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Global Warming and Cumulative CO2

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  • Nowarski Engineering

Abstract and Figures

This publication analysis a correlation between the cumulative CO2 emissions and the global surface temperature change. The change in global surface temperature was calculated as the difference in the two most recent 31 years neighboring periods, and the change in the cumulative CO2 emissions is the difference between the actual values in the centers of the periods. This approach resulted in 0.000556°C/GtCO2 for the year 2000 and 0.000745°C/GtCO2 for the year 2021.
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Global Warming and Cumulative CO2
Joseph Nowarski, M.Sc., ME – Energy Conservation Expert
Version 1.1.1, 6 June 2022
DOI:10.5281/zenodo.6619550
all versions DOI:10.5281/zenodo.6619549
Keywords: Climate Change
Global Warming
Cumulative CO2
Global Warming forecast
Global temperature forecast
Abstract
This publication analysis a correlation between the cumulative CO2 emissions and
the global surface temperature change.
The change in global surface temperature was calculated as the difference in the
two most recent 31 years neighboring periods, and the change in the cumulative
CO2 emissions is the difference between the actual values in the centers of the
periods.
This approach resulted in 0.000556°C/GtCO2 for the year 2000 and
0.000745°C/GtCO2 for the year 2021.
Glossary
ACCO2 acceleration of change in cumulative CO2 emissions, tCO2/y2 (ton
CO2 per year per year)
Ave average
Global Warming and Cumulative CO2 v1.1.1 - Joseph Nowarski
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CCO2 global cumulative CO2 emissions according to publication [1] [2], CO2
emissions produced from fossil fuels and cement production only –
land use change is not included
CO2 emissions of Carbon Dioxide, CO2
CO2GW relation between global cumulative CO2 emissions according to
publication [1] [2], and change in global surface temperature as in
Formula 1, °C/GtCO2
dCCO2 change in CCO2 between the centers of two periods as in Formula 1,
GtCO2
dGW change in average GW between two most recent 31 years periods as
in Formula 1, °C
GtCO2 Giga-ton of CO2, 109 ton, 10^9 ton, 1,000,000,000 ton of CO2
GWA Global Warming Acceleration, annual change in the global warming
rate, °C/y2 [3]
GWR Global Warming Rate – average change in global surface
temperature per year in the trendline period, °C/y [3]
OWID Our World in Data – Internet site [1] [2]
Ref reference
tCO2 ton CO2
VCCO2 velocity of change in cumulative CO2 emissions, tCO2/y
VCO2GW velocity of change in CO2GW, °C/(GtCO2,y)
Global Warming and Cumulative CO2 v1.1.1 - Joseph Nowarski
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Cumulative CO2
The annual changes in cumulative CO2 were calculated in the publication
Global Warming: Velocity and Acceleration of Change in Cumulative CO2
Emissions” [3] based on publications [1] [2].
Table 1 - Database of global cumulative CO2 emissions [1] [2]
Source of data OWID
Reference [1] [2]
Baseline year 1749
From year 1750
To year 2020
Period, years 271
CO2 from fossil fuels Yes
CO2 from cement production Yes
CO2 from other sources No
Other GHG No
Land use change No
Units ton CO2
Resolution 1 ton CO2/y
The database is from publication [1] [2], CO2 emissions produced from fossil fuels
and cement production only – land use change is not included.
Chart 1 - Annual change in cumulative CO2 emissions [GtCO2/y] [3]
0
5
10
15
20
25
30
35
40
1750
1770
1790
1810
1830
1850
1870
1890
1910
1930
1950
1970
1990
2010
The change in 2019 was +36.70 GtCO2/y and in 2020 +34.81 GtCO2/y.
Global Warming and Cumulative CO2 v1.1.1 - Joseph Nowarski
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Chart 2 - Velocity of change in cumulative CO2 emissions, VCCO2
[GtCO2/y] [3]
0
5
10
15
20
25
30
35
40
1755
1765
1775
1785
1795
1805
1815
1825
1835
1845
1855
1865
1875
1885
1895
1905
1915
1925
1935
1945
1955
1965
1975
1985
1995
2005
2015
Axis x is the center of the 11 years period applied for the calculation
The average change in cumulative CO2 emissions in the period 1990-2020 is 0.559
GtCO2/y.
