I’ve moved to WordPress. This post can now be found at Segmented Low Latitude Northern Hemisphere TLT – Of Course ENSO and Volcanic Eruptions Dominate##############
And The El Nino Events Cause Upward Step Changes at These Latitudes, Too
Low latitude Northern Hemisphere lower troposphere temperature (TLT) anomaly data has been divided by longitudes in this post to reflect continents and oceans. As a reference, low latitude (0 to 30N) TLT anomalies of the Northern Hemisphere are illustrated in Figure 1.
ENSO events and the 1982 and 1991 volcanic eruptions of El Chichon and Mount Pinatubo dominate the lower troposphere temperatures (TLT) of the Northern Hemisphere’s lower latitudes (0 to 30N). This should be obvious in Figure 1. It will also be obvious with the segmented data, especially when compared to NINO3.4 SST anomaly and Sato Stratospheric Mean Optical Thickness data. There are two other effects worth noting in the following.
First, the bias introduced by the volcanic eruptions. The volcanic eruptions of El Chichon (1982) and Mount Pinatubo (1991) lower the global TLT anomaly data in early years, thereby increasing the overall trend. The lower latitude TLT anomaly data for the Northern Hemisphere illustrated in this post reinforces that.
Second, step changes. There are visible upward step changes in the lower latitude TLT anomaly data for the Northern Hemisphere. The causes of these steps were discussed in earlier posts:
Can El Nino Events Explain All of the Global Warming Since 1976? – Part 1
Can El Nino Events Explain All of the Global Warming Since 1976? – Part 2
The previous post in this series also reinforces these step changes:
El Ninos Create Step Changes in TLT of the Northern Hemisphere Mid Latitudes
Note 1: The Lower Troposphere Temperature (TLT) anomaly data identified as AHU MSU was accessed using the coordinate-based system available through the KNMI website. They cover the period of January 1979 to November 2008. The NINO3.4 SST data is ERSST.v2 data available through the NOAA NOMADS system. The SST anomaly data for the SST versus TLT comparative graphs (Figures 22, 23 and 24) is OI.v2 SST data, with a higher resolution that the ERSST.v2 data used for NINO3.4. The reason for the two SST datasets is the OI.v2 data does not cover the entire time period of the TLT data, while ERSST.v2 does. The Northern Hemisphere Sato Index data is available from GISS. All TLT data in the graphs (with the exception of Figure 1) have been smoothed with a 12-month running-average filter. The data is raw in Figure 1.
NOTE 2: NINO3.4 SST anomaly and Sato Index (mean optical thickness of stratospheric volcanic aerosols) data are provided to aid in the illustration of the timing of the ENSO and volcanic eruptions only. They have not been scaled for any other purpose. The NINO3.4 SST anomalies are adjusted by factor of 0.24. The Sato Index data has been inverted using a factor of -3. They also have not been smoothed.
NOTE 3: I’ve divided the low latitudes of the Northern Hemisphere into subsets as shown in Figure 2 to reflect the TLT anomalies over the oceans and continents. I used the same longitudes as the previous post in this series that covered the mid latitudes of the Northern Hemisphere.
COMPARISONS TO NINO3.4 AND SATO INDEX DATA
Figure 3 is a comparative graph of low latitude Northeast Pacific TLT anomaly and scaled NINO3.4 SST anomaly and Sato Index data. The first thing that stands out is how well the low latitude Northeast Pacific TLT anomalies and scaled NINO3.4 SST anomalies correlate. They should, since the majority of the Northern half of the NINO3.4 region is contained by the area of the low latitude Northeast Pacific TLT anomaly data. The second thing: There was little to no impact by the 1982 El Chichon eruption on the low latitude Northeast Pacific TLT anomalies, while the 1991 Mount Pinatubo eruption did flatten the response to the El Nino events then.
Note: In the earlier post on segmented mid latitude Northern Hemisphere TLT anomaly data, I commented on the dip in the TLT anomaly data from late 1983 to 1986. In fact, I highlighted a similarly timed dip in the Old World West dataset of that post and added a note, “Lagged Response To Volcano?” (Refer to Figure 21 of El Ninos Create Step Changes in TLT of the Northern Hemisphere Mid Latitudes) Returning to this post, since the low latitude Northeast Pacific TLT anomalies are affected little by the 1982 volcanic eruption, the dip in this dataset appears to be an over-reaction to the minor La Nina at the time. (Keep in mind the scaling of the NINO3.4 data.)
Figures 4 through 7 compare scaled NINO3.4 SST anomaly and Sato Index data to the following low latitude Northern Hemisphere TLT anomaly subsets:
-Old World West, and
-Old World East.
Note the varying responses to ENSO events and both volcanic eruptions. Lag times to the 1997/98 El Nino also increase as the datasets move east.
