INITIAL NOTE
This is the third month with the new format. I’ve replaced the smoothed curve with a horizontal line that represents the Current Value.
MONTHLY SEA SURFACE TEMPERATURE ANOMALY MAP
The following is a Global map of Reynolds OI.v2 Sea Surface Temperature (SST) anomalies for June 2016. It was downloaded from the KNMI Climate Explorer. The contour range was set to -2.5 to +2.5 deg C and the anomalies are referenced to the WMO-preferred period of 1981-2010.
June 2016 Sea Surface Temperature (SST) Anomalies Map
(Global SST Anomaly = +0.37 deg C)
MONTHLY GLOBAL OVERVIEW
Global Sea Surface Temperature anomalies made an uptick in June, an increase of about +0.03 deg C. Surface temperature anomalies rose in the Northern Hemisphere, and for the Southern Hemisphere, there was basically no change. Last month, the only ocean basins to show cooling were the North Atlantic and Indian Oceans. The El Niño peaked in November, and the global sea surface temperature response to the El Niño peaked as well, about 2 months later in January 2016.
The monthly Global Sea Surface Temperature anomalies are presently at +0.37 deg C, referenced to the WMO-preferred base years of 1981 to 2010.
(1)Global Sea Surface Temperature Anomalies
Monthly Change = +0.03 deg C
THE EQUATORIAL PACIFIC
The monthly NINO3.4 Sea Surface Temperature anomalies for June 2016 are continuing to decline and they are now below zero but above the threshold of an La Niña. They were at -0.15 deg C, a decrease since the prior month…having declined about -0.43 deg C since May. (The Weekly data, as shown near the end of the post, have remained well within ENSO-neutral range…that is, the equatorial Pacific is not in El Niño or La Niña phase.)
(2) NINO3.4 Sea Surface Temperature Anomalies
(5S-5N, 170W-120W)
Monthly Change = -0.43 deg C
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The sea surface temperature anomalies for the NINO3.4 region in the east-central equatorial Pacific (5S-5N, 170E-120E) are a commonly used index for the strength, frequency and duration of El Niño and La Nina events. We keep an eye on the sea surface temperatures there because El Niño and La Niña events are the primary cause of the yearly variations in global sea surface temperatures AND they are the primary cause of the long-term warming of global sea surface temperatures over the past 30 years. See the discussion of the East Pacific versus the Rest-of-the-World that follows. We present NINO3.4 sea surface temperature anomalies in monthly and weekly formats in these updates.
Also see the weekly values toward the end of the post.
INITIAL NOTES
Note 1: I’ve downloaded the Reynolds OI.v2 values from the KNMI Climate Explorer, using the base years of 1981-2010. The updated base years help to reduce the seasonal components in the ocean-basin subsets—they don’t eliminate those seasonal components, but they reduce them.
Note 2: We discussed the reasons for the elevated sea surface temperatures in 2014 in the post On The Recent Record-High Global Sea Surface Temperatures – The Wheres and Whys. For 2015, The Blob and the El Niño are responsible for the noticeable increases. See General Discussion 3 – On the Reported Record High Global Surface Temperatures in 2015 – And Will Those Claims Continue in 2016? in my ebook On Global Warming and the Illusion of Control – Part 1.
Note 3: I’ve moved the model-data comparison to the end of the post.
Note 4: I recently added a graph of the sea surface temperature anomalies for The Blob in the eastern extratropical North Pacific. It also is toward the end of the post.
Note 5: The sea surface temperature data in this post is the original (weekly/monthly, 1-deg spatial resolution) version of NOAA’s Optimum Interpolation (OI) Sea Surface Temperature (SST) v2 (aka Reynolds OI.v2)…not the (over-inflated, out-of-the-ballpark, extremely high warming rate) high-resolution, daily version of NOAA’s Reynolds OI.v2 data, which we illustrated and discussed in the recent post On the Monumental Differences in Warming Rates between Global Sea Surface Temperature Datasets during the NOAA-Picked Global-Warming Hiatus Period of 2000 to 2014.
THE EAST PACIFIC VERSUS THE REST OF THE WORLD
NOTE: This section of the updates has been revised. We discussed the reasons for the changes in the post Changes to the Monthly Sea Surface Temperature Anomaly Updates.
For years, we have shown and discussed that the surfaces of the global oceans have not warmed uniformly during the satellite era of sea surface temperature composite. In fact, some portions of the global oceans have cooled during that 3+ decade period. One simply has to look at a trend map for the period of 1982 to 2013 to see where the ocean surfaces had warmed and where they had not. Yet the climate science community has not addressed this. See the post Maybe the IPCC’s Modelers Should Try to Simulate Earth’s Oceans.
