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Global Warming Online Universal Baselines Converter

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This publication includes details regarding the online converter of global warming baselines "Global Warming Online Baselines Converter, °C" available on the Internet site nowagreen.com/globalwarming. This converter displays the conversion factor from any period to any period in the range 1850-2021 for land+ocean, 1880-2021 for ocean-only, or 1750-2021 for land-only.
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Global Warming Online Universal Baselines Converter
Joseph Nowarski, M.Sc., ME – Energy Conservation Expert
Version 1.1.1, 18 April 2022
DOI:10.5281/zenodo.6467315
Abstract
This publication includes details regarding the online converter of global warming
baselines “Global Warming Online Baselines Converter, °C” available on the
Internet site nowagreen.com/globalwarming.
This converter displays the conversion factor from any period to any period in the
range 1850-2021 for land+ocean, 1880-2021 for ocean-only, or 1750-2021 for land-
only.
Glossary
Ave average
BL baseline
CF conversion factor between baselines or reference periods
DB dataset, database
LBL Berkeley Earth (Lawrence Berkeley Laboratory)
Units
The temperature change unit in this work is °C.
Global Warming Online Universal Baselines Converter - Joseph Nowarski
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Global Warming Online Baselines Converter
The converter is on the Internet site “Global Warming Online Baselines Converter,
°C” nowagreen.com/globalwarming [13]. The converter is free and is very easy to
use.
It applies datasets converted to the 1850-1900 baseline.
Global Warming Databases
In this work “global warming” means annual changes in the global surface
temperature above some specific baseline. The baseline is usually indicated in
each database.
The converter [13] applies the following databases:
NASA [1] [2]
NOAA [3]
Berkeley Earth (LBL) [4] [5] [6] [7]
Global Warming Baselines
As described in publications [10] [12] it takes a lot of effort to find conversion
factors between various baselines applied by the main institutions involved in
global warming, datasets and research works.
The EU determines the “global temperature increase” according to the IPCC
baseline 1850-1900 [9].
IPCC Report 2011 [9] 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”.
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All main databases apply other baselines than IPCC, UN-FCCC and EU. NASA [1]
[2] and Berkeley Earth [4] [5] [6] apply the 1951-1980 baseline, and NOAA [3]
applies the 20th century baseline, 1901-2000.
Table 1 - Global warming databases, land+ocean [12]
NASA NOAA LBL
Reference [1] [2] [3] [4] [5]
Units °C °C °C
From 1880 1880 1850
To 2021 2020 2021
Years 142 141 172
Baseline (BL) 1951-1980 1901-2000 1951-1980
BL years 30 100 30
Decimal places 2 2 3
Ave in BL +0.0003 +0.0004 +0.0171
Table 2 - Global warming databases, land only [12]
NASA LBL
Reference [1] [2] [6]
Units °C °C
Records annual monthly
from 1880 1750
to 2021 2021
years 142 272
Baseline (BL) 1951-1980 1951-1980
BL years 30 30
Decimal places 2 3
Ave in BL +0.0010 +0.0010
Table 3 - Global warming databases, ocean only [12]
NASA
Reference [1] [2]
Units °C
Records annual
from 1880
to 2021
years 142
Baseline (BL) 1951-1980
BL years 30
Decimal places 2
Ave in BL +0.0007
As the ocean-only dataset is from 1880, it is not possible to convert the
temperature changes baselines for periods before 1880. In such a case it is
recommended to use the 1951-1980 baseline and the conversion factor from 1951-
1980 to 1850-1900 baseline, as detailed below.
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Conversion Factors between Main Datasets Baselines
The conversion factors between main datasets baselines were determined in the
publication “Global Warming Baselines Conversion Factors” [10].
Table 4 - Conversion factors to 1850-1900 baseline [°C] [10]
from BL: Land+Ocean Land Ocean
1850-1900 +0.00 +0.00 +0.00
1901-2000 +0.28 +0.49 +0.23
1951-1980 +0.31 +0.49 +0.29
CSV File
Table 5 - CSV file
Column A B C D
Year Land+Ocean Land only Ocean only
Baseline 1850-1900 1850-1900 1850-1900
Range 1750-2021 1850-2021 1750-2021 1880-2021
Units °C °C °C
Decimal places 3 3 2
Data Ave(NASA, NOAA, LBL) Ave(NASA, LBL) NASA
Source of data [1] [2] [3] [4] [5] [1] [2] [6] [7] [1] [2]
Determination of Average Error
Three 31 years periods were selected for the determination of errors between 1880
and 2020, based on the absolute difference between the specific datasets (NASA,
NOAA and LBL) and the averages of all of them.
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Estimation of Error for Land+Ocean
Table 6 - Estimation of error for land+ocean [°C]
Period NASA NOAA LBL Ave Δ
[1] [2] [3] [4] [5] °C °C
1880-1910 0.055 0.027 -0.030 0.017 0.047
1935-1965 0.290 0.291 0.296 0.292 0.004
1990-2020 0.916 0.881 0.965 0.921 0.044
Δmax 0.047
Δave 0.032
Δ max absolute difference between the average and each dataset
Estimation of Error for Land Only
Table 7 - Estimation of error for land only [°C]
Period NASA LBL Ave Δ
[1] [2] [6] [7] °C °C
1880-1910 +0.086 +0.061 +0.074 0.013
1935-1965 +0.508 +0.477 +0.493 0.016
1990-2020 +1.397 +1.365 +1.381 0.016
Δmax 0.016
Δave 0.015
Δ max absolute difference between the average and each dataset
This work includes only one dataset for ocean-only: NASA [1] [2].
The maximum and average errors for ocean-only were calculated in the
publication “Global Warming Baselines Conversion Factors” [10].
Table 8 - Estimation of error for ocean only [10] [°C]
IPCC LBL Ave Δ
Reference [9] [4] [5] °C °C
CF +0.31 +0.27 +0.29 0.02
Average Errors
Table 9 - Average errors [°C]
Land+ocean °C 0.032
Land only °C 0.015
Ocean only °C 0.020
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References
1. 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
2. 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.
3. 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/
4. Berkeley Earth - Global Temperature Report for 2021
http://berkeleyearth.org/global-temperature-report-for-2021/
5. 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.
6. Berkeley Earth - Time Series Data, Land Only (1750 – Recent), Monthly
Average Temperature (annual summary)
http://berkeleyearth.org/data/
7. Global Surface Temperature Changes over Land Dataset – Joseph
Nowarski. DOI:10.5281/zenodo.6373255
8. European Commission, Climate Action, EU Action,
Climate strategies & targets, 2050 long-term strategy, 4 March 2020
https://ec.europa.eu/clima/eu-action/climate-strategies-targets/2050-long-
term-strategy_en
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9. 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.
Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy,
J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou
(eds.)]. Cambridge University Press. In Press.
10. Global Warming Baselines Conversion Factors - Joseph Nowarski.
DOI:10.5281/zenodo.6373058
11. Global Surface Temperature Changes Datasets Converted to 1850-1900
Baseline - Joseph Nowarski. DOI:10.5281/zenodo.6386191
12. Global Warming Datasets Converted to 1850-1900 Baseline - Joseph
Nowarski. DOI:10.5281/zenodo.6386179
13. Global Warming Online Baselines Converter, °C – Joseph Nowarski
https://nowagreen.com/globalwarming
* * *
ResearchGate has not been able to resolve any citations for this publication.
Global Surface Temperature Changes Datasets Converted to 1850-1900 Baseline
Data
Full-text available
  • Mar 2022
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.
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The Berkeley Earth Land/Ocean Temperature Record
Article
Full-text available
  • Dec 2020
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 10.5281/zenodo.3634713 (Rohde and Hausfather, 2020).
View
Improvements in the GISTEMP Uncertainty Model
Article
Full-text available
  • Jun 2019
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).
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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
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.