Exploring the effect of data assimilation by WRF-3DVar for numerical rainfall prediction with different types of storm events

2012 ◽  
Vol 27 (25) ◽  
pp. 3627-3640 ◽  
Author(s):  
Jia Liu ◽  
Michaela Bray ◽  
Dawei Han
Keyword(s):  
Data Assimilation ◽  
Storm Events ◽  
Rainfall Prediction ◽  
Different Types

scholarly journals Statistics of Simulated Storm Waves over Bathymetry

2021 ◽  
Vol 9 (7) ◽  
pp. 784
Author(s):  
Arnida Lailatul Latifah ◽  
Durra Handri ◽  
Ayu Shabrina ◽  
Henokh Hariyanto ◽  
E. van Groesen
Keyword(s):  
Water Waves ◽  
Open Water ◽  
Storm Events ◽  
Extreme Waves ◽  
Marine Structures ◽  
Wave Statistics ◽  
Storm Waves ◽  
Different Types ◽  
Run Up ◽  
Good Agreement

This paper shows simulations of high waves over different bathymetries to collect statistical information, particularly kurtosis and crest exceedance, that quantifies the occurrence of exceptionally extreme waves. This knowledge is especially pertinent for the design and operation of marine structures, safe ship trafficking, and mooring strategies for ships near the coast. Taking advantage of the flexibility to perform numerical simulations with HAWASSI software, with the aim of investigating the physical and statistical properties for these cases, this paper investigates the change in wave statistics related to changes in depth, breaking and differences between long- and short-crested waves. Three different types of bathymetry are considered: run-up to the coast with slope 1/20, waves over a shoal, and deep open-water waves. Simulations show good agreement in the examined cases compared with the available experimental data and simulations. Then predictive simulations for cases with a higher significant wave height illustrate the changes that may occur during storm events.

Exfiltration from gravity sewers: a pilot scale study

2003 ◽  
Vol 47 (4) ◽  
pp. 69-76 ◽  
Author(s):  
J. Vollertsen ◽  
T. Hvitved-Jacobsen
Keyword(s):  
Groundwater Pollution ◽  
Pilot Scale ◽  
Storm Events ◽  
Sewer Network ◽  
Leakage Factor ◽  
Different Types ◽  
Different Soils

Pilot-scale experiments were conducted on exfiltration of wastewater from gravity sewers. The effect of storm events, flushing of pipes and alternating infiltration/exfiltration were simulated. Exfiltration through different types of sewer leaks and into different soils were studied. It was found that the exfiltration rate became constant after some days of exfiltration. It stayed constant for the duration of the experiments, which typically spanned over some weeks. The exfiltration was governed by the development of a clogging zone at the sewer leak and could be characterized by a leakage factor. The leakage factor may then be used to estimate the risk of groundwater pollution from a sewer network.

scholarly journals Typhoon rainstorm simulations with radar data assimilation on the southeast coast of China

2021 ◽  
Vol 21 (2) ◽  
pp. 723-742
Author(s):  
Jiyang Tian ◽  
Ronghua Liu ◽  
Liuqian Ding ◽  
Liang Guo ◽  
Bingyu Zhang
Keyword(s):  
Data Assimilation ◽  
Doppler Radar ◽  
Weather Prediction ◽  
Radar Data ◽  
Time Interval ◽  
Storm Events ◽  
Catchment Scale ◽  
Southeast Coast ◽  
Assimilation Time ◽  
Radar Data Assimilation

Abstract. As an effective technique to improve the rainfall forecast, data assimilation plays an important role in meteorology and hydrology. The aim of this study is to explore the reasonable use of Doppler radar data assimilation to correct the initial and lateral boundary conditions of the numerical weather prediction (NWP) systems. The Weather Research and Forecasting (WRF) model is applied to simulate three typhoon storm events on the southeast coast of China. Radar data from a Doppler radar station in Changle, China, are assimilated with three-dimensional variational data assimilation (3-DVar) model. Nine assimilation modes are designed by three kinds of radar data and at three assimilation time intervals. The rainfall simulations in a medium-scale catchment, Meixi, are evaluated by three indices, including relative error (RE), critical success index (CSI), and root mean square error (RMSE). Assimilating radial velocity at a time interval of 1 h can significantly improve the rainfall simulations, and it outperforms the other modes for all the three storm events. Shortening the assimilation time interval can improve the rainfall simulations in most cases, while assimilating radar reflectivity always leads to worse simulations as the time interval shortens. The rainfall simulations can be improved by data assimilation as a whole, especially for the heavy rainfall with strong convection. The findings provide references for improving the typhoon rainfall forecasts at catchment scale and have great significance on typhoon rainstorm warning.

scholarly journals Satellite radiance data assimilation for rainfall prediction in Java Region

