This week I have some bad news for you. Late 20th century warming was not natural event in Australasia, but it seems that we did it with our fossil fuels. When we started warming up the Earth with carbon dioxide from fossil fuels, I guess we just didn't realize that climate sensitivity is bigger for that than for solar forcing. We see that for example in tropospheric water vapor increase and in oceanic warming. Summer monsoon is also weakening and making air pollution situation even worse. Humans might be affected too, as has happened during past climate changes.

So what do we do? We start using biofuels, but that then seems to destroy stratospheric ozone, which protects us from solar UV radiation. El Niño is of no help, because it just mixes up the carbon dioxide in the atmosphere. We could try to see if we can identify tree rings in Ethiopia, but that might be just fun recreational activity and might not actually help. Perhaps we should just hope that climate sensitivity is not that bad. After all, there is uncertainty in cloud feedback, so it might be that we only get 2+ Kelvins of warming. Perhaps best thing to do is to sit back, read some more studies next week, and hope they come up with a plan for us, right?

Transition from fossil fuels to biofuels might be bad idea from ozone layer perspective

Impacts of the production and consumption of biofuels on stratospheric ozone - Revellet al.(2012)

Abstract:"Biofuels are becoming increasingly popular sources of renewable energy as economic pressures and environmental consequences encourage the use of alternatives to fossil fuels. However, growing crops destined for use as biofuels incurs large N₂O emissions associated with the use of nitrogen-based fertilizers. Besides being a greenhouse gas, N₂O is also the primary source of stratospheric NO_x(NO + NO₂) which leads to stratospheric ozone depletion. In this paper, the potential effects on the ozone layer of a large-scale shift away from fossil fuel use to biofuels consumption over the 21st century are examined. Under such a scenario, global-mean column ozone decreases by 2.6 DU between 2010 and 2100 in contrast to a 0.7 DU decrease under a control simulation (the IPCC SRES B1 scenario for greenhouse gases) and a 9.1 DU increase under the more commonly used SRES A1B scenario. Two factors cause the decrease in ozone in the biofuels simulation: 1) large N₂O emissions lead to faster rates of the ozone-depleting NO_xcycles and; 2) reduced CO₂emissions (due to less fossil fuel burning) lead to relatively less stratospheric cooling over the 21st century, which decreases ozone abundances. Reducing CO₂emissions while neglecting to reduce N₂O emissions could therefore be damaging to the ozone layer."

Citation:Revell, L. E., G. E. Bodeker, P. E. Huck, and B. E. Williamson (2012), Impacts of the production and consumption of biofuels on stratospheric ozone, Geophys. Res. Lett., 39, L10804, doi:10.1029/2012GL051546.

Late 20th century warming was unusual and outside natural variability in Australasia during last millenium

Evidence of unusual late 20th century warming from an Australasian temperature reconstruction spanning the last millennium - Gergiset al.(2012)[FULL TEXT]

Abstract:"This study presents the first multi-proxy warm season (September-February) temperature reconstruction for the combined land and oceanic region of Australasia (0°S-50°S, 110°E-180°E). We perform a 3000-member ensemble Principal Component Reconstruction (PCR) using 27 temperature proxies from the region. The proxy network explained 69% of the inter-annual variance in the HadCRUT3v SONDJF spatial mean temperature over the 1921-1990 calibration period. Applying eight stringent reconstruction‘reliability’ metrics identified post A.D. 1430 as the highest quality section of the reconstruction, but also revealed a skilful reconstruction is possible over the full A.D. 1000-2001 period. The average reconstructed temperature anomaly in Australasia during A.D. 1238-1267, the warmest 30-year pre-instrumental period, is 0.09°C (±0.19°C) below 1961-1990 levels. Following peak pre-industrial warmth, a cooling trend culminates in a temperature anomaly of 0.44°C (±0.18°C) below 1961-1990 levels between A.D. 1830-1859. A preliminary assessment of the roles of solar, volcanic, and anthropogenic forcings and natural ocean-atmosphere variability is performed using CSIRO Mk3L model simulations and independent palaeoclimate records. Solar and volcanic forcing does not have a marked influence on reconstructed Australasian temperature variations, which appear to be masked by internal variability. In 94.5% of the 3000-member reconstruction ensemble, there are no other warm periods in the past 1,000 years that match or exceed post-1950 warming observed in Australasia. The unusual 20th century warming cannot be explained by natural variability alone, suggesting a strong influence of anthropogenic forcing in the Australasian region."

