Previous Energy Matters posts that have dealt with the cloud/temperature relationship (here and here) have concluded, as have most other studies, that cloud cover acts as a control on global surface temperatures. In this post I dust off a widely ignored but apparently robust cloud cover series – the ICOADS ocean series – which suggests that ocean surface temperatures may in fact be acting as a control on cloud cover rather than the other way round.
In his 2015 post on NASA climatology data Euan Mearns presented a version of this graph:
Figure 1: ISCCP cloud cover vs. HadCRUT4 surface temperature
And captioned it thus:
ISCCP global mean cloud amount in black varies inversely with temperature in blue. No major surprise there, less cloud and a warmer surface, but what causes what?
What causes what indeed? It is of course commonly assumed that fewer clouds cause warmer temperatures and more clouds cooler temperatures. But how you interpret the relationship depends on which cloud data set you use, and here I present some data sets that suggest an alternative interpretation.
The ISCCP series is one of a number of cloud cover series derived from data collected by the AVHHR, MODIS and other satellites, and Figure 2 shows all of them plotted together. The conclusion reached by the World Climate Research Programme, which included this graph as Figure 3.5.1 in its voluminous 2012 report, was that you can’t deduce anything from these results: “At present, one can only conclude that global mean monthly cloud amount is constant over the last 25 years to within 2.5%, within the range of annual variability”:
Figure 2: Global cloud cover data derived from all satellites
Here’s a simplified version of the Figure 2 plot from Nigel Calder’s website:
Figure 3: Selected satellite and other global cloud cover series
The ISCCP cloud cover series seems to be cherry-picked, which leaves me free to cherry-pick a series of my own. I’ve chosen PATMOS-x, which is actually a little longer than ISCCP. Figure 4 isolates it.
Figure 4: PATMOS-x cloud cover series
Figure 5 now adds four more series – scales are not shown partly because I don’t know how to make them compatible but mostly because the idea is simply to show trends.
The first series is one that hardly anyone ever looks at – the ICOADS ocean cloud cover series, which I downloaded from KNMI Climate Explorer. Note that because the oceans are cloudier than the land roughly 80% of the world’s clouds form over the oceans.
The second is the NASA NVAP-M atmospheric water column series, which we might expect to be related to cloud cover. (h/t to Clive Best for bringing it to my attention):
The third is the unadjusted ICOADS SST series, also downloaded from KNMI (HadSST3 is essentially the same over this time period).
The fourth is a crude measure of the average tropospheric lapse rate that I put together by subtracting the RSS lower stratosphere temperature anomalies from the ICOADS SST anomalies. (The two downward excursions are present in the stratosphere record and were caused by the El Chichón and Pinatubo eruptions). Presumably lapse rate would also have some impact on cloud formation, although I don’t insist on it:
Figure 5: Five cloud-cover and cloud-cover-related series
All five series show the same basic trends – increasing before the late 1990s, peaking around the time of the 1997/8 El Niño and deceasing or flattening thereafter.
This congruence of trends seems a little too close to be coincidental. It implies a relationship between temperature and clouds in the sense opposite to that usually assumed, i.e. with temperatures increasing rather than decreasing as cloud cover increases. It’s difficult to see how an increase in cloud cover could cause warming, so the supposition would be that the ocean surface warming is causing the increase in cloud cover.
The series shown in Figure 5, however, go back only to 1982. Can we trace a temperature/cloud relationship before then? Indeed we can. The ICOADS ocean cloud cover series, which extends back to 1855, shows a positive relationship with ICOADS SST (also downloaded from KNMI) going all the way back to around 1890 before it begins to break apart:
Figure 6: ISCCP cloud cover vs. HadCRUT4 surface temperature
If this relationship is real it raises the possibility that the +/-1C increase in ocean surface temperature during the 20th century caused a +/-10% increase in ocean cloud cover. The objection that the ICOADS cloud cover series, which is put together from visual shipboard observations, and the SST series aren’t reliable will inevitably surface here, so we will now address the question of whether they are reliable or not. The conclusion is that while their accuracy can’t be guaranteed there are no reasons to suppose that there is anything seriously wrong with them after 1960.
The question of the reliability of the ICOADS ocean cloud cover series, which is constructed from many millions of visual cloud cover observations made from ships, has been reviewed by various investigators, including:
And apart from some localized biases and a minor “night-reading” bias (observers tend to measure fewer clouds at night) none of them seems to have found anything seriously wrong with it. Smith sums it up thus: “The annual analysis indicates oceanic cloudiness variations that are broadly consistent with known climate modes such as ENSO. Variations also indicate multi-decadal variations, including trend-like variations over the 20th Century consistent with changes in global SSTs. Because of those consistencies with independent analyses it is likely that most of the analyzed variations are caused by climate variability.” Not a completely clean bill of health, but close.
