Investigating the Influence of Water Vapor on Heavy Rainfall Events in the Southern Korean Peninsula

Kim, Yoo-Jun; Jee, Joon-Bum; Lim, Byunghwan

doi:10.3390/rs15020340

Cited by 4 publications

(2 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The terrain of the study area is relatively flat, but micro-terrain features such as the northern mountainous region and the southern hills affect the formation, intensity, and spatial-temporal distribution of extreme rainfall to a certain degree by influencing atmospheric stability, wind fields, and water vapor transport, among other factors [90]. Mountains can affect the generation of extreme precipitation by lifting or blocking low-level airflow and inducing substantial rain when unstable airflow impacts the terrain [91,92]. Meanwhile, the terrain affects atmospheric water vapor transport, and upward airflow can cause convective precipitation, enhancing precipitation intensity.…”

Section: Discussionmentioning

confidence: 99%

Spatiotemporal Variation of Hourly Scale Extreme Rainstorms in the Huang-Huai-Hai Plain and Its Impact on NDVI

Zuo

2023

Remote Sensing

View full text Add to dashboard Cite

This paper utilizes high-resolution ERA5 hourly data from 1980 to 2020 and long-term normalized difference vegetation index (NDVI) time series obtained from remote sensing and applies trend analysis, correlation analysis, lag analysis, and other methods to study the spatiotemporal characteristics of extreme rainfall at daily and hourly scales in the Huang-Huai-Hai Plain. The paper explores the NDVI’s variability and its relationship with extreme hourly precipitation and analyzes the main factors affecting it. The study made the following observations: (1) The extreme daily precipitation in the Huang-Huai-Hai Plain shows a decreasing trend, with a 13.6 mm/yr reduction rate. In contrast, the proportion of extreme rainfall to total precipitation generally exceeds 20%, and the intensity of extreme rain has gradually increased. The spatial distribution pattern of extreme rainfall follows the distribution pattern of China’s rain belts, with the terrain being an important influencing factor. The high-incidence areas for extreme rainfall are the Huaihe River region and the Shandong Peninsula. (2) The observed significant increase in hourly extreme precipitation events in the Shandong and Henan provinces of the Huang-Huai-Hai Plain has led to an increased risk of flooding, while the corresponding events in the northwest region of the Plain have exhibited a gradual weakening trend over time. (3) The extreme hourly precipitation in the Huang-Huai-Hai plain shows a frequent and scattered pattern, with decreasing intensity over time. Extreme precipitation mainly occurs in the first half of the night, especially between 19:00 and 21:00, with extreme hourly rainfall intensity fluctuating between 0.2 and 0.25 and the proportion of rainfall to total precipitation reaching as high as 10%. The spatial distribution of extreme hourly rainstorms during the peak period (19:00–21:00) exhibits a high rainfall volume, intensity, and frequency pattern in the eastern region, while the western part exhibits low rainfall volume, intensity, and frequency. (4) The incidence of extremely heavy rainfall in an hour has exhibited a more significant increase compared to extreme daily events in the Huang-Huai-Hai Plain, primarily in the form of backward-type precipitation. Hourly extreme precipitation events in the Huang-Huai-Hai Plain are affected by terrain and land use/cover change (LUCC), with the micro-topography of hilly areas leading to a concentrated distribution of precipitation and LUCC suppressing extreme precipitation events in arid climates. (5) At the ten-day scale, the spatial distribution of the NDVI shows a gradually increasing trend from northwest to southeast, with the highest NDVI value reaching up to 0.6 in the southern part of the study area. For extreme hourly precipitation, there is no significant change observed at the multi-year ten-day scale; while the NDVI in the northern and central parts of the Huang-Huai-Hai Plain shows a significant decreasing trend, in contrast, it presents a significant increasing trend in the southern region. (6) Finally, the correlation between NDVI at the ten-day scale and extreme hourly precipitation exhibits a decreasing pattern from north to south, with a correlation coefficient decreasing from 0.48 to 0.08. The lagged correlation analysis of extreme hourly rainfall and NDVI for one, two, and three ten-day periods shows that the lagged effect of extreme hourly precipitation on NDVI is negligible. Analyzing the correlation between extreme hourly rainfall and NDVI for different months, the impact of extreme hourly precipitation on NDVI is predominantly negative, except for June, which shows a positive correlation (0.35), passing the significance test. This study offers a scientific foundation for enhancing disaster warning accuracy and timeliness and strengthening the research on disaster reduction techniques.

show abstract

Section: Discussionmentioning

confidence: 99%

Spatiotemporal Variation of Hourly Scale Extreme Rainstorms in the Huang-Huai-Hai Plain and Its Impact on NDVI