Citation:Joëlle Gergis, Raphael Neukom, Steven J. Phipps, Ailie J. E. Gallant, David J. Karoly, and PAGES Aus2K Project Members, Journal of Climate 2012, doi: http://dx.doi.org/10.1175/JCLI-D-11-00649.1.

Is climate sensitivity less for solar forcing than for carbon dioxide forcing?

Sensitivity of an Earth system climate model to idealized radiative forcing - Andrewset al.(2012)

Abstract:"We diagnose forcing and climate feedbacks in benchmark sensitivity experiments with the new Met Office Hadley Centre Earth system climate model HadGEM2-ES. To identify the impact of newly-included biogeophysical and chemical processes, results are compared to a parallel set of experiments performed with these processes switched off, and different couplings with the biogeochemistry. In abrupt carbon dioxide quadrupling experiments we find that the inclusion of these processes does not alter the global climate sensitivity of the model. However, when the change in carbon dioxide is uncoupled from the vegetation, or when the model is forced with a non-carbon dioxide forcing– an increase in solar constant– new feedbacks emerge that make the climate system less sensitive to external perturbations. We identify a strong negative dust-vegetation feedback on climate change that is small in standard carbon dioxide sensitivity experiments due to the physiological/fertilization effects of carbon dioxide on plants in this model."

Citation:Andrews, T., M. A. Ringer, M. Doutriaux-Boucher, M. J. Webb, and W. J. Collins (2012), Sensitivity of an Earth system climate model to idealized radiative forcing, Geophys. Res. Lett., 39, L10702, doi:10.1029/2012GL051942.

Updated estimates of world ocean heat content and sea level change

World ocean heat content and thermosteric sea level change (0–2000 m), 1955–2010 - Levituset al.(2012)

Abstract:"We provide updated estimates of the change of ocean heat content and the thermosteric component of sea level change of the 0–700 and 0–2000 m layers of the World Ocean for 1955–2010. Our estimates are based on historical data not previously available, additional modern data, and bathythermograph data corrected for instrumental biases. We have also used Argo data corrected by the Argo DAC if available and used uncorrected Argo data if no corrections were available at the time we downloaded the Argo data. The heat content of the World Ocean for the 0–2000 m layer increased by 24.0± 1.9× 10²²J (±2S.E.) corresponding to a rate of 0.39 W m⁻²(per unit area of the World Ocean) and a volume mean warming of 0.09°C. This warming corresponds to a rate of 0.27 W m⁻²per unit area of earth's surface. The heat content of the World Ocean for the 0–700 m layer increased by 16.7± 1.6× 10²²J corresponding to a rate of 0.27 W m⁻²(per unit area of the World Ocean) and a volume mean warming of 0.18°C. The World Ocean accounts for approximately 93% of the warming of the earth system that has occurred since 1955. The 700–2000 m ocean layer accounted for approximately one-third of the warming of the 0–2000 m layer of the World Ocean. The thermosteric component of sea level trend was 0.54± .05 mm yr⁻¹for the 0–2000 m layer and 0.41± .04 mm yr⁻¹for the 0–700 m layer of the World Ocean for 1955–2010."

Citation:Levitus, S., et al. (2012), World ocean heat content and thermosteric sea level change (0–2000 m), 1955–2010, Geophys. Res. Lett., 39, L10603, doi:10.1029/2012GL051106.

Radiosondes and reanalyses see positive trends in tropospheric water vapor over parts of Arctic

Recent changes in tropospheric water vapor over the Arctic as assessed from radiosondes and atmospheric reanalyses - Serrezeet al.(2012)[Presentation material]

