Weighted average temperature (Tm) plays a crucial role in global navigation satellite system (GNSS) precipitable water vapor (PWV) retrieval. Aiming at the poor applicability of the existing Tm models in Europe, in the article, we used observations from 48 radiosonde stations over Europe from 2014 to 2020 to establish a weighted average temperature model in Europe (ETm) by the nonlinear least squares estimation method. The ETm model takes into account factors such as ground temperature, water vapor pressure, latitude, and their annual variation, semiannual variation and diurnal variation. Taking the Tm obtained from the radiosonde data by the integration method in 2021 as the reference value, the accuracy of the ETm model was evaluated and compared with the commonly used Bevis model, ETmPoly model, and GPT2w model. The results of the 48 modeled stations showed that the mean bias and root mean square (RMS) values of the ETm model were 0.06 and 2.85 K, respectively, which were 21.7%, 11.5%, and 31.8% higher than the Bevis, ETmPoly, and GPT2w-1 (1° × 1° resolution) models, respectively. In addition, the radiosonde data of 12 non-modeling stations over Europe in 2021 were selected to participate in the model accuracy validation. The mean bias and RMS values of the ETm model were –0.07 and 2.87 K, respectively. Compared with the Bevis, ETmPoly, and GPT2w-1 models, the accuracy (in terms of RMS values) increased by 20.5%, 10.6%, and 35.2%, respectively. Finally, to further verify the superiority of the ETm model, the ETm model, and other Tm models were applied to the GNSS PWV calculation. The ETm model had mean RMS_PWV and RMS_PWV/PWV values of 0.17 mm and 1.03%, respectively, which were less than other Tm models. Therefore, the ETm model has essential applications in GNSS PWV over Europe.

The study of cross-border transport connectivity is significant for the development of regional integration and insight into global patterns. Comprehensive connectivity evaluations are lacking and insufficient attention has been paid to Latin American connectivity, so it is of great practical importance to comprehensively and rationally evaluate Latin American connectivity. In this article, based on the four modes of transport, namely, sea, road, air and railroad, and using the actual trade volume as a comparison, a connectivity evaluation index system with considerable reliability and generalization ability was constructed using the expert scoring method, QAP correlation analysis, QAP regression, and statistics, and the connectivity calculations of Latin America were obtained. Analyzing the connectivity structure of Latin America, it was found that cross-border passenger and cargo transport in the region was dominated by sea transport and supplemented by road and air transport, with railroads used the least. The overall connectivity of Latin America was low, and the overall development was unbalanced, with a strong law of spatial differentiation, which was mainly manifested in the strongest connectivity of the integrated coastal countries, followed by the island countries, and the lowest connectivity of the landlocked countries. Different countries assumed different roles in regional connectivity, which could be categorized into global hub type, local hub type and non-hub type based on the calculations. There was a spatial pattern of decreasing connectivity with distance in typical countries, but the rate of decline was closely related to their geographic location and the role they played in the connectivity network. This study can provide reference and inspiration for regional connectivity evaluation, improvement, and sustainable development.