Global versus Greenland Holocene Temperatures

By Andy May

Last week, I posted a global temperature reconstruction based mostly on Marcott, et al. 2013 proxies. The post can be found here. In the comments on the Wattsupwiththat post there was considerable discussion about the difference between my Northern Hemisphere mid-latitude (30°N to 60°N) and the GISP2 Richard Alley central Greenland temperature reconstruction (see here for the reference and data). See the comments by Dr. Don Easterbrook and Joachim Seifert (weltklima) here and here, as well as their earlier comments.

Richard Alley’s (Richard Alley, 2000) central Greenland reconstruction has become the de facto standard reconstruction and is displayed often in papers and posts. And, truth be told, I’ve often used it. See here for an example. But, it is a central Greenland reconstruction, uncorrected for elevation differences over time, and all of Greenland is north of 60°N. A better comparison is with my Arctic reconstruction that goes from 60°N to the North Pole. This comparison is shown in figure 1.

Figure 1

Alley’s reconstruction is based upon trapped air in ice cores taken from central Greenland and his proxies are calibrated to air temperatures on land. My Arctic reconstruction is based upon nine proxies, five are marine proxies and 3 are land proxies. Only one of the land proxies is a Greenland ice core and I used a composite of two Greenland area ice cores, Agassiz and Renland, by Vinther, et al. (2009) and not the better-known Alley reconstruction. The Vinther reconstruction and the Alley reconstruction are compared, using actual temperature, in figure 2.

Figure 2

As can be seen in figure 2, the Vinther Agassiz and Renland reconstruction is less erratic and has a more prominent Holocene Climatic Optimum (HCO) than the Alley reconstruction. In addition, the Vinther Medieval Warm Period is older and the Roman and Minoan Warm periods are far less prominent and offset in time. Notice the reconstructions match in the Little Ice Age (LIA) and that the Vinther Holocene Climatic Optimum (HCO) from 8000 BC to 4500 BC is more prominent. The HCO doesn’t really show up in the Alley record. Below we compare our Arctic reconstruction to the Vinther record in Figure 3.

Figure 3

Vinther’s record shows a more prominent HCO than ours, more detail and a deeper LIA. Finally, let’s compare both Vinther and Alley to our Northern Hemisphere mid-latitude reconstruction in figures 4 and 5.

Figure 4

It is interesting that Vinther agrees with the mid-latitude Northern Hemisphere reconstruction in the Neoglacial period (roughly 5700 BP or 4300 BCto the present), but agrees better with the Arctic reconstruction during the HCO. I’m not completely sure why that is.

Figure 5

Comparing figure 4 to figure 5, we can see that Alley has a very flat trend and is more active than Vinther. Vinther is a better match to our Northern Hemisphere mid-latitude reconstruction. Alley’s reconstruction starts to show the HCO and then fizzles at about 1,000 years in to it. Figures 4 and 5 are anomalies from the mean temperature from 9000 BP to 500 BP, however, which distorts the picture a bit given the two reconstructions differ on the temperatures of the HCO and the LIA. I refer you to figure 2, where we compare Vinther to Alley in actual temperature and not in an anomaly form. Here the two reconstructions agree on the temperature of LIA, but the Alley reconstruction does not see the HCO. We see that the key difference between the two is the degree of warming during the HCO.

Why are Alley and Vinther different?

The short answer is that Vinther, et al. (2009) corrected their ice core records, including GISP II and GRIP, for elevation differences and Alley did not. In Vinther’s words:

“The previous interpretation of evidence from stable isotopes (δ18O) in water from GIS [Greenland Ice Sheet] ice cores was that Holocene climate variability on the GIS differed spatially and that a consistent Holocene climate optimum—the unusually warm period from about 9,000 to 6,000 years ago found in many northern latitude palaeoclimate records—did not exist. Here we extract both the Greenland Holocene temperature history and the evolution of GIS surface elevation at four GIS locations. We achieve this by comparing δ18O from GIS ice cores with δ18O from ice cores from small marginal icecaps [Agassiz and Renland]. Contrary to the earlier interpretation of δ18O evidence from ice cores, our new temperature history reveals a pronounced Holocene climatic optimum in Greenland coinciding with maximum thinning near the GIS margins. Our δ18O -based results are corroborated by the air content of ice cores, a proxy for surface elevation.”

In figure 6 we see a summary of the Vinther, et al. (2009) data, it is their figure 1.

Figure 6 (Source: Vinther, et al. 2009)

The six cores are well distributed across Greenland, with Agassiz on Ellesmere Island very close to Greenland. Agassiz and Renland are both coastal cores and have similar profiles. It is possible to reconstruct the elevation histories for these two locations with confidence, so they are used to develop corrections for the remaining 4 ice cores. All six core records shown were included in the Vinther, et al. (2009) reconstruction after adjustment for elevation and ice thickness changes, but the Agassiz and Renland cores are the key cores. The corrections to these cores are shown in 6D. The δ18O profiles for these cores, after the uplift (or elevation) correction has been applied, is shown in 6c. Considering that Agassiz and Renland are on opposite sides of the GIS and 1,500 km apart, the agreement between the two corrected records is astounding, as Vinther, et al. (2009) described it in their paper.

Alley’s reconstruction focused on the GRIP and GISP II cores, these two cores are 30 km apart in central Greenland, they are combined into one point called GRIP in figure 6.

Below is a better location map for the Greenland ice cores, shown as figure 7.

Figure 7 (Source CDIAC)

Temperature determination in these ice cores is done with a function of δ18O and it has been shown by Johnsen and White (1989) that the average δ18O level over and around the Greenland Ice Sheet (GIS) is almost completely described by altitude (-0.6‰/100m) and latitude (-0.54‰/degree N). The altitude effect is due to the moist-adiabatic cooling of an air mass rising above the GIS. As it cools, precipitation and fractionation take place. There are more details on this in the Vinther, et al., 2009 supplementary materials. Thus, there is a sound basis for building a good δ18O temperature record if the altitude of the ice surface is known throughout the Holocene. Elevation differences must be taken into account. As Vinther, et al. (2009) write:

“… the differences in the long-term δ18O trends seem to be related to changing GIS elevation …”

The Holocene Climatic Optimum was a warm period and it caused melting of the GIS. Thinning at the Camp Century and DYE-3 sites started very soon after the HCO began over 9,000 years ago. The thinning progressed from there to the GISP II/GRIP location in a few thousand years, certainly by 6,000 BP. This affected the GISP δ18O temperature record and all but eliminated the HCO response that we see in other Northern Hemisphere records. The elevation corrections applied to the four sites, including GRIP, NGRIP and GISP II are shown in figure 8, from Vinther, et al. (2009).

Figure 8

The Camp Century and DYE-3 locations are on the coast and they are affected most. In the interior GRIP and NGRIP locations (remember GISP II is next to GRIP, see figure 7) the effect is less, but still significant.

Conclusions

If we accept the work that Vinther, et al. (2009) have done as being correct, and I see no problems with it, then the Aggasiz-Renland δ18O records, after correction for elevation records are correct. These records are 1,500 km apart and on opposite sides of the GIS, thus the temperature record of Greenland for this period must be fairly uniform for this period of time. Because of the geological conditions at the Aggasiz and Renland sites, their elevation histories can be reconstruction with some confidence as explained in Vinther, et al.’s paper and supplementary materials. Given that we also know the controls on the average δ18O with confidence, then we can provide a reliable temperature record for these sites. This is the record used in my Arctic reconstruction and the other 8 records used in the reconstruction agree fairly well.

Vinther, et al.’s reconstruction also agrees well with my Northern Hemisphere reconstruction from 4,000 BC to the present. It reaches a lower temperature extreme in the HCO, but matches the HCO of my Arctic reconstruction. Generally, I prefer the Vinther et al. reconstruction to Alley’s earlier GISP II reconstruction for the purpose of detecting the major climatic events of the Holocene and estimating the difference between HCO temperatures and LIA temperatures.