Abstract:"Changes in tropospheric water vapor over the Arctic are examined for the period 1979 to 2010 using humidity and temperature data from nine high latitude radiosonde stations north of 70°N with nearly complete records, and from six atmospheric reanalyses, emphasizing the three most modern efforts, MERRA, CFSR and ERA-Interim. Based on comparisons with the radiosonde profiles, the reanalyses as a group have positive cold-season humidity and temperature biases below the 850 hPa level and consequently do not capture observed low-level humidity and temperature inversions. MERRA has the smallest biases. Trends in column-integrated (surface to 500 hPa) water vapor (precipitable water) computed using data from the radiosondes and from the three modern reanalyses at the radiosonde locations are mostly positive, but magnitudes and statistical significance vary widely between sites and seasons. Positive trends in precipitable water from MERRA, CFSR and ERA-Interim, largest in summer and early autumn, dominate the northern North Atlantic, including the Greenland, Norwegian and Barents seas, the Canadian Arctic Archipelago and (on the Pacific side) the Beaufort and Chukchi seas. This pattern is linked to positive anomalies in air and sea surface temperature and negative anomalies in end-of-summer sea ice extent. Trends from ERA-Interim are weaker than those from either MERRA or CFSR. As assessed for polar cap averages (the region north of 70°N), MERRA, CFSR and ERA-Interim all show increasing surface-500 hPa precipitable over the analysis period encompassing most months, consistent with increases in 850 hPa air temperature and 850 hPa specific humidity. Data from all of the reanalyses point to strong interannual and decadal variability. The MERRA record in particular shows evidence of artifacts likely introduced by changes in assimilation data streams. A focus on the most recent decade (2001–2010) reveals large differences between the three reanalyses in the vertical structure of specific humidity and temperature anomalies."

Citation:Serreze, M. C., A. P. Barrett, and J. Stroeve (2012), Recent changes in tropospheric water vapor over the Arctic as assessed from radiosondes and atmospheric reanalyses, J. Geophys. Res., 117, D10104, doi:10.1029/2011JD017421.

El Niño has an influence to atmospheric carbon dioxide distribution

Influence of El Niño on Mid-tropospheric CO₂from Atmospheric Infrared Sounder and Model - Jianget al.(2012)

Abstract:"We investigate the influence of El Niño on the mid-tropospheric CO₂from the Atmospheric Infrared Sounder (AIRS) and Model of Ozone and Related Chemical Tracers version 2 (MOZART-2). AIRS mid-tropospheric CO₂data are used to study the temporal and spatial variability of CO₂in response to El Niño. CO₂difference between the Central Pacific and Western Pacific correlates well with the Southern Oscillation Index. To reveal the temporal and spatial variability of El Niño signal in the AIRS mid-tropospheric CO₂, a multiple regression method is applied to the CO₂data from September 2002 to February 2011. There is more (less) mid-tropospheric CO₂in the Central Pacific and less (more) mid-tropospheric CO₂in the Western Pacific during El Niño (La Niña) events. Similar results are seen in the MOZART-2 convolved mid-tropospheric CO₂, although the El Niño signal in the MOZART-2 is weaker than that in the AIRS data."

Citation:Xun Jiang, Jingqian Wang, Edward T. Olsen, Maochang Liang, Thomas S. Pagano, Luke L. Chen, Stephen J. Licata, and Yuk L. Yung, Journal of the Atmospheric Sciences 2012, doi: http://dx.doi.org/10.1175/JAS-D-11-0282.1.

Were historical population crises in China related to climate?

A tale of two population crises in recent Chinese history - Lee& Zhang (2012)[FULL TEXT]

Abstract:"The fall of the Ming dynasty in the first half of the 17th century and the Taiping Rebellion from 1851–1864 were two of the most chaotic periods in Chinese history, and each was accompanied by large-scale population collapses. The‘Kang-Qian Golden Age’ (also known as‘High Qing’), during which population size expanded rapidly, falls in between the two. Scholars remain divided in their opinions concerning the above alternation of population growth and decline as to whether variations in population size or climate change should be identified as the root cause. In either case, the synergistic impact of population growth and climate change upon population growth dynamics is overlooked. In the present study, we utilized high-resolution empirical data, qualitative survey, statistical comparison and time-series analysis to investigate how the two factors worked synergistically to drive population cycles in 1600–1899. To facilitate our research, we posited a set of simplified pathways for population growth in historical agrarian China. Our results confirm that the interrelation between population growth, climate change and population crises in recent Chinese history basically followed our posited pathways. The recurrences of population crises were largely determined by the combination of population growth and climate change. Our results challenge classic Malthusian/post-Malthusian interpretations and historians’ views of historical Chinese population cycles."

