![]() ![]() A UK case study further demonstrates the performance of the GSDR-QC procedure, while showing how region-specific data and understanding can be incorporated into the quality control process. Comparison with manually quality-controlled gauge data shows that the procedure results in an overall improvement to the quality of the GSDR dataset. The quality checks and rule base are adaptable to help incorporate local or regional information. The algorithm is based on 25 quality checks, which are combined into a simple rule base to remove suspicious data. This paper presents a new, open-source quality control algorithm (GSDR-QC) to identify these issues in hourly rainfall data, along with an application of the algorithm to the Global Sub-Daily Rainfall (GSDR) observational dataset. However, gauge records often have quality issues, for example due to equipment malfunctions and recording errors. Sub-daily rainfall observations are vital to help us understand, model and adapt to changing climate extremes. This study shows that ARs are important synoptic mechanisms within observed precipitation trends over East Asia, such that understanding their response to a warming climate is a prerequisite to characterizing the nature of future precipitation changes in this region. Moreover, in contrast to the general decreasing trends in boreal summer, AR activity during boreal winter-spring exhibits significant increasing trends, implying a potential weakening of the seasonality of ARs. These responses include the intensification of the upper-level westerly jet accompanied with the strengthening of the South Asian Anticyclone during summer season. These changes are associated with a warmer and more humid environment along AR axes, as well as the southward shift of ARs driven by the dynamical responses of the large-scale environments in the context of climate warming. In contrast, increasing AR activity and the associated precipitation and heavy rain events over the south of East Asia are observed. The decreasing trend in ARs over the north is principally related to the intensification and southward displacement of the southwesterly monsoon flow in boreal summer. These dynamical changes dominate the decreasing trend of total summer precipitation amounts in parts of northern China. The results indicate a significant decreasing trend in ARs and the associated precipitation over the north of East Asia. ![]() These datasets are produced at a relatively high spatial resolution of 0.25° × 0.25°, which allows for evaluation of the long-term trends in the fine-scale characteristics of ARs. In this study, long-term trends in ARs over East Asia for the period 1951–2015 are investigated using long-term records of historical climate, including the ERA5 climate reanalysis and the APHRODITE precipitation dataset. The results given by newly proposed QC components, which use multiple data records at the same station but from different data sources, show that such comparison tests are important and work well for detecting errors such as unit misconversions.Ītmospheric rivers (ARs) play an important role in the climate of East Asia due to their close linkage to precipitation extremes. While most of the errors were found in data which had not been subjected to thorough QC, many basic errors were also found in this widely used global/regional dataset. The results are illustrated herein with examples with discussions of possible causes for each kind of error. ![]() The authors applied the QC system to a continental-scale rain-gauge network. A total of 14 components have been developed for daily rain-gauge data, but many of the components can easily be applied to other weather elements such as temperature with appropriate changes in parameters. This QC system was basically designed to detect obvious errors such as clerical errors automatically and objectively. An automated quality control (QC) system was developed for detecting errors in daily rain-gauge data.
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