Local Ensemble Transform Kalman Filter: An Efficient Scheme for Assimilating Atmospheric Data

نویسندگان

  • John Harlim
  • Brian R. Hunt
چکیده

We present an efficient variation of the Local Ensemble Kalman Filter (Ott et al. 2002, 2004) and the results of perfect model tests with the Lorenz-96 model. This scheme is locally analogous to performing the Ensemble Transform Kalman Filter (Bishop et al. 2001). We also include a four-dimensional extension of the scheme to allow for asynchronous observations.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Assimilating Nonlocal Observations using a Local Ensemble Kalman Filter

Many ensemble Kalman filter data assimilation schemes benefit from spatial localization, often in both the horizontal and vertical coordinates. On the other hand, satellite observations are often sensitive to the dynamics over a broad layer of the atmosphere; that is, the observation operator that maps the model state to the observed satellite radiances is a nonlocal function of the state. Simi...

متن کامل

Eakf-cmaq: Development and Initial Evaluation of an Ensemble Adjustment Kalman Filter Based Data Assimilation for Co

An integrated approach to modeling atmospheric chemistry with trace gas data assimilation is a relatively new focus of the atmospheric chemistry modeling community. It is expected that the predictive capability of CTMs can be significantly improved by assimilating measurements of key trace gases from satellite-based platforms and surface monitors. Ensemble adjustment Kalman filter (EAKF) method...

متن کامل

A Local Ensemble Transform Kalman Filter Data Assimilation System for the Global FSU Atmospheric Model

Data assimilation is the process by which measurements and model predictions are combined to obtain an accurate representation of the state of the modeled system. We implemented a data assimilation scheme called LETKF (local ensemble transform Kalman filter) with FSUGSM (Florida State University Global Spectral Model) and made an experiment to evaluate the initial condition generated to numeric...

متن کامل

Title of Document : CARBON CYCLE DATA ASSIMILATION USING A COUPLED ATMOSPHERE - VEGETATION MODEL AND THE LOCAL ENSEMBLE TRANSFORM KALMAN FILTER

Title of Document: CARBON CYCLE DATA ASSIMILATION USING A COUPLED ATMOSPHEREVEGETATION MODEL AND THE LOCAL ENSEMBLE TRANSFORM KALMAN FILTER Ji Sun Kang, Doctor of Philosophy, 2009 Directed By: Professor Eugenia Kalnay Department of Atmospheric and Oceanic Science We develop and test new methodologies to best estimate CO2 fluxes on the Earth’s surface by assimilating observations of atmospheric ...

متن کامل

Global Data Assimilation by Artificial Neural Networks for an Atmospheric General Circulation Model: Conventional Observation

An Artificial Neural Network (ANN) is designed to investigate its application for data assimilation. This procedure provides an appropriated initial condition to the atmosphere to weather forecasting. Data assimilation is a method to insert observational information into a physicalmathematical model. The goal here is the process for assimilating meteorological observations. The numerical experi...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2006