The North Atlantic (anomalies illustrated later in the post) has had the greatest warming over the past 3+ decades, but the reason for this is widely known. The North Atlantic has an additional mode of natural variability called the Atlantic Multidecadal Oscillation. If you’re not familiar with the Atlantic Multidecadal Oscillation see the NOAA Frequently Asked Questions About the Atlantic Multidecadal Oscillation (AMO) webpage and the posts An Introduction To ENSO, AMO, and PDO — Part 2 and Multidecadal Variations and Sea Surface Temperature Reconstructions. As a result of the Atlantic Multidecadal Oscillation, the surface of the North Atlantic warmed at a rate that was more than twice the rate of the surface of the rest of the global oceans. See the trend comparison graph here.
The East Pacific Ocean also stands out in the trend map linked above. Some portions of its surfaces warmed and others cooled. It comes as no surprise then that the linear trend of the East Pacific (90S-90N, 180-80W) Sea Surface Temperature anomalies since the start of the Reynolds OI.v2 composite is so low. With the strong El Nino conditions in the eastern tropical Pacific and The Blob, it has acquired a slight positive trend, but it’s still far below the approximate +0.15 deg C/decade warming rate predicted by the CMIP5 climate models. Please see Figure 19 in the post Maybe the IPCC’s Modelers Should Try to Simulate Earth’s Oceans. (Note that the region also includes portions of the Arctic and Southern Oceans.) That is, there has been little warming of the sea surfaces of the East Pacific (from pole to pole) in 3-plus decades. The East Pacific is not a small region. It represents about 33% of the surface area of the global oceans.
Notice how there appears to have been a strong El Niño event in 2014 in the East Pacific values, while there had only been a small off season event that year, and how the strong El Niño in 2015 is causing a further rise. Note also how there appears to have been a shift in 2013. Refer again to the post On The Recent Record-High Global Sea Surface Temperatures – The Wheres and Whys.
(3) East Pacific Sea Surface Temperature (SST) Anomalies
(90S-90N, 180-80W)
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That leaves the largest region of the trend map, which includes the South Atlantic, the Indian and West Pacific Oceans, with the corresponding portions of the Arctic and Southern Oceans. Sea surface temperatures there warmed in very clear steps, in response to the significant 1986/87/88 and 1997/98 El Niño/La Niña events. It also appears as though the sea surface temperature anomalies of this subset have made another upward shift in response to the 2009/10 El Niño and 2010/11 La Niña events. I further described the ENSO-related processes that cause these upward steps in the recent post Answer to the Question Posed at Climate Etc.: By What Mechanism Does an El Niño Contribute to Global Warming?
As you’ll note, the values for the South Atlantic, Indian and West Pacific Oceans appear now to be responding to the El Nino. Will we see an uptick like that associated with the 1997/98 El Niño?
(4) Sea Surface Temperature Anomalies of The South Atlantic-Indian-West Pacific Oceans
(Weighted Average of 0-90N, 40E-180 @ 27.9% And 90S-0, 80W-180 @72.1%)
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The periods used for the average temperature anomalies for the South Atlantic-Indian-West Pacific subset between the significant El Niño events of 1982/83, 1986/87/88, 1997/98, and 2009/10 are determined as follows. Using the original NOAA Oceanic Nino Index (ONI) for the official months of those El Niño events, I shifted (lagged) those El Niño periods by six months to accommodate the lag between NINO3.4 SST anomalies and the response of the South Atlantic-Indian-West Pacific Oceans, then deleted the South Atlantic-Indian-West Pacific values that corresponds to those significant El Niño events. I then averaged the South Atlantic-Indian-West Pacific Oceans sea surface temperature anomalies between those El Niño-related gaps.
You’ll note I’ve ended the updates for the period after the 2009-10 El Niño. That was done to accommodate the expected response to the 2015/16 El Niño.
The Sea Surface Temperature anomalies of the East Pacific Ocean, or approximately 33% of the surface area of the global oceans, have shown comparatively little long-term warming since 1982 based on the linear trend. And between upward shifts, the Sea Surface Temperature anomalies for the South Atlantic-Indian-West Pacific subset (about 52.5% of the global ocean surface area) remain relatively flat, though they actually cool slightly. Anthropogenic forcings are said to be responsible for most of the rise in global surface temperatures over this period, but the Sea Surface Temperature anomaly graphs of those regions discussed above prompt a two-part question: Since 1982, what anthropogenic global warming processes would overlook the sea surface temperatures of 33% of the global oceans and have an impact on the other 52% but only during the months of the significant El Niño events of 1986/87/88, 1997/98 and 2009/10?