However, for locating climate events in time and whether the event is a warming event or a cooling event, using a single ice core proxy, that is well dated is fine. And the dating error in ice cores is very low, less than 1% (Alley, 2000). It is just that the magnitude of the temperature swings are probably incorrect in the GISP II and GRIP cores due to elevation changes as Vinther, et al. have shown. These changes (or errors in temperature) are the most severe in the HCO. This problem affects the magnitude of the estimated temperature but not the timing of the events.

Using multiple proxies, as I have, helps measure a more accurate and robust temperature anomaly for a region or the whole globe, but adversely affects the timing of events due to averaging multiple proxies with possibly inaccurate dates. Dating errors of 100 to 150 years are probably common and when averaging records with this sort of error, there will be loss of short term amplitude and problems estimating the timing of major events. This always needs to be considered in this sort of work. Amplitude reduction or excessive smoothing of the temperature reconstruction can be minimized by using fewer proxies, higher resolution proxies (shorter sample intervals), minimizing the proxy drop out at both ends of the reconstruction by avoiding short term proxies, and selecting proxies that are not overly affected by local events or local geology. Careful proxy selection is critical for a robust record, for more details on proxies to be avoided and proxies to include see my posts on the reconstructions I made. The final post, which will lead you to the others is here.

So, what is the purpose? Do you want to know, as accurately as possible, when a Northern Hemisphere warming event or cooling event occurred? Then using GISP II or GRIP will work best. Do you want to estimate the average temperature change during the event? Then I would recommend my reconstructions, but realize that the estimate may be conservative and the date of the event may be incorrect by 100 to 150 years. Our knowledge and data about Holocene temperatures are limited, but by using what we have wisely we can begin to get our arms around it.

A Holocene Temperature Reconstruction Part 4: The global reconstruction

By Andy May

In previous posts (here, here and here), we have shown reconstructions for the Antarctic, Southern Hemisphere mid-latitudes, the tropics, the Northern Hemisphere mid-latitudes, and the Arctic. Here we combine them into a simple global temperature reconstruction. The five regional reconstructions are shown in figure 1. The R code to map the proxy locations, the references and metadata for the proxies, and the global reconstruction spreadsheet can be downloaded here. For a description of the proxies and methods used, see part 1, here.

Figure 1A, all proxies except TN057-17 on the Antarctic Polar Front

Figure 1B, the proxies used for the reconstructions

It is interesting that the Northern Hemisphere is the odd reconstruction. This was also true for the Marcott et al. (2013) Northern Hemisphere reconstruction from 30°N to 60°N, see figure S10f, in their supplementary materials. The Northern Hemisphere has the greatest temperature variation of the five regions and a clearly different trend. Is this because it contains most of the land? Perhaps so. It may be, in part, the impact of the melting continental glaciers from the last glacial advance. Certainly, the high Northern Hemisphere insolation, early in the Holocene due to orbital precession and obliquity played a significant role (see figure 2 in part 1, also shown for convenience as figure 2 below). In the figure, the colored curves are the seasonal changes due to precession and the background color is insolation by latitude due to obliquity changes. The black curve is the Greenland NGRIP temperature reconstruction, note that the end of the last glacial period is when both orbital obliquity and precession hit their peak insolation in the Northern Hemisphere. The labels on the curves indicate Northern Hemisphere as “N” and Southern Hemisphere as “S.” The letters after that are the first letters of the months of the year. At the beginning of the Holocene, the Northern Hemisphere summer had maximal insolation due to precession and the higher latitudes (poles) had greater insolation, due to obliquity, at the expense of the tropics. Thus, both the precession cycle and the obliquity cycle were in their warmest phases for the Northern Hemisphere mid and high latitudes. This changed a few thousand years later and the climatic equator (the Intertropical Convergence Zone) shifted and the long Neoglacial cooling period began (see figure 12, in part 2).

Figure 2 (Source: Javier, see his post for a detailed explanation of the figure.)

The Southern Hemisphere is also a bit anomalous, with a dip in the period of the HCO, corresponding with a dip in winter insolation in the Southern Hemisphere. The other interesting thing about the reconstructions is that the Northern Hemisphere has a higher and longer Holocene Climatic Optimum. The Northern Hemisphere was affected much more by the last glacial advance due to the large continental ice masses there. The Southern Hemisphere ice was mostly sea ice which, presumably, melts at a steadier rate with less dramatic effect.

The Arctic and Antarctic each cover 6.7% of the globe, the southern and northern mid-latitudes cover 18.3% each and the tropics covers 50%. If we weight each reconstruction by the area of its region we get the reconstruction in figure 3. Figure 3A uses all proxies, except for TN057-17, which was removed in part 2. Figure 3B also eliminates ODP-658C, KY07-04-01 and OCE326-GGC26. The removal of the latter three proxies are discussed in part 2 and part 3. The two reconstructions only differ in detail.

Figure 3A, all proxies

Figure 3B, three additional proxies removed

We will discuss the reconstruction in figure 3B since we prefer it. In this reconstruction, the depth of the Little Ice Age (LIA) occurs in 1610 AD. The apparent Medieval Warm Period (MWP) is smeared over several hundred years and occurs from around 510 AD to 1050 AD which does not fit the historical record. Oddly, only the Southern Hemisphere and the tropics show a distinct Medieval Warm Period (MWP) in its historical time. This is despite abundant historical evidence of a Northern Hemisphere MWP from around 900 AD to 1200 AD. The Antarctic reconstruction shows several warm spikes during the period, but nothing very distinct. The reason for the lack of a distinct MWP signature in the northern reconstructions is not known. In part 3 we looked at the individual proxies for the Northern Hemisphere and saw that they disagree on the presence and timing of the MWP.

The Roman Warm Period (RWP) shows up well in the reconstruction, at about the right time. The “collapse of civilization” at the end of the Bronze Age is clearly seen. The 4.2 kiloyear event that led to the collapse of the Akkadian empire in 4170 BP can be seen (deMenocal, 2001). The 5.9 kyr event that occurred as the Sahara was turning into a desert, causing a great migration to the Nile valley that ultimately resulted in the Egyptian Old Kingdom is clearly seen. The LIA is the most significant climatic event of the Holocene without question, but the second most severe climatic event may well be the 8.2 kyr event. This event ended the Pre-Pottery Neolithic B culture and was when the Black Sea was catastrophically connected to the Mediterranean in an event that may be remembered as Noah’s great flood (Ryan and Pittman). The 10.3 kiloyear event takes place about the time the Pre-Pottery Neolithic period began. For more details on human history and climate change see “Climate and Human Civilization over the last 18,000 years” here. The historical climatic events match this reconstruction well, except for the MWP.

The details of the regional areas are in Table 1. This table is different from the one presented in part 1 of this series because after part 1 was put up we dropped ODP-658C from the tropics reconstruction and KY07-04-01 and OCE326-GGC26 from the Northern Hemisphere reconstruction. Marcott, et al. (2013) used 73 proxies for their reconstruction and our first pass retained 31 of these and added the Rosenthal et al. (2013) Indonesian proxy for a total of 32. As the study progressed we dropped three more proxies and ended with 29. Fifty-five percent of the proxies are north of 30°N and only 21% are south of 30°S.

Table 1

If we simply average the 5 reconstructions with no weighting, we get the reconstruction in figure 4.

Figure 4, Straight average, no weighting, final proxy set

The two reconstructions are not very different. In this reconstruction, the depth of the Little Ice Age (LIA) occurs between 1530 AD and 1670 AD and the temperature anomaly is -0.84°C. The Holocene Climatic Optimum (HCO) runs from 10500 BP to 4500 BP and has numerous peaks between 0.35°C and 0.48°C. Figure 3B is similar, with a slightly larger temperature range. The average temperature difference then, in these reconstructions, is between 1.2°C and 1.4°C. This compares well to the geological and biological evidence presented in Javier, 2017.

A word about error

There are many sources of potential error in these reconstructions. In this series of posts, we have emphasized those sources we thought were most important and significant. Specifically, we focused on the geographic distribution of the proxies, proxy selection, the choice of the mean used to generate the temperature anomalies, the effects of proxy dropout, proxy resolution, and the impact of local conditions on the proxies. The latter problem relates to how applicable the proxy is to regional climate as opposed to local climate. Examples of inappropriate proxies due to local conditions are TN057-17 and ODP-658C which are discussed in part 2.

