Archive for the ‘Blog Article’ Category

UAH Global Temperature Update for June 2020: +0.43 deg. C

Thursday, July 2nd, 2020

The Version 6.0 global average lower tropospheric temperature (LT) anomaly for June, 2020 was +0.43 deg. C, down from the May, 2020 value of +0.54 deg. C.

The linear warming trend since January, 1979 is +0.14 C/decade (+0.12 C/decade over the global-averaged oceans, and +0.18 C/decade over global-averaged land).

Various regional LT departures from the 30-year (1981-2010) average for the last 18 months are:

 YEAR MO GLOBE NHEM. SHEM. TROPIC USA48 ARCTIC AUST 
2019 01 +0.38 +0.35 +0.41 +0.36 +0.53 -0.14 +1.15
2019 02 +0.37 +0.47 +0.28 +0.43 -0.02 +1.05 +0.05
2019 03 +0.34 +0.44 +0.25 +0.41 -0.55 +0.97 +0.58
2019 04 +0.44 +0.38 +0.51 +0.54 +0.49 +0.93 +0.91
2019 05 +0.32 +0.29 +0.35 +0.39 -0.61 +0.99 +0.38
2019 06 +0.47 +0.42 +0.52 +0.64 -0.64 +0.91 +0.35
2019 07 +0.38 +0.33 +0.44 +0.45 +0.11 +0.34 +0.87
2019 08 +0.39 +0.38 +0.39 +0.42 +0.17 +0.44 +0.23
2019 09 +0.61 +0.64 +0.59 +0.60 +1.14 +0.75 +0.57
2019 10 +0.46 +0.64 +0.27 +0.30 -0.03 +1.00 +0.49
2019 11 +0.55 +0.56 +0.54 +0.55 +0.21 +0.56 +0.38
2019 12 +0.56 +0.61 +0.50 +0.58 +0.92 +0.66 +0.94
2020 01 +0.56 +0.60 +0.53 +0.61 +0.73 +0.12 +0.66
2020 02 +0.76 +0.96 +0.55 +0.76 +0.38 +0.02 +0.30
2020 03 +0.48 +0.61 +0.34 +0.63 +1.09 -0.72 +0.16
2020 04 +0.38 +0.43 +0.34 +0.45 -0.59 +1.03 +0.97
2020 05 +0.54 +0.60 +0.49 +0.66 +0.17 +1.15 -0.15
2020 06 +0.43 +0.45 +0.41 +0.46 +0.38 +0.80 +1.20

The UAH LT global gridpoint anomaly image for June, 2020 should be available within the next week here.

The global and regional monthly anomalies for the various atmospheric layers we monitor should be available in the next few days at the following locations:

Lower Troposphere: http://vortex.nsstc.uah.edu/data/msu/v6.0/tlt/uahncdc_lt_6.0.txt
Mid-Troposphere: http://vortex.nsstc.uah.edu/data/msu/v6.0/tmt/uahncdc_mt_6.0.txt
Tropopause: http://vortex.nsstc.uah.edu/data/msu/v6.0/ttp/uahncdc_tp_6.0.txt
Lower Stratosphere: http://vortex.nsstc.uah.edu/data/msu/v6.0/tls/uahncdc_ls_6.0.txt

CMIP6 Climate Models Producing 50% More Surface Warming than Observations since 1979

Thursday, June 25th, 2020

Those who defend climate model predictions often produce plots of observed surface temperature compared to the models which show very good agreement. Setting aside the debate over the continuing adjustments to the surface temperature record which produce ever-increasing warming trends, let’s look at how the most recent (CMIP6) models are doing compared to the latest version of the observations (however good those are).

First, I’d like to explain how some authors get such good agreement between the models and observations. Here are the two “techniques” they use that most annoy me.

