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Thursday, May 28, 2009

ICOADS Monthly Tropical and Extratropical SST Samplings from 1800 to 2008

I’ve moved to WordPress.  This post can now be found at ICOADS Monthly Tropical and Extratropical SST Samplings from 1800 to 2008
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I regularly mention in ENSO posts that there was little SST sampling in the eastern equatorial Pacific prior to the opening of the Panama Canal in 1914, that the reader needs to keep that in mind when viewing early NINO3.4 data.

BUT THE SAME HOLDS TRUE FOR ALL SST DATA

The farther back in time we explore, the less accurate the SST data becomes because of the minimal sampling in early years.

I’m working on a post about a curious dataset created by JISAO, the Global-SST ENSO Index.
http://www.jisao.washington.edu/data_sets/globalsstenso/
Attached to it are listings of the number of monthly tropical and extratropical ICOADS SST readings (the last two columns here)…
http://www.jisao.washington.edu/data_sets/globalsstenso/globalsstenso18002008.ascii
…which I’ve broken down into five graphs. It’s very easy to see why the Hadley Centre and the NCDC don’t present SST anomaly data before 1850.
http://i42.tinypic.com/2w53hip.jpg
1800 to 2008
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http://i41.tinypic.com/3502ka1.jpg
1800 to 1849
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http://i44.tinypic.com/1zevwv8.jpg
1850 to 1899
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http://i43.tinypic.com/2m6jrwg.jpg
1900 to 1949
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http://i42.tinypic.com/14tlvmq.jpg
1950 to 2008

Wednesday, May 27, 2009

Animations of Ocean Heat Content, Depth-Averaged Temperature, And Sea Surface Height

I’ve moved to WordPress.  This post can now be found at Animations of Ocean Heat Content, Depth-Averaged Temperature, And Sea Surface Height
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OPENING NOTE

I created two animations and discovered a third while I was trying to find a way to illustrate a specific process. I haven’t been successful in showing that process, but I’ve elected to post the videos for those who would like different views of other ocean processes, currents, and the like.

UPDATE January 28, 2010: In a later post, Animation Of NODC Ocean Heat Content Data (0-700 Meters) 1955 to 2009, I used the mapping graphics capabilities of the KNMI Climate Explorer to create another OHC animation. I’ve linked it here for convenience. It's much better than the animation of the maps provided by the NODC.


http://www.youtube.com/watch?v=dVeQ2tW24xoYouTube Link

Back To The Original Post
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THE ANIMATION OF THE OHC MAPS WAS DISAPPOINTING

Levitus et al provided OHC maps as supplemental material for their 2009 paper “Global Ocean Heat Content 1955–2008 in Light of Recently Revealed Instrumentation Problems”. Link to the paper:
ftp://ftp.nodc.noaa.gov/pub/data.nodc/woa/PUBLICATIONS/grlheat08.pdf
Link to the supplemental material:
http://www.nodc.noaa.gov/OC5/3M_HEAT_CONTENT/index.html
Link to the OHC “maps page”:
http://www.nodc.noaa.gov/cgi-bin/OC5/3M_HEAT/showfigheat.pl?action=start

The animation of the OHC maps wasn’t as noisy as the Sea Surface Height Video from JPL that I used in The Lingering Effects of the 1997/98 El Nino, but the OHC maps illustrated quarterly data, so there were gaps in the data from frame to frame. This can be seen by clicking on the last link above and selecting “Show Animation.” By downloading the maps and creating my own animation I had hoped to be able to prompt something, anything, worthwhile by adjusting the speed. But other than reddish brown blobs moving around on a background of blue, I’ve had no luck. Another problem was the very limited color coding of the maps. The positive OHC is a reddish brown, while the negative OHC is blue. That’s the extent of the color coding. Refer to Figure 1.


http://i44.tinypic.com/2gumuco.jpg
Figure 1

As you can see, the gradients of positive and negative OHC are not colored to illustrate intensity. With those limitations, the OHC map animation is not very informative.

YouTube Link
http://www.youtube.com/watch?v=e2Zt_LsL1c8

Then on the other hand…

THE DEPTH-AVERAGED TEMPERATURE MAP ANIMATION WAS MUCH MORE INFORMATIVE

The European Centre for Medium-Range Weather Forecasts (ECMWF) provides various views of a number of datasets in their S2 Ocean Reanalyses and Real-Time Ocean Analyses web pages. ECMWF Link:
http://www.ecmwf.int/products/forecasts/d/charts/ocean/

The ocean reanalysis record starts in 1959. It is updated with an 11-day delay. ECMWF Link:
http://www.ecmwf.int/products/forecasts/d/charts/ocean/reanalysis/

Selecting “Horizontal Maps” and then selecting “Temp averaged in upper 300m” in the drop-down menu under “Field” will bring you to the maps of depth-averaged temperature used in this video. Refer to Figure 2. ECMWF Link:
http://www.ecmwf.int/products/forecasts/d/charts/ocean/reanalysis/xymaps/Monthly!monthly!200904!Anomaly!Temp%20averaged%20in%20upper%20300m!global!/

A sample ECMWF depth-averaged temperature map is shown in Figure 2. Note in the temperature scale to the right that anomalies between -0.5 to +0.5 deg C are not shown. This definitely reduces noise.
http://i44.tinypic.com/iop4x0.jpg
Figure 2

When I loaded the individual monthly maps into GIF Movie Gear, the animation flew past, but it showed an incredible number of currents, gyres, oceanic processes, etc. The Pacific Warm Pool makes its presence known, Figure 3, as do the NINO areas in the East Equatorial Pacific.
http://i41.tinypic.com/33w2snl.jpg
Figure 3

Easy to identify in the animation are the Kuroshio Extension, the North Atlantic Subpolar Gyre, and the Brazil-Malvinas Confluence. Occasionally, the west to east flow of the Antarctic Circumpolar Current (ACC) is also visible.
http://i41.tinypic.com/oppmdy.jpg
Figure 4

Please open the video in a new or separate window for better clarity. You may even wish to expand it to full screen.

