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2015 SkS Weekly News Roundup #48

A chronological listing of the news articles posted on the Skeptical Science Facebook page during the past week.

Sun, Nov 22

Mon, Nov 23

Tue, Nov 24

Wed, Nov 25

Thu, Nov 26

Fri, Nov 27

Sat, Nov 28



from Skeptical Science http://ift.tt/1PTl8nh

A chronological listing of the news articles posted on the Skeptical Science Facebook page during the past week.

Sun, Nov 22

Mon, Nov 23

Tue, Nov 24

Wed, Nov 25

Thu, Nov 26

Fri, Nov 27

Sat, Nov 28



from Skeptical Science http://ift.tt/1PTl8nh
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Venus and Spica in late November, 2015

Tomorrow before dawn – November 29, 2015 – it’ll be hard to miss the planets Venus and Jupiter blazing away in the sky before sunrise. Venus and Jupiter rank as the third-brightest and fourth-brightest celestial bodies, respectively, after the sun and moon. In the predawn hours, you can also catch Spica, the constellation Virgo’s brightest star, near Venus. After you spot Venus and Spica, think of this. For the rest of your life – every 8 Earth-years (every 13 Venus-years) – Venus and Spica will meet up in this same place in the morning sky. So that’s 2015, 2023, 2031, 2039 and so on.

What’s more, Venus will reach perihelion – its closest point to the sun in its orbit – on November 29, 2015. Venus’ orbit is the closest to being circular of all the planets in our solar system. Its distance from the sun only varies by only about 1.5% between perihelion and aphelion (farthest point from the sun).

Venus is well known for its 8-year cycles. This planet – which orbits the sun one step inward from Earth – swings to perihelion 13 times every 8 years. So Venus’ 13th return to perihelion will happen some 8 years from now – on November 28, 2023 – with Venus and Spica returning to virtually the same spot in the November 2023 morning sky.

Venus returns to perihelion 13 times in 8 years:

1. 2016 July 10
2. 2017 Feb 20
3. 2017 Oct 3
4. 2018 May 16
5. 2018 Dec 26
6. 2019 Aug 8
7. 2020 Mar 20
8. 2020 Oct 30
9. 2021 Jun 12
10. 2022 Jan 23
11. 2022 Sep 4
12. 2023 Apr 17
13. 2023 Nov 28

Almost gone! EarthSky lunar calendars make great gifts. Order now.

Spica, a key star of the Zodiac, serves as a perfect example of a 1st-magnitude star. In other words, Spica is one of the brightest stars in our sky.

Yet Spica pales next to dazzling Venus, which outshines this star by a hundredfold.

You can reliably count on brighter Venus to guide your eye to fainter Spica throughout late November and early December, 2015. When Venus is no longer there for guidance, you can always star-hop to Spica from the constellation Corvus the Crow.

By the way, you can also spot the red planet Mars between Venus and Jupiter, as shown on the chart at the top of this post. The green line on the chart depicts the ecliptic – Earth’s orbital plane projected onto the dome of sky – and thus the sun’s apparent yearly path through the constellations of the Zodiac.

Dates of sun’s entry into each constellation of the Zodiac

Because the planets of our solar system orbit the sun on nearly the same plane as Earth, you know you can always look for planets on or near the ecliptic, or the sun’s annual path in front of the backdrop stars.

Bottom line: Watch for the brilliant planet Venus near the bright star Spica in late November and early December, 2015.

EarthSky astronomy kits are perfect for beginners. Order today from the EarthSky store

Donate: Your support means the world to us



from EarthSky http://ift.tt/1MARaUo

Tomorrow before dawn – November 29, 2015 – it’ll be hard to miss the planets Venus and Jupiter blazing away in the sky before sunrise. Venus and Jupiter rank as the third-brightest and fourth-brightest celestial bodies, respectively, after the sun and moon. In the predawn hours, you can also catch Spica, the constellation Virgo’s brightest star, near Venus. After you spot Venus and Spica, think of this. For the rest of your life – every 8 Earth-years (every 13 Venus-years) – Venus and Spica will meet up in this same place in the morning sky. So that’s 2015, 2023, 2031, 2039 and so on.