  1. They look at long periods of time, say the last 100+ years. This improves the apparent agreement because most of that period was before there was substantial forcing of the climate system by increasing CO2.
  2. They plot anomalies about a common reference period, but do not show trend lines. Or, if they show trends lines, they do not start them at the same point at the beginning of the record. When you do this, the discrepancy between models and observations is split in half, with the discrepancy in the latter half of the record having the opposite sign of the discrepancy in the early part of the record. They say, “See? The observed temperatures in the last few decades nearly match the models!”

In the following plot (which will be included in a report I am doing for the Global Warming Policy Foundation) I avoid both of those problems. During the period of strongest greenhouse gas forcing (since 1979), the latest CMIP6 models reveal 50% more net surface warming from 1979 up to April 2020 (+1.08 deg. C) than do the observations (+0.72 deg. C).

Note I have accounted for the trends being somewhat nonlinear, using a 2nd order polynomial fit to all three time series. Next, I have adjusted the CMIP time series vertically so that their polynomial fit lines are coaligned with the observations in 1979. I believe this is the most honest and meaningful way to intercompare the warming trends in different datasets.

As others have noted, it appears the CMIP6 models are producing even more warming than the CMIP5 models did… although the KNMI Climate Explorer website (from which all of the data was downloaded) has only 13 models archived so far.

COVID-19 Global Economic Downturn not Affecting CO2 Rise: May 2020 Update

Friday, June 5th, 2020

The Mauna Loa atmospheric CO2 concentration data continue to show no reduction in the rate of rise due to the recent global economic slowdown. This demonstrates how difficult it is to reduce global CO2 emissions without causing a major disruption to the global economy and exacerbation of poverty.

After removal of the strong seasonal cycle in Mauna Loa CO2 data, and a first order estimate of the CO2 influence of El Nino and La Nina activity (ENSO), the May 2020 update shows no indication of a reduction in the rate of rise in the last few months, when the reduction in economic activity should have shown up.

I had previously explained why the slowdown would likely not be large enough to affect measured atmospheric CO2 levels compared to natural variations in global sources and sinks of CO2. I calculated that the Energy Information Administration-estimated 11% reductions in CO2 emissions during 2020 would have to be four times larger to stop the rise of atmospheric CO2 over 2019 values (assuming no substantial natural variations in CO2 sources and sinks).

UAH Global Temperature Update for May 2020: +0.54 deg. C

Tuesday, June 2nd, 2020

The Version 6.0 global average lower tropospheric temperature (LT) anomaly for May, 2020 was +0.54 deg. C, up from the April, 2020 value of +0.38 deg. C.

The linear warming trend since January, 1979 is +0.14 C/decade (+0.12 C/decade over the global-averaged oceans, and +0.18 C/decade over global-averaged land).

Various regional LT departures from the 30-year (1981-2010) average for the last 17 months are:

 YEAR MO GLOBE NHEM. SHEM. TROPIC USA48 ARCTIC AUST 
2019 01 +0.38 +0.35 +0.41 +0.36 +0.53 -0.14 +1.15
2019 02 +0.37 +0.47 +0.28 +0.43 -0.02 +1.05 +0.05
2019 03 +0.34 +0.44 +0.25 +0.41 -0.55 +0.97 +0.59
2019 04 +0.44 +0.38 +0.51 +0.54 +0.49 +0.92 +0.91
2019 05 +0.32 +0.29 +0.35 +0.40 -0.61 +0.98 +0.38
2019 06 +0.47 +0.42 +0.52 +0.64 -0.64 +0.91 +0.35
2019 07 +0.38 +0.33 +0.44 +0.45 +0.10 +0.33 +0.87
2019 08 +0.39 +0.38 +0.39 +0.42 +0.17 +0.44 +0.24
2019 09 +0.61 +0.64 +0.59 +0.60 +1.14 +0.75 +0.57
2019 10 +0.46 +0.64 +0.28 +0.31 -0.03 +0.99 +0.50
2019 11 +0.55 +0.56 +0.54 +0.55 +0.21 +0.56 +0.38
2019 12 +0.56 +0.61 +0.50 +0.58 +0.92 +0.66 +0.94
2020 01 +0.56 +0.60 +0.53 +0.62 +0.73 +0.12 +0.66
2020 02 +0.76 +0.96 +0.55 +0.76 +0.38 +0.02 +0.30
2020 03 +0.48 +0.61 +0.34 +0.63 +1.09 -0.72 +0.17
2020 04 +0.38 +0.43 +0.34 +0.45 -0.59 +1.03 +0.97
2020 05 +0.54 +0.60 +0.49 +0.66 +0.17 +1.15 -0.15

