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Wednesday, September 24, 2008

Tropical SST Anomalies Revisited - Introduction

INTRODUCTION

In their recent paper “Limits on CO2 Climate Forcing from Recent Temperature Data of Earth”, Douglass and Christy state in their summary remarks, “An underlying temperature trend of 0.062±0.010 deg K/decade was estimated from data in the tropical latitude band. Corrections to this trend value from solar and aerosols climate forcings are estimated to be a fraction of this value. The trend expected from CO2 climate forcing is 0.070g degC/decade, where g is the gain due to any feedback. If the underlying trend is due to CO2 then g~1. Models giving values of g greater than 1 would need a negative climate forcing to partially cancel that from CO2. This negative forcing cannot be from aerosols.” The if statement, “If the underlying trend is due to CO2 then g~1,” drives the conclusion about the underlying trend. Suppose there are other easily observable variables that would reduce the CO2 contribution.

The intent of this post is not to define the values of the forcings, but to identify any oceanic oscillations that can be used to explain all or part that warming. I will post hemispheric tropical data for individual oceans and attempt to identify the sources of their variations in subsequent posts.

GLOBAL AND HEMISPHERIC TROPICAL SST ANOMALIES

Figure 1 illustrates monthly Global and Tropical SST Anomaly data from January 1854 to August 2008. The data have been smoothed with 85-month running-average filters. There is a period of substantial difference between 1945 and 1975. During that time, tropical SST anomalies dipped well below global SST anomalies. Other than that, the two data sets correlate well.


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Figure 1

In Figure 2, I’ve divided the data at the equator, creating Northern and Southern Tropical SST anomaly data sets. The dip from 1945 to 1975 was most prevalent in the Southern Hemisphere.
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Figure 2

Recent short-term Tropical SST Anomaly data for both hemispheres is illustrated in Figure 3. Note that the Southern Hemisphere responses to the two major El Nino events are larger than the Northern Hemisphere. Does this indicate a difference in how the two El Nino events originated? Or does it reflect a difference in how the two hemispheres react?
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Figure 3

DIVIDING THE DATA SETS FURTHER – TWO PROBLEM AREAS

In the tropics of the Northern Hemisphere, the Atlantic and Pacific Oceans are separated by Central America. Refer to Figure 4. And in the tropics for the Southern Hemisphere, the border between the Indian and Pacific Oceans is normally represented to include Sumatra, the Lesser Sunda Islands, then on to Australia.
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Figure 4

These two borders do not lend themselves to being separated at single longitudes, which is required by the NOAA NOMADS system, the source of the data used in these Smith and Reynolds SST posts. Are the differences between the data between those oceans significant enough for concern? Or does a similarity with only one of the two oceans suggest that those areas be included in one but not the other data set? Or are should they be excluded so not to unduly influence either data? Only one way to find out.

Figure 5 shows SST anomalies for the Tropical North Atlantic, for the Tropical Northeast Pacific, and for Mixed Atlantic-Pacific Data, the area that separates the prior two. At this stage, the mixed data was not included in the Atlantic or Pacific data. There is enough difference between the three data that I’ve elected to exclude the Mixed Atlantic-Pacific Data completely. I’ll just have to consider it if an unusual bias unveils itself in subsequent posts.
http://i37.tinypic.com/15d8cqt.jpg
Figure 5

I went through the same process for the Indian, West Pacific, and the Mixed Indian-Pacific data sets for the Southern Tropics. Refer to Figure 6. While the Mixed data has greater variations than the Southern Tropical Indian Ocean data, a result possibly of the small geographic area, it’s clear that the Mixed data does follow the underlying trends of the Indian Ocean data. This is further illustrated by the short-term data in Figure 7. I will include the Mixed data with the Indian Ocean.
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Figure 6



http://i36.tinypic.com/2lmw9jn.jpg
Figure 7

Figure 8 is just a graphic with notes to document those conclusions.
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Figure 8

COORDINATES TO BE USED FOR THE INDIVIDUAL OCEANS

The last illustration, Figure 9, is the global Mercator projection that shows the areas to be looked at in the following posts and their coordinates.
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Figure 9

SOURCE

Sea Surface Temperature Data is Smith and Reynolds Extended Reconstructed SST (ERSST.v2) available through the NOAA National Operational Model Archive & Distribution System (NOMADS).
http://nomads.ncdc.noaa.gov/#climatencdc

Wednesday, September 17, 2008

August 2008 SST and SOI Update

CORRECTION - November 7, 2008

In the opening paragraph of this post, I make the following statement: “I’ve added graphs of NINO3.4 SST anomaly, since it’s a driver of global temperature anomaly (lag 3 to 5 months), and the Southern Oscillation Index, because it precedes NINO3.4 by a few months.”

