. 2015 Jan 10;21(6):839–859. doi: 10.1007/s11027-014-9627-7

Table 4.

Application of methodological considerations for tracking adaptation in large urban areas globally (Araos et al. In review)

Methodological consideration	Application	Challenges
Consistency	• Step 1: Adaptations defined broadly as “adjustments in natural or human systems in response to actual or expected climate stimuli and their effects.” • Step 2: Record adaptation initiatives only if they are explicitly communicated as adaptations to climate change. • Step 3: Organize adaptation policies into a database of discrete initiatives.	• Some initiatives may reduce vulnerability but not be framed as climate change adaptation. • Some initiatives address natural climate variability rather than long term change. • Some initiatives may be maladaptive.
Comparability	• Urban municipal governments defined as the unit of comparison. • Adaptation initiatives recorded only if they are undertaken by the municipal government. • Large cities analyzed (>1 m), small cities excluded. • Systematic web search for Adaptation Plans, Climate Action Plans, NGO-partnered initiatives, and official government websites.	• Exclusion of other actors undertaking adaptation: - Exclude adaptation by private individuals or households. - Exclude adaptation from the private sector. - Exclude adaptation from other governmental scales (national / regional). • Lack of generalizable metrics to evaluate effectiveness of adaptation.
Comprehensiveness	• Use translators to capture >90 % of cities over 1 m. • Classify initiatives sectorally to grasp breadth of adaptation (e.g., water supply, transportation, human health). • Analyze 402 cities to produce a large enough dataset for inferential statistical analysis: - Identify and analyze drivers of adaptation (e.g., GDP, population, good governance index).	• Reporting bias: - Measuring the ability to communicate adaptation rather than adaptation itself. - Low capacity governments may not publish adaptation projects, but may be partnered with other organizations to undertake initiatives. • Logistical and resources constraints in analyzing large number of cities with diverse languages.
Coherence	• Use policy classification methods coherent with existing theory: - Groundwork vs. action. - Which vulnerabilities are addressed? (e.g., temperature increase, soil erosion, sea level rise). - Which sectors are targeted? (e.g., energy supply, infrastructure, social services). - What is the policy’s typology? (e.g., management, capacity building, financing, research). • Develop methods to capture substantiality of the initiatives. • Match existing and planned initiatives against stated commitments and goals. • Perform qualitative case studies to identify policy pathways facilitating adaptation	• Conceptual difficulty in measuring the impact of adaptation policy – how do we measure averted risk? • Variations in the definition of adaptation “success”. • Fuzziness of adaptation goals across government scales. • Difficulty in sorting policies intentionally designed as adaptation to climate change vs. re-labeled existing policies.

Methodological consideration

Application

Challenges

Consistency

• Step 1: Adaptations defined broadly as “adjustments in natural or human systems in response to actual or expected climate stimuli and their effects.”

• Step 2: Record adaptation initiatives only if they are explicitly communicated as adaptations to climate change.

• Step 3: Organize adaptation policies into a database of discrete initiatives.

• Some initiatives may reduce vulnerability but not be framed as climate change adaptation.

• Some initiatives address natural climate variability rather than long term change.

• Some initiatives may be maladaptive.

Comparability

• Urban municipal governments defined as the unit of comparison.

• Adaptation initiatives recorded only if they are undertaken by the municipal government.

• Large cities analyzed (>1 m), small cities excluded.

• Systematic web search for Adaptation Plans, Climate Action Plans, NGO-partnered initiatives, and official government websites.

• Exclusion of other actors undertaking adaptation:

- Exclude adaptation by private individuals or households.

- Exclude adaptation from the private sector.

- Exclude adaptation from other governmental scales (national / regional).

• Lack of generalizable metrics to evaluate effectiveness of adaptation.

Comprehensiveness

• Use translators to capture >90 % of cities over 1 m.

• Classify initiatives sectorally to grasp breadth of adaptation (e.g., water supply, transportation, human health).

• Analyze 402 cities to produce a large enough dataset for inferential statistical analysis:

- Identify and analyze drivers of adaptation (e.g., GDP, population, good governance index).

• Reporting bias:

- Measuring the ability to communicate adaptation rather than adaptation itself.

- Low capacity governments may not publish adaptation projects, but may be partnered with other organizations to undertake initiatives.

• Logistical and resources constraints in analyzing large number of cities with diverse languages.

Coherence

• Use policy classification methods coherent with existing theory:

- Groundwork vs. action.

- Which vulnerabilities are addressed? (e.g., temperature increase, soil erosion, sea level rise).

- Which sectors are targeted? (e.g., energy supply, infrastructure, social services).

- What is the policy’s typology? (e.g., management, capacity building, financing, research).

• Develop methods to capture substantiality of the initiatives.

• Match existing and planned initiatives against stated commitments and goals.

• Perform qualitative case studies to identify policy pathways facilitating adaptation

• Conceptual difficulty in measuring the impact of adaptation policy – how do we measure averted risk?

• Variations in the definition of adaptation “success”.

• Fuzziness of adaptation goals across government scales.

• Difficulty in sorting policies intentionally designed as adaptation to climate change vs. re-labeled existing policies.

This table illustrates the application of the 4Cs in the context of a project tracking adaptation in urban areas globally. The project analyzed 402 urban municipal governments and classified cities according to their adaptation profiles. We used systematic web searches to identify government adaptation documents, and then extracted discrete adaptation initiatives into a database. We only gathered initiatives if they were explicitly communicated as adaptations to climate change. We retrieved adaptation data only for cities over one million inhabitants and from cities in which the official languages was spoken by at least five cities total. Once gather adaptation data we classified initiatives based on whether they were groundwork or action, which impacts and sectors they targeted, and adaptation policy typology