They were also discussed in great detail in my recently published book Who Turned on the Heat? The Unsuspected Global Warming Culprit, El Niño-Southern Oscillation. The Free Preview includes the Table of Contents; the Introduction; the beginning of Section 1, with the cartoon-like illustrations; the discussion About the Cover; and the Closing. Also see the blog post Everything You Every Wanted to Know about El Niño and La Niña… for an overview. It’s now free. Click here for a copy.
STANDARD NOTE ABOUT THE REYNOLDS OI.V2 COMPOSITE
The MONTHLY graphs illustrate raw monthly OI.v2 sea surface temperature anomalies from November 1981 to June 2016, as it is presented by the KNMI Climate Explorer. While NOAA uses the base years of 1971-2000 for this product, those base years cannot be used at the KNMI Climate Explorer because they extend before the start year of the product. (NOAA had created a special climatology for the Reynolds OI.v2 product.) I’ve referenced the anomalies to the period of 1981 to 2010, which is actually 1982 to 2010 for most months.
MONTHLY INDIVIDUAL OCEAN AND HEMISPHERIC SEA SURFACE TEMPERATURE UPDATES
(5) Northern Hemisphere Sea Surface Temperature (SST) Anomalies
Monthly Change = +0.08 deg C
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(6) Southern Hemisphere Sea Surface Temperature (SST) Anomalies
Monthly Change = +0.00 deg C
####################################
(7) North Atlantic Sea Surface Temperature (SST) Anomalies
(0 to 70N, 80W to 0)
Monthly Change = -0.01 deg C
####################################
(8) South Atlantic Sea Surface Temperature (SST) Anomalies
(0 to 60S, 70W to 20E)
Monthly Change = +0.09 deg C
####################################
(9) Pacific Sea Surface Temperature (SST) Anomalies
(60S to 65N, 120E to 80W)
Monthly Change = +0.10 Deg C
####################################
(10) North Pacific Sea Surface Temperature (SST) Anomalies
(0 to 65N, 100E to 90W)
Monthly Change = +0.18 Deg C
####################################
(11) South Pacific Sea Surface Temperature (SST) Anomalies
(0 to 60S, 120E to 70W)
Monthly Change = +0.02 deg C
####################################
(12) Indian Ocean Sea Surface Temperature (SST) Anomalies
(60S to 30N, 20E to 120E)
Monthly Change = -0.19 deg C
####################################
(13) Arctic Ocean Sea Surface Temperature (SST) Anomalies
(65N to 90N)
Monthly Change = +0.20 deg C
####################################
(14) Southern Ocean Sea Surface Temperature (SST) Anomalies
(90S-60S)
Monthly Change = +0.08 deg C
####################################
WEEKLY SEA SURFACE TEMPERATURE ANOMALIES
Weekly NINO3.4 sea surface temperature anomalies are at -0.4 deg C, within the realm of ENSO neutral (not El Niño and not La Niña). Based on the weekly Reynolds OI.v2 data, they peaked at a higher anomaly than the 1997/98 El Niño. But as discussed in the post Is the Current El Niño Stronger Than the One in 1997/98?, the 1997/98 El Niño was a stronger East Pacific El Niño than the one taking place now. If you’d like to argue that this is the strongest El Niño EVER, also see the post The Differences between Sea Surface Temperature Datasets Prevent Us from Knowing Which El Niño Was Strongest According NINO3.4 Region Temperature Data.
(15) Weekly NINO3.4 Sea Surface Temperature (SST) Anomalies
You’ll note that I also included a comparison of the evolutions of the NINO3.4 sea surface temperature anomalies for the 1997/98 and 2015/16 El Niños. Just wanted to show that the transition this year toward La Niña is starting to lag behind the transition in 1998.
Note: I’ve used the weekly NINO3.4 values available from the NOAA/CPC Monthly Atmospheric & SST Indices webpage, specifically the listing here.
####################################
MODEL-DATA COMPARISON: To counter the nonsensical “Just what AGW predicts” rantings of alarmists about the “record-high” global sea surface temperatures in 2014 and 2015, I’ve added a model-data comparison of satellite-era global sea surface temperatures to these monthly updates. See the example below. The models are represented the multi-model ensemble-member mean of the climate models stored in the CMIP5 archive, which was used by the IPCC for their 5th Assessment Report. For further information on the use of the model mean, see the post here. For most models, historic forcings run through 2005 (2012 for others) and the middle-of-the-road RCP6.0 forcings are used after in this comparison. The data are represented by NOAA’s Optimum Interpolation Sea Surface Temperature data, version 2—a.k.a. Reynolds OI.v2—which is NOAA’s best. The model outputs and data have been shifted so that their trend lines begin at “zero” anomaly for the (November, 1981) start month of this composite. That “zeroing” helps to highlight how poorly the models simulate the warming of the ocean surfaces…noticeably higher than the observed warming rate. Both the Reynolds OI.v2 values and the model outputs of their simulations of sea surface temperature (TOS) are available to the public at the KNMI Climate Explorer.
