## 2 Materials and Methods
### Satellite Products  
To determine the distribution of cloud cover and atmospheric humidity, as a proxy of precipitation, we used a dataset from the Geostationary Operational Environmental Satellite-12 (GOES-12) centered over the CS at 75\({}^{\circ}\) W [70]. The dataset includes imagery from the water vapor (6.5 \(\upmu\)m) and infrared (13.3 \(\upmu\)m) channels with a \(4\times 8\) km and 30-min spatial and temporal resolution, respectively. Infrared images are capable of measuring cloud-top temperature [71], thus providing an estimate of the cloud's vertical development. Pixels colder than \(-60\)\({}^{\circ}\)C generally delineate deep clouds in the TC core and within 444 km from the TC center (e.g., [71; 72]). This temperature is at an elevation of \(\sim\)13 km from July through October in the atmosphere over the CS [73; 74]. To examine changes during the approach and landfall of selected TCs, we created a visualization tool (animation) available online (see Table S2) ([[https://met-bcs.cicese.mx/LSU](https://met-bcs.cicese.mx/LSU)]([https://met-bcs.cicese.mx/LSU](https://met-bcs.cicese.mx/LSU))). Specifically, this tool is a compilation of water vapor time-series to aid in the analysis of the TCs' large-scale environmental impact and footprint [75]. A set of animations from this analysis is listed in the results section and the full list of web links is in Table S2 (Supplemental Materials).  
We identified vegetation following TCs' landfall using the Enhanced Vegetation Index (EVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) at a 250-m spatial resolution and the applied product MOD13Q1V from the on-line Google Earth Engine platform [76]. The EVI is derived from red (0.620-0.670 \(\upmu\)m), near-infrared (0.841-0.876 \(\upmu\)m), and blue (0.459-0.479 \(\upmu\)m) reflectance bands; the EVI was averaged over time to detect vegetation change on a per-pixel basis [77]. This index minimizes canopy background variations, maintains sensitivity over dense vegetation, and includes an atmospheric correction along with a mask for water, clouds, and cloud shadows. The EVI has been used to assess TC impact on coastal vegetation (e.g., [78]) and is sensitive to structural variations in canopy structure. Here, we computed changes between two adjacent years for the periods with the same number of days before and after landfall to estimate either an increase (gain) or decrease (loss) of vegetation areas.  
We used the surface satellite-based Chl-\(a\) values as a proxy to assess potential changes in coastal aquatic primary productivity (e.g., [79; 80; 81]) using daily satellite observations at \(4\times 4\)-km spatial resolution (i.e., _GlobColour_; [82; 83; 84]) and level-4 processing provided by the European Space Agency [85]. These products are recommended for studies of small-scale and high-frequency phenomena in coastal areas [86]. The estimated Chl-\(a\) spatial differences were estimated before and after landfall along the YP coastal ocean bounded by the coordinates 18\({}^{\circ}\) N, 24\({}^{\circ}\) N, 85\({}^{\circ}\) W, and 93\({}^{\circ}\) W. These values were similar to Chl-\(a\) reported by other studies in the same coastal regions in the GOM [87; 88; 89]. We also evaluated the temporal changes of satellite-based Chl-\(a\) along a 850 km long transect at 25 m isobath from the Campeche sound and encompassing the states of Campeche, Yucatan, and partially, northern Quintana Roo coastlines. The Chl-\(a\) values along this transect are influenced by the potential interaction between the groundwater discharge and water column mixing [39; 40] after TC landfall. The partial coverage of Quintana Roo's coastline was selected to determine changes in Chl-\(a\) during TC impact at the western, northern, and eastern YP coastlines (Figure 1).