Cooling Down the Hysteria About Global Warming

Reblogged from Watts Up With That:

Guest essay by Rich Enthoven

Recently, NASA released its annual report on global temperatures and reported that 2018 was the fourth hottest year on record, surpassed only by three recent years. This claim was accompanied by dire predictions of climate change and for immediate action to dramatically curtail CO2 emissions around the globe. Like every concerned citizen read this report with interest. I also read it as an informed and trained climate analyst – and I can tell that there are some serious problems with the report and its conclusions.

For starters, I can assure my readers that I am not a climate change “denier.” No one doubts the climate changed when it experienced the Ice Age that ended 12,000 years ago. I have read enough scientific literature to believe the well documented view that the planet experienced the Medieval Warm Period (950 – 1250 AD) and Little Ice Age (1550 – 1850 AD) when global temperatures changed materially. I have also read enough scientific literature to understand that solar and ocean cycles affect global climate.

NASA is now reporting significant changes to the global temperature. According to NASA (and others) the entire globe experienced a persistent warming trend in the early part of the 20th century (1911 – 1940). Then, this trend reversed, and the globe cooled until the 1970’s.[1] Now, NASA is reporting that the global temperature increased .31° C in the last 10 years and that this trend is different than the .31° C increase NASA reports for the 1930’s[2]. But, a closer look at the data and methods used by NASA should make any reader skeptical of their results.

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Land Temperatures

It turns out, that over long periods of time it is actually quite difficult to measure temperature changes from climate consistently. The problems arise from changes in measurement technology (mercury bulbs then, semiconductors now) and changes in the sites surrounding the measurement locations. A good way to think about this problem is to consider Dallas Love Field Airport where average temperatures have been reported monthly since 1940. During that time Love Field transformed from a tiny airport near a small city[3] – to large urban airport with 200 daily flights. These changes have generated massive heat at the airport. It is no wonder that the reported temperatures at Love Field have trended up by approximately 2.9 ° F since 1940. [4]

image

But, when we look at the temperatures in Centerville, TX – much less affected by land use changes – we see the opposite trend. The average reported temperature in Centerville has been on a declining trend and now averages (on trend) .3 °F less than it was in 1940.[5]

As a result of this urban heat effect, scientists around the world have been identifying (or constructing) ‘pristine’ weather monitoring stations to get a clearer look at temperature changes. These stations are located in areas where urban development has not occurred and is not expected. These locations do not show any meaningful change in reported land temperatures. The best data comes from the National Oceanic and Atmospheric Administration (NOAA) which set up 114 rural temperature monitoring stations in the US in 2002 (USCRN). When we look at these, we see no persistent increase in US temperatures.[6] In fact, 2018 was .3°F colder than the first two years measured. February and March 2019 combined to be the coldest two-month period (temperature anomaly) ever recorded by the USCRN.

MONTHLY TEMPERATURE CHANGES AT USCRN STATIONS

image

And it is not just the US rural temperatures that are stable – all around the globe, temperature growth is eliminated once land use changes are eliminated. Shown below are temperature graphs from rural areas in Netherlands, Ireland, Chile, Antarctica, Japan[7], and China[8].

image

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Further calling into question the global land temperature data used by NASA are climate scientists themselves. Seventeen leading climate scientists (including scientists at NOAA) recently co-authored a paper calling for a new network of global weather stations in which they lamented the “imperfect measurements and ubiquitous changes in measurement networks and techniques.”[9]

Even these efforts to measure temperature change may not be enough – even the ‘pristine’ USCRN temperature measurement locations continue to biased towards warmer temperatures from land use changes. For example, a parking area and road was built next to the USCRN weather station[10] at the University of Rhode Island leading to a .34 ° C increase in measured temperatures at that location.[11][12]

image

Ocean and Satellite Temperature Measurement

The NASA global temperature estimate also relies heavily on estimates of temperatures in the ocean and air above it. Ocean temperatures have been measured over the years with highly inconsistent methods (buckets off ships; water flowing through ship engine rooms; buoys; and lately, satellites). In addition to technology changes, there are short term annual ocean cycles such as the well-publicized El Nino/La Nina and long term (multi decade) cycles such as the Pacific (and Atlantic) Decadal Oscillations which affect ocean temperatures at many depths over decades. A recent report out of UC San Diego described the problem “Determining changes in the average temperature of the entire world’s ocean has proven to be a nearly impossible task due to the distribution of different water masses.”[13]

Respected climate scientists are tackling the ocean measurement challenge and come up with results very different than the NASA report. Satellite measurements from University of Alabama show atmosphere temperatures over the ocean increasing since 1980 (end of the last cooling period per NASA) but only at .13 ° C per decade.[14] Both major satellite measurement groups report temperatures are lower now than they were in 1998, although by different amounts.[15] Harvard University oceanographer Carl Wunsch estimated the average temperature of the ocean grew by .02 degrees during 1994 – 2013.[16] Scripps Institute of Oceanography recently estimated the ocean temperature growth at .1 ° C total over the last 50 years. The science and history of measuring ocean temperatures is far from ‘settled’ and there are plenty of credible estimates that ocean temperatures are not changing rapidly or at anywhere near the rate that NASA is estimating.

Back to the NASA Temperature Estimate

To come up with their global temperature assessments, NASA faces all these problems and more. For starters, there is very little reliable global scale land data before 1940, and there are still shortages of reliable data in many parts of the world. (Africa, Middle East). Most of the historical data has been affected by land use changes and measurement technology changes. As they have tried to deal with these problems, NASA has dramatically changed the locations and methods that they use to assess temperatures over the last several decades.[17] Some observers question whether the new locations and technologies have the same pattern as the old ones would have had.

Not only have they adjusted the locations they take land measurements from, NASA adjusts the data that goes into their estimates[18]. Here are examples from the NASA website for Darwin Airport, Australia and Reykjavik, Iceland that show the liberal data changes adopted by NASA.[19]

image

image

Readers should note several problematic elements of these graphs:

1) The unadjusted data does not indicate warming at these locations over the last 80 years.

2) The unadjusted data is shown in such a faint outline that its hard to see. Why would NASA present it this way?

