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Global Warming Datasets Converted to 1850-1900 Baseline

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Abstract

This publication includes global warming databases converted to the uniform baseline. The publication includes NASA, NOAA and Berkeley Earth databases of global surface temperature changes in the period 1850-2021 for land+ocean, 1750-2021 for land only and 1880-2021 for ocean only. The databases are converted to the 1850-1900 baseline showing minor differences between them. 61 years linear trendlines indicate constant increase of global warming reaching in 2021 0.017 °C/y for land+ocean, 0.026 °C/y for land only, and 0.012 °C/y for ocean only.
Global Warming Datasets Converted to 1850-1900 Baseline
Joseph Nowarski, M.Sc., ME – Energy Conservation Expert
Version 1.1.1, 25 March 2022
DOI:10.5281/zenodo.6386179
Abstract
This publication includes global warming databases converted to the uniform
baseline. The publication includes NASA, NOAA and Berkeley Earth databases of
global surface temperature changes in the period 1850-2021 for land+ocean,
1750-2021 for land only and 1880-2021 for ocean only. The databases are
converted to the 1850-1900 baseline showing minor differences between them. 61
years linear trendlines indicate constant increase of global warming reaching in
2021 0.017 °C/y for land+ocean, 0.026 °C/y for land only, and 0.012 °C/y for ocean
only.
Glossary
Ave average
BL baseline
CF conversion factor between baselines or reference periods
DB dataset, database
LBL Berkeley Earth, Lawrence Berkeley Laboratory
Ref reference
TL trendline
Global Warming Datasets Converted to 1850-1900 Baseline - Joseph Nowarski
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Units
The temperature change unit is °C.
Global warming rate, global warming per year is in °C/y.
Global Warming Databases
There are few databases of annual averages of global surface temperature
changes.
Each database applies its own baseline.
This work includes the following databases:
NASA [1] [2]
NOAA [3]
Berkeley Earth (LBL) [4] [5] [6] [11]
Global Warming Baselines
The EU aims to be climate-neutral by 2050 – an economy with net-zero greenhouse
gas emissions [7].
The EU policy is "in line with the Paris Agreement to keep the global temperature
increase to well below 2°C and pursue efforts to keep it to 1.5°C" [7].
The EU determines the “global temperature increase” according to the IPCC
baseline 1850-1900 [8].
IPCC Report 2011 [8] page 5 note 9: “The period 1850–1900 represents the earliest
period of sufficiently globally complete observations to estimate global surface
temperature and, consistent with AR5 and SR1.5, is used as an approximation for
pre-industrial conditions”.
Global Warming Datasets Converted to 1850-1900 Baseline - Joseph Nowarski
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However, all main databases apply other baselines than IPCC and EU. NASA [1] [2]
and Berkeley Earth [4] [5] [6] apply the 1951-1980 baseline, and NOAA[3] applies
the 20
th
century baseline, 1901-2000.
The NASA and NOA databases are from 1880 and not 1850.
It takes a lot of effort to find conversion factors between the IPCC 1850-1900
baseline and the main exiting databases, which have different baselines. The
example of such efforts may be a long blog on site Climate Lab Book - Defining
‘pre-industrial’ [10], concluded with the following statement of Mark Bassham:
IPCC AR5 (WG1 report), Figure 12.40 (page 1100) indicates a difference between
‘pre-industrial’ temperatures and the 1980-1999 Reference Period (non-standard,
only 20 years long instead of the usual 30) of EXACTLY 0.5°C. Note that ‘pre-
industrial’ means different things to different IPCC Chapter Lead Authors”.
Conversion to 1850-1900 Baseline
All data in this work are above the 1850-1900 baseline.
The publication “Global Warming Baselines Conversion Factors” [12] includes the
conversion factors to 1850-1900 baseline applying all 3 above baselines [1] [2] [3]
[4] [5] [6] [11] and other reference periods.
Table 1 - Conversion factors to 1850-1900 baseline [12] [°C]
  
