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Global_warming_hiatus.gif (509 × 370 pixels, file size: 500 KB, MIME type: image/gif, looped, 42 frames, 18 s)

Summary

Description
English: By selecting or cherry-picking data, the trend of global warming appears to mistakenly stop, as in the period from 1998 to 2012, which is actually a random contrary fluctuation.
Date
Source Own work
Author Physikinger
Other versions German version File:Vermeindlicher Stillstand der globalen Erwaermung.gif
GIF development
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This plot was created with Matplotlib.
Source code
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Python code

# This source code is public domain

import numpy
import matplotlib.pyplot as plt
import imageio

year_T = {
    # https://data.giss.nasa.gov/gistemp/tabledata_v4/GLB.Ts+dSST.txt
    # GLOBAL Land-Ocean Temperature Index in 0.01 degrees Celsius   base period: 1951-1980
    # sources:  GHCN-v4 1880-07/2021 + SST: ERSST v5 1880-07/2021
    # using elimination of outliers and homogeneity adjustment
    # Divide by 100 to get changes in degrees Celsius (deg-C).
    # Year  J-D (annual mean Temperature Jan to Dec)
    1880: -16, 1881:  -8, 1882: -11, 1883: -17, 1884: -28,
    1885: -33, 1886: -31, 1887: -36, 1888: -17, 1889: -10,
    1890: -35, 1891: -22, 1892: -27, 1893: -31, 1894: -30,
    1895: -22, 1896: -11, 1897: -11, 1898: -27, 1899: -17,
    1900:  -8, 1901: -15, 1902: -28, 1903: -37, 1904: -47,
    1905: -26, 1906: -22, 1907: -38, 1908: -43, 1909: -48,
    1910: -43, 1911: -44, 1912: -36, 1913: -34, 1914: -15,
    1915: -14, 1916: -36, 1917: -46, 1918: -30, 1919: -28,
    1920: -27, 1921: -19, 1922: -29, 1923: -27, 1924: -27,
    1925: -22, 1926: -11, 1927: -22, 1928: -20, 1929: -36,
    1930: -16, 1931:  -9, 1932: -16, 1933: -29, 1934: -13,
    1935: -20, 1936: -15, 1937:  -3, 1938:   0, 1939:  -2,
    1940:  13, 1941:  19, 1942:   7, 1943:   9, 1944:  20,
    1945:   9, 1946:  -7, 1947:  -3, 1948: -11, 1949: -11,
    1950: -17, 1951:  -7, 1952:   1, 1953:   8, 1954: -13,
    1955: -14, 1956: -19, 1957:   5, 1958:   6, 1959:   3,
    1960:  -3, 1961:   6, 1962:   3, 1963:   5, 1964: -20,
    1965: -11, 1966:  -6, 1967:  -2, 1968:  -8, 1969:   5,
    1970:   3, 1971:  -8, 1972:   1, 1973:  16, 1974:  -7,
    1975:  -1, 1976: -10, 1977:  18, 1978:   7, 1979:  16,
    1980:  26, 1981:  32, 1982:  14, 1983:  31, 1984:  16,
    1985:  12, 1986:  18, 1987:  32, 1988:  39, 1989:  27,
    1990:  45, 1991:  40, 1992:  22, 1993:  23, 1994:  31,
    1995:  45, 1996:  33, 1997:  46, 1998:  61, 1999:  38,
    2000:  39, 2001:  53, 2002:  63, 2003:  62, 2004:  53,
    2005:  67, 2006:  63, 2007:  66, 2008:  54, 2009:  65,
    2010:  72, 2011:  61, 2012:  65, 2013:  67, 2014:  74,
    2015:  90, 2016: 101, 2017:  92, 2018:  85, 2019:  97,
    2020: 102, 2021:  85, 2022:  89, 2023: 117
    }
    
x, y = (numpy.array(list(x()), dtype='d') for x in (year_T.keys, year_T.values))
y = y / 100

xMinFocus, xMaxFocus = 1998, 2012
i0 = x.tolist().index(xMinFocus)
i1 = x.tolist().index(xMaxFocus) + 1

nPoly = 4
phi = numpy.array([x**i for i in range(nPoly)])
A = phi @ phi.T
b = phi @ y
c = numpy.linalg.solve(A, b)
yPoly = c @ phi

phiHist = phi[:,:i1]
A = phiHist @ phiHist.T
b = phiHist @ y[:i1]
c = numpy.linalg.solve(A, b)
yPolyHist = c @ phi

nPoly = 3
phiF = phi[:nPoly,i0:i1]
A = phiF @ phiF.T
b = phiF @ y[i0:i1]
c = numpy.linalg.solve(A, b)
yPolyFocus = c @ phi[:nPoly]
yMinTotal, yMaxTotal = numpy.min(y) - 0.02, numpy.max(y) + 0.02
xMinTotal, xMaxTotal = numpy.min(x), numpy.max(x)
yMinFocus, yMaxFocus = numpy.min(y[i0:i1]) - 0.02, numpy.max(y[i0:i1]) + 0.02
plt.xlim(xMinFocus-0.1, xMaxFocus+0.1)

# Frame-Parameter:
#   t: Frame duration
#   trans1: transition 0 to 1 towards full time frame
#   trans2: transition 0 to 1 towards full data set
#   showTrend: Trend (0: None, 1: Zoom, 2: full history, 3: full time frame)

parameters = [ # (t, trans1, trans2, showTrend)
    (1, 0.0, 0.0, 0),
    (4, 0.0, 0.0, 1),
    *[(0.1, t**2, 0.0, 1) for t in numpy.linspace(0,1,25)],
    (1.0, 1.0, 0.0, 1),
    (0.5, 1.0, 0.0, 0),
    (1, 1.0, 0.0, 2),
    *[(0.1, 1.0, t,2) for t in numpy.linspace(0,1,10)],
    (0.5, 1.0, 1.0, 2),
    (6, 1.0, 1.0, 3),
    ]

images = []
duration = []
for t, trans1, trans2, showTrend in parameters:
    duration.append(t)
    zoom = 4*(1-trans1) + 1*trans1
    fig = plt.figure(figsize=(5.1,3.7), dpi=100)
    plt.rc('axes', titlesize=14, labelsize=12)
    plt.rc('xtick', labelsize=11)
    plt.rc('ytick', labelsize=11)
    plt.rc('legend', fontsize=16)
    if showTrend == 1: plt.plot(x[i0-15:], yPolyFocus[i0-15:], 'r--', label='Trend')
    if showTrend == 2: plt.plot(x, yPolyHist, 'b--', label='Trend')
    if showTrend == 3: plt.plot(x, yPoly, 'b--', label='Trend')
    iMax = int(i1 + trans2*(len(x)-i1))
    plt.plot(x[:iMax], y[:iMax], 'C0.-', alpha=0.8, linewidth=0.8*zoom, markersize=6*zoom)
    plt.plot(x[i0:i1], y[i0:i1], 'C3.-', linewidth=0.805*zoom, markersize=6.05*zoom)
    plt.grid(True, alpha=0.7)
    yMax = yMaxFocus + trans1*(yMaxTotal-yMaxFocus)
    xMax = xMaxFocus + trans1*(xMaxTotal-xMaxFocus)
    xMin = xMinFocus*(1-trans1) + xMinTotal*trans1
    plt.xlim(xMin-0.1, xMax+0.1+1*trans1)
    plt.ylim(yMinFocus*(1-trans1) + yMinTotal*trans1, yMaxFocus*(1-trans1) + yMax*trans1+0.03*trans1)
    plt.text(0.02, 0.89, '%i - %i'%(xMin, x[iMax-1]), transform=plt.gca().transAxes, fontsize=20)
    plt.title('Global Warming Hiatus')
    plt.xlabel('Year')
    plt.ylabel('Relative Global Temperature (°C)')
    plt.gca().yaxis.set_label_coords(-0.13, 0.5)
    if showTrend: leg = plt.legend(frameon=False, loc='lower right')
    fig.subplots_adjust(
        top=0.9,
        bottom=0.13,
        left=0.15,
        right=0.95,
        hspace=0.2,
        wspace=0.2
    )
    fig.canvas.draw()
    s, (width, height) = fig.canvas.print_to_buffer()
    images.append(numpy.array(list(s), numpy.uint8).reshape((height, width, 4)))
    fig.clf()
    plt.close('all')

# Save GIF animation
fileOut = 'Global_warming_hiatus.gif'
imageio.mimsave(fileOut, images, duration=duration)

# Optimize GIF size
from pygifsicle import optimize
optimize(fileOut, colors=20)

Licensing

I, the copyright holder of this work, hereby publish it under the following license:
Creative Commons CC-Zero This file is made available under the Creative Commons CC0 1.0 Universal Public Domain Dedication.
The person who associated a work with this deed has dedicated the work to the public domain by waiving all of their rights to the work worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law. You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission.

Captions

Apparent stagnation of global warming

Items portrayed in this file

depicts

1 September 2021

image/gif

File history

Click on a date/time to view the file as it appeared at that time.

Date/TimeThumbnailDimensionsUserComment
current20:52, 17 April 2023Thumbnail for version as of 20:52, 17 April 2023509 × 370 (500 KB)PhysikingerShorter red line
18:36, 13 April 2023Thumbnail for version as of 18:36, 13 April 2023509 × 370 (511 KB)PhysikingerExtrapolation, Timing
21:01, 12 April 2023Thumbnail for version as of 21:01, 12 April 2023509 × 370 (510 KB)PhysikingerUpdate 2022, single zoom transition
12:37, 7 September 2021Thumbnail for version as of 12:37, 7 September 2021509 × 370 (511 KB)PhysikingerSmaller file size
22:09, 6 September 2021Thumbnail for version as of 22:09, 6 September 2021509 × 370 (617 KB)PhysikingerFixed label, less colors
19:01, 1 September 2021Thumbnail for version as of 19:01, 1 September 2021509 × 370 (884 KB)PhysikingerUploaded own work with UploadWizard

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