3) As NASA changed each data set, they made the past appear cooler – the “adjusted, cleaned” data is cooler than the “unadjusted” data – and the “homogenized” data is cooler still. A cooler past allows NASA to claim current temperatures are dramatically higher.

The NASA has “adjusted, cleaned, and homogenized” the data from these locations along with thousands of others to make up the data set that NASA uses. They then add data from satellites and use data grid methodology to come up with a final temperature change result.

Needless to say, the NASA changes have been the subject of considerable debate – within the climate scientist community, the climate “skeptic” community, and even NASA itself.[20] The “unadjusted” raw data has been adjusted meaningfully over the years as NASA recalculates.[21] The satellite measurements are very controversial according Zeke Hausfather, climate researcher at Berkley Earth – “If you don’t like adjustments, you really shouldn’t use the satellite record.”[22] A major problem is that the average adjustments between raw and final data average strongly in one direction – the adjustments tend to cool the past – which makes the present temperatures seem warmer by comparison.[23] NASA itself is apparently unhappy with their current formulas and plans to release version four of their “adjustments” soon.[24]

Other Indicators of Global Temperatures

The debate about the temperatures adjustments and estimates used by NASA can quickly get in to mathematical manipulations that are well beyond the level of this article. Scientists are arguing about changes in the global temperature that are on the order of one percent of one degree centigrade. Fortunately, we can look at a variety of other climate indicators in an effort to verify whether temperatures are changing. According to the theory endorsed by NASA, humans have been increasing carbon dioxide (CO2) in the atmosphere for more than 70 years[25] – and this increased CO2 has led to demonstrably higher global temperatures which affect major aspects of global climate.

Fortunately for the planet, there is no evidence of change in large scale climate indicators that should be changing with the temperature. Here are some notable examples:

· US Land Temperatures: In 1986, James Hansen testified to congress that rising CO2 levels would cause US temperatures to rise by three to four degrees by 2020. [26] This prediction was spectacularly wrong – US land temperatures have moved at most a fraction of that amount since 1986.[27]

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· Sea Level Rise: NASA (and later Al Gore) have made it clear that a warmer planet would cause ice to melt and the seas to expand – rising by up to four feet in 2050[28]. An accelerating trend in sea levels would potentially inundate lower elevation cities. But, NOAA data makes it clear that there is no change in the rate of sea level increase since measurements began.[29] If the warming globe would accelerate sea level changes, and we don’t see acceleration – it seems reasonable to suggest the globe isn’t warming.

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· Hurricanes and Other Adverse Weather Events: By the early 2000s climate scientists told us to expect an increase in hurricanes due to higher temperatures in the ocean. Instead, the US experienced a major hurricane drought from 2006 – 2016.[30] In fact, global hurricanes/typhoon activity have shown no up trend in frequency or severity for the last fifty years.[31] The IPCC also reported in 2013 that there was no change in frequency of other adverse events such as droughts, floods, and tornados.

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· Glaciers: Observers often become concerned as they see glaciers melting and blame it on global warming. It is certainly true that on average glaciers in the northern hemisphere have been retreating lately. But, glaciers have been retreating since the end of the Little Ice Age (1850) and numerous studies point out that many glaciers were actually melting faster during early 1900’s than they are today.[32] Glacier Bay in Alaska is a good example of the long term melting trend.

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· Snowfall: In 2001, the scientists at IPCC (worlds global authority on climate change) said that rising global temperatures would result in a reduction in snowfall and even the end of skiing industry.[33] However, according to both NOAA and Rutgers University, snowfall has been trending up across the northern hemisphere since 1970. If less snow is expected from higher temperatures – is more snow an indicator of lower temperatures?[34]

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These are large scale indicators that should not be subject to much measurement debate. They are not subject to “adjustments.” They all tell me that the NASA report is hopelessly biased in favor of reporting a temperature increase that is not happening.

Motivation for NASA to Report Higher Temperatures

Why would NASA come up with results so different from those of other climate observations? Consider the history of the NASA global temperature estimates. In 1986, James Hansen broadly publicized his global warming theory in testimony before the US Senate. For the next 27 years, Mr. Hansen was the chief scientist at NASA in charge of preparing and presenting those estimates. Is it unreasonable to suggest that the “adjustments” and formulas he used after his Senate testimony were biased with an effort to make his predictions turn out to be correct? How much of the NASA estimate is a simple self-fulfilling prophesy?

It’s not just NASA that is subject to significant pressure which likely introduces bias into their results. Climate scientists may be in the same position as those in other fields (i.e. nutrition, pharmaceuticals, psychology) where the desire to produce a pre-selected result influences the inputs, methods, and findings of their science. Alarming results (“hottest ever!” “disaster predicted” “urgent action needed”) all generate headlines; speaking engagements; trips to climate conferences (IPCC); and additional funding for more research. When scientists find opposite results (“nothing is really changing” “it’s just weather” “random events as usual”) they get no publicity; no funding; and instead are attacked (“pro big oil” “anti-environment” or worst of all, a “climate change denier.”)[35] There are indeed thousands of scientific papers that are at odds with NASA, but they don’t get nearly the media coverage and they are not included in NASA’s estimates.

Summary

It is time for a much more open and fair reporting and debate about global temperatures and climate change. Every time an adverse weather event occurs, we have news media blaming it on climate change that isn’t happening. We now have people marching in the streets over a non-existent crisis. All around the globe, trillions of dollars are being spent to avert a perceived global temperature crisis that is not happening. These energies and funds could be spent on far better uses to protect our environment, educate our people, and actually help the planet. We could be spending money on keeping toxins out of our ecosystems; keeping our oceans clean and healthy; improving sustainable farming techniques; expanding and protecting our natural habitats. Its time to take real action to protect and improve our planet – and stop the misplaced worry about climate change.


[1].https://climate.nasa.gov/vital-signs/global-temperature/

[2] Temp anomalies per NASA site: 2018 +.82 ° C less 2008 +.51 ° C =+.31 ° C. 1939 -.03 ° C – 1929 -.34 ° C =+.31 ° C

[3] Dallas population 400,000. Love Field had three daily flights. Wikipedia

[4] Data per iweathernet.com. Authors trend analysis – least squares regression.

[5] Iweathernet.com Authors trend analysis – least squares regression.