Chart 3 - Acceleration of change in cumulative CO2 emissions, ACCO2
[GtCO2/y2], [Giga-ton CO2 per year per year] [3]
y = 0.020664973607x - 0.139577412972
-0.1
0.0
0.1
0.2
0.3
0.4
0.5
0.6
1765
1775
1785
1795
1805
1815
1825
1835
1845
1855
1865
1875
1885
1895
1905
1915
1925
1935
1945
1955
1965
1975
1985
1995
2005
Axis x is the center of the trendline period (2005 is the center of the 1990-2020 trendline period)
Global Warming and Cumulative CO2 v1.1.1 - Joseph Nowarski
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Global Surface Temperature Changes
The dataset of global surface temperature changes for land and ocean
converted to 1850-1900 baseline is publicly available in publication [9]. The dataset
is based on NASA [4] [5], NOAA [6], and Berkley Earth [7] [8].
Chart 4 - Trendlines, land+ocean, 1850-1900 baseline [°C] [10]
-0.5
-0.3
-0.1
0.1
0.3
0.5
0.7
0.9
1.1
1.3
1.5
1850
1860
1870
1880
1890
1900
1910
1920
1930
1940
1950
1960
1970
1980
1990
2000
2010
2020
Ave TL1 TL2 TL3 TL4
Ave average of all databases [°C]
Chart 5 - GWR – Global Warming Rate, land+ocean [°C/y] [10]
-0.005
0.000
0.005
0.010
0.015
0.020
1880 1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1991
Axis x is the center of the 61 years trendline period
Global Warming and Cumulative CO2 v1.1.1 - Joseph Nowarski
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Chart 6 - GWA - Global Warming Acceleration, land+ocean [°C/y2]
[10]
TL(GWA) = 0.000032352964 x - 0.000041422880
-0.0002
-0.0001
0.0000
0.0001
0.0002
0.0003
0.0004
0.0005
0.0006
1920
1930
1940
1950
1960
1970
1980
1990
2000
2010
2020
Axis x is the end of the 61 years trendline period
Correlation between Cumulative CO2 Emissions and Global Temperature
Formula 1 - CO2 to global warming, CO2GW, average GW in two
31 years periods, and CCO2 in the center of the periods
CO2GW= dGW / dCCO2
CO2GW relation between global cumulative CO2 emissions according
to publication [1] [2], CCO2, and the change in global surface
temperature, GW, °C/GtCO2
dGW change in average GW between two 31 years periods, °C
dCCO2 change in CCO2 between the centers of two periods, GtCO2
Two most recent 31 neighboring periods were selected in this work for the
determination of CO2GW: 1961-1991 and 1991-2021.
Table 2 - Application of Formula 1 for the year 2000
1940-1970 1970-2000 Δ
Center year 1955 1985
Ave GW °C +0.307 +0.548 +0.241
CCO2 GtCO2 264.04 698.46 434.42
CO2GW °C/GtCO2 0.000556
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Table 3 - Application of Formula 1 for the year 2021
1961-1991 1991-2021 Δ
Center year 1976 2006
Ave GW °C +0.425 +0.938 +0.513
CCO2 GtCO2 524.92 1,212.72 687.80
CO2GW °C/GtCO2 0.000745
CO2GW = 0.000745°C/GtCO2
Table 4 - Velocity of change in CO2GW, VCO2GW [°C/(GtCO2,y)]
Δ
Center of Period year 1985 2006
21
CO2GW °C/GtCO2 0.000556 0.000745
+0.000190
VCO2GW °C/(GtCO2,y) +0.000009
References
1. Hannah Ritchie, Max Roser, Edouard Mathieu, Bobbie Macdonald and
Pablo Rosado - Data on CO and Greenhouse Gas Emissions by Our World
in Data
https://github.com/owid/co2-data#data-on-co2-and-greenhouse-gas-
emissions-by-our-world-in-data
2. Our World in Data, Cumulative CO emissions, 2020
https://ourworldindata.org/grapher/cumulative-co-emissions
3. Global Warming: Velocity and Acceleration of Change in Cumulative CO2
Emissions version 2.2.1 – Joseph Nowarski, DOI:10.5281/zenodo.6617814
Global Warming and Cumulative CO2 v1.1.1 - Joseph Nowarski
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4. GISTEMP Team, 2022: GISS Surface Temperature Analysis (GISTEMP), version
4. NASA Goddard Institute for Space Studies. Dataset accessed 2022-02-05
at https://data.giss.nasa.gov/gistemp
5. Lenssen, N., G. Schmidt, J. Hansen, M. Menne, A. Persin, R. Ruedy, and D.
Zyss, 2019: Improvements in the GISTEMP uncertainty model. J. Geophys.
Res. Atmos., 124, no. 12, 6307-6326, doi:10.1029/2018JD029522.
