in the range of ∼0.25x10-3 – 1.5x10-3 (cm/s), which is useful tuning parameter for convective and shallow clouds. The small-scale study also guides to choose better conversion rate from cloud to rain water based on relative dispersion. The robustness of the hypothesis and small-scale study is verified by doing two climate model simulations (i.e., control and modified). The modified model of coupled forecast system (CFSv2) demonstrates significant improvement in rainfall distribution, which is further linked with of the probability distribution of thermodynamical, cloud and dynamical variables. Therefore, continuous effort on basic research of microphysical processes using small-scale model is important for accurate representation of them in large-scale models.
    Language: English
    Type: info:eu-repo/semantics/conferenceObject
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  • 2
    Publication Date: 2023-07-18
    Description: This paper describes, documents, and validates the TM5-FAst Scenario Screening Tool (TM5-FASST), a global reduced-form air quality source–receptor model that has been designed to compute ambient pollutant concentrations as well as a broad range of pollutant-related impacts on human health, agricultural crop production, and short-lived pollutant climate metrics, taking as input annual pollutant emission data aggregated at the national or regional level. The TM5-FASST tool, providing a trade-off between accuracy and applicability, is based on linearized emission-concentration sensitivities derived with the full chemistry-transport model TM5. The tool has been extensively applied in various recent critical studies. Although informal and fragmented validation has already been performed in various publications, this paper provides a comprehensive documentation of all components of the model and a validation against the full TM5 model. We find that the simplifications introduced in order to generate immediate results from emission scenarios do not compromise the validity of the output and as such TM5-FASST is proven to be a useful tool in science-policy analysis. Furthermore, it constitutes a suitable architecture for implementing the ensemble of source–receptor relations obtained in the frame of the HTAP modelling exercises, thus creating a link between the scientific community and policy-oriented users.
    Language: English
    Type: info:eu-repo/semantics/article
    Format: application/pdf
    Format: application/pdf
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