Microphysical Characteristics of Precipitation during Pre-monsoon, Monsoon, and Post-monsoon Periods over the South China Sea

Zeng, Qingwei; Zhang, Yun; Lei, Hongxing; Xie, Yusheng; Gao, Taichang; Zhang, Lifeng; Wang, Chunming; Huang, Yulin

doi:10.1007/s00376-019-8225-8

Cited by 36 publications

(23 citation statements)

References 75 publications

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“…DOI 10.1175/JHM-D-21-0078.1. Unauthenticated | Downloaded 12/27/21 03:23 AM UTC over South China Sea, probably attributed to the differences in warm and cold rain processes, raindrop evaporation, convective activities, and other meteorological factors (Zeng et al 2019). The DSDs of tropical cyclones exhibit seasonal variations with more large drops in southwest monsoon than in northeast monsoon (Radhakrishna and Narayana Rao 2010).…”

Section: Introductionmentioning

confidence: 99%

Microphysics of Convective and Stratiform Precipitation during the Summer Monsoon Season over the Yangtze–Huaihe River Valley, China

Chen

Zheng

Hong

et al. 2022

Journal of Hydrometeorology

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Precipitation microphysics are critical for precipitation estimation and forecasting in numerical models. Using six years of observations from the Global Precipitation Measurement satellite, the spatial characteristics of precipitation microphysics are examined during the summer monsoon season over the Yangtze–Huaihe River valley. The results indicate that the heaviest convective rainfall is located mainly between the Huaihe and Yangtze Rivers, associated with a smaller mass-weighted mean diameter (Dm = ∼1.65 mm) and a larger mean generalized intercept parameter (Nw) (∼41 dBNw) at 2 km in altitude than those over the surrounding regions. Further, the convection in this region also has the lowest polarization-corrected temperature at 89 GHz (PCT89 < 254 K), indicating high concentrations of ice-hydrometeors. For a given rainfall intensity, stratiform precipitation is characterized by a smaller mean Dm than convective precipitation. Below 4.5 km in altitude, the vertical slope of medium reflectivity factor varies with the rainfall intensity, which decreases slightly downwards for light rain (< 2.5 mm h−1), increases slightly for moderate rain (2.5–7.9 mm h−1), and increases more sharply for heavy rain (≥8 mm h−1) for both convective and stratiform precipitation. The increase in the amplitude of heavy rain for stratiform precipitation is much higher than that for convective precipitation, probably due to more efficient growth by warm rain processes. The PCT89 values have a greater potential to inform the near-surface microphysical parameters in convective precipitation compared with stratiform precipitation.

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Section: Introductionmentioning

confidence: 99%

Microphysics of Convective and Stratiform Precipitation during the Summer Monsoon Season over the Yangtze–Huaihe River Valley, China

Chen

Zheng

Hong

et al. 2022

Journal of Hydrometeorology

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“…Existing methods for precipitation observation mainly include the tipping-bucket rain gauges (TBRGs) network and weather radars (WRs) [5]. A rain gauge network can provide more accurate rain intensity at fixed locations in the monitoring region, but its spatial representativeness is not sufficient for the disaster warning especially in complex terrain [6,7]. The weather radar achieves regional quantitative precipitation estimations (QPEs) with higher spatiotemporal resolution [8].…”

Section: Introductionmentioning

confidence: 99%

Reconstruction and Nowcasting of Rainfall Field by Oblique Earth-Space Links Network: Preliminary Results from Numerical Simulation

et al. 2020

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High-precision rainfall field reconstruction and nowcasting play an important role in many aspects of social life. In recent years, the rain-induced signal attenuation of oblique earth-space links (OELs) has been presented to monitor regional rainfall. In this paper, we set up the first OEL in Nanjing, China, for the estimation of rain intensity. A year of observations from this link are also compared with the measurements from laser disdrometer OTT-Parsivel (OTT), between which the correlation is 0.86 and the determination coefficient is 0.73. Then, the simulation experiment is carried out: an OELs network is built, and the Kriging interpolation algorithm is employed to perform rainfall field reconstruction. The rainfall fields of plum rain season from 2016 to 2019 have been reconstructed by this network, which shows a good agreement with satellite remote sensing data. The resulting root-mean-square errors are lower than 3.46 mm/h and spatial correlations are higher than 0.80. Finally, we have achieved the nowcasting of rainfall field based on a machine-learning approach, especially deep learning. It can be seen from experiment results that the motion of rain cell and the position of peak rain intensity are predicted successfully, which is of great significant for taking concerted actions in case of emergency. Our experiment demonstrates that the densely distributed OELs are expected to become a futuristic rainfall monitoring system complementing existing weather radar and rain gauge observation networks.

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“…Since the pioneering work of Marshall and Palmer [1948] on the rain DSDs, most of those which followed, such as [Atlas et al, 1999, Cerro et al, 1997, Chen et al, 2019, Tenorio et al, 2012, Tokay and Short, 1996, Uijlenhoet et al, 2003, Ulbrich, 1983, Ulbrich and Atlas, 1998, Wen et al, 2018, Willis, 1984, Zeng et al, 2019, Zhang et al, 2003etc. ], analyse it with N (D) function, defined by spectrum of a given period T (1 min).…”

Section: Methodsmentioning

confidence: 99%

“…When we assume a DSD model, the theoretical moment of order n of a rain DSD spectrum (whatever the integration time steps) is defined [Chapon et al, 2008, Lee et al, 2004, Ochou et al, 2007, Sempere-Torres et al, 1994, Zeng et al, 2019 by…”

Section: The Structuring Of the Measured Spectramentioning

confidence: 99%

Impact of integration time steps of rain drop size distribution on their structuring and their modelling: a case study in northern Benin

Moumouni¹,

Adjikpé²,

Lawin³

2021

Comptes Rendus. Géoscience

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Microphysical Characteristics of Precipitation during Pre-monsoon, Monsoon, and Post-monsoon Periods over the South China Sea

Cited by 36 publications

References 75 publications

Microphysics of Convective and Stratiform Precipitation during the Summer Monsoon Season over the Yangtze–Huaihe River Valley, China

Microphysics of Convective and Stratiform Precipitation during the Summer Monsoon Season over the Yangtze–Huaihe River Valley, China

Reconstruction and Nowcasting of Rainfall Field by Oblique Earth-Space Links Network: Preliminary Results from Numerical Simulation

Impact of integration time steps of rain drop size distribution on their structuring and their modelling: a case study in northern Benin

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