What Global Warming?

Berkeley Earth is a popular resource among climate alarmists. Today I will examine their most popular data, available here. This data is the basis of a very popular meme, the global warming color stripes. But how valid is it? Could it be a misinterpretation?

First, we will need three tools:

> sudo apt install gnuplot ncview nco

Then download & plot:

> (echo 'set term png size 740,370;set grid;unset key;plot "-" u 1:2 w lines lw 2 lc rgb "red"'; wget -qO- http://berkeleyearth.lbl.gov/auto/Global/Land_and_Ocean_summary.txt | awk 'length($1)==4{print $1" "$2}') | gnuplot > t.png

http://berkeleyearth.lbl.gov/auto/Global/Land_and_Ocean_summary.txt (1st and 2nd Column)

Looks like legit global warming! OK, we’re done!

We must demand extremely costly legislation!

No wait …

Let’s download their whole dataset from here. (Warning: File is 400MB+, Don’t Click!)

> wget -c -O temps.nc http://berkeleyearth.lbl.gov/auto/Global/Gridded/Land_and_Ocean_LatLong1.nc

Open up the file with ncview:

> ncview temps.nc

Here is coverage for January of years: 1850, 1875, 1900, 1925, 1950, and 2019

White = Missing Data

As you can see, we obviously did not have global coverage for most of the interested period. Could it possibly be that the “global” warming reported by Berkeley Earth and similar outfits is actually a statistical artifact due to increased coverage and incompatible comparison? In other words, is it the whole globe that’s warming or is it just the shifting and increasing subset of the globe that’s warming?

Good question! Let’s investigate …

We need elevation data so that we can see if that’s a factor. We get that from here. Download using:

> wget -c http://research.jisao.washington.edu/data_sets/elevation/elev.1-deg.nc

The Berkeley Earth data file has information about the baseline temperatures for Jan 1950 through Dec 1980. We examine this first. Create a new file called base.sh, and paste in the following text:

#!/usr/bin/bash
# Zoe Phin, 2019/12/29

ncks --trd -HC elev.1-deg.nc -v data | sed \$d | awk -F[=\ ] '$8>=0{print $8} $8<0{print 0}' > .elev

onemonth() {
	for l in `seq 0 179`; do
		ncks -v climatology -d month_number,$1,$1 -d latitude,$l,$l temps.nc |\
		sed -n '/climatology =/,/;/p' | sed 1d | tr -d ' ;' | tr ',' '\n' |\
		awk -v l=$l 'function rad(x) { return x*atan2(0,-1)/180 } {
			lat = l - 89.5; lon = n - 179.5; n += 1

			a = 6378137.678; b = 6356752.964; E = 1-b^2/a^2;
			x = rad(lat)
			A = (a*rad(1))^2*(1-E)*cos(x)/(1-E*sin(x)^2)^2

			printf "%5.1f %6.1f %10.6f %20.18f\n", lat, lon, $1, A/510072261022077
		}'    
	done > .t$1
	paste .t$1 .elev
}

allmonths() {
	for t in `seq 0 11`; do
		printf "%2d " $(($t+1)); onemonth $t |\
			awk '$3!="nan"{T+=$3*$4;L+=$1*$4;A+=$4;E+=$5*$4}END{
				printf "%10.6f %5.3f %6.3f %7.2f\n",T,A,L/A,E/A}'
	done | awk '{print;S+=$2}END{print "AVG: "S/12}'
}

allmonths

Make this file executable and run it:

> chmod +x temps.sh
> ./base.sh

 1  12.243634 1.000  0.000  232.86
 2  12.429942 1.000  0.000  232.86
 3  13.030878 1.000  0.000  232.86
 4  13.999172 1.000  0.000  232.86
 5  14.955463 1.000  0.000  232.86
 6  15.675272 1.000  0.000  232.86
 7  15.915606 1.000  0.000  232.86
 8  15.757542 1.000  0.000  232.86
 9  15.143898 1.000  0.000  232.86
10  14.242063 1.000  0.000  232.86
11  13.198164 1.000  0.000  232.86
12  12.521963 1.000  0.000  232.86
AVG: 14.0928

