As countries gear up for the COP 30 negotiations in Belém, one of the most anticipated discussions would be centred around the finalisation of the indicators for the Global Goal on Adaptation (GGA). What started off as an exhaustive pool of close to 10,000 indicators has iteratively been pruned down to a list of 100, spread across both thematic and dimensional targets as listed in paras 9–10 under Decision 2/CMA 5. Representing a monumental step towards operationalising the United Arab Emirates (UAE)-Belem Work Programme, what shape the indicator list ends up taking will determine not only the effectiveness of GGA assessments globally, but also the flexibility of Parties in aligning indicators with national circumstances and adaptation priorities.
To begin with, for finalising indicators, India could consider categorising them into three groups, namely, positive, flexible, and negative. The first category would include indicators that are already part of existing reporting mechanisms under the United Nations Framework Convention on Climate Change (UNFCCC) or integrated within domestic policies and programmes. Similarly, the negative list may comprise indicators that would elicit additional efforts for data collection, processing and analysis or may weaken the country’s negotiation stance. And finally, the flexible category, having indicator options that require certain refinement or may not be a hundred percent match to existing data. This would help create a prioritised list on which initial work can begin.
The idea is not to dismiss any indicator merely because it adds to the reporting burden. Rather, to avoid endorsing indicators without a proper national reporting mechanism at present, as these may prove problematic later on. These include indicators such as “Change in the annual rate of reported heat-related occupational injuries and deaths”, “Proportion of workers in climate-vulnerable economic sectors/activities”, etc. Similarly, there are also cases of indicators that have been developed by third-party agencies and have been included in the GGA indicator set. However, as per India’s official submission on the GGA and the UAE – Belem Work Programme, the country has underscored the importance of using official Party-submitted data for tracking adaptation progress, such as Biennial Update Reports (BURs), National Communications (NATCOMs), etc. This is based on the understanding that reliance on third-party databases may “undermine the transparency and sovereignty of national reporting processes”. A case in point is the indicator “Ecosystem resilience under climate change (measured by the Bioclimatic Ecosystem Resilience Index, BERI)”. This index is a sub-component of the Environmental Performance Index (EPI) developed by Yale and Columbia University. According to an earlier release by the Press Information Bureau, India has expressed reservations against the results of this index on the grounds that the calculations were found to be based on unfounded assumptions.
On the domestic front, initial groundwork as regards climate adaptation has been laid with the submission of the Initial Adaptation Communication to UNFCCC, the National Adaptation Plan (NAP) being set to be released shortly, as well as the release of the Draft Framework of India’s Climate Finance Taxonomy However, despite these headways, what one finds missing is a clear-cut, quantifiable target-setting mechanism with respect to adaptation outcomes. Unlike the case of mitigation, where one has the National Determined Contribution (NDC) targets stipulating a 45% reduction in emissions intensity of the Gross Domestic Product (GDP) relative to the 2005 levels and having an installed capacity of 50% electric power installed capacity from non-fossil fuel-based sources by 2030, there is an absence of adaptation targets for India. The closest mention to any form of adaptation “target”, so to speak, in the NDC document is “….To better adapt to climate change by enhancing investments in development programmes in sectors vulnerable to climate change, particularly agriculture, water resources, Himalayan region, coastal regions, health and disaster management…….”. Similarly, the draft climate finance taxonomy document also includes only the agriculture and water sectors under its ambit as far as adaptation is considered and defines adaptation interventions as “….an essential intervention reflected through the focus on enhancing investments in development programmes in sectors that are vulnerable to climate change, particularly agriculture, water resources, the Himalayan region, coastal regions, and health and disaster management…..”. This still leaves many questions unanswered as regards what is to be considered as an adaptation intervention in practice. Bridging this gap requires moving from general intent to specific, measurable outcomes. A good starting point would be identifying a handful of sectors, perhaps those alluded to in the aforementioned documents, for defining targets. For instance, one may consider linking the adoption of early warning systems with improvement in adaptive capacity based on measurable reductions in climate-induced disaster-related losses as one such target. Thus, with the updated NDCs poised for release this year, it is an opportune time to incorporate quantitative targets for adaptation so as to transform intent (present as part of NAP) into action.
The idea is to kill two birds with one stone. The fact that countries are already reporting on a number of adaptation-relevant indicators under existing reporting frameworks, such as the Sustainable Development Goals (SDGs), Sendai Framework for Disaster Risk Reduction, Convention on Biological Diversity (CBD), etc., that are also included as part of the consolidated indicator list, can be leveraged. In other words, countries should self-select options based on national circumstances, aspects that they would want to highlight as part of their respective national adaptation progress. With India’s NAP being set to release shortly, the obvious next step would be to set up a Monitoring, Evaluation and Learning (MEL) framework that helps track performance periodically. The argument being made here is to pre-emptively align those efforts with the GGA indicator reporting process such that there is coherence
(Views expressed are the authors’ own and do not reflect those of ICRIER)