YouTube Link
http://www.youtube.com/watch?v=ofmepknTFN4

And saving the best for last…

THE HIGH-RESOLUTION SEA SURFACE HEIGHT VIDEO

This is not the SSH video I’ve used in past posts:
Recharging The Pacific Warm Pool , and
The Lingering Effects of the 1997/98 El Nino

I discovered this animation on YouTube and contacted the author, Sebastian Krieger, for permission to use it. Sebastian identified the source of the data in his reply: NASA / JPL PO.DAAC. He wrote that he, “regridded it using an auto-correlation based weighted average algorithm.”

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Sebastian Krieger’s description of the video on YouTube reads, “15 years of sea surface height anomaly (in mm) from merged TOPEX/Poseidon and Jason-1 datasets ranging from January 1993 to December 2007.“Note the persistent structures like the western boundary currents (Kuroshio, Gulf, Brazil-Malvinas confluence, East-Australian) and the Antarctic Circumpolar Current. Look at the great oceanic gyres. See the discrete seasonal change between the northern and the southern hemispheres. Watch the massive effect of the 1997 El Niño and 1998 La Niña over the surface height. Note especially the westward propagating slow Rossby waves and the faster reflected Kelvin waves, object of my study.
“Finally if you look carefully, notice how the sea surface tends to become more and more red over the years, which means the ocean level is rising.”

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At a high resolution, the SSH animation shows the shifting of heat back and forth in the tropical Pacific associated with ENSO events. The Kuroshio Extension, the Gulf Stream, the Agulhas Current and Antarctic Circumpolar Current (ACC), Figure 5, are clearly evident.
http://i42.tinypic.com/2m6lftv.jpg
Figure 5

The Mozambique and East Madagascar Currents in the western Indian Ocean, Figure 6, are visible, as is a significant eddy where the Agulhas, Benguela, and Antarctic Circumpolar Current meet. The East Australian Current in the western South Pacific can be seen. The Brazil-Malvinas Confluence also stands out.
http://i40.tinypic.com/atslu0.jpg
Figure 6

I had downloaded the video from YouTube with the intent of providing an introduction and some commentary, but the video lost much of the resolution in the conversion. I’ve, therefore, linked the video in its original form. Again, please open the video in a new or separate window for better clarity. You may even wish to expand it to full screen and watch it in high definition. It is so clear one might be able to track how slowly (or quickly) many of the ocean currents and processes transport energy around the globe.

YouTube Link
http://www.youtube.com/watch?v=VNefCmc3_1Y&NR=1

Hopefully, Sebastian Krieger will monitor this post occasionally and answer any of your questions about the video, especially those questions pertaining to Kelvin and Rossby waves.

Monday, May 25, 2009

Revisiting “Misunderstandings About The PDO – Revised”

I’ve moved to WordPress.  This post can now be found at Revisiting “Misunderstandings About The PDO – Revised”
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My post “Misunderstandings about the PDO – REVISED” also ran at WattsUpWithThat (WUWT) and received a number of comments, some agreeing, others disagreeing. A link to the WUWT version:
http://wattsupwiththat.com/2009/04/28/misunderstandings-about-the-pacific-decadal-oscillation/

In that post, I illustrated how the Pacific Decadal Oscillation (PDO) is calculated, what it represents, and what it does not represent. I also quoted from a Newman et al (2003) paper that appears to have been controversial. Link to Newman et al:
http://www.cdc.noaa.gov/people/gilbert.p.compo/Newmanetal2003.pdf

Most bloggers do not have the time to sort through all of the comments, so I’ve reworded and expanded on a few of my replies from the WUWT version of the post. I’ve also added a few more illustrations to reinforce a specific point.

THE PDO LAGS ENSO

Bloggers many times note that El Nino events dominate ENSO during the positive phase of the PDO, and La Nina events prevail during the negative PDO phase. It would be difficult, however, for the phase of the PDO to dictate whether El Nino or La Nina events dominate an epoch if the PDO lagged ENSO. And the PDO does lag ENSO.

The calculation of the PDO is based on the methods used in the Zhang et al (1997) paper “ENSO-like Interdecadal Variability: 1900–93”. Refer to:
http://www.atmos.washington.edu/~david/zwb1997.pdf

Zhang et al refer to the PDO as “NP”, and, for an ENSO index, they use the Cold Tongue Index (CT) in place of NINO3.4 SST anomalies, which are used more frequently now. The Cold Tongue Index represents SST Anomalies of 6S-6N, 180-90W, where NINO3.4 SST Anomalies represent the area of 5S-5N, 170W-120W. In Figure 7 of Zhang et al, they illustrate the cross-correlation functions between the Cold Tongue and the other time series they examined. Note how in the bottom cell NP (PDO) lags (CT) ENSO by approximately 3 months.

http://i39.tinypic.com/14o3beb.jpg
Zhang et al Figure 7

They wrote on page 1011 (pdf page 8), “Figure 7 shows the cross-correlation function between CT and each of the other time series in Fig. 5. The lag is barely perceptible for TP and G and it increases to about a season for G - TP and NP, confirming that on the interannual timescale the remote features in THE PATTERNS SHOWN IN Fig. 6 ARE OCCURRING IN RESPONSE TO THE ENSO CYCLE RATHER THAN AS AN INTEGRAL PART OF IT, consistent with the conclusions of Alexander (1992a,b) and Yulaeva and Wallace (1994).” [Emphasis added]

