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- W4387398701 abstract "<strong class=journal-contentHeaderColor>Abstract.</strong> A geospatial data processing tool, GEO4PALM, has been developed to generate geospatial static input for the Parallelised Large Eddy Simulation (PALM) model system. PALM is a community-driven large eddy simulation model used for atmospheric and environmental research. Throughout PALM’s 20-year development, research interests have been increasing in its application in realistic conditions, especially for urban areas. For such applications, geospatial static input is essential. Although abundant geospatial data are accessible worldwide, currently, no tools are available in the community to automatically generate PALM’s geospatial static input for most areas of the world. In addition, geospatial data availability and quality are highly variable and inconsistent. Therefore, PALM users face significant challenges, particularly regarding data acquisition, data pre-processing, and conversion of all information and metadata into PALM Input Data Standard (PIDS). This paper presents and describes a free and open-source tool, GEO4PALM, to help users generate the PALM static input with a simple and standardized process. GEO4PALM is compatible with geospatial data obtained from any source provided that the data sets comply with common geo-information formats. Users can either provide existing geospatial data sets or use the embedded data interfaces to download geo-information data from free online sources for any global geographic area of interest. All online data sets incorporated in GEO4PALM are globally available with several data sets having the finest resolution of 1 m. Two application examples are presented to demonstrate successful PALM simulations driven by geospatial input generated by GEO4PALM using different geospatial data sources for Berlin, Germany and Christchurch, New Zealand. GEO4PALM provides an easy and efficient way for PALM users to configure and conduct PALM simulations for applications and investigations such as urban heat island effects, air pollution dispersion, renewable energy resourcing, and weather-related hazard forecasting." @default.
- W4387398701 created "2023-10-07" @default.
- W4387398701 date "2023-10-06" @default.
- W4387398701 modified "2023-10-16" @default.
- W4387398701 title "Comment on gmd-2023-150" @default.
- W4387398701 doi "https://doi.org/10.5194/gmd-2023-150-rc1" @default.
- W4387398701 hasPublicationYear "2023" @default.
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