Low latitude Northwest Pacific TLT anomaly, scaled NINO3.4 SST anomaly and scaled (inverted) Sato Index data are compared in Figure 8. Note how little the Northwest Pacific TLT anomalies react to the 1997/98 El Nino compared with the other datasets. Note also that it rebounds to near the El Nino-caused peak in 2002 after dipping with the 1999/2000/2001 La Nina. That step change is better illustrated in the following section.
During the ~30 years of data, there were two significant El Nino events that were not suppressed by volcanic eruptions, the 1986/87/88 and 1997/98 El Ninos. The peaks of the TLT anomaly responses to those El Ninos occur near to January 1988 and January 1998, making those months a good place to separate the datasets. The processes that caused step changes in global SST in response to those El Nino events are discussed in the two posts titled Can El Nino Events Explain All of the Global Warming Since 1976? – Part 1 and Can El Nino Events Explain All of the Global Warming Since 1976? – Part 2.
With that in mind, I’ve calculated the average TLT anomalies for each of the low latitude Northern Hemisphere TLT datasets from:
-January 1979 to December 1987, from
-January 1988 to December 1997, and from
-January 1998 to November 2008, to illustrate the step changes, if there were any. Note that I left the temperature scaling in the following graphs constant for those who wanted to flip between datasets. (There’s a gif animation of the datasets with linear trends in Figure 21 for this purpose also.)
In Figure 9, the period averages have been added to the graph of low latitude Northwest Pacific TLT anomalies. Using those averages as reference, the 1997/98 El Nino shifted low latitude Northwest Pacific TLT anomalies, increasing them by approximately 0.23 deg C. The response of the low latitude Northwest Pacific TLT anomalies to the 1991 Mount Pinatubo eruption was greater than the El Chichon eruption in 1982. This lowered the average TLT during the period of January 1988 to December 1997, offsetting some of the increase caused by the 1986/87/88 El Nino.
An interesting graph, Figure 10 provides the same comparison for the low latitude Northeast Pacific TLT anomalies. There were little changes in the Northeast Pacific TLT anomalies. This is caused by the dominance of ENSO events on that data. (There is no trend to speak of in NINO3.4 SST anomaly data from January 1979 to November 2008. It is flat.) The suppression of the 1991/92 El Nino and minor El Nino in 1993 by Mount Pinatubo also contributed to the similarity of the averages.
Figures 11 through 14 illustrate period averages for the low latitude TLT anomalies for:
-Old World West
-Old World East.
Note that part of the rises in the low latitude Central American and North Atlantic TLT anomalies result from the Atlantic Multidecadal Oscillation (AMO). Also note how much larger the responses to the 1991 Mount Pinatubo eruption are for the two datasets that include the greatest land areas, the Old World West (Figure 13) and Old World East (Figure 14).
I’m not one for trend analysis, but there are those who are, so I’ve included the graphs that were the bases for the preceding period-average graphs, without the notations. At the end is a gif animation of the six low latitude Northern Hemisphere TLT anomaly subsets for comparison.
And the gif animation.
TLT VERSUS SST
The three oceanic TLT anomaly datasets in this post afford the opportunity to compare them directly to SST anomalies for the same areas. Note that the low latitude North Atlantic TLT anomaly data also includes small portions of Western Africa and Northern South America, so there will be minor land biases in that data. The low latitude Northwest and Northeast Pacific TLT data include no significant lass mass. These comparison graphs are being provided for reference only at this time. In a future post, I’ll discuss the very basic reason for the differences, which, on a global basis, is easiest explained as a difference in response of SST and the TLT over oceans to ENSO events.
As illustrated in this post and in the two previous posts in this series, El Nino events and volcanic eruptions dominate climate over the term of the satellite-based TLT data. In the next part of this series, I’ll examine the low latitude TLT anomalies for the Southern Hemisphere. Since the Indian Ocean plays a larger role in the Southern Hemisphere and the Southern Ocean has an influence, there may be differences.
Under the heading of TLT VERSUS SST, I noted that the difference between TLT over oceans and SST is a function of ENSO.
The TLT over the oceans is available from the AHU MSU website. Refer to the third column of data here:
Subtracting the Global OI.v2 SST Anomalies from the AHU MSU Global Ocean TLT for the period of November 1981 to November 2008 creates the temperature difference graph illustrated in Figure 25. There are, of course, volcanic eruption influences.
Examining TLT over the oceans and SST anomalies in any detail regionally would require knowledge of weather at the time, and that’s beyond my capability. And since the modeling of El Nino events with any accuracy is beyond the capabilities of GCMs, it would make regional prediction of climate difficult for those few GCMs that attempt to model ENSO. For those GCMs that don’t model ENSO well or at all, regional climate predictions should be impossible.
The AHU MSU Lower Troposphere Temperature data is available through the KNMI Climate Explorer website:
The Optimally Interpolated Sea Surface Temperature Data (OI.v2 SST) and Extended Reconstructed Sea Surface Temperature Data (ERSST.v2) are available through the NOAA National Operational Model Archive & Distribution System (NOMADS).
The Sato Index Data is available from GISS at: