scholarly journals A Cloud-Resolving 4DVAR Assimilation Experiment for a Local Heavy Rainfall Event in the Tokyo Metropolitan Area

2011 ◽  
Vol 139 (6) ◽  
pp. 1911-1931 ◽  
Author(s):  
Takuya Kawabata ◽  
Tohru Kuroda ◽  
Hiromu Seko ◽  
Kazuo Saito
Keyword(s):  
Data Assimilation ◽  
Metropolitan Area ◽  
Heavy Rainfall ◽  
Rainfall Event ◽  
Radar Reflectivity ◽  
Heavy Rainfall Event ◽  
Convective System ◽  
Single Observation ◽  
Assimilation Experiment ◽  
Reflectivity Data

Abstract A cloud-resolving nonhydrostatic four-dimensional variational data assimilation system (NHM-4DVAR) was modified to directly assimilate radar reflectivity and applied to a data assimilation experiment using actual observations of a heavy rainfall event. Modifications included development of an adjoint model of the warm rain process, extension of control variables, and development of an observation operator for radar reflectivity. The responses of the modified NHM-4DVAR were confirmed by single-observation assimilation experiments for an isolated deep convection, using pseudo-observations of rainwater at the initial and end times of the data assimilation window. The results showed that the intensity of convection could be adjusted by assimilating appropriate observations of rainwater near the convection and that undesirable convection could be suppressed by assimilating small or no reflectivity. An assimilation experiment using actual observations of a local heavy rainfall in the Tokyo, Japan, metropolitan area was conducted with a horizontal resolution of 2 km. Precipitable water vapor derived from global positioning system data was assimilated at 5-min intervals within 30-min assimilation windows, and surface and wind profiler data were assimilated at 10-min intervals. Doppler radial wind and radar-reflectivity data below the elevation angle of 5.4° were assimilated at 1-min intervals. The 4DVAR assimilation reproduced a line-shaped rainband with a shape and intensity consistent with the observation. Assimilation of radar-reflectivity data intensified the rainband and suppressed false convection. The simulated rainband lasted for 1 h in the extended forecast and then gradually decayed. Sustaining the low-level convergence produced by northerly winds in the western part of the rainband was key to prolonging the predictability of the convective system.

scholarly journals Assimilation of Doppler Radar Data and Its Impact on Prediction of a Heavy Meiyu Frontal Rainfall Event

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Hongli Li ◽  
Xiangde Xu ◽  
Yang Hu ◽  
Yanjiao Xiao ◽  
Zhibin Wang
Keyword(s):  
Heavy Rainfall ◽  
Doppler Radar ◽  
Radar Data ◽  
Correction Method ◽  
Rainfall Event ◽  
Radar Reflectivity ◽  
Local Analysis ◽  
Heavy Rainfall Event ◽  
Radar Observations ◽  
Reflectivity Data

Operational Doppler radar observations have potential advantages over other above-surface observations when it comes to assimilation for mesoscale model simulations with high spatial and temporal resolution. To improve the forecast of a heavy frontal rainfall event that occurred in the Yangtze-Huaihe River Basin from 4 July to 5 July 2014 in China, operational radar observations are assimilated by the Local Analysis and Prediction System (LAPS). Radar reflectivity data are used primarily in the LAPS cloud analysis procedure, which retrieves the number of hydrometeors and adjusts the moisture and cloud fields. Radial velocity data are analyzed through the LAPS wind analysis-based successive correction method. A new correction method is developed to correct three-dimensional radar reflectivity data based on hourly surface rain gauge observations. The performance of the correction method is demonstrated by assimilating radar reflectivity observations into LAPS. Experiments with different radar data assimilation are examined. Results show that the assimilation of radar data can effectively correct the background errors and improve the heavy rainfall forecast. The simulated intensity, pattern, and temporal evolution of the heavy rainfall event are better improved with radar reflectivity assimilation, especially when the correction method is implemented to correct radar observations.

scholarly journals A Comparative Study on Performance of Analysis Nudging and 3DVAR in Simulation of a Heavy Rainfall Event Using WRF Modeling System

2012 ◽  
Vol 2012 ◽  
pp. 1-21 ◽  
Author(s):  
Ashish Routray ◽  
Krishna K. Osuri ◽  
Makarand A. Kulkarni
Keyword(s):  
Data Assimilation ◽  
Heavy Rainfall ◽  
Three Dimensional ◽  
Correlation Coefficients ◽  
Rainfall Event ◽  
Initial Time ◽  
Heavy Rainfall Event ◽  
Synoptic Features ◽  
Wrf Modeling ◽  
Data Assimilation Technique

