El Niño Comparison 1997-98 versus 2015-16

Note: updated graphs are included in the ENSO page accessible at the top of this page.

The current El Niño that started in 2015 appears to have peaked and to be slowly declining now as can be seen in Figure 1.

Multivariate ENSO Index comparison for 1997-98 versus 2015-16

Figure 1. Multivariate ENSO Index comparison for 1997-98 versus 2015-16.

This figure compares the Multivariate El Niño Southern Oscillation (ENSO) Index (MEI) provided by the US National Atmospheric and Ocean Administration (NOAA) for the current 2015-16 El Niño versus the 1997-98 El Niño.  Since the satellite global temperature estimates typically show the largest response to El Niño events, global estimates of the temperature of the lower troposphere (TLT) estimates from Remote Sensing Systems (RSS) and the University of Alabama at Huntsville (UAH) are presented in Figures 1 and 2.  Both figures compare the TLT estimates for the 1997-98 El Niño versus the 2015-16 El Niño so far.

RSS global TLT anomaly comparison for 1997-98 versus 2015-16

Figure 2. RSS global TLT anomaly comparison for 1997-98 versus 2015-16.

Satellite peak global TLT estimates for El Niño events often lag the peak MEI and that appears to be happening with the current El Niño event.  Both the RSS and UAH global TLT estimates through January 2016 are still rising.

UAH global TLT anomaly comparison for 1997-98 versus 2015-16

Figure 3. UAH global TLT anomaly comparison for 1997-98 versus 2015-16.

If the current El Niño follows a similar pattern to the 1997-98 El Niño, the global TLT estimates may not peak until somewhere in the February to April range.  The 1997-98 El Niño, as well as the 2010-11 El Niño were both followed by strong La Niña cooling events as can be seen in Figure 4 (click to enlarge).  Thus, it seems likely that the current El Niño will also be followed by a strong La Niña, although time will tell.

UAH global TLT anomalies vs Multivariate ENSO Index 1996 through 2016 so far

Figure 4. UAH global TLT anomalies vs Multivariate ENSO Index 1996 through 2016 so far.

Figures 5 shows the current Sea Surface Temperature  (SST) anomalies for today (February 7, 2016) which can be compared to the Figure 6 map of SST anomalies for the same date in 1998.  Both maps were provided by the University of Maine Climate Change Institute.  Click on these figures to enlarge.

Global SST anomalies for 2016 February 7

Figure 5. Global SST anomalies for 2016 February 7.

Global SST anomalies for 1998 February 7

Figure 6. Global SST anomalies for 1998 February 7.

These maps indicate that in 1998 the El Niño was more intense in the far eastern equatorial Pacific Ocean, as compared 2016 where the highest SST anomalies are farther west, in the central portions of the equatorial Pacific Ocean, and slightly weaker.  Interestingly, both years exhibit a cold SST anomaly pool in the North Central Pacific Ocean.

For monthly updates to key figures, see the ENSO page accessible from the menu bar at the top of this page.

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Global Satellite Temperature versus ENSO

With the current El Niño possibly peaking now it will be interesting to see when the satellite derived global temperature anomalies peak. If past history during the satellite era is any indication, the satellite indicated global lower tropospheric temperature anomaly could peak as much as 3 to 6 months after the El Niño Southern Oscillation (ENSO) peak. The latest monthly Multivariate ENSO Index (MEI) from the US National Oceanic and Atmospheric Administration (NOAA) indicates a slight downturn in the MEI for October compared to September, which could possibly indicate the peak was in September. However, we will have to wait another month or two to be more confident. If the peak was in September, this El Niño will rank as the third most intense of the satellite era based on the MEI, after the 1997-98 and 1982-83 events.

The University of Alabama at Huntsville (UAH) satellite derived monthly global temperature for the lower troposphere (TLT) anomaly estimates showed a sharp rise from September to October as shown with the MEI in Figure 1. Also shown are the Mauna Loa apparent sunlight transmission monthly averages to indicate significant volcanic effects on sunlight transmission through the atmosphere. Effects from reduced sunlight transmission are evident after the El Chichón and Pinatubo volcanic eruptions in April 1982 and June 1991 respectively, after which sharp drops can be seen in the TLT anomaly estimates. Most of the strongest El Niños have been followed by La Niñas with corresponding drops in TLT for as much as a year or two following.