The “trend-like variations over the 20th Century consistent with changes in global SSTs” that Smith refers to are seen in Figure 6 above. There is a strong correlation between ocean cloud cover and sea surface temperature (R^2 = 0.84 for annual means) after 1890. It persists during World War II, when both records show a large spike caused by a wartime observational bias, and also during the period of no warming since 1998, when both cloud cover and SST decrease or flatten out:
Why should ocean cloud cover and SST track each other over a period of 120 years? There are two possibilities. Either the SST data or the cloud data, or both, are distorted by biases that make them appear to be related, or they really are related.
We will deal with the bias issue first. Here’s a summary of the evidence for the existence of biases in the ICOADS cloud cover and SST records:
1. The SST/cloud correlation breaks down before 1890, raising the question of whether the correlation after 1890 might not be spurious. (An alternative explanation is bad and/or insufficient data before 1890.)
2. According to conventional wisdom the SST record is variably distorted by instrumental biases before about 1960 (I think it isn’t, but that’s beside the point). However, it’s also generally accepted that it isn’t seriously distorted after 1960.
3. Increasing areal coverage during the second half of the 19th century and the first half of the 20th could have caused an overall shift of observations from cooler and less cloudy to warmer and more cloudy areas, thereby making it appear that global SST and cloud cover were increasing even though they weren’t. Since 1960, however, coverage has been essentially stable except for the area south of 40S latitude, and deleting the small amount of data below 40S makes no significant difference to global cloud cover and SST trends (Figure 7).
4. Before 1950 there’s an inverse relationship between cloud cover estimates and the number of observations (Figure 8), which is evidence for a bias of some kind (the same relationship is visible in the SST record, but less well-defined). There is, however, no clear relationship between cloud cover or SST and the number of observations after 1950. (Figure 8 shows negative numbers of observations because KNMI treats nobs as a climate variable and expresses it as anomalies relative to the mean, but this doesn’t change the shape of the plot.)
5. According to Eastman et al. “a major change in the classification of cloud types (from tenths to oktas) was instituted in 1949, and it was not until 1954 that the change was adopted by ships of all nations”, which is why the Eastman reconstruction begins in 1954. There’s no evidence that this change distorted the cloud cover record but we’ll take it into account anyway.
6. The data during WWII are clearly bad and should be deleted.
Figure 7: ICOADS cloud cover observations, global coverage 1860-1960
Figure 8: ICOADS cloud cover series vs. number of observations
But none of these six potential sources of bias affects the data after 1960, so we can eliminate all of them simply by deleting the data before 1960. This leaves us with a continuous 64-year-long ocean cloud cover series that again broadly tracks sea surface temperatures:
Figure 9: ICOADS cloud cover vs. SST series, 1960 on
A few more checks before proceeding to see if we can detect any other flaws in the ICOADS records. Figure 10 matches the ICOADS SST data against independently-measured GISS surface air temperatures since 1960 (data again from KNMI):
Figure 10: ICOADS SST vs. GISS surface air temperature series
There are no reliable independent data sets to compare the ICOADS cloud cover data against, but Figure 11, which compares monthly cloud cover records from 11 coastal stations in Europe (from the ECA data base) against the cloud cover data in the ICOADS grid blocks that overlap these stations, shows generally excellent agreement between land-based and shipboard observers over a period of almost 50 years:
Figure 11: Cloud cover observations, ICOADS shipboard vs. ECA land-based
And for what it’s worth Figure 12 shows a respectably close match between the ICOADS and ISCCP grid blocks covering these 11 stations after 1989:
Figure 12: Cloud cover observations, ICOADS shipboard vs. ISCCP satellite
From Figures 11 and 12 we can deduce that ground and shipboard observers do a good job of counting clouds.
Inevitably, however, there are instances where the cloud/SST correlation breaks down. Figure 13 plots ICOADS SST against ICOADS total cloud cover in the 30-60N, 0-30N, 0-30S and 30-60S latitude zones. The temperature-cloud correlation is present in the 0-30N, 0-30S and 30-60S bands but not in the 30-60N band:
Figure 13: ICOADS cloud cover and SST in different latitude zones
And while there’s a long-term correlation between global SST and global cloud cover in most places there is no correlation over shorter periods. Figure 14, which compares detrended monthly ICOADS global SST with detrended monthly ICOADS global total cloud cover, has an R^2 of 0.02.
Figure 14: Detrended ICOADS cloud cover and SST data
There is just one place where we see a strong short-term positive correlation between SST and cloud cover – in the El Niño zone (5N-5S, 160E-100W, Figure 15). Note that the two plots use the same Y-scale. One gets the impression that ENSO events, in particular strong El Niños, manufacture a lot of the world’s clouds:
Figure 15: ICOADS cloud cover (orange) and SST (blue) inside & outside El Niño zone
That concludes the data review. It isn’t fully diagnostic, but there is no good evidence that there is anything seriously wrong with either the ICOADS SST or the ICOADS ocean cloud cover series at least after 1960. That being the case I submit that the possibility that temperatures control clouds, and not the other way round, should be considered.