Ensemble Kalman filter assimilation of Doppler radar data with a compressible nonhydrostatic model: OSS Experiments Mingjing Tong and Ming Xue* School of Meteorology and Center for Analysis and Prediction of Storms
نویسنده
چکیده
منابع مشابه
Impact of Configurations of Rapid Intermittent Assimilation of Wsr-88d Radar Data for the 8 May 2003 Oklahoma City Tornadic Thunderstorm Case
The operational WSR-88D Doppler radar network of the United States (Crum and Alberty 1993) has dramatically improved the ability of severe weather warning in routine operations (Serafin and Wilson 2000); it is also playing an important role in storm-scale data assimilation and model initialization, because it is the only observational network that can resolve convective storms. However, the ana...
متن کاملP1.44 The Issue of Data Density and Frequency with EnKF Radar Data Assimilation in a Compressible Nonhydrostatic NWP Model
1. Introduction Since its first introduction by Evensen (1994), the ensemble Kalman filter (EnKF) technique for data assimilation has received much attention. Rather than solving the equation for the time evolution of the probability density function of model state, the EnKF methods apply the Monte Carlo method to estimate the forecast error statistics. A large ensemble of model states are inte...
متن کاملData Assimilation and Prediction at the Convective Scale: Recent Progresses
In this paper, we briefly present some recent results of initialization and prediction of convectivescale weather systems using a high-resolution numerical model and its data assimilation systems. For cases with pre-existing storms, the WSR-88D radar data are assimilated, at 5 to 15 minute intervals, over a typically one-hour assimilation window, using three-dimensional variational (3DVAR) meth...
متن کاملThe Impact of T - TREC - retrieved Wind and Radial Velocity Data Assimilation 5 using EnKF and
8 Mingjun Wang1,2, Ming Xue1,2,3 and Kun Zhao1 9 1Key Laboratory for Mesoscale Severe Weather/MOE and School of Atmospheric 10 Science, Nanjing University, Nanjing, China 11 12 2Center for Analysis and Prediction of Storms, and 3School of Meteorology, University of 13 Oklahoma, Norman, Oklahoma, 73072 14 15 16 July, 2015 17 Submitted to Journal of Geophysical Research 18 Revised October 2015 19 20
متن کاملError modeling of simulated reflectivity observations for ensemble Kalman filter assimilation of convective storms
[1] The impact of two different ways of modeling errors in simulated radar reflectivity data for observing system simulation experiments (OSSEs) with an ensemble Kalman filter is investigated. An error model different from the one used in earlier studies is introduced, and it specifies relative Gaussian-distributed errors in the linear domain of the equivalent radar reflectivity factor. This mo...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2004