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During the XXI century, South America has been the epicenter of vibrant discussions on human mobility. A new vocabulary emerged with legal principles such as the non-criminalization of irregular migration or the right to migrate as a fundamental right taking central stage. The combination of the arrival of COVID-19 together with the important emigration of Venezuelans in the region, as well as economic and political crisis are putting into question some of these advances and present a complex scenario of migration governance in the region for the years to come.

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The field of global migration law looks beyond international law to incorporate all levels of the law, including the regional. This essay explores the regional regulation of mobility, which has indeed become a central subject of discussion and academic analysis. The expansion of human rights law coupled with the explosion of regional processes of integration are the two most important phenomena that have limited the state's capacity to restrict the entry of foreigners and their rights. It should come as no surprise that regional agreements facilitating mobility have proliferated and now involve around 120 countries, either at a bilateral or multilateral level. For one thing, most global migration is regional, whether in Europe, Africa, Asia, or Southern and Central America. In addition, regional instruments can be agreed on more rapidly and, in principle, introduce higher standards of protection and rights due to the more limited number of actors involved in the negotiations. There is, of course, huge variation across regions as to the degree of development of the various agreements, the categories of individuals entitled to mobility and equal treatment and their effective application and enforcement mechanism devices.

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<p>Chemical Transport Models (CTMs) simulate the emission, transformation, and transport of atmospheric chemical species, providing concentration and deposition estimates. While greatly sophisticated, these are still imperfect representations of reality. Data Assimilation (DA), a technique whereby observations are integrated into the simulations, helps alleviate the models' weaknesses, improving their simulation outputs and enabling parameter and state estimation. The variational DA method is an efficient approach for large-scale parameter and state estimation, but it is not straightforward to implement due to the need for a tangent linear matrix of the adjoint model forecast operator. To circumvent this difficulty, the ensemble-based 4DEnVar DA technique was used in this work.</p><p>Daily NO<sub>2</sub> observations from the TROPOspheric Monitoring Instrument (TROPOMI) at resolutions of 3x5 km were acquired for 2019 and assimilated into the LOTOS-EUROS CTM. Due to the scarcity of ground-based monitoring stations for atmospheric gases in Colombia, especially outside urban areas, satellite data provide an attractive alternative for DA.</p><p>The 4DEnVar DA was first evaluated via the Design of Experiments (DOE) methodology with the Lorenz96 model assimilating synthetic data. Different parameters were changed (ensemble number, spread, forcing factor and width of the assimilation time window) according to a complete 2<sup>4</sup> factorial design followed by a Box Behnken design, providing an empirical model that guided the selection about how to modify those tuning parameters. The evaluation criteria used to test the 4DEnVar DA performance was the Root-Mean-Square (RMS) error between the analysis step and the synthetic data. Once this methodology was implemented, it was scaled up to the high-dimensional LOTOS-EUROS experiment.</p><p>The setup for the LOTOS-EUROS DA experiment was simplified in terms of domain area, chemical species of interest, dominant dynamics and considerations about how to perturb the parameters or initial conditions. A range of ensemble-members generated from perturbed parameters or input initial states were studied in conjunction with ensemble inflation experiments and Singular Value Decomposition projections, characterizing the degeneracy of the Gaussian assumption through the time propagation of the ensemble. Additionally, a complimentary analysis of this Gaussian ensemble degeneration was performed using the Shapiro-Wilk and Kolmogorov-Smirnov normality tests, which permitted a rational selection of the spin-up time of the model before the start of the assimilation window and the DA window size.</p><p>The assimilation of satellite NO<sub>2</sub> observations into LOTOS-EUROS made possible the estimation of parameters and states. Before the DA, the non-assimilated model overestimated the magnitude of the observation, this technique improves the simulation in the sense that the analysis result approaches the observations reducing the RMS. Through this methodology, it was possible to circumvent the absence of an adjoint model associated with the chemical components of this CTM. To our knowledge, this is the first application of ensemble variational DA on a CTM for the Northwestern South America region.</p>

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