the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 05 Dec 2024
An observational record of global gridded near surface air temperature change over land and ocean from 1781
Abstract. We present a new gridded data set of air temperature change across global land and ocean extending back to the 1780s. This data set, called the GloSAT reference analysis, has two novel features: it uses marine air temperature observations rather than the sea surface temperature measurements typically used by pre-existing data sets, and it extends further into the past than existing merged land and ocean instrumental temperature records which typically estimate temperature changes from the mid-to-late 19th century onwards. New estimates of diurnal heating biases in marine air temperatures have enabled the use of daytime observations, extending the dataset further into the past compared to nighttime-only marine air temperature data. The data set uses an extended version of the CRUTEM5 station database over land areas, incorporating newly available bias adjustments for non-standard thermometer enclosures used prior to the adoption of Stevenson screens and new climatological normal estimates for stations with limited data in the 1961–1990 baseline period. Land and marine temperature anomalies are combined to produce a gridded data set following the methods developed for HadCRUT5. The GloSAT global and hemispheric temperature anomaly series show close agreement with those based on sea-surface temperature for much of the overlapping period of their records but with slightly less warming overall.
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Status: final response (author comments only)
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CC1: 'Comment on essd-2024-500', Zeke Hausfather, 12 Dec 2024
Really excited about this new paper extending the temperature record further back in time. One small recommendation for the authors is to show how their pre-1850 land temperature reconstruction compares to that published by Berkeley Earth (which also goes back to the 1700s).
Citation: https://doi.org/10.5194/essd-2024-500-CC1 -
CC4: 'Reply on CC1', Robert Rohde, 04 Jan 2025
I've attached a file with Berkeley Earth's Land time series overlaid on the manuscript's Figure 4a. There are obvious similarities, including the cold swings during the early periods with high volcanic activity. As an alternative instrumental reconstruction prior to 1850, I would agree that a comparison like this probably ought to be included in the paper.
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CC4: 'Reply on CC1', Robert Rohde, 04 Jan 2025
- RC1: 'Comment on essd-2024-500', Anonymous Referee #1, 18 Dec 2024
- RC2: 'Comment on essd-2024-500', Anonymous Referee #2, 25 Dec 2024
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CC2: 'Use of LEK', Robert Rohde, 04 Jan 2025
I'm rather bothered by the use of "Taylor et al. (in prep.)" to describe the LEK process of estimating normals and how little information is provided to describe the process in the current manuscript. The LEK approach is one of several core innovations being used in this manuscript, but there isn't enough detail appearing in the text to really understand what is being done. Or more precisely, I could imagine several different ways to formulate such a Kriging process, and the current text is much too vague to be clear what approach is being taken. For example, how are the covariances being estimated? Is there explicit consideration of common covariates (e.g. latitude, elevation)? Further, a single sentence is used to describe a test of the accuracy of the method (again referenced to Taylor et al.) but without enough elaboration to be clear exactly how it is being tested. Nor does it say whether the error depends on how much of the 1961-1990 interval is missing? Is the error different depending on the time coverage of the station (e.g. is a station running 1980-2020 going to have more accurate normals than one running 1880-1920?) Based on personal experience with station biases and Inhomogeneities, it feels implausible that the typical error in estimating normals via the process described would only be 0.2 C when considering station time series that end well before the modern period.
Given that LEK is one of several core innovations being applied here, I would suggest that either it needs to be thoroughly described in this manuscript (perhaps in supplementary methods?) or this manuscript should pause publication under after "Taylor et al. (in prep.)" can be published and made available.
Citation: https://doi.org/10.5194/essd-2024-500-CC2 -
CC3: 'Number of Observations over Time', Robert Rohde, 04 Jan 2025
The maps summarizing two decades at a time are helpful, but it is still hard to get a sense of how much (or how little) data is available. I would urge the authors to also include a time series of the number of observations available over time, and the number of non-empty grid cells over time. This could be done separately for global, land, and ocean. I believe such plots would be very helpful in getting a sense of how much data is being used when, especially for the early parts of the record.
Citation: https://doi.org/10.5194/essd-2024-500-CC3 -
RC3: 'Comment on essd-2024-500', Anonymous Referee #3, 05 Jan 2025
Review of Morice et al., ‘An observational record of global gridded near surface air temperatures’
This paper is a valuable piece of work which describes a new global temperature data set which adds considerably to the diversity of available data sets, both because of its length and because of its use of marine air temperature. The approach of the paper is to draw heavily on existing papers for its methodology (in particular the Cornes 2020, Cropper 2023 and Wallis 2024 papers) and it is not my intention here to re-review the methods used in those papers; the main significance of the work described here is in merging these methods into a consistent data set. My comments are relatively limited and I expect the paper will be publishable with only modest changes, but I would like to see the author responses to the major comments and have therefore given a ‘major revisions’ rating.
Major comments
- Figure 5 indicates a marked breakpoint c. 1820 in the difference series between GloSAT and Pages 2K, which is not commented on at all in the current text. If this is indeed a response to high volcanic activity (which seems a plausible hypothesis), do you have any comment on how volcanic activity might impact GloSAT differently to the proxy records used in PAGES 2k? (If it turns out that this points to an unresolved inhomogeneity in PAGES 2k, that might have implications for the IPCC AR6 assessment (Cross-Chapter Box 1.2) that warming from 1750 to 1850-1900 was 0.1 (-0.1 to 0.3) °C, as PAGES 2k was a major data source for that).
- I think the implications of the land/sea mix of data and how that has changed over time should be considered – land is warming faster than ocean so a lack of land data may create biases relative to a more spatially complete series. I note here that there is essentially no Southern Hemisphere land data before 1850, and only a limited proportion of Southern Hemisphere oceans is sampled in the earlier years (from Figure 2, this looks like it’s essentially the Europe-to-south Asia via the Cape of Good Hope route), which has the potential to create sampling biases. The incomplete spatial sampling also potentially creates other issues too – e.g. one would not expect the ENSO signal in global temperatures in a data set with the coverage of GloSAT pre-1850 to be similar to the ENSO signal in more globally complete sets.
Minor comments
L42 – it would probably also be worth mentioning the almost complete lack of pre-1850 Southern Hemisphere land data at this point (especially as that then becomes relevant to later discussion).
L226 – typo – should read ‘at least one value’
L381-383 – I’m a little surprised that MAT has a longer length scale than SST, do you have any idea why this might be the case?
L408-409 – ‘slightly reduced southern hemisphere coverage’ – this could perhaps be elaborated on – as I understand it, there is almost no MAT data south of 40 °S outside of summer (presumably because most of the observing ship traffic, such as it is, in that region is vessels servicing Antarctic and sub-Antarctic bases). Does the concentration of observations in one part of the year create a bias we need to consider? Also relevant to discussion at L447-450.
L488-493 – it could be mentioned here (from AR6 findings) that in reanalyses GSAT also warms faster than GMST. This discrepancy between observed and model-based data sets is intriguing and definitely worth further study (as the authors state at L492-493).
Section 4.4 – if possible, I think it would be useful for comparison to report a metric for GloSAT temperature change for 1850-1900 to 2011-2020, to match the corresponding metrics reported for GMST data sets in AR6.
L525-537 – I would have expected that a lot of the additional variability in GloSAT comes from the incomplete (and spatially uneven) sampling pre-1850. I think that should be commented on before the reference to volcanic activity.
Citation: https://doi.org/10.5194/essd-2024-500-RC3 -
CC5: 'Regarding Natural Diurnal Variability', Robert Rohde, 06 Jan 2025
Strangely, this paper fails to acknowledge that there are in fact two kinds of diurnal variability affecting marine air temperatures.
The paper heavily discusses diurnal heating biases arising from the ship absorbing solar radiation and warming during the day. The authors are right to pay careful attention to such heating biases since the warming of the ship can often spuriously raise the daytime marine air temperature measured by the ship by ~1-4 °C (e.g. Cropper et al. 2023) relative to the corresponding nighttime measurements by the same ship.
However, despite this extensive attention to diurnal heating biases, the paper never acknowledges that natural diurnal variability can also exist in marine air temperatures. In many contexts, the buffering capacity of the oceans often makes diurnal temperature variability of the ocean and air quite small (e.g. ~0.1 °C). But in the tropics, in shallow water, and/or near shore the diurnal temperature range can be substantially larger (e.g. 0.5 °C). This is especially true in near-shore environments, where differential heating of land and ocean can lead to predictable intraday shifts of wind direction from off-shore to on-shore with corresponding large variations in the characteristics of the advected air mass. Though natural diurnal variability is smaller (and sometimes much smaller) than the spurious diurnal heating biases, I don't think it is reasonable for a paper focused so extensively on marine air temperature to entirely ignore the potential for natural diurnal variations.