What’s more, Venus will reach perihelion – its closest point to the sun in its orbit – on November 29, 2015. Venus’ orbit is the closest to being circular of all the planets in our solar system. Its distance from the sun only varies by only about 1.5% between perihelion and aphelion (farthest point from the sun).

Venus is well known for its 8-year cycles. This planet – which orbits the sun one step inward from Earth – swings to perihelion 13 times every 8 years. So Venus’ 13th return to perihelion will happen some 8 years from now – on November 28, 2023 – with Venus and Spica returning to virtually the same spot in the November 2023 morning sky.

Venus returns to perihelion 13 times in 8 years:

1. 2016 July 10
2. 2017 Feb 20
3. 2017 Oct 3
4. 2018 May 16
5. 2018 Dec 26
6. 2019 Aug 8
7. 2020 Mar 20
8. 2020 Oct 30
9. 2021 Jun 12
10. 2022 Jan 23
11. 2022 Sep 4
12. 2023 Apr 17
13. 2023 Nov 28

Almost gone! EarthSky lunar calendars make great gifts. Order now.

Spica, a key star of the Zodiac, serves as a perfect example of a 1st-magnitude star. In other words, Spica is one of the brightest stars in our sky.

Yet Spica pales next to dazzling Venus, which outshines this star by a hundredfold.

You can reliably count on brighter Venus to guide your eye to fainter Spica throughout late November and early December, 2015. When Venus is no longer there for guidance, you can always star-hop to Spica from the constellation Corvus the Crow.

By the way, you can also spot the red planet Mars between Venus and Jupiter, as shown on the chart at the top of this post. The green line on the chart depicts the ecliptic – Earth’s orbital plane projected onto the dome of sky – and thus the sun’s apparent yearly path through the constellations of the Zodiac.

Dates of sun’s entry into each constellation of the Zodiac

Because the planets of our solar system orbit the sun on nearly the same plane as Earth, you know you can always look for planets on or near the ecliptic, or the sun’s annual path in front of the backdrop stars.

Bottom line: Watch for the brilliant planet Venus near the bright star Spica in late November and early December, 2015.

EarthSky astronomy kits are perfect for beginners. Order today from the EarthSky store

Donate: Your support means the world to us



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News digest – children’s cancer death rates fall, Spending Review, childhood obesity stats and…meat sales?

What has happened to sausage sales?
What has happened to sausage sales?
  • Children’s cancer death rates have fallen by almost a quarter in the last 10 years, according to our latest figures. The Mirror, Sun and Sky News covered this, and we caught up with children’s cancer expert, Professor Richard Gilbertson, to get his take on the improvements.
  • And two studies reinforced the need to focus on the long-term side-effects of treatment as these survival figures for children’s cancers continue to improve. Reuters has the details.
  • George Osborne announced how much money different government departments will have to spend in the next five years. Here’s our analysis of what this means for science and cancer.
  • An early-stage clinical trial in Sheffield and Manchester is set to test a new ‘Trojan-horse therapy’ that uses a patient’s immune cells to deliver a cancer-killing virus to prostate tumours. The Mail Online has the details.
  • More promising data emerged for a combination of two immunotherapy drugs – ipilimumab and nivolumab – for people with advanced melanoma, according to the Mail Online.