Dating the proxy samples can be problematic. Marcott, et al. (2013) emphasize potential dating errors in their paper and supplementary materials. They consider dating errors to be the largest source of error. Marcott, et al. (2013) also provide a very detailed discussion of proxy-to-temperature calibration uncertainty in their supplementary materials. Generally, they assume one standard deviation (normally distributed) to be the error inherent in the proxy-to-temperature conversion, otherwise they follow the proxy author’s recommendations.

Marcott, et al. assumed a fundamental dating error of 120 to 150 years for most cases and accounted for it using a Monte Carlo procedure (1,000 realizations) which is detailed in their supplementary materials. For the layer counted Antarctic ice-core records they assumed a ±2% uncertainty and for Greenland cores they assumed a ±1% error. All radiocarbon dates were recalibrated using IntCal09. Our reconstructions use the original published dates and not the recalibrated dates.

Dating errors and proxy-to-temperature errors are undoubtedly important and Marcott et al. (2013) provide a good discussion of these problems and their supplementary database contains estimates for these sources of uncertainty. They also considered that some of the proxies may have a seasonal bias and attempted to account for this source of error in their Monte Carlo procedure. They do not believe that seasonal bias is an important source of error. We have nothing to add to their work on these uncertainties and the interested reader is referred to their paper. They do present an interesting figure in their supplementary materials displaying the 1,000 Monte Carlo realizations that result from their study of error due to dating and proxy-to-temperature conversion. It suggests that error due to these factors is roughly ±0.5°C. We show their figure as our figure 5:

Figure 5 (Source: Marcott, et al., 2013 supplementary material)

Marcott, et al. (2013) also provide their own latitudinal temperature reconstructions and display them in their supplementary figure S10, not reproduced here. Their regional reconstructions are different in detail than ours because they use more proxies, but their 30°N to 60°N reconstruction for the Holocene is the same big outlier we see in our figures 1A and 1B. They also note, as others have, that computer simulations of Holocene climate do not agree with the proxy reconstructions, the so-called Holocene temperature conundrum. The largest difference between the simulation results and the proxy reconstructions occurs in the mid-high latitude Northern Hemisphere, which suggests that the models are missing some key component of Northern Hemisphere climate. They suggest that the models may not be modeling north Atlantic Ocean circulation properly, we agree. The global climate models also have other problems, for a discussion see here.

We believe the greater source of error in these reconstructions is in the proxy selection. As documented in this series, some of the original 73 proxies are affected by resolution issues that hide significant climatic events and some are affected by local conditions that have no regional or global significance. Others cover short time spans that do not cover the two most important climatic features of the Holocene, the Little Ice Age and the Holocene Climatic Optimum.

Conclusions

We’ve tried to address the criticism of the Marcott et al. (2013) global temperature reconstruction. Steve McIntyre, Grant Foster and others contested their adjustments of the published proxy dates, their inclusion of some inconsistent proxies, and not compensating very well for proxy drop out. Javier has pointed out that their proxy reconstruction does not reflect abundant geological and biological evidence that the average sea surface temperatures were at least one degree Celsius warmer during the Holocene Climatic Optimum than during the Little Ice Age. In addition, the use of proxies that do not cover the interval from the LIA to the HCO is problematic since these are the two best defined temperature extremes in the period. Further, we are using temperature anomalies from the mean to build these reconstructions and prefer to get the mean from the period 9000 BP to 500BP so that the mean represents both the high temperatures of HCO and low temperatures of the LIA. This is not possible if the proxy does not cover this interval.

We also avoided proxies with long sample intervals (greater than 130 years) because they tend to reduce the resolution of the reconstruction and they dampen (“average out”) important details. The smallest climate cycle is roughly 61 to 64 years, the so-called “stadium wave,” and we want to try and get close to seeing its influence. In this simple reconstruction, we have tried to address these issues.

The reconstructions show a difference of 1.2°C to 1.4°C between the LIA and the HCO. This suggests that the underlying data support this temperature difference. These reconstructions also show more detail. The additional detail appears to correspond to known climatic events. While the LIA, HCO, Roman Warm Period, Minoan Warm Period and other historical events show up well in the reconstructions, the Medieval Warm Period does not, it appears dampened and offset in time from historical records. The reasons for this are unclear. As discussed in part 3, some Northern Hemisphere proxies show an MWP and some do not. The proxies may be wrong or perhaps the MWP occurred in different times or in different intensity in different places, smearing it on a global reconstruction. Either way proxy choice determines the MWP intensity and timing, which is disappointing. More work and better proxies are needed to improve our Holocene temperature record.

An accurate Holocene temperature reconstruction is not possible, even measuring the potential error in a reconstruction this long is incredibly difficult. Marcott, et al. (2013) did a good job of estimating dating error and proxy-to-temperature error, in our opinion. But, they do not address the other issues, such as proxy selection, that may be more important. But, even without a viable error calculation, a generally accepted estimate of Holocene temperature trends is greatly desired. To understand the present, we must know the past. This is a very simple reconstruction and it is not meant to be definitive, but we present it as a starting point for future work. It is a presentation of the data and some useful tools needed to work the data.

To improve the reconstruction, I think we need to compare it and the component proxies to other data. In particular, historical records, archeological records, glacial advance histories, biological and geological data. This “outside data” can be used to select proxies and guide the reconstruction.

The R code to map the proxy locations, the references and metadata for the proxies, and the global reconstruction spreadsheet can be downloaded here.

I am very grateful to Javier who has read this post and made many very helpful suggestions. Any errors are the author’s alone.

A Holocene Temperature Reconstruction Part 3: The NH and Arctic

By Andy May

In the last post (see here) we reexamined the Marcott, et al. (2013) proxies for the Southern Hemisphere mid-latitudes and the tropics. In this post, we will present two more reconstructions using their proxies, these are for the Northern Hemisphere mid-latitudes (30°N to 60°N) and for the Arctic region (60°N to 90°N). These two regions contain over half of the proxies used in this study. The next post will present a global area-weighted composite temperature reconstruction. As we did in the previous two posts, we will examine each proxy and reject any that have an average time step greater than 130 years or if it does not cover at least part of the Little Ice Age (LIA) and the Holocene Climatic Optimum (HCO). We are looking for coverage from 9000 BP to 500 BP or very close to these values. Only simple statistical techniques that are easy to explain will be used.

Northern hemisphere mid-latitudes

There are 10 proxies that meet our basic criteria for the Northern Hemisphere reconstruction, although two of them are combined into one record. The final reconstruction is shown in figure 1. Figure 1A includes all proxies that meet our basic criteria, figure 1B excludes two anomalous proxies and trims the early data from two more to avoid spikes caused by proxy drop out. The R code, input and output datasets can be downloaded here.

Figure 1A, all proxies that meet the basic criteria (resolution and span)

Figure 1B, excludes KY07-04-01 and OCE326-GGC26

If all proxies are included, as in figure 1A, this reconstruction shows a very flat Holocene Climatic Optimum (HCO) from 10000 BP to 6800 BP and then a steady decline in temperatures to the Little Ice Age (LIA) around 240 years ago (180 BP or about 1770 AD). The range of Holocene temperatures in both reconstructions is 4°C, this is the largest range of any region, including the Arctic. We generally prefer the reconstruction in figure 1B and will discuss the features of this reconstruction here. Since the temperature change in this reconstruction exceeds that seen in the Antarctic and Arctic reconstructions, it calls into question the concept of “Polar Amplification.” We cannot say polar amplification does not exist, but we do not see evidence of it in these proxies. Excluding the two anomalous proxies the coldest portion of the LIA was around 1610 AD.

The 17th and 18th centuries were a time of intense cold weather in Europe, Asia and North America, these centuries were the worst part of the LIA. The early 18th century saw lakes freeze solid in Italy and ice skating took place in Venice. Ships were frozen into ice in New England in 1740. More stories of the severe cold in the Northern Hemisphere in the 18th century can be seen here. The 17th century, if anything, was worse. The 17th century revolutions, droughts, famines, wars and other calamities are detailed in Geoffrey Parker’s book Global Crisis.