The UAH LT global gridpoint anomaly image for May, 2020 should be available within the next week here.

The global and regional monthly anomalies for the various atmospheric layers we monitor should be available in the next few days at the following locations:

Lower Troposphere: http://vortex.nsstc.uah.edu/data/msu/v6.0/tlt/uahncdc_lt_6.0.txt
Mid-Troposphere: http://vortex.nsstc.uah.edu/data/msu/v6.0/tmt/uahncdc_mt_6.0.txt
Tropopause: http://vortex.nsstc.uah.edu/data/msu/v6.0/ttp/uahncdc_tp_6.0.txt
Lower Stratosphere: http://vortex.nsstc.uah.edu/data/msu/v6.0/tls/uahncdc_ls_6.0.txt

Record Cold Upper Mesospheric Temperatures Suggest Another Good Noctilucent Cloud Viewing Season

Sunday, May 31st, 2020

Noctilucent clouds (NLCs) are often visible in the extreme upper atmosphere (80-85 km altitude) well after sunset in the late spring and summer at high northern latitudes. They form from ice condensing on meteoric dust at extremely cold temperatures (below 150 Kelvin or -190 deg. F). The cold temperatures are due to adiabatic cooling from dynamic uplift combined with little ozone to absorb the sun’s ultraviolet radiation.

Noctilucent clouds on May 31, 2020 (Alan Tough, Scotland)

With current solar minimum conditions reducing solar heating by ultraviolet radiation, and slowly increasing CO2 in the atmosphere causing enhanced infrared cooling to outer space, record low temperature are occurring. This has extended the southernmost viewing opportunity for NLCs from the usual ~60 deg. N latitude to as low as 35N latitude last year, with NLC sightings near Los Angeles and Las Vegas in 2019.

This recent article by Dr. Tony Phillips suggested that 2020 is shaping up to be another good NLC viewing season. An earlier article by Tony included this nice plot of April-May temperatures at 80 N latitude from this year compared to previous years, showing the general cooling trend during the current solar minimum conditions.

Data plot courtesy of Dr. Lynn Harvey, U. of Colorado.

We downloaded some more recent Aura satellite Microwave Limb Sounder data, and plotted it as a function of latitude. Note how fast temperatures dropped in only 6 days… 1-2 deg. C per day depending upon latitude.

Upper mesospheric temperatures at 83 km altitude on two different days in May, 2020 as a function of latitude. Lines are 2nd order polynomial fits to the data, providing average temperatures as a function of latitude.

The 141 K average temperature on May 27 (Day 148) at 80N latitude appears to be a new record low if we compare it to the data in the previous plot by Dr. Harvey.

I will try to keep track of these temperatures as the NLC season progresses in the coming weeks. So far, NLC sightings have been mostly in northern Europe and the UK.

Why the Current Economic Slowdown Won’t Show Up in the Atmospheric CO2 Record

Friday, May 15th, 2020

Summary: Atmospheric levels of carbon dioxide (CO2) continue to increase with no sign of the global economic slowdown in response to the spread of COVID-19. This is because the estimated reductions in CO2 emissions (around -11% globally during 2020) is too small a reduction to be noticed against a background of large natural variability. The reduction in economic activity would have to be 4 times larger than 11% to halt the rise in atmospheric CO2.