Number of the week

24

The percentage drop in children’s cancer death rates over the last 10 years

  • And early lab research revealed that combining an immunotherapy drug with the breast cancer drug trastuzumab (Herceptin) could shrink drug-resistant tumours in mice. The Mail Online had this story too, but it’s still early days.
  • Scientists around the world are very excited about how a new gene-editing technology, called CRISPR, could help understand what fuels cancer. This article from The Atlantic explains why.
  • The Government has been urged to act immediately in response to the “alarming” number of children who are overweight or obese when leaving primary school in England. We covered the latest figures, as did the Guardian and BBC.
  • And we looked at the three leading scientific theories behind how obesity causes cancer.
  • This article in the Guardian looked at how charities can help support the NHS.
  • The Guardian also ran this touching tribute to Professor Jane Wardle, who died last month.
  • Experts at a UK breast cancer prevention centre reported an increase in preventative double mastectomies since Angelina Jolie announced that she had undergone the procedure in 2013. We covered this, as did Sky News, the Mirror and the Mail Online.
  • Is a cheap-to-make pill worth more than futuristic therapies? Forbes explores how pricing certain cancer drugs based on what they cost to manufacture might make sense (if you ignore how much it costs to develop the drug in the first place).

And finally

  • Bacon and sausage sales have been burned following the recent World Health Organisation announcement on processed meat and cancer (unless you read the Express of course). The Guardian has more on this, and here’s our blog post covering the meat of the issue.

Nick



from Cancer Research UK - Science blog http://ift.tt/1Tdfyu3
What has happened to sausage sales?
What has happened to sausage sales?
  • Children’s cancer death rates have fallen by almost a quarter in the last 10 years, according to our latest figures. The Mirror, Sun and Sky News covered this, and we caught up with children’s cancer expert, Professor Richard Gilbertson, to get his take on the improvements.
  • And two studies reinforced the need to focus on the long-term side-effects of treatment as these survival figures for children’s cancers continue to improve. Reuters has the details.
  • George Osborne announced how much money different government departments will have to spend in the next five years. Here’s our analysis of what this means for science and cancer.
  • An early-stage clinical trial in Sheffield and Manchester is set to test a new ‘Trojan-horse therapy’ that uses a patient’s immune cells to deliver a cancer-killing virus to prostate tumours. The Mail Online has the details.
  • More promising data emerged for a combination of two immunotherapy drugs – ipilimumab and nivolumab – for people with advanced melanoma, according to the Mail Online.

Number of the week

24

The percentage drop in children’s cancer death rates over the last 10 years

  • And early lab research revealed that combining an immunotherapy drug with the breast cancer drug trastuzumab (Herceptin) could shrink drug-resistant tumours in mice. The Mail Online had this story too, but it’s still early days.
  • Scientists around the world are very excited about how a new gene-editing technology, called CRISPR, could help understand what fuels cancer. This article from The Atlantic explains why.
  • The Government has been urged to act immediately in response to the “alarming” number of children who are overweight or obese when leaving primary school in England. We covered the latest figures, as did the Guardian and BBC.
  • And we looked at the three leading scientific theories behind how obesity causes cancer.
  • This article in the Guardian looked at how charities can help support the NHS.
  • The Guardian also ran this touching tribute to Professor Jane Wardle, who died last month.
  • Experts at a UK breast cancer prevention centre reported an increase in preventative double mastectomies since Angelina Jolie announced that she had undergone the procedure in 2013. We covered this, as did Sky News, the Mirror and the Mail Online.
  • Is a cheap-to-make pill worth more than futuristic therapies? Forbes explores how pricing certain cancer drugs based on what they cost to manufacture might make sense (if you ignore how much it costs to develop the drug in the first place).

And finally

  • Bacon and sausage sales have been burned following the recent World Health Organisation announcement on processed meat and cancer (unless you read the Express of course). The Guardian has more on this, and here’s our blog post covering the meat of the issue.

Nick



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088/366: Geese [Uncertain Principles]

So, today, we engaged in the traditional Black Friday activity of, um, going to the park and chasing birds:

SteelyKid and The Pip scaring geese with their swords at the park on the day after Thanksgiving.

SteelyKid and The Pip scaring geese with their swords at the park on the day after Thanksgiving.

