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Quarterly Journal of the Royal Meteorological Society

From Wikipedia, the free encyclopedia

Quarterly Journal of the Royal Meteorological Society
DisciplineMeteorology
LanguageEnglish
Edited byJohn Methven and Andrew N. Ross
Publication details
Former name(s)
Bibliography of Meteorological Literature
History1871-present
Publisher
Frequency8/year
7.237 (2021)
Standard abbreviations
ISO 4Q. J. R. Meteorol. Soc.
Indexing
CODENQJRMAM
ISSN0035-9009 (print)
1477-870X (web)
LCCNsf80001033
OCLC no.270648634
Links

The Quarterly Journal of the Royal Meteorological Society is a peer-reviewed scientific journal of meteorology published eight times per year. It was established in 1871 as Bibliography of Meteorological Literature, obtaining its current name in 1873. It is published by Wiley-Blackwell on behalf of the Royal Meteorological Society.

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Transcription

How do we measure global warming? Thermometer records, which are maintained and checked by a number of groups, tell us that the planet is warming. We also know it is warming from satellites, tree-rings and ice cores. In this lecture, we will investigate how we know the thermometer record is accurate enough to detect human-caused warming. We can never measure anything exactly. So whenever we measure something, we also try to estimate how *accurate* that measurement is. We know that our estimate is only approximate, so we also estimate how far off it might be. Scientists call this the *uncertainty* in the measurement. What they’re talking about is the range of possible values. When scientists estimate global temperature, they also work out the *accuracy* of those estimates. Accuracy is often represented on a graph by error bars, or by shading. They indicate how close we think our measurement is to to the truth. How do scientists determine the accuracy in their global surface temperature estimates? Le's look at one very simple method. Consider two weather station records - we'll colour them red and blue. The stations are close together, so they should show similar temperatures. If the thermometer measurements are accurate, then the records from the two stations will look quite similar. However, if the thermometers are inaccurate, the station records will look quite different. The data themselves can give us a measure of their accuracy. Do we have enough weather stations to estimate global surface temperature? Again, we can compare neighbouring stations. As the stations get farther apart, they will experience different weather, and the records will start to differ. Again, the data can tell us if we have enough stations. But we don't have just two weather station records. We have thousands. How do we check *all* of them to get a measure of the accuracy of the global mean temperature? There is a very simple extension of our two station test. Here are the actual weather stations listed in the Global Historical Climate Network. Let’s randomly divide the thousands of stations into two groups: red and blue. We'll calculate a global temperature record from the average of just the red stations. Then we'll calculate another global temperature record from just the blue stations. If the two records agree, it tells us that the stations are reliable, and that we have enough of them. As you can see, the red and blue temperature records are not identical, but they are very similar. The difference between the two records is an estimate of the accuracy of the temperature record. The differences are small compared to the warming signal we are trying to observe. This is just one simple way to look at accuracy of the temperature record. This approach and others like it are used across many fields of science. And the data themselves tell us that the record is reliable. That's not the only way we know the temperature record is reliable. There are a lot of different sources of temperature information we can compare. Firstly, here are versions of the thermometer record calculated by different groups around the world. But scientists can also calculate global temperature without using the weather station thermometers. Weather forecasting software can be used to estimate air temperatures using ship data and air *pressure* observations. Satellites also measure air temperature from the radio noise coming from different layers of the atmosphere. Finally, there are various natural thermometers, like tree rings and ice cores. All of these confirm that the planet has warmed over recent decades. The natural thermometers can also give us temperature records over much longer periods. These tell us that the recent warming is very different from natural climate change. Despite all this evidence, there is a myth that the thermometer record is unreliable. One claim is that early thermometer readings are not sufficiently accurate to detect a change of about one degree Celsius over the course of a century. Another claim is that there aren't enough weather stations to produce an accurate estimate of global land temperature. But scientists have included both of these when estimating the accuracy of the global temperature. So what is the fallacy here? If someone says our measurements aren't perfect, so much of the warming could be due to measurement errors, they are jumping to conclusions. When we estimate the measurement errors, they are much smaller than the warming that we see. We know that the thermometer record is reliable, both because the data themselves tell us so, and because they agree with other sources of temperature data.

Abstracting and indexing

The journal is abstracted and indexed in Current Contents/Physical, Chemical & Earth Sciences and the Science Citation Index.[1] According to the Journal Citation Reports, the journal has a 2021 impact factor of 7.237, ranking it 11th out of 94 journals in the category "Meteorology & Atmospheric Sciences".[2]

References

  1. ^ "Master Journal List". Intellectual Property & Science. Thomson Reuters. Retrieved 2014-05-12.
  2. ^ "Journals Ranked by Impact: Meteorology & Atmospheric Sciences". 2021 Journal Citation Reports. Web of Science (Science ed.). Thomson Reuters. 2021.

External links

This page was last edited on 14 November 2023, at 12:53
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