The present study focuses on the performance-based comparison of simulations carried out using nudging (NUD) technique and three-dimensional variational (3DVAR) data assimilation system (3DV) of a heavy rainfall event occurred during 25–28 June 2005 along the west coast of India. The Indian conventional and nonconventional observations are used in the 3DV experiment. Three numerical experiments are conducted using WRF modeling system, the model is integrated upto 54 hours from the initial time 0000 UTC of 25 June 2005. It is noticed that the meteorological parameters are improved in the resulting high-resolution analyses prepared by NUD and 3DV compared to without data assimilation experiment (i.e., called CNTL experiment). However, after the successful inclusion of observations using the 3DVAR data assimilation technique, the model is able to simulate better structure of the convective organization as well as prominent synoptic features associated with the mid-tropospheric cyclones (MTC) than the NUD experiment and well correlated with the observations. The simulated location and intensity of rainfall is also improved in 3DV simulation as compared with other experiments. Similar results are noticed in the root mean squar errors, correlation coefficients, and Equitable Threat Scores between TRMM and model simulated rainfall for all the three experiments.

scholarly journals Numerical Simulations and Analysis of June 16, 2010 Heavy Rainfall Event over Singapore Using the WRFV3 Model

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
B. H. Vaid
Keyword(s):  
Numerical Simulations ◽  
Heavy Rainfall ◽  
Global Analysis ◽  
Heavy Rain ◽  
Rainfall Event ◽  
Cumulus Parameterization ◽  
Heavy Rainfall Event ◽  
Convective System ◽  
Rain Event ◽  
Simulated Precipitation

The Numerical Simulations of the June 16, 2010, Heavy Rainfall Event over Singapore are highlighted by an unprecedented precipitation which produced widespread, massive flooding in and around Singapore. The objective of this study is to check the ability of Weather Research Forecasting version 3 (WRFV3) model to predict the heavy rain event over Singapore. Results suggest that simulated precipitation amounts are sensitive to the choice of cumulus parameterization. Various model configurations with initial and boundary conditions from the NCEP Final Global Analysis (FNL), convective and microphysical process parameterizations, and nested-grid interactions have been tested with 48-hour (June 15–17, 2010) integrations of the WRFV3. The spatial distributions of large-scale circulation and dynamical and thermodynamical fields have been simulated reasonably well in the model. The model produced maximum precipitation of ~5 cm over Changi airport which is very near to observation (6.4 cm recorded at Changi airport). The model simulated dynamic and thermodynamic features at 00UTC of June 16, 2010, lead to understand the structure of the mesoscale convective system (MCS) that caused the extreme precipitation over Singapore. It is observed that Singapore heavy rain was the result of an interaction of synoptic-scale weather systems with the mesoscale features.

scholarly journals Roles of Land and Topography on Propagating Convective Systems During the Heavy Rainfall Event of the 2002 Jakarta Flood, Indonesia

2021 ◽  
Author(s):  
Erma Yulihastin ◽  
Danang Eko Nuryanto ◽  
Robi Muharsyah
Keyword(s):  
Heavy Rainfall ◽  
Weather Prediction ◽  
Rainfall Event ◽  
Movement Direction ◽  
Heavy Rainfall Event ◽  
Convective System ◽  
Upward Motion ◽  
West Java ◽  
Convective Systems

The movement direction of propagating convective systems originating from both inland and offshore over the north coast of West Java in Indonesia is determined primarily by the prevailing wind. However, the role of a land-sea contrast and a rugged topography over southern West Java is also expected to affect propagating convective systems by increasing land-sea breezes and enhancing upward motion. These hypotheses are tested using a weather prediction model incorporating convection (up to 3 km height) to simulate the heavy rainfall event during 26–29 January associated with the 2002 Jakarta flood. First, we addressed the influence of land-sea contrast and topography on the local circulation, particularly in the area surrounding Jakarta, by replacing the inland topography over western Indonesia (96°–119°E, 17°S–0°) with a water body with an altitude of 0 m. We then compared the results of model simulations with and without topography. The results show that the main role of the topography here is enhancing the upward motion and generating a deep convective cloud in response to the land-based convective system during 26–27 January 2002, which then continuously and rapidly propagates offshore due to the cold pool mechanism. Furthermore, the land-sea contrast has a significant role in increasing sea breeze under the rapidness of the landward propagation system during 28–29 January 2002, which was strengthened by the gravity waves and resulted in early morning convection over coastal regions.

