Evaluation of a Spatial/Spectral Covariance Localization Approach for Atmospheric Data Assimilation
نویسندگان
چکیده
منابع مشابه
Background error covariance estimation for atmospheric CO2 data assimilation
[1] In any data assimilation framework, the background error covariance statistics play the critical role of filtering the observed information and determining the quality of the analysis. For atmospheric CO2 data assimilation, however, the background errors cannot be prescribed via traditional forecast or ensemble-based techniques as these fail to account for the uncertainties in the carbon em...
متن کاملa new approach to credibility premium for zero-inflated poisson models for panel data
هدف اصلی از این تحقیق به دست آوردن و مقایسه حق بیمه باورمندی در مدل های شمارشی گزارش نشده برای داده های طولی می باشد. در این تحقیق حق بیمه های پبش گویی بر اساس توابع ضرر مربع خطا و نمایی محاسبه شده و با هم مقایسه می شود. تمایل به گرفتن پاداش و جایزه یکی از دلایل مهم برای گزارش ندادن تصادفات می باشد و افراد برای استفاده از تخفیف اغلب از گزارش تصادفات با هزینه پائین خودداری می کنند، در این تحقیق ...
15 صفحه اولEnsemble-based Chemical Data Assimilation II: Covariance Localization
Data assimilation is the process of integrating observational data and model predictions to obtain an optimal representation of the state of the atmosphere. As more chemical observations in the troposphere are becoming available, chemical data assimilation is expected to play an essential role in air quality forecasting, similar to the role it has in numerical weather prediction. Considerable p...
متن کاملAn approach to localization for ensemble-based data assimilation
Localization techniques are commonly used in ensemble-based data assimilation (e.g., the Ensemble Kalman Filter (EnKF) method) because of insufficient ensemble samples. They can effectively ameliorate the spurious long-range correlations between the background and observations. However, localization is very expensive when the problem to be solved is of high dimension (say 106 or higher) for ass...
متن کاملMultiscale Algorithm for Atmospheric Data Assimilation
We propose a novel multiscale algorithm for the problem of model assimilation of data. The algorithm allows one to efficiently perform optimal statistical interpolation of observed data from a given forecast wf and vector of observations wo. The core of the new approach is a combination of two multiscale tools: a multiresolution iterative process and a multigrid fastsummation technique. Our app...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Monthly Weather Review
سال: 2012
ISSN: 0027-0644,1520-0493
DOI: 10.1175/mwr-d-10-05052.1