Guest Commentary from Urs Neu
When discussing the influence of anthropogenic global warming on hurricane or tropical cyclone (TC) frequency and intensity (see e.g. here, here, and here), it is important to examine observed past trends. As with all climate variables, the hurricane record becomes increasingly uncertain when we go back in time. However, the hurricane record has some peculiarities: hurricanes are highly confined structures, so you have to be at the right place at the right time to observe them. Secondly, hurricanes spend most of their life in the open oceans, i.e. in regions where there are very few people and no fixed observations. This means that the reliability of the long-term hurricane record is dependent on who was measuring them, and how, at any given time. The implementation of new observation methods, for example, might have altered the quality of the record considerably. But how much? This crucial question has been widely discussed in the recent scientific literature (e.g. Chang and Guo 2007, Holland and Webster 2007, Kossin et al. 2007, Landsea 2007, Mann et al. 2007). Where do we stand at the moment? This post will concentrate on the North Atlantic, which has the longest record.
The official Atlantic hurricane record provided by the U.S. National Hurricane Center (HURDAT) represents the reference data base for most of the studies and contains all observed TCs, their individual tracks and intensity. The record has been extended back to 1850, and the earlier periods (until 1914) have been re-analysed in recent years. Reanalysis work continues, and updates and corrections are regularly reported.
This record contains two important abrupt inhomogeneities. The introduction of air reconnaissance flights in 1944 and the launch of the first geostationary satellite ATS-I in December 1966 mark two important improvements of measurement facilities and thus the observational coverage of the area under examination. Landsea (2007) claims a third one in 2002, since the new advanced microwave sounding unit (Quikscat) has lead to the retrospective detection of additional tropical cyclones in the last few years. Some also argue for placing the start of the satellite area later, in the mid-1970s relying on the launch of the GEOS-satellites. Furthermore, there are some changes in ship track patterns after 1914 with the opening of the Panama Canal and during the two world wars.
In addition, there are also a number of gradual observational improvements over time, e.g. the increasing quality of satellite images, or in earlier times the increase of the number of ship tracks or the growing population density on the coastlines, both of which enhance the probability that a TC would have been observed. And last but not least, there might be inhomogeneities due to the subjective component in the classification of tropical storms (the so-called Dvorak method, Dvorak 1984) which might lead to systematic differences between different forecasters. However, the homogeneous reanalysis of the last 23 years has shown that this subjectivity and improved observations has not lead to a noticeable alteration of the long-term trend for Atlantic storms (Kossin et al. 2007).
Climate change impacts on hurricanes generally focus on two key quantities, the frequency and intensity of storms. There is no reason to believe that both quantities will change similarly. In the discussion of past activity, the frequency is described by the number of tropical storms that occur annually in each basin. The maximum intensity (or even more complex metrics such as the Power Dissipation Index which integrates intensity over space and time; Emanuel 2005) is harder to measure, because it requires detailed information about the storm along the storm track over its entire lifetime. Therefore most discussions of historical trends have focused on tropical storm frequency/number or in some cases the number of intense storms (e.g. the number of major hurricanes).
Thus the key question is: how many storms did we miss in the past? Recently there have been a number of attempts to estimate this ‘undercount bias’ in the tropical storm record. These attempts have included:
- reconstruction of the observational bias by relating past observation density (e.g. ship tracks) to modern storm tracks
- using the relation between total TC number and better known subsets of the TC record (e.g. landfalling storms)
- using relationships of known underlying variables (e.g. relevant climate indices) to annual TC numbers to create a ‘predicted’ TC record, and compare it to the observed record.
All these approaches have a common caveat, namely the assumption that the relationships they rely upon are constant over time. The validity of this assumption therefore has to be examined in any studies using such approaches. Let us consider some recent such studies:
(1) Landsea  performed a simple analysis to estimate the observational bias for the time from 1900 until the begin of the satellite period in 1966. He examined the percentage of tropical cyclones that struck land (PTL) and notices a considerable difference between the time periods 1900-1965 (pre-satellite period, PTL=75%) and 1966-2006 (PTL=59%). He suggests that this difference indicates an underestimation of about 2 tropical cyclones per year before 1965.
Unfortunately, Landsea does not discuss the evolution of PTL before 1900 (left side of the red dashed line in Figure 1). If PTL really is a proxy for underreporting due to decreasing observation density, PTL should further increase before 1900. However, there is a decrease. The period 1851-1899 has an average PTL of 67%, the period 1851-1885 even has an average PTL of 61%, which is not significantly different from the satellite period after 1966 (59%).
Figure 1. Percentage of all reported tropical storms, subtropical storms, and hurricanes that struck land 1851-2006. Extension of Fig. 2b in Landsea .
Therefore it is questionable if PTL really is a reliable proxy of underreporting. One might argue, as Landsea implicitly does, that after 1900 the population density on the coasts and islands was high enough to catch all tropical cyclones, and the underreporting is only due to decreasing density of shipping tracks, while before 1900 also some tropical cyclones that struck land were missed. However, before 1900 not only population density but also shipping track density was lower and therefore PTL likely should be about at the same level as after 1900 but not significantly lower. In addition, Landsea contradicts that argument himself by stating that even in 2005 a retrospective analysis reveals that there was a tropical cyclone that made landfall in a sparsely populated area and was therefore not initially included as a landfalling storm.