[6] https://www.ncdc.noaa.gov/temp-and-precip/national-temperature-index/time-series?datasets%5B%5D=uscrn&parameter=anom-tavg&time_scale=p12&begyear=2004&endyear=2019&month=3 See also https://agupubs.onlinelibrary.wiley.com/doi/10.1002/2015GL067640 for discussion of this data series. Trend is not significant at any reasonable level of certainty. Measurements themselves are subject to +/-.3°C at source.

[7] Temperatures from Japanese Meteorological Association.

[8] https://www.sciencedirect.com/science/article/pii/S0048969718331978

[9] Journal of Climatology 3/1/18 – https://rmets.onlinelibrary.wiley.com/doi/10.1002/joc.5458

[10] Data available at: https://www1.ncdc.noaa.gov/pub/data/uscrn/products/monthly01/CRNM0102-RI_Kingston_1_W.txt

[11] https://iowaclimate.org/2018/04/09/infrastructure

[12] Moose, Wy in Grand Teton National Park is experiencing record park visitors. Are they affecting measured temperatures at the USCRN site there?

[13] https://www.sciencedaily.com/releases/2018/01/180103160129.htm)

[14] https://www.nsstc.uah.edu/climate/2019/february2019/tlt_201902_bar.png Note this is closer to one third of the NASA estimated increase.

[15] http://www.drroyspencer.com/2014/10/why-2014-wont-be-the-warmest-year-on-record/

[16] https://www.tandfonline.com/doi/full/10.1080/16000870.2018.1471911)

[17] https://data.giss.nasa.gov/gistemp/history/

[18] https://data.giss.nasa.gov/gistemp/history/

[19] https://data.giss.nasa.gov/cgi-bin/gistemp/stdata_show.cgi?id=501941200000&dt=1&ds=5

[20] Sample paper on the debate from Journal of Geophysical Research – “There remain important inconsistencies between surface and satellite records.” https://pielkeclimatesci.files.wordpress.com/2009/11/r-345.pdf

[21] https://realclimatescience.com/2019/03/nasa-tampering-with-reykjavik-raw-temperature-data/

[22] https://www.carbonbrief.org/explainer-how-surface-and-satellite-temperature-records-compare

[23] https://data.giss.nasa.gov/gistemp/history/

[24] https://data.giss.nasa.gov/gistemp/

[25] CO2 has risen from 315 ppm to 380 ppm per Mauna Loa Observation 1960 – 2018.

[26] https://reason.com/archives/2016/06/17/climate-change-prediction-fail/print).

[27] https://www.ncdc.noaa.gov/temp-and-precip/national-temperature-index/time-series?datasets%5B%5D=uscrn&parameter=anom-tavg&time_scale=p12&begyear=2004&endyear=2019&month=2.

[28] https://www.nytimes.com/1988/06/24/us/global-warming-has-begun-expert-tells-senate.html?/pagewanted=all

[29] NOAA Tides & Currents – https://tidesandcurrents.noaa.gov/sltrends/sltrends_station.shtml?id=9414750

[30] US Hurricanes: https://journals.ametsoc.org/doi/pdf/10.1175/BAMS-D-17-0184.1

[31]Global Cyclone activity: https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2011GL047711

[32] http://appinsys.com/globalwarming/gw_4ce_glaciers.htm

https://www.the-cryosphere-discuss.net/tc-2018-22/tc-2018-22.pdf https://www.researchgate.net/publication/312185500_High_sensitivity_of_North_Iceland_Trollaskagi_debris-free_glaciers_to_climatic_change_from_the_%27Little_Ice_Age%27_to_the_present

[33] https://www.theguardian.com/environment/2001/jan/23/globalwarming.climatechange)

[34] In 2019, Mother Nature is making this point emphatically with at or near record snowfall and cold temperatures across North America and Europe.

[35] Prof. Ross McKitrick http://www.rossmckitrick.com/uploads/4/8/0/8/4808045/gatekeeping_chapter.pdf and Judith Curry are well known commentators on this phenomenon.

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Climate Modellers Waiting for Observations to Catch Up with Their Predictions

Reblogged from Watts Up With That:

Guest essay by Eric Worrall

h/t Dr. Willie Soon; In climate science, when your model predictions are wrong, you wait for the world to correct itself.

New climate models predict a warming surge
By Paul VoosenApr. 16, 2019 , 3:55 PM

For nearly 40 years, the massive computer models used to simulate global climate have delivered a fairly consistent picture of how fast human carbon emissions might warm the world. But a host of global climate models developed for the United Nations’s next major assessment of global warming, due in 2021, are now showing a puzzling but undeniable trend. They are running hotter than they have in the past. Soon the world could be, too.

In earlier models, doubling atmospheric carbon dioxide (CO2) over preindustrial levels led models to predict somewhere between 2°C and 4.5°C of warming once the planet came into balance. But in at least eight of the next-generation models, produced by leading centers in the United States, the United Kingdom, Canada, and France, that “equilibrium climate sensitivity” has come in at 5°C or warmer. Modelers are struggling to identify which of their refinements explain this heightened sensitivity before the next assessment from the United Nations’s Intergovernmental Panel on Climate Change (IPCC). But the trend “is definitely real. There’s no question,” says Reto Knutti, a climate scientist at ETH Zurich in Switzerland. “Is that realistic or not? At this point, we don’t know.”

Many scientists are skeptical, pointing out that past climate changes recorded in ice cores and elsewhere don’t support the high climate sensitivity —nor does the pace of modern warming. The results so far are “not sufficient to convince me,” says Kate Marvel, a climate scientist at NASA’s Goddard Institute for Space Studies in New York City. In the effort to account for atmospheric components that are too small to directly simulate, like clouds, the new models could easily have strayed from reality, she says. “That’s always going to be a bumpy road.”

In assessing how fast climate may change, the next IPCC report probably won’t lean as heavily on models as past reports did, says Thorsten Mauritsen, a climate scientist at Stockholm University and an IPCC author. It will look to other evidence as well, in particular a large study in preparation that will use ancient climates and observations of recent climate change to constrain sensitivity. IPCC is also not likely to give projections from all the models equal weight, Fyfe adds, instead weighing results by each model’s credibility.