It was an unbelievably warm day for late November– if you look closely, you can see that SteelyKid is wearing shorts and a T-shirt– so we couldn’t very well sit inside. So we went across to the other side of Whitney Point Lake to Dorchester Park to let the kids run around. We hiked up the stream, played on the playground, and chased the big flocks of Canada geese into the lake.

This did serve the intended purpose of tiring the kids out. Also, tiring me out, because I took an hour-and-a-half nap after lunch. But hey, it’s Thanksgiving…



from ScienceBlogs http://ift.tt/1Q3zWhO

So, today, we engaged in the traditional Black Friday activity of, um, going to the park and chasing birds:

SteelyKid and The Pip scaring geese with their swords at the park on the day after Thanksgiving.

SteelyKid and The Pip scaring geese with their swords at the park on the day after Thanksgiving.

It was an unbelievably warm day for late November– if you look closely, you can see that SteelyKid is wearing shorts and a T-shirt– so we couldn’t very well sit inside. So we went across to the other side of Whitney Point Lake to Dorchester Park to let the kids run around. We hiked up the stream, played on the playground, and chased the big flocks of Canada geese into the lake.

This did serve the intended purpose of tiring the kids out. Also, tiring me out, because I took an hour-and-a-half nap after lunch. But hey, it’s Thanksgiving…



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Ask Ethan: Can Two Planets Share The Same Orbit? (Synopsis) [Starts With A Bang]

“We are not like the social insects. They have only the one way of doing things and they will do it forever, coded for that way. We are coded differently, not just for binary choices, go or no-go. We can go four ways at once, depending on how the air feels: go, no-go, but also maybe, plus what the hell let’s give it a try.” -Lewis Thomas

One of the most important characteristics of a planet, at least according to the IAU definition, is that it clear its orbit of all other bodies. But if we allowed for a special caveat — the possibility of two similarly-sized objects sharing the same orbit — could we have a stable configuration where that occurred?

Image credit: Wikimedia Commons user Silver Spoon.

Image credit: Wikimedia Commons user Silver Spoon.

Surprisingly, not only is the answer yes, but there are three ways to do it: to have one at the L4/L5 Lagrange point of the other, to have a close-orbiting binary planet, or to have orbit-swapping worlds, where they periodically change spots with one another. Unbelievably, our Solar System has a history of all three!

Image credit: NASA/Ames/JPL-Caltech.

Image credit: NASA/Ames/JPL-Caltech.

Come get the full story on this amazing question on this week’s Ask Ethan!



from ScienceBlogs http://ift.tt/1Ifbmtf

“We are not like the social insects. They have only the one way of doing things and they will do it forever, coded for that way. We are coded differently, not just for binary choices, go or no-go. We can go four ways at once, depending on how the air feels: go, no-go, but also maybe, plus what the hell let’s give it a try.” -Lewis Thomas

One of the most important characteristics of a planet, at least according to the IAU definition, is that it clear its orbit of all other bodies. But if we allowed for a special caveat — the possibility of two similarly-sized objects sharing the same orbit — could we have a stable configuration where that occurred?

Image credit: Wikimedia Commons user Silver Spoon.

Image credit: Wikimedia Commons user Silver Spoon.

Surprisingly, not only is the answer yes, but there are three ways to do it: to have one at the L4/L5 Lagrange point of the other, to have a close-orbiting binary planet, or to have orbit-swapping worlds, where they periodically change spots with one another. Unbelievably, our Solar System has a history of all three!

Image credit: NASA/Ames/JPL-Caltech.

Image credit: NASA/Ames/JPL-Caltech.

Come get the full story on this amazing question on this week’s Ask Ethan!



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A Buoy-Only Sea Surface Temperature Record Supports NOAA’s Adjustments

This is an update of an update of an article which originally appeared at Climate Etc. The authors are grateful for the helpful comments which have informed the updates.

