Saturday, June 15, 2024

GISS May global temperature down by 0.19°C from April.

The GISS V4 land/ocean temperature anomaly was 1.14°C in May, down from 1.33°C in April. This fall is similar to the 0.168°C reported here for TempLS.

As with TempLS, May was the warmest May in the record - next was 1.01°C in 2020.

I mentioned in the earlier post that the TempLS was made on a reduced number of stations that had reported.    Even now only 3303 non-US stations have reported, whereas last year there would have been over 4000. So it seems to be a permament change.

As usual here, I will compare the GISS and earlier TempLS plots below the jump.

Here is GISS V4


And here is the TempLS V4 FEM-based plot


This post is part of a series that has now run for twelve years. The GISS data completes the month cycle, and is compared with the TempLS result and map. GISS lists its reports here, and I post the monthly averages here.
The TempLS mesh data is reported here, and the recent history of monthly readings is here. Unadjusted GHCN is normally used, but if you click the TempLS button there, it will show data with adjusted, and also with different integration methods. There is an interactive graph using 1981-2010 base period here which you can use to show different periods, or compare with other indices. There is a general guide to TempLS here.

The reporting cycle starts with the TempLS report, usually about the 8th of the month. Then when the GISS result comes out, usually about the 15th, I discuss it and compare with TempLS. The TempLS graph now comes from a high resolution regular grid on the sphere; the residuals are displayed more directly using a triangular grid in a WebGL plot here.

A list of earlier monthly reports of each series in date order is here:

  1. NCEP/NCAR Reanalysis report
  2. TempLS report
  3. GISS report and comparison with TempLS



4 comments:

  1. Hi Nick, I'm in debate with the Gorman couple in WUWT. Apart from their hair raising ignorance about a lot of things, they claim that the average temperature in climatology is calculated with the formula of (min+max)/2. Now this is a useful formula but the average is sum(Xi)/N, obviously, and this latter has much more pleasant properties w/r/t error propagation. In the old days we only had min-max thermometers so in a sense we only had the first data but the first is a good approximation of the second anyway (with caveats, this is why climate science is a science, to handle these things well).
    Anyway, I have to admit that I don't know enough about this, and there is this sentence in https://preview.climate.gov/maps-data/climate-data-primer/how-do-weather-observations-become-climate-data : " For instance, a station's daily average (mean) temperature is calculated by averaging the minimum and maximum temperatures for the day: daily average = (minimum + maximum) / 2"
    I suppose this is sloppy wording.
    Could you explain to us these things? It's almost useless to use the net for this.

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    Replies
    1. Hi, and welcome to Moyhu. Yes, in Gorman world there are endles complaints about all aspects of averaging. I think you have summarized the situation well; until late last century, we relied on min/max thermometers to give the best summary of the weather for the day with manageable effort. Most popular summaries of the weather still do that. You don't see TV stations saying what the hourly average T will be tomorrow (or was yesterday).

      It's an index; hourly average is another, and both are informative. I did some studies here and here comparing min/max with hourly for Boulder, Colorado, mainly focusing on the dependence of min/max on when you actually reset the thermometer. The graph in the second link might be the most helpful. It shows the min/max curves varying with reading times and the hourly average embedded among them.

      One can get too hung up on whether an index is exactly the right one. It's only a temperature inside a box, and we don't really care about what it is. What we want to know is how it changes, because that is probably reflected on a much wider scale outside. And then there really isn't much difference.

      Anyway, as you said, if you want to look at a long history, you have no choice.

      Delete
  2. Oops, I'm nyolci, I comment on WUWT quite rarely.

    ReplyDelete