Their Figure 6 shows the spatial pattern for the North Pacific associated with the PDO:
http://i44.tinypic.com/112h3k8.jpg
Zhang et al Figure 6

They also observed the interdecadal variability of the PDO (NP), but did not appear to feel it conflicted with the above findings that the PDO occurs in response to ENSO. On page 1012 (pdf page 9) they wrote, “In summary, of the time series in Fig. 8, CT is most strongly dominated by the interannual variability associated with the ENSO cycle, while G - TP and NP exhibit the clearest evidence of interdecadal variability. This distinction is also evident in the autocorrelation functions shown in Fig. 9: CT’s negative sidelobe reflects the ENSO cycle, WHILE NP’S POSITIVE VALUES OUT TO LAGS OF 5 yr AND BEYOND REFLECT THE GREATER PROMINENCE OF INTERDECADAL VARIABILITY.” [Emphasis added]

http://i41.tinypic.com/200zfk0.jpg
Zhang et al Figure 9

THE PDO, IN AND OF ITSELF, DOES NOT RAISE AND LOWER GLOBAL TEMPERATURE ACCORDING TO ITS PHASE

The PDO represents a pattern of SST anomalies; it does not represent SST anomalies of the North Pacific. In the original post, I also wrote something to the same effect. Why is this important? The often-repeated comment by many bloggers is that global temperatures rise when the PDO is positive and global temperatures decline when the PDO is negative. The visual correlation exists for that argument, but it’s the average SST anomalies for the North Pacific that dictate whether the area is contributing to or impeding the rise or fall in global temperature.

The following SST anomaly map was cropped from Figure 7 from the original post. The larger version is here:
http://i39.tinypic.com/262prfa.jpg
It shows the North Pacific, North of 20N. That is the only part of the Pacific Ocean expressed by the PDO. The PDO illustrates nothing more, only the pattern of SST variability for that area. The illustration is from the NASA Earth Observatory webpage here: http://earthobservatory.nasa.gov/IOTD/view.php?id=8703
Specifically, this linked page: http://earthobservatory.nasa.gov/images/imagerecords/8000/8703/sst_anomaly_AMSRE_2008105_lrg.jpg

http://i39.tinypic.com/4r5oxx.jpg
The Area Represented By The PDO

The illustration shows SST anomalies (Correction/clarification: It shows the PDO) in a cool phase, which means the SST anomalies in the eastern North Pacific are cool while the SST anomalies in the central and western portions are warm. But note that the warm area is significantly larger than the cool area in the east. The average SST anomalies for the North Pacific north of 20N in that case are probably positive even though the PDO is in the cool phase. And if the average SST anomaly is positive, it is contributing more positive anomalies to the global average than "normal".

The following graph illustrates the PDO and the temperature difference between the SST anomalies of the North Pacific north of 20N (the same area as the PDO) and Global Temperature anomalies. That second dataset is calculated as North Pacific SST anomalies minus Global Temperature anomalies. Note that between the early 1940s and the late 1970s, the PDO was below zero (in the cool phase) for the most part. But during that same period, North Pacific SST anomalies were greater than Global temperature anomalies, so that part of the Pacific Ocean was actually contributing positive anomalies to the global average--in other words, it was heating.
http://i42.tinypic.com/345kgsk.jpg
PDO vs North Pacific SST Anomalies Minus Global Temperature Anomalies

I do understand that while the PDO is in the cool phase, other parts of the Pacific are NORMALLY cooler than normal, like the eastern tropical Pacific, like the equatorial Pacific (the NINO areas), etc. And someone could try to argue that fact. The point is, the PDO only deals with a specific area of the North Pacific. Nothing else. There is another dataset to express the pattern of variability in the entire Pacific basin, and it’s called the Interdecadal Pacific Oscillation or IPO. And there’s another dataset for discussions of the pattern of variability for the global ocean called the “G” Time Series. If someone wants to discuss the eastern equatorial Pacific SST anomalies, there are the NINO indices and the Cold Tongue Index (CTI).

TEMPERATURES IN THE PACIFIC NORTHWEST DO CORRELATE WITH THE PDO

The SST anomalies in the Northeast portion of the North Pacific tend to agree with the phase of the PDO. That is, when the PDO is positive, the SST anomalies in the Northeast “coastal region” of the North Pacific also tend to be positive. Additionally, the Eastern North Pacific SST anomalies of that near coastal area impact Western North America Land Surface Temperature anomalies, as they should. The following graph confirms that fact:

http://i41.tinypic.com/2ee8uj7.jpg
Eastern Northeast Pacific SST Anomalies vs Pacific Northwest LST Anomalies

Hence, if the PDO is positive, Pacific Northwest land surface temperature anomalies tend to be above normal, and the reverse occurs when the PDO is negative. But the Pacific Northwest only represents a small portion of the globe.

Keep in mind, on the other side of the Pacific, the Western North Pacific SST anomalies have an impact on Eastern Asian Land Surface Temperatures, and here's that graph:
http://i42.tinypic.com/20ppslw.jpg
Western North Pacific SST Anomalies vs Eastern Asian Land Surface Temperatures

The areas included in the two preceding graphs are:

http://i40.tinypic.com/v4cb6b.jpg
Areas Used For Above Two Comparisons of SST and LST

ENSO, NOT THE PDO, DOMINATES THE PACIFIC

The KNMI Climate Explorer allows users to compute and illustrate EOFs of datasets. The following series of four maps show the EOFs (November through February) of HADSST SST anomalies (1850 to 2008) for the North Pacific, North of 20N, which is the area included in the PDO. The pattern shows a positive PDO.
http://i39.tinypic.com/ztxehh.jpg
North Pacific EOFs

But in the next set of four maps of that same EOF analysis, I’ve expanded the viewing area to the entire Pacific. The eastern equatorial Pacific dominates the maps. The ENSO regions are so dominant that the color scale shifts to accommodate it, muting the North Pacific.
http://i40.tinypic.com/eitx1u.jpg
Pacific EOFs

Wednesday, May 20, 2009

Mid-May 2009 ENSO and AMO Update

I’ve moved to WordPress.  This post can now be found at Mid-May 2009 ENSO and AMO Update
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NINO3.4 SST ANOMALIES

NINO3.4 SST anomalies have continued their rise. They are still within ENSO neutral temperatures and have reached (approximately) the levels they had climbed to last July/August.
http://i40.tinypic.com/2wh4enb.jpg
Mid-May NINO3.4 SST Anomalies

AMO

I’ll use the North Atlantic SST anomalies as a proxy for the AMO. As noted in earlier posts, to illustrate the Atlantic Multidecadal Oscillation, the NOAA Earth System Research Laboratory (ESRL) simply detrends North Atlantic SST anomaly data, but they do this to a long-term SST anomaly dataset. Since the OI.v2 SST dataset that's updated weekly begins in 1990, it does not seem appropriate to detrend that North Atlantic dataset.

North Atlantic SST anomalies appear to have ended their precipitous decline. They are now hovering at approximately +0.07 deg C.
http://i43.tinypic.com/2lnwlm0.jpg
North Atlantic SST Anomalies

SOURCE

The OI.v2 SST data is available through the NOAA NOMADS system:
http://nomad3.ncep.noaa.gov/cgi-bin/pdisp_sst.sh?lite=

Update of Recent Differences Between GISS and NCDC SST Anomaly Data And A Look At The Multiple NCDC SST Datasets

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THE AVAILABILITY OF ERSST.v2 DATA

In a post at Climate Audit “Bob Tisdale on SST”, Steve McIntyre noted that NOAA has stated, regarding their ERSST data, that “V3b is now the official version. V2 will no longer be updated. It will still be available in our subdirtectory /Datasets/noaa.ersst/V2/'”
http://www.cdc.noaa.gov/data/gridded/data.noaa.ersst.html

There is no date on the notice from NOAA, and it has been my understanding for a few months that ERSST.v2 would no longer be updated.

--BUT--

The ERSST.v2 data available through the KNMI Climate Explorer is current through April 2009. Go figure.


Thanks again to Steve McIntyre.


THE REASON FOR DELETING THE SATELLITE DATA FROM THE ERSST.v3 DATA

Reynolds, Smith, and Liu gave the reasons for removing the satellite data from ERSST.v3 data as, “In the ERSST version 3 on this web page WE HAVE REMOVED SATELLITE DATA from ERSST and the merged product. The addition of satellite data caused problems for many of our users. Although, the satellite data were corrected with respect to the in situ data as described in reprint, there was a residual cold bias that remained as shown in Figure 4 there. The bias was strongest in the middle and high latitude Southern Hemisphere where in situ data are sparse. THE RESIDAL BIAS LED TO A MODEST DECREASE IN THE GLOBAL WARMING TREND AND MODIFIED GLOBAL ANNUAL TEMPERATURE RANKINGS.” [Emphasis added.]

The link for that quote is here:
http://www.ncdc.noaa.gov/oa/climate/research/sst/papers/merged-product-v3.pdf

So, how much did the removal of the satellite data change the appearance of the Southern Ocean data? Figure 1 is a comparison of the ERSST.v3 and ERSST.v3b versions of the Southern Ocean SST anomalies from January 1970 to April 2008, smoothed with a 12-month running-average filter. It clearly shows the change to the annual temperature rankings of the Southern Ocean.

http://i40.tinypic.com/2zg9i5h.jpg
Figure 1

Figure 2 is a long-term comparison of the ERSST.v3 and ERSST.v3b SST Anomaly data for the Southern Ocean, smoothed with a 37-month filter. With the smoothing, the ERSST.v3 version has been cooling since the 1980s, and in the ERSST.v3b version, the cooling was delayed for more than a decade. There also appear to have been some other adjustments made to the earlier data that would not have been a part of the satellite data fix.
http://i40.tinypic.com/2rw6sg7.jpg
Figure 2

SOURCES

The ERSST.v3b SST anomaly data is available through the NCDC’s ERSST.v3 webpage:
http://www.ncdc.noaa.gov/oa/climate/research/sst/ersstv3.php
Link to the available datasets:
ftp://eclipse.ncdc.noaa.gov/pub/ersstv3b/pdo
I used this dataset for this post:
ftp://eclipse.ncdc.noaa.gov/pub/ersstv3b/pdo/aravg.mon.ocean.90S.60S.asc

I used the obsolete ERSST.v3 I had on file for the comparison graphs.

Monday, May 18, 2009

Recent Differences Between GISS and NCDC SST Anomaly Data And A Look At The Multiple NCDC SST Datasets

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OR There are Increases in Trend with Each Update While The Causes of Downward Biases Are Deleted

In the recent WUWT post Something hinky this way comes: NCDC data starts diverging from GISS, the differences between GISS and NCDC global temperature anomaly data was discussed. I commented that the GISS and NCDC global surface temperature anomaly data relied on two different SST datasets.

