6/11/2023 0 Comments Winds rss readerYou can listen while browsing, skip back or forward, and even speed up playback to get through episodes more efficiently. The podcast player is quite good, offering most of the features you would expect. It provides recommendations based on the same interests you select for relevant feeds, and you can listen to them without switching to a different application. If you haven’t gotten into podcasts yet, this app is a great place to start. There is no way to change the dimensions of the text panel, and the lack of a dark mode affects reading most of all. There are few ways to innovate when creating an RSS reader, and Winds works well enough, but some improvements are needed. This app can help you find relevant feeds by asking for your main interests when it is launched for the first time. RSS feeds are used by pretty much every news website to provide users with an easy way to keep track of new content and read it in a simple, standardized format. It is an open-source app, also available for Windows, Linux and on the web, that lets you manage all your news sources and podcast series from a single interface. Winds is an attempt to combine your feeds and podcasts into a neat little package. Many of us use both of these technologies to keep track of news and other developments, but we normally have to rely on separate apps for each of them. Finally, as a demonstration of concept, we discuss how comparing feedback files of the different reanalyses can guide users to useful scales of variability.RSS feeds have been around for a very long time, and podcasts have grown in popularity a great deal in the past few years. 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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