6. NOAA National Centers for Environmental information, Climate at a Glance:
Global Time Series, published February 2022, retrieved on March 9, 2022
from https://www.ncdc.noaa.gov/cag/
7. Berkeley Earth - Global Temperature Report for 2021
http://berkeleyearth.org/global-temperature-report-for-2021/
8. Rohde, R. A. and Hausfather, Z.: The Berkeley Earth Land/Ocean
Temperature Record, Earth Syst. Sci. Data, 12, 3469-3479,
https://doi.org/10.5194/essd-12-3469-2020, 2020.
9. Global Surface Temperature Changes Datasets Converted to 1850-1900
Baseline v1.1.2 – Joseph Nowarski, DOI:10.5281/zenodo.6461153
10. Global Warming Acceleration v1.2.1 - Joseph Nowarski,
DOI:10.5281/zenodo.6616928
* * *
ResearchGate has not been able to resolve any citations for this publication.
Data
Full-text available
Changes in this version: added original baselines data, added formula for conversion from the original baseline to 1850-1900 baseline, including relevant conversion factor.
Article
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A global land–ocean temperature record has been created by combining the Berkeley Earth monthly land temperature field with spatially kriged version of the HadSST3 dataset. This combined product spans the period from 1850 to present and covers the majority of the Earth's surface: approximately 57 % in 1850, 75 % in 1880, 95 % in 1960, and 99.9 % by 2015. It includes average temperatures in 1∘×1∘ lat–long grid cells for each month when available. It provides a global mean temperature record quite similar to records from Hadley's HadCRUT4, NASA's GISTEMP, NOAA's GlobalTemp, and Cowtan and Way and provides a spatially complete and homogeneous temperature field. Two versions of the record are provided, treating areas with sea ice cover as either air temperature over sea ice or sea surface temperature under sea ice, the former being preferred for most applications. The choice of how to assess the temperature of areas with sea ice coverage has a notable impact on global anomalies over past decades due to rapid warming of air temperatures in the Arctic. Accounting for rapid warming of Arctic air suggests ∼ 0.1 ∘C additional global-average temperature rise since the 19th century than temperature series that do not capture the changes in the Arctic. Updated versions of this dataset will be presented each month at the Berkeley Earth website (http://berkeleyearth.org/data/, last access: November 2020), and a convenience copy of the version discussed in this paper has been archived and is freely available at https://doi.org/10.5281/zenodo.3634713 (Rohde and Hausfather, 2020).
Article
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We outline a new and improved uncertainty analysis for the Goddard Institute for Space Studies Surface Temperature product version 4 (GISTEMP v4). Historical spatial variations in surface temperature anomalies are derived from historical weather station data and ocean data from ships, buoys, and other sensors. Uncertainties arise from measurement uncertainty, changes in spatial coverage of the station record, and systematic biases due to technology shifts and land cover changes. Previously published uncertainty estimates for GISTEMP included only the effect of incomplete station coverage. Here, we update this term using currently available spatial distributions of source data, state‐of‐the‐art reanalyses, and incorporate independently derived estimates for ocean data processing, station homogenization, and other structural biases. The resulting 95% uncertainties are near 0.05 °C in the global annual mean for the last 50 years and increase going back further in time reaching 0.15 °C in 1880. In addition, we quantify the benefits and inherent uncertainty due to the GISTEMP interpolation and averaging method. We use the total uncertainties to estimate the probability for each record year in the GISTEMP to actually be the true record year (to that date) and conclude with 87% likelihood that 2016 was indeed the hottest year of the instrumental period (so far).
Bobbie Macdonald and Pablo Rosado -Data on CO₂ and Greenhouse Gas Emissions by Our World in Data
  • Hannah Ritchie
  • Max Roser
  • Edouard Mathieu
Hannah Ritchie, Max Roser, Edouard Mathieu, Bobbie Macdonald and Pablo Rosado -Data on CO₂ and Greenhouse Gas Emissions by Our World in Data https://github.com/owid/co2-data#data-on-co2-and-greenhouse-gasemissions-by-our-world-in-data
2022: GISS Surface Temperature Analysis (GISTEMP), version 4. NASA Goddard Institute for Space Studies
  • Gistemp Team
GISTEMP Team, 2022: GISS Surface Temperature Analysis (GISTEMP), version 4. NASA Goddard Institute for Space Studies. Dataset accessed 2022-02-05 at https://data.giss.nasa.gov/gistemp
Improvements in the GISTEMP uncertainty model
  • Zyss
Zyss, 2019: Improvements in the GISTEMP uncertainty model. J. Geophys.