Citation:Harry F. Lee and David D. Zhang, Climatic Change, 2012, DOI: 10.1007/s10584-012-0490-9.

Trying to see annual tree-rings in permanent growing readiness trees of Ethiopia

Growth dynamics and potential for cross-dating and multi-century climate reconstruction of Podocarpus falcatus in Ethiopia - Krepkowskiet al.(2012)

Abstract:"Podocarpus falcatus is an indigenous evergreen conifer species of tropical mountain forests in southeastern Ethiopia, showing potential tree ages of around 500 years. To study the influence of seasonal climate on the growth pattern of P. falcatus, we combined high-resolution electronic dendrometer measurements with wood anatomical investigations of microcores from the outermost stem parts collected in monthly intervals. At any time of the year sufficient rain events are able to cause cambial activity in P. falcatus. This permanent growing readiness leads to irregular wood formation with the formation of intra-annual density fluctuations and missing rings. Wood anatomical studies of microcores collected around the circumference of a mature P. falcatus revealed locally different activity status of the cambium on different lobes of the stem. Tree-ring width measurements of stem disks resulted in tentative tree ages that were confirmed by radiocarbon dating of selected wood samples. Although our efforts to cross-date ring-width series from several stem disks were not successful, further sampling in areas with different rainfall regimes, additional radiocarbon dating and measurements of stable isotopes hopefully would enable the establishment of a multi-century-long tree-ring series for climate reconstruction."

Citation:Julia Krepkowski, Achim Bräuning, Aster Gebrekirstos, Dendrochronologia, http://dx.doi.org/10.1016/j.dendro.2012.01.001.

Weakening of summer monsoon has increased aerosol concentrations over eastern China

Increases in aerosol concentrations over eastern China due to the decadal-scale weakening of the East Asian summer monsoon - Zhuet al.(2012)[FULL TEXT]

Abstract:"China has been experiencing increased concentrations of aerosols, commonly attributed to the large increases in emissions associated with the rapid economic development. We show by using a chemical transport model driven by the assimilated meteorological fields that the observed decadal-scale weakening of the East Asian summer monsoon also contributed to the increases in aerosols in China. We find that the simulated aerosol concentrations have strong negative correlations with the strength of the East Asian Summer monsoon. Accounting for sulfate, nitrate, ammonium, black carbon, and organic carbon aerosols, the summer surface-layer PM_2.5concentration averaged over eastern China (110°–125°E, 20°–45°N) can be 17.7% higher in the weakest monsoon years than in the strongest monsoon years. The weakening of the East Asian Summer monsoon increases aerosol concentrations mainly by the changes in atmospheric circulation (the convergence of air pollutants) in eastern China."

Citation:Zhu, J., H. Liao, and J. Li (2012), Increases in aerosol concentrations over eastern China due to the decadal-scale weakening of the East Asian summer monsoon, Geophys. Res. Lett., 39, L09809, doi:10.1029/2012GL051428.

Differences in cloud feedbacks continue to be important contributors to 2.1–4.7 K range of equilibrium climate sensitivity

Forcing, feedbacks and climate sensitivity in CMIP5 coupled atmosphere-ocean climate models - Andrewset al.(2012)

Abstract:"We quantify forcing and feedbacks across available CMIP5 coupled atmosphere-ocean general circulation models (AOGCMs) by analysing simulations forced by an abrupt quadrupling of atmospheric carbon dioxide concentration. This is the first application of the linear forcing-feedback regression analysis of Gregory et al. (2004) to an ensemble of AOGCMs. The range of equilibrium climate sensitivity is 2.1–4.7 K. Differences in cloud feedbacks continue to be important contributors to this range. Some models show small deviations from a linear dependence of top-of-atmosphere radiative fluxes on global surface temperature change. We show that this phenomenon largely arises from shortwave cloud radiative effects over the ocean and is consistent with independent estimates of forcing using fixed sea-surface temperature methods. We suggest that future research should focus more on understanding transient climate change, including any time-scale dependence of the forcing and/or feedback, rather than on the equilibrium response to large instantaneous forcing."

