Abstract
The magnitude of net carbon dioxide emissions resulting from global forest carbon change, and hence the contribution of forests to global climate change, is highly uncertain, owing to the lack of direct measurement by Earth observation and ground data collection. This paper uses a new method to evaluate this uncertainty with greater precision than before. Sources of uncertainty are divided into conceptualization and measurement categories and distributed between the spatial, vertical and temporal dimensions of Earth observation. The method is applied to Forest Reference Emission Level (FREL) reports and National Greenhouse Gas Inventories (NGGIs) submitted to the UN Framework Convention on Climate Change (UNFCCC) by 12 countries containing half of tropical forest area. The two sets of estimates are typical of those to be submitted to the Reducing Emissions from Deforestation and Degradation (REDD+) mechanism of the UNFCCC and the 2023 Global Stocktake of its Paris Agreement, respectively. Assembling the Uncertainty Fingerprint of each estimate shows that Uncertainty Scores are between 10 and 14 for the NGGIs and 5 and 10 for the FREL reports, and so both exceed the threshold of 2 when it is advisable to evaluate uncertainty by standard statistical methods. Conceptualization uncertainties account for 60% of all uncertainties in the NGGIs and 47% in the FREL reports, e.g., there is incomplete coverage of forest carbon fluxes, and limited disaggregation of fluxes between different ecosystem types and forest carbon pools. Of the measurement uncertainties, all FREL reports base forest area estimates on at least medium resolution satellite data, compared with only 3 NGGIs; after REDD+ Readiness schemes, mean area mapping frequency has fallen to 2.3 years in Latin America and 3.0 years in Asia, but only 8.3 years in Africa; and carbon density estimates are based on national forest inventory data in all FREL reports but only 4 NGGIs. The effectiveness of the Global Stocktake and REDD+ monitoring will therefore be constrained by considerable uncertainties, and to reduce these requires a new phase of REDD+ Readiness to ensure more frequent national forest inventories and forest carbon mapping.
Highlights
How uncertain is information on global environmental change phenomena derived wholly or partly from very large numbers of satellite images? This is one of the challenges that will face the UN Framework Convention on Climate Change (UNFCCC) when in 2023 it holds the first Global Stocktake, to monitor implementation of its Paris Agreement to reduce carbon dioxide (CO2) emissions that contribute to global climate change and keep the rise in mean global temperature “to well below 2 ◦C above pre-industrial levels” [1]
To assess the reliability of estimates of forest carbon fluxes submitted to the first UNFCCC Global Stocktake by its member countries in their National Greenhouse Gas Inventories (NGGIs) the UNFCCC should compare estimates for common reporting categories
This paper has shown that extending the Uncertainty Assessment Framework (UAF) [20] can identify the sources of global environmental uncertainties in a way that shows how to reduce them through better use of Earth observation technologies
Summary
This is one of the challenges that will face the UN Framework Convention on Climate Change (UNFCCC) when in 2023 it holds the first Global Stocktake, to monitor implementation of its Paris Agreement to reduce carbon dioxide (CO2) emissions that contribute to global climate change and keep the rise in mean global temperature “to well below 2 ◦C above pre-industrial levels” [1] It affects how the UNFCCC monitors progress in reducing emissions linked to forest carbon change under its Reducing Emissions from Deforestation and Degradation (REDD+) mechanism [2]. Various REDD+ Readiness programmes have been implemented to strengthen capacity so that developing countries can establish the Measurement, Reporting and Verification (MRV) centres needed to participate in REDD+ [13] These programmes have led to more frequent forest area surveys in some countries, but progress generally has been mixed [14], especially in measuring forest carbon fluxes. Forest degradation is reversed by natural forest regrowth, and offset by enhanced growth in existing forest resulting from carbon fertilization and other processes linked to global climate change [26]
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