2017 ◽  
Vol 54 ◽  
pp. 012037 ◽  
Author(s):  
Novvria Sagita ◽  
Rini Hidayati ◽  
Rahmat Hidayat ◽  
Indra Gustari
Keyword(s):  
Data Assimilation ◽  
Rainfall Prediction ◽  
Satellite Radiance Data ◽  
Radiance Data

scholarly journals Typhoon rainstorm simulation with radar data assimilation in southeast coast of China

2020 ◽  
Author(s):  
Jiyang Tian ◽  
Ronghua Liu ◽  
Liuqian Ding ◽  
Liang Guo ◽  
Bingyu Zhang
Keyword(s):  
Data Assimilation ◽  
Radial Velocity ◽  
Doppler Radar ◽  
Radar Data ◽  
Radar Reflectivity ◽  
Time Interval ◽  
Storm Events ◽  
Southeast Coast ◽  
Assimilation Time ◽  
Radar Data Assimilation

Abstract. As an effective technique to improve the rainfall forecast, data assimilation plays an important role in meteorology and hydrology. The aim of this study is to explore the reasonable use of Doppler radar data assimilation to correct the initial and lateral boundary conditions of the Numerical Weather Prediction (NWP) systems. The Weather Research and Forecasting (WRF) model is applied to simulate three typhoon storm events in southeast coast of China. Radar data from Changle Doppler radar station are assimilated with three-dimensional variational data assimilation (3-DVar) model. Nine assimilation modes are designed by three kinds of radar data (radar reflectivity, radial velocity, radar reflectivity and radial velocity) and three assimilation time intervals (1 h, 3 h and 6 h). The rainfall simulations in a medium-scale catchment, Meixi, are evaluated by three indices including relative error (RE), critical success index (CSI) and root mean square error (RMSE). Assimilating radial velocity with time interval of 1 h can significantly improve the rainfall simulations and outperforms the other modes for all the three storm events. Shortening the assimilation time interval can improve the rainfall simulations in most cases, while assimilating radar reflectivity always leads to worse simulation as the time interval shortens. The rainfall simulation can be improved by data assimilation as a whole, especially for the heavy rainfall with strong convection. The findings provide references for improving the typhoon rainfall forecasts in catchment scale and have great significance on typhoon rainstorm warning.

scholarly journals Data Assimilation for Bathymetry Estimation at a Tidal Inlet

2016 ◽  
Vol 33 (10) ◽  
pp. 2145-2163 ◽  
Author(s):  
S. Moghimi ◽  
H. T. Özkan-Haller ◽  
G. W. Wilson ◽  
A. Kurapov
Keyword(s):  
Data Assimilation ◽  
Synthetic Data ◽  
Tidal Inlet ◽  
Current Data ◽  
Radar System ◽  
Surface Velocity ◽  
Tidal Circulation ◽  
X Band ◽  
Different Types ◽  
Synthetic Aperture Radar System

AbstractThis study involved developing and testing a data assimilation framework that accommodates different types of geophysical ocean data (i.e., surface velocity and wave information) and provides an estimation of the bathymetry of a mixed-energy tidal inlet. This framework was successfully applied to a highly variable tidal environment using synthetic data (twin test). The synthetic data consisted of surface velocity components associated with the tidal circulation and wavenumber–frequency pairs of incoming surface gravity waves that mimic data that could be derived from an airborne synthetic aperture radar system and a tower-mounted X-band radar system, respectively. The present ensemble-based assimilation framework has previously been applied in both wave-dominated coastal and current-dominated riverine environments. In contrast, the inlet environment is neither wave nor current dominated. The assimilation of wave and current data together was most useful to obtain a skillful estimate of the spatial map of bathymetry.

scholarly journals Investigation of Data Assimilation Methods for Soil Parameter Estimation with Different Types of Data

2019 ◽  
Vol 18 (1) ◽  
pp. 190013 ◽  
Author(s):  
Yuanyuan Zha ◽  
Penghui Zhu ◽  
Qiuru Zhang ◽  
Wei Mao ◽  
Liangsheng Shi
Keyword(s):  
Parameter Estimation ◽  
Data Assimilation ◽  
Soil Parameter ◽  
Different Types

GUERRILLA HEAVY RAINFALL PREDICTION BY DATA ASSIMILATION OF SIMULATED CLOUD OBSERVATION

2018 ◽  
Vol 74 (4) ◽  
pp. I_61-I_66
Author(s):  
Kosei YAMAGUCHI ◽  
Kazuki UESHIMA ◽  
Yosuke HORIIKE ◽  
Eiichi NAKAKITA
Keyword(s):  
Data Assimilation ◽  
Heavy Rainfall ◽  
Rainfall Prediction
Sign in / Sign up

Export Citation Format

Share Document