NCDC has their own SST anomaly dataset for their global surface temperature product, and they calculate anomalies against the base years of 1901 to 2000. GISS has used the NCDC OI.v2 SST anomaly data since December 1981, and before that they had used the Hadley Centre’s HADSST data. GISS then splices the two datasets together. This post does not discuss the HADSST data, but delves into the differences between the multiple NCDC SST anomaly datasets, one of which is used by GISS.

GRAPHS OF GLOBAL OI.v2 (USED BY GISS) and “NCDC Ocean” SST ANOMALY DATA

I have not been able to find GISS SST anomaly data as a separate dataset, so for a short-term comparison, I’ll use their source, the OI.v2 SST anomaly data available through the NOAA NOMADS system. Unfortunately, the OI.v2 SST data uses a third climatology for their anomalies (with base years of 1971-2000), but don’t let that concern you. It just makes for an unusual comparative graph.

Figure 1 is a short-term comparison (November 1981 to April 2009) of the OI.v2 Global SST anomaly data (used by GISS) and the NCDC’s “Global Ocean Temperature”. The NCDC data is available toward the bottom of the NCDC Global Surface Temperature Anomalies webpage here:
http://www.ncdc.noaa.gov/oa/climate/research/anomalies/index.php
Specifically:
ftp://ftp.ncdc.noaa.gov/pub/data/anomalies/monthly.ocean.90S.90N.df_1901-2000mean.dat
http://i41.tinypic.com/sec4kh.jpg
Figure 1

The two datasets appear to track one another, and the obvious difference, the shift in the data, is a result of the different base years. But if we subtract the OI.v2 SST data from the NCDC “Global Ocean” SST anomaly data, we can see that one dataset rose more than the other since November 1981. Refer to Figure 2. The NCDC “Global Ocean” SST anomaly dataset rose at a greater rate than the OI.v2 SST anomaly data that’s used by GISS. This would bias the NCDC global surface temperature upward over this time span, or bias the GISS data down, depending on your point of view.
http://i39.tinypic.com/qzlsvo.jpg
Figure 2

So to conclude this section of this post, part of the difference between the GISS and NCDC global surface temperatures discussed in WUWT post Something hinky this way comes: NCDC data starts diverging from GISS results from the use of different SST anomaly datasets.

WHAT’S THE DIFFERENCE BETWEEN THE TWO DATASETS?

The use of satellite data appears to have an impact.

NOAA describes the Optimum Interpolation (OI.v2) SST anomaly data (used by GISS) as, “The optimum interpolation (OI) sea surface temperature (SST) analysis is produced weekly on a one-degree grid. The analysis uses in situ and satellite SST's plus SST's simulated by sea-ice cover.” The in situ data is from buoy and ship measurements. The full description of the OI.v2 data is here:
http://www.cdc.noaa.gov/data/gridded/data.noaa.oisst.v2.html

The NCDC identifies the “Global Ocean Temperature” dataset as SR05 in its Global Surface Temperature Anomalies webpage:
http://www.ncdc.noaa.gov/oa/climate/research/anomalies/index.php#sr05

Linked to the webpage is a paper by Smith et al (2005) “New surface temperature analyses for climate monitoring” GEOPHYSICAL RESEARCH LETTERS, VOL. 32, L14712, doi:10.1029/2005GL023402, 2005.
http://www.ncdc.noaa.gov/oa/climate/research/Smith-comparison.pdf

On page 2, Smith et al describe the SR05 data as, “The SR05 SST is based on the International Comprehensive Ocean Atmosphere Data Set (ICOADS [Woodruff et al., 1998]). It uses different, though similar, historical bias adjustments to account for the change from bucket measurements to engine intake SSTs [Smith and Reynolds, 2002]. In addition, SR05 is based on in situ data.”

It appears, from that quote and the rest of the paper, the SR05 SST dataset does NOT use satellite data. This is consistent with NCDC’s other long-term SST datasets. They also abstain from satellite data.

COMPARISON OF SR05 TO THE NCDC’s OTHER TWO SST ANOMALY DATSETS

In addition to the SR05 SST data, the NCDC also has two other long-term SST datasets called Extended Reconstructed SST (ERSST) data. The ERSST.v2 (Version 2) data was introduced in 2004 with the Smith and Reynolds (2004) paper Improved Extended Reconstruction of SST (1854-1997), Journal of Climate, 17, 2466-2477. Many of my early Smith and Reynolds SST Posts used ERSST.v2 data through the NOAA NOMADS system. Unfortunately, ERSST.v2 data is no longer available through that NOAA system, so the latest ERSST.v2 global SST anomaly data from NOMADS I have on file runs through October 2008.

The ERSST.v2 data was updated with ERSST.v3 data. In my opinion, it provides the most detailed analysis of high latitude SST in the Southern Hemisphere (the Southern Ocean). The ERSST.v3 data was introduced last year with the Smith et al (2008) paper: Improvements to NOAA's Historical Merged Land-Ocean Surface Temperature Analysis (1880-2006), Journal of Climate,21, 2283-2296. The NCDC updated it with their ERSST.v3b version later in 2008, but more on that later. A limited number of datasets (based on latitude) for the ERSST.v3b data are available from NCDC (though it is available on a user-selected coordinate basis through the KNMI Climate Explorer website, as is ERSST.v2 data).

I have found no source of SR05 SST anomaly data, other than the Global, Northern Hemisphere, and Southern Hemisphere "Ocean Temperature" datasets linked to the Global Surface Temperature webpage.

Figures 3 and 4 are long-term comparisons (1880 to “present”) of the “NCDC Global Ocean” (SR05) SST anomaly data to the ERSST.v2 and to the ERSST.v3b SST anomalies. Based on the linear trends, the “NCDC Global Ocean” (SR05) data resides between the older ERSST.v2 and the more recent ERSST.v3b data.
http://i40.tinypic.com/am84ma.jpg
Figure 3
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http://i43.tinypic.com/2u9pwk6.jpg
Figure 4

But note that the trend increases with each SST dataset improvement.

THE ERSST.v3 DATASET ONCE USED SATELLITE DATA

In “Improvements to NOAA's Historical Merged Land-Ocean Surface Temperature Analysis (1880-2006)”, Smith et al note the use of satellite data for ERSST.v3 data in their abstract, “Beginning in 1985, improvements are due to the inclusion of bias-adjusted satellite data.” That’s a positive description. They further proclaim, “Of the improvements, the two that have the greatest influence on global averages are better tuning of the reconstruction method and inclusion of bias adjusted satellite data since 1985.” In fact there is a whole subsection in the paper about the satellite adjustments.

WHY THEN DID THE NCDC DELETE THE SATELLITE DATA IN THE MOST RECENT VERSION, ERSST.v3b?

Reynolds, Smith, and Liu write in a November 14, 2008 attachment to their main ERSST.v3b webpage, “In the ERSST version 3 on this web page WE HAVE REMOVED SATELLITE DATA from ERSST and the merged product. The addition of satellite data caused problems for many of our users. Although, the satellite data were corrected with respect to the in situ data as described in reprint, there was a residual cold bias that remained as shown in Figure 4 there. The bias was strongest in the middle and high latitude Southern Hemisphere where in situ data are sparse. THE RESIDAL BIAS LED TO A MODEST DECREASE IN THE GLOBAL WARMING TREND AND MODIFIED GLOBAL ANNUAL TEMPERATURE RANKINGS.” [Emphasis added.]

The link for that quote is here:
http://www.ncdc.noaa.gov/oa/climate/research/sst/papers/merged-product-v3.pdf

Note that the “merged product” referenced above is their ERSST.v3b-based land plus sea surface temperature data.

Figure 5 illustrates the difference between the ERSST.v3b and ERSST.v3 global SST anomaly data (ERSST.v3 data MINUS ERSST.v3b data). The “dip” after 1985 would appear to be the satellite bias.
http://i43.tinypic.com/6yfx8h.jpg
Figure 5

Hmmm. It looks as though, if you’re a SST data producer, downward biases are bad, but increases in trend with each update are good.

SOURCES

The ERSST.v3b SST anomaly data is available through the NCDC’s ERSST.v3 webpage:
http://www.ncdc.noaa.gov/oa/climate/research/sst/ersstv3.php
Link to the available datasets:
ftp://eclipse.ncdc.noaa.gov/pub/ersstv3b/pdo
I used this dataset for this post:
ftp://eclipse.ncdc.noaa.gov/pub/ersstv3b/pdo/aravg.mon.ocean.90S.90N.asc

The NCDC’s “Global Ocean Temperature” dataset is available through:
http://www.ncdc.noaa.gov/oa/climate/research/anomalies/index.php
Specifically:
ftp://ftp.ncdc.noaa.gov/pub/data/anomalies/monthly.ocean.90S.90N.df_1901-2000mean.dat

ERSST.v2 data are no longer available through the NOAA NOMADS System. I relied on ERSST.v2 global SST anomaly data from my files for this post. I also used the ERSST.v3 I also had on file for the comparison to the ERSST.v3b data.

The OI.v2 data is available through the NOAA NOMADS system:
http://nomad3.ncep.noaa.gov/cgi-bin/pdisp_sst.sh?lite

Wednesday, May 13, 2009

Levitus et al (2009) Ocean Heat Content – Comparison of The Ocean Basin Data

I’ve moved to WordPress.  This post can now be found at Levitus et al (2009) Ocean Heat Content – Comparison of The Ocean Basin Data
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INTRODUCTION

In my post The Latest Revisions to Ocean Heat Content Data, I provided comparisons of the recent Levitus et al (2009) Ocean Heat Content (OHC) data to other recently released reconstructions. This post compares ocean basin data from the Levitus et al (2009). The OHC data are available through the NOAA National Oceanographic Data Center here:
http://www.nodc.noaa.gov/OC5/3M_HEAT_CONTENT/index.html
There is also a link to the Levitus et al (2009) paper on the webpage:
ftp://ftp.nodc.noaa.gov/pub/data.nodc/woa/PUBLICATIONS/grlheat08.pdf

COMPARSION CHART OF OHC BY BASIN

Figure 1 is a comparison chart of the OHC for the Atlantic, Indian, and Pacific Ocean basins. This presentation does not consider the differences in the areas of the three oceans. The Pacific Ocean has more than twice the surface area of the Indian Ocean and ~60% more surface area than the Atlantic Ocean. Regardless of area, the Atlantic Ocean Heat Content rose more than the OHC of the Indian and Pacific Oceans.
http://i41.tinypic.com/dmvbxj.jpg
Figure 1

