Abstract
This work describes the implementation and evaluation of an Ensemble Adjustment Kalman Filter (EAKF) with a global atmospheric zoom model (version 5) of the Laboratoire de Météorologie Dynamique (LMDZ5, Z stands for zoom). An interface has been developed to use Data Assimilation Research Testbed (DART), a community EAKF system, with LMDZ5 model. The NCEP PREBUFR real observation data have been assimilated to evaluate the performance of newly developed LMDZ5-DART system. It has been demonstrated with the help of a numerical experiment that LMDZ5-DART system successfully assimilates real observations. A one month LMDZ5-DART analysis has been created using assimilation of NCEP PREBUFR observation data, and the assimilated fields are compared with NCEP CDAS reanalysis. Results show that LMDZ5-DART produces remarkably similar reanalysis to NCEP products. This is therefore a very encouraging result towards a long-term goal of creating a high quality analysis over the Indian subcontinent from the assimilation of local satellite products.
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DART Website. http://www.image.ucar.edu/DAReS/DART/
Acknowledgment
The authors are grateful to the Space Application Centre (SAC) of the Indian Space Research Organization (ISRO) for providing valuable funds in the form of a Research Scholarship to one of us (T. Singh) to carry out this work at the Indian Institute of Technology Delhi (IITD), New Delhi (India).
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Singh, T., Mittal, R., Upadhyaya, H.C. (2015). Ensemble Adjustment Kalman Filter Data Assimilation for a Global Atmospheric Model. In: Ravela, S., Sandu, A. (eds) Dynamic Data-Driven Environmental Systems Science. DyDESS 2014. Lecture Notes in Computer Science(), vol 8964. Springer, Cham. https://doi.org/10.1007/978-3-319-25138-7_26
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DOI: https://doi.org/10.1007/978-3-319-25138-7_26
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