Moreover, in another study (Holland, 2007) it has been shown, that the natural variability of TC numbers is different for different regions of the tropical Atlantic. Therefore, the proportion of TCs over the open sea also varies naturally, altering the landfall proportion for reasons unrelated to observation bias. Thus PTL seems not to be a good proxy for observational biases. The study showed that the decrease in PTL in the 1960s is mainly due to a decrease of TC number in the Caribbean and the Gulf of Mexico. Since these regions are well observed by dense ship tracks and a number of islands, this decrease is very unlikely to be mainly an observational bias.
(2) Sticking to ship tracks, Chang and Guo (2007) performed a different type of analysis: They compared the ship tracks of the years before the satellite era with TC tracks of recent years. For example, they took the ship tracks of the year 1917 and overlaid the TC tracks of 1999 and determined how many of the 1999 tropical cyclones would have been observed if the ships had navigated as in 1917. By comparing the years before the satellite era to all the ‘satellite’ years (after 1965) they obtained statistics for how many TCs would likely have been missed in earlier years if the distribution of TC tracks had been similar to that during the satellite period. In this way they estimated a TC undercount of about 2 per year in the period 1903-1914, 1-2 per year 1915-1925 and of less than 1 per year from 1925-1965.
The adequacy of this estimation depends on several assumptions: a) that the distribution of the hurricane tracks is about the same in the satellite period than in the periods before. As we have seen before (Holland 2007), there are shifts in the regional distribution over the 20th century. This could influence the estimation of underreporting both in a positive or negative way; b) that all landfalling storms have been detected correctly. It is likely that some of the landfalling storms (or their true strength) might have been missed, which would bias the estimate artificially low; c) that ships did not circumnavigate the storms (e.g. on the basis of predictions). If this was the case, the undercount estimate might be too conservative; d) that ships measured wind correctly. Because this error is random, a significant systematic bias of the undercount estimate is unlikely; and e) that all ship tracks are recorded in the database used. There may have been other, unrecorded ship tracks, which might have detected a storm missed by known ship tracks. This would lead to an exaggerated undercount estimate. Altogether these assumptions likely tend to somewhat underestimate the undercount.
(3) In a third study (Mann et al. 2007; in full disclosure, I was a co-author of this paper), an alternative approach was used employing the statistical relationship between Atlantic TC numbers and three climate variables influencing Atlantic TC activity (1. August-October sea surface temperatures over the main development region (“MDR”); 2. the El Niño/Southern Oscillation, and 3. the North Atlantic Oscillation) during the modern period of reconnaissance flights and satellite observations (1944-2006). This relationship was then used to predict TC numbers for the period 1870-1943 as would be expected from the behavior of the three climate variables used over that period. These estimates were then compared to the observed TC record, the difference providing an estimate for the underreporting. The results yielded an undercount before 1944 of 1.2 TCs per year (best estimate), with a range of 0.5-2 TC per year.
This analysis also relies on several assumptions. Namely, that a) the underlying climate variables do not contain artificial trends or other inhomogeneities that might bias the results. That the results were insensitive to using different alternative SST datasets, or switching the role of training period and prediction period (i.e. training on 1870-1943 and predicting for 1944-2006) was taken, however, as evidence against this being a significant issue. b) that there are no long-term trends in other climate variables not included in the statistical model, but that do influence TC numbers (e.g. wind shear or vertical stability) or might influence the relationships between TC numbers and the variables that are used. Although such an influence cannot be excluded, cross-checks that were performed such as statistical validation and switching the order of training and prediction intervals, seem to argue against this being a problem.
In summary, according to current knowledge, the best estimate for the underreporting bias in the hurricane record seems to be about one tropical cyclone per year on average over the period 1920-1965 and between one and three tropical cyclones per year before 1920. With only a few years of data available, the influence of Quikscat analyses after 2002 as discussed by Landsea, is difficult to as yet meaningfully estimate.
Chang, E. K. M., and Y. Guo (2007): Is the number of North Atlantic tropical cyclones significantly underestimated prior to the availability of satellite observations? Geophys. Res. Lett., 34, L14801, doi:10.1029/2007GL030169.
Holland, G. (2007): Misuse of landfall as a proxy for Atlantic tropical cyclone activity. Eos Trans. AGU, 88, 349.
Holland, G.J., and P.J. Webster (2007): Heightened tropical cyclone activity in the North Atlantic: natural variability or climate trend? Philos. Trans. R. Soc. Ser. A, 365, 2695– 2716, doi:10.1098/rsta.2007.2083.
Kossin, J. P., K. R. Knapp, D. J. Vimont, R. J. Murnane, B. A. Harper (2007): A globally consistent reanalysis of hurricane variability and trends. Geophys. Res. Lett., 34, L04815, doi:10.1029/2006GL028836.
Landsea, C. W. (2007), Counting Atlantic Tropical Cyclones Back to 1900. EOS, 18, 197-208.
Mann, M.E., T.A. Sabbatelli, U. Neu (2007): Evidence for a modest undercount bias in early historical Atlantic tropical cyclone counts. Geophys. Res. Lett., 34, L22707, doi:10.1029/2007GL031781.