scholarly journals Rainfall distribution in Yamuna catchment and quantitative estimation of heavy rainfall in related synoptic situations

MAUSAM ◽  
2021 ◽  
Vol 43 (3) ◽  
pp. 295-300
Author(s):  
Y. M. DUGGAL ◽  
H. S. SAGAR ◽  
A. K. MITTAL
Keyword(s):  
Moisture Transport ◽  
Heavy Rainfall ◽  
Quantitative Estimation ◽  
Rainfall Distribution

A study of rainfall over Yamuna catchment from its origin upto Delhi for the period from 1976to 1990 IS made with an attempt to understand the fine distribution of rainfall in different ranges over the catch-ment for the flood operational period from .1 June to 15 October. The study of associated synoptic situations for heavy rainfall activity in the catchment is made for synoptic typing. Synoptic empirical diagrams have been developed for estimation of average isohyetal rainfall over the catchment from estimation of moisture transport.

Diverse synoptic weather patterns of warm-season heavy rainfall events in South Korea

2021 ◽  
Author(s):  
Chanil Park ◽  
Seok-Woo Son ◽  
Joowan Kim ◽  
Eun-Chul Chang ◽  
Jung-Hoon Kim ◽  
...  
Keyword(s):  
North Pacific ◽  
Moisture Transport ◽  
Heavy Rainfall ◽  
Eastern China ◽  
Warm Season ◽  
Sea Level Pressure ◽  
Rainfall Events ◽  
Weather Patterns ◽  
Synoptic Weather ◽  
Heavy Rainfall Events

AbstractThis study identifies diverse synoptic weather patterns of warm-season heavy rainfall events (HREs) in South Korea. The HREs not directly connected to tropical cyclones (TCs) (81.1%) are typically associated with a midlatitude cyclone from eastern China, the expanded North Pacific high and strong southwesterly moisture transport in between. They are frequent both in the first (early summer) and second rainy periods (late summer) with impacts on the south coast and west of the mountainous region. In contrast, the HREs resulting from TCs (18.9%) are caused by the synergetic interaction between the TC and meandering midlatitude flow, especially in the second rainy period. The strong south-southeasterly moisture transport makes the southern and eastern coastal regions prone to the TC-driven HREs. By applying a self-organizing map algorithm to the non-TC HREs, their surface weather patterns are further classified into six clusters. Clusters 1 and 3 exhibit frontal boundary between the low and high with differing relative strengths. Clusters 2 and 5 feature an extratropical cyclone migrating from eastern China under different background sea-level pressure patterns. Cluster 4 is characterized by the expanded North Pacific high with no organized negative sea-level pressure anomaly, and cluster 6 displays a development of a moisture pathway between the continental and oceanic highs. Each cluster exhibits a distinct spatio-temporal occurrence distribution. The result provides useful guidance for predicting the HREs by depicting important factors to be differently considered depending on their synoptic categorization.

A Record Rainfall at Okinawa

1959 ◽  
Vol 40 (12) ◽  
pp. 609-612 ◽  
Author(s):  
C. L. Jordan ◽  
Michio Shiroma
Keyword(s):  
Heavy Rainfall ◽  
Weather Conditions ◽  
Rainfall Distribution ◽  
Maximum Rainfall

A maximum rainfall of 38 in. was recorded during an 18-hr period as a typhoon passed over the island of Okinawa in September 1956. The observed weather conditions during the typhoon passage are discussed in relationship to the observed rainfall distribution on the island and some comments are offered on the problems of evaluating the reliability of measurements of very heavy rainfall.

scholarly journals Relationships among Rainfall Distribution, Surface Wind, and Precipitable Water Vapor during Heavy Rainfall in Central Tokyo in Summer

2018 ◽  
Vol 96A (0) ◽  
pp. 35-49 ◽  
Author(s):  
Yoshihito SETO ◽  
Hitoshi YOKOYAMA ◽  
Tsuyoshi NAKATANI ◽  
Haruo ANDO ◽  
Nobumitsu TSUNEMATSU ◽  
...  
Keyword(s):  
Water Vapor ◽  
Heavy Rainfall ◽  
Surface Wind ◽  
Precipitable Water ◽  
Precipitable Water Vapor ◽  
Rainfall Distribution

scholarly journals Modeling of Heavy Rainfall Triggering Landslide Using WRF Model