Changes in the atmospheric reservoir of CO2 occur when there is an imbalance between surface sources and sinks of CO2. While the global land and ocean areas emit approximately 30 times as much CO2 into the atmosphere as humans produce from burning of fossil fuels, they also absorb about an equal amount of CO2. This is the global carbon cycle, driven mostly by biological activity.

There are variations in the natural carbon cycle, such as during El Nino (more CO2 accumulation in the atmosphere) and La Nina (more CO2 removed from the atmosphere). Greater wildfire activity releases more CO2, while major volcanic eruptions (paradoxically) lead to greater photosynthesis from more diffuse sunlight and extra removal of CO2 from the air. The most dramatic variations are seasonal, as the land-dominated Northern Hemisphere experiences an annual cycle of vegetation growth (CO2 removal) and decay (CO2 release).

The increase in atmospheric CO2 observed since the 1950s is most likely dominated by anthropogenic CO2 emissions, which are twice as large as that needed to explain the observed rise. As I have shown before, a simple CO2 budget model driven by (1) estimates of global yearly anthropogenic CO2 emissions, (2) El Nino and La Nina activity, and (3) a CO2 removal rate that is proportional to how much “extra” CO2 is in the atmosphere compared to a “preferred baseline” CO2 level, yields an excellent fit to yearly CO2 observations at Mauna Loa, Hawaii.

Fig. 1. Yearly Mauna Loa, HI CO2 observations since 1959 (red) versus a simple CO2 budget model (blue).

 

But those are yearly measurements, and we are now interested in whether the recent global economic slowdown is showing up in the monthly Mauna Loa CO2 data. If we remove the large seasonal variations (driven by the seasonal growth and decay of Northern Hemisphere vegetation), we see no evidence of the economic slowdown through April, 2020.

Fig. 2. Monthly CO2 data since 2015 from Mauna Loa, HI after the average seasonal cycle is statistically removed.

As can be seen in Fig. 2, there are some pretty large month-to-month jumps and dips around the long-term increase (represented by the dotted line). These are probably natural variations due to fluctuations in the average seasonal variations in vegetation growth and decay, wildfire activity, and El Nino and La Nina activity (which are imperfectly removed in the solid blue line in Fig. 2). Variations in economic activity might also be involved in these fluctuations.

The point is that given the large month-to-month variations in natural CO2 sources and sinks seen in Fig. 2, it would be difficult to see a downturn in the anthropogenic source of CO2 unless it was very large (say, over 50%) and prolonged (say over a year or longer).

Instead, the U.S. Energy Information Administration (EIA) estimates that the global economic slowdown this year due to the spread of the novel coronavirus will amount to only about an 11% reduction in global CO2 emissions. This is simply too small of a decrease in CO2 emissions to show up against a background of considerable monthly and yearly natural variability in the atmospheric CO2 budget.

That relatively small 11% reduction also illustrates how dependent humanity is on energy, since the economic disruption is leading to U.S. unemployment rates not seen since the Great Depression of the 1930s. Everything that humans do requires access to abundant and affordable energy, and even the current economic downturn is not enough to substantially reduce global CO2 emissions.

ADDENDUM: How much of a decrease in CO2 emissions would be required to stop the atmospheric rise in CO2?

An interesting aspect of the observed rise of atmospheric CO2 is that it indicates the greater the CO2 concentration, the faster the “extra” CO2 is removed by biological activity. The observed annual rate of removal is 2.3% of the excess above a baseline of 295 ppm. The greater the “excess”, the faster the rate of removal.

Because of this rapid rate of removal, the anthropogenic CO2 emissions do not have to go to zero to stop the observed rise in atmospheric CO2. Using my simple model (blue line in Fig. 1, above), I find that a 43% reduction in anthropogenic CO2 emissions in 2020 would — in the absence of natural fluctuations in the carbon cycle — lead to a halt in the observed rise of atmospheric CO2 in 2020 over 2019 levels. This is about 4 times larger than the EIA estimate of an 11% reduction in CO2 emissions for the year 2020.