Read more: https://www.sciencemag.org/news/2019/04/new-climate-models-predict-warming-surge

It’s nice to learn that the IPCC is considering using observations to constrain model projections.

GHCN v3.3 vs v4 Anomaly North America

Reblogged from Musings from the Chiefio:

GHCN v3.3 vs v4 Anomaly North America

In prior postings I did a sample of various countries around the world, and a full set of South America and Antarctica. This extends that set with North America.

I’m goiing to group things into North Continental (USA, Canada, Greenland), Central (Mexico and Central American countries) and Carib, those islands in the Caribbean Sea. Why? Because countries in those areas ought to look a lot more like each other in terms of Anomaly than like those in other groups. The Caribbean is dominated by water and tropical conditions. Central America and Mexico are about the same but with a bit less water influence. The USA, Canada and to some extent Greenland are large land masses prone to cold winters and significantly further north (so more summer / winter sun changes). This also lets me group making the graphs into smaller work units and it is less oppressive 😉

Here’s the Koppen Climate graph for North America so you have something for comparison.

Koppen Climate Zones for North America

From that I think you can see why I’d put Cuba into the Caribbean rather than count it in South America… like GHCN did…

The Graphs

Northern Big 3 (Canada, USA, Greenland)

Greenland

GHCN v3.3 vs v4 Greenland Difference

So about 1 C range of changes both ways. So an error band of about 1 C? Is that what this means? So we can’t know if there is 1/2 C of warming… The the actual anomalies below bounce around by a 3 C range (that might have a flier off the graph – I didn’t check). Looks to me like Greenland data is just chaotic weather. I do note that the really big DIP happens right on the “baseline period” used by GISStemp (1950-1980) or Hadley (1960-1990)…

GHCN v3.3 vs v4 Greenland Anomaly

Canada

GHCN v3.3 vs v4 Canada Difference

Interesting that it’s a roll off to colder. The anomalies (below) look a mess, but without evident warming. More like the loss of some very low going extremes recently. (One wonders if the big freeze in the last couple of years will show up in future data?)

GHCN v3.3 vs v4 Canada Anomaly

USA

GHCN v3.3 vs v4 USA Anomaly Difference

Again with recent data cooled. Wonder if they were embarrassed by all the attention over the last few years. We also again see no real warming tops, only loss of cold excursions and a general narrowing of the range. Or perhaps being early to the party, they had already “cooked” the v2 data so no more needed here. /snark;

GHCN v3.3 vs v4 USA Anomaly

The Caribbean & Bermuda

These are all in one large shallow water basin with common weather. They ought to be nearly identical.

Antigua & Barbuda

Antigua has no data in GHCN v3.3:

MariaDB [temps]> SELECT COUNT(deg_C) 
FROM anom3 AS A 
INNER JOIN country AS C on A.country=C.cnum 
WHERE C.abrev="AC";
+--------------+
| COUNT(deg_C) |
+--------------+
|            0 |
+--------------+
1 row in set (0.00 sec)

So all we get is the v4 anomaly graph:

GHCN v4 Antigua & Barbuda Anomaly

Bermuda

GHCN v3.3 vs v4 Bermuda Difference

Not a lot of change in the data. They seem to have cooled since 1980 (see graph below) and were hotter back around 1880 – 1860.

GHCN v3.3 vs v4 Bermuda Anomaly

The Bahamas

GHCN v3.3 vs v4 Bahamas Difference

About 1/2 of recent data warmed about 1/2 C, and a cool dip about 1940-1980; but now about the same as the mid 1800s. Cyclical changes?

GHCN v3.3 vs v4 Bahamas Anomaly

Barbados

GHCN v3.3 vs v4 Barbados Difference

Drop the past about 0.4 C and warm the recent about 1/4 C – Presto! a trend! Except that those pesky 1800s look about the same as now. Better use that cold snap from 1940 to 1980 as the “baseline period” and ony measure warming against it.

GHCN v3.3 vs v4 Barbados Anomaly

Cayman Islands

GHCN v3.3 vs v4 Cayman Islands Difference

Again with cooling the past a bit. But from 1990 to date is basically flat. Ought not the “warming from CO2” be more now and less in 1970?

GHCN v3.3 vs v4 Cayman Islands Anomaly

Dominica

Dominica has no data in v3.3, so all we get is the v4 anomaly graph.

MariaDB [temps]> SELECT COUNT(deg_C) 
FROM anom3 AS A 
INNER JOIN country AS C on A.country=C.cnum 
WHERE C.abrev="DO";
+--------------+
| COUNT(deg_C) |
+--------------+
|            0 |
+--------------+
1 row in set (0.06 sec)

GHCN v4 Dominica Anomaly

Dominican Republic

GHCN v3.3 vs v4 Dominican Republic Difference

So they had a crazy high 2 C “warming” rate, chop 1 C out of it and get a more respectable 1 C rate. Or is there just 1.5 C of “random” in temperature measuring on islands?

GHCN v3.3 vs v4 Dominican Republic Anomaly

Grenada

GHCN v3.3 vs v4 Grenada Difference

Again with 2 C of warming, so chop a degree C out of some of it, yet the most recent data points (see below graph) are below normal. But that’s just weather, right?

GHCN v3.3 vs v4 Grenada Anomaly

Guadaloupe

GHCN v3.3 vs v4 Guadeloupe Difference

A whopping 5 C range of temperatures, but currently about the same as 1940. Natural variability or error band, one of the other, is way higher than that 1/2 C of Project Fear Warming.

GHCN v3.3 vs v4 Guadeloupe Anomaly

Haiti

GHCN v3.3 vs v4 Haiti Difference

Looks like nobody fooled with the temperatures between versions. Guess a major hurricane will stop that kind of thing for a while. Anomaly graph below is rather flat too. Had a rise in to 1960, then was ignored for about 20 years, and now the temperatures are like “1940 all over again”.

GHCN v3.3 vs v4 Haiti Anomaly

Jamaica

GHCN v3.3 vs v4 Jamaica Difference

Push up the 40s (outside the baseline interval) a 1/2 C and drop the baseline spots about 1/2 C but with some noise in it, then lift the very recent by about 1/2 C. I think we’ve seen that before.