By Zeke Hausfather and Kevin Cowtan

Significant recent media and political attention has been focused on the new NOAA temperature record, which shows considerably more warming than their prior record during the period from 1998 to present. The main factor behind these changes is the correction in ocean temperatures to account for the transition from ship engine room intake measurement to buoy-based measurements and a calibration of differences across ships using nighttime marine air temperatures (NMAT). Here we seek to evaluate the changes to the NOAA ocean temperature record by constructing a new buoy-only sea surface temperature record. We find that a record using only buoys (and requiring no adjustments) is effectively identical in trend to the new NOAA record and significantly higher than the old one.

The changes to the prior NOAA global land/ocean temperature series are shown in Figure 1. There are some large changes in the 1930s that are interesting but have little impact on century-scale trends. The new NOAA record also increases temperatures in recent years, resulting a in a record where the period subsequent to 1998 has a trend identical to the period from 1950-1997 (and giving rise to the common claim that the paper was “busting” the recent slowdown in warming).

Figure 1
Figure 1: New and old homogenized global land/ocean records from Karl et al, 2015.

The paper that presented the revised record, Karl et al, didn’t actually do much that was new. Rather, they put together two previously published records: an update to the NOAA sea surface temperature record (called ERSST) from version 3 to version 4, and the incorporation of a new land record from the International Surface Temperature Initiative (ISTI) that makes use of around 32,000 land stations rather than the 7,000 or so GHCN-Monthly stations previously utilized. The new land record is quite similar to that produced by Berkeley Earth, though it has relatively little impact on the temperature trend vis-à-vis the old land record, particularly during the recent 1998-present period.

The slowdown-busting nature of the Karl et al paper relies almost entirely on the update from ERSST v3b to v4. During the post 1998 period, this is primarily due to a revised treatment of buoys and ship engine room intake (ERI) measurements and an improved calibration of differences across ships. During the past few decades the number of automated SST measurement buoys has expanded rapidly from effectively zero before 1980 to over 70 percent of all SST measurements today as shown in the figure below. Buoys are appealing measurement platforms, as they are not restricted to shipping routes and often have fully automated reporting via satellite uplink.

Figure 2Figure 2: Share of SST observations by instrument type from Kennedy et al 2011. Note that this figure ends in 2006; since then buoys have continued to grow in observation share.

NOAA argues that the transition to buoys introduced a spurious cooling bias into the record. ERIs tend to warm the water a bit before measuring it (ship engine rooms being rather hot), whereas buoys do not. They identify a bias of around 0.1 C between buoys and ERIs and remove it by adjusting buoy records up to match ERI records in ERSST v4, as well as use NMAT readings to calibrate the differences across ships. These adjustments had not been done in the prior ERSST v3b. As an aside, the decision to adjust buoys up to ERIs or ERIs down to buoys should nominally be trend neutral. Indeed, in their work on HadSST3 Kennedy and colleagues explicitly tested this, and found “no appreciable difference” on trends.

However, there is a rather straightforward way for us to test if the adjustments done in ERSST v4 are proper or not: compare their adjusted record to a record made only from buoys. The buoy records are from purpose built instruments which are largely standardized, resulting in much more homogeneous record [details]. On the other hand, the buoy record is short, and has limited coverage in the early 90's.

The buoy-only record is prepared by calculating daily averages for each buoy. Buoys which show a large daily temperature variation are rejected: in deep water the daily temperature range is only a few tenths of a degree, but in very shallow water it can be substantial which presents problems when some data are missing. Next, the daily data are placed into 550 x550km equal area grid cells based on the location of the buoy for that day, and monthly averages are determined for each cell.

The resulting coverage is still limited and so produces a biased estimate of global sea surface temperature. To produce a useful comparison to ERSST, we therefore reduce the coverage of the ERSST datasets to match the buoy dataset (now using a fine 1 degree grid for all the data) and then calculate anomalies for all the datasets using a 2001-2010 baseline. The area weighted mean temperature is then calculated for each record. While this doesn't provide a very good estimate of global SST, it does allow a strict like-with-like comparison against ERSST over the regions where the buoys have coverage. The percent of global ocean covered by buoy measurements varies from around 40% in the mid 1990s to around 70% in recent years.