Here we see the month number, the average area-weighted temperature, coverage (100%), average latitude (equator), and average elevation. Average elevation will come in handy later. At the end is an annual average temperature. So far so good. Now we do latitude analysis. Create a new file latitudes.sh, and paste in the following:

#!/usr/bin/bash
# Zoe Phin, 2019/12/29

paste .t0 .t1 .t2 .t3 .t4 .t5 .t6 .t7 .t8 .t9 .t10 .t11 | awk '{
	$1 += 0.5; if ($1 < 0) $1 = 0 - $1
	printf "%5.1f %6.1f %10.6f\n", $1, $2, 
		($3+$7+$11+$15+$19+$23+$27+$31+$35+$39+$43+$47+$51+$55+$59+$63)/12
}' | awk '{
	L[$1]+=$3 } END {
	for (l in L) {
		L[l]/=720
		if (l == "0.0") { L[l]*=2 }
		printf "%5.1f %10.6f\n", l, L[l]
	}
}'  | sort -n | awk '{print $1" "$2-L;L=$2}'\
	| sed 1d | sed -n 1,24p | awk '{S+=$2}END{print S/NR}'

Now run it:

> bash latitudes.sh

-0.133022

This tells us that in the tropics, for every degree latitude away from the equator, the temperature drops 0.133 °C, according to 1950-1980 baseline data. This fact will come in handy later.

Now we are ready to analyze the temporal data. Create a new file called temps.sh and paste the following text into it:

#!/usr/bin/bash
# Zoe Phin, 2019/12/29

ncks -v data -lat,0,0 elev.1-deg.nc |\                                                                              
    sed -n '/data =/,/;/p' | sed 1d |\                                            
    tr -d ' ;' | tr ',' '\n' | sed '/^$/d' |\
    awk '$1>=0{print $1}$1<0{print 0}' > .elev

onetime() {
    for l in `seq 0 179`; do
        ncks -v temperature -d time,$1,$1 -d latitude,$l,$l temps.nc |\
        sed -n '/temperature =/,/;/p' | sed 1d | tr -d ' ;' | tr ',' '\n' |\
        awk -v l=$l 'function rad(x) { return x*atan2(0,-1)/180 } {  
            lat = l - 89.5; lon = n - 179.5; n += 1
            a = 6378137.678; b = 6356752.964; E = 1-b^2/a^2;
            x = rad(lat)
            A = (a*rad(1))^2*(1-E)*cos(x)/(1-E*sin(x)^2)^2
            printf "%5.1f %6.1f %10.6f %20.18f\n", lat, lon, $1, A/510072261022077
        }'    
    done > .tmp                                                                                                       
    paste .tmp .elev 
}   

alltimes() {
    for t in `seq 0 2027`; do
        printf "%4d " $t 
        onetime $t | awk '
            $3!="nan"{T+=$3*$4;L+=$1*$4;A+=$4;E+=$5*$4}END{printf "%10.6f %5.3f %6.3f %7.2f\n",T,A,L/A,E/A}'
    done
}   

alltimes

Make new file executable, and run it. Then wait hours. lol

> chmod +x temps.sh
> ./temps.sh | tee temps.csv

While you’re waiting for temps.csv to be completely filled, create a new program that will analyze and adjust the results. Call it analyze.sh

#!/usr/bin/bash
# Zoe Phin, 2019/12/29

monthly() {
    awk '{printf "%4d %02d %10.6f %5.3f %6.3f %6.2f\n",$1/12+1850,$1%12+1,$2,$3,$4,$5}'
}

yearly() {
    awk '{T[$1]+=$3; C[$1]+=$4; L[$1]+=$5; E[$1]+=$6} END {
        for (y in T) { 
            printf "%4d %10.6f %5.3f %6.3f %6.2f\n",y,T[y]/12,C[y]/12,L[y]/12,E[y]/12 
        }
    }' | sort -n
}

adjust() {
    awk '{
        if ($4 < 0) $4 = 0 - $4
        printf "%s  %8.6f  %7.4f\n", $0, $4*0.133022, -0.0057*(232.86-$5)
    }' |\
    awk '{
        printf "%s  = %10.6f\n", $0, $2 + $6 + $7
    }'
}

monthly | yearly | adjust

Notice that I’m using two parameters we discovered earlier: 0.133022 and 232.86 (mean elevation). A third parameter is 0.0057, which is just the average lapse rate in °C/meter.