Per the anomaly graph below, Jamaica has warmed about 3 C. All that without setting regular record temperatures and with nearby islands not having the same rise. Airport tarmac anyone? Didn’t Jamaica have a big pop in tourism with the whole Bob Marley / Reggae thing? I know I went. Locals were complaining about added traffic, all the airplanes and hotels… I note in passing the hot late 1800s highs are about the same as now.

GHCN v3.3 vs v4 Jamaica Anomaly

Martinique

GHCN v3.3 vs v4 Martinique Difference

Differences look like about 1 C range of random. Anomaly trend looks like it was cold in the ’60s and recovered.

GHCN v3.3 vs v4 Martinique Anomaly

Netherlands Antilles

GHCN v3.3 vs v4 Netherlands Antilles Difference

A nice 1/4 C or so cooling of the past, and another 1/4 C to 1/2 C warming of the recent data, pretty soon you got yourself a trend. Except now is about the same as 1980.

GHCN v3.3 vs v4 Netherlands Antilles Anomaly

Puerto Rico

GHCN v3.3 vs v4 Puerto Rico Difference

Well that’s interesting. In v3.3 it was heating up by 1 C in Puerto Rico, so now the change is a 1 C cooling, and Puerto Rico is showing mostly flat trend in the red anomaly spots below. Almost like a decade of scrutiny and being pulled before congress might have caused some folks to fear being caught…

GHCN v3.3 vs v4 Puerto Rico Anomaly

St. Kits & Nevis

GHCN v3.3 vs v4 Saint Kits & Nevis Difference

Nothing goning on in St. Ktis & Nevis. Oddly, as all these islands are in the bathtub together, their anomaly graphs ought to all look alike. Yet they don’t…

GHCN v3.3 vs v4 Saint Kits & Nevis Anomaly

St. Lucia

Saint Lucia has no data in either version, so no graphs at all:

MariaDB [temps]> SELECT COUNT(deg_C) 
FROM anom3 AS A 
INNER JOIN country AS C on A.country=C.cnum 
WHERE C.abrev="DO";
+--------------+
| COUNT(deg_C) |
+--------------+
|            0 |
+--------------+
1 row in set (0.06 sec)


MariaDB [temps]> SELECT COUNT(deg_C) 
FROM anom4 WHERE abrev="ST";
+--------------+
| COUNT(deg_C) |
+--------------+
|            0 |
+--------------+
1 row in set (0.31 sec)

Kinda makes you wonder why it is in the inventory at all.

St. Pierre & Miquelon

GHCN v3.3 vs v4 Saint Pierre & Miquelon Difference

Nice gentle almost unnoticed 1/4 C cooling of the past, a narrow “dip” in the baseline interval. All in all, nicely done sculpting.

GHCN v3.3 vs v4 Saint Pierre & Miquelon Anomaly

ST. Vincent & The Grenadines

Saint Vincent & The Grenadines have no data in version v3.3.

MariaDB [temps]> SELECT COUNT(deg_C) 
FROM anom3 AS A 
INNER JOIN country AS C on A.country=C.cnum 
WHERE C.abrev="VC";
+--------------+
| COUNT(deg_C) |
+--------------+
|            0 |
+--------------+
1 row in set (0.01 sec)

So all we get is this v4 anomaly graph:

GHCN v4 Saint Vincent & The Grenadines Anomaly

Trinidad & Tobago

GHCN v4 Trinidad & Tobago Difference

WOW, that 2 C of change down in the “baseline interval” is about the same as the dip in the anomaly graph then… Without that 2 C of down, Trinidad & Tobago would look sort of flat; with “now” temps about the same as the 1920-1930 temps.

GHCN v4 Trinidad & Tobago Anomaly

Virgin Islands (US)

One wonders what happened to the British Virgin Islands in terms of temperatures… but moving on…

GHCN v4 U.S. Virgin islands Difference

Sure doesn’t look like warming to me. Given some islands flat, and some with 3 C of warming, I think we’re looking at land use issues, thermometer location, or error bands / data fudging.

GHCN v4 U.S. Virgin islands Anomaly

Mexico & Central America

Mexico

GHCN v3.3 vs v4 Mexico Difference

Gee, that recent rise at the tail of the anomaly data (below) seems to match in shape the rise in the difference graph (above).

GHCN v3.3 vs v4 Mexico Anomaly

Belize

GHCN v3.3 vs v4 Belize Difference

The actual anomaly data (below) isn’t warming on the top end, though we do see the loss of low going anomalies in the recent data. As though tons of concrete at the airport held heat over night… The change graph isn’t doing much either, though around 1980 got a spike. Sleepy little Belize…

GHCN v3.3 vs v4 Belize Anomaly

Guatemala

GHCN v3.3 vs v4 Guatemala Difference

Not really warming though we lose some of the low going anomalies in recent data (see graph below) and the changes between v3.3 and v4 are not much. Looks like nobody is paying attention to Guatemala.

GHCN v3.3 vs v4 Guatemala Anomaly

El Salvador

GHCN v3.3 vs v4 El Salvador Difference

Looking at the anomaly plot below, there’s a nice “dip” in the baseline interval, and a gap about 1990-2005, but then some crazy changes in the above difference graph. Looks to me like +/- 1 C of error band and nobody really knowing just what the temperature is in tenths of C.

GHCN v3.3 vs v4 El Salvador Anomaly

Honduras

GHCN v3.3 vs v4 Honduras Difference

Already has a nice “dip” in the baseline interval, but those changes in the recent time are just wild.

GHCN v3.3 vs v4 Honduras Anomaly

Nicaragua

GHCN v3.3 vs v4 Nicaragua Difference

We have 1/2 C drop added to the baseline, and 1 C of rise added in recent data. Just about the same as the “warming” found. Looks like someone found a way to get Nicaragua data in line with goals.

GHCN v3.3 vs v4 Nicaragua Anomaly

Coasta Rica

GHCN v3.3 vs v4 Costa Rica Difference

Nice dip in the baseline interval, but what’s this with the cooing at the end? Costa Rica just not getting hot? And right next to Nicaragua too. Ought to be nearly identical, but isn’t.