Figure 3
Figure 3: ERSST v3b, v4, and Buoy-Only SST anomalies and trends from 1995 through the end of 2014. The trend periods shown are the full record (1995-2014) and the “hiatus” period (1998-2014). 2015 is excluded as the year is incomplete, and the period prior to 1995 is excluded due to limited buoy coverage. The anomaly graph is baselined to 1995-2005 to show the time-evolution of differences.

As shown in Figure 3, a buoy-only record is quite similar to the ERSST v4 but shows statistically significantly more warming than ERSST v3b during the period from 1995 through the end of 2014 (p < 0.05 trend in the differences). This suggests that ERSST v3b suffered a cooling bias when blending buoy and ship records that is properly corrected in ERSST v4, at least for the areas where both ship and buoy records are available. Because the buoy record is relatively homogenous and requires no adjustments, it provides a good check in the validity of the combined ship-buoy series when normalized for spatial coverage.

In addition to the buoy-only dataset, we can also examine data from ARGO floats (which are not included in our buoy dataset). The ARGO floats have fairly good spatial coverage over the period since 2005. They are primarily intended to measure deep ocean temperatures, but also measure sea surface temperatures during their ascent from the depths to the surface. NOAA provides another sea surface dataset called OISST, which includes data from ships, buoys, and satellites. There are two versions of OISST: a daily version which is newer and includes adjustments to account for the transition from ships to buoys, and a weekly version which does not include this correction. Figure 4 shows how both the ARGO record and daily OISST record compare to ERSST v3b, v4, and our new buoy-only record when spatial coverage is normalized across all records.

Figure 4
Figure 4: ERSST v3b, v4, and buoy-only, ARGO, and OISST SST anomalies from 1995 through the end of 2014. The anomalies shown are relative to a 1995-2005 period; the ARGO record is too short for this baseline and instead is matched to the buoy-only record during the period of overlap.

Over the period from 2005 to 2014, ARGO buoys show statistically significantly more warming than ERSST v3b (p < 0.05 using an ARMA[1,1] model), but indistinguishable from ERSST v4 or the buoy-only record. Similarly, OISST has the highest trend of all series over the 1995-2014 period. The trends of all series over these two periods are shown in Figure 5.

Figure 5
Figure 5: ERSST v3b, v4, and buoy-only, ARGO, and OISST SST trends from 1995-2014 and 2005-2014. The latter period is chosen to compare ARGO to other records, as the ARGO record does not have sufficient coverage prior to 2005. Confidence intervals are calculated using an ARMA[1,1] model to account for autocorrelation. Note: the confidence intervals indicate the uncertainty in the trends, which is dominated by interannual variability. The uncertainty in the trend in the differences is much lower, leading to a statistically significant difference between the buoys and ERSSTv3b.

The ship records are important because they form the foundation for a long sea surface temperature record, but they require careful calibration. The differences between HadSST3 and ERSSTv4 suggest that the finer details of the ship record are not yet settled, and as a result care is required especially when considering short term trends. However the buoy data, ARGO floats, and daily OISST record all support the NOAA claim that ERSSTv3b suffered a significant cool bias over recent years arising from inhomogeneities in the ship record and the increasing use of buoys.

Code for downloading and processing the data for this analysis is available here: http://ift.tt/1QCAGvM. While the code and data are only 18 MB, the (optional) raw buoy data are approximately 44 GB. Gridded 1x1 files are also provided for buoy, ERSSTv3b, and ERSSTv4 data.



from Skeptical Science http://ift.tt/1kXTfxZ

This is an update of an update of an article which originally appeared at Climate Etc. The authors are grateful for the helpful comments which have informed the updates.