000 – Model-Data Comparison
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THE BLOB
After decades of no surface warming in the North Pacific as a whole, a prolonged weather event in the eastern extratropical North Pacific caused an unusual and unexpected warming there, raising sea surface temperatures in the North Pacific to new levels. That region of unusually warm sea surfaces in the eastern extratropical North Pacific has become known as The Blob. We’ve discussed The Blob in detail in the post North Pacific Update: The Blob’s Strengthening Suggests It’s Not Ready to Depart. There are links to numerous earlier discussions of the North Pacific in that post, some reaching back as far as the boreal summer of 2013. And the most recent Blob update is here.
The Blob had returned to the neighborhood of “Normal” values, but it has made sizeable upticks since April. We’ll keep an eye on it for a few more months to see if it reemerges.
(16) The Blob
(40N-50N, 150W-130W)
Monthly Change = +0.09 deg C
Note: I’ve changed the coordinates for The Blob to 40N-50N, 150W-130W to agree with those used in the NOAA/NCEP Monthly Ocean Briefing. I had been using the coordinates of 35N-55N, 150W-125W for The Blob.
INTERESTED IN LEARNING MORE ABOUT HOW DATA SUGGEST THE GLOBAL OCEANS WARMED NATURALLY?
Why should you be interested? The hypothesis of manmade global warming depends on manmade greenhouse gases being the cause of the recent warming. But the sea surface temperature record indicates El Niño and La Niña events are responsible for the warming of global sea surface temperature anomalies over the past 32 years, not manmade greenhouse gases. Scroll back up to the discussion of the East Pacific versus the Rest of the World. I’ve searched sea surface temperature records for more than 4 years, and I can find no evidence of an anthropogenic greenhouse gas signal. That is, the warming of the global oceans has been caused by Mother Nature, not anthropogenic greenhouse gases.
My e-book (pdf) about the phenomena called El Niño and La Niña is titled Who Turned on the Heat? with the subtitle The Unsuspected Global Warming Culprit, El Niño Southern Oscillation. It is intended for persons (with or without technical backgrounds) interested in learning about El Niño and La Niña events and in understanding the natural causes of the warming of our global oceans for the past 30 years. Because land surface air temperatures simply exaggerate the natural warming of the global oceans over annual and multidecadal time periods, the vast majority of the warming taking place on land is natural as well. The book is the product of years of research of the satellite-era sea surface temperature data that’s available to the public via the internet. It presents how the data accounts for its warming—and there are no indications the warming was caused by manmade greenhouse gases. None at all.
Who Turned on the Heat? was introduced in the blog post Everything You Ever Wanted to Know about El Niño and La Niña… …Well Just about Everything. The Free Preview includes the Table of Contents; the Introduction; the beginning of Section 1, with the cartoon-like illustrations; the discussion About the Cover; and the Closing.
Who Turned on the Heat? is now free. Click here for a copy.
A NEW BOOK AND IT’S FREE
I also published On Global Warming and the Illusion of Control (25MB .pdf) back in November. The introductory post is here.
SOURCES
The monthly Sea Surface Temperature (SST) anomalies, the map and model outputs used in this post are available from the KNMI Climate Explorer.
Bob Tisdale - Climate Observations 
Pingback: Absturz der globalen Temperaturen! Ungewöhnlich schwache Sonne – La Niña kommt: „Global Warming“ Reality Check Juni 2016 – wobleibtdieglobaleerwaermung
Thanks, again, Bob.
Dave
Great update Bob and always great work.
Ot
Anyway you can chart all great lakes ice years(yearly max coverage) with solar cycles & PDO from past 50 years?
Results Should show years with highest ice are all around solar cycle bottoms for the exception of 13-14 and 14-16 winters at the peak of lowest cycle in 200 years.
Thanks Bob.
14-15
Thanks Bob
A while back (2008&2013) you did pieces on the Interdecadal Pacific Oscillation. Recently IPO cited for the changes in Antarctic sea ice… So I poked around and found this on IPO and global temp and precipitation
https://www.researchgate.net/profile/Bo_Dong18/publication/272366368_The_influence_of_the_Interdecadal_Pacific_Oscillation_on_Temperature_and_Precipitation_over_the_Globe/links/570d0d3508aed31341cf012d.pdf?origin=publication_detail
I don’t know if that is anything meaningful. Anything you have new on IPO?
Alec, thanks for the link. Unfortunately, I haven’t written anything about the IPO for a couple of years.
https://bobtisdale.wordpress.com/?s=Interdecadal+Pacific+Oscillation
Bob,
At figure 4 you showed uptics in temperatures after each El Nino event. From such plots (and other evidence) you have made a conclusion that El Ninos (and not CO2) are the reason of recent warming (e.g. from 1980 till now). Am I right in this sentence?