In Parker’s book, we see historical records of unusually cold and devastating winters that occurred in Europe and the Middle East in 1620, the United States between 1640 and 1644, China in 1640, Hungary between 1638 and 1641. 1641 remains the coldest year ever in Scandinavia. In the Balkans, in 1654, wine and olive oil froze in jars. In Egypt, in the 1670’s, a country where furs were unknown, was so cold that the citizens started wearing fur coats. Crop yields plunged in Guangxi and Guangdong (Hong Kong area) in southern China due to very cold weather in 1633 and 1634. Icebergs floated down the Thames River in January of 1649 as Charles Stuart was beheaded. In 1698 it was reported, in London, by John Evelyn that the weather was colder than anyone could remember. Harvests failed in Scotland every year between 1688 and 1698 mainly due to cold. And the stories go on and on.

The highest Medieval Warm Period (MWP) peak is at 890 AD. The Medieval Warm Period is very tepid in this reconstruction. Some of the proxies show a bump near the historical MWP and some do not. Below are plots of each set, figure 2 is the set with a visible MWP and figure 3 is the set without.

The proxies with an apparent MWP in figure 2, reach their peaks at different times and they do not line up well, this spreads out the MWP in a reconstruction and dampens the amplitude. The only two that line up are Flarken Lake (Sweden) and D13822 (Portugal). The MWP peak in the MD01-2421 composite from Japan occurs a little later it does in the Newfoundland proxy OCE326-GGC26. MD95-2015 (southwest of Iceland) is a very anomalous proxy with peaks at 1110 AD and 760 AD. In short, in this reconstruction, while it appears the LIA is well defined, the MWP is not. The historical warming from around 760 AD to 1200 AD shows up in these proxies, but not as a single well-defined event.

Figure 2

The Northern Hemisphere proxies in figure 3 do not have a noticeable temperature anomaly in the MWP. KY07-04-01 is in the East China Sea, south of Japan. CH07-98-GGC19 is off the US east coast near Washington, DC; it shows a minor bump around 1060 AD to 900 AD. OCE326-GGC30 is near Nova Scotia, Canada; it shows no response at all. The IOW merged dataset is from the Baltic Sea near Sweden and it also shows no MWP response. These proxies run counter to historical records for this time period.

Figure 3

The Roman Warm Period peak is at 90 BC (figures 1A and 1B) and very noticeable in the reconstruction. So, we see the LIA and the Roman Warm Period here, but the MWP not so clearly. This could be because the proxies are erroneous or because the MWP occurred at different times in different areas and was dampened by averaging. The MWP exists, it is a matter of historical record, but it does not show up well in these proxies.

All nine proxy records are shown in figure 4A.

Figure 4A, all proxies

Figure 4B, proxies used

The anomalous records in figure 4A are OCE326-GGC26 (Sachs 2007, near Newfoundland), KY07-04-01 (Kubota et al., 2010, just south of Japan) and Flarken Lake (Seppa et al., 2005, in Sweden). Flarken Lake is probably being affected by meltwater from glaciers that remained in the area long after the last glacial maximum. The retreating ice delayed the Holocene Climatic Optimum in many northern areas (Bender, 2013). We do not think Flarken Lake was a problem and retained the proxy.

OCE326-GGC26

This proxy is just south of Newfoundland and near the Grand Banks. See the location map in figure 5. This proxy record is plotted alongside its neighbor, OCE326-30GGC, in figure 6. Both proxies agree well from 8000 BP to 0 BP, then OCE326-GGC30 flattens out like most of the Northern Hemisphere proxies and OCE326-GGC26 makes a large jump in temperature ending with a 7°C anomaly 11410 BP. This proxy is problematic and was excluded from the reconstruction.

Figure 5 (source: Sachs, 2007)

Figure 6

KY07-04-01

This proxy was also excluded from the reconstruction for being anomalous. The core is from the East China Sea near the southern tip of Japan. See the map in figure 7.

Figure 7 (Source: Kubota, et al., 2010)

Figure 8

The KY07-04-01 proxy is plotted in figure 8. The proxy is very flat from the present day to 10000 BP, with minor fluctuations up and down. This is a Mg/Ca proxy and the core is located near the mouth of the Changjiang (or Yangtze) River. This river is the largest in China, and has its mouth north of Shanghai. The water here is a varying mixture of fresh water from the river and sea water from the East China Sea. The composition of the water varies with monsoon intensity. The river discharge has also varied during the Holocene as inland glaciers melted. Finally, as noted in Kubota, et al. (2010), this temperature proxy does not compare well with other proxies in the area. The other proxies show normal cooling during the Holocene, see the lower portion of figure 9, which is taken from Kubota, et al., 2010. We chose to exclude this proxy from the reconstruction.

Figure 9 (source: Kubota, et al., 2010)

A map of all the Northern Hemisphere proxy locations can be seen in figure 10. For this region, we have a widespread set of proxies.

Figure 10

The Northern Hemisphere proxies represent a larger range of temperatures and a larger range of temperature anomalies than the other regions. For this reason, proxy drop out at the beginning of the proxy records, about 12000 BP, causes larger than normal temperature fluctuations. This is easily seen in figure 4A between 12000 BP and 10000 BP. Even after excluding KY07-04-01 and OCE326-GGC26, unrealistic fluctuations appeared as proxies ended in the early time and dropped out. To avoid this, we deleted the earliest 3 samples of OCE326-GGC30 and the earliest 20 samples of CH07-98-GGC19. By comparing the right side of figures 4A and 4B you can see what was eliminated.

Proxy drop out at both ends of the reconstructions is a problem. We are using anomalies from the mean for these reconstructions which helps, since the anomalies tend to have similar ranges. But, in the case of the Northern Hemisphere, even the anomalies have widely different values and depending upon the order in which they drop out, they can cause strange spikes at the beginning and the end of each reconstruction. The earliest few values and the last few values for the Northern Hemisphere proxies are shown in figure 11 as an example.

Figure 11

At 0 BP (1950 AD, the upper panel) we have no values for four of the proxies, “NA” means no value. The three remaining proxies have values of -1.698, -3.422, and -2.323, that average to -2.481. At -20 BP (1970) we only have two values as GGC30A has dropped out, so the average is a very different -1.86. Compare this to the situation at very early time where the MD012421 proxy is about -5.5 and the GGC30 proxy is 1.84 and you can see the problem with drop out in the Northern Hemisphere. This problem is much less pronounced in the other regions which show less variability. We only trimmed excessive values like this in the Northern Hemisphere.

Arctic reconstruction

The Arctic reconstruction is shown in figure 11. The R code and input and output datasets can be downloaded here.

Figure 11

The lowest point in the LIA in this reconstruction, occurs at 1850 AD. There is no well-defined Medieval Warm Period, but there are peaks at 850 AD and 1070 AD. The Roman Warm Period is seen from 270 BC to 50 BC. Figure 12 plots the nine component proxies.

Figure 12

A map showing the proxy locations is presented in figure 13. The proxies are all in the north Atlantic area, but widespread.

Figure 13

Only JR51GC-35 and GIK23258-2 look a little anomalous, but not severely so. GIK23258-2 (Sarnthein, et al., 2003) is the most northerly proxy with a latitude of 75°N. This may explain the slightly anomalous warm anomalies at about 9000 BP and between 2500 BP and 1000 BP. The Iceland proxy JR51GC-35 is quite spiky. The location of the JR51GC-35 is shown in figure 14. It is in an area where multiple currents can influence the temperature quite dramatically, which probably explains the spiky nature of the curve.

Figure 14

Conclusions

These regions have the most data and are probably well represented by the proxies. The Northern Hemisphere mid-latitude reconstruction is quite different from the other regions. Most of the regions show a Holocene temperature variability of ±1°C whereas the Northern hemisphere reconstruction shows a temperature variability of ±4°C.