By Zeke Hausfather and Kevin Cowtan

Significant recent media and political attention has been focused on the new NOAA temperature record, which shows considerably more warming than their prior record during the period from 1998 to present. The main factor behind these changes is the correction in ocean temperatures to account for the transition from ship engine room intake measurement to buoy-based measurements and a calibration of differences across ships using nighttime marine air temperatures (NMAT). Here we seek to evaluate the changes to the NOAA ocean temperature record by constructing a new buoy-only sea surface temperature record. We find that a record using only buoys (and requiring no adjustments) is effectively identical in trend to the new NOAA record and significantly higher than the old one.

The changes to the prior NOAA global land/ocean temperature series are shown in Figure 1. There are some large changes in the 1930s that are interesting but have little impact on century-scale trends. The new NOAA record also increases temperatures in recent years, resulting a in a record where the period subsequent to 1998 has a trend identical to the period from 1950-1997 (and giving rise to the common claim that the paper was “busting” the recent slowdown in warming).

Figure 1
Figure 1: New and old homogenized global land/ocean records from Karl et al, 2015.

The paper that presented the revised record, Karl et al, didn’t actually do much that was new. Rather, they put together two previously published records: an update to the NOAA sea surface temperature record (called ERSST) from version 3 to version 4, and the incorporation of a new land record from the International Surface Temperature Initiative (ISTI) that makes use of around 32,000 land stations rather than the 7,000 or so GHCN-Monthly stations previously utilized. The new land record is quite similar to that produced by Berkeley Earth, though it has relatively little impact on the temperature trend vis-à-vis the old land record, particularly during the recent 1998-present period.

The slowdown-busting nature of the Karl et al paper relies almost entirely on the update from ERSST v3b to v4. During the post 1998 period, this is primarily due to a revised treatment of buoys and ship engine room intake (ERI) measurements and an improved calibration of differences across ships. During the past few decades the number of automated SST measurement buoys has expanded rapidly from effectively zero before 1980 to over 70 percent of all SST measurements today as shown in the figure below. Buoys are appealing measurement platforms, as they are not restricted to shipping routes and often have fully automated reporting via satellite uplink.

Figure 2Figure 2: Share of SST observations by instrument type from Kennedy et al 2011. Note that this figure ends in 2006; since then buoys have continued to grow in observation share.

NOAA argues that the transition to buoys introduced a spurious cooling bias into the record. ERIs tend to warm the water a bit before measuring it (ship engine rooms being rather hot), whereas buoys do not. They identify a bias of around 0.1 C between buoys and ERIs and remove it by adjusting buoy records up to match ERI records in ERSST v4, as well as use NMAT readings to calibrate the differences across ships. These adjustments had not been done in the prior ERSST v3b. As an aside, the decision to adjust buoys up to ERIs or ERIs down to buoys should nominally be trend neutral. Indeed, in their work on HadSST3 Kennedy and colleagues explicitly tested this, and found “no appreciable difference” on trends.

However, there is a rather straightforward way for us to test if the adjustments done in ERSST v4 are proper or not: compare their adjusted record to a record made only from buoys. The buoy records are from purpose built instruments which are largely standardized, resulting in much more homogeneous record [details]. On the other hand, the buoy record is short, and has limited coverage in the early 90's.

The buoy-only record is prepared by calculating daily averages for each buoy. Buoys which show a large daily temperature variation are rejected: in deep water the daily temperature range is only a few tenths of a degree, but in very shallow water it can be substantial which presents problems when some data are missing. Next, the daily data are placed into 550 x550km equal area grid cells based on the location of the buoy for that day, and monthly averages are determined for each cell.

The resulting coverage is still limited and so produces a biased estimate of global sea surface temperature. To produce a useful comparison to ERSST, we therefore reduce the coverage of the ERSST datasets to match the buoy dataset (now using a fine 1 degree grid for all the data) and then calculate anomalies for all the datasets using a 2001-2010 baseline. The area weighted mean temperature is then calculated for each record. While this doesn't provide a very good estimate of global SST, it does allow a strict like-with-like comparison against ERSST over the regions where the buoys have coverage. The percent of global ocean covered by buoy measurements varies from around 40% in the mid 1990s to around 70% in recent years.

Figure 3
Figure 3: ERSST v3b, v4, and Buoy-Only SST anomalies and trends from 1995 through the end of 2014. The trend periods shown are the full record (1995-2014) and the “hiatus” period (1998-2014). 2015 is excluded as the year is incomplete, and the period prior to 1995 is excluded due to limited buoy coverage. The anomaly graph is baselined to 1995-2005 to show the time-evolution of differences.

As shown in Figure 3, a buoy-only record is quite similar to the ERSST v4 but shows statistically significantly more warming than ERSST v3b during the period from 1995 through the end of 2014 (p < 0.05 trend in the differences). This suggests that ERSST v3b suffered a cooling bias when blending buoy and ship records that is properly corrected in ERSST v4, at least for the areas where both ship and buoy records are available. Because the buoy record is relatively homogenous and requires no adjustments, it provides a good check in the validity of the combined ship-buoy series when normalized for spatial coverage.

In addition to the buoy-only dataset, we can also examine data from ARGO floats (which are not included in our buoy dataset). The ARGO floats have fairly good spatial coverage over the period since 2005. They are primarily intended to measure deep ocean temperatures, but also measure sea surface temperatures during their ascent from the depths to the surface. NOAA provides another sea surface dataset called OISST, which includes data from ships, buoys, and satellites. There are two versions of OISST: a daily version which is newer and includes adjustments to account for the transition from ships to buoys, and a weekly version which does not include this correction. Figure 4 shows how both the ARGO record and daily OISST record compare to ERSST v3b, v4, and our new buoy-only record when spatial coverage is normalized across all records.

Figure 4
Figure 4: ERSST v3b, v4, and buoy-only, ARGO, and OISST SST anomalies from 1995 through the end of 2014. The anomalies shown are relative to a 1995-2005 period; the ARGO record is too short for this baseline and instead is matched to the buoy-only record during the period of overlap.

Over the period from 2005 to 2014, ARGO buoys show statistically significantly more warming than ERSST v3b (p < 0.05 using an ARMA[1,1] model), but indistinguishable from ERSST v4 or the buoy-only record. Similarly, OISST has the highest trend of all series over the 1995-2014 period. The trends of all series over these two periods are shown in Figure 5.

Figure 5
Figure 5: ERSST v3b, v4, and buoy-only, ARGO, and OISST SST trends from 1995-2014 and 2005-2014. The latter period is chosen to compare ARGO to other records, as the ARGO record does not have sufficient coverage prior to 2005. Confidence intervals are calculated using an ARMA[1,1] model to account for autocorrelation. Note: the confidence intervals indicate the uncertainty in the trends, which is dominated by interannual variability. The uncertainty in the trend in the differences is much lower, leading to a statistically significant difference between the buoys and ERSSTv3b.

The ship records are important because they form the foundation for a long sea surface temperature record, but they require careful calibration. The differences between HadSST3 and ERSSTv4 suggest that the finer details of the ship record are not yet settled, and as a result care is required especially when considering short term trends. However the buoy data, ARGO floats, and daily OISST record all support the NOAA claim that ERSSTv3b suffered a significant cool bias over recent years arising from inhomogeneities in the ship record and the increasing use of buoys.

Code for downloading and processing the data for this analysis is available here: http://ift.tt/1QCAGvM. While the code and data are only 18 MB, the (optional) raw buoy data are approximately 44 GB. Gridded 1x1 files are also provided for buoy, ERSSTv3b, and ERSSTv4 data.



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Friday Cephalopod: Ever have one of those days where you have a tough time telling where your food ends and you begin? [Pharyngula]



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