Then if strong El Nino events are causing warming, what should cause cooling (without cooling oceans could boil during holocene)? And why we didn’t observe cooling between El Ninos during recent period (from 1980 till now)?
Sorry, if I ask something that you already explained. But I have read many of your posts and didn’t find the answer on this question in them.
Pavel says: “At figure 4 you showed uptics in temperatures after each El Nino event.”
After each STRONG El Niño event. Not every El Niño is capable of releasing enough warm water from below the surface of the western tropical Pacific to cause an upward shift in global surface temperatures.
Pavel says: “From such plots (and other evidence) you have made a conclusion that El Ninos (and not CO2) are the reason of recent warming (e.g. from 1980 till now). Am I right in this sentence?”
You are correct in that statement, inasmuch as the leftover warm waters from strong El Niño events caused upward shifts in the surface temperatures of the South Atlantic, Indian and West Pacific Oceans. More specifically, ENSO acts as a chaotic, naturally occurring, sunlight-fueled recharge-discharge oscillator.
Pavel says: “Then if strong El Nino events are causing warming, what should cause cooling (without cooling oceans could boil during holocene)?”
Boil? Don’t you think you’re exaggerating with boil? If a strong El Niño is capable of raising the sea surface temperatures of 50% of the global oceans about 0.2 deg C, and if strong El Niño events occur at 5 to 10 year intervals, how long would take to raise sea surface temperatures that high, Pavel?
Pavel says: “And why we didn’t observe cooling between El Ninos during recent period (from 1980 till now)?”
Why would there be cooling? Are you assuming the Earth was in an energy balance before 1980? If so, then what caused surface temperatures to warm from the 1910s to the 1940s?
Bob, What really recently was the story about Lake Poopo in Bolivia drying up, big lake but only 9′ deep, just El Niño. But in the article was this:
“The temperature on the plateau had increased 0.9 degrees Celsius, or about 1.6 degrees Fahrenheit, from 1995 to 2005 alone, much faster than Bolivia’s national average.”
http://www.nytimes.com/interactive/2016/07/07/world/americas/bolivia-climate-change-lake-poopo.html?emc=edit_th_20160708&nl=todaysheadlines&nlid=39625020&_r=1
0.9 is a big number… in the middle of 1995-2005 is 2000 when IPO transitioned from positive to negative.
When I looked at the correlation map in the temp study Bolivia is indicated as a high positive….
Alec, this is my favorite “…lakes in Canada and Mongolia are jeopardized by rising temperatures.”
Aren’t they aware that there’s supposed to be more moisture in the atmosphere and increased precipitation with global warming?
Cheers
Bob Tisdale says: Boil? Don’t you think you’re exaggerating with boil? If a strong El Niño is capable of raising the sea surface temperatures of 50% of the global oceans about 0.2 deg C, and if strong El Niño events occur at 5 to 10 year intervals, how long would take to raise sea surface temperatures that high, Pavel?
Let’s calculate. Let’s take 10 years as average period between strong El Nino. Then each 10 years there should be 0.2 degC rise, each 100 years – 2 degC rise, each 1000 years – 20 degC rise, each 10000 years – 200 degC rise. Holocene duration is about 14000 years (if I’m not mistaken), so there was enough time to start boiling. Of course this is exaggerating but it shows that cooling between El Ninos should be normal behaviour. And thus the absence of cooling between El Ninos in recent period (from 1980 till now) need some explanation. If this explanation is not CO2 (I also think that it is not CO2 and, if you are interested, can write my arguments letter) then we should suggest some other explanation. What do you think about this?
Pavel, after your quick calculation, you wrote, “Of course this is exaggerating but it shows that cooling between El Ninos should be normal behaviour.”
That’s a monstrous assumption on your part. You’re assuming, for your example, that the strength, frequency, duration and aftereffects of ENSO we’ve seen during the satellite era had been the same prior to 1982 and throughout the Holocene. The differences between long-term sea surface temperature reconstructions (Kaplan, HADISST, HADSST3, ERSST.v3b and ERSST.v4) are so great that they are of little research value related to ENSO and its long-term impacts. Some show multidecadal variations in the strength, frequency and duration of ENSO. Others do not. Some show positive trends in NINO3.4 region sea surface temperature anomalies since 1900. Others do not. (Kaplan SST has a negative trend for NINO3.4 SSTa, and with HADISST, the trend of NINO3.4 SSTa is basically flat.) All however show a sudden shift in the strengths of El Nino events starting in the 1970s.
