Global_warming_hiatus.gif(509 × 370 пиксела, големина на файла: 500 КБ, MIME-тип: image/gif, зациклен, 42 кадъра, 18 сек)

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Резюме

Описание
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.
Дата
Източник Собствена творба
Автор Physikinger
други версии German version File:Vermeindlicher Stillstand der globalen Erwaermung.gif
GIF развитие
InfoField
 
This plot was created with Matplotlib.
Изходен код
InfoField

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,     
    }
    
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)

Лицензиране

Аз, носителят на авторските права над тази творба, я публикувам тук под следния лиценз:
Creative Commons CC-Zero Този файл е достъпен под лиценза Creative Commons CC0 1.0 Универсален Посвещение на публичните домейни.
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.

Описания

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Apparent stagnation of global warming

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Някаква стойност без обект в Уикиданни

1 септември 2021

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Дата/ЧасМиникартинкаРазмерПотребителКоментар
текуща20:52, 17 април 2023Миникартинка на версията към 20:52, 17 април 2023509 × 370 (500 КБ)PhysikingerShorter red line
18:36, 13 април 2023Миникартинка на версията към 18:36, 13 април 2023509 × 370 (511 КБ)PhysikingerExtrapolation, Timing
21:01, 12 април 2023Миникартинка на версията към 21:01, 12 април 2023509 × 370 (510 КБ)PhysikingerUpdate 2022, single zoom transition
12:37, 7 септември 2021Миникартинка на версията към 12:37, 7 септември 2021509 × 370 (511 КБ)PhysikingerSmaller file size
22:09, 6 септември 2021Миникартинка на версията към 22:09, 6 септември 2021509 × 370 (617 КБ)PhysikingerFixed label, less colors
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