GHCN v3.3 vs v4 Costa Rica Anomaly

Panama

GHCN v3.3 vs v4 Panama Difference

Gee.. Looks to me like Panama is being flat to slightly cooling (see below) and not much change at all between v3.3 and v4. I wonder if this is at a US Military Base and they are grumpy if you play with their data? I wonder if that’s why it cuts off in 1980… Seems to me someone ought to know the temperature in Panama right now.

GHCN v3.3 vs v4 Panama Anomaly

Tech Talk

The specifics on the report / graph making programs is in the first “by country” posting so will not be repeated here.

This SQL produced the list of countries in North America (Region 4):

SELECT cnum, abrev,region, cname 
FROM country WHERE region=4 ORDER BY cname;

Here’s the list:

MariaDB [temps]> source bin/Namerica.sql
+------+-------+--------+------------------------------------+
| cnum | abrev | region | cname                              |
+------+-------+--------+------------------------------------+
| 426  | AC    | 4      | Antigua and Barbuda                |
| 423  | BF    | 4      | Bahamas, The                       |
| 401  | BB    | 4      | Barbados                           |
| 402  | BH    | 4      | Belize                             |
| 427  | BD    | 4      | Bermuda [United Kingdom]           |
| 403  | CA    | 4      | Canada                             |
| 429  | CJ    | 4      | Cayman Islands [United Kingdom]    |
| 405  | CS    | 4      | Costa Rica                         |
| 430  | DO    | 4      | Dominica                           |
| 407  | DR    | 4      | Dominican Republic                 |
| 408  | ES    | 4      | El Salvador                        |
| 431  | GL    | 4      | Greenland [Denmark]                |
| 409  | GJ    | 4      | Grenada                            |
| 432  | GP    | 4      | Guadeloupe [France]                |
| 410  | GT    | 4      | Guatemala                          |
| 411  | HA    | 4      | Haiti                              |
| 412  | HO    | 4      | Honduras                           |
| 413  | JM    | 4      | Jamaica                            |
| 433  | MB    | 4      | Martinique [France]                |
| 414  | MX    | 4      | Mexico                             |
| 434  | NT    | 4      | Netherlands Antilles [Netherlands] |
| 415  | NU    | 4      | Nicaragua                          |
| 416  | PM    | 4      | Panama                             |
| 435  | RQ    | 4      | Puerto Rico [United States]        |
| 417  | SC    | 4      | Saint Kitts and Nevis              |
| 436  | ST    | 4      | Saint Lucia                        |
| 438  | SB    | 4      | Saint Pierre and Miquelon [France] |
| 437  | VC    | 4      | Saint Vincent and the Grenadines   |
| 424  | TD    | 4      | Trinidad and Tobago                |
| 425  | US    | 4      | United States                      |
| 440  | VQ    | 4      | Virgin Islands [United States]     |
+------+-------+--------+------------------------------------+
31 rows in set (0.00 sec)

In Conclusion

So there you have it. A few days of “seat time” at the computer. Hopefully it is of use to someone. I think it does point out what country’s data needs more scrutiny. Then there’s also the question of why trends in some nations are different from another very nearby and in the same body of water. Furthermore, there’s a great “cross check” for this in that there is surface water temperature data from decades of hurricane tracking. On these small islands, air temperature never strays far from water temperature. I was swimming in Jamaica once when rain started. The ocean, air, and rain all at 86 F.

It does look like there was a cyclical “dip” after the hot 1930s-40s into a cool ’50s-70s and we have newspaper and magazine articles from then shouting about a New Little Ice Age (and I personally remember it – IT Happened.) So despite the folks saying that picking it for a “baseline” doesn’t matter, I think it’s just too convenient. The method I used to calculate anomaly has no baseline. A given thermometer is only compared to itself over a selected month across the years. (So, for example, the Jamaica Airport thermometer would have all of its Januaries averaged then the January anomaly computed against that. Repeat for each other month of the year for each instrument.) Then there is just the shortness of most records. Many just start in that cold period and rise out of it, not having an old 1870 hot sample to see in their past.

Finally, with that much change showing up in some very small countries, you know they didn’t have a dozen thermometers to choose from in 1890. It must be some kind of “intervention” when decades of data all move by the same amount. It just screams “Fudging the data” (though I’m sure they would call it fixing errors in the past). But when all the “warming” comes from the “fixing up” and “adjusting” (even of this “unadjusted” data) or from splicing a 1/2 cycle and calling it a trend: Just where is the room for CO2?

It took me a few days of “seat time” to make this set and post it, so don’t worry if you just want to look at a few each day over time. After the first dozen even my eyes started to glaze over 😉 But these will be here for months or years to come, for your pondering.

Inconvenient stumps

Reblogged from Watts Up With That:

Climate alarmists tell us that the Earth has never been warmer, and that we can tell by looking at tree rings, treelines, and other proxy indicators of climate.

Climate scientists claim the warmth is unprecedented.

We’ve been told it is warming so fast, we have only 12 years left!

Yet nature seems to not be paying attention to such pronouncements, as this discovery shows.

This photo shows a tree stump of White Spruce that was radiocarbon dated at 5000 years old. It was located 100 km north of the current tree line in extreme Northwest Canada.

The area is now frozen tundra, but it was once warm enough to support significant tree growth like this.

If climate was this warm in the past, how did that happen before we started using the fossil fuels that supposedly made our current climate unprecedentedly warm?

GHCN v3.3 vs v4 Anomaly South America

Reblogged from Musings from the Chiefio:

Earlier I looked at a subset of countries globally, comparing their “change of temperature from the average” (anomaly) for a given set of thermometers in a given country as it is found in the Global Historical Climate Network version 3.3 when compared to version 4. Now you might think that since this is “historical” it ought not change. And since it is based on “anomalies”, if you have a couple of different thermometers in the set (as the Warmers constantly insist) it would not cause a change. (After all, if it’s 1 C warmer in your front yard it’s also 1 C warmer in your back yard…) So you would expect that there ought to either be NO change, or any change will be due to the application of changed “adjustments” to the temperatures (that just happen to exactly match ALL global warming found…) But these are the “unadjusted” data sets, so ought not to have any of that.