Also, you’re reading way too much into what I’ve illustrated and discussed. I’ve simply presented ENSO processes and their impacts over the past 30+ years, the satellite era. Other sea surface temperature datasets (ERSST.v3b and HADSST3) show that the sea surface temperatures for the South Atlantic, Indian and West Pacific Oceans have responded to ENSO in this way during that time period.
One of my early examinations of HADSST3 data suggest that there were also upward shifts in the sea surface temperatures of the East Indian/West Pacific subset in response to the 1918/19/20 and 1939-41 El Ninos. See Figure 8-20 and Chapter 8.12 of my ebook here:
Click to access v2-tisdale-who-turned-on-the-heat-free-edition.pdf
But they only appear in the HADSST3 data as far as I know.
Speaking of upward shifts, please allow me to ask a few questions, assuming you are the author of the 2015 paper “Hidden staircase signal in recent climate dynamic”, which examines global surface temperature data since 1950. (I have not read the paper yet.)
http://link.springer.com/article/10.1007%2Fs13143-015-0081-6
The abstract mentions upward shifts in 1987/88 and 1997/98 and the existence of a “regulation mechanism in climate system”. What was the “regulation mechanism” you found and what did you propose for the mechanism that caused the upward shifts in 1987/88 and 1997/98?
Regards.
Most Recent 6 Months
Sea Surface Temperature Anomaly Animation
(Pacific Ocean)
A negative Indian Ocean Dipole (IOD) pattern has established in the Indian Ocean.
Current weekly IOD index values are the lowest in at least the past 15 years. Climate models predict the negative IOD pattern will persist and develop through the southern winter and spring.
A negative IOD typically brings above-average rainfall to southern Australia during winter-spring, with cooler-than-average daytime temperatures across southern Australia, and warmer day and night-time temperatures in northern Australia. Find out more about the Indian Ocean Dipole.
In the tropical Pacific Ocean, sea surface temperatures have continued to cool in recent weeks. With all ocean and atmospheric indicators near normal, the tropical Pacific Ocean is in a neutral El Niño–Southern Oscillation (ENSO) state.
However, a large volume of cooler than normal water below the ocean surface suggests La Niña remains possible in 2016. Recent observations, combined with current climate model outlooks, have left the Bureau’s ENSO Outlook unchanged at La Niña WATCH. This means the likelihood of La Niña forming later in 2016 is around 50%.
Typically during La Niña, winter-spring rainfall is above average over northern, central and eastern Australia. If La Niña does develop, climate models suggest it is unlikely to reach levels seen in the most recent event of 2010–12—one of the strongest La Niña events on record.
http://media.bom.gov.au/releases/278/negative-indian-ocean-dipole-emerges-as-pacific-ocean-remains-neutral/
Weekly data to 10 Jul 2016.
Reblogged this on Climate Collections.
Bob, I’m sorry for not quick reply – several jobs lead to permanent lack of time.
You’re right that, I’m one of the authors of “Hidden staircase signal in recent climate dynamic” paper. It is freely available on researchgate:
Click to access 565bc41208ae1ef92980fba7.pdf
In this study we by means of simple statistical methods observed the same as you upward shifts following 1987/88 and 1997/98 El Ninos. We considered HadCRUT4 dataset for 1950-2014 period. We know that ENSO variations produce short-term significant variations of temperature especially in East Pacific. The idea was to look on temperature anomalies dynamic adjusted for these variations. We didn’t consider here any aftereffects and nonlinear responses to ENSO. But largest temperature anomalies changes approximately linearly related to ENSO indexes. So we subtract linear projection of ENSO index on HadCRUT4 dataset from initial dataset. We called obtained field “ENSO adjusted HadCRUT4”. Of course, it is not adjustment for all ENSO effects but for most of cyclical component. And it was interesting to look on this new field.
Global timeseries of ENSO adjusted HadCRUT4 looked as staircase with quasi-stable 1950-1987, 1988-1997 (taking into account 1991 Pinatubo erruption) and 1998-2014 periods with upward shifts following 1987/88 and 1997/98 El Ninos. As you mentioned not all the El Ninos followed by upward shifts (for example no effect after 1972 El Nino). Also one of the interesting results is that well-known 1976/1977 shift disappeared in our ENSO adjusted field. This means that it was closely connected with ENSO variability and without 1987/1988 upward shift global temperatures should return to pre-1976 values after 1988. Another interesting result is that upward changes became visible in East Pacific SST anomalies (1987/88 and 1997/98 shifts observed can be observed, but not very clear).