Citation:Andrews, T., J. M. Gregory, M. J. Webb, and K. E. Taylor (2012), Forcing, feedbacks and climate sensitivity in CMIP5 coupled atmosphere-ocean climate models, Geophys. Res. Lett., 39, L09712, doi:10.1029/2012GL051607.

Observed tropical tropopause cooling might not be statistically significant

How well do we know recent climate trends at the tropical tropopause? - Wanget al.(2012)

Abstract:"The tropical tropopause is a transition layer between the troposphere and stratosphere that influences global climate and atmospheric chemistry. Several studies have reported multidecadal tropical tropopause cooling and have suggested a correlation between observed tropopause temperature and stratospheric water vapor. Our more rigorous examination of the observations shows tropopause trends have greater uncertainty than previously suggested and the cooling may not be statistically significant. We used two approaches to remove time-varying bias effects from cold-point tropopause trends estimated from radiosonde observations. Our results are consistent with expectations from a conceptual model of tropopause changes and could resolve discrepancies between complex climate models and observations."

Citation:Wang, J. S., D. J. Seidel, and M. Free (2012), How well do we know recent climate trends at the tropical tropopause?, J. Geophys. Res., 117, D09118, doi:10.1029/2012JD017444.

CLASSIC OF THE WEEK: Dobson (1923)

Measurements of the Sun's Ultra-Violet Radiation and Its Absorption in the Earth's Atmosphere - Dobsonet al.(1923)[FULL TEXT]

Abstract:No abstract. Quote from the paper: "The object of the present work was to obtain, if possible, a long series of measurements of the ultra-violet light radiated by the sun, the atmospheric transmission coefficient for this light and also the amount of ozone in the atmosphere."

Citation:G. M. B. Dobson, Proc. R. Soc. Lond. A September 1, 1923 104 725 252-271; doi:10.1098/rspa.1923.0107 .

This is a cross-post fromAGW Observer. When each paper is published, it is notified in AGW ObserverFacebook pageandTwitter page. At least some of these are also retweeted in Skeptical Science Twitter page. Here'sthe archive for the research papers of previous weeks. If this sort of thing interests you, be sure to check outA Few Things Illconsidered. They also have a weekly posting containing lots of links to new research and other climate related news.

The Hadley Centre of the UK Meteorological office and the Climatic Research Unit (CRU) of the University of East Anglia have since 1989 jointly maintained a global surface temperature record, HadCRUT. The current version of this record, HadCRUT3, is very widely cited in the academic literature (currently around 900 citations), and provides a record of combined land and ocean temperatures running back to 1850. The dataset is updated monthly to provide a continuous snapshot of the state of the climate.

Recently a new version of the record, HadCRUT4, has been released running to December 2010, with monthly updates planned in future. This update is a response to several factors. In the case of the CRUTEM land temperature record, coverage has been declining because of the need for current weather stations to have a sufficient number of readings in the baseline period 1960-1990. As weather stations move, continuity back to this period is lost. The impact of this decline in coverage has been assessed by two reports, by theECMWFandGISS, and also reproducedhere, and has led to an underestimation of recent land temperature trends. TheCRUTEM4update introduces a number of new station records to address this coverage issue.

A second motivation for the update is the discovery of a bias in the sea surface temperature record, HadSST2, leading to a significant cool bias following the second world war. A new version,HadSST3, addresses this bias, but also has some impact on recent temperature trends. HadSST3 also introduces a new approach to estimating uncertainties in temperature records through the use of an ensemble of realisations; this approach is carried through to HadCRUT4.

The method and results are described inMorice et al (2012). In this article we will examine the impact of these changes on the global surface temperature record and consider the implications for other datasets.

What has changed?

Figure 1 shows a comparison of the change in temperatures over recent years in HadCRUT3 and HadCRUT4, using the difference between the 5 year means 2006-2010 and 1996-2000, and showing the change in coverage. Note that the rectangular projection used here exaggerates area at high latitudes. (The temperature scale ranges from +2C (red) to -2C (blue).

Most obvious is the improvement in land coverage, with many fewer gaps in coverage in the high Northern latitudes, which are mostly warm (red cells). More subtle is a slight increase in sea surface temperatures, spread across the whole globe - this can be seen in many sea cells becoming marginally more red or less blue. Both these effects tend to increase the 15 year trend, although the relative size of the effects is not apparent from this figure. We will examine their relative contributions shortly.