Considering the abundant historical evidence from the Northern Hemisphere for the Medieval Warm Period, it is odd that this climatic event does not show up well in the Northern Hemisphere reconstruction. It is possible that this warming event took place in different areas at different times and this smeared and dampened the record. The variation in the Northern Hemisphere proxies suggests that the climatic history of the Northern Hemisphere was very complex during the Holocene, relative to the other regions.

We see no evidence of polar amplification in these reconstructions. The Northern Hemisphere mid-latitudes shows a larger range of temperatures than either the Arctic or the Antarctic.

The Northern Hemisphere reconstruction illustrates the problem with proxy selection and with temperature proxies in general. Proxies are not thermometers, they do not measure temperature directly. They react to temperature in the present day in a certain way and we assume they react in the same way in the distant past. How accurate are the temperature estimates? Further, we assume that burial and time have had no effect, or a predictable effect on the quantities measured. We assume that we have measured the age and depth or height of each sample accurately. Finally, we assume that each proxy represents the surface temperature of a very large area with no local distortions. So, how do we choose which proxies to include and which to reject? Our basic requirements of a span of 9000 BP to 500 BP and a resolution better than 130 years are reasonable. Was it reasonable to reject KY07-04-01 and OCE326-GGC26? Perhaps, but it is hard to tell, the decision was mostly subjective.

In the next post, we will present a global reconstruction. We will also discuss the various sources of error in the proxies.

The R code and input and output datasets for the Arctic reconstruction can be downloaded here.

I am very grateful to Javier who has read this post and made many very helpful suggestions. Any errors are the author’s alone.

A Holocene Temperature Reconstruction Part 2: More reconstructions

By Andy May

In the last post (see here) we introduced a new Holocene temperature reconstruction for Antarctica using some of the Marcott, et al. (2013) proxies. In this post, we will present two more reconstructions, one for the Southern Hemisphere mid-latitudes (60°S to 30°S) and another for the tropics (30°S to 30°N). The next post will present the Northern Hemisphere mid-latitudes (30°N to 60°N) and the Arctic (60°N to the North Pole). As we did for the Antarctic, we will examine each proxy and reject any that have an average time step greater than 130 years or if it does not cover at least part of the Little Ice Age (LIA) and the Holocene Climatic Optimum (HCO). We are looking for coverage from 9000 BP to 500 BP or very close to these values. Only simple statistical techniques that are easy to explain will be used.

Southern Hemisphere mid-latitudes

Our reconstruction for this region is shown in figure 1. The R code and the input and output datasets for the Southern Hemisphere mid-latitudes can be downloaded here.

Figure 1

This reconstruction has a more defined HCO than we saw in the Antarctic and it is placed between 8000 BP and 5000 BP. The HCO occurs at different times in different places as discussed by Renssen, et al. (2012). Following this, the temperature generally drops to a low in the LIA. In this reconstruction, we see two LIA lows, one at 1690 AD and one at 1550 AD. The Medieval Warm Period (peak 1030 AD) and the Roman Warm Period (peak 90 BC) are very distinct in this reconstruction. The Minoan Warm Period (peak 1890 BC) can also be seen.

There are only four proxies in this reconstruction, three in New Zealand and one off the coast of Chile. The locations are shown in figure 2.

Figure 2

Two of the proxies have been combined into one record, the three proxies used are plotted in figure 3.

Figure 3

Three proxies were rejected due to large sample intervals, TN057-17 (Nielsen, et al., 2004) was rejected because it was very anomalous. See the plot in figure 4.

Figure 4

TN057-17 is a sea surface temperature proxy located in the Southern Ocean, right on the Antarctic Polar Front (APF), see Figure 5. The APF has a very abrupt sea surface temperature change. It is the southern limit of synchrony with the Northern Hemisphere climate system. This location, currently, has sea ice cover about two weeks per year (Nielsen, et al., 2004) but the time of ice cover has changed a lot during the Holocene and this has probably had a dramatic effect on the proxy. The maximum sea ice cover was 4300 BP, which is also the time of the lowest TN057-17 temperature.

Figure 5, source (Nielsen, et al., 2004)

Sea ice presence (SIP) at the TN057-17 location is shown in figure 6.

Figure 6, Sea ice presence (SIP) at TN057-17 (Source: Nielsen, et al., 2004)

There is a risk that the TN057-17 proxy has been affected by local conditions that are only vaguely connected to climate change and for this reason the proxy was rejected.

The Chilean GeoB 3313-1 proxy (Lamy et al., 2002) only went back to 7000 BP and for this reason would be rejected on its own. But, the New Zealand proxy MD97-2121 (Pahnke and Sachs, et al., 2006) has nearly the same latitude and is continuous from 12464 BP to 3316 BP. So, these two proxies were merged by adjusting them to the mean of the overlapping interval 6900 BP to 4000 BP. See figure 7.

Figure 7

The logic in combining these two proxies is it gives us one more proxy in a region that has few available and, at least part of this composite is outside the New Zealand area. The most recent portion of MD97-2121 (4000 BP to 3300 BP) was not used in the composite as it looked suspicious. Pahnke and Sacks (2006) report that the MD97-2121 core top (the most recent sediments in the core) may be problematic due to lack of recent sediments at the cored location. In any case, a 3000-year-old core top, presumably close to the sea floor, has probably been churned quite a bit and should be greeted with suspicion. Older than 4000 BP, the results are consistent with GeoB-3313-1.

Tropics

The reconstruction for the tropics (30°S to 30°N) is shown in figure 8. The ODP-658C proxy is problematic, so we present a reconstruction including it in figure 8A and one without it in figure 8B. The R code and the input and output datasets for the tropics can be downloaded here.

Figure 8A, with the ODP-658C proxy

Figure 8B, without the ODP-658C proxy

There is a very distinct LIA at 1630 AD. The two peaks around the classical MWP are 1090AD and 930 AD. The Roman Warm Period (90 BC) and the Minoan Warm Period are apparent. In this reconstruction, the HCO is from 9600 BP to 7700 BP.

There are eight usable proxies in the tropics using our criteria, they are plotted in figure 9.

Figure 9

The location of the proxies is shown in figure 10, there are quite a few in Indonesia so we did not put arrows on the figure for each one. One of the Indonesian proxies, Ros_BJ813GGC, is not a Marcott et al. (2013) proxy. It is from Rosenthal, et al. 2013.

Figure 10

The rejected proxies, except for ODP-658C, were all because of resolution or because they did not cover the period from the Holocene Climatic Optimum to the Little Ice Age. ODP-658C (deMenocal et al., 2000) is the brown line in figure 9. It is located off West Africa, the northern most arrow off West Africa in figure 10. The proxy is plotted in figure 11. This proxy was left out of the final reconstruction, but figure 8A shows a reconstruction that includes it.

Figure 11

The sharp break in the proxy at 5700 BP appears to be a data problem until we consider that this is the end of the African humid period when the Sahara turned into a desert due to the abrupt movement of the Intertropical Convergence Zone or “ITCZ” (deMenocal et al. 2000 and Javier, 2017). Figure 12 shows the worldwide change that took place around 5700 BP, it is from Javier’s essay here. This change in the location of the climatic equator (ITCZ) is often called the Mid-Holocene Transition when the world goes from the Holocene Climatic Optimum (HCO) period to the Neoglacial period. This data suggests that the Mid-Holocene Transition, in this area, occurred in less than 120 years between 5808 BP and 5683 BP using the dates given by deMenocal, et al. This is how long it took for sea surface temperatures at the ODP-658C location to increase over 2°C. The core location is shown in figure 12 with a red star. Around 5700 BP the ITCZ migrated from north of this location to south of it.

Figure 12 (Source: Javier, here)

The proxy temperature record labeled 17940 (Pelejero, et al., 1999) from the South China Sea could also be considered slightly anomalous since in the Neoglacial period it trends warmer, rather than cooler. It also shows no Holocene Climatic Optimum. The proxy is displayed below in figure 13.

