This study focuses on the identification of weather regimes (WRs) over Mexico, the tropical eastern Pacific, Central America and the Caribbean, associated with seasonal precipitation over southern Mexico. A self-organizing maps (SOM) analysis of sea level pressure, 850-hPa horizontal winds and 925-hPa-specific humidity for the period 1997-2013 was carried out to identify the circulation patterns. This approach allowed the discrimination of wet and dry regimes, with clear and distinct features. Weather patterns exhibiting negative (positive) mean sea level pressure anomalies, southerly (northerly) winds, above-(below-) average low-level moisture and little (large) influence of the North Atlantic Subtropical High (NASH), resulted in above-(below-) average precipitation over southern Mexico. The intra-seasonal variability of the WRs and their associated rainfall is well captured by this methodology. In particular, the mid-summer drought (MSD) during late July and early August, is clearly represented by a group of patterns, which evidence a strong influence of the NASH, strong easterly winds in the Caribbean Basin and reduced low-level humidity, all factors that combine to induce below-normal rainfall over southern Mexico. The analysis of the inter-annual variability of the WRs suggests that year-to-year variations in their frequencies can impact summer rainfall in the regions of southern Mexico considered in this study. In particular, the analysis indicates that the dominant WR associated with the MSD exhibits a 3-to 4-year modulation in its frequency of occurrence, which has not been previously reported in the literature. The main MSD pattern is more frequent during dry years and has a significant correlation with the Multivariate El Niño-Southern Oscillation (ENSO) Index (MEI), indicating that MSD is stronger during 'El Niño' years. Also, WRs associated with negative (positive) rainfall anomalies showed positive (negative) correlations with the MEI, suggesting a possible modulation by ENSO phases.

In this study, twenty large-scale circulation patterns are identified to generate a synoptic classification of Weather Types (WT) over a region that comprises Mexico, the Intra-Americas Seas, Central America, and northern South America. This classification is performed using Self-Organizing Maps (SOMs) with mean sea-level pressure standardized anomalies from reanalysis. The influence of quasi-permanent pressure centers over the region, such as North Atlantic Subtropical High (NASH) and North Pacific High (NPH) are well captured. Seasonal variability of high-pressure centers for dry (November–April) and wet (May–October) periods over the entire region are also well represented in amplitude and pattern among the WTs. The NASH influence and intensification of the Caribbean low-level jet and the North American monsoon system is well captured. During the dry period, a strong trough wind advects cold air masses from mid-latitudes to the subtropics over the western Atlantic Ocean. High-frequency transitions among WTs tend to cluster around the nearest neighbors in SOM space, while low-frequency transitions occur along columns instead of rows in the SOM matrix. Low-frequency transitions are related to intraseasonal and seasonal scales. The constructed catalog can identify near-surface atmospheric circulation patterns from a unified perspective of synoptic climate variability, and it is in high agreement with previous studies for the region.

Abstract. Eight years of upper-tropospheric (UT) ice crystal measurements with the backscatter cloud probe (BCP), installed on commercial aircraft operated as part of the In-Service Aircraft for a Global Observing System (IAGOS), have been analyzed to assess the frequency and characteristics of extreme ice crystal events (EIEs), defined in this study as encounters with clouds that have number concentrations exceeding 5000 L−1. A total of 3196 events, in clouds of horizontal extent ≥ 2.5 km, were identified during the period from December 2011 to March 2020 in the latitude band between 30∘ S and 30∘ N. Regions of anthropogenic sources of carbon monoxide, with particles that can alter cloud microphysics, were attributed to these EIEs in UT clouds using the SOFT-IO model. The evaluation of low- and upper-level kinematic variables from the European Centre for Medium-Range Weather Forecasts (ERA5) reanalysis, combined with spatial distributions of aerosol optical depth and regions of biomass burning, highlights the physical mechanisms by which the particles are lofted to flight levels in regions of deep convection. The maps of lightning frequency, derived from the World Wide Lightning Location Network (WWLLN), provide additional evidence of the role of deep convection in transporting aerosol particles, cloud hydrometeors and carbon monoxide to aircraft cruising altitudes. The evaluation of aerosol particle mass concentrations and composition from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) contributes additional evidence for a link between regions of EIEs and surface emissions of dust, black carbon (BC), organic carbon (OC) and sulfate particles. Given the composition of the source aerosols and the role of deep convection in their transport to the UT, the sampled ice clouds likely originate from the homogeneous or heterogeneous freezing of droplets formed on these particles, as has been reported in previous studies. The results from this study, which have been obtained from a large sample of measurements, have ramifications related to satellite measurement validation, weather forecasting and climate change. In addition, over 2000 of the randomly sampled clouds had derived ice water contents larger than 1 g m−3, a concentration that is considered potentially hazardous to commercial aircraft operations.

The fifth phase of the Coupled Model Inter-Comparison Project (CMIP5) is frequently used to force regional climate models for dynamic downscaling and projections, which decision makers in turn use for future plans in different sectors. It is, therefore, highly important to assess their performance in order to use them as reliable tools. A weather-type approach for the evaluation of the performance of CMIP5 models is employed in this study, with the objective of providing insight into model errors under a set of distinct synoptic conditions and circulation types associated with the rainy season over Mexico and Central America. The Self-Organizing Maps algorithm is used to identify the main weather regimes (constructed from sea level pressure, specific humidity, and low-level winds at a daily time-scale), which are then evaluated against reanalysis. The results show that model performance depends on the weather type in all of the variables except for sea level pressure, which confirms the usefulness of this approach. The models simulate better the humidity patterns that show weak deviations from the climatological norm. In addition, the wind pattern representing the Caribbean Low Level Jet is well reproduced by all the models. The results show the capacity of this methodology for determining the extent to which climate models represent the main circulation patterns that characterize the climate and local weather in Mexico.

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