What is the impact of these changes on the instrumental temperature record? Figure 2 shows a comparison of HadCRUT3 and HadCRUT4, using a 12 month running mean.

1900-20101980-2010

The big difference is the near-elimination of the temperature drop after the second world war, as a result of the corrections introduced in HadSST3. The recent changes are rather smaller, but there is a noticeable increase in temperatures since the late 90's.

Where do the differences come from? This question can be answered by separating out the contribution of the changes to CRUTEM and HadSST. Since Hadley and CRU distribute gridded datasets for the land and ocean data, they can be combined in any combination using a land mask to select between land and ocean series, or to perform a weighted average in the case of coastal cells - this is the method employed in constructing the HadCRUT4 combined maps (HadCRUT3 used a slightly different approach for coastal cells). Combining CRUTEM3 and HadSST2 give a very close approximation to HadCRUT3, and CRUTEM4 and HadSST3 give an almost exact reproduction of HadCRUT4. (This also reveals that additional corrections incorporated into HadCRUT4 have minimal impact).

By also calculating an intermediate series, using the new CRUTEM4 and the old HadSST2, and taking differences with the HadCRUT3 and HadCRUT4, we can separate the contributions of the new land and sea surface temperatures. The results are shown in Figure 3 using a 12 month moving average.

The differences are exactly what we would expect from our examination ofCRUTEM4andHadSST3- the changes are very similar to the changes in the land and sea records respectively, scaled down by the proportion of the globe covered by each (or rather the proportion sampled).

The biggest difference arises from the change in the sea surface temperatures after the second world war. As wesaw previously, at the end of the war there was a switch from using warm-biased engine room intake (ERI) temperatures back to using cool-biased bucket measurements - shown on the right. (The switch from buckets to ERIs at the beginning of the war was already corrected in existing records.) This known but previously uncorrected cool bias required an upward adjustment to the post-war sea surface temperatures.

Land temperatures estimates over the past two decades have increased in the new series owing to improved coverage of the fastest-warming high Northern latitudes. This change is solely due to the inclusion of additional data, rather than any change in methodology (since the issue of averaging conventions described in the previous article does not apply to global data). Recent sea surface temperatures have also seen a small upward adjustment owing to a continuing transition from warm-biased engine room intake measurements to buoy measurements over this period, arising from the new bias correction.

Given that recent temperature trends are a topic of significant public interest, we will examine them in detail. The following table shows the HadCRUT3 and HadCRUT4 trends over the 15 year period 1996-2010, as well as the 13 year period starting in the year 1998, since that year is often used as a starting point for recent trends. The contributions of the land and sea changes have been separated out.

The contribution of the two updates to the trend from 1996 is roughly equal. The change in trend since 1998 is more strongly affected, with the 1998/1999 surface temperatures receiving a significant downward adjustment in both the land and sea surface temperature records. (The whole record is then shifted upward due to temperature changes in the baseline period.)

HadCRUT3 was always an outlier amongst the surface temperature records for its high 1998 temperature, so this change brings HadCRUT4 more into line with the other versions of the instrumental temperature record. The change in the land temperature record was expected due to the change in coverage. The impact of the bias correction to the SST data on the 1999 temperature was more of a surprise.

Uncertainties

HadCRUT4 provides an ensemble of temperature series to allow trend uncertainties to be calculated which take into account the effects of correlation in the bias corrections. This approach, described in our examination ofHadSST3, is an additional source of uncertainty not accounted for by post-hoc uncertainty estimates such as that employed in the Skeptical Science trend calculator. Assuming that the two sources of uncertainty are uncorrelated, they can be combined using the RMS (root-mean-square) of the individual uncertainties. Trend uncertainties calculated using this approach are tabulated below.

In this case of the recent trend calculations the additional uncertainty due to correlated errors in the bias correction is small. This is likely to be true for most recent trends.

One other innovation in HadCRUT4 is the use of the NCEP/NCAR reanalysis dataset to determine the additional uncertainty in the global mean temperature arising from incomplete coverage. The effect of coverage is simulated in the NCEP data by reducing the coverage to match a given month from the HadCRUT4 data, and seeing how the  estimated global temperature changes. Results from every month in the NCEP data are combined to determine an uncertainty estimate for each month in the HadCRUT4 record.

