<h2>Viewer for GHCN V4, with search and active graph</h2>

I have made an active viewer for the GHCN V4 database of station monthly average temperatures, as used in TempLS and other indices. I was prompted to do so after adapting the GHCN webGL page to use GHCN V4. I think the results are generally good, and I'll write more about that soon. But there are a few stations that stand out as having very odd anomalies. The viewer shows adjusted and unadjusted temperature data for each of the 27380 stations in current GHCN V4. I'll link the page more permanently through the data portal page on the right panel.

The main viewing mechanism is an active graph, from which you can download station data. The pink rectangle below the graph (below) has a search box. You can put in a part of the station name. The GHCN 4 convention is that stations are in all caps, with underscores replacing spaces. The search will return up to 20 names; each line giving the full name (to 18 chars), the GHCNv4 station number, and the approximate year range of the data. To the left of each line is a radio button. Clicking this will download the data for that station and show an active graph.

Below the graph is a table of checkboxes with names of months. There is a column of unadjusted, and one of adjusted. Check the boxes to determine which graphs are shown. There is a legend box below the graph, which shows the selected names and color. You can drag this onto the polot to act as a legend.

The graph is active (like this one). That means that you can drag with mouse the location of the plot. If you swipe horizontally below the x-axis it will shrink or expand the x-range, and similarly behind the y-axis. So you can adjust the plot to see best what you want.

Update If you don't like a color you can change it. Just click the button of that color in the legend to randomly choose from a palette of 64.

The Data button above the checkboxes creates a new window with a printout of the data that is showing. You can save this, or copy and paste.

I should note that I have excluded any data with a quality flag; sometimes this is quite a lot. Anyway, here is the plot: