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Thursday, December 30, 2010

Very Basic Introduction To The KNMI Climate Explorer

I’ve moved to WordPress.  This post can now be found at Very Basic Introduction To The KNMI Climate Explorer
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UPDATE (January 2, 2010): I just received a reply to an email, and the always-helpful Geert Jan van Oldenborgh of KNMI suggested that I replot Figure 15 using the “gridbox” option instead of “shaded”. The “gridbox” option provides a better indication of the data location. The “shaded” option interpolates, it does not extrapolate, “so isolated (rows) of values are not drawn.”

UPDATE 2 (January 5, 2010): Fixed the link to the Monthly observations webpage at KNMI Climate Explorer.

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Dr. Geert Jan van Oldenborgh of the Royal Netherlands Meteorological Institute (KNMI) created and maintains (in addition to all of his research endeavors) the web application called the KNMI Climate Explorer. It allows users to perform statistical analysis of climate data. There are a multitude of datasets and analyses available, and any attempt on my part to describe what is available would not do justice to the efforts that have gone into the tool. Many of the datasets are updated monthly. Some are not. And for some datasets, the source may not update the data for a month or two. HADISST always lags the other SST datasets by a month. You can even investigate some of the climate model outputs used for the IPCC AR4.

Readers here know that I use the KNMI Climate Explorer to prepare the vast majority of my posts and my comments in blogs. I use it for data, correlation maps, anomaly maps for comparisons and animations, etc.

Begin with the Climate Explorer: Starting point and explore. Refer also to the note and link on that page that reads, “Some restrictions are in force, notably the possibility to define your own indices, to upload data into the Climate Explorer and to handle large datasets. If you want to use these features please log in or register.”

VERY BASIC INTRODUCTION
So you want to see, for example, if there is any evidence of the 1976/77 Pacific Climate Shift in tropical Pacific Sea Surface Temperature (SST) anomaly data. The KNMI Climate Explorer is a coordinate-based system, so you’ll need to know the coordinates of that area. Based on a map (Figure 1) you elect to use 20S-20N for the latitudes and 120E-90W for the longitudes.


http://i53.tinypic.com/20zsndd.jpg
Figure 1

Open the Monthly observations webpage (Figure 2). There are combined land plus sea surface temperature datasets at the top. Scrolling down, there are datasets for many other variables: land surface temperature, sea surface temperature, marine air temperature, lower troposphere temperature, precipitation, etc. The “more information” buttons (i) to the right of each are links to the web pages of the sources.
http://i53.tinypic.com/245ftih.jpg
Figure 2

Looking at the available SST datasets, Figure 3, you decide to use HADISST. It’s a good choice for a long-term SST dataset, because it is spatially complete (they infilled all of the missing data) and the raw data is reinserted after the infilling. Click on HADISST, and hit enter.
http://i55.tinypic.com/2ezl4p4.jpg
Figure 3

That brings you to the “Field” page, Figure 4. Enter the coordinates you’ve selected: 20S-20N, 120E-90W. There are different ways they could be entered. Some will give you the correct results. Others will not. And there are other ways to investigate the dataset, so it is best to standardize on a method that will work elsewhere.

For example, there is a map-making tool “Plot this field” under the right-hand menu heading of “Investigate this field”. There, Climate Explorer requires you to enter the southern latitude of the area you’re investigating in the left-hand field and the northern latitude in the right-hand one. If you don’t, it won’t produce a map. Latitudes south of the equator are input as negative numbers. That is, if you were looking for the SST data for the latitudes of 70S-40S, you’d enter -70 in the left-hand field and -40 in the right. Likewise, west longitudes are input as negative numbers. That is, 70W is -70.

The western longitude for the area you’re examining is entered in the left-hand field. And the eastern longitude of the area is entered in the right. If you enter them in the reverse order, you’ll get data but it’s not what you want. By inputting the longitudes in reverse order the data would represent the SST of all longitudes except the tropical Pacific.

Crossing the dateline in the map-making webpage also requires that you enter a longitude in the left-hand field that is lower than the right-hand field. That is, you cannot enter 120 (for 120E) in the left-hand field and -90 (for 90W) in the right-hand one, because Climate Explorer will not produce a map. You have to use 120 (for 120E) and 270 (for 90W) or you can enter -240 (for 120E) and -90 (for 90W). If that explanation was confusing, click on “Plot this field” and produce maps for the area outlined in red in Figure 1, using those two examples.

You’ll note in Figure 4 how I’ve entered the coordinates of 20S-20N, 120E-90W. Click on “Make time series”.
http://i53.tinypic.com/343kpeg.jpg
Figure 4

For Figure 5, I’ve changed the zoom on the screen so that all three graphs on the “Time series” page are visible. The top graph presents the data in raw form. For HADISST, the values are the raw SST data. (For datasets such as GISTEMP or CRUTEMP or HADSST2 that are not presented in absolute form, the upper graph will present anomalies). The middle graph is the climatology data used to create the anomalies. And the bottom graph illustrates the anomaly data.
http://i53.tinypic.com/2j4ualy.jpg
Figure 5

Click on the “raw data” link above the top map. The Raw HADISST SST data for the selected coordinates are presented in tabular form, Figure 6. The first column is the year, obviously, and the other twelve columns are the monthly SST data, starting with January in the second column.
http://i54.tinypic.com/if94r8.jpg
Figure 6

Go back to the “Time series” page and click on the “Raw data” link above the bottom (anomaly) graph. The anomaly data is presented in two columns, Figure 7. The first is the month in numerical form and the second is the SST anomaly data for that month. The data is provided as a mix that includes values in scientific notation. (Caution: Do not delete the E-01, or E-02, etc., after the value. Your spreadsheet understands that it’s scientific notation and will accommodate it.)
http://i51.tinypic.com/qn1vls.jpg
Figure 7

Go back to the “Time series” page and scroll down to the “select years” fields under the heading of “Manipulate this times series,” Figure 8. Let’s say you want to examine the data starting in 1950. Fill in both fields and click on “Select”.
http://i52.tinypic.com/xo0ap0.jpg
Figure 8

The KNMI Climate Explorer default base years for anomalies are the entire term of the data you’ve selected. In this example, they would be 1950 through 2010. I’ve highlighted where that’s shown on the anomaly graph in Figure 9. But let’s say you want to use a 30-year period as the base years--for example 1951-1980 like GISS. Enter them in the “Redisplay the anomalies using the years” fields directly below the anomaly graph, and click “Select.”

http://i54.tinypic.com/op0lqq.jpg
Figure 9

There will only be two graphs on the page: climatology and anomalies. Again, I’ve highlighted the base years in Figure 10.
http://i53.tinypic.com/2ia4ccn.jpg
Figure 10

Click on “Raw data” above the anomaly map and Climate Explorer presents the monthly data, Figure 11. “Select all”, then copy and paste to a spreadsheet. And if you’d like to know how to get the numerical months and monthly data into separate columns in EXCEL, refer to Converting txt Data Into Columns In EXCEL.
http://i52.tinypic.com/33cxces.jpg
Figure 11

A FEW NOTES

Figure 12 shows that there is an extra month added to the end the data. The actual final month for the data in Figure 12 is October 2010, but there is a duplicate of the October value listed in November with the note “# repeat last y to get nice gnuplot plot”. I haven’t asked Geert Jan why the extra month is there, but I’ve assumed that it exists to advise you that the download is complete. Note: Don’t use the data for the extra month in your spreadsheet.
http://i51.tinypic.com/24gogef.jpg
Figure 12

There are datasets that are spatially incomplete. For example, HADSST2 (the other Hadley Centre SST dataset) was corrected for known biases, but it is not infilled. (The Hadley Centre is updating it again and correcting for additional biases. HADSST3 should be available sometime in 2011.) Let’s say you wanted to duplicate the work of Thompson et al when they were investigating the 1945 discontinuity in global HADSST2 SST data. One of the subsets they used was an ENSO index called the CTI (Cold Tongue Index), which represents the SST anomalies of the coordinates 6S-6N, 180-90W. So you select HADSST2, enter those coordinates, then limit the time period to 1940 to 1950. The anomaly curve, Figure 13, shows that there are large gaps in the data for the CTI during that period.
http://i56.tinypic.com/2nvb9s7.jpg
Figure 13

Click on “Raw data” above the graph. There's lots of missing data, Figure 14. Climate Explorer identifies missing data with “# repeat last y to get nice gnuplot plot”. The repeated value is handy if only one month is missing. Then the repeated value can be used to fill in the gap. Or if you like, you can delete the repeated data. But there are gaps much longer than one month in the CTI data during this period.
http://i52.tinypic.com/jau9le.jpg
Figure 14

If you were to make a map of one of the missing months (November 1940), Figure 15, you’d note that there is data, not a lot of it, but there is data in the CTI region.
http://i52.tinypic.com/35jxt8i.jpg

“You can retrieve that data to also reduce the gaps. Back up to the “Field” page, which is where the coordinates are entered, Figure 16. There is a field there identified as “Demand at least: ___ % valid points in this region”. The default is 30%. Click on the “help” (i) button and KNMI explains its use:
"Percentage valid points
“The area average is only considered valid when at least this many valid points are included. Enter a smaller number to get more valid data in the resulting time series, but the quality of these data will be lower. A higher number gives fewer but higher-quality data points.”

So you can reduce the gaps in the data by entering a number in the “Demand at least:” field as low as zero (0), but the quality of the data drops.
http://i51.tinypic.com/e8s3dz.jpg
Figure 16

CLOSING NOTES
I use only a tiny fraction of the capabilities of KNMI Climate Explorer. (I try to write my posts for non-technical people, and sometimes I succeed, so I don’t need all of its tools.) Therefore, I will not be able to answer many of your questions. You’ll find it has capabilities that interest you that I haven’t yet found.

Very Important: Research the dataset you intend to use. For example, a large part of the ISCCP cloud amount data is incomplete over the Indian Ocean before 1998, and, if memory serves me well, that dataset was influenced by volcanic aerosols of the El Chichon and Mount Pinatubo eruptions. If you understand where the pitfalls are in the data, it saves embarrassment after the fact.

Oops, almost forgot. If you missed it, there was evidence of the 1976/77 Pacific Climate shift in the tropical Pacific SST data. Refer again to Figure 9 or 10.

I have found Climate Explorer extremely educational and I thank Geert Jan for it.

Wednesday, December 29, 2010

PRELIMINARY December 2010 SST Anomaly Update

I’ve moved to WordPress.  This post can now be found at PRELIMINARY December 2010 SST Anomaly Update
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Sorry for the delay. The December 2010 Reynolds OI.v2 Sea Surface Temperature (SST) data through the NOAA NOMADS website won’t be official until January 10th. Refer to the schedule on the NOAA Optimum Interpolation Sea Surface Temperature Analysis Frequently Asked Questions webpage. The following are the preliminary Global and NINO3.4 SST anomalies for December 2010 that the NOMADS website prepares based on incomplete data for the month. I’ve also included the weekly data through December 24, 2010, but I’ve shortened the span of the weekly data, starting it in January 2004, so that the variations can be seen.

PRELIMINARY MONTHLY DATA
Monthly NINO3.4 SST anomalies had stopped their decline last month and had risen slightly. The preliminary December data shows they dropped slightly, but nothing to indicate there will be a significant further decline. Presently they’re at -1.52 deg C.
http://i52.tinypic.com/flbuww.jpg
Monthly NINO3.4 SST Anomalies
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Monthly Global SST anomalies, according to the preliminary data, have dropped another 0.01 deg C. The preliminary global SST anomaly is 0.085 deg C.
http://i52.tinypic.com/25hmk9t.jpg
Monthly Global SST Anomalies
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A NOTE ABOUT THE YEAR-TO-YEAR VARIABILITY
The following is a repeat of a discussion from the Mid-December 2010 SST Anomaly Update.

As noted in the November 2010 SST Anomaly Update, the global SST anomalies do not appear as though they will drop to the level they had reached during the 2007/08 La Niña, even if one were to account for the differences in NINO3.4 SST anomalies. This of course will be raised by alarmists as additional proof of anthropogenic global warming.

But the reason the global SST anomalies have warmed in that time is due primarily to the fact that the East Indian and West Pacific Oceans (about 25% of the surface area of the global oceans) can warm in response to both El Niño and La Niña events. Refer to Can El Niño Events Explain All of the Global Warming Since 1976? – Part 1 and Can El Niño Events Explain All of the Global Warming Since 1976? – Part 2, and the video included in La Niña Is Not The Opposite Of El Niño – The Videos. In addition, the North Atlantic also remains at elevated levels during La Niña events in response to the ENSO-related warming of the Kuroshio-Oyashio Extension. This was discussed and illustrated in the recent post The ENSO-Related Variations In Kuroshio-Oyashio Extension (KOE) SST Anomalies And Their Impact On Northern Hemisphere Temperatures.

Keep in mind, the warm water released from below the surface of the Pacific Warm Pool doesn’t simply vanish at the end of the El Niño.

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WEEKLY DATA
The weekly NINO3.4 SST anomaly data are cycling up and down at what appears to be the low end of the 2010/11 La Niña. They are at -1.73 deg C.
http://i54.tinypic.com/saxonp.jpg
Weekly NINO3.4 SST Anomalies
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Weekly Global SST Anomalies have dropped slightly, and it appears they also might have reached the seasonal low. It’s impossible to tell if they will they drop more? They are presently at +0.089 deg C.
http://i56.tinypic.com/2pq7uyb.jpg
Weekly Global SST Anomalies
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SOURCES
SST anomaly data is available through the NOAA NOMADS website:
http://nomad1.ncep.noaa.gov/cgi-bin/pdisp_sst.sh
or:
http://nomad3.ncep.noaa.gov/cgi-bin/pdisp_sst.sh?lite=

Friday, December 24, 2010

Links To NODC Ocean Heat Content Posts

I’ve moved to WordPress.  This post can now be found at Links To NODC Ocean Heat Content Posts
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The National Oceanographic Data Center calculated and maintains an OCEAN HEAT CONTENT (OHC) dataset. This is the dataset based on the Levitus et al (2009) paper “Global ocean heat content(1955-2008) in light of recent instrumentation problems”, Geophysical Research Letters. Refer to Manuscript.

The NODC OHC data is available through the KMNI Climate Explorer, which is the source of the data presented in the following posts.

THE IMPACTS OF NATURAL VARIABLES
A. ENSO Dominates NODC Ocean Heat Content (0-700 Meters) Data

B. North Pacific Ocean Heat Content Shift In The Late 1980s

C. North Atlantic Ocean Heat Content (0-700 Meters) Is Governed By Natural Variables

QUARTERLY UPDATES OF NODC (LEVITUS ET AL 2009) OHC DATA SINCE JANUARY 2010

March 17, 2011 - October to December 2010 NODC Ocean Heat Content (0-700Meters) Update and Comments


October 18, 2010 - Update And Changes To NODC Ocean Heat Content Data

June 27, 2010- January To March 2010 NODC Ocean Heat Content (0-700m) Update And Comments

February 5, 2010 - OHC Linear Trends and Recent Update of NODC OHC (0-700 Meters) Data

January 31, 2010 - NODC Ocean Heat Content (0-700 Meters) - 2007, 2008 & 2009 Corrections
ARGO-ERA POST
ARGO-Era NODC Ocean Heat Content Data (0-700 Meters) Through December 2010

Thursday, December 23, 2010

Happy Holidays

I’ve moved to WordPress.  This post can now be found at Happy Holidays
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Thanks to all who read and comment on my posts here and at WattsUpWithThat. I, like many people, will be spending most of my time with family over the next few days (until December 27th), so if comment moderation seems to take a little longer than normal, you'll understand.

Enjoy the holidays.

Regards

Bob Tisdale

Wednesday, December 22, 2010

TAO Project Sea Air And Sea Surface Temperature Data

I’ve moved to WordPress.  This post can now be found at TAO Project Sea Air And Sea Surface Temperature Data
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This is brief introduction to the TAO Project Sea Air and Sea Surface Temperature data that’s available through the KNMI Climate Explorer.

The Monthly observations webpage of the KNMI Climate Explorer includes Sea Air Temperature and Sea Surface Temperature data from the NOAA Pacific Marine Environmental Laboratory (PMEL) Tropical Atmosphere Ocean (TAO) project. Refer to the TOA Project Home webpage. A Flash player overview of the TAO project is provided here: The TAO Story.

If you were to download the data from the KNMI Climate Explorer for the full area covered (8S-9N, 137E-95W), you’d note that data starts as early as 1980. But, like all datasets, the timing of partial and complete coverage needs to be understood. There may be TOA Project data available as far back as 1980, but it is very sparse in early years. The installation of the buoys was not completed until 1994. As an initial reference, Animation 1 shows the locations of available TOA Project sea air and sea surface temperature data for Januaries starting in 1989. It shows how sparse the coverage was of the tropical Pacific prior to 1994. So caution should be exercised when using TAO project data before 1994. And as you will note, there can be months after 1994 when data from individual buoys is not available, leaving incomplete coverage.
http://i52.tinypic.com/23k3zwx.jpg
Animation 1

Keeping that in mind, Figure 1 compares Sea Surface and Sea Air Temperature data (not anomalies) for the NINO3.4 region (5S-5N, 170W-120W) of the central equatorial Pacific starting in 1995. As one would expect, monthly NINO3.4 SST is higher than NINO3.4 Sea Air Temperature.
http://i54.tinypic.com/ve6a78.jpg
Figure 1

If we subtract the NINO3.4 Sea Air Temperature from the NINO3.4 Sea Surface Temperature, Figure 2, the difference appears to be a noisy ENSO dataset. And it clearly illustrates that the monthly SST data stays above the monthly Sea Air temperature for the NINO3.4 region. The average monthly NINO3.4 Sea Surface Temperature is approximately 0.55 deg C warmer than the average Sea Air Temperature. Referring back to the animation, the sharp drop in 2008 could be caused by the loss of data in that area.
http://i56.tinypic.com/2z5uq9s.jpg
Figure 2

Smoothing the data with a 13-month running average filter to reduce the noise, the difference compares well to scaled NINO3.4 SST anomalies, Figure 3.
http://i54.tinypic.com/5m05jc.jpg
Figure 3

The TAO project Sea Surface and Sea Air Temperatures for the entire dataset (8S-9N, 137E-95W) are illustrated in Figure 4. SST is clearly higher then SAT on a monthly basis.
http://i55.tinypic.com/sv5dmq.jpg
Figure 4

The difference is shown in Figure 5. Since 1995, the average monthly equatorial Pacific Sea Surface Temperature has been approximately 0.82 deg C higher than Sea Air Temperature.
http://i52.tinypic.com/2ypkpsl.jpg
Figure 5

And as one would expect, the variations in the difference between the TAO Project Sea Air and Sea Surface Temperatures is a function of ENSO. Refer to Figure 6, which compares the difference to scaled and ranged NINO3.4 SST anomalies.
http://i53.tinypic.com/291na4x.jpg
Figure 6

SOURCE
The TAO Project data used in this post is available through the KNMI Climate Explorer:
http://climexp.knmi.nl/selectfield_obs.cgi?someone@somewhere

Monday, December 20, 2010

Hmmm. My Comment Got Deleted At Tamino’s “Not So” Open Mind

I’ve moved to WordPress.  This post can now be found at Hmmm. My Comment Got Deleted At Tamino’s “Not So” Open Mind
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Occasionally I will run a google blog search of my name to see who’s writing what about one of my posts. And when someone misses a point or misrepresents something, I reply. This morning I found that a commenter at Tamino's Open Mind had referred to one. It was in the thread of Tamino’s post Odd Man Out, by blogger Same Ordinary Fool at December 17, 2010 at 9:51 pm.

I copied my reply before it was deleted during moderation. It follows.

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Bob Tisdale December 20, 2010 at 10:09 am Reply

Your comment is awaiting moderation.

Same Ordinary Fool : About Anthony’s title “’Tisdale K.O.e’s GISS’s latest ‘warmest-year nonsense’”, you wrote, “Presumably the title refers to what was also Steve Goddard’s favorite objection, and what is only briefly mentioned here:
“‘GISS deletes SST data from areas with seasonal sea ice and extends land surface data out over the oceans (Arctic and Southern) with its 1200km radius smoothing.’”

The title was a play on words. My post was about the Kiroshio-Oyashio Extension, a.k.a. KOE.

Also, Steve Goddard’s objection was the GISS 1200km radius smoothing in general. I wrote the post about the GISS deletion of SST data:
http://bobtisdale.blogspot.com/2010/05/giss-deletes-arctic-and-southern-ocean.html
WUWT co-post is here:
http://wattsupwiththat.com/2010/05/31/giss-deletes-arctic-and-southern-ocean-sea-surface-temperature-data/

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I wonder what it was Tamino didn’t like in that reply. It’s the truth. I wrote the post about GISS Deleting Arctic And Southern Ocean Sea Surface Temperature Data. And GISS does delete it. The Arctic and Southern Ocean SST data exists in the source Reynolds OI.v2 SST data, but parts of it are not present in the GISS LOTI product.

Anthony Watts cross posted my post The ENSO-Related Variations In Kuroshio-Oyashio Extension (KOE) SST Anomalies And Their Impact On Northern Hemisphere Temperatures, and came up with the play-on-words title of Tisdale K.O.e’s GISS’s latest “warmest-year nonsense”.

And Steve Goddard at his new blog Real Science has continued with his posts about GISS. Apparently, Steve does not like anything about the GISS surface temperature products.

Mid-December 2010 SST Anomaly Update

I’ve moved to WordPress.  This post can now be found at Mid-December 2010 SST Anomaly Update
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This mid-month update only includes the shorter-term NINO3.4 and global SST anomaly graphs; that is, the ones from January 2004 to present. There’s not much happening, other than both datasets appear to have reached their seasonal lows for this La Niña.

As noted in the November 2010 SST Anomaly Update, the global SST anomalies do not appear as though they will drop to the level they had reached during the 2007/08 La Niña, even if one were to account for the differences in NINO3.4 SST anomalies. This of course will be misrepresented by some people as additional proof of anthropogenic global warming.

But the reason the global SST anomalies have warmed in that time is due primarily to the fact that the East Indian and West Pacific Oceans (about 25% of the surface area of the global oceans) can warm in response to both El Niño and La Niña events. Refer to Can El Niño Events Explain All of the Global Warming Since 1976? – Part 1 and Can El Niño Events Explain All of the Global Warming Since 1976? – Part 2, and the video included in La Niña Is Not The Opposite Of El Niño – The Videos. In addition, the North Atlantic also remains at elevated levels during La Niña events in response to the ENSO-related warming of the Kuroshio-Oyashio Extension. This was discussed and illustrated in the recent post The ENSO-Related Variations In Kuroshio-Oyashio Extension (KOE) SST Anomalies And Their Impact On Northern Hemisphere Temperatures.

Keep in mind, the warm water released from below the surface of the Pacific Warm Pool doesn’t simply vanish at the end of the El Niño.

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NINO3.4
NINO3.4 SST anomalies for the week centered on December 15, 2010 show that central equatorial Pacific SST anomalies have risen slightly in the past two weeks after a small dip. In other words, they’ve apparently reached the low end of this La Niña and they’re simply varying slightly at the seasonal La Niña level. They’re at approximately -1.4 deg C.
http://i56.tinypic.com/rbn0js.jpg
NINO3.4 SST Anomalies - Short-Term

GLOBAL

Weekly Global SST anomalies may have reached their seasonal low. They are presently at +0.1 deg C.
http://i55.tinypic.com/16bhhz7.jpg
Global SST Anomalies - Short-Term

SOURCE

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

Wednesday, December 8, 2010

The ENSO-Related Variations In Kuroshio-Oyashio Extension (KOE) SST Anomalies And Their Impact On Northern Hemisphere Temperatures

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OVERVIEWThis post provides brief background information about the Kuroshio-Oyashio Extension (KOE), and discusses the relationship between NINO3.4 SST anomalies and the SST anomalies of the KOE following major El Niño events. Using correlation maps the post also illustrates the possible impacts of the KOE Sea Surface Temperature (SST) anomalies on North Atlantic SST anomalies, Combined Land and Ocean Surface Temperature anomalies, and Lower Troposphere Temperature anomalies.

INTRODUCTION

The Kuroshio Current and Oyashio Current are located in the western North Pacific Ocean. The Kuroshio Current is the western boundary current of the North Pacific Subtropical Gyre. Its counterpart in the North Atlantic Ocean is the well-known Gulf Stream. The Kuroshio Current carries warm tropical waters northward from the North Equatorial Current to the east coast of Japan. The East Kamchatka Current and the Oyashio Current are the western boundary currents of the Western Subarctic Gyre. The East Kamchatka Current is renamed the Oyashio Current south of the Bussol Strait (which is located about half way between Hokkaido and the Kamchatka Peninsula). They carry cold subarctic waters south to the east coast of Japan. The Kuroshio and Oyashio currents meet and form the North Pacific Current that runs from west to east across the North Pacific at mid latitudes. The Qiu, (2001) paper Kuroshio and Oyashio Currents. In Encyclopedia of Ocean Sciences, (Academic Press, pp. 1413-1425) provides a detailed but easily readable description of the two currents. Figure 1, from Qiu (2001), illustrates the general locations and paths of the Kuroshio and Oyashio Currents.

http://i51.tinypic.com/15zs014.jpg
Figure 1

As noted above, the Kuroshio and Oyashio Currents collide East of Japan and form the western portion of the North Pacific Current. These waters are often referred to as the Kuroshio-Oyashio Extension or the KOE. For the purpose of this post, I’ve used the coordinates of 30N-45N, 150E-150W for the Kuroshio-Oyashio Extension, Figure 2.
http://i52.tinypic.com/14twvox.jpg
Figure 2

CORRELATION WITH NORTHERN HEMISPHERE TEMPERATURES

Sea Surface Temperature (SST) anomalies for much of the North Atlantic warm (cool) when the Kuroshio-Oyashio Extension SST anomalies warm (cool). This can be seen in the correlation map of annual (January to December) Kuroshio-Oyashio Extension SST anomalies and annual North Atlantic SST anomalies, Figure 3.
http://i52.tinypic.com/fjj23r.jpg
Figure 3

And, as shown in Figures 4 (RSS) and 5 (UAH), annual TLT anomalies for much of the Northern Hemisphere correlate with the annual SST anomalies of the Kuroshio-Oyashio Extension.
http://i52.tinypic.com/6gd98k.jpg
Figure 4
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http://i53.tinypic.com/2qsx7j8.jpg
Figure 5

The same thing holds true for combined land plus sea surface temperature datasets such as the GISS Land-Ocean Temperature Index (LOTI) data for the Northern Hemisphere, Figure 6. Much of the Northern Hemisphere GISS LOTI data warms (cools) as KOE SST anomalies warm (cool). (Also note the differences in the North Atlantic correlations in Figures 3 and 6. They’re based on the same SST dataset, so why are there differences? GISS deletes SST data from areas with seasonal sea ice and extends land surface data out over the oceans with its 1200km radius smoothing. Refer to GISS Deletes Arctic And Southern Ocean Sea Surface Temperature Data.)
http://i54.tinypic.com/303llxg.jpg
Figure 6

WHEN DOES THE KOE WARM?
As we’ve seen in past posts, the East Indian and West Pacific Oceans warm in response to El Niño events and then during the subsequent La Nina events. As part of the East Indian-West Pacific subset, the Kuroshio-Oyashio Extension warms significantly during La Niña events. Animation 1 is taken from the videos in the post La Niña Is Not The Opposite Of El Niño – The Videos. It presents the 1997/98 El Niño followed by the 1998 through 2001 La Niña. Each map represents the average SST anomalies for a 12-month period and is followed by the next 12-month period in sequence. Using 12-month averages eliminates the seasonal and weather noise. The effect is similar to smoothing data in a time-series graph with a 12-month running-average filter. Note how the Kuroshio-Oyashio Extension warms significantly during the La Niña event and how the warming persists for the entire term of the La Niña.
http://i53.tinypic.com/etb58j.jpg
Animation 1

