Estimating observation impact without adjoint model in an ensemble Kalman filter

Quarterly Journal of the Royal Meteorological Society - Tập 134 Số 634 - Trang 1327-1335 - 2008
Junjie Liu1, Eugenia Kalnay2
1University of California, Berkeley, California, USA,
2University of Maryland, College Park, Maryland, USA J. Liu E. Kalnay

Tóm tắt

AbstractWe propose an ensemble sensitivity method to calculate observation impacts similar to Langland and Baker (2004) but without the need for an adjoint model, which is not always available for numerical weather prediction models. The formulation is tested on the Lorenz 40‐variable model, and the results show that the observation impact estimated from the ensemble sensitivity method is similar to that from the adjoint method. Like the adjoint method, the ensemble sensitivity method is able to detect observations that have large random errors or biases. This sensitivity could be routinely calculated in an ensemble Kalman filter, thus providing a powerful tool to monitor the quality of observations and give quantitative estimations of observation impact on the forecasts. Copyright © 2008 Royal Meteorological Society

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Quarterly Journal of the Royal Meteorological Society

Tập 134 Số 634

1327-1335

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