The NINO3.4 SST anomaly does NOT always follow the SOI, though it has been doing so for the past few months. They do correlate remarkably well, but there are times when the changes in NINO3.4 will precede the SOI and times when they can become slightly out of synch. Therefore, I’ll retract the blanket statement of the SOI preceding NINO3.4 by a few months.

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All graphs are from January 1978 to August 2008.

I’ve added graphs of NINO3.4 SST anomaly, since it’s a driver of global temperature anomaly (lag 3 to 5 months), and the Southern Oscillation Index, because it precedes NINO3.4 by a few months. For those not familiar with the SOI, I’ve also inverted it to permit a comparison to NINO3.4 SST anomaly.

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1. NINO3.4 SST Anomaly – Monthly Change = +0.181 deg C


http://i38.tinypic.com/etuu5i.jpg
2. SOI – Monthly Change = +6.9


http://i37.tinypic.com/2zs7akw.jpg
3. Inverted SOI – Monthly Change = -6.9

I’ve also added the following SST anomaly graphs:
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4. Global – Monthly Change = +0.022 deg C


http://i37.tinypic.com/n4abf7.jpg
5. Northern Hemisphere – Monthly Change = -0.02 deg C


http://i37.tinypic.com/24zbr11.jpg
6. Southern Hemisphere – Monthly Change = +0.055 deg C


The remainder:

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7. North Atlantic (0 to 75N, 70W to 10E) – Monthly Change = +0.004 deg C


http://i34.tinypic.com/15xx06g.jpg
8. South Atlantic (0 to 60S, 70W to 20E) – Monthly Change = -0.041 deg C


http://i33.tinypic.com/10yo0ac.jpg
9. North Pacific (0 to 65N, 90 to 180W) & (0 to 65N, 100 to 180E) – Monthly Change = -0.038 deg C


http://i35.tinypic.com/fcrx1e.jpg
10. South Pacific (0 to 60S, 70 to 180W) & (0 to 60S, 145 to 180E) – Monthly Change = +0.061 deg C


http://i35.tinypic.com/2639dur.jpg
11. Indian Ocean (30N to 60S, 20 to 145E) – Monthly Change = +0.104 deg C


http://i38.tinypic.com/mn1boo.jpg
12. Arctic Ocean (65 to 90N) – Monthly Change = +0.101 deg C


http://i35.tinypic.com/2ikzivd.jpg
13. Southern Ocean (60 to 90S) – Monthly Change = +0.033 deg C

SOURCE

Sea Surface Temperature Data is Smith and Reynolds Extended Reconstructed SST (ERSST.v2) available through the NOAA National Operational Model Archive & Distribution System (NOMADS).
http://nomads.ncdc.noaa.gov/#climatencdc

Tuesday, September 16, 2008

GISS Model E Climate Simulations Part 2

INITIAL NOTE

The following is a continuation of the thread titled “GISS Model E Climate Simulations”.
http://bobtisdale.blogspot.com/2008/09/giss-model-e-climate-simulations.html

GISS MODEL E CLIMATE SIMULATION WITHOUT VOLCANIC AEROSOL FORCING

In the first part of this series, I noted how the curve of the GISS Model E climate simulation with all forcings had the “appearance…of a noisy exponential curve with the effects of volcanic eruptions added.” Refer to Figure 1, in which I've smoothed the data to reduce the noise.

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Figure 1

I failed to include an illustration of that GISS Model E Climate Simulation with the volcanic aerosols removed, which also would have illustrated the effect. So I simply subtracted the smoothed data of the GISS Model E climate simulation for volcanic aerosols from the smoothed data of the climate simulation for all forcings. The result is shown in Figure 2.

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Figure 2

Compared again to the GISTEMP representation of global temperature anomaly, the correlation, or lack thereof, is clearly visible.
http://i37.tinypic.com/2a68ggp.jpg
Figure 3

In the GISS Model E climate simulation data, note the obvious absence of the impacts of oceanic oscillations such as the El Nino-Southern Oscillation (ENSO), the Atlantic Multidecadal Oscillation (AMO), and the North Pacific Residual.

COMPARISON OF SIMULATION OF ALL FORCINGS AND GLOBAL TEMPERATURE ANOMALY

As noted in the first post of this series, with the volcanic aerosols in place, Figure 4, the variance between the GISS Model E climate simulation for all forcings and the GISTEMP global temperature anomaly curves appears to result from their failure to include oceanic variables in the simulation.
http://i37.tinypic.com/2h4aza1.jpg
Figure 4

CLOSING

ENSO, the AMO, and the North Pacific Residual contributed significantly to the warming from 1910 to 1940 and from the late 1970s to 2003, and contributed to the cooling period from 1940 to the late 1970s. The attempts by climatologists to duplicate global temperature anomaly without accounting for these oceanic oscillations is folly. Establishing a trend without the oceanic variables and extending that trend forward in time to predict the impacts of anthropogenic greenhouse gases on future climate clearly distorts reality.

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