Global Satellite Temperature versus ENSO

Figure 1. Comparison of monthly UAH satellite temperature for the lower troposphere (TLT) anomaly estimates, NOAA Mulitivariate ENSO Index, and NOAA Mauna Loa Apparent Transmission (MLAT) of sunlight (click to enlarge)

For the latest monthly ENSO updates, see the ENSO page accessible from the menu bar at the top of this post.

21st Century Global Temperature Trends

This analysis focuses on global temperature anomaly trends for our current 21st century so far, beginning in 2001, as we approach the first 15 years. The previous post covered trends over the entire satellite weather data era back to 1979.

As mentioned in my previous post, there are three main relatively independent sources of global surface temperature anomaly estimates available, derived from:  the Global Historical Climate Network (and sometimes including additional land stations) coupled with sea surface temperature measurements (GHCN), global weather forecast model input data, and satellite estimates of lower tropospheric temperatures.  There are multiple groups that compile and publish estimates from these sources, but for simplicity, estimates from four of these groups are presented here.  For the GHCN related estimates, this analysis uses the US National Center for Environmental Information (NCEI) estimates and the Berkeley Earth Surface Temperature (BEST) estimates.  These are compared to the satellite estimates from the University of Alabama Huntsville (UAH) and global forecast system (GFS) estimates provided by the University of Maine (UM) Climate Change Institute (CCI).

I compiled and graphed monthly global temperature anomaly estimates from each of these four groups for the period 2001 through September 2015 and calculated linear regression trends to indicate the overall change over this period. The UM CCI GFS estimates in Figure 1 show the lowest trend at -0.0014 degrees Celsius (C) per month over the period of nearly 15 years, which corresponds to -1.68C per century if maintained. The next lowest trend, shown in Figure 2, is +0.00005C per month from the UAH satellite estimates, which corresponds to +0.06C per century if maintained. The second highest trend is +0.0006C per month for the BEST GHCN estimates shown in Figure 3, which corresponds to +0.72C per century. The highest trend of 0.0009C per month is from the NCEI GHCN estimates shown in Figure 4 and corresponds to +1.08C per century if maintained.

Global temperature anomaly trend for 1979-2015 based on UM CCI GFS monthly estimates

Figure 1. Global temperature anomaly trend for 1979-2015 based on UM CCI GFS monthly estimates.

Global temperature anomaly trend for 1979-2015 based on UAH satellite monthly estimates

Figure 2. Global temperature anomaly trend for 1979-2015 based on UAH satellite monthly estimates.

Global temperature anomaly trend for 1979-2015 based on BEST GHCN monthly estimates

Figure 3. Global temperature anomaly trend for 1979-2015 based on BEST GHCN monthly estimates.

Global temperature anomaly trend for 1979-2015 based on NCEI GHCN monthly estimates

Figure 4. Global temperature anomaly trend for 1979-2015 based on NCEI GHCN monthly estimates.

The variation in these trends underscores the uncertainty in all of these approaches. I suspect that the satellite derived estimate of +0.06C per century is the best compromise among these estimates. I find it very interesting that the GFS derived estimate of -1.68C per century contrasts so greatly with the GHCN derived trends. This discrepancy provides further evidence that ongoing adjustments to the GHCN based estimates are pushing them farther away from reality. We have no way of knowing whether these trends will be maintained for a full century, but there is certainly no clear evidence of an upward trend so far this century despite continued rapid increases in carbon dioxide (CO2). The implication is that CO2 is not at all the driver for global temperature trends and does not warrant expensive efforts to control.

Satellite Era Global Temperature Trends

This analysis focuses on global temperature anomaly trends for the satellite era beginning in 1979. Prior to this time, data coverage over oceans was much more sparse and this problem is worse moving farther back in time. Since the oceans cover 71 percent of the earth’s surface, poor coverage over the oceans leads to great uncertainty in global temperature anomaly estimates and trends prior to the satellite era. Consequently, I have little confidence in any global temperature trend analyses that include estimates from before the satellite era.