Natural diurnal variability, to the extent that it exists, isn't a bias in the sense that the term is normal used, rather it is legitimate feature of the weather. The discussion in the paper is sometimes confusing or even misleading because it fails to separately address the existence and possible impacts of such variability.
Most measurements of diurnal temperature range over the ocean have focused on the variation in ocean temperatures, e.g.
HadDTR (https://www.metoffice.gov.uk/hadobs/haddtr/)
AMSR-E Satellite measurements (Large & Caron: https://doi.org/10.1002/2014JC010691)
Such natural diurnal temperature variations vary not only by location, but also by time of year.
The diurnal variation in marine air temperatures will often be at least as large as the corresponding variation in sea surface temperatures, and in near-shore environments, the diurnal range of marine air temperature can be considerably larger due to regular patterns of advection from terrestrial air masses.
The corrections applied for diurnal heating biases (Cropper et al. going back to BKT) are primarily designed to deal with the biases arising from the ship itself. For example, despite natural diurnal variability exhibiting substantial spatial structure, the positional dependence of the corrections appears to be limited to considering latitude and solar declination. Nonetheless, since the bias adjustments are being empirically fit, the corrections may partially capture (and hence remove) natural diurnal variability in addition to the ship-based diurnal heating biases. However, it is unclear from the present paper and Cropper et al. to what extent that is the case. Based on the present methods, one might suspect that ships that travel across regions with varying degrees of natural diurnal variability will have poorer fits. The authors say "... the full diurnal cycle is removed from the data and GloSATMAT should be considered a nighttime-equivalent dataset", but that's only true to the extent that the Cropper et al. process removes both the ship-based diurnal heating biases (that it was designed for) and the marine air temperature's natural diurnal variability (which it was apparently not designed for).
To the extent that natural diurnal variability persists in the bias-corrected marine air temperatures, then changes in the time-of-day composition of the measurement network could lead to biases in the apparent marine air temperature trends. In this context, it might be useful if the authors would provide time series indicating what fraction of the marine air temperatures are nighttime vs. adjusted daytime measurements.
In terms of revisions, I'd like to see the authors acknowledge the existence of natural diurnal variability in marine air temperatures and discuss the extent to which the Cropper et al. process is capturing the natural variability in addition to the ship-based heating biases. Further, I would hope for some discussion of the potential impact that residual natural diurnal variability might have on the assessment of long-term marine air temperature trends.
Citation: https://doi.org/10.5194/essd-2024-500-CC5 -
CC6: 'Comment on essd-2024-500', Raphael Neukom, 07 Jan 2025
Great to see this important contribution to integrations of early instrumental temperatures. Just briefly with regards to the Hausfather/Rohde comments and Referee #3:
It seems unlikely that the very large variance increase in GloSAT (and BE) prior to ca. 1860 is just caused by the volcanic activity, as it persists also before and after the large eruptions. In PAGES2k (2019) there is a comparison to an early instrumental composite over 1775-1900 (their Figure S19), which shows comparable variance with the reconstructions over this time period and no such substantial variance changes. Even though this composite is only from Europe, this may add to the argument that the pre-1860 variance inflation may be an artifact of replication/coverage changes.Nevertheless it is likely that the variance of the PAGES2k ensemble median is too small (as already stated in the paper), mainly due to the averaging accross the large ensemble. This could be assessed by a member-by-member comparison for both ensemlbes for Fig. 5, although this is already partly addresseed in Fig S5. Given the probable under- and over- estimation of variance by the two curves, it seems likely that the truth is somewhere in between...
Citation: https://doi.org/10.5194/essd-2024-500-CC6 -
CC7: 'Reply on CC6', Robert Rohde, 08 Jan 2025
This figure is quite old now (and rather simplistic) but it might still be a bit useful. It shows an estimate of the expected temperature response to volcanic events as compared to Berkeley Earth's land record. The volcanic events are scaled based on their corresponding sulfur loading in polar ice.
Such a figure can help to convey that the pre-1850 volcanic perturbations really were extremely large, which potentially explains some of the early variability.
I would agree though that there is likely to also be some spurious variability in the early period.
Citation: https://doi.org/10.5194/essd-2024-500-CC7
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CC7: 'Reply on CC6', Robert Rohde, 08 Jan 2025
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