TY - JOUR
T1 - Observation Quality Control with a Robust Ensemble Kalman Filter
AU - Roh, Soojin
AU - Genton, Marc G.
AU - Jun, Mikyoung
AU - Szunyogh, Istvan
AU - Hoteit, Ibrahim
N1 - KAUST Repository Item: Exported on 2020-10-01
PY - 2013/12
Y1 - 2013/12
N2 - Current ensemble-based Kalman filter (EnKF) algorithms are not robust to gross observation errors caused by technical or human errors during the data collection process. In this paper, the authors consider two types of gross observational errors, additive statistical outliers and innovation outliers, and introduce a method to make EnKF robust to gross observation errors. Using both a one-dimensional linear system of dynamics and a 40-variable Lorenz model, the performance of the proposed robust ensemble Kalman filter (REnKF) was tested and it was found that the new approach greatly improves the performance of the filter in the presence of gross observation errors and leads to only a modest loss of accuracy with clean, outlier-free, observations.
AB - Current ensemble-based Kalman filter (EnKF) algorithms are not robust to gross observation errors caused by technical or human errors during the data collection process. In this paper, the authors consider two types of gross observational errors, additive statistical outliers and innovation outliers, and introduce a method to make EnKF robust to gross observation errors. Using both a one-dimensional linear system of dynamics and a 40-variable Lorenz model, the performance of the proposed robust ensemble Kalman filter (REnKF) was tested and it was found that the new approach greatly improves the performance of the filter in the presence of gross observation errors and leads to only a modest loss of accuracy with clean, outlier-free, observations.
UR - http://hdl.handle.net/10754/552743
UR - http://journals.ametsoc.org/doi/abs/10.1175/MWR-D-13-00091.1
UR - http://www.scopus.com/inward/record.url?scp=84896967796&partnerID=8YFLogxK
U2 - 10.1175/MWR-D-13-00091.1
DO - 10.1175/MWR-D-13-00091.1
M3 - Article
SN - 0027-0644
VL - 141
SP - 4414
EP - 4428
JO - Monthly Weather Review
JF - Monthly Weather Review
IS - 12
ER -