Yet they are different. Often for what ought to be the SAME thermometer in the same time and place in history. (You can’t go back to 1850 and add a new thermometer in Cuba…)

I’ll be presenting two graphs for each country. One has black spots for the Anomaly in a given year for GHCN v3.3 in that country, and red spots for what is the same country, year, and anomaly process but from GHCN v4. Often they are different (almost always). Sometimes up to whole degrees C. Now if your thermometer selection and processing can change THE SAME PLACE AND TIME in history by 1 C, what are the odds that 1/2 C of “global warming” comes from just that sort of instrument change? I’d rank it at about 100%.

For reference, here’s the climate zones from the Wiki on South America

South America Koppen – Geiger Climate Zones

The Graphs

Since we saw Argentina and Brazil in the earlier posting, I’ll Start with Brazil, then add the countries near it to the north and away from the Andes. Then we’ll travel down the spine of the Andes ending with Chile and Argentina, then finally fill in Paraguay and Uruguay on the south side of Brazil up against Argentina. Ending with the two island clusters of the Falkland islands and South Georgia & Sandwich Islands.

Brazil

GHCN v3.3 vs v4 Brazil Difference

GHCN v3.3 vs v4 Brazil Anomaly

Cuba

Cuba is included in South America, but personally I’d have accounted for it in with all the other Caribbean islands.

GHCN v3.3 vs v4 Cuba Difference

Mostly the old data is “cooled” and the recent data given a bit of a “lift”. Looking at the raw anomalies below, it looks like Cuba has some cycles in it, and like it was “way hot” in the long ago past.

GHCN v3.3 vs v4 Cuba Anomaly

Venezuela

GHCN v3.3 vs v4 Venezuela Difference

The past cooled by 1/4 to 3/4 C in a nice general slope. Has the past of Venezuela really cooled?…

GHCN v3.3 vs v4 Venezuela Anomaly

French Guiana

GHCN v3.3 vs v4 French Guiana Difference

Looking at the anomalies down below, not much to work with. So we get that tail in the present being changed a lot higher. But hey, what’s a full degree C of “fixing it up” anomaly change when you need to get a global 1/2 C of “warming’ out of stable actual data… But really, what a “dogs breakfast” that is. A “dip” of 1/2 C in the “baseline period” and then an added almost a full C in the most recent common data? What can possibly justify that? Remember, this is supposed to be the same place same times.. and many of the same instruments if not all of them the same.

GHCN v3.3 vs v4 French Guiana Anomaly

Guyana

GHCN v3.3 vs v4 Guyana Difference

Oh wow. A full degree C of “dip” in the baseline near 1980, then a 2 c “FLYER” negative before 2000, then up to 1 C of “uplift” in the recent tail. Sheesh.

GHCN v3.3 vs v4 Guyana Anomaly

Suriname

GHCN v3.3 vs v4 Suriname Difference

1.5 C of “rise” added recently. Really? WT?… Nice 1/2 C “dip” in the tail of the baseline period.

GHCN v3.3 vs v4 Suriname Anomaly

Colombia

GHCN v3.3 vs v4 Colombia Difference

Then we hit Colombia and it’s just not happening. Looks rather flat and dull. Guess they were too busy with the cocaine trade to give a fig about the UN Climate Graft money… Or maybe CO2 got kinda high and forgot to warm things up… Well, someone got high…

GHCN v3.3 vs v4 Colombia Anomaly

Ecuador

GHCN v3.3 vs v4 Ecuador Difference

Half a degree down in the baseline, to 3/4 C down, then 1/2 C up recently in the “fixing”. Now that’s someone on board with the agenda!

GHCN v3.3 vs v4 Ecuador Anomaly

Peru

GHCN v3.3 vs v4 Peru Difference

Actual anomalies (below) not going anywhere… Short record. What to do, what to do… How about dip it 0.4 C in the baseline and lift the near end another 1/2 C?

GHCN v3.3 vs v4 Peru Anomaly

Bolivia

GHCN v3.3 vs v4 Bolivia Difference

Highly volatile (see below) and not much trend, then the “fix” being all over the place. What a mess. On this we bet the global economy?

GHCN v3.3 vs v4 Bolivia Anomaly

Chile

GHCN v3.3 vs v4 Chile Difference

Not much really happening below, so what’s our “Go To” thing? Dip the baseilne around the ’50s and bump up the present by 1/4 C to 1/2 C.

GHCN v3.3 vs v4 Chile Anomaly

Argentina

GHCN v3.3 vs v4 Argentina Difference

GHCN v3.3 vs v4 Argentina Anomaly

Paraguay

GHCN v3.3 vs v4 Paraguay Difference

Just WOW. Drop the WHOLE past by 1/4 C, then pop up 1/5 C to a full 1.5 C in the recent data. Just WOW.

GHCN v3.3 vs v4 Paraguay Anomaly

Uruguay

Guess Uruguay is not all that interesting. Not a team players. Only gets about .4 C of dip at the very end of the “baseline period” and can’t get more than 1/4 C of “lift” in the recent data.

Then we once again leave the mainland for two groups of Islands in the Southern Ocean.

The Falkland Islands

GHCN v3.3 vs v4 Falkland Islands Difference

Nothing really happening in the Falklands. (In more ways than one). Gee, think a stable station in the middle of the south Atlantic Gyre might mean not much is happening? (Someone will need to fix that in v5… I’d /sarc; it but I’m not sure that’s valid…)

GHCN v3.3 vs v4 Falkland Islands Anomaly

South Georgia and Sandwich Island

GHCN v3.3 vs v4 South Georgia & Sandwich Islands Difference

This one is interesting. Some “High Fliers” in years where the prior data set had no data. How’d they do that? Go back and put data in where none was reported? Overall, another flat island in the ocean. But with mystery fliers. Though they did manage to cool almost the entire history by about 1/3 C, so there’s that…

GHCN v3.3 vs v4 South Georgia & Sandwich Islands Anomaly

Tech Talk

This would basically be a repeat of the tech stuff in the prior posting, so take a look there for example code and the hows / whys / and designs.

https://chiefio.wordpress.com/2019/04/09/ghcn-v3-3-vs-v4-selected-country-anomaly-differences

In Conclusion

I’ve scattered some detail comments through the graphs and as I get time to stare at them a bit, if I see something else I’ll add it in comments. You may well see something I’ve not seen, so stare at ’em and ponder…

In general, I’ve noticed some places hardly change at all. Often very minor places like an island somewhere. Larger places look more “manicured” with loss of low going excursions in the data lately. Then there’s the general tendency to cool the past, and put “dips” in the “baseline” period used by GISStemp and Hadley (1950 to 1990). Is it really the case that all those places had just those same needs to cool the past, dip the baseline and juice up the recent highs while clipping recent lows? What physicality could possible account for that? What systematic failure of thermometer tech Globally can account for those “errors”?

