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Weather is not climate

Commentaire :

Many climate skeptics use this argument, saying that it is impossible to predict at 100 years as it is already difficult to do so at 10 days.

Except that these predictions (1) do not use the same models, and (2) do not predict the same durations (in 2 hours or in 100 years), nor during the same durations (rain for 15 minutes, versus average warming of 1°C), or in the same geographical areas (in a district versus a country).

Commentaire :

Although analyzing similar (and sometimes identical) variables, climate and weather models are nevertheless based on different methods and tools.

But this situation is not unique. Other fields, such as macro- and microeconomics, which analyze monetary interactions between agents, do so at different scales and for different purposes. The same goes for many fields of physics which, modeling or analyzing similar objects or phenomena, do so with distinct tools: geometric optics or wave optics, classical mechanics and relativistic mechanics, etc.

Commentaire :

Meteorological models are models which describe the evolution of the atmosphere according to 1/ an initial state, such as the humidity rate and the pressure at this very moment, and 2/ mathematical laws which describe the evolution since a T state to a T+1 state – like when weather forecasts “advance” in time when shown on TV.

And, as this initial state is imperfect (it is impossible to describe all the drops of water for example) and as these laws are imperfectly approximated (solution of a partial differential equation), it results that the more one predicts for a distant date, the more chance there is of being wrong. To find out more, it’s here or there. And to really know a lot more, it’s here.

There are also many different models. Also known as numerical weather prediction (NWP).

Commentaire :

There are different climates, i.e. geographical areas that share the same characteristics (temperature, pressure, precipitation, etc.) over time. For more details on how to distinguish these climates, we recommend this explanation from Larousse encyclopedia. It should be noted that this distinction is only one among others since there are several classifications – of Köppen-Geiger, Troll and Paffen or others – which depend on the variables used to distinguish said climates.

Commentaire :

Like weather models, climate models – described in more detail in this blog post by Jean-Marc Jancovici or in the Environment Encyclopedia – ​​describe the evolution of certain variables (temperature, precipitation, heat , etc) from an initial state, according to laws which describe the progressive variation of this state. Nevertheless, these two families of models differ in several respects.

On the one hand, the variables described are not exactly the same, and the mathematical and physical laws that describe their evolution are different. And on the other hand, the time step between one state of the system and the next is not of the order of a minute or ten minutes (weather) but of a month or more (climate). This explains why the variables described are over longer periods. The spatial resolution (i.e. the size of the region over which the system is described) is often higher in the case of climate models which are not interested, in essence, in the amount of rain that there will be at 7 p.m. in a specific city.

Commentaire :

If we haven’t succeeded in convincing you, maybe others will do it better than us, whether it’s the article “How to stop confusing weather and climate” from the Bon pote blog or the videos of Météo France or of Bright Blue.

Commentaire :

These figures were made by us from data available in the Summary for Policymakers of the IPCC WP1 AR6 reportdata from Figure SPM 1 (page 6) freely available here. The first line only aggregates data observed since 1855. The lack of homogeneous and/or reliable observations led to reconstructing data for previous years: we are talking about reconstructed data for temperatures between the year 5 and 1855.

These graphics are inspired by the warming stripes popularized by Ed Hawkins. And do not hesitate to ask us for the code (in Python) if you want to reproduce the figures.

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