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Global Warming Datasets 1-2024

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Abstract and Figures

This work describes the global warming datasets in the period 1-2024. The data for the period 1-1850 are from paleoclimate records and are used for determination of global warming in the last 2,000 years. The data for the 1850-2024 period are based on directly measured records. This work extends also the lower limit of the global warming over land and global warming over the ocean datasets from 1850 to 1750. The original data are according to various baselines and were converted in this work to the uniform "preindustrial" 1850-1900 baseline. The final dataset of global warming in the 1-2024 period based on this work is available on the site nowagreen.com.
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Global Warming Datasets 1-2024
Joseph Nowarski, M.Sc., ME – Energy Conservation Expert
Version 1.1.1, 12 March 2025
DOI:10.5281/zenodo.15013054
all versions DOI:10.5281/zenodo.15013053
Abstract
This work describes the global warming datasets in the period 1-2024.
The data for the period 1-1850 are from paleoclimate records and are used for
determination of global warming in the last 2,000 years.
The data for the 1850-2024 period are based on directly measured records.
This work extends also the lower limit of the global warming over land and global
warming over the ocean datasets from 1850 to 1750.
The original data are according to various baselines and were converted in this
work to the uniform “preindustrial” 1850-1900 baseline.
The final dataset of global warming in the 1-2024 period based on this work is
available on the site nowagreen.com.
Global Warming Datasets 1-2024 – Joseph Nowarski
2/31
Glossary
Amp amplitude of data around trendline, °C
Ave Average, °C
BL baseline of Global Warming data
CF Conversion Factor across baselines, °C
CF(pBL) conversion Factor to 1850-1900 preindustrial baseline, °C
GW Global Warming, global surface temperature of land+ocean, °C
above the 1850-1900 baseline
GWL global surface temperature over land only, °C above the 1850-1900
baseline
GWO global surface temperature over the ocean only, °C above the 1850-
1900 baseline
miniAmp dataset with reduced amplitude
Paleo Global Warming dataset based on paleoclimate records in the last
2,000 years [1] [2]
pBL global warming data above 1850-1900 preindustrial period baseline
Ref reference
Thermo thermal measurements for determination of global warming using
thermometers and satellites (after 1750)
TL trendline
Global Warming Baseline and Units
All results of calculations in this work are in °C above the preindustrial 1850-1900
baseline (pBL).
Global Warming Datasets 1-2024 – Joseph Nowarski
3/31
Datasets Conversion to the Preindustrial Baseline 1850-1900
Most datasets include the 1850-1900 period which allows direct determination of
the conversion factor for each dataset.
NASA dataset starts after 1850 and cannot be directly converted to the 1850-1900
baseline. The NASA dataset is above the 1951-1980 baseline.
The NASA conversion factor will be determined using the averages of the 1951-
1980 period of other converted datasets.
Table 1 - Global Warming GW (Land+Ocean) Datasets
Table 2 - Global Warming GW (Land+Ocean) datasets considered in this work
Ref ID 1-1850 1850-1880 1880-1950 1950-2000 2000-2014 2014-2024
Paleo [1] [2] DB11
Thermo [1] [2] DB12
NASA [3] [4] DB13
NOAA [5] DB14
LBL [6] [7] DB15
IPCC [8] DB16
Ave * DB17
* this publication
Paleo Database (DB11) 1-2000 for GW (Land+Ocean)
This dataset is based on paleoclimatology.
Paleoclimate
From IPCC [1] wg1, Section 6.2.1.2 and 6.2.1.3:
”Perhaps one of the most important aspects of modern palaeoclimatology is that
it is possible to derive time series of atmospheric trace gases and aerosols for the
period from about 650 kyr to the present from air trapped in polar ice and from
the ice itself.”
Global Warming Datasets 1-2024 – Joseph Nowarski
4/31
“Tree ring records are generally the most accurate, and are accurate to the year,
or season of a year (even back thousands of years). There are a host of other
proxies that also have annual layers or bands (e.g., corals, varved sediments, some
cave deposits, some ice cores) but the age models associated with these are not
always exact to a specific year.”
“There continue to be significant advances in radiometric dating. Each
radiometric system has ranges over which the system is useful, and palaeoclimatic
studies almost always publish analytical uncertainties. Because there can be
additional uncertainties, methods have been developed for checking assumptions
and cross verifying with independent methods. For example, secular variations in
the radiocarbon clock over the last 12 kyr are well known, and fairly well
understood over the last 35 kyr. These variations, and the quality of the
radiocarbon clock, have both been well demonstrated via comparisons with age
models derived from precise tree ring and varved sediment records, as well as with
age determinations derived from independent radiometric systems such as
uranium series.”
Table 3 - DB11 - Paleo Database info [1] [2]
DB11 Paleo
Name Paleo
ID DB11
Reference [1] [2]
Units °C
Records annual
From 1
To 2000
Years 2,000
Baseline (BL) 1961-1990
BL years 30
Ave in BL -0.0008
Decimal places 4
CF(pBL) +0.3794
Global Warming Datasets 1-2024 – Joseph Nowarski
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Chart 1 - DB11 - Paleo dataset - Global Warming (Land +Ocean) 1-2000, °C
above pBL [1] [2]
-0.4
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
0
100
200
300
400
500
600
700
800
900
1000
1100
1200
1300
1400
1500
1600
1700
1800
1900
2000
Global Warming Datasets 1-2024 – Joseph Nowarski
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Thermo Database (DB12) 1850-2017 for GW (Land+Ocean)
Table 4 - DB12 - Thermo Database info [1] [2]
DB12 Thermo
Name Thermo
ID DB12
Reference [1] [2]
Units °C
Records annual
From 1850
To 2017
Years 168
Baseline (BL) 1961-1990
BL years 30
Ave in BL 0.0000
Decimal places 4
CF(pBL) +0.3536
Chart 2 - DB12 - Thermo dataset - Global Warming (Land+Ocean) 1850-2017, °C
above pBL [1] [2]
-0.4
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1850
1860
1870
1880
1890
1900
1910
1920
1930
1940
1950
1960
1970
1980
1990
2000
2010
Global Warming Datasets 1-2024 – Joseph Nowarski
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NASA Database (DB13) 1880-2024 for GW (Land+Ocean)
Table 5 - DB13 - NASA Database info [3] [4]
DB13 NASA
Name NASA
ID DB13
Reference [3] [4]
Units °C
Records annual
From 1880
To 2024
Years 145
Baseline (BL) 1951-1980
BL years 30
Ave in BL -0.0003
Decimal places 2
CF(pBL) +0.2807
Chart 3 - DB13 - NASA dataset - Global Warming (Land+Ocean) 1880-2024, °C
above pBL [3] [4]
-0.4
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
1880
1890
1900
1910
1920
1930
1940
1950
1960
1970
1980
1990
2000
2010
2020
Global Warming Datasets 1-2024 – Joseph Nowarski
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NOAA Database (DB14) 1850-2024 for GW (Land+Ocean)
Table 6 - DB14 - NOAA Database info [5]
DB14 NOAA
Name NOAA
ID DB14
Reference [5]
Units °C
Records annual
From 1850
To 2024
Years 175
Baseline (BL) 1901-2000
BL years 100
Ave in BL +0.0002
Decimal places 2
CF(pBL) +0.1704
Chart 4 - DB14 - NOAA dataset - Global Warming (Land+Ocean) 1850-2024, °C
above pBL [5]
-0.4
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1850
1860
1870
1880
1890
1900
1910
1920
1930
1940
1950
1960
1970
1980
1990
2000
2010
2020
Global Warming Datasets 1-2024 – Joseph Nowarski
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Berkley Earth (LBL) Database (DB15) 1850-2024 for GW (Land+Ocean)
Table 7 - DB15 - LBL Database info [6] [7]
DB15 Berkley Earth
Name LBL
ID DB15
Reference [6] [7]
Units °C
Records annual
From 1850
To 2024
Years 175
Baseline (BL) 1951-1980
BL years 30
Ave in BL +0.0174
Decimal places 3
CF(pBL) +0.3062
Chart 5 - DB15 – Berkley Earth (LBL) dataset - Global Warming (Land+Ocean)
1850-2024, °C above pBL [6] [7]
-0.5
0.0
0.5
1.0
1.5
2.0
1850
1860
1870
1880
1890
1900
1910
1920
1930
1940
1950
1960
1970
1980
1990
2000
2010
2020
Global Warming Datasets 1-2024 – Joseph Nowarski
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IPCC Database (DB16) 1950-2014 for GW (Land+Ocean)
Table 8 - DB16 - IPCC Database info [8]
DB16 IPCC
Name IPCC
ID DB16
Reference [8]
Units °C
Records annual
From 1950
To 2044
Years 95
Baseline (BL) 1850-1900
BL years 51
Ave in BL N/A
Decimal places 6
Chart 6 - DB16 – IPCC dataset - Global Warming (Land+Ocean) 1950-2014, °C
above pBL [8]
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1950
1960
1970
1980
1990
2000
2010
Global Warming Datasets 1-2024 – Joseph Nowarski
11/31
All Datasets for GW (Land+Ocean)
Chart 7 - All datasets - Global Warming (Land+Ocean) 1850-2024, °C above pBL
-0.5
0.0
0.5
1.0
1.5
2.0
1850
1860
1870
1880
1890
1900
1910
1920
1930
1940
1950
1960
1970
1980
1990
2000
2010
2020
Paleo Thermo NASA NOAA LBL IPCC
Chart 8 - DB17 Average dataset - Global Warming (Land+Ocean) 1850-2024, °C
above pBL
-0.5
0.0
0.5
1.0
1.5
2.0
1850
1860
1870
1880
1890
1900
1910
1920
1930
1940
1950
1960
1970
1980
1990
2000
2010
2020
Paleo Thermo NASA NOAA LBL IPCC Ave
Global Warming Datasets 1-2024 – Joseph Nowarski
12/31
Average Dataset (DB17) 1-2024 for GW (Land+Ocean)
The average dataset is based on the following datasets:
o Paleo DB11
o Thermo DB12
o NASA DB13
o NOAA DB14
o LBL DB15
o IPCC DB16
Chart 9 - DB17 Average dataset - Global Warming (Land+Ocean) 1-2024, °C
above pBL
-0.4
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
0
100
200
300
400
500
600
700
800
900
1000
1100
1200
1300
1400
1500
1600
1700
1800
1900
2000
Global Warming Datasets 1-2024 – Joseph Nowarski
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Chart 10 - DB17 Average dataset – 31 years moving average
-0.4
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
0
100
200
300
400
500
600
700
800
900
1000
1100
1200
1300
1400
1500
1600
1700
1800
1900
2000
The red line is related to the center of the moving average, for instance, the
average of the data between 1985 and 2015 is indicated in the year 2000.
Global Warming Datasets 1-2024 – Joseph Nowarski
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Global Warming over Land GWL Datasets
Table 9 - Global Warming over Land only GWL datasets considered in this work
Ref ID 1750-1850 1850-1880 1880-2024
NASA [3] [4] DB21
NOAA [5] DB22
LBL [6] [7] DB23
LBL miniAmp * DB24
Ave * DB25
* this publication
NASA Database (DB21) 1880-2024 for GWL (Land only)
Table 10 - DB21 - NASA GWL Database info [3] [4]
DB21 NASA
Name NASA
ID DB21
Reference [3] [4]
Units °C
Records annual
From 1880
To 2024
Years 145
Baseline (BL) 1951-1980
BL years 30
Ave in BL 0.0003
Decimal places 2
CF(pBL) +0.4428
Chart 11 - DB21 - NASA dataset - GWL (Land only) 1880-2024, °C above pBL [3]
[4]
-0.5
0.0
0.5
1.0
1.5
2.0
2.5
1880
1890
1900
1910
1920
1930
1940
1950
1960
1970
1980
1990
2000
2010
2020
Global Warming Datasets 1-2024 – Joseph Nowarski
15/31
NOAA Database (DB22) 1850-2024 for GWL (Land only)
Table 11 - DB22 - NOAA GWL Database info [5]
DB22 NOAA
Name NOAA
ID DB22
Reference [5]
Units °C
Records annual
From 1850
To 2024
Years 175
Baseline (BL) 1901-2000
BL years 100
Ave in BL 0.0000
Decimal places 2
CF(pBL) +0.4512
Chart 12 - DB22 - NOAA dataset - GWL (Land only) 1850-2024, °C above pBL [5]
-0.5
0.0
0.5
1.0
1.5
2.0
2.5
1850
1860
1870
1880
1890
1900
1910
1920
1930
1940
1950
1960
1970
1980
1990
2000
2010
2020
Global Warming Datasets 1-2024 – Joseph Nowarski
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Berkley Earth Database (DB23) 1750-2024 for GWL (Land only)
Table 12 - DB23 - LBL GWL Database info [6] [7]
DB23 Berkley Earth
Name LBL
ID DB23
Reference [6] [7]
Units °C
Records annual
From 1750
To 2024
Years 275
Baseline (BL) 1951-1980
BL years 30
Ave in BL 0.0000
Decimal places 3
CF(pBL) +0.4540
Chart 13 - DB23 - LBL dataset - GWL (Land only) 1750-2024, °C above pBL [6] [7]
-2.5
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
2.5
1750
1760
1770
1780
1790
1800
1810
1820
1830
1840
1850
1860
1870
1880
1890
1900
1910
1920
1930
1940
1950
1960
1970
1980
1990
2000
2010
2020
Global Warming Datasets 1-2024 – Joseph Nowarski
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LBL miniAmp Dataset (DB24) 1750-2024 for GWL (Land only)
The above chart of DB23 has very big amplitude in the 1750-1878 period.
The 1880-1930 period has much smaller amplitude.
The correction procedure will uniformly decrease the amplitude in the 1750-1880
period by the ratio of the average amplitudes in both periods.
Table 13 - Cubic trendline of DB23 in 1750-1930
y = 0.00000 00657 16612 x
3
+ 0.00000374 41309 06x
2
+ 0.0006212 938532 81x - 0.3167973 11183 706
-2.5
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
1750
1760
1770
1780
1790
1800
1810
1820
1830
1840
1850
1860
1870
1880
1890
1900
1910
1920
1930
Table 14 - Cubic trendline of DB23 in 1750-1930 period
a 0.000000226114691 x3
b -0.000056055010124 x2
c 0.006262266395394 x
d -0.422224482223104
Start 1749
Table 15 - Average amplitudes in 1750-1880 and 1880-1930 periods
Period Max Amp Ave Amp Max/Ave
Before correction
1750-1880 1.615 0.380 4.2
1880-1930 0.344 0.129 2.7
Period2/Period1 0.213 0.339
After correction
1750-1880 0.547 0.129 4.2
Global Warming Datasets 1-2024 – Joseph Nowarski
18/31
Chart 14 - miniAmp - reduced amplitude of LBL dataset in 1750-1880 - GWL
(Land only) °C above pBL [6] [7]
-2.5
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
2.5
1750
1760
1770
1780
1790
1800
1810
1820
1830
1840
1850
1860
1870
1880
1890
1900
1910
1920
1930
1940
1950
1960
1970
1980
1990
2000
2010
2020
LBL miniAmp Poly. (LBL)
Chart 15 - DB24 - LBL miniAmp dataset - GWL (Land only) 1750-2024, °C above
pBL
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
2.5
1750
1760
1770
1780
1790
1800
1810
1820
1830
1840
1850
1860
1870
1880
1890
1900
1910
1920
1930
1940
1950
1960
1970
1980
1990
2000
2010
2020
Global Warming Datasets 1-2024 – Joseph Nowarski
19/31
All Datasets for GWL (Land only)
Chart 16 - All datasets - GWL (Land only) 1750-2024, °C above pBL
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
2.5
1750
1760
1770
1780
1790
1800
1810
1820
1830
1840
1850
1860
1870
1880
1890
1900
1910
1920
1930
1940
1950
1960
1970
1980
1990
2000
2010
2020
NASA NOAA LBL miniAmp
The similarity of all the datasets in the 1880-2024 period is quite impressive
indicating also the correctness of baseline conversion factors.
Global Warming Datasets 1-2024 – Joseph Nowarski
20/31
Average Dataset (DB25) 1750-2024 for GWL (Land only)
The average dataset is based on the following datasets:
o NASA DB21
o NOAA DB22
o LBL miniAmp DB24
Chart 17 - DB25 Average dataset - GWL (Land only) cubic trendline 1750-2024,
°C above pBL
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
2.5
1750
1760
1770
1780
1790
1800
1810
1820
1830
1840
1850
1860
1870
1880
1890
1900
1910
1920
1930
1940
1950
1960
1970
1980
1990
2000
2010
2020
Chart 18 - DB25 Average dataset - GWL (Land only) moving average 31 years,
°C above pBL
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
2.5
1750
1760
1770
1780
1790
1800
1810
1820
1830
1840
1850
1860
1870
1880
1890
1900
1910
1920
1930
1940
1950
1960
1970
1980
1990
2000
2010
2020
Global Warming Datasets 1-2024 – Joseph Nowarski
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Global Warming over the Ocean GWO Datasets
Table 16 - Global Warming over the Land only GWO datasets considered in this
work
Ref ID 1750-1850 1850-1880 1880-2024
NASA [3] [4] DB31
NOAA [5] DB32
DB33 DB1+DB24 DB33
Ave * DB34
* this publication
NASA Database (DB31) 1880-2024 for GWO (Ocean only)
Table 17 - DB31 - NASA GWO Database info [3] [4]
DB31 NASA
Name NASA
ID DB31
Reference [3] [4]
Units °C
Records annual
From 1880
To 2024
Years 145
Baseline (BL) 1951-1980
BL years 30
Ave in BL 0.0007
Decimal places 2
CF(pBL) +0.0981
Global Warming Datasets 1-2024 – Joseph Nowarski
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Chart 19 - DB31 - NASA dataset - GWO (Ocean only) 1880-2024, °C above pBL
[3] [4]
-0.6
-0.4
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1880
1890
1900
1910
1920
1930
1940
1950
1960
1970
1980
1990
2000
2010
2020
Global Warming Datasets 1-2024 – Joseph Nowarski
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NOAA Database (DB32) 1850-2024 for GWO (Ocean only)
Table 18 - DB32 - NOAA GWO Database info [5]
DB32 NOAA
Name NOAA
ID DB32
Reference [5]
Units °C
Records annual
From 1850
To 2024
Years 175
Baseline (BL) 1901-2000
BL years 100
Ave in BL 0.0000
Decimal places 2
CF(pBL) +0.0441
Chart 20 - DB32 - NOAA dataset - GWO (Ocean only) 1850-2024, °C above pBL
[5]
-0.6
-0.4
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1850
1860
1870
1880
1890
1900
1910
1920
1930
1940
1950
1960
1970
1980
1990
2000
2010
2020
Global Warming Datasets 1-2024 – Joseph Nowarski
24/31
Global Warming over the Ocean in 1750-1850 (DB33)
Publication [9] includes formula for calculation of GW using GWL and GWO
according to land and ocean area.
Formula 1 - Calculation of GW using GWL and GWO according to
land and ocean area [9]
GW = GWL*AL + GWO*AO
GW Global Warming, global surface temperature above the 1850-1900
baseline, land+ocean, °C
GWL global surface temperature over the land only above the 1850-1900
baseline, °C
GWO global surface temperature over the ocean only, above the 1850-
1900 baseline, °C
AL global area of land, %
AO global area of the ocean, %
AL and AO are determined in the publication [9] as follows:
Based on the Global Warming data, the average land area (AL) in the period
1990-2021 was 31.18% of the total area of the Earth, and the ocean area (AO) was
68.82%.
Table 19 - Land area and ocean area [9]
Global Land Area AL 31.18%
Global Ocean Area AO 68.82%
The current publication includes data of GW and GWL for 1750-1850, which allows
calculations of GWO in this period applying Formula 1.
GWO = (GW - GWL*AL) / AO
Global Warming Datasets 1-2024 – Joseph Nowarski
25/31
Table 20 - Datasets applied for DB33 calculations
GW GWL
Name Paleo miniAmp
ID DB11 DB24
Ref [1] [2] *
BL 1850-1900 1850-1900
*this publication
Chart 21 - DB33 dataset - GWO (Ocean only) 1750-1850 calculated with Formula
1, °C above pBL
-1.0
-0.8
-0.6
-0.4
-0.2
0.0
0.2
0.4
0.6
1750
1760
1770
1780
1790
1800
1810
1820
1830
1840
1850
GW Paleo GWL miniAmp GWO DB33 Poly. (GWO DB33)
Global Warming Datasets 1-2024 – Joseph Nowarski
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All Datasets for GWO (Ocean only)
Chart 22 - All datasets - GWO (Ocean only) 1750-2024, °C above pBL
-0.6
-0.4
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1750
1760
1770
1780
1790
1800
1810
1820
1830
1840
1850
1860
1870
1880
1890
1900
1910
1920
1930
1940
1950
1960
1970
1980
1990
2000
2010
2020
NASA NOAA DB33 Formula 1
Like the GWL datasets, the GWO datasets show impressive similarity indicating also
the correctness of baseline conversion factors.
