This study investigates the Global Navigation Satellite System (GNSS) radio occultation (RO) data from FORMOSAT-7/COSMIC-2 (FS7/C2), which provides considerably more and deeper profiles at lower latitudes than those from the former FORMOSAT-3/COSMIC (FS3/C). The statistical analysis of six-month RO data shows that the rate of penetration depth below 1 km height within ±45° latitudes can reach 80% for FS7/C2, significantly higher than 40% for FS3/C. For verification, FS7/C2 RO data are compared with the observations from chartered missions that provided aircraft dropsondes and on-board radiosondes, with closer observation times and distances from the oceanic RO occultation over the South China Sea and near a typhoon circulation region. The collocated comparisons indicate that FS7/C2 RO data are reliable, with small deviations from the ground-truth observations. The RO profiles are compared with collocated radiosondes, RO data from other missions, global analyses of ERA5 and National Centers for Environmental Prediction (NCEP) final (FNL), and satellite retrievals of NOAA Unique Combined Atmospheric Processing System (NCAPS). The comparisons exhibit consistent vertical variations, showing absolute mean differences and standard deviations of temperature profiles less than 0.5 °C and 1.5 °C, respectively, and deviations of water vapor pressure within 2 hPa in the lower troposphere. From the latitudinal distributions of mean difference and standard deviation (STD), the intertropical convergence zone (ITCZ) is evidentially shown in the comparisons, especially for the NUCAPS, which shows a larger deviation in moisture when compared to FS7/C2 RO data. The sensitivity of data collocation in time departure and spatial distance among different datasets are presented in this study as well.

In this study, we introduce a newly developed upper-air observational instrument for atmospheric research. The “Storm Tracker” is an ultra-lightweight (about 20 g including battery), multi-channel simultaneous capable radiosonde designed by the Department of Atmospheric Sciences at National Taiwan University. Developed in 2016, the Storm Tracker aims to provide an alternative for observing atmospheric vertical profiles with a high temporal resolution, especially the lower-level atmosphere under severe weather conditions such as extreme thunderstorms and tropical cyclones. Field experiments were conducted as trial runs in Wu-Chi, Taichung, Taiwan, to examine the ability of the Storm Tracker to observe the boundary layer, in addition to the intercomparison between the Storm Tracker and the widely used Vaisala RS41-SGP radiosonde. Among the co-launches of the Storm Tracker and Vaisala RS41 radiosondes, the measurements of pressure, wind speed, and wind direction are highly consistent between the measurements of the Storm Tracker and the Vaisala RS41-SGP. However, a significant daytime warm bias in the Storm Tracker was found due to solar heating. A metal shield specifically for the Storm Tracker was thus installed and showed mitigation for the warm biases and the overall variance. With the much lower costs of the radiosondes and the simultaneous multi-channel receiver, the Storm Tracker system has shown great potential for high-frequency observational needs in atmospheric research.

In this study, we introduce a newly-developed upper-air observational instrument for atmospheric research. The Storm Tracker (or NTU mini-Radiosonde), is an ultra-lightweight (about 20 g including battery), multi-channel simultaneous capable radiosonde designed by the Department of Atmospheric Sciences at National Taiwan University. Developed since 2016, the Storm Tracker aims to provide an alternative for observation of atmospheric vertical profiles with a high temporal resolution, especially lower-level atmosphere under severe weather such as extreme thunderstorms and tropical cyclones. Two field experiments were conducted as trial runs in December 2017 and July 2018 at Wu-Chi, Taichung, Taiwan, to compare the Strom Tracker with the widely used Vaisala RS41 radiosonde. Among 53 co-launches of the Storm Tracker and Vaisala RS41 radiosondes, the raw measurements of pressure, wind speed, and wind direction are highly consistent between the Strom Tracker and Vaisala RS41. However, a significant daytime warm bias was found due to solar heating. A metal shield specifically for the Storm Tracker was thus installed and shows good mitigation for the warm biases. With the much lower costs of the sondes and the simultaneous multi-channel receiver, the Storm Tracker system has been proved to be beneficial for high-frequency observational needs in atmospheric research.

