## 1 Introduction
It raises the questions of whether the standardization of procedures for appraisal, transfer and up-scaling of initiatives within the CoM framework are ready or not to be implemented in the MA framework, given that the local actions can be deeply influenced by their geographical, political and cultural contexts, disregarding climate goals and strategies [16]. In a similar way, scientific studies often seek to understand the strategies of CoMs by making classifications from an approach based on mitigation objectives [17]. However, this is not the case when analyzing the adaptation approach, as there are very few studies that have compared European local adaptation measures on a wide scale [18]. The research presented here aims to fill the gap in systematic studies on adaptation initiatives, by exploring and classifying actions labeled as \"good practices\" [19] by the Mayors Adapt program during its year of activity prior to its integration with the CoM. The aim of this work is the development of a new method for the comparative evaluation of European adaptation initiatives. For this purpose, the strategies and municipal good practices in the framework of the MA are analyzed in an exploratory and heuristic way. In order to do so, the context (geographical framework, biogeographical framework and impact of climate change) of these good practices is analyzed, as well as the adaptation strategies elaborated by their municipal governments (actions, approach, methodology and estimated difficulty of development), obtaining such information from 84 different municipal strategies from the initiative's repository [19]. There are some studies that have carried out comparative analyses of adaptation strategies that allow a good contextualization [18; 20], even providing a classification of the strategies, basing their knowledge on the division into groups based on one-dimensional factors and often previously selected. The methodology proposed for the classification of strategies aims to avoid assuming a priori a given relevance of the variables. For this purpose, a heuristic methodology is proposed for the classification of information patterns and profiles by means of a methodology based on artificial neural networks, specifically Self-Organizing Maps [21], which has proved effective in patterns recognition in other areas [22; 23; 24; 25; 26; 27; 28; 29], to finally carry out the characterization and critical comparison of such profiles by using non-parametric statistical techniques [30; 31] and odds ratio analysis (OR) [32; 33]. This classification and characterization is intended to be useful to understand the different strategies and their relationship with others belonging to the same typology or strategic pattern and as a frame of reference for future implementations of local climate change adaptation policies and actions, and with the possibility of drawing comparisons with other strategies, such as the CoM mitigation strategies. The paper is structured as follows: Section 2 introduces the strategic context of the CoM and MA initiatives; Section 3 shows the state of the art in research, identifying types of climate change strategies in the EU; Section 4 describes the sources of information and procedures carried out on them; Section 5 shows the results achieved, describing and characterizing the different patterns and profiles of adaptation strategies found in the good practices studied in the Mayors Adapt initiative; Section 6 gives the main contributions of the work in relation to the state of the art. Finally, the main conclusions are highlighted in the last section of the document.