Urbanization and cropland irrigation modify land surface water and energy budgets in different ways; however, few observational studies have explicitly quantified their contrasts. Using high-resolution observations from over 2000 surface weather stations and urban and irrigation fraction data, this study investigated the individual and combined effects of urbanization and cropland irrigation on surface air temperature over the Beijing–Tianjin–Hebei (BTH) region in China, where highly urbanized areas and heavily irrigated croplands exist together. The results indicate that (1) the daytime irrigation cooling (with surface air temperature decreasing by ~0.1–0.5 °C at irrigated stations) was non-negligible in late autumn, early winter, and later spring months, when winter wheat irrigation mainly occurred over the BTH region, while a slight warming was observed at many irrigated stations during the nighttime. By contrast, urban warming was most pronounced in the nighttime, especially in winter, and the daytime warming at urban sites was much weaker and comparable to the magnitude of cooling induced by concurrent irrigation for winter wheat. (2) Collectively, the vast stretches of irrigated croplands helped mitigate urban warming, and their combined effect on the daytime surface air temperature over the whole region resulted in a slight cooling of ~0.2 °C in some of the winter wheat-growing months. (3) The contrasting temperature changes due to urbanization and irrigation were spatially variable. Beijing was predominantly characterized by urban warming, while Shijiazhuang, with extensive irrigation, exhibited irrigation cooling (or slight warming) during the daytime (or nighttime) in most of the winter wheat-growing months, which could be a possible contributor to the daytime cooling (or stronger nighttime warming) at urban sites. This work highlights the temperature contrasts between urban areas and surrounding irrigated croplands, as well as the potential role of extensive irrigation in mitigating (or enhancing) daytime (or nighttime) urban warming.

As a significant threat to aviation safety, clear-air turbulence (CAT) is often diagnosed and forecast operationally by using multiple indices, yet reliable diagnosis remains challenging due to its complex physical mechanisms and the lack of universally applicable thresholds for different indices. This study evaluated the performance of 22 diagnostics for capturing CAT over China during the cold season, using Pilot Reports (PIREPs) turbulence records and reanalysis data. Four threshold-setting methods were compared: (1) the Receiver Operating Characteristic (ROC) point nearest the upper left corner (called ROC-optimal for simplicity), (2) the observation-based percentile, (3) the observation-based median, and (4) the reanalysis-based percentile. A method-selection recommendation for threshold setting was further proposed to enhance the performance of CAT diagnostics under varying intensities and data scenarios. Results showed that the ROC-optimal method yielded the highest True Skill Statistic (TSS) for moderate (0.48) and severe (0.28) turbulence, whereas the observation-based percentile method performs best for light turbulence (0.42). The observation-based median method showed moderate performance, while the reanalysis-based percentile method yielded the lowest TSS for all intensities. Given the influence of turbulence intensity and data availability on diagnosis, we suggest using the observation-based percentile method for light turbulence warnings, while the ROC-optimal method is recommended for moderate and severe cases. The reanalysis-based percentile method may be considered for light turbulence warnings when observations are limited.