To me it looks like deliberately cooking the books.

In Aftermath of Volcanic Eruption, Photosynthesis Waxes, Carbon Dioxide Wanes

From Scientific American:

By Laura Wright on March 28, 2003

 

Read more from this special report:

A Guide to Volcanoes

In June 1991, when Mt. Pinatubo in the Philippines spewed tons of volcanic ash and gases into the atmosphere, it just so happened that halfway around the world scientists were beginning to obtain good data from carbon dioxide monitors high above the tree canopy in Harvard Forest, outside Boston, Mass. Now, more than a decade later, the measurements taken during the years following the eruption are providing new insight into how atmospheric aerosols affect photosynthesis. The findings, published today in the journal Science, are forcing scientists to rethink the factors that influence the cycling of carbon through the environment, particularly carbon dioxide, a major player in global warming.

 

Within three weeks of the Mt. Pinatubo eruption, the largest volcanic blast of the century, a band of sulfur aerosol had encircled the globe. By early 1992, the volcanic gases and aerosols had diffused through the stratosphere, veiling the earth. During that time, global carbon dioxide levels fell more sharply than any other decline on record. Some scientists suggested that global cooling caused ecosystem respiration to drop, lowering the amount of carbon dioxide emitted into the atmosphere. But Lianhong Gu of Oak Ridge National Laboratory, lead author of the Science report, didn’t think that could be the only explanation.

Gu knew that crop scientists had discovered that plants grow best in diffuse light. When sunlight is too intense, some leaves fall into shadow, unable to photosynthesize, while others bask in the direct beams but will reach a photosynthetic saturation point. Moderate cloud cover and aerosols block direct beams, but allow light to bounce back and forth off water vapor and other molecules, creating a “softer” light that reaches leaves that would otherwise be shaded. As a result, the plants photosynthesize more, using up carbon dioxide in the process. Gu and his collaborators determined that the same principles apply to forest canopies. The Harvard Forest data show that carbon dioxide levels dropped for two years following the eruption at Mt. Pinatubo findings that the scientists suggest represent a worldwide phenomenon given that the eruption had a global atmospheric effect. “Up until now we hadn’t linked aerosols and clouds with carbon studies,” Gu says. “In order to understand atmospheric carbon dioxide concentrations, which affect climate, we have to look at how aerosols and clouds affect the global carbon cycle.”

Warmists Epic History Fail

Science Matters

Geologist Gregory Whitestone provides a climate history lesson for warmists who skipped history classes protesting against global warming.  Hist article at Town Hall is Ocasio-Cortez’s Climatology Lacks Historical Context. Excerpts in italics with my bolds. H/T Climate Depot.

When Sam Cooke sang “Don’t know much about history” in 1960 he could not have had U.S. Rep. Alexandria Ocasio-Cortez in mind, but only because she lives a half century later.

Whatever Ocasio-Cortez got from history classes during her time at Boston University, it wasn’t an appreciation of historical context because it is sorely lacking in her assertions about climate and its effect on humankind. She and others promoting the Green New Deal have the facts exactly backwardswhen they claim that warming temperatures are an existential threat to humanity.

Ocasio-Cortez recently warned in a House Oversight Committee hearing that the United States would have “blood on our hands” if legislation to…

View original post 850 more words

Inconvenient stumps

Reblogged from Watts Up With That:

Climate alarmists tell us that the Earth has never been warmer, and that we can tell by looking at tree rings, treelines, and other proxy indicators of climate.

Climate scientists claim the warmth is unprecedented.

We’ve been told it is warming so fast, we have only 12 years left!

Yet nature seems to not be paying attention to such pronouncements, as this discovery shows.

This photo shows a tree stump of White Spruce that was radiocarbon dated at 5000 years old. It was located 100 km north of the current tree line in extreme Northwest Canada.

The area is now frozen tundra, but it was once warm enough to support significant tree growth like this.

If climate was this warm in the past, how did that happen before we started using the fossil fuels that supposedly made our current climate unprecedentedly warm?

California water supply dream

sunshine hours

I’m dreaming of a wet California …

“With full reservoirs and a dense snowpack, this year is practically a California water supply dream,” California DWR Director Karla Nemeth said April 2, 2019, after latest Sierra snowpack measurement.

California state officials made their monthly snowpack measurement at Phillips Station in the Sierra and confirmed there will be no lack of water this year.

Snowpack at the station was at 200% of average while statewide snowpack is 162% of average.

“This is great news for this year’s water supply, but water conservation remains a way of life in California, rain or shine,” California Department of Water Resources said.

The state has experienced more than 30 atmospheric rivers since the start of the water year, six in February alone, and statewide snow water equivalent has nearly tripled since February 1, officials said.

Phillips Station now stands at 106.5 inches (270.5 cm) of snow…

View original post 111 more words

The Little Ice Age (LIA) was most likely the coldest period of the Holocene Epoch

This is a comment by David Middleton from Jim Steele’s post on Watts Up With That:

The Little Ice Age (LIA) was most likely the coldest period of the Holocene Epoch. In Central Greenland it was roughly the same temperature as it was during the Bølling-Allerød glacial interstadial.

The modern rise in atmospheric CO2 lagged behind the warm up from the LIA.

The LIA clearly appears to be related to a roughly 1,000-yr quasi-periodic fluctuation.

The 1,000-yr quasi-periodic fluctuation appears to be the dominant climate signal of the Holocene.

Davis_Fig_6Davis_Fig_7

And the modern warming is statistically indistinguishable from the Medieval Warm Period.

Yet we’re supposed to destroy our economy and become good little Marxists because Hockey Stick-head is a fracking moron.