Figure 13

The South China Sea is a very large marginal basin in the western Pacific. It is bounded by broad shallow shelves in the northwest and southwest that emerge during periods of low sea level. Sea level was low enough during the early Holocene for these shelves to be emergent. The position of the shelves can be seen by following the 100-meter isobath (water depth) contour in the map in figure 14. In addition, core 17940 is only 400 km from the mouth of the Pearl River, the second largest river in China. Due to the large sediment discharge from the river the location has a very high sedimentation rate, further it was larger in the past as the glaciers retreated to their present position and sea level was lower. We kept the proxy in the reconstruction, but recognize that it is sensitive to the changes in sea level experienced during the Holocene and to changes in the discharge rate from the Pearl River. The sea surface temperatures of the other cores in the South China Sea are similar.

Figure 14 (Source: Pelejero, et al. 1999)

In the next post, we will discuss the Northern Hemisphere Holocene proxies and the Arctic proxies. The supplementary materials for the tropics reconstruction can be downloaded here.

Conclusions

The Southern Hemisphere mid-latitude reconstruction is built from very little data. The data is mostly in the New Zealand area and cannot be considered representative of the whole region. But, we work with what we have.

The tropics reconstruction is built from widely dispersed proxies that sample all major ocean basins. It is probably representative of the region. The reconstruction without the anomalous ODP-658C proxy is probably the best to use. The Mid-Holocene Transition is a real event, but probably had no global temperature effect. It is merely a shift in the climatic equator or the Intertropical Convergence Zone or “ITCZ.” The ODP-658C location warmed dramatically 5700 BP, but presumably another location, that is not sampled, cooled as dramatically. Including the warming at the ODP-658C site, without the cooling elsewhere distorts the regional and global picture. Therefore, we excluded the proxy.

I am very grateful to Javier who has read this post and made many very helpful suggestions. Any errors are the author’s alone.

Thermodynamics and the greenhouse effect

There is an exciting new post on notrickszone.com here, that discusses a new paper on thermodynamics and the greenhouse effect.  In addition to Gerlich and Tscheuschner and the new paper Hertzberg, et al. (2017), the recent paper Kramm and Dlugi (2011) is interesting.

Yes, indeed, all objects radiate energy if their temperature is above absolute zero.  No question about it.  But, if you place an object that is radiating at 101 degrees C next to an object radiating at 100 degrees C, they will both soon be radiating at 101 degrees C, not 201 degrees C.  A cooler object cannot warm a warmer object, it does not happen, sorry.  The second law of thermodynamics does apply.

“Thermodynamics is a funny subject. The first time you go through it, you don’t understand it at all. The second time you go through it, you think you understand it, except for one or two small points. The third time you go through it, you know you don’t understand it, but by that time you are so used to it, it doesn’t bother you any more. (Physicist Arnold Sommerfeld (1868-1951))”

A Holocene Temperature Reconstruction Part 1: the Antarctic

By Andy May

The only recent attempt at a global Holocene temperature reconstruction available today is the one by Marcott, et al. (2013), the paper abstract can be viewed here. His reconstruction is shown in figure 1.

Figure 1

The Y axis is a reconstructed global temperature anomaly from the 1961-1990 mean. “Years BP” are years before 1950. This reconstruction shows a fairly flat Holocene Climatic Optimum (or HCO, also called the Holocene Thermal Optimum, see description here) temperature anomaly of +0.4°C from 9500 BP to 5000 BP, declining to a low of -0.4°C about 300 BP (1650 AD) in the Little Ice Age (LIA). This 0.8°C difference between the HCO and the LIA is smaller than the generally accepted difference of 1°C to 1.5°C. This is documented in some detail by Javier here. The higher accepted difference is clear in glacial records as shown by Koch, et al., 2014 (link). It can also be seen in the biosphere as shown by Kullman 2001 (link); Pisaric et al. 2003 (link); MacDonald et al. 2000 (link); Tinner, et al. 1996 (link) and Thouret et al. 1996 (link)). Further, the marine biosphere also shows a larger temperature difference as seen in Werne et al., 2000 (link) and Rosenthal et al., 2013 (link).

The reconstruction in figure 1 goes from the present (1950) on the left to nearly the beginning of the Holocene about 11,700 years ago on the right. The Holocene is normally defined as “…the first signs of climatic warming at the end of the Younger Dryas/Greenland Stadial 1 cold phase…” (Walker et al. 2009). It is often considered a geological epoch or series. It is part of the Quaternary geological period and is equivalent to the older geological term “Recent.”

The reconstruction shows an abrupt warming in the last 100 years (see the left side of figure 1). This single point at 1940 AD is due to proxy drop out, proxy inconsistencies and the authors changing some published dates in the proxies according to Steve McIntyre at climateaudit.com here, here and here. Also see “The Tick” by Grant Foster here for more discussion, the first comment to “The Tick” is by our own Nick Stokes. Even Marcott has acknowledged that his reconstruction from 1890 AD onward is not robust. The following quote is by Marcott, here.

“We showed that no temperature variability is preserved in our reconstruction at cycles shorter than 300 years, 50% is preserved at 1000-year time scales, and nearly all is preserved at 2000-year periods and longer. Our Monte-Carlo analysis accounts for these sources of uncertainty to yield a robust (albeit smoothed) global record. Any small “upticks” or “downticks” in temperature that last less than several hundred years in our compilation of paleoclimate data are probably not robust, as stated in the paper.”

The problem is that 300 years is a very long time. As we will see, many very significant climatic events begin and end in less than 300 years. Marcott et al. (2013) chose too many proxies with poor temporal resolution, which reduced the resolution of their reconstruction to the point that significant details were lost.

This is a new look at Marcott’s proxies. It is a good collection and most of them are marine sea surface temperature proxies. This is a good thing because most of the heat energy or heat capacity on the Earth’s surface is in the oceans. In fact, over 99.9% of the surface heat content is in the oceans and only 0.071% is in the atmosphere, for the details of this calculation see the spreadsheet here. Warming of the atmosphere is not particularly significant on a climatic scale.

It is very logical to investigate long term climate changes using ocean temperature proxies from foraminifera shells and fossils (“forams”), planktonic and algal material. Traditionally the magnesium and calcite (Mg/Ca) percentages or δ18O ratios in planktonic foraminifera have been used to deduce ancient sea surface temperatures. On land, ice core δ18O records and pollen are used to estimate ancient air temperatures. More recently we have seen more use of haptophyte algal alkenones, especially the U37K’ (also written as UK’37) index to get ancient sea surface temperatures, see the link here. TEX86 records from marine plankton have also been used recently to obtain sea surface temperatures and are among Marcott’s proxies, see here for a discussion. The original reference for the TEX86 sea surface temperature proxy is Schouten, et al. (2002) here. A complete list of the proxies used by Marcott, plus one I added from Rosenthal, et al. (2013) and references and links to the original papers can be downloaded here. I did not use all Marcott’s proxies in my reconstructions, those that I did use are noted in the spreadsheet.

Proxy selection

The proxies were examined considering the criticism of Marcott’s analysis by Javier, McIntyre and Foster. The 500-meter depth Indonesian ocean proxy presented in Rosenthal, et al. 2013 was added to the list. Proxies used in this reconstruction were selected using the following criteria:

  1. The span of the proxy reconstruction had to cover at least 600 BP to 8000 BP so the proxy covered part of the LIA and the HCO.
  2. The resolution (time between samples) had to be less than 130 years.
  3. Complex statistical techniques were avoided as much as possible.

The major climatic events of the Holocene are the Holocene Climatic Optimum (HCO) and the Little Ice Age (LIA), these events represent the maximum global average temperature and the minimum temperature respectively in this period. As noted above, there is abundant evidence that the global temperature difference between these two points exceeds one degree Celsius. Therefore, it seems logical to make sure the proxies cover both events. Further, since all the reconstructions are temperature anomalies, we have built the anomalies as differences from the proxy mean between 9000 BP and 500 BP.

There is concern that the reason the Marcott, et al. (2013) reconstruction is underestimating the LIA to HCO temperature difference is that they included too many proxies with very long sample intervals. Proxies with long sample intervals miss essential detail and smooth and dampen detail in any reconstruction. Just averaging too many proxies can dampened detail if there is error in the proxy dates.