Comparison to other datasets

The HadCRUT4 record can be compared to the other land-ocean temperature records using the tools fromWood for Trees,Nick Stokes, orSkeptical Science. (Unlike the CRUTEM4 case the impact of averaging conventions is minimal for the land-ocean data, so the distributed records are comparable.)

Morice et al (2012)make an interesting comparison to other datasets in their Figures 11 and 12. Excerpts from these figures are shown in Figure 4, showing the recent Northern hemisphere temperatures in which the disagreement between the different records is greatest. The curves are HadCRUT4 (black), GISTEMP (red), NCDC (green) and JMA (blue). The grey region is the HadCRUT4 uncertainty interval, and the straight lines are 1979-2010 trends. The left hand figure compares global surface temperature, showing the disagreement between the datasets. The right hand figure is a comparison of temperatures calculated only over the regions where all the datasets have coverage: This is a test previously performed byHansen et al (2010), which we reproducedhere. As with the previous studies, they find that the principal difference between the datasets is due to differing coverage - over the regions where the datasets share coverage they are in good agreement.

Impact on the other temperature records

An interesting question is how the HadCRUT4 update will  influence the temperature records from other groups. The CRUTEM4 update is not relevant to the other datasets, since the main change has been to increase coverage. The NASA and NCDC datasets already had significantly better coverage than CRUTEM3.

The HadSST3 update may affect the other records directly or indirectly. GISTEMP uses sea surface temperature data from HadISST, which incorporates data from HadSST2. If HadISST is updated to use HadSST3, then GISTEMP will be affected accordingly. The NCDC record uses NOAA’s ERSST ocean data, and so will not be affected directly. However it is likely that NOAA will examine the work of Kennedy et al and evaluate whether the biases identified in that work are correct.

Summary

HadCRUT4 integrates updated versions of the CRU land-temperature dataset and the Hadley sea surface temperature datasets. The update to the land surface temperature data addresses a cool bias over the recent years owing to poor coverage at higher latitudes, a well known problem with the CRUTEM3 record.

The update to the sea surface temperatures is more interesting, since it introduces a new bias correction to the SST data which has not been addressed in existing datasets. It will be interesting to see what other experts in the field make of this development. An independent investigation of the SST bias problem using different approaches would help to establish whether the new record is realistic.

Morice et al (2012)reproduce a result previously obtained by the GISTEMP team and others, showing that the bulk of the disagreement between various versions of the instrumental temperature record arises from differing coverage rather than any difference in the data or methods. Over the regions where the datasets share coverage, agreement is good.

In this article and the preceding articles on HadSST3 and CRUTEM4 I have presented an overview of the literature and data. There will be one further article in this series, in which I will present my own comparisons and evaluation of the new records.

SkS Highlights

Rob Painting'sDavid Evans: All at Sea about Ocean Warming and Sea Level Rise and Dana'sClimate Change Consequences - Often Unexpected received the most attention (as measured by comments posted) by SkS readers during the past week. Rob Honeycutt'sWho Are the Most Prominent Advocates of Global Warming? came in third using the "comments posted" metric.

Toon of the Week

Source:Joe Mohr's Cartoon Archive

Quote of the Week

 "Averaging the global land and ocean as a whole, the combined land and ocean surface temperature during April 2012 was 0.65°C (1.17°F) above the 20^thcentury average of 13.7°C (56.7°F), marking the fifth warmest April since records began in 1880 and the 326^thconsecutive month with a global temperature above the 20^thcentury average. February 1985 was the last month with below-average temperatures, at 0.01°C (0.02°F) below average. This was also the warmest global land and ocean surface temperature anomaly since November 2010, near the onset of first back-to-back La Niñas in 2010."

Source: State of the Climate Global Analysis April 2012, National (US) Oceanic and Atmospheric Administration, May, 2012 

Issue of the Week 

Does SkS pay enough attention to ocean acidification? 

Words of the Week

Climate:Climate in a narrow sense is usually defined as the average weather, or more rigorously, as the statistical description in terms of the mean and variability of relevant quantities over a period of time ranging from months to thousands or millions of years. The classical period for averaging these variables is 30 years, as defined by the World Meteorological Organization. The relevant quantities are most often surface variables such as temperature, precipitation and wind. Climate in a wider sense is the state, including a statistical description, of the climate system. In various chapters in this report different averaging periods, such as a period of 20 years, are also used.