Make the file executable and run it after temps.csv is completely generated.

> ./chmod +x analyze.sh
> cat temps.csv | ./analyze.sh | tee final.csv

1850  -0.357290 0.770  9.075 230.12  1.207175  -0.0156 =   0.834285
1851  -0.283336 0.782  7.687 226.25  1.022540  -0.0377 =   0.701504
1852  -0.258400 0.780  7.954 217.99  1.058057  -0.0848 =   0.714857
1853  -0.306750 0.832  5.019 224.64  0.667637  -0.0469 =   0.313987
1854  -0.274175 0.842  3.801 219.65  0.505617  -0.0753 =   0.156142
1855  -0.241830 0.833  3.595 224.71  0.478214  -0.0465 =   0.189884
1856  -0.355853 0.843  3.705 225.26  0.492847  -0.0433 =   0.093694
1857  -0.461720 0.849  3.100 219.24  0.412368  -0.0776 =  -0.126952
1858  -0.354328 0.834  3.874 222.37  0.515327  -0.0598 =   0.101199
1859  -0.313976 0.829  2.207 230.06  0.293580  -0.0160 =  -0.036396
1860  -0.337673 0.747  3.282 224.38  0.436578  -0.0483 =   0.050605
1861  -0.372894 0.664  5.272 187.82  0.701292  -0.2567 =   0.071698
1862  -0.424297 0.689  4.241 216.75  0.564146  -0.0918 =   0.048049
1863  -0.245435 0.604  6.774 167.69  0.901091  -0.3715 =   0.284156
1864  -0.295420 0.690  5.608 193.15  0.745987  -0.2263 =   0.224267
1865  -0.209959 0.606  5.634 190.14  0.749446  -0.2435 =   0.295987
1866  -0.170314 0.587  7.426 210.01  0.987821  -0.1302 =   0.687307
1867  -0.167626 0.605  4.531 208.39  0.602723  -0.1395 =   0.295597
1868  -0.164820 0.693  1.542 221.86  0.205120  -0.0627 =  -0.022400
1869  -0.212144 0.811  3.939 239.15  0.523974   0.0359 =   0.347730
1870  -0.273406 0.841  3.148 237.14  0.418753   0.0244 =   0.169747
1871  -0.281568 0.826  2.503 239.02  0.332954   0.0351 =   0.086486
1872  -0.260434 0.851  2.382 229.30  0.316858  -0.0203 =   0.036124
1873  -0.245535 0.870  3.264 236.25  0.434184   0.0193 =   0.207949
1874  -0.316410 0.858  2.290 236.99  0.304620   0.0235 =   0.011710
1875  -0.343630 0.902  3.548 227.12  0.471962  -0.0327 =   0.095632
1876  -0.351453 0.880  3.113 229.60  0.414097  -0.0186 =   0.044044
1877  -0.010802 0.891  3.061 227.45  0.407180  -0.0308 =   0.365578
1878   0.070294 0.920  3.761 220.60  0.500296  -0.0699 =   0.500690
1879  -0.219576 0.905  3.533 222.53  0.469967  -0.0589 =   0.191491
1880  -0.283391 0.903  2.997 219.83  0.398667  -0.0743 =   0.040976
1881  -0.199763 0.920  3.777 219.21  0.502424  -0.0778 =   0.224861
1882  -0.246604 0.933  3.889 227.58  0.517323  -0.0301 =   0.240619
1883  -0.295346 0.935  3.978 228.95  0.529162  -0.0223 =   0.211516
1884  -0.445828 0.939  3.970 229.57  0.528097  -0.0188 =   0.063469
1885  -0.421912 0.934  4.251 232.04  0.565477  -0.0047 =   0.138865
1886  -0.458854 0.939  4.209 229.30  0.559890  -0.0203 =   0.080736
1887  -0.481525 0.941  4.258 231.56  0.566408  -0.0074 =   0.077483
1888  -0.299911 0.937  4.022 232.11  0.535014  -0.0043 =   0.230803
1889  -0.173886 0.928  3.699 234.59  0.492048   0.0099 =   0.328062
1890  -0.434682 0.914  3.849 232.06  0.512002  -0.0046 =   0.072720
1891  -0.335364 0.905  3.290 240.85  0.437642   0.0455 =   0.147778
1892  -0.382409 0.926  3.818 234.61  0.507878   0.0100 =   0.135469
1893  -0.373769 0.930  3.979 233.86  0.529295   0.0057 =   0.161226
1894  -0.362064 0.913  4.107 233.84  0.546321   0.0056 =   0.189857
1895  -0.301138 0.905  3.449 237.65  0.458793   0.0273 =   0.184955
1896  -0.209349 0.914  3.530 239.58  0.469568   0.0383 =   0.298519
1897  -0.200136 0.919  3.538 238.05  0.470632   0.0296 =   0.300096
1898  -0.395082 0.942  4.022 232.84  0.535014  -0.0001 =   0.139832
1899  -0.239184 0.945  4.072 231.99  0.541666  -0.0050 =   0.297482
1900  -0.134154 0.943  4.175 231.34  0.555367  -0.0087 =   0.412513
1901  -0.205338 0.944  4.127 231.32  0.548982  -0.0088 =   0.334844
1902  -0.334302 0.945  4.046 231.59  0.538207  -0.0072 =   0.196705
1903  -0.435556 0.952  3.585 232.03  0.476884  -0.0047 =   0.036628
1904  -0.472943 0.953  3.521 231.87  0.468370  -0.0056 =  -0.010173
1905  -0.323819 0.952  3.588 232.04  0.477283  -0.0047 =   0.148764
1906  -0.256762 0.952  3.605 232.17  0.479544  -0.0039 =   0.218882
1907  -0.413088 0.952  3.583 232.06  0.476618  -0.0046 =   0.058930
1908  -0.439984 0.953  3.575 231.93  0.475554  -0.0053 =   0.030270
1909  -0.500328 0.953  3.578 231.99  0.475953  -0.0050 =  -0.029375
1910  -0.474652 0.951  3.589 231.81  0.477416  -0.0060 =  -0.003236
1911  -0.487573 0.951  3.567 231.32  0.474489  -0.0088 =  -0.021884
1912  -0.414555 0.954  3.496 231.90  0.465045  -0.0055 =   0.044990
1913  -0.382771 0.953  3.555 231.92  0.472893  -0.0054 =   0.084722
1914  -0.223899 0.951  3.667 232.11  0.487792  -0.0043 =   0.259593
1915  -0.157645 0.949  3.819 232.08  0.508011  -0.0044 =   0.345966
1916  -0.380000 0.941  4.299 232.10  0.571862  -0.0043 =   0.187562
1917  -0.480852 0.931  4.939 229.73  0.656996  -0.0178 =   0.158344
1918  -0.323954 0.908  6.281 225.14  0.835511  -0.0440 =   0.467557
1919  -0.258707 0.918  5.622 226.10  0.747850  -0.0385 =   0.450643
1920  -0.241853 0.943  4.200 232.26  0.558692  -0.0034 =   0.313439
1921  -0.182841 0.948  3.915 232.11  0.520781  -0.0043 =   0.333640
1922  -0.272134 0.953  3.580 232.01  0.476219  -0.0048 =   0.199285
1923  -0.251429 0.950  3.737 232.01  0.497103  -0.0048 =   0.240874
1924  -0.247327 0.951  3.701 231.85  0.492314  -0.0058 =   0.239187
1925  -0.205461 0.950  3.764 231.94  0.500695  -0.0052 =   0.290034
1926  -0.069547 0.952  3.631 232.06  0.483003  -0.0046 =   0.408856
1927  -0.176755 0.952  3.640 232.03  0.484200  -0.0047 =   0.302745
1928  -0.155696 0.950  3.732 232.09  0.496438  -0.0044 =   0.336342
1929  -0.333335 0.951  3.666 231.75  0.487659  -0.0063 =   0.148024
1930  -0.120497 0.950  3.776 232.05  0.502291  -0.0046 =   0.377194
1931  -0.070735 0.952  3.594 231.95  0.478081  -0.0052 =   0.402146
1932  -0.103892 0.953  3.550 231.85  0.472228  -0.0058 =   0.362536
1933  -0.278755 0.954  3.498 232.04  0.465311  -0.0047 =   0.181856
1934  -0.149201 0.953  3.517 232.06  0.467838  -0.0046 =   0.314037
1935  -0.186067 0.953  3.549 232.07  0.472095  -0.0045 =   0.281528
1936  -0.138241 0.955  3.426 231.90  0.455733  -0.0055 =   0.311992
1937   0.023886 0.954  3.484 231.98  0.463449  -0.0050 =   0.482335
1938   0.028060 0.955  3.431 231.90  0.456398  -0.0055 =   0.478958
1939   0.003556 0.950  3.683 230.77  0.489920  -0.0119 =   0.481576
1940   0.099252 0.936  4.594 228.66  0.611103  -0.0239 =   0.686455
1941   0.074650 0.925  5.307 228.02  0.705948  -0.0276 =   0.752998
1942   0.035199 0.925  5.355 227.44  0.712333  -0.0309 =   0.716632
1943   0.070681 0.916  5.850 227.37  0.778179  -0.0313 =   0.817560
1944   0.156531 0.890  7.065 200.57  0.939800  -0.1841 =   0.912231
1945   0.032824 0.877  7.844 205.34  1.043425  -0.1569 =   0.919349
1946  -0.042840 0.950  3.540 229.52  0.470898  -0.0190 =   0.409058
1947   0.050743 0.960  3.004 231.05  0.399598  -0.0103 =   0.440041
1948  -0.064158 0.963  2.719 230.03  0.361687  -0.0161 =   0.281429
1949  -0.084292 0.964  2.721 231.53  0.361953  -0.0076 =   0.270061
1950  -0.161060 0.977  1.753 236.13  0.233188   0.0186 =   0.090728
1951   0.001301 0.985  1.177 235.44  0.156567   0.0147 =   0.172568
1952   0.076559 0.963  2.836 232.62  0.377250  -0.0014 =   0.452409
1953   0.131789 0.960  2.998 232.61  0.398800  -0.0014 =   0.529189
1954  -0.055526 0.975  1.926 231.30  0.256200  -0.0089 =   0.191774
1955  -0.111239 0.981  1.329 229.13  0.176786  -0.0213 =   0.044247
1956  -0.180457 0.997  0.183 232.94  0.024343   0.0005 =  -0.155614
1957   0.051807 0.999  0.078 232.86  0.010376  -0.0000 =   0.062183
1958   0.061004 0.999  0.082 232.72  0.010908  -0.0008 =   0.071112
1959   0.035838 0.997  0.196 232.82  0.026072  -0.0002 =   0.061710
1960  -0.012004 0.998  0.104 232.77  0.013834  -0.0005 =   0.001330
1961   0.073172 0.999  0.078 232.80  0.010376  -0.0003 =   0.083248
1962   0.025351 0.998  0.128 232.91  0.017027   0.0003 =   0.042678
1963   0.065958 0.997  0.165 232.75  0.021949  -0.0006 =   0.087307
1964  -0.204562 0.999  0.051 232.78  0.006784  -0.0005 =  -0.198278
1965  -0.103658 0.999  0.027 232.74  0.003592  -0.0007 =  -0.100766
1966  -0.035893 0.999  0.030 232.84  0.003991  -0.0001 =  -0.032002
1967   0.007587 1.000  0.014 232.89  0.001862   0.0002 =   0.009649
1968  -0.056209 1.000  0.018 232.88  0.002394   0.0001 =  -0.053715
1969   0.086212 1.000  0.009 232.85  0.001197  -0.0001 =   0.087309
1970   0.022673 0.999  0.044 232.89  0.005853   0.0002 =   0.028726
1971  -0.098918 0.999  0.060 232.96  0.007981   0.0006 =  -0.090337
1972  -0.009380 0.999  0.076 233.00  0.010110   0.0008 =   0.001530
1973   0.107283 0.999  0.050 232.97  0.006651   0.0006 =   0.114534
1974  -0.109770 0.999  0.082 232.98  0.010908   0.0007 =  -0.098162
1975  -0.053170 0.999  0.065 232.98  0.008646   0.0007 =  -0.043824
1976  -0.161628 0.998  0.155 233.01  0.020618   0.0009 =  -0.140110
1977   0.136867 0.999  0.041 232.94  0.005454   0.0005 =   0.142821
1978   0.009959 1.000  0.017 232.90  0.002261   0.0002 =   0.012420
1979   0.096247 1.000  0.005 232.87  0.000665   0.0001 =   0.097012
1980   0.215677 1.000  0.000 232.86  0.000000  -0.0000 =   0.215677
1981   0.264261 1.000  0.000 232.86  0.000000  -0.0000 =   0.264261
1982   0.044925 1.000  0.000 232.86  0.000000  -0.0000 =   0.044925
1983   0.237702 1.000  0.000 232.86  0.000000  -0.0000 =   0.237702
1984   0.072032 1.000  0.000 232.86  0.000000  -0.0000 =   0.072032
1985   0.059067 1.000  0.000 232.86  0.000000  -0.0000 =   0.059067
1986   0.113913 1.000  0.000 232.86  0.000000  -0.0000 =   0.113913
1987   0.246261 1.000  0.000 232.86  0.000000  -0.0000 =   0.246261
1988   0.292035 1.000  0.000 232.86  0.000000  -0.0000 =   0.292035
1989   0.175688 1.000  0.000 232.86  0.000000  -0.0000 =   0.175688
1990   0.367576 1.000  0.000 232.86  0.000000  -0.0000 =   0.367576
1991   0.350261 1.000  0.000 232.86  0.000000  -0.0000 =   0.350261
1992   0.163420 1.000  0.000 232.86  0.000000  -0.0000 =   0.163420
1993   0.195115 1.000  0.000 232.86  0.000000  -0.0000 =   0.195115
1994   0.246145 1.000  0.000 232.86  0.000000  -0.0000 =   0.246145
1995   0.390852 1.000  0.000 232.86  0.000000  -0.0000 =   0.390852
1996   0.293093 1.000  0.000 232.86  0.000000  -0.0000 =   0.293093
1997   0.436165 1.000  0.000 232.86  0.000000  -0.0000 =   0.436165
1998   0.587775 1.000  0.000 232.86  0.000000  -0.0000 =   0.587775
1999   0.353628 1.000  0.000 232.86  0.000000  -0.0000 =   0.353628
2000   0.366550 1.000  0.000 232.86  0.000000  -0.0000 =   0.366550
2001   0.508265 1.000  0.000 232.86  0.000000  -0.0000 =   0.508265
2002   0.586163 1.000  0.000 232.86  0.000000  -0.0000 =   0.586163
2003   0.570285 1.000  0.000 232.86  0.000000  -0.0000 =   0.570285
2004   0.473007 1.000  0.000 232.86  0.000000  -0.0000 =   0.473007
2005   0.655408 1.000  0.000 232.86  0.000000  -0.0000 =   0.655408
2006   0.607471 1.000  0.000 232.86  0.000000  -0.0000 =   0.607471
2007   0.616768 1.000  0.000 232.86  0.000000  -0.0000 =   0.616768
2008   0.482518 1.000  0.000 232.86  0.000000  -0.0000 =   0.482518
2009   0.615649 1.000  0.000 232.86  0.000000  -0.0000 =   0.615649
2010   0.688333 1.000  0.000 232.86  0.000000  -0.0000 =   0.688333
2011   0.573430 1.000  0.000 232.86  0.000000  -0.0000 =   0.573430
2012   0.585135 1.000  0.000 232.86  0.000000  -0.0000 =   0.585135
2013   0.611063 1.000  0.000 232.86  0.000000  -0.0000 =   0.611063
2014   0.675435 1.000  0.000 232.86  0.000000  -0.0000 =   0.675435
2015   0.813036 1.000  0.000 232.86  0.000000  -0.0000 =   0.813036
2016   0.951589 1.000  0.000 232.86  0.000000  -0.0000 =   0.951589
2017   0.836485 1.000  0.000 232.86  0.000000  -0.0000 =   0.836485
2018   0.770258 1.000  0.000 232.86  0.000000  -0.0000 =   0.770258