Agromet ◽  
2020 ◽  
Vol 34 (1) ◽  
pp. 55-65
Author(s):  
Danang Eko Nuryanto ◽  
Yuaning Fajariana ◽  
Radyan Putra Pradana ◽  
Rian Anggraeni ◽  
Imelda Ummiyatul Badri ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Temporal Pattern ◽  
Heavy Rainfall ◽  
Wrf Model ◽  
Cloud Formation ◽  
Rainfall Distribution ◽  
Model Simulations ◽  
Starting Time ◽  
Landslide Event ◽  
Event Based

This study revealed the behavior of heavy rainfall before landslide event based on the Weather Research Forecasting (WRF) model. Simulations were carried out to capture the heavy rainfall patterns on 27 November 2018 in Kulonprogo, Yogyakarta. The modeling was performed with three different planetary boundary layer schemes, namely: Yonsei University (YSU), Sin-Hong (SH) and Bougeault and Lacarrere (BL). Our results indicated that the variation of rainfall distribution were small among schemes. The finding revealed that the model was able to capture the radar’s rainfall pattern. Based on statistical metric, WRF-YSU scheme was the best outperforming to predict a temporal pattern. Further, the study showed a pattern of rainfall development coming from the southern coastal of Java before 13:00 LT (Local Time=WIB=UTC+7) and continued to inland after 13:00 LT. During these periods, the new clouds were developed. Based on our analysis, the cloud formation that generated rainfall started at 10:00 LT, and hit a peak at 13:00 LT. A starting time of cloud generating rainfall may be an early indicator of landslide.

scholarly journals Moisture trajectories during heavy rainfall events using Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model

2021 ◽  
Vol 2070 (1) ◽  
pp. 012066
Author(s):  
S Aryalakshmi ◽  
Dhanya Madhu
Keyword(s):  
Single Particle ◽  
Moisture Transport ◽  
Heavy Rainfall ◽  
Back Trajectory ◽  
Hysplit Model ◽  
Monsoon Period ◽  
Back Trajectories ◽  
North East ◽  
The North ◽  
South West Monsoon

Abstract Heavy rainfall inducing other catastrophic events are frequently experienced globally. Understanding the mechanisms of moisture transport during such events will help in furthering our knowledge about such systems. In the current study, estimation of most likely moisture trajectoriesis performed using back trajectory analyses. Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model available from National Oceanic and Atmospheric Administration’s (NOAA) Air Resources Laboratory (ARL) is used for the purpose. A preliminary analysis is conducted by calculating the frequencies of back trajectories from two locations in Kerala for three heavy rainfall cases. The analysis indicates that both the locations have similar pattern of moisture trajectories during the cases occurring in south west monsoon and pre monsoon periods. However, a change in the behaviour of the trajectories for the two locations is observed for the case during the north east monsoon period. Since this study involved only individual cases, robust conclusions cannot be made based on this for the dynamics of moisture transport for these locations. More detailed analysis will follow this preliminary study in future for the purpose.

scholarly journals Rainfall distribution over Delhi State during monsoon

MAUSAM ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 57-66
Author(s):  
D. A. MOOLEY
Keyword(s):  
Spatial Distribution ◽  
Heavy Rainfall ◽  
Extreme Values ◽  
Monsoon Season ◽  
The State ◽  
Rainfall Distribution ◽  
Mean Values ◽  
The Mean ◽  
Rainy Days

Based on the data for the period 1939-1954, the mean values of rainfall and number of rainy days during the, monsoon season at the various raingauge stations as well as the extreme values of these have been given; spatial distribution of heavy, rainfall over the State and the incidence of heavy rainfall at the various location have been studied. From a study of the synoptic charts on days prior to the days on which local heavy rainfall over was reported, an attempt has been made to indicate the topical synoptic situations which usually lead to local heavy rainfall over Delhi State during the next 24hours.Typical situation ‘have been illustrated by charts.  

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