UAH Global Temperature Update for April 2020: +0.38 deg. C

Friday, May 1st, 2020

UPDATE: Changed emphasis from Northern Hemisphere extratropics to entire Northern Hemisphere (h/t John Christy)

In April, 2020, the Northern Hemisphere experienced its 2nd largest 2-month drop in temperature in the 497-month satellite record.

The Version 6.0 global average lower tropospheric temperature (LT) anomaly for April, 2020 was +0.38 deg. C, down from the March, 2020 value of +0.48 deg. C.

The Northern Hemisphere temperature anomaly fell from +0.96 deg. C to 0.43 deg. C from February to April, a 0.53 deg. C drop which is the 2nd largest 2-month drop in the 497-month satellite record. The largest 2-month drop was -0.69 deg. C from December 1987 to February 1988.

The linear warming trend since January, 1979 has now increased to +0.14 C/decade (but remains statistically unchanged at +0.12 C/decade over the global-averaged oceans, and +0.18 C/decade over global-averaged land).

Various regional LT departures from the 30-year (1981-2010) average for the last 16 months are:

 YEAR MO GLOBE NHEM. SHEM. TROPIC USA48 ARCTIC AUST 
 2019 01 +0.38 +0.35 +0.41 +0.36 +0.53 -0.15 +1.15
 2019 02 +0.37 +0.47 +0.28 +0.43 -0.02 +1.04 +0.06
 2019 03 +0.35 +0.44 +0.25 +0.41 -0.55 +0.97 +0.59
 2019 04 +0.44 +0.38 +0.51 +0.54 +0.49 +0.92 +0.91
 2019 05 +0.32 +0.29 +0.35 +0.40 -0.61 +0.98 +0.39
 2019 06 +0.47 +0.42 +0.52 +0.64 -0.64 +0.91 +0.35
 2019 07 +0.38 +0.33 +0.44 +0.45 +0.10 +0.33 +0.87
 2019 08 +0.39 +0.38 +0.39 +0.42 +0.17 +0.44 +0.24
 2019 09 +0.62 +0.64 +0.59 +0.60 +1.14 +0.75 +0.57
 2019 10 +0.46 +0.64 +0.28 +0.31 -0.03 +0.99 +0.50
 2019 11 +0.55 +0.56 +0.54 +0.55 +0.21 +0.56 +0.38
 2019 12 +0.56 +0.61 +0.50 +0.58 +0.92 +0.66 +0.94
 2020 01 +0.57 +0.60 +0.53 +0.62 +0.73 +0.12 +0.66
 2020 02 +0.76 +0.96 +0.55 +0.76 +0.38 +0.02 +0.30
 2020 03 +0.48 +0.61 +0.34 +0.63 +1.09 -0.72 +0.17
 2020 04 +0.38 +0.43 +0.34 +0.45 -0.59 +1.03 +0.97

The UAH LT global gridpoint anomaly image for April, 2020 should be available within the next week here.

The global and regional monthly anomalies for the various atmospheric layers we monitor should be available in the next few days at the following locations:

Lower Troposphere: http://vortex.nsstc.uah.edu/data/msu/v6.0/tlt/uahncdc_lt_6.0.txt
Mid-Troposphere: http://vortex.nsstc.uah.edu/data/msu/v6.0/tmt/uahncdc_mt_6.0.txt
Tropopause: http://vortex.nsstc.uah.edu/data/msu/v6.0/ttp/uahncdc_tp_6.0.txt
Lower Stratosphere: http://vortex.nsstc.uah.edu/data/msu/v6.0/tls/uahncdc_ls_6.0.txt

March 2020 CO2 Levels at Mauna Loa Show No Obvious Effect from Global Economic Downturn

Tuesday, April 7th, 2020

The COVID-19 disease spread is causing a worldwide shutdown in economic activity as business close, airlines cancel flights, and people shelter in their homes. For example, there was a 28% decline in global commercial air traffic in March 2020 compared to March of last year.