Climate changes over the Holocene occur, in large part, by latitude. This is due to the Earth’s orbital obliquity (amount of axial tilt which changes over a 41,000-year cycle) and precession (wobbling of the axis over 19,000 to 23,000 years) cycles, as well as the long-term transport of heat by ocean currents. This is explained well by Javier here. In the same post, Javier explains the orbital effects in this way:

“Changes due to obliquity have the effect of redistributing insolation between different latitudes following an obliquity cycle of 41,000 years. When obliquity was maximal 9,500 years ago, both poles received more insolation due to obliquity, while the tropics received less. Obliquity also affects seasonality, at maximal axial tilt, there is an increased difference between summer and winter at high latitudes. But unlike precession changes, obliquity alters the amount of annual insolation at different latitudes in a 41,000-year cycle. This is represented by the background color of figure 34, that shows how the polar regions received increasing insolation from 30,000 yr BP to 9,500 yr BP. Since then, and for the next 11,500 years, the poles will be receiving decreasing insolation. Unlike precessional insolation changes, obliquity changes are symmetrical. Although the annual insolation change is not too large, it accumulates over tens of thousands of years and the total change is staggering, creating a huge insolation deficit or surplus. This changes the equator-to-pole temperature gradient, and is largely responsible for entering and exiting glacial periods (Tzedakis et al., 2017) and for the general evolution of global temperatures and climate during the Holocene.”

The emphasis is in the original post. Javier’s figure 34 is presented below as our figure 2.

Figure 2

Javier’s description of this figure, in part:

Figure 34 [our figure 2]. Insolation changes due to orbital variations of the Earth. The insolation changes for the last 40,000 years are represented. Black temperature proxy curve represents δ18O isotope changes from NGRIP Greenland ice core (without scale). The insolation curves are presented as the insolation anomaly for summer, winter, spring, and fall. N (red) or S (blue) are the Northern or Southern Hemisphere and the three letters are the month initials. Northern and southern summer insolation represented with thick curves. Background color represents changes in annual insolation by latitude and time due to changes in the Earth’s axial tilt (obliquity), shown in a colored scale. … changes in obliquity … are symmetrical for both poles. Changes … caused by the precession cycle (modified by eccentricity) are asymmetric and less important for the global response, although they cause profound changes in regional climatic differences. The Holocene Climatic Optimum corresponds to high insolation surplus in polar latitudes (red area), while Neoglacial conditions represent the first 5,000 years of a 10,000 year drop into a high glacial insolation deficit in polar latitudes (blue area).”

Since latitude has such a large influence on climate and climate changes, we will produce reconstructions in 30° regions of latitude. The Antarctic region, with latitudes from 90°S to 60°S is presented first in this post. In the next post, we will present reconstructions for the southern hemisphere mid-latitudes (60°S to 30°S) and for the tropics (30°S to 30°N). The northern hemisphere mid-latitudes and the Arctic will follow in part 3. Our final global reconstruction will be a combination of these. It is presented in part 4.

The Marcott, et al. (2013) reconstruction is based upon 5° by 5° global grid created using their proxies. Gridding data is an accepted way of spreading unevenly spaced data evenly over a map, but it can cause distortions. The distortions can occur due to isolated, but extreme values or because the values gridded are incompatible, or simply because of data clustering, that is many values in one part of the map, see an example here. Table 1 shows the distribution of the proxies used in this series.

Table 1

The Marcott, et al. (2013) proxies are much more numerous in the northern hemisphere than in the south, so for this reason, we chose not to grid the data, but instead create five simple latitude bounded regional reconstructions and merge them. A great effort was made to make the process used as simple as possible and completely reproducible. All calculations were done with R, a statistical software package that is available for free (see here). As you can see in table 1, only 19% of the proxies that meet our criteria fall in the southern hemisphere below 30°S, which is 25% of the Earth. The same 25% area in the northern hemisphere contains 56% of the proxies. We hope that using our method will reduce any distortion introduced by the proxy distribution.

All R code and the R input and output text files will be made available in the supplementary materials for each post. We also provide spreadsheets containing metadata, references and plots of the original proxy temperatures. No error analysis has been done on these reconstructions, but this should be done. Readers are encouraged to use my code and data to do their own error analysis. Ideas on how to separate the various error components, such as dating error, proxy error, geographic error, depth or altitude error, etc. are welcomed. One thing that complicates the computation of error, is that in some cases different proxies were used for the same core (see 74KL, in the Arabian Sea, by Huguet et al., 2006) and the resulting reconstructions were different. This could be due to seasonal differences, depth or altitude differences or due to local weather variability (Huguet, et al. 2006). In all cases I used the original published dates, no adjustments have been made except to align them to a 1950 reference which is the standard reference for “BP.”

The Antarctic reconstruction

The final Antarctic reconstruction is shown in figure 3. The curve is the anomaly from the 9000BP to 500 BP mean.

Figure 3

In the Antarctic reconstruction, we appear to see a slight Little Ice Age drop at 1230 AD. There are several peaks in the Medieval Warm Period from 1110 AD to 890 AD, but nothing very dramatic.

Marcott, et al. (2013) had four temperature proxies below 60°S. We selected three from this set, Vostok, Dome C and EDML. The proxy details and metadata are in the supplementary spreadsheet “Reconstruction_References.xlsx” which can be downloaded here. Dome F was rejected due to a 500-year resolution. These are all ice core proxies that estimate air temperature. A map of the proxies (see figure 4) shows that all are in East Antarctica.

Figure 4

Figure 5 shows the three proxies used in the reconstruction. All of the proxies are anomalies from the 500BP to 9000 BP mean.

Figure 5

The three proxies generally agree with one another and the reconstruction, with minor suspicious looking differences such as the spike in the Vostok record at 8200 BP.

After reading the proxies into R, a matrix of reconstructed temperatures was created with a regular spacing of 20 years from -60 BP (2010) to 11980 BP (10,030 BC). This matrix is then populated with the proxies, taking care to average multiple values if they are within 11 years of the matrix date. Gaps in each proxy are filled with a cubic spline function allowing a maximum gap of 11 samples or 220 years. No extrapolation at the ends of the vectors was allowed, this is to reduce the chance of spurious spikes at the end of the proxy records.

After filling gaps table 2 shows the beginning of the matrix:

Table 2

Most of Marcott’s proxies contain actual estimated temperatures, but these proxies are all anomalies. The R missing value code is “NA.” The anomalies are from different means. The zeros from 0 BP to 120 BP in the Vostok column look suspicious, but they are in the Pettit, et al. (1997) data. By 100 BP (1850 AD) we have data for all three cores. Dome C shows warming from 100 BP to 40 BP, so the uptick at the end of the reconstruction is due to two points in one core. Table 3 shows the end of the matrix.

Table 3

All three cores show rapid warming from 11900 BP to 11720 BP. Each of the three proxies are converted to new anomalies from their individual mean temperatures from 9000BP to 500 BP, this is to give them all the same chronological basis. Finally, the Antarctic region reconstruction is created by averaging the three anomalies. The result is figure 3. Figure 6 is the same reconstruction, but plotted by R with an overlain smoothed curve.

Figure 6

The graph shows Holocene climatic optima from 11000 BP to 9500 BP and 6000 BP to 3000 BP. The later period is slightly warmer than the earlier period which is very different from what is seen in the northern hemisphere and the other regions in this study. This result is similar to what has been reported by Masson, et al., 2000. Masson, et al. (2000) write:

“All the records confirm the widespread Antarctic early Holocene optimum between 11,500 and 9000 yr; in the Ross Sea sector, a secondary optimum is identified between 7000 and 5000 yr, whereas all eastern Antarctic sites show a late optimum between 6000 and 3000 yr.”

Unlike Masson, et al. (2000) we show the later optimum to be slightly warmer than the earlier one. But, the difference is only a few tenths of a degree and probably not significant. The choice of proxies can be critical when dealing with small differences in temperature. It is interesting to look at the variety of deuterium profiles presented by Masson, et al. (2000) in their figure 3, which is not reproduced here.

