CO2 forecasts

The longest time series for atmospheric CO2 is for the Pacific island of Mauna Loa. Based on this time series, the development of the CO2 level can be forecasted on a monthly basis.

CO2 forecast update: January 2020

The longest time series for atmospheric CO2 is for the Pacific island of Mauna Loa. Based on this time series, the development of the CO2 level can be forecasted on a monthly basis.

Figure 1 shows that the CO2 level is expected to continue its typical cyclical evolution in combination with secular growth.  

Forecasted CO levels (upper panel) 2020(1)-2021(12) and growth rates (lower panel)

The next figure shows the actual CO2 measurement from 2019 together with the family of forecasts produced so far. Staring with the projection from September 2019 and ending with the current January 2020 forecast.

Actual Atmospheric CO2 (red solod line) and a family of five projections. The oldest starts in September 2019 and the newest in January 2020 (the current forecast).

There is not a lot of differences between the five projections. The graphs show that the forecast from September 2019 has under-predicted CO2 evolution in the four last months of 2019 somewhat. The three other forecast from 2019 appear to be very precise (but there are also fewer observations to compare with).

Four of the five projections agree that a new “all time high” in atmospheric CO2 can become a reality already in March or April 2020.   

Pdf file with the January 2020 forecasts: Januaryforecast.pdf

The data set with the January 2020 forecasts: jan2020_forecast.xlsx

Posted 9 January 2020

Previous forecast: December 2019

The figure shows forecasts for the 16 month period from December 2019 to March 2021

Forecasts for Mauna Loa atmospheric CO2, December 2019-March 2021.
Forecasts produced 10 December 2019, based on data where CO2 in November 2019 is
the last observation. pdf version of the graph.

CO2 is forecasted to increase by 0.62 percent from December 2018 to December 2019. For the two 12 month periods ending in January and February 2020, the forecasted changes are 0.50 and 0.53 percent increases.

The graph below shows the forecasted CO2 level for the 12 months from December 2019 to November 2020 compared with the actual CO2 levels in the 12 months for December 2018 to November 2019.

Plot of CO2 forecasts Dec 2019- Nov 2020, with actual CO2 level for Dec 2018-Nov 2019 shown for comparison. pdf with graph

The graphs in the figure indicate that the forecasted CO2 level over the next 12 months are significantly higher than the latest historical levels for the same months.

The forecasted numbers are available in 10dec20019_forecast.xlsx

Posted 10 december 2019 (Normetrics.no)

Previous forecast: November 2019

The figure shows forecasts for the 16 month period from November 2019 to February 2021

Forecasts for Mauna Loa atmospheric CO2, November 2019-February 2021. Forecasts produced 19 November 2019, based on data where CO2 in October 2019 is the last observation. pdf version of the graph.

According to this forecast, CO2 is excpected to increase by 0.57 percent from November 2018 to November 2019. For the two 12 month periods ending in December 2019 and January 2020, the forecasted changes are 0.62 and 0.43 percent increases.

The graph below shows the forecasted CO2 level for the 12 months from November 2019 to October 2020 compared with the actual CO2 levels in the 12 months from November 2018 to October 2019.

Plot of CO2 forecasts Nov 2019- Oct 2020, with actual CO2 level for Nov 2018-Oct 2019 shown for comparison. pdf version of graph

The graphs indicate that forecasted CO2 level over the next 12 months are significantly higher than the latest historical levels for the same months.

The forecasted numbers are in 19nov2019.xlsx .

Previous forecast: October 2019

The graph below shows forecasts for the 16 month period from October 2019 to January 2021.

Forecasts for Mauna Loa atmospheric CO2. October 2019-January 2021. Forecast produced 23 October 2019, based on data where CO2 in September 2019 is the last observation. pdf version of the graph.

According to this forecast CO2 is expected to increase by 0.58 percent from October 2019 to October 2020. For the two 12 month periods ending in November and December 2019, the forecasts are 0.56 and 0.62 percent increases.

The forecasted numbers are in 23oct20019_forecast.xlsx .

Previous forecast: September 2019

The graph below shows the previous forecast, for the period from September 2019 to December 2020.

Forecasts for Mauna Loa atmospheric CO2. September 2019-December 2020. Forecast produced 23 September 2019, based on data where CO2 in August 2019 is the last observation. pdf-version of the graph.

The forecasted numbers are in 23sept2019_forecast.xlsx

The forecasted value for September 2019 was 408.05 ppm, while the actual monthly average was 408.54 pmm. The forecast was just inside the upper bound of the 95 % forecast bound (408,69 ppm).

Institutional forecasts

Forecasts of Mauna Loa CO2 have been published by among others, the UK Met.office: https://www.metoffice.gov.uk/research/climate/seasonal-to-decadal/long-range/forecasts/co2-forecast. These forecasts, produced by large instituions, are high-quality and are based on extensive measurements and the use of scientific models.

Methodology

The forecasts on this page only use the information in the time series itself, and that information is processed with the use of methods originally developed for empirical macroeconometric modelling, see Doornik og Hendry (2018, Ch. 14.8), Henry og Doornik (2014), Nymoen (2019, Ch. 11), among others. This means that the forecasts can be updated soon after the publication of a new monthly mean of atmospheric CO2 over Mauna Loa has been published. In each forecast round the forecasting function is updated withe the use an alogrithm of for automatic model specification

References:

Data: https://www.esrl.noaa.gov/gmd/ccgg/trends/data.html, Dr. Pieter Tans, NOAA/ESRL (www.esrl.noaa.gov/gmd/ccgg/trends/) and Dr. Ralph Keeling, Scripps Institution of Oceanography (scrippsco2.ucsd.edu/)

Method:

David F. Hendry and Jurgen A. Doornik (2014): Empirical Model Discovery and Theory Evaluation. Automatic Selection Methods in Econometrics, MIT, Press.

David F. Hendry and Jurgen A. Doornik (2018): Empirical Econometric Modelling. PcGive 15. Volume I. Timberlake Consultants.

Ragnar Nymoen (2019) Dynamic Econometrics for Macroeconomic Modelling, World Scientific.