When climate deniers are desperate because the measurements don’t fit their claims, some of them take the final straw: they try to deny and discredit the data.
The years 2014 and 2015 reached new records in the global temperature, and 2016 has done so again. Some don’t like this because it doesn’t fit their political message, so they try to spread doubt about the observational records of global surface temperatures. A favorite target are the adjustments that occur as these observational records are gradually being vetted and improved by adding new data and eliminating artifacts that arise e.g. from changing measurement practices or the urban heat island effect. More about this is explained in this blog article by Victor Venema from Bonn University, a leading expert on homogenization of climate data. And of course the new paper by Hausfather et al, that made quite a bit of news recently, documents how meticulously scientists work to eliminate bias in sea surface temperature data, in this case arising from a changing proportion of ship versus buoy observations. More »
The Norwegian Meteorological institute has celebrated its 150th anniversary this year. It was founded to provide weather data and tentative warnings to farmers, sailors, and fishermen. The inception of Norwegian climatology in the mid-1800s started with studies of geographical climatic variations to adapt important infrastructure to the ambient climate. The purpose of the meteorology and climatology was to protect lives and properties.
I have a post at Nate Silver’s 538 site on how we can predict annual surface temperature anomalies based on El Niño and persistence – including a (by now unsurprising) prediction for a new record in 2016 and a slightly cooler, but still very warm, 2017.
Some of you that follow my twitter account will have already seen this, but there was a particularly amusing episode of Q&A on Australian TV that pitted Prof. Brian Cox against a newly-elected politician who is known for his somewhat fringe climate ‘contrarian’ views. The resulting exchanges were fun: More »
How should one make graphics that appropriately compare models and observations? There are basically two key points (explored in more depth here) – comparisons should be ‘like with like’, and different sources of uncertainty should be clear, whether uncertainties are related to ‘weather’ and/or structural uncertainty in either the observations or the models. There are unfortunately many graphics going around that fail to do this properly, and some prominent ones are associated with satellite temperatures made by John Christy. This post explains exactly why these graphs are misleading and how more honest presentations of the comparison allow for more informed discussions of why and how these records are changing and differ from models. More »