Likewise, the rapid warming out of the Younger Dryas seen in the northern hemisphere around 11500 BP appears to occur hundreds of years earlier in the Antarctic. It is also possible that there is no discernable Younger Dryas cooling in the southern hemisphere (Barrows, et al., 2007). Southern Ocean sea surface temperature reconstructions shown in Bostock, et al. (2013) (see their figure 3B, reproduced as our figure 7) show that the early temperature optimum in the Southern Ocean is quite variable. In some areas, it is at about 10000 BP and in others it is about 6000 BP. But, often the difference between the peaks is quite small and perhaps below the accuracy of the data.

Figure 7 (source Bostock et al., 2013)

Our proxies are all eastern Antarctic land air temperature proxies and they reach a much later peak, around 6000 BP to 3000 BP by a few tenths of a degree.

Conclusions

The Marcott, et al. 2013 worldwide reconstruction has its problems, but many of the proxies used in the reconstruction are quite good and very usable.

The Antarctic reconstruction created here is comparable to previous temperature reconstructions, especially those focusing on eastern Antarctica. It shows two climatic optima, one from 11500 BP to 9000 BP and another from 6000 BP to 3000 BP. In eastern Antarctica, using our proxies, the later optimum is warmer. But, in other areas the earlier optimum is warmer, however, the difference is small.

In following posts, I will create similar reconstructions for the Arctic, the southern and northern mid-latitudes and one for the tropics. These will be area weighted and merged into one proposed global reconstruction in the final post.

The R code used to create this reconstruction and the input and output datasets can be downloaded here. The list of proxies used for all six reconstructions, the original references and links can be downloaded here.

I am very grateful to Javier who has read this post and made many very helpful suggestions. Any errors are the author’s alone.

Lindzen, Soon and Spencer debunked?

By Andy May

On Bret Stephens facebook page, I complimented Mr. Stephens on what I thought was a very good column. I also noted that the eminent climate scientist Dr. Richard Lindzen had said similar things. To this a George Smith replied, in part, as follows:

“Few “skeptics” have been debunked as much as Lindzen and Spencer.”

Link to comment here.

If you follow the link you will see it is followed with a google search for “Lindzen debunked.” No support, no data, no peer reviewed references, just anything that says “Lindzen debunked.” This is “internet slime” at its worst. We see a lot of this sort of reprehensible behavior around climate science, often by people who have no scientific background at all. But, I am a scientist with 42 years’ experience and have been studying and writing about climate science for years, so I do want to address some of the scurrilous attacks found in this google search.

The first reference in my search led to desmogblog, here. This post is by an anonymous author who calls himself “climate nexus.” The climate nexus group, including Jeff Nesbit and Robert Tanner, does not include anyone with scientific training that I could find. They seem to be a team of professional writers and political hacks.

Their arguments appear to be as vacuous as their resumes. First they claim that climate models are accurate. This has been disproven by Dr. John Christy for the recent past and by Liu, et al. for the entire Holocene epoch. In the figure below (source Javier, here) proxy global average temperatures for the whole Holocene (last 11,500 years) are shown in black. Computer model temperatures calculated by Liu, et al. (2014) are shown in green, carbon dioxide and methane concentrations from ice cores are also shown. For the Neoglacial Period, temperatures go down, but the computer model temperatures go up, so does the carbon dioxide level. Quite obviously, for the Holocene, neither CO2 nor the computer models are predictive of temperature. This has been called the Holocene Temperature Conundrum.

Figure 1 (source here)

Below we see Dr. Christy’s graph comparing computer model temperatures with satellite and weather balloon measurements. I should mention that the satellite and weather balloon measurements are completely independent of one another and support each other:

Figure 2 (source here)

All of this “hottest year on record” nonsense is absurd, we are talking about very small changes in the average temperature. The surface temperature records are only accurate to +-0.2°C at best and almost all of the last 35 years of satellite and weather balloon data fit between -.2°C and +.2°C. The exceptions are the 1998 and 2015 El Ninos and a few other anomalies. Also, see the discussion of temperature accuracy by Lindzen here and especially his figure 1. See below:

Figure 3 (Data sources here and here)

There is a secular warming trend that has persisted since the end of the Little Ice Age in the 19th century. But the Little Ice Age was a very cold period where multiple solar and ocean cycles hit their lows all at once. This is a period of cold that is unlikely to occur again for a very long time, except in a major glacial episode. We should be grateful we are coming out of it. In the Little Ice Age the cold was devastating, glaciers advanced and destroyed villages. The Little Ice Age cold was blamed, in part, for plagues. The public at the time often blamed the cold on Jews and witches and murdered supposed witches by the tens of thousands because they thought the witches were controlling the climate and causing the cold, see the story here. The figure below is a 1486 woodcut of a supposed sorceress conjuring up a hailstorm. It is from Professor Wolfgang Behringer’s excellent book A Cultural History of Climate.

Figure 4, “Anthropogenic Climate Change” (source here)

Then, as now, the public chose to blame people for climate change without proof. We really have not advanced very far in the last 500 years.

For more details about the cause of the Little Ice Age, see the post by Javier here, especially the top frame of figure 6. We can easily see the minimums of the Eddy cycle and the Bray cycle occurring in the Little Ice Age, along with the Wolf, Sporer, Maunder and Dalton solar minima. Coming out of such a cold period we would expect dramatic natural warming.

Desmogblog posts the following comparison of supposed projections by Lindzen and Hansen to an unnamed observation record of global temperatures. Their reference is a blog post at Skeptical Science. Below is the graphic, showing the supposed “comparison.”

Figure 5, the misleading graph in Desmogblog here.

When we go to the source article at skepticalscience here, we find that Dr. Lindzen did not make any temperature predictions in 1989 or in any other year. The line shown above is the author’s (Dana Nuccitelli’s) interpretation of someone’s (Eugene Mallove’s) notes of a lecture given by Dr. Lindzen in 1989. We do not even have Dr. Lindzen’s own notes of the lecture! Below is the actual comparison of Hansen’s 1988 projections to the GISTEMP dataset of surface temperatures.

Figure 6 (source)

Ignore the Lindzen lines, they are made up. Hansen et al., 1988 provided three scenarios. His scenario A is way off, scenario B isn’t bad until the pause (see here) begins about 2000, then it overshoots actual temperatures by quite a bit. They stop the GISTEMP graph in 2008, so we don’t see how bad it actually gets. See figure 2 for a better picture against more accurate measurements. Scenario C is probably the best, but it is not a problem for mankind. Either way, the graph in DeSmogblog is misleading. I would accuse the team of scientific malpractice if they were scientists, but they are not.

They go on to say Lindzen’s Iris effect from tropical clouds has been debunked, which is nonsense. Lindzen’s idea (see here) is alive and well and the subject of vigorous debate, as are all good ideas in science. No one knows whether clouds are a net positive feedback or a net negative feedback on global temperatures, evidence goes both ways. For interesting discussions of clouds and their effects on climate see here and here. I favor Lindzen’s idea personally, as do many scientists, but others disagree. For more on this interesting idea see these posts by Judith Curry and Rud Istvan.  Only time will tell.

Then they go on to my friend Dr. Willie Soon, who was viciously attacked in the New York Times by a Greenpeace written slander piece published on the front page of the paper, disguised as reporting by Justin Gillis and John Schwartz, for more details see here and here.

As for Dr. Roy Spencer, one of the inventors of satellite atmospheric temperature measurements, the idea that he has been debunked is absurd. He is the team leader for the Advanced Microwave Scanning Radiometer for NASA’s Aqua satellite. His landmark original algorithm for measuring temperature, in the early 1990’s, did not properly take into account satellite orbital decay for sure. But, this was fixed 20 years ago! Why beat a 20-year-old drum! Dr. Spencer is an evangelical Christian, but in the United States we are not supposed to discriminate based on religion, one is free to have their own beliefs. So far as I know, and I’ve read most of what Dr. Spencer has written on climate, his views are very mainstream. None have been debunked, although not everyone agrees with him on all issues.

I write for blogs, including my own, but I try and document what I do and keep it as accurate as possible. Doing google searches for a phrase like “Lindzen debunked” and then picking out headlines that agree with your preconceived ideas and posting them without checking them is disgusting.  Just my opinion.