As mentioned in my previous post, there are three main relatively independent sources of global surface temperature anomaly estimates available, derived from:  the Global Historical Climate Network (and sometimes including additional land stations) coupled with sea surface temperature measurements (GHCN), global weather forecast model input data, and satellite estimates of lower tropospheric temperatures.  There are multiple groups that compile and publish estimates from these sources but for simplicity, estimates from four of these groups are presented here.  For the GHCN related estimates, this analysis uses the US National Center for Environmental Information (NCEI) estimates and the Berkeley Earth Surface Temperature (BEST) estimates.  These are compared to the satellite estimates from the University of Alabama Huntsville (UAH) and global forecast system (GFS) estimates provided by the University of Maine (UM) Climate Change Institute (CCI).

I compiled and graphed monthly global temperature anomaly estimates from each of these four groups for the period 1979 through September 2015 and calculated linear regression trends to indicate the overall change over this period. The UAH satellite estimates in Figure 1 show the lowest trend at +0.0009 degrees Celsius (C) per month over the period of nearly 37 years, which corresponds to +1.08C per century if maintained. The next lowest trend, shown in Figure 2, is +0.0011C per month from the UM CCI GFS estimates, which corresponds to +1.32C per century if maintained. The second highest trend is +0.0013C per month for the NCEI GHCN estimates shown in Figure 3, which corresponds to +1.56C per century. The highest trend of +0.0014C per month is from the BEST GHCN estimates shown in Figure 4 and corresponds to +1.68C per century if maintained.

Global temperature anomaly trend

Figure 1. Global temperature anomaly trend for 1979-2015 based on UAH satellite monthly estimates.

Global temperature anomaly trend

Figure 2. Global temperature anomaly trend for 1979-2015 based on UM CCI GFS monthly estimates.

Global temperature anomaly trend

Figure 3. Global temperature anomaly trend for 1979-2015 based on NCEI GHCN monthly estimates.

Global temperature anomaly trend

Figure 4. Global temperature anomaly trend for 1979-2015 based on BEST GHCN monthly estimates.

My best guesstimate of uncertainty for global temperature anomaly estimates is at least plus or minus 0.3C to 0.5C and thus these trends appear to be significant, although with a fairly low confidence. I suspect that the satellite derived estimate of +1.08C per century is the most accurate of these estimates, followed by the GFS estimate of +1.32C per century, neither of which is especially alarming considering evidence of much larger century scale changes in temperatures in the past during our current Holocene epoch as previously described in this blog. Also, we have no way of knowing whether these trends will be maintained for a full century and so far for the first 15 years of the 21st century, there is evidence that the upward trend could be ending or at least slowing. My next post will take a closer look at global temperature trends for the 21st century so far.

Satellite Era Global Temperature Anomaly Comparisons

It is interesting and instructive to compare different independent estimates of global temperature anomalies.  The largest amount of data available for input to global temperature estimates has occurred with the advent of satellite weather surveillance and global weather forecast models in the late 1970’s.  Prior to that time, data coverage was much more limited, especially over the oceans that make up about 71% of the earth’s surface.  Therefore the older estimates are likely to be less accurate and thus more uncertain.  Consequently, this comparison will focus on the period from 1979 to present where we have more data.

There are three main relatively independent sources of global surface temperature anomaly estimates available, derived from:  the Global Historical Climate Network (and sometimes including additional land stations) coupled with sea surface temperature measurements (GHCN), global weather forecast model input data, and satellite estimates of lower tropospheric temperatures.  There are multiple groups that compile and publish estimates from these sources but for simplicity, estimates from four of these groups are presented here.  For the GHCN related estimates, this analysis uses the US National Center for Environmental Information (NCEI) estimates and the Berkeley Earth Surface Temperature (BEST) estimates.  These are compared to the satellite estimates from the University of Alabama Huntsville (UAH) and global forecast system (GFS) estimates provided by the University of Maine (UM) Climate Change Institute (CCI).

Monthly global temperature anomaly estimates from all four groups representing three independent sources are presented in Figure 1 for the period 1979 through September 2015 and normalized to the 30-year climatic reference period 1981 through 2010.  The most widely publicized of these estimates are from NCEI and are highlighted in bold red.  In general, there is a fairly close agreement, typically within plus or minus 0.2 degrees Celsius (C) for most months.  The general trend over the entire 37 year period is upward by about 0.4C.  The variability between these estimates hints at the uncertainty but does not fully characterize it.  My best guess is that the uncertainty of estimates during this period is at least plus or minus 0.3C to 0.5C, as described in more detail here:
Uncertainty in Global Temperature Assessments

Considering the size of the uncertainty compared to the size of the trend, my opinion is that we can only say with low confidence that there may be a small rise in the global temperature during this period.