In tree risk assessment, visual tree assessment (VTA) commonly involves tapping the trunk or branches to detect abnormal sounds as a basis for further assessment. However, interpreting tapping sounds typically requires extensive professional experience and may be subject to subjective judgment. Therefore, research on the classification of tapping sounds may provide valuable supplementary information for assessing local decay in trees. Tapping sounds from a tree trunk can provide cues to the local internal condition, but their classification performance must be evaluated on trees not seen during training. This study examined 30 sweetgum (Liquidambar formosana) trees at a private nursery on the outskirts of Taipei, using mallet taps recorded with a smartphone, with reference labels established by directly sawing open the trunk cross-section after sampling. Each tap point was assigned to one of three original labels—healthy (L0), mildly decayed (L1), and decayed (L2); the binary classification merged L1 and L2 into an “affected” class for comparison with the healthy class (L0), covering all 966 recordings (449 healthy, 517 affected) without excluding any measurement position. The model comparison included a support vector machine, a random forest, and extreme gradient boosting using a 611-dimensional acoustic feature vector, together with a convolutional neural network (CNN) using log-mel spectrograms, with a deeper classification head and feature fusion serving as robustness checks; all per-fold epoch budgets and decision thresholds were chosen by nested cross-validation (tree-grouped inner validation within each outer training fold), and evaluation used five-fold cross-validation grouped by tree. The four main models performed comparably, with five-fold-averaged macro-F1 between 0.6288 and 0.6548 (highest for XGBoost, lowest for the CNN) and ROC-AUC up to about 0.73; no model was decisively superior, and the deep CNN did not outperform the conventional feature-based classifiers, while neither a deeper head nor feature fusion produced a stable improvement. The fold-to-fold variation of every model exceeded its seed-to-seed variation, and all models were lowest on the same fold, indicating cross-tree generalization as the primary source of variation. Although the pooled area under the curve on the 24 mixed-label trees was comparable to that on the full dataset, the median within-tree ROC-AUC (for the RF model) was only 0.511, close to chance, indicating that the pooled metric mainly reflects between-tree differences rather than within-tree discrimination of local decay; the approach therefore cannot reliably localize decay within an individual tree. An exploratory threshold analysis showed that, because the affected class is the majority and the default threshold is already near-optimal, threshold tuning offers limited benefit. Overall, the results provide preliminary support for the feasibility of using tree-trunk tapping sounds as auxiliary information for population-level decay screening; the approach cannot yet identify decayed locations within a single tree, and validation using additional independent trees and external sites is still needed.

The rapid growth of urban populations and the scarcity of living space have necessitated the construction of high-rise buildings in most cities. However, the impact of these structures on vertical thermal environments remains inadequately understood, posing risks to urban dwellers. While high-rise buildings are typically equipped with central air conditioning systems, their outdoor environments still influence energy consumption and natural ventilation. This study assessed vertical urban bioclimatic conditions on the Taipei 101 Tower using Physiologically Equivalent Temperature (PET) and modified PET (mPET), analyzing a decade-long dataset (2012-2021) collected from balcony measurements at two heights (150 m and 350 m), with PET showing a wider range (-3.8 ºC to 46.4 ºC) than mPET (0.3 ºC to 42.8 ºC), indicating more extreme thermal sensations.Winter thermal perceptions were significantly influenced by variations in meso-scale weather systems, with cold patterns leading to colder thermal perceptions at both elevations. In contrast, warmer weather conditions resulted in warmer thermal perceptions. In addition to large-scale atmospheric influences, the observed homogenization of hot thermal perceptions at both elevations during the summers of 2020 and 2021 may largely be attributed to the influence of increasing high-rise buildings through urban development.This study highlights the significant impacts of large-scale weather patterns and climate change on vertical thermal perception in cold seasons. Furthermore, global warming likely contributes to increasing hot thermal perceptions during spring and autumn. These findings have important implications for urban planning and climate adaptation strategies in high-rise urban environments. The dense high-rise developments may negatively expand the vertical scope of heat island effects, and future policy initiatives will require unprecedented approaches in urban planning and design of climate adaptations with serious considerations. Keywords: Physiologically Equivalent Temperature, modified Physiologically Equivalent Temperature, Taipei 101 Tower, Vertical Thermal Perception