Note in Animation 1 that the SST anomalies of the Kuroshio-Oyashio Extension were cool during the 1997/98 El Niño. The KOE actually started with depressed SST anomalies, and they did not drop significantly during the 1997/98 El Niño. Refer to Figure 7. On the other hand, the KOE SST anomalies did rise significantly during the transition from the El Niño to the La Niña in 1998. The other major El Niño event that wasn’t impacted by the aerosols of an explosive volcanic eruption was the 1986/87/88 event. The SST anomalies of the Kuroshio-Oyashio Extension cooled during the 1986/87/88 El Niño, but also rose significantly during the 1988/89 La Nina. We’ll take a closer look at that event later in the post.
http://i53.tinypic.com/2qa1onl.jpg
Figure 7

This response of the Kuroshio-Oyashio Extension to El Niño and La Niña events is easier to see if the NINO3.4 SST anomalies are inverted, Figure 8. That is, the Kuroshio-Oyashio Extension warms much more during the 1998/99/00/01 La Niña event than it cools during the 1997/98 El Niño. But could the significant drop in the Kuroshio-Oyashio Extension during the 1986/87/88 El Niño impact the global response to that El Niño? Again, we’ll examine that later in the post.
http://i52.tinypic.com/wjvow.jpg
Figure 8

WHY DOES THE KOE WARM DURING LA NIÑA EVENTS?

Let’s start with the El Niño. During an El Niño event, a significant volume of warm water from the west Pacific Warm Pool travels east to the central and eastern equatorial Pacific, where it releases heat primarily through evaporation. And most of the warm water from the Pacific Warm Pool water comes from below the surface. There is “leftover” warm water when the La Niña forms, and a portion of this leftover warm water is returned to the western tropical Pacific at approximately 10 deg N latitude. Video 1 illustrates global Sea Level Residuals from January 1998 to June 2001. It captures the 1998/99/00/01 La Niña in its entirety. The video was taken from the JPL video “tpglobal.mpeg”. The phenomenon shown carrying warm waters from east to west in the tropical Pacific at approximately 10 deg N is called a slow-moving Rossby Wave.

Video 1
Link to Video 1:
http://www.youtube.com/watch?v=MF5vZErQ6HM

Unfortunately, the video “tpglobal.mpeg” is no longer available at the JPL VIDEOS web page, but for those who would like to watch the entire video, I uploaded it to YouTube as Sea Surface Height Animation 1992 to 2002 - JPL Video tpglobal.mpg.

In Video 1, the warm “leftover” warm water from the 1997/98 El Niño is clearly carried as far west as the Philippines. Shortly thereafter Kuroshio-Oyashio Extension sea level residuals rise and remain elevated for the duration of the La Niña.

In addition, there are other factors that add to and maintain the elevated SST anomalies in the Kuroshio-Oyashio Extension during the La Niña. As shown in Animation 1 (the gif animation, not the video), Sea Surface Temperature anomalies outside of the tropical Pacific rise in response to the El Niño. The changes occur first in the Atlantic, then Indian, and finally the west Pacific. Sea Surface Temperature anomalies rise as changes in atmospheric circulation caused by the El Niño make their way eastward around the globe to the western Pacific. Then, during the La Niña, the opposite occurs for much of the globe. But in the tropical Pacific, the trade winds strengthen and the North and South Equatorial Currents return warm “leftover” surface waters from the El Niño to the west. So the western Pacific is warmed cumulatively by the El Niño and then by the La Niña. In the northwest Pacific, the Kuroshio Current carries the leftover warm water up to the Kuroshio-Oyashio Extension.

Additionally, the increased strength of the trade winds during the La Niña also reduces cloud cover over the tropical Pacific, which increases the amount of Downward Shortwave Radiation (visible light) there. The increased Downward Shortwave Radiation warms the tropical Pacific. The warmed water is carried to the west by the Equatorial Currents and the North Pacific Gyre spins the warmed water up to the Kuroshio-Oyashio Extension.

WHY IS THIS IMPORTANT?

In the post “RSS MSU TLT Time-Latitude Plots...Show Climate Responses That Cannot Be Easily Illustrated With Time-Series Graphs Alone”, I illustrated that the RSS Lower Troposphere Temperature (TLT) anomalies of Southern Hemisphere and of the Tropics (70S-20N) followed the basic variations in NINO3.4 SST anomalies, Figure 9. This is how one would expect TLT anomalies to respond to El Niño and La Niña events. El Niño events cause the TLT anomalies to rise because they release more heat than normal to the atmosphere, and La Niña events cause TLT anomalies to fall because the tropical Pacific is releasing less heat than normal.
http://i54.tinypic.com/r9h0d5.jpg
Figure 9

But the TLT anomalies of the Northern Hemisphere north of 20N, Figure 10, appear to rise in a step after the 1997/98 El Niño. That is, there is very little response to the 1998 through 2001 La Niña. It appears as though a secondary source of heat is maintaining the Northern Hemisphere TLT anomalies at elevated levels.
http://i53.tinypic.com/11lsb6e.jpg
Figure 10

A similar upward step can be seen in the GISS Land-Ocean Temperature anomaly index (LOTI) for the latitudes of 20N-65N, Figure 11. (North of 65N the GISS data is biased by their deleting Sea Surface Temperature data and replacing it with land surface data with a higher trend. Again, refer to GISS Deletes Arctic And Southern Ocean Sea Surface Temperature Data.)
http://i53.tinypic.com/34qr5t2.jpg
Figure 11

And a similar upward step is visible in the North Atlantic SST anomaly data, Figure 12.
http://i56.tinypic.com/1zewmqq.jpg
Figure 12

The North Atlantic SST anomalies, the Lower Troposphere Temperature( TLT) anomalies of the Northern Hemisphere north of 20N, and the Northern Hemisphere Land-Ocean Temperature anomalies (20N-65N) all rise in response to the 1997/98 El Niño, but fail to respond fully to the 1998/99/00/01 La Niña. The similarity of the curves can be seen in Figure 13.
http://i54.tinypic.com/200v0j5.jpg
Figure 13

The correlation maps in Figures 3 through 6 show that a portion of the warming of the Northern Hemisphere north of 20N should be a response to the elevated Kuroshio-Oyashio SST anomalies during the 1998 through 2001 La Niña. To further illustrate this relationship, Figure 14 compares the KOE SST anomalies (not scaled) to the three datasets shown in Figure 13. I did not scale the Kuroshio-Oyashio SST anomalies because I wanted to illustrate the differences in the magnitudes of the variations. The variations in Kuroshio-Oyashio SST anomalies are clearly far greater than the variations of the other three datasets in Figure 14. In fact, the KOE SST anomaly variations are about 40% to 50% of the variations in NINO3.4 SST anomalies (refer back to Figures 7 and 8).
http://i56.tinypic.com/29e0pvp.jpg
Figure 14

Figure 15 presents the same datasets as Figure 14, but in Figure 15, the Kuroshio-Oyashio Extension SST anomalies have been scaled. Keep in mind that the three Northern Hemisphere temperature anomaly datasets rise first in response to the El Niño.
http://i54.tinypic.com/25hl2tz.jpg
Figure 15

It appears the warming of the Kuroshio-Oyashio Extension during the 1998/99/00/01 La Niña and its interaction with the other datasets could explain a portion of the trend in Northern Hemisphere SST anomalies, TLT anomalies, and Land-Ocean temperature anomalies since 1995. The warming of the Kuroshio-Oyashio Extension during that La Niña counteracts the normal cooling effects of the La Niña and prevents the temperature anomalies for the three datasets shown in Figures 13, 14, and 15 from responding fully to the La Niña.

THE 1986/87/88 EL NIÑO & 1988/89 LA NIÑA

There is a similar effect during the 1988/89 La Niña. That is, Northern Hemisphere temperature anomalies do not drop as one would expect during a La Niña. But the response during the 1986/87/88 El Niño may help to confirm the impact of the Kuroshio-Oyashio Extension on Northern Hemisphere temperatures.

Figure 16 compares scaled NINO3.4 SST anomalies for the period of 1985 through 1994 to the same datasets used in Figures 13: North Atlantic SST anomalies, the Lower Troposphere Temperature (TLT) anomalies of the Northern Hemisphere north of 20N, and the GISS Northern Hemisphere Land-Ocean Temperature anomalies (20N-65N). Once again, the Northern Hemisphere datasets rise in response to the El Niño event, but don’t drop in response to the La Niña. Note also that the North Atlantic SST anomalies lag the NINO3.4 SST by more than 6 months during the ramp-up phase, but the lag in the Northern Hemisphere TLT and Surface Temperature datasets is excessive, about 18 months. Why?
http://i53.tinypic.com/iqx3te.jpg
Figure 16

Could the dip in the Kuroshio-Oyashio Extension SST anomalies during the 1986/87/88 El Niño have counteracted their responses to the El Niño? Refer to Figure 17. It compares Kuroshio-Oyashio Extension SST anomalies (not scaled) to the North Atlantic and Northern Hemisphere datasets. The drop in KOE SST anomalies is significant in 1986/87/88.
http://i51.tinypic.com/2cwjs6c.jpg
Figure 17

And in Figure 18, the Kiroshio-Oyashio SST anomalies have been scaled. The North Atlantic SST anomalies rise in response to the 1986/87/88 El Niño as noted earlier. The timing of the rises in the KOE data and the GISS LOTI data are very similar. But the rise in the TLT anomalies north of 20N precedes the rise in the KOE data. If the dip in KOE SST anomalies were the only factor preventing the TLT anomalies from rising in response to the El Niño, shouldn’t we expect the TLT anomalies to lag the rise in the KOE data? Or are the TLT anomalies responding to the rise in North Atlantic SST anomalies?
http://i52.tinypic.com/2r5xdl3.jpg
Figure 18

If we replace the RSS TLT data with TLT data from UAH, Figure 19, the lag decreases between the North Atlantic SST anomalies and the TLT anomalies north of 20N.
http://i52.tinypic.com/2wqbui9.jpg
Figure 19

CLOSING
An El Niño event releases vast amounts of warm water from below the surface of the west Pacific Warm Pool. But the end of an El Niño event does not mean all of that warm water suddenly disappears. The warm water sloshes back to the western tropical Pacific during the La Niña. And some of that warm water is spun up into the Kuoshio-Oyashio Extension where it continues to release heat.

Kuroshio-Oyashio Extension SST anomalies rose significantly during the La Niña events of 1988/89 and 1998/99/00/01. These warmings appear to have counteracted the effects of those La Niña events on North Atlantic SST anomalies, and on Lower Troposphere Temperature anomalies north of 20N, and on combined Land-Ocean temperature anomalies of the Northern Hemisphere between the latitudes of 20N-65N. During the 1997/98 El Niño, the drop in Kuroshio-Oyashio Extension SST anomalies was very small and the KOE does not appear to have had a noticeable impact on the effects of that El Niño. On the other hand, the Kuroshio-Oyashio Extension SST anomalies did drop significantly during the 1986/87/88 El Niño and they appear to have suppressed the effects of that El Niño on Northern Hemisphere temperature anomalies. But why did the Kuroshio-Oyashio Extension SST anomalies drop significantly during the 1986/87/88 El Niño but not during the 1997/98 El Niño? Differences in Sea Level Pressure?