The thing that looks most curious for me is the existence of quasi-stable periods nevertheless of growing greenhouse forcing. You also showed flat periods in many of you plots. It is a sign of thermo-regulating mechanism. Of course I need to write more explanations here, but it is time to finish my comment. If you are interested – ask questions and I will try to answer. And I don’t know what mechanism is exactly – Willis Eschenbach thermostat looks quite adequate. As for the reasons of 1987/88 and 1997/98 shifts we consciously didn’t discuss this question. It is likely that as you described that heat distributed by El Nino triggered 1987/88 and 1997/98 events. But these El Ninos should also produce some changes to regulating mechanism. In other case El Nino heat should quickly disappear, like cooling produced by Pinatubo eruption.
Also the same periods and shifts were detected by John McLean (his methods and conclusions have differences):
https://wattsupwiththat.com/2014/10/30/new-paper-links-warming-since-1950-to-enso-and-cloud-cover-variations/
Bob, I will be happy if you read our article and write your opinion. And If you interested we can discuss interesting moments. I suppose our results have much common.
Regards.
Pavel, thank you for the link to your paper. I’ll try to study it on Wednesday.
Cheers.
Pavel, please confirm the equation you used for removing the ENSO signal from HADCRUT4 data.
It appears you first calculated the 1st PC of detrended global HADSST3 data from 1950 to 2014 for your ENSO signal. You then subtracted that ENSO signal from global HADCRUT4 data.
Bob, you wrote: “Pavel, please confirm the equation you used for removing the ENSO signal from HADCRUT4 data. It appears you first calculated the 1st PC of detrended global HADSST3 data from 1950 to 2014 for your ENSO signal. You then subtracted that ENSO signal from global HADCRUT4 data.”
Yes, in a paper was described this variant. Also we currently preparing a paper in which applied the same analysis to the satellite-based datasets. The draft with obtained figures is here:
https://www.researchgate.net/profile/Pavel_Belolipetsky/project/Staircase-signal-in-satellite-based-datasets/attachment/5790525308aeb59d9d33e920/AS:386147101495297@1469076051842/download/Staircase+signal_30_05.doc?context=projectDetails
You also can easily reproduce results using Climate Explorer site. I have written a step by step instructions as supplementary in 2014 preprint:
Click to access 53db64f00cf2e38c6339ae70.pdf
Pavel, thank you for the links, especially the step by step instructions for Climate Explorer.
If I simply use a spreadsheet to subtract the 1st PC of the global HADSST3 data from the HADCRUT4 data I get different results. Why?
Bob, you wrote: “If I simply use a spreadsheet to subtract the 1st PC of the global HADSST3 data from the HADCRUT4 data I get different results. Why?”
Results should be the same. I have checked this feature before. I can suppose the following reasons:
1. You need to use 1st PC of the (!)detrended global HADSST3. In other case 1st PC may include warming trend.
2. If you perform analysis including pre-1950 years this may introduce some differences.
I will check this feature tomorrow and download spreadsheat.
Pavel, I’ve reread your paper and it occurs to me that the results would NOT be similar. By using the Climate Explorer to remove the linear effects of the ENSO signal, we are only removing the ENSO signal where it occurs, not globally.
Bob, I haven’t fully understand what do you mean by words “removing the ENSO signal where it occurs not globally.”
From mathematical point of view, the global average minus PC1 linear influence will be the same with average of all locals linearly adjusted for PC1. I have made comparison for HadSST3 dataset. You can set the resulting Excel file here:
https://www.researchgate.net/profile/Pavel_Belolipetsky/project/Staircase-signal-in-satellite-based-datasets/attachment/57919bef08ae03b41910bdcc/AS:386501016866816@1469160431967/download/Climexp+spreadsheat+comparison.xlsx?context=projectDetails
The only difference was constant difference due to anomalies calculation related to different means. After adding the constant results became absolutely similar. The aim to use the projection by means of Climate Explorer was my interest to regional behavior during shifts. Also it allowed to respond on some critique.
Probably, by “removing the ENSO signal where it occurs” you mean that we are not removing all ENSO effects but only in the place of origin. I’m fully agree. Residuals of ENSO influence are visible: in some places they may be lagged, in some – non-linearly related to index, we don’t distinguish between normal El Nino and El Nino Mudoki and etc. Nevertheless, suggested simple adjustment allows removing largest part of short-term effect on global temperature anomalies. And this allowed us to see the effects masked by ENSO variations in initial datasets.
Bob, I want to ask you as one of the best specialists on ENSO, do you think that suggested in paper simple adjustment is adequate?
Pavel, of course you are correct that “the global average minus PC1 linear influence will be the same with average of all locals linearly adjusted for PC1”. The results are basically the same:
That was what I had originally expected.
My recent statement was based on a comparison I had made (but had not presented) of the unadjusted HADCRUT4 data to the adjusted HADCRUT4 data minus the 1st PC of the HADSST3 data. I could not see the upward steps. In fact, the adjusted data increased the warming rate from 2001-2013, reducing the global warming hiatus then.
