![]() To see the output, you can run the following command in terminal and visit http://localhost:8000/rss. You can find all available options in docs. This is passed on to the custom_elements field in serializer. ![]() But because the process is expensive, it is not build on development. Gatsby-plugin-mdx exposes an html field for the purpose of building RSS blogs. Note to add the published filter if you use this format to hide drafts. Query field inside this object stands for graphql query that retrieves all the pages in the blog. Because we have a MDX Blog, we need a custom serializer to transform pages into HTML objects that the RSS Feed readers understand. This defines all the options for our RSS Feed. In addition, as an open-source project, Winds keeps getting better thanks to contributions from its growing user base (now over 14,000 users and 5,500 stars). Inside feeds array, we have our feed object. In this case, leveraging Stream and other great services allowed us to build a podcast and RSS reader, Winds, in months rather than years. For example, one for your blog and another for your podcast. This is an array so that you can create multiple feeds. You can import individual feeds or OPML files, define how and when feeds are updated, use filters or notifications, and customize how contents are displayed to you. The program ships with all the bells and whistles youd except it to. This data is important to construct siteUrl and guids. QuiteRSS QuiteRSS is a full blown RSS reader for Windows that is in active development. Finally, as a demonstration of concept, we discuss how comparing feedback files of the different reanalyses can guide users to useful scales of variability.The first query attribute let’s us query for site level attributes like siteMetadata. We also identified stations with homogeneity problems in the reported station values, demonstrating how reanalyses can be applied to support quality control for the observed station data. We discuss some typical examples where differences are found, e.g., where the mean wind distributions differ (probably related to either height or model topography differences) and where the correlations break down (because of unresolved local topography) which applies to a minority of stations. ![]() Still, the inter-annual variability connected to the North Atlantic Oscillation (NAO) found in the reanalysis surface wind anomalies is in accordance with the anomalies recorded by the stations. As expected from the lower spatial resolution and reduced amount of data assimilated into ERA-20C, the correlation of monthly means decreases somewhat relative to the other reanalyses (in our investigated period of 2007 to 2010). Generally, the correlation between the higher resolved COSMO-REA6 wind fields and station observations is highest, for both assimilated and non-assimilated (i.e., independent) observations. High correlations (larger than 0.9) can be found between stations and reanalysis monthly mean wind speeds all over Germany. We show that for the majority of the stations, the Weibull parameters of the daily mean wind speed frequency distribution match remarkably well with the ones derived from the reanalysis fields. We compare with a regional reanalysis (COSMO-REA6) and two global reanalyses, ERA-Interim and ERA-20C. In this period, the station time series in Germany can be expected to be mostly homogeneous. Here we compare the statistical properties of wind speeds observed at 210 traditional meteorological stations over Germany with the reanalyses' near-surface fields, confining the analysis to the recent years (2007 to 2010). Inter-comparing reanalyses via employing independent observations can help to guide users to useful spatio-temporal scales. Reanalysis near-surface wind fields from multiple reanalyses are potentially an important information source for wind energy applications.
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