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   
   
Publically available Excel file [13] includes all datasets applied in this work
converted to 1850-1900 baseline using the above conversion factors.
Global Warming Datasets Converted to 1850-1900 Baseline - Joseph Nowarski
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Linear Trendline Formula
Formula 1 - Linear trendline
T(y) = (y-n) * a + b
T(y) global surface temperature above 1850-1900 baseline in year y [°C]
n the year before the trendline start point, i.e., for trendline in period
1961-2022 n=1960
a, b parameters related to the linear function displayed on Excel trendline
chart and detailed for each dataset
Period Applied for Calculations of Trendlines
The period applied in this work for calculations of trendlines is 61 years. The display
period of the trendlines is usually different and depends on the crossing point
between the trendlines.
Global Surface Temperature Changes over Land and Ocean
Table 2 - Global warming databases, land+ocean
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Global Warming Datasets Converted to 1850-1900 Baseline - Joseph Nowarski
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Chart 1 - Global surface temperature changes above 1850-1900 baseline,
land+ocean [°C]
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Table 3 - Trendlines, land+ocean, 1850-1900 baseline, [°C]
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         
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The parameter “a” is the average global warming per year in the trendline period,
°C/y. For the last trendline 1961-2021 the global warming per year was 0.017 °C/y,
0.004 °C/y more than in the 1950-2010 trendline, 11 years before.
More about changes of global warming per year parameter can be found in the
publication “Acceleration of Global Warming” [14].
Global Warming Datasets Converted to 1850-1900 Baseline - Joseph Nowarski
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Chart 2 - Trendlines, land+ocean, 1850-1900 baseline [°C]
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Ave average of all databases [°C]
Global Surface Temperature Changes over Land
This work includes two databases of global surface temperature changes over
land:
NASA [1] [2]
Berkeley Earth (LBL) [6]
Table 4 - Global warming databases, land only
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Global Warming Datasets Converted to 1850-1900 Baseline - Joseph Nowarski
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Chart 3 - Global surface temperature changes above 1850-1900 baseline, land
only [°C]
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Table 5 - Trendlines, land only, 1850-1900 baseline [°C]
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Global Warming Datasets Converted to 1850-1900 Baseline - Joseph Nowarski
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Chart 4 - Trendlines, land only, 1850-1900 baseline [°C]
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For the last trendline 1961-2021, the global warming per year for land only was
0.026 °C/y, 0.006 °C/y more than in the 1950-2010 trendline, 11 years before.
Global Surface Temperature Changes over the Ocean
Table 6 - Global warming databases, ocean only
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Global Warming Datasets Converted to 1850-1900 Baseline - Joseph Nowarski
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Chart 5 - Global surface temperature changes above 1850-1900 baseline, ocean
only [°C]
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Table 7 - Trendlines, ocean only, 1850-1900 baseline [°C]
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In the case of ocean only, the trendline TL3 1950-2010 could not be applied to the
chart along with TL4 1961-2021, due to too small differences. However, the TL3 “a”
parameter can be compared to the TL4, indicating a change in the global
warming per year parameter.
Global Warming Datasets Converted to 1850-1900 Baseline - Joseph Nowarski
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Chart 6 - Trendlines, ocean only, 1850-1900 baseline [°C]
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For the last trendline 1961-2021 the global warming per year was 0.012 °C/y, 0.003
°C/y more than in the 1950-2010 trendline, 11 years before.
Global Warming Datasets Converted to 1850-1900 Baseline - Joseph Nowarski
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All Trendlines
Chart 7 - Trendlines 1850-1900 baseline [°C]
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Global Warming Datasets Converted to 1850-1900 Baseline - Joseph Nowarski
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References
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Zyss, 2019: Improvements in the GISTEMP uncertainty model. J. Geophys.
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http://berkeleyearth.org/global-temperature-report-for-2021/
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Temperature Record, Earth Syst. Sci. Data, 12, 3469-3479,
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Global Warming Datasets Converted to 1850-1900 Baseline - Joseph Nowarski
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13. Global Surface Temperature Changes Datasets Converted to 1850-1900
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Data
Full-text available
Global warming datasets converted to the uniform baseline. NASA, NOAA and Berkeley Earth datasets of global surface temperature changes in the period 1850-2021 for land+ocean, 1750-2021 for land only and 1880-2021 for ocean only, converted to the 1850-1900 baseline.
Article
Full-text available
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
Full-text available
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).
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.
Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change
  • V Masson-Delmotte
  • P Zhai
  • A Pirani
  • S L Connors
  • C Péan
  • S Berger
IPCC, 2021: Summary for Policymakers. In: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N.