Average Dataset (DB34) 1750-2024 for GWO (Ocean only)
The average dataset Includes the following datasets:
o NASA DB31
o NOAA DB32
o DB33 calculated with Formula 1 based on DB11 (Paleo) and DB24 (miniAmp)
Global Warming Datasets 1-2024 – Joseph Nowarski
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Chart 23 - DB34 Average dataset - GWO (Ocean only) cubic trendline 1750-
2024, °C above pBL
-0.6
-0.4
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1750
1760
1770
1780
1790
1800
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Chart 24 - DB34 Average dataset - GWO (Ocean only) moving average 31
years, °C above pBL
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Global Warming Datasets 1-2024 – Joseph Nowarski
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Datasets GW, GWL, GWO
Chart 25 - GW, GWL, GWO, °C above pBL
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Chart 26 - Difference between GWL and GW 1750-2024, °C
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The linear and the cubic trendline show that the difference between GWL and GW
increases constantly, from -0.40°C in 1750 to +0.47°C in 2024, 0.00316°C per year.
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Availability of the GW, GWL, GWO datasets
GW, GWL, GWO datasets according to this work are publically available online on
site nowagreen.com
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References
1. IPCC - Changes in global surface temperature reconstructed from
paleoclimate archives (1–2000)
2. Kaufman, D., McKay, N., Routson, C. et al. Holocene global mean surface
temperature, a multi-method reconstruction approach. Sci Data 7, 201
(2020)
3. GISS Surface Temperature Analysis (GISTEMP), NASA Goddard Institute for
Space Studies
https://data.giss.nasa.gov/gistemp
4. 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
5. NOAA National Centers for Environmental Information - Climate at a Glance
https://www.ncei.noaa.gov/access/monitoring/climate-at-a-glance
6. Berkeley Earth – Global Warming - Global Temperature Data
https://berkeleyearth.org/data/
7. Rohde, R. A. and Hausfather, Z.: The Berkeley Earth Land/Ocean
Temperature Record, Earth Syst. Sci. Data, 12, 3469-3479, 2020,
https://doi.org/10.5194/essd-12-3469-2020
8. IPCC Sixth Assessment Report, Working Group 1
https://www.ipcc.ch/report/ar6/wg1/
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9. Global Warming Forecast over the Land and over the Ocean – Joseph
Nowarski, DOI:10.5281/zenodo.14581167
10. Global Warming Dataset Land+Ocean (1-2024), Land only (1750-2024),
Ocean only (1750-2024) – Joseph Nowarski, DOI:10.5281/zenodo.15013056
* * *

Supplementary resource (1)

Global Warming Dataset Land+Ocean (1-2024), Land only (1750-2024), Ocean only (1750-2024)
Data
March 2025
Joseph Nowarski
ResearchGate has not been able to resolve any citations for this publication.
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).
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Holocene global mean surface temperature, a multi-method reconstruction approach
Article
Full-text available
  • Jun 2020
An extensive new multi-proxy database of paleo-temperature time series (Temperature 12k) enables a more robust analysis of global mean surface temperature (GMST) and associated uncertainties than was previously available. We applied five different statistical methods to reconstruct the GMST of the past 12,000 years (Holocene). Each method used different approaches to averaging the globally distributed time series and to characterizing various sources of uncertainty, including proxy temperature, chronology and methodological choices. The results were aggregated to generate a multi-method ensemble of plausible GMST and latitudinal-zone temperature reconstructions with a realistic range of uncertainties. The warmest 200-year-long interval took place around 6500 years ago when GMST was 0.7 °C (0.3, 1.8) warmer than the 19th Century (median, 5th, 95th percentiles). Following the Holocene global thermal maximum, GMST cooled at an average rate −0.08 °C per 1000 years (−0.24, −0.05). The multi-method ensembles and the code used to generate them highlight the utility of the Temperature 12k database, and they are now available for future use by studies aimed at understanding Holocene evolution of the Earth system.
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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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