SOURCE
Data for graphs are available through, and the correlation and anomaly maps were downloaded from, the KNMI Climate Explorer:
http://climexp.knmi.nl/selectfield_obs.cgi?someone@somewhere

Monday, December 6, 2010

November 2010 SST Anomaly Update

I’ve moved to WordPress.  This post can now be found at November 2010 SST Anomaly Update
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MONTHLY SST ANOMALY MAP
The map of Global OI.v2 SST anomalies for November 2010 downloaded from the NOMADS website is shown below. With the exception of the South Atlantic, all ocean basins showed a decline in SST anomalies in November.

http://i56.tinypic.com/2r71xsi.jpg
November 2010 SST Anomalies Map (Global SST Anomaly = +0.097 deg C)

MONTHLY OVERVIEW

Monthly NINO3.4 SST anomalies MAY have reached their seasonal low value. The Monthly NINO3.4 SST Anomaly is -1.46 deg C.

Global SST anomalies dropped in both hemispheres this month for a total decline of about 0.041 deg C. Over the past two months, global SST anomalies have declined almost 0.1 deg C.
http://i56.tinypic.com/6hnudt.jpg
Global
Monthly Change = -0.041 deg C
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http://i55.tinypic.com/2rzp4ax.jpg
NINO3.4 SST Anomaly
Monthly Change = +0.13 deg C

EAST INDIAN-WEST PACIFIC
The SST anomalies in the East Indian and West Pacific made a major decline this month.

I’ve added this dataset in an attempt to draw attention to what appears to be the upward steps in response to significant El Niño events that are followed by La Niña events.
http://i56.tinypic.com/2qnvzix.jpg
East Indian-West Pacific (60S-65N, 80E-180)
Monthly Change = -0.126 deg C

Further information on the upward “step changes” that result from strong El Niño events, refer to my posts from a year ago Can El Niño Events Explain All of the Global Warming Since 1976? – Part 1 and Can El Niño Events Explain All of the Global Warming Since 1976? – Part 2

And for the discussions of the processes that cause the rise, refer to More Detail On The Multiyear Aftereffects Of ENSO - Part 2 – La Niña Events Recharge The Heat Released By El Niño Events AND...During Major Traditional ENSO Events, Warm Water Is Redistributed Via Ocean Currents -AND- More Detail On The Multiyear Aftereffects Of ENSO - Part 3 – East Indian & West Pacific Oceans Can Warm In Response To Both El Niño & La Niña Events

The animations included in post La Niña Is Not The Opposite Of El Niño – The Videos further help explain the reasons why East Indian and West Pacific SST anomalies can rise in response to both El Niño and La Niña events.

NOTE ABOUT THE DATA
The MONTHLY graphs illustrate raw monthly OI.v2 SST anomaly data from November 1981 to November 2010.

MONTHLY INDIVIDUAL OCEAN AND HEMISPHERIC SST UPDATES http://i51.tinypic.com/20u78l4.jpg
Northern Hemisphere
Monthly Change = -0.073 deg C
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http://i52.tinypic.com/208abko.jpg
Southern Hemisphere
Monthly Change = -0.016 deg C
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http://i52.tinypic.com/2vs1bpv.jpg
North Atlantic (0 to 75N, 78W to 10E)
Monthly Change = -0.069 deg C
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http://i54.tinypic.com/25zmatu.jpg
South Atlantic (0 to 60S, 70W to 20E)
Monthly Change = +0.170 deg C

Note: I discussed the upward shift in the South Atlantic SST anomalies in the post The 2009/10 Warming Of The South Atlantic. Will the South Atlantic return to the level it was at before that surge or will it remain at a new plateau?

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http://i54.tinypic.com/2mwrngw.jpg
North Pacific (0 to 65N, 100 to 270E, where 270E=90W)
Monthly Change = -0.103 Deg C
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http://i55.tinypic.com/2i21zeu.jpg
South Pacific (0 to 60S, 145 to 290E, where 290E=70W)
Monthly Change = -0.097 deg C
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http://i54.tinypic.com/23w3ehv.jpg
Indian Ocean (30N to 60S, 20 to 145E)
Monthly Change = -0.023 deg C
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http://i54.tinypic.com/2cprsih.jpg
Arctic Ocean (65 to 90N)
Monthly Change = -0.238 deg C
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http://i55.tinypic.com/156rcav.jpg
Southern Ocean (60 to 90S)
Monthly Change = -0.051 deg C

WEEKLY SST ANOMALIES
The weekly NINO3.4 SST anomaly data illustrate OI.v2 data centered on Wednesdays. The latest weekly NINO3.4 SST anomalies are -1.32 deg C. That’s an increase of about 0.5 deg C since the minimum of about a month ago.
http://i53.tinypic.com/33v0uxg.jpg
Weekly NINO3.4 (5S-5N, 170W-120W)

The weekly global SST anomalies are at +0.071 deg C. They do not appear as though they will drop to the level they had reached during the 2007/08 La Niña, even if one were to account for the differences in NINO3.4 SST anomalies. This of course will be raised as additional proof the global oceans are warming. But the reason the global SST anomalies have warmed in that time is due primarily to the fact that the East Indian and West Pacific Oceans warm in response to both El Niño and La Niña events. Keep in mind, the warm water released from below the surface of the Pacific Warm Pool doesn’t simply vanish at the end of the El Niño. Also, the unusual rise in South Atlantic SST anomalies has added to the trend.
http://i54.tinypic.com/2j0e6p4.jpg
Weekly Global

SOURCE
The Optimally Interpolated Sea Surface Temperature Data (OISST) are available through the NOAA National Operational Model Archive & Distribution System (NOMADS).
http://nomad1.ncep.noaa.gov/cgi-bin/pdisp_sst.sh
or
http://nomad3.ncep.noaa.gov/cgi-bin/pdisp_sst.sh

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Comment Policy, SST Posts, and Notes

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