AREA-ADJUSTED COMPARISON CHART

Figure 2 shows the area-adjusted OHC for the individual oceans, where the data is in terms of OHC/million sq km. The surface areas of the oceans used in Levitus et (2009) were not listed, so it’s impossible to determine if the Arctic and Southern were included in the data of the three major oceans, or if the Gulf of Mexico, Mediterranean Sea and Caribbean Sea were included in the Atlantic data. So I used the standard ocean surface areas listed in Wikipedia, but excluded the “seas” from the Atlantic: 82.4 million sq km for the Atlantic, 73.5 million sq km for the Indian, and 169.2 million sq km for the Pacific. The Atlantic Ocean heat Content has had the largest increase over the term of the data.
http://i40.tinypic.com/nxlsh4.jpg
Figure 2

Adding linear trends to the area-adjusted data, Figure 3, shows that Indian and Pacific Oceans trends were fundamentally the same. It also shows that the Atlantic Ocean Heat Content rose at a rate that was more than twice that of the Indian and Pacific Oceans.
http://i40.tinypic.com/23rpmc7.jpg
Figure 3

COMPARISONS OF SST ANOMALIES AND SSTs

The rise in the area-adjusted OHC for the Atlantic was unexpected, since the rise in the SST anomalies of the Indian Ocean exceeded the Atlantic and Pacific Oceans. Refer to Figure 4.
http://i44.tinypic.com/724p5e.jpg
Figure 4

And for those wondering about actual SSTs, Figure 5 is a comparison of Atlantic, Indian, and Pacific Ocean SSTs (not anomalies). The SST of the Atlantic Ocean is ~2.5 deg C lower than the Indian and Pacific Oceans.
http://i42.tinypic.com/24c5uh1.jpg
Figure 5

NORTH AND SOUTH ATLANTIC OHC

Curious about the rise in the OHC of the Atlantic, I plotted the North and South Atlantic OHC data, Figure 6. The rise in the North Atlantic OHC was obviously greater than in the South Atlantic.
http://i39.tinypic.com/v5ebzp.jpg
Figure 6

Again, I do not know if the Levitus et al included the Gulf of Mexico, Mediterranean Sea and Caribbean Sea in the North Atlantic data. But in Figure 7, I assumed they were excluded. I also assumed the area of the Atlantic Ocean without the additional seas (82.4 million sq km) was evenly split between the hemispheres. The rise in the area-adjusted OHC of the North Atlantic is more than twice that of the South Atlantic. And note that the linear trend of the South Atlantic is approximately twice that of the Pacific and Indian Oceans, Figure 3.
http://i41.tinypic.com/2yzfv2r.jpg
Figure 7

Why did the increase in area-adjusted Atlantic Ocean OHC more than double the rise of the Indian and Pacific Oceans? This can also be seen in the “Heat Storage Per Unit Area” values presented by Levitus et al in their Table T1. Refer to Figure 8.


If the answer lies with Atlantic Meridional Overturning Circulation, then the use of only the top 700 meters for OHC might be misleading.
http://i44.tinypic.com/pc7b9.jpg
Figure 8

Saturday, May 9, 2009

Comparison of Annual ERSST.v3b and HADISST NINO3.4 SST (Not Anomaly) Data

I’ve moved to WordPress.  This post can now be found at Comparison of Annual ERSST.v3b and HADISST NINO3.4 SST (Not Anomaly) Data
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INITIAL NOTE

This post illustrates differences between ERSST.v3b and HADISST NINO3.4 SST data. I am in no way attempting to indicate if one or the other is correct.

INTRODUCTION

In the December 18, 2008 post NINO3.4 Data Comparison--HADSST and ERSST.v3, I provided a simple comparison of the two datasets in terms of SST anomalies. This post will use SST data, not anomalies, for the NINO3.4 region. This allows illustrations of annual averages, maximums, minimums and the temperature difference between annual maximums and minimums. I’ve also smoothed the above subsets with 11-year running-average filters to help show those differences on decadal bases. There appears to be a multidecadal pseudo-periodic cycle that takes a simple analysis to uncover.

The Panama Canal opened in 1914. Prior to then, sampling of eastern equatorial Pacific SST was very sporadic. Keep that in mind when reviewing any early ENSO SST data.

BACKGROUND

The earlier post also included a few quotes from the paper “Improvements to NOAA’s Historical Merged Land–Ocean Surface Temperature Analysis (1880–2006)”, Smith and Reynolds (2008), JOURNAL OF CLIMATE, VOLUME 21, provides an explanation for the difference between the ERSST.v3 and HADSST versions. Refer to page 2293, or pdf document page 11 of 14.

http://www.ncdc.noaa.gov/oa/climate/research/sst/papers/SEA.temps08.pdf

I’ll repeat and expand one quote regarding the NINO3.4 data now:

“The all-month anomaly correlation of HadISST with ERSST.v3 in this region for 1880–1997 is 0.90. Both analyses are clearly producing consistent interannual variations. But there are important differences in this region in periods when sampling is sparse. In Niño-3.4 prior to 1950, HadISST is biased about 0.3°C warmer than ERSST.v3. Much of the bias is due to the use of different historical bias adjustments in the two analyses prior to 1942. Another important difference depends on the method used to compute low frequency variations. In HadISST they are computed by fitting data to a global mode, while here simpler averaging and filtering is used, as discussed above.”

Is the HADISST data biased warmer or the ERSST.v3b data biased cooler? That’s the question for you to decide.

