{"title":"High-Resolution simulations of Heavy-Rain-Producing Mesoscale Convective Systems using Cloud-Resolving models","authors":"K. Tsuboki","doi":"10.54302/mausam.v74i2.6029","DOIUrl":null,"url":null,"abstract":"In East Asia, heavy-rain-producing mesoscale convective systems (MCSs) often develop in monsoon systems and cause severe floods and landslides. To understand and forecast these high-resolution simulations using cloud-resolving models (CRMs) are necessary. Tsuboki and Luo (2020) reviewed recent studies of MCSs using CRMs and remarked that data assimilation (DA) of radar observations to CRMs is promising for the improvement of simulation and numerical weather prediction (NWP) of MCSs. The DA of radar observations to CRMs is very effective for short-range NWP of MCSs using CRMs. Various convective-scale DAs have been developed to improve the NWP of heavy-rain-producing MCSs. Following Tsuboki and Luo (2020), this paper introduces recent studies on MCS using CRMs, phased array weather radars and DAs of radar observations.","PeriodicalId":18363,"journal":{"name":"MAUSAM","volume":" ","pages":""},"PeriodicalIF":0.7000,"publicationDate":"2023-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"MAUSAM","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.54302/mausam.v74i2.6029","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
In East Asia, heavy-rain-producing mesoscale convective systems (MCSs) often develop in monsoon systems and cause severe floods and landslides. To understand and forecast these high-resolution simulations using cloud-resolving models (CRMs) are necessary. Tsuboki and Luo (2020) reviewed recent studies of MCSs using CRMs and remarked that data assimilation (DA) of radar observations to CRMs is promising for the improvement of simulation and numerical weather prediction (NWP) of MCSs. The DA of radar observations to CRMs is very effective for short-range NWP of MCSs using CRMs. Various convective-scale DAs have been developed to improve the NWP of heavy-rain-producing MCSs. Following Tsuboki and Luo (2020), this paper introduces recent studies on MCS using CRMs, phased array weather radars and DAs of radar observations.
期刊介绍:
MAUSAM (Formerly Indian Journal of Meteorology, Hydrology & Geophysics), established in January 1950, is the quarterly research
journal brought out by the India Meteorological Department (IMD). MAUSAM is a medium for publication of original scientific
research work. MAUSAM is a premier scientific research journal published in this part of the world in the fields of Meteorology,
Hydrology & Geophysics. The four issues appear in January, April, July & October.