Last month I described a simple method for removing the large seasonal cycle from the Mauna Loa CO2 data, and well as the average effects from El Nino and La Nina (the removal is noisy and imperfect), in an effort to capture the underlying trend in CO2 and so provide a baseline to compare future months’ measurements too.

What we are looking for is any evidence of a decline in the atmospheric CO2 content that would be strong enough to attribute to the economic downturn. As can be seen, the latest CO2 data show a slight downturn, but it’s not yet out of the ordinary compare to previous month-to-month downturns.

I personally doubt we will see a clear COVID-19 effect in the CO2 data in the coming months, but I would be glad to be proved wrong. As I mentioned last month, those who view the economic downturn as an opportunity to reduce atmospheric CO2 would have to wait many years — even decades — before we would see the impact of a large economic downturn on global temperatures, which would occur at great cost to humanity, especially the poor.

Correcting Recent U.S. Weekly Death Statistics for Incomplete Reporting

Monday, April 6th, 2020

I am seeing an increasing number of people on social media pointing to the weekly CDC death statistics which show a unusually low number of total deaths for this time of year, when one would expect the number to be increasing from COVID-19. But what most people don’t realize is that this is an artifact of the late arrival of death certificate data as gathered by the National Center for Health Statistics (NCHS).

This first came to my attention as a tweet by some researchers who were using the CDC weekly death data in a research paper pointing out the downturn in deaths in early 2020 and had to retract the paper because of the incomplete data problem. A disclaimer at the CDC website points out the incomplete nature of recent data. While they say that the new totals could be adjusted either upward or downward, it appears that the adjustments are almost always upward (i.e. recent data have a low bias in reported deaths).

As a first attempt to possibly correct for this under-reporting problem, I downloaded the data two weeks in a row (approximately March 30 and April 5, 2020) to examine how the recent data changes as new death certificate data are obtained. I realize this is only one week’s worth of changes, and each week would provide additional statistics. But the basic methodology could be applied with additional weeks of data added.

I first use the 4.5 years of reported weekly death data to compute an average seasonal cycle in deaths, with the slow upward trend included (red line in the following figure). Also shown are the total deaths reported on 2 successive weeks, showing the increase in reported deaths from late reports coming in.

Although it is not obvious in the above plot, there were new deaths reported as much as 1 year late. If we use the difference between the two successive weeks’ reports as an estimate of how many new reports will come in each week as a percentage of the average seasonal cycle, and sum them up for 52 weeks, we can get a rough estimate of what the totals will look like a year from now (the blue line in the following figure).

The blue line shows behavior quite close to that seen last year at this time. Keep in mind that Week 10 is only through early March, at which point there were only 30 COVID-19 deaths reported, which is too small a number to show up on these plots. I’m posting this as just a suggestion for those who want to analyze recent weekly death data and make some sense out of it.

It is also of interest how bad the 2017-18 flu season was compared to this season. I’m sure many medical people are aware of this, but I don’t recall it being a huge news story two years ago.

Australia Bushfire Smoke Now Warming the Lower Stratosphere? March 2020 Update

Wednesday, April 1st, 2020

Last month I noted how the global average lower stratospheric temperature had warmed considerably in recent months, especially in February, and tentatively attributed it to smoke from the Australian bushfires entering the lower stratosphere. You can read more there about my reasoning that the effect was unlikely to be due to the recent Taal volcanic eruption.

Here’s the March 2020 update, showing continued warming.

The effect cannot be as clearly seen in regional averages (e.g. tropics or Southern Hemisphere) because those regions routinely see large changes which are compensated for by changes of the opposite sign in other regions, due to strong adiabatic warming (sinking motion) or cooling (rising motion) in the statically stable stratosphere. Thus, global averages show the best signal of something new going on, even if that something new is only occurring in a specific region.