scholarly journals X-Net-Based Radar Data Assimilation Study over the Seoul Metropolitan Area

2020 ◽  
Vol 12 (5) ◽  
pp. 893 ◽  
Author(s):  
Ji-Won Lee ◽  
Ki-Hong Min ◽  
Young-Hee Lee ◽  
GyuWon Lee
Keyword(s):  
Data Assimilation ◽  
Radial Velocity ◽  
Metropolitan Area ◽  
Numerical Data ◽  
Radar Data ◽  
Radar Reflectivity ◽  
Model Verification ◽  
Seoul Metropolitan Area ◽  
X Band ◽  
Reflectivity Data

This study investigates the ability of the high-resolution Weather Research and Forecasting (WRF) model to simulate summer precipitation with assimilation of X-band radar network data (X-Net) over the Seoul metropolitan area. Numerical data assimilation (DA) experiments with X-Net (S- and X-band Doppler radar) radial velocity and reflectivity data for three events of convective systems along the Changma front are conducted. In addition to the conventional assimilation of radar data, which focuses on assimilating the radial velocity and reflectivity of precipitation echoes, this study assimilates null-echoes and analyzes the effect of null-echo data assimilation on short-term quantitative precipitation forecasting (QPF). A null-echo is defined as a region with non-precipitation echoes within the radar observation range. The model removes excessive humidity and four types of hydrometeors (wet and dry snow, graupel, and rain) based on the radar reflectivity by using a three-dimensional variational (3D-Var) data assimilation technique within the WRFDA system. Some procedures for preprocessing radar reflectivity data and using null-echoes in this assimilation are discussed. Numerical experiments with conventional radar DA over-predicted the precipitation. However, experiments with additional null-echo information removed excessive water vapor and hydrometeors and suppressed erroneous model precipitation. The results of statistical model verification showed improvements in the analysis and objective forecast scores, reducing the amount of over-predicted precipitation. An analysis of a contoured frequency by altitude diagram (CFAD) and time–height cross-sections showed that increased hydrometeors throughout the data assimilation period enhanced precipitation formation, and reflectivity under the melting layer was simulated similarly to the observations during the peak precipitation times. In addition, overestimated hydrometeors were reduced through null-echo data assimilation.

scholarly journals Convective-Scale Sampling Error and Its Impact on the Ensemble Radar Data Assimilation System: A Case Study of a Heavy Rainfall Event on 16 June 2008 in Taiwan

2020 ◽  
Vol 148 (9) ◽  
pp. 3631-3652
Author(s):  
Pin-Ying Wu ◽  
Shu-Chih Yang ◽  
Chih-Chien Tsai ◽  
Hsiang-Wen Cheng
Keyword(s):  
Data Assimilation ◽  
Heavy Rainfall ◽  
Sampling Error ◽  
Rainfall Event ◽  
Heavy Rainfall Event ◽  
Observation Error ◽  
Sampling Errors ◽  
Precipitation Prediction ◽  
Convective Scale ◽  
Assimilation System

ABSTRACT Sampling error stems from the use of ensemble-based data assimilation (EDA) with a limited ensemble size and can result in spurious background error covariances, leading to false analysis corrections. The WRF-LETKF radar assimilation system (WLRAS) is performed separately with 256 and 40 members to investigate the characteristics of convective-scale sampling errors in the EDA and its impact on precipitation prediction based on a heavy rainfall event on 16 June 2008. The results suggest that the sampling errors for this event are sensitive to the relationships between the simulated observations and model variables, the intensity of reflectivity, and how the prevailing wind projects to the radial wind in the areas that the radar cannot resolve U or V wind. The sampling errors lead to an underprediction of heavy rainfall when the horizontal localization radius is inadequately large, but this can be mitigated when a more accurate moisture condition is provided. In addition, being able to use a larger vertical localization plays an important role in providing necessary adjustments for representing the vertical thermodynamical structure of convection, which further improves precipitation prediction. A strategy mitigating the impact of sampling errors associated with the limitation of radial wind measurement by inflating the observation error over sensitive areas can bring benefits to precipitation prediction.

Sign in / Sign up

Export Citation Format

Share Document