In fact, there is very little difference between the adjusted and unadjusted data, other than to increase the post 2001 warming rate.
The ENSO-caused hidden staircase does exist in the HADSST3 data. I’ve been illustrating it for years. It’s in the sea surface temperature anomalies of the Atlantic, Indian and West Pacific Oceans (90-90N, 80W-180).
There is no need for adjustment. It simply exists in the data.
Bob, you are great!
I like very much you last figure. This is the illustration of the same feature as we observed but obtained much simpler. I’m sorry but I’ve missed such figure with exactly such staircase in your previuous publications. In future I will always make reference.
You wrote: “There is no need for adjustment. It simply exists in the data”.
I don’t want to dispute your opinion. Probably you are right. But may be for some people our approach will provide additional arguments confirming your results. And also we have presented staircase in reanalysis data – this is additional independent argument. In any case it is good to came to the same results by different ways.
And let’s discuss last figure with ENSO-caused hidden staircase. I’m sorry if I take much of you time. But I suppose this is in the scope of your interests (like mine) and this discussion could be valuable for both of us. If I bore you – please write and I will not continue.
Returning to figure I think that quasi-stationary 1950-1986, 1987-1997 and 1998-2009 periods are very curious. We know that during each of these periods there was growing CO2 forcing. But there was no any respounces inside the periods. I see to possible explanations:
1. CO2 forcing is insignificantly small. This is in contradiction with radiation-convection vertical models of atmosphere. (looks less probable to me)
2. Climate system has regulating mechanism (thermostat) maintaining global temperature near some constant during each quasi-stationary period. Additional argument for this explanation is that influence of solar cycles is also not observed. And at last after the end of Pinatubo erruption effects temperatures quickly returned to pre-erruption level.
Then the coseqence of second explanation is that ENSO-caused 1987 and 1998 shifts changed thermostat target point. In other case temperatures should return quickly to pre-1987 or pre-1998 levels, like after Pinatubo erruptions.
What do you think about such ideas.
HadCRUT4:
ENSO Adjusted HadCRUT4:
I wanted just to insert pictures in comment but it was not successfully. I will make another attempt.
HadCRUT4:
ENSO Adjusted HadCRUT4:
Bob, how to insert pictures in comment?
Looks like they worked, Pavel. And they confirmed my two illustrations above.
With respect to your July 22, 2016 at 9:56 pm comment, I will agree that the ENSO-caused steps suggest an extremely low sensitivity to CO2 and/or a mechanism that regulates sea surface temperatures between ENSO-caused upward steps.
Basically, strong El Nino events relocate a tremendous volume of sunlight-created warm water from beneath the surface of the West Pacific Warm Pool to the surface. The warm water resides temporarily in the East Pacific during the El Nino and afterwards the warm water is relocated to the Atlantic, Indian, and West Pacific Oceans.
Cheers.
Nice, after moderation pictures appeared.
Bob, in one of your pictures at previous comment you compared adjusted and initial HadCRUt4 and wrote: “I could not see the upward steps. ”
I also couldn’t see steps and quasi-stationary periods on this figure. But I clearly see staircase in figures at my paper. I have rechecked calculations and found that we have different results of adjustment. Probably you just subtracted PC1 without making regression on HadCRUT4 dataset?
In a previous comments I have inserted initial and adjusted HadCRUT4. And from my point of view steps are clearly seen in adjusted dataset. Do you agree?
As for the trend during pause – I don’t care about this. Datasets were so many times corrected in order to increase warming trend. So it is not surprising that trend became visible. But in comparison with magnitude of steps it is near zero.
P.S. I will examine my instructions – probably I have missed something.
Pavel says: “As for the trend during pause – I don’t care about this…”
But everyone else does. If the trend from 2001-2014 is similar to the trend from 1950-2014, then it’s no longer a pause.
Bob, a niggling comment:
1950-2014 includes the 1950-1975 “decline” in the global temperature estimates. The 2001-2014 estimate period includes the 2013-2014 “blob” and the 2014 aborted El Nino.
Only in the Gavin Schmidt world is the “hiatus” equivalent to the post-1950 “tend.” One needs to abuse both endpoints to make that assertion.
Dave Fair
Moderator, did my use of “niggling” throw me into moderation?
I am aware of thin-skinned reactions to mere similar-sounding words, evidenced by the supposedly educated guy who jumped up and objected to the word “niggardly” in a professional presentation. We don’t even have to go to college “snowflake” examples.
Sheese.
Dave Fair
Dave, you were simply awaiting moderation. I moderate all comments….and I don’t have any words listed in my filters to throw a comment into spam.
Cheers.
Thanks, Bob. Given the current state of U.S. social/political discourse, I’m probably overly sensitive to what I perceive as attempts at speech and thought control by public authorities and the media.
Dave
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