Global monthly temperature anomaly estimate comparisons for 1979-2015

Figure 1. Global monthly temperature anomaly estimate comparisons for 1979-2015

To allow more direct comparisons, Figures 2 through 5 present estimates for two groups at a time.  The GHCN related estimates from BEST and NCEI are compared in Figure 2.  As might be expected, these estimates show a striking similarity, although there is a hint of slightly larger monthly variations in the BEST estimates.  They both show a very similar trend.

Global Temperature Anomaly Estimates 1979-2015 BEST NCEI

Figure 2. Global temperature anomaly estimates 1979-2015 for GHCN BEST and GHCN NCEI

Figure 3 compares the GFS UM CCI estimates with the GHCN NCEI estimates.  For most of the period the two estimates are close, with the exception of two periods where the GFS UM CCI estimates are consistently slightly higher for 1980-1981 and 2002-2007 and for the most recent period since about 2010 where the GHCN NCEI estimates have suddenly departed substantially higher than the GFS UM CCI estimates by a fairly constant offset near 0.2C.  I am not aware of any major changes in the methodology or data inputs for the GFS UM CCI, but the GHCN NCEI estimates are constantly being revised and adjusted.  It appears that recent adjustments may have introduced a substantial high bias since 2010, especially considering that the GFS UM CCI and UAH satellite estimates show a fairly good match during this period.

Global Temperature Anomaly Estimates 1979-2015 for GFS UM CCI and GHCN NCEI

Figure 3. Global temperature anomaly estimates 1979-2015 for GFS UM CCI and GHCN NCEI

The UAH satellite estimates show the same general trend as the GHCN NCEI estimates, but a larger monthly variability as shown in Figure 4.  Considering that the UAH satellite estimates are for the lower troposphere whereas the GHCN NCEI estimates are for the surface, this comparison is easily within the previously mentioned uncertainty range.  This comparison also shows a hint of a possible high bias in the GHCN NCEI estimates since 2010.

Global Temperature Anomaly Estimates 1979-2015 for Satellite UAH and GHCN NCEI

Figure 4. Global temperature anomaly estimates 1979-2015 for Satellite UAH and GHCN NCEI

The UAH satellite estimates seem to subjectively show a slightly better comparison to the GFS UM CCI estimates as seen in Figure 5 than compared with the GHCN NCEI estimates in Figure 4.  The main deviations seem to be associated with El Niño and La Niña events.  The UAH satellite estimates are much higher during the very strong 1998 El Niño and slightly higher during weaker El Niños in 1983, 1987, 1991, and 2010 and somewhat lower during the 2007-2008 La Niña period.  The UAH satellite and GFS UM CCI estimates show a good agreement since 2010, unlike the suspect GHCN NCEI estimates.

Global Temperature Anomaly Estimates 1979-2015 for GFS UM CCI and Satellite UAH

Figure 5. Global temperature anomaly estimates 1979-2015 for GFS UM CCI and Satellite UAH

These comparisons give me less confidence in the GHCN NCEI estimates, especially since 2010.  My feeling is that the GFS UM CCI estimates, which are based on data with much better spatial coverage than the GHCN related estimates, probably provide the most accurate surface temperature anomaly estimates for this period.  In my next post, I will compare the trends in these estimates across the full 37 year period and then in a following post trends for the current century so far 2001-2015.