ANNUAL AVERAGE SST

Figure 1 compares annual average NINO3.4 SSTs, without smoothing, for the ERSST.v3b and HADISST datasets. The annual variations do agree quite well, as noted in the Smith and Reynolds paper. The underlying differences can also be seen.

http://i44.tinypic.com/23rk2sh.jpg
Figure 1

Smoothing the two NINO3.4 SST datasets with 11-year running-average filters, Figure 2, emphasizes the differences prior to 1950. From 1900 to 1916, the decrease in the ERSST.v3b data is approximately twice that of the HADISST data.
http://i41.tinypic.com/s46hsm.jpg
Figure 2

COMPARISONS TO TROPICAL SST (SMOOTHED)

Figures 3 and 4 are comparisons of Tropical SST and annual average NINO3.4 SST data for the HADISST and ERSST.v3b datasets. The data has been smoothed with 11-year filters. The NINO3.4 region is contained within the tropics. It seemed like a logical comparison.
http://i41.tinypic.com/rutx1e.jpg
Figure 3
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http://i40.tinypic.com/4htlw3.jpg
Figure 4

ANNUAL MAXIMUM SST

The Annual Maximum NINO3.4 SSTs for the ERSST.v3b and HADISST datasets are shown in Figure 5.
http://i42.tinypic.com/inhevb.jpg
Figure 5

The smoothed Annual Maximum data, Figure 6, shows less divergence in the 1880s through 1900 than the annual averages in Figure 2.
http://i44.tinypic.com/2a0f30g.jpg
Figure 6

ANNUAL MINIMUM SST

Figure 7 illustrates the Annual Minimum NINO3.4 SSTs for the ERSST.v3b and HADISST datasets.
http://i44.tinypic.com/6p1bmv.jpg
Figure 7

And again the smoothed Annual Minimum data in Figure 8 shows the divergence from the late 1800s to ~1950.
http://i41.tinypic.com/2dnvye.jpg
Figure 8

ANNUAL MAXIMUM SST MINUS ANNUAL MINIMUM SST

To create Figure 9, the Annual Minimum Data was subtracted from the Annual Maximum data. This would emphasize those El Nino events that were followed by a significant La Nina.
http://i39.tinypic.com/285k3.jpg
Figure 9

Smoothing the annual minimum to maximum temperature difference data, Figure 10, reveals a semi-periodic multidecadal variation. The “cycle” disappears before 1910. Is this a result of the limited data availability during early years?
http://i42.tinypic.com/wgs3m.jpg
Figure 10

SUPPLIMENTS TO THIS POST

Comparison graphs serve their purpose but can mask characteristics of the individual datasets. For this reason, in supplemental posts, I have included graphs (without commentary) of the Average, Maximum, Minimum, and Max-to-Min delta-T NINO3.4 SST data for the ERSST.v3b and HADISST datasets. Refer to:

The HADISST graphs are included in Supplement 1 to Comparison of Annual ERSST.v3b and HADISST NINO3.4 SST (Not Anomaly) Data

The ERSST.v3b graphs are included in Supplement 2 to Comparison of Annual ERSST.v3b and HADISST NINO3.4 SST (Not Anomaly) Data

SOURCE

The ERSST.v3b and HADISST data are available through the KNMI Climate Explorer website:
http://climexp.knmi.nl/selectfield_obs.cgi?someone@somewhere

Supplement 1 to Comparison of Annual ERSST.v3b and HADISST NINO3.4 SST (Not Anomaly) Data

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HADISST DATA

This post provides stand-alone illustrations of the HADISST NINO3.4 SST data used in the post Comparison of Annual ERSST.v3b and HADISST NINO3.4 SST (Not Anomaly) Data , without the distraction of the other dataset in the comparison charts. Included are Annual Average, Annual Maximum, and Annual Minimum NINO3.4 SST data, and the difference between the Annual Maximum and Minimum data. Graphs of raw and smoothed data (11-year running-average filter) are provided. Also provided is a comparison of NINO3.4 and Tropical SSTs, both datasets smoothed.

ANNUAL AVERAGE NINO3.4 SST

http://i39.tinypic.com/nguj5y.jpg
Figure 1 – Raw
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http://i39.tinypic.com/v7scuo.jpg
Figure 2 – Smoothed

ANNUAL AVERAGE NINO3.4 SST vs ANNUAL AVERAGE TROPICAL SST (SMOOTHED)
http://i41.tinypic.com/v6hx82.jpg
Figure 3 - Smoothed

ANNUAL MAXIMUM NINO3.4 SST
http://i44.tinypic.com/2q84oxt.jpg
Figure 4 – Raw
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http://i39.tinypic.com/5f2mnr.jpg
Figure 5 – Smoothed

ANNUAL MINIMUM NINO3.4 SST
http://i41.tinypic.com/2epmxw7.jpg
Figure 6 – Raw
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http://i41.tinypic.com/24pgmxl.jpg
Figure 7 – Smoothed

ANNUAL MAXIMUM NINO3.4 SST MINUS MINIMUM NINO3.4 SST
http://i44.tinypic.com/15obdr5.jpg
Figure 8 – Raw
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http://i42.tinypic.com/29cqivs.jpg
Figure 9 – Smoothed

SOURCE

The HADISST data are available through the KNMI Climate Explorer website:
http://climexp.knmi.nl/selectfield_obs.cgi?someone@somewhere

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Comment Policy, SST Posts, and Notes

Comments that are political in nature or that have nothing to do with the post will be deleted.
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The Smith and Reynolds SST Posts DOES NOT LIST ALL SST POSTS. I stopped using ERSST.v2 data for SST when NOAA deleted it from NOMADS early in 2009.

Please use the search feature in the upper left-hand corner of the page for posts on specific subjects.
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NOTE: I’ve discovered that some of the links to older posts provide blank pages. While it’s possible to access that post by scrolling through the history, that’s time consuming. There’s a quick fix for the problem, so if you run into an absent post, please advise me. Thanks.
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If you use the graphs, please cite or link to the address of the blog post or this website.