• Atmosphere
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• v.34 no.4
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• pp.337-347
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• 2024

This study reevaluated the Chukwookee precipitation records of the Diary of the Royal Secretariat and The Record of Daily Reflections, which are highly regarded as unprecedentedly long continuous meteorological records in world history. I have reconstructed them called "Hanyang Rainfall Data Set" (1770~1907). This dataset focuses on increased rainfall during 'leap monthly years' compared to regular years. Based on the analysis of First Hanyang Rainfall Data Set, leap monthly years (1,273.4 mm) were +6.0% higher than the overall annual average (1,201.6 mm), and +9.8% higher than 'non-leap monthly years' (1,159.6 mm). Upon further review using Second Modern Rainfall Data Set (1908~2019, 112 years), leap monthly years (1,369.1 mm) showed a +3.2% increase compared to the overall annual average (1,326.9 mm), and a +5.1% increase compared to non-leap monthly years (1,302.6 mm), demonstrating a consistent trend. When consolidated over the longest span of 250 years in Third Seoul Rainfall Data Set (1770~2019), leap monthly years (1,316.1 mm) were found to be +4.6% higher than the overall annual average (1,257.8 mm), and +7.5% higher than non-leap monthly years (1,223.8 mm). Furthermore, examining annual rainy days, leap monthly years in "Hanyang Rainfall Table" (56.3 days) showed a +3.9% increase compared to non-leap monthly years (54.2 days), indicating an overall increase in rainy days during leap monthly years. The occurrence of such peculiar increases in rainfall during leap monthly years could be attributed to meteorological changes throughout the year, caused by the additional intercalary month. However, specific academic discussions require consultation and evaluation from the meteorological community.

• The Korean Journal of Applied Statistics
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• v.13 no.2
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• pp.321-328
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• 2000

Working day variations caused by trading days, holidays and leap year make it difficult to analyze monthly or quarterly economic time series. In this paper, we adjust working day variations from economic time series via RegARIMA model.