Globally Averaged Marine Surface Monthly Mean CO2

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This dataset contains the Monthly Mean CO2 trends in globally distributed networks of air sampling sites from January 1st, 1980 until April 30th, 2018. It contains estimated data for every single month during the given period around the globe.

Categories: ,
Complexity

This dataset is sourced from the US Government’s Earth System Research Laboratory (ESRL), Global Monitoring Division (GMD). The study under discussion comprises of the Global Time series starting from 1980.

The Global Monitoring Division of National Oceanic and Atmospheric Administration (NOAA)/ESRL has measured carbon dioxide and other greenhouse gases for several decades at a globally distributed network of air sampling sites [Conway, 1994]. A global average is constructed by first fitting a smoothed curve as a function of time to each site, and then the smoothed value for each site is plotted as a function of latitude for 48 equal time steps per year. A global average is calculated from the latitude plot at each time step [Masarie, 1995].

Data are reported as a dry air mole fraction defined as the number of molecules of carbon dioxide divided by the number of all molecules in the air, including CO2 itself, after water vapor has been removed. The mole fraction is expressed as parts per million (ppm). For Example, 0.000400 is expressed as 400 ppm.

The NOAA ESRL Carbon Cycle Group computes global mean surface values using measurements of weekly air samples from the Cooperative Global Air Sampling Network [Conway et al., 1994; Dlugokencky et al., 1994; Novelli et al., 1992; Trolier et al., 1996]. Global values can be computed for nearly all trace gas species and stable isotopes routinely measured by ESRL and the University of Colorado INSTAAR. Here, a brief description of methodology for computing global mean surface values is illustrated using CO2.

The global estimate is based on measurements from a subset of network sites. Only sites where samples are predominantly of well-mixed marine boundary layer (MBL) air representative of a large volume of the atmosphere are considered. These “MBL” sites are typically at remote marine sea level locations with prevailing onshore winds. Measurements from sites at altitude (e.g., Mauna Loa) and from sites close to anthropogenic and natural sources and sinks (e.g., Park Falls, Wisconsin) are excluded from the global estimate. The use of MBL data results in a low-noise representation of the global trend and allows to make the estimate directly from the data without the need for an atmospheric transport model.

It is observed that CO2 is increasing at about the same rate everywhere it is measured. Because CO2 is a long lived gas in the atmosphere, emissions anywhere will, in about one year, contribute to higher CO2 everywhere. One cannot “hide” CO2 emissions from the MBL sites for more than about a month. Thus the MBL gives probably the best low-noise representation of the ongoing global increase of CO2. The ESRL researchers continue to base their global average on MBL sites because it is not clear how to properly weight continental sites in a global average. It is evident so far that the NOAA MBL global average is representative, internally consistent and stable over time with respect to the addition of new MBL sites.

Date Created

2017-07-05

Last Modified

2018-07-05

Version

2018-07-05

Update Frequency

Monthly

Temporal Coverage

N/A

Spatial Coverage

N/A

Source

John Snow Labs => Earth System Research Laboratory

Source License URL

John Snow Labs Standard License

Source License Requirements

N/A

Source Citation

N/A

Keywords

Global CO2 Trends, Atmospheric CO2, Marine Surface, Dry Air Mole Fraction

Other Titles

Global Time Series about Averaged Marine Surface Monthly Mean CO2, Global Monthly Mean CO2 Trends from 1980 through 2017, Monthly Mean over Averaged Marine Surface CO2 Trends around the Globe

NameDescriptionTypeConstraints
Recorded_DateRefers to the specific date when the specific data is recorded.daterequired : 1
Decimal_DateThe decimal date format represents a raw date in years-only format in which the months and days are converted to partial years. For instance, if we want to calculate the exact day on which the data is recorded, we can use the decimal date to convert it back to the exact day of the year. Here is an example: ((x−1880)×365)+0.5 [where x = decimal date for year 1880]numberrequired : 1 level : Ratio
Average_Monthly_Mean_CO2The monthly mean CO2 mole fraction determined from daily averages.numberrequired : 1 level : Ratio
CO2_TrendIt normally referred to the values that represent the long-term movement in a cyclical context.numberrequired : 1 level : Ratio
Recorded_DateDecimal_DateAverage_Monthly_Mean_CO2CO2_Trend
1990-08-011990.625351.5354
2003-02-012003.125375.3374
1986-01-011986.042347346.32
1995-01-011995.042360359.15
2001-02-012001.125371369.85
2001-03-012001.208371.41370
2004-07-012004.542375.82377
2012-02-012012.125393391.58
2016-02-012016.125403401.64
1983-06-011983.458343.4342.6