Zuo

2023

Remote Sensing

View full text Add to dashboard Cite

show abstract

“…To explore the temporal and spatial interaction characteristics of PWV and actual rainfall during typhoon 'Chandu' and three other typhoon events in Taiwan from 2015 to 2017, they were investigated using the PWV retrieved from the real-time precise point positioning technology or ground-based GPS data [22,23]. Kim et al found that the most intense rainfall events occurred after a rapid increase in PWV along with a strong southwesterly water-vapor flow during convective instability [24]. Zhao et al used the anomalous variations of the PWV inverted by ERA5 with other atmospheric parameters related to typhoons to analyze a typhoon-monitoring method with and without considering the typhoon's acceleration during the time of the maximum value of the PWV during the typhoon period [25].…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Temporal and Spatial Characteristics of PWV and Rainfall with the Typhoon Movement: A Case Study of ‘Meihua’ in 2022

Li,

Wang,

Wei

et al. 2023

Atmosphere

View full text Add to dashboard Cite

The serious and frequent typhoon activities can easily cause extreme precipitation weather in the eastern coastal area of China, which is affected by land and sea differences. To explore the temporal and spatial characteristics of Precipitable Water Vapor (PWV) and rainfall during the typhoon period, the data of the conspicuous case named ‘Meihua’ in 2022 is adopted in analysis. In this paper, firstly, the accuracy of the PWV retrieved by ERA5 was evaluated, which met the experimental analysis requirements, compared with the conference value of the Radiosonde (RS). Secondly, the correlation between PWV, rainfall and the typhoon path were analyzed qualitatively and quantitatively, using 16 meteorological stations in the typhoon path. The results indicated that PWV reached its peak value 2–6 h than rainfall, which was an important reference for rainfall forecasting. Then, the ‘Pearson correlation coefficient’ method was used for the quantitative evaluation of the correlation between PWV and the distance of the ‘weather station-typhoon’. The results showed that PWV had an obvious upward trend, with a decrease in the distance between the ‘weather station-typhoon’. The variation in PWV is intense at a reduced distance, and can reach its peak 16 h before the arrival of the typhoon. A strong negative correlation was demonstrated, with an average value of −0.73 for the Pearson correlation coefficient. Analyzing the temporal and spatial changes of the typhoon track, PWV and rainfall, the results show that before the typhoon passes through the region, both the PWV and rainfall certainly reach their maximum. The variation trends of PWV and rainfall in the period of the typhoon are significantly consistent. The center of PWV and rainfall is mainly located on the northwest side of the typhoon center, which showed obvious asymmetry.

show abstract

Modeling trends and periodic components in geodetic time series: a unified approach

Kermarrec,

Maddanu,

Klos

et al. 2024

J Geod

View full text Add to dashboard Cite

Geodetic time series are usually modeled with a deterministic approach that includes trend, annual, and semiannual periodic components having constant amplitude and phase-lag. Although simple, this approach neglects the time-variability or stochasticity of trend and seasonal components, and can potentially lead to inadequate interpretations, such as an overestimation of global navigation satellite system (GNSS) station velocity uncertainties, up to masking important geophysical phenomena. In this contribution, we generalize previous methods for determining trends and seasonal components and address the challenge of their time-variability by proposing a novel linear additive model, according to which (i) the trend is allowed to evolve over time, (ii) the seasonality is represented by a fractional sinusoidal waveform process (fSWp), accounting for possible non-stationary cyclical long-memory, and (iii) an additional serially correlated noise captures the short term variability. The model has a state space representation, opening the way for the evaluation of the likelihood and signal extraction with the support of the Kalman filter (KF) and the associated smoothing algorithm. Suitable enhancements of the basic methodology enable handling data gaps, outliers, and offsets. We demonstrate the advantage of our method with respect to the benchmark deterministic approach using both observed and simulated time series and provide a fair comparison with the Hector software. To that end, various geodetic time series are considered which illustrate the ability to capture the time-varying stochastic seasonal signals with the fSWp.

show abstract

Investigating the Influence of Water Vapor on Heavy Rainfall Events in the Southern Korean Peninsula

Cited by 4 publications

References 36 publications

Spatiotemporal Variation of Hourly Scale Extreme Rainstorms in the Huang-Huai-Hai Plain and Its Impact on NDVI

Spatiotemporal Variation of Hourly Scale Extreme Rainstorms in the Huang-Huai-Hai Plain and Its Impact on NDVI

Analysis of the Temporal and Spatial Characteristics of PWV and Rainfall with the Typhoon Movement: A Case Study of ‘Meihua’ in 2022

Modeling trends and periodic components in geodetic time series: a unified approach

Contact Info

Product

Resources

About