Climate system:The climate system is the highly complex system consisting of five major components: the atmosphere, the hydrosphere, the cryosphere, the land surface and the biosphere, and the interactions between them. The climate system evolves in time under the influence of its own internal dynamics and because of external forcings such as volcanic eruptions, solar variations and anthropogenic forcings such as the changing composition of the atmosphere and land-use change.

Climate change:Climate change refers to a change in the state of the climate that can be identified (e.g., by using statistical tests) by changes in the mean and/or the variability of its properties, and that persists for an extended period, typically decades or longer. Climate change may be due to natural internal processes or external forcings, or to persistent anthropogenic changes in the composition of the atmosphere or in land use. Note that the Unite Nations Framework Convention on Climate Change (UNFCCC), in its Article 1, defines climate change as:‘a change of climate which is attributed directly or indirectly to human activity that alters the composition of the global atmosphere and which is in addition to natural climate variability observed over comparable time periods’. The UNFCCC thus makes a distinction between climate change attributable to human activities altering the atmospheric composition, and climate variability attributable to natural causes. See alsoClimate variability; Detection and Attribution.

Source:Annex I (Glossary)to Climate Change 2007: Working Group I: The Physical Science Basis, IPCC Fourth Assessment Report.

The Week in Review

A complete listing of the articles posted on SkS during the past week. 

• Latest Southern Ocean research shows continuing deep ocean change by John Hartz
• Who Are the Most Prominent Advocates of Global Warming? by Rob Honeycutt
• David Evans: All at Sea about Ocean Warming and Sea Level Rise by Rob Painting
• Dear Heartland, Stop using Arthur Robinson's Trick to Hide the Incline by Mark Boslough
• Richard Alley's Escalator by Dana
• Climate Change Consequences - Often Unexpected by Dana
• New research from last week 19/2012 by Ari Jokimäki
• CRUTEM4: A detailed look by Kevin C

Coming Soon

A list of articles that are in the SkS pipeline. Most of these articles, but not necessarily all, will be posted during the week. 

• Hansen and Sato Estimate Climate Sensitivity from Earth's History(Dana)
• New research from last week 20/2012(Ari Jokimäki)
• If you want them to remember, tell a story(Tom Smerling)
• HadCRUT4: A detailed look(Kevin C)
• Modeled and Observed Ocean Heat Content - Is There a Discrepancy?(Dana)
• Pen letter to an anonymous climate scientist(Dumb Scientist)
• In Search Of: Himalayan Ice Loss(mspelto, Daniel Bailey)

SkS in the News

Ari Jokimäki'sNew research from last week 19/2012was re-posted on PlanetSave By Zachary Shahan under the title,Climate Science Weekly Research Roundup.

SkS Spotlights

TheOeschger Centre for Climate Change Researchis a leading institution for climate research based at the University of Bern, Switzerland. It was founded in the summer of 2007 and is named afterHans Oeschger (1927-1998), a pioneer of modern climate research who worked at the University of Bern.

The Oeschger Centre brings together researchers from nine institutes and four faculties and carries out interdisciplinary research that is at the forefront of climate research. Only through the co-operation of the fields of natural, human and social sciences as well as economics and law can we find ways to deal with the various levels of global climate change: regionally embedded and globally linked.

The University of Bern has a tradition in climate research that spans more than 150 years and is the leading house of the National Centre of Competence in Research Climate (NCCR Climate). Approximately 40 professors teach and conduct research in various areas that deal with questions on climate change. Approximately 35 PhD theses on climate change are submitted each year.

The Oeschger Centre does not only conduct research of high international standard, but also trains young scientists. TheGraduate School of Climate Sciencesoffers a specialised, internationally oriented Masters degree in climate sciences. This unique graduate degree is carried out in close co-operation with the ETH Zurich.

On the one hand, the Oeschger Centre examines the long-term development and dynamics of the climate system, as well as the present and future climate. On the other hand, the effects of climate change on important land ecosystems as well as on the economy and society are investigated. In particular, strategies are being developed to adapt to and to mitigate climate change.