Warmer and warmer

Furthermore, soil moisture may affect T(2m), linking temperature to precipitation. The energy flow (heat fluxes) between the ground/lakes/sea and the atmosphere may also affect surface temperatures. However, both precipitation and heat fluxes are computed by the reanalysis atmosphere model without direct constraints, and are therefore only loosely tied to the observations fed into the models. Furthermore, both heat fluxes and precipitation can vary substantially over short distances, and are often not smooth spatial functions.

While the evidence suggesting more extremely high temperatures are mounting over time, the number of resources offering data is also growing. Some of these involve satellite borne remote sensing instruments, but many data sets do not incorporate such data.

In the book “A Vast Machine“, Paul N. Edwards discusses various types of data and how all data involve some type of modelling, even barometers and thermometers. It also provides an account on the observational network, models, and the knowledge we have derived from these. Myles Allen has written a review of this book in Nature, and I have reviewed it for Physics World (subscription required for the latter).

All data need to be screened though a quality control, to eliminate misreadings, instrument failure, or other types of errors. A typical screening criterion is to check whether e.g. the temperature estimated by satellite remote sensing is unrealistically high, but sometimes such screening may also throw out valid data, such as was the case of the Antarctic ozone hole. Such post-processing is done differently in analyses, satellite measurements, and reanalyses.

The global mean temperature estimated from the ERAINT, however, is not very different from other analyses or reanalyses (see figure below) for the time they overlap. We also see a good agreement between the ERA40 reanalysis, the NCEP/NCAR reanalysis, and the traditional datasets – analyses – of gridded temperature (GISTEMP, HadCRUT3v, NCDC).

Do the ERAINT and ERA40 provide a sufficient basis for making meaningful

inferences about extreme temperatures and unprecedented heat waves? An important point with reanalyses, is that the model used doesn’t change over the time spanned by the analysis, but reanalyses are generally used with caution for climate change studies because the number and type of observations being fed into the computer model changes over time. Changes in the number of observations and instruments is also an issue affecting the more traditional analyses.

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