Monthly global temperature anomaly sources:

NCEI
http://www.ncdc.noaa.gov/cag/time-series/global/globe/land_ocean/p12/12/1880-2015.csv

BEST
http://berkeleyearth.lbl.gov/auto/Global/Land_and_Ocean_complete.txt

UAH
http://vortex.nsstc.uah.edu/data/msu/v6.0beta/tlt/tltglhmam_6.0beta3.txt

UM CCI
http://cci-reanalyzer.org/Reanalysis_monthly/output/tseries_1_0_0_12_0.csv

No Real Global Warming for 20 Years Now

A paper published in Nature magazine in 2014 (see link below) looked at recent trends in global temperature in the lower troposphere (TLT) from satellite observations and attempted to remove the effects from major volcanic activity and from the El Nino Southern Oscillation (ENSO). The result indicates no global warming for over 20 years now, despite the continued rapid increase in carbon dioxide concentrations. Yet one more study that greatly calls into question the “settled science” of man-made global warming. More evidence that the effects of man-made carbon dioxide on global temperature are quite small and perhaps not even significant.  See the graphs below.

Global Temp no ENSO-volcanic

Most people don’t realize that carbon dioxide is NOT a pollutant and is absolutely critical for plant survival. Higher carbon dioxide levels actually promote more rapid plant growth and therefore have a major beneficial effect for crops as well as natural plant growth. From 3 million years ago back to more than 200 million years ago, Earth had no glaciers, global temperatures were much warmer, and carbon dioxide levels were much higher than today. Then about about 3 million years ago at the start of the Pleistocene period for reasons unknown global temperatures gradually cooled and Earth entered an ice age that continues today.

We are lucky to live in one of the relatively short interglacial warm periods between the much longer intense glacial periods. During the last 500,000 years there have been five intensely cold glacial periods each lasting about 80,000 to 100,000 years and separated by interglacial warm periods with much less ice but each lasting only about 10,000 to 15,000 years on average. Our present interglacial period is called the Holocene and started about 11,700 years ago and based on past history will likely end sometime within the next few thousand years or less. The next glacial period will be a major challenge for humanity, with ice covering most of Canada, the northern US, and northern Europe. With colder global temperatures come drier air and expanding deserts as well as much lower carbon dioxide levels that will inhibit plant growth. We should count our blessings today and explore the deep meaning of true climate change over the ages to prepare for what will come.

Thanks to Paul Homewood for the tip:
No Underlying Global Temperature Increase For 20 Years

Original 2014 paper by Benjamin Santer, et al,  in Nature:
Volcanic contribution to decadal changes in tropospheric temperature

More on Earth’s climate changes in the last 3 million years:
Three Million Years of Climate Change

Comparison of NCEP CFSR versus NCDC Global Temperature Anomalies

The US National Center for Environmental Prediction (NCEP) has produced a Climate Forecast System Reanalysis (CFSR) based on “all available conventional and satellite observations”.  Most of these data were used to initialize real-time global weather forecast model runs four times each day since 1979.  This reanalysis can also be used to estimate annual global temperatures and temperature anomalies.  The University of Maine Climate Change Institute has compiled the CFSR data and provided an easy-to-use interface for viewing some of the data using maps and graphs with their Climate Reanalyzer web site.

I pulled CFSR annual global temperature anomaly data from the Climate Reanalyzer for 1979 through 2013 and added a compatible estimate for 2014 from the Weather Bell model temperature web page to complete the period 1979-2014.  I then graphed this data against the US National Climatic Data Center (NCDC) estimates based on the Global Historical Climate Network (GHCN) for the same period, as shown in Figure 1 below.  Both data sets have been normalized to the 1981-2010 period for comparison.

Figure 1. Comparison of NCEP CFSR versus NCDC estimates of annual global temperature anomalies from 1979 through 2014.

Figure 1. Comparison of NCEP CFSR versus NCDC estimates of annual global temperature anomalies from 1979 through 2014.

In general, the two approaches show a similar result, but there are some interesting differences.  These differences help to indicate some of the uncertainty in trying to estimate a global temperature anomaly as discussed in my previous post.  Of particular interest is the result for the most recent portion from 2001 through 2014.  The “pause” in the NCDC estimates is actually more of a peak and decline in the CFSR estimates.  The warmest years in the CFSR estimates are 2002-2003 and 2005-2007 with a peak in 2005.  In contrast, the warmest year estimated by NCDC is 2014.  In the CFSR data, 2014 ranks 12th for the 36-year period – far from being the “hottest year ever” as promoted by some.

Considering that the NCEP CFSR approach incorporates a much larger data set with much better spatial coverage for estimating global temperatures than the NCDC GHCN approach, I suspect the CFSR annual estimates are more accurate.