I have previously written Michael E. Mann's predictions.
But to this day, I realized his own autopsy analysis. Mann's reflection on the 2024 Hurricane Season of 2024 provides a fascinating case research on how to predict climate prediction and how their authors work hard to re -list them as meaningful contributions. Although the work must first herald the “positive, destructive and fatal” hurricane season, its real focus is that it is a less successful story: Mann's own predictions and reality failure failed.
Settings: Bold prediction, but the results are bland
The beginning of Mann is a dramatic language about the “unprecedented” hurricane and its connection with the warm ocean. His work asserts that the warmth caused by artificially drives a stronger storm, because it has been rapidly strengthened under specific circumstances such as Hurricane (reached 185 miles/h), and even speculates that the hypothesis needs to be hypothetical. “Category 6” classification.
Indeed, Milton almost violated a recent study, which constitutes a new hurricane “sixth category” capabilities, which appeared in an unprecedented ocean warmth era. Another study estimates that through human warming, the deadly flood in Hylun in the southeast of the United States increased by 50 %.
However, these strong claims about hurricanes are inconsistent with the latest discovery of IPCC. The sixth evaluation report (AR6) clearly states that the evidence of the frequency and strength of the frequency and strength of the hurricane is not yet conclusive, and there is no detection of global cyclone frequency and mixed regional trends that can be detected. Although short -term variability may produce extreme seasons, a wider situation is contradictory with Mann's insistence on climate change. His narrative depends on the extreme situation of selecting cherries, not a complete record.
This misalignment has expanded to his prediction. Mann (Mann) and his team predicted a “extremely active” hurricane season, most likely to estimate 33 named storms. Instead, only 18 or 19 are produced in this season, if we generously include a boundary case. From a perspective, this is far lower than Mann's expected 27-39 storm range. Not exactly the expected “record” season.
Express: blame variables, ignore the model
Mann and his colleagues did not have the shortcomings of predicts, but turned to a familiar script: quoting unpredictable variables to explain their miss. They accused Madden-Julian oscillating (MJO) a well-known atmospheric cycle, because the formation of storms in the peaks in key July and August. The outbreak of the Sahara dust is also called a factor.
Therefore, there is no real difference about the second half of the season. Basically, it is as active as expected. This problem is why the seasonal large -scale climate conditions are obviously favorable, but July and August are so quiet. Here, people will fall into the complications of mutation within the season. The so-called Madden-Julian oscillation or “MJO” for his friend. MJO is about 40-50 days in the tropical atmospheric cycle. It affects the position of the convection and moves towards the opposite position during a single 40-50-day cycle. When the center of the convection is consistent with the tropical Atlantic Ocean, the conditions are beneficial to tropical ring reproductive.
Although these factors have undoubtedly played a role, they have almost no “unknown”. For a long time, these two phenomena are considered influence in tropical weather. Should complicated statistical models be touted as a conventional variant of “most accurate”? Mann's dependence on these explanations is less Relying, not the reason for traceability.
Alternative model: When one prediction fails, please transfer to another prediction
Mann (Mann) strangely, Mann emphasized a alternative model of 19.9 storm, which is very close to the total number of observed. However, he acknowledged that this model is usually not as reliable as failed. Touching the secondary, the success of less accurate framework seems to be hedging and gambling instead of improving science. If your “backup” prediction is better, why not use it as the main model of progress? This plan is more question than answering.
There is also a noteworthy detail here. Our group has made an alternative prediction, of which the tropical sea surface temperature (SST) in the main development area (MDR) is replaced by “relative SST”, defined as the difference between the average SST of the MDR SSST and the entire tropical tropical tropical Essence Some researchers believe that this may be a better prediction indicator for the Atlantic hurricane. Although our previous analysis found that this alternative model is less skilled prediction, it is worth noting that this year's forecast is more accurately predicted by a storm of 19.9 +/- 4.5, which is very close to the total number of seasonality.
More powerful hurricane? Not so fast
One of the particularly bold claims in Mann's reflection is that the artificial warming directly led to the rapid strengthening and increasing damage to the storm. He pointed out that Milton and Helen are evidence, and even quoted research on research to propose the need for new “6 categories” hurricane classification.
However, this narrative ignores IPCC's cautious position on this issue. IPCC AR6 only found lower confidence that can be detected by global hurricane intensity. Although the peak wind speed of tropical cyclones has increased, these trends have not been observed in all marine basins. In addition, the number of global cyclones has decreased or kept flat. Mann's narrative about a dangerous storm world is more rhetorical than strict science.
This is the reality of the tropical cyclone trend of Roger Pielke JR and Ryan Maue
“We have determined the frequency of the global hurricane landing; however, in the resolution of available data, our evidence does not support a large amount of small, large or total hurricanes during the period of available quality data. Long -term global or single basin linear trend. “
Mann's position inadvertently highlights the key issues of climate science: the gap between predicting confidence and observation results. When the forecast fails, climate scientists often claim that the climate system is no longer predictable, and their models are still correct, but they cannot adapt to the “change system.” This raises a key question: If the behavior of the system is unpredictable, how to predict how to ask for such a firm trust, let alone to prove that the wide climate policy is reasonable?
Mann's reflection ends with the vigorous development of ominous: “There may be more unpleasant surprises in the greenhouse.” Although this warning is useful for catching headline news, they have It may destroy public confidence. If we are not sure what will happen, who can be determined on the impact of climate change? This is not very scientific and more speculative to tell stories.
Finally thought: unconstrained and moving door columns
The 2024 Atlantic Hurricane Season is not a predictive disaster. Although the storm indeed is destructive, there is far from expectations throughout the season. This triggered a key issue: When the prediction fails, should we perfect the model or double the narrative of fear drive?
Man's reflection implied the latter method. The prediction he insisted on missed still “taught us important courses” avoided more obvious conclusions: the disadvantages of excessive self -confidence in flawed models are greater than benefits. He believes that the rules of the climate system may be changing, rather than acknowledging that these forecasts have restrictions. This is a convenient excuse, but convincing.
In order to give climate science any reputation, it needs to honestly work hard to grasp its uncertainty, rather than re -composition to prove an unknown and constantly changing reality. Prior to this, people couldn't help but regard it as another chapter of the increasingly serious climate forecast.