Columns:

1	Year
2	Original Temperature Anomaly
3	Global Coverage (1 = 100%)
4	Average Latitude
5	Average Elevation
6	Latitude Adjustment Needed
7	Elevation Adjustment Needed
8	=
9	Final Temperature Anomaly = Column 2 + Column 6 + Column 7

Now we plot final.csv

> echo 'set term png size 740,370;set grid;unset key;plot "final.csv" u 1:9 w lines lw 2 lc rgb "red"' | gnuplot > final.png

Latitude and Elevation Adjusted Temperature Anomaly

Reality sure looks a lot different once we properly adjust for shifting average latitude and elevation.

What are the 10 hottest years?

> cat final.csv | awk '{print $9" "$1}' | sort -rn | head

0.951589 2016
0.919349 1945
0.912231 1944
0.836485 2017
0.834285 1850
0.817560 1943
0.813036 2015
0.770258 2018
0.752998 1941
0.716632 1942

What’s the trend?

> sudo apt install gmt
> cat final.csv | awk '{print $1" "$9}' | gmt gmtregress -Fp -o5

0.0013332235319

From 1850 to 2019, we’ve been warming up by 0.0013 °C/year.

We’ve warmed up by 0.22 °C since 1850. I wouldn’t worry about it! A linear regression is inappropriate anyway. The data is obviously cyclical.

Summary: After adjusting Berkeley Earth’s data for latitude and elevation, we found no serious global warming.

Latitude and Elevation Adjusted Temperature Anomaly. Trend Slope = 0.00133°C/year.

Enjoy 🙂 -Zoe

---

Addendum:

Average Latitude Drift; Slope = -0.0327°/year

In case it wasn’t obvious: The so-called “global warming” is primarily due to incompleteness of data, and the average latitude drifting south towards equator in the data we do have.

Data Coverage, 0 to 1 = 0 to 100%

Mean Elevation, meters

We should rename Climate Change to Historic Mean Latitude Change.

Who’s with me?

---

Update 2020/01/03

A youtube channel operator claims that Berkeley already performed a latitude and elevation adjustment. This is absolutely bogus. He has since censored our discussion thread from the public. Let’s address this anyway…

In the Berkeley grid data , there are 16635 cells (out of 64800) that have complete data from 1850 to 2018. I compare these 16635 cells to Berkeley’s global summary (first chart on this post). Result:

There ought to have been a huge difference between 1850 and ~1980, if they really accounted for latitude. There is hardly a difference. It’s also painfully obvious that Berkeley stuffs the missing data with neighboring data and model interpolations – and the result is hardly different than just taking a plain area-weighted average of time-persistent locations, which have a VERY Northern bias.

Update 2020/01/04

Below is a very long term weather station in the Netherlands; one of the oldest continuous stations that exist.

What do you see? Uhuh

Before you accuse me of cherrypicking, consider that this cherry has been getting wrapped in more CO2 and it didn’t make a lick of difference. Why is that? Uhuh

Update 2020/01/17

More confirmation that what I’ve done here is correct, available here.