Assimilation of wind speed and direction observations: a new formulation and results from idealised experiments
By: Xiang-Yu Huang, Feng Gao, Neil A. Jacobs and Hongli Wang
References
- Andersson
. Fisher. Munro. McNally. Diagnosis of background errors for radiances and other observable quantities in a variational data assimilation scheme, and the explanation of a case of poor convergence. Quart. J. Roy. Meteor. Soc. 2000; 126: 1455– 1472. 10.3402/tellusa.v65i0.19936. - Barker
. Huang. Liu. Auligne. Zhang. co-authors. The weather research and forecasting (WRF) model's community variational/ensemble data assimilation system: WRFDA. Bull. Amer. Meteor. Soc. 2012; 93: 831– 843. 10.3402/tellusa.v65i0.19936. - Barker
. Huang. Guo. Bourgeois. Xiao. A three-dimensional variational data assimilation system for MM5: implementation and initial results. Mon. Wea. Rev. 2004; 132: 897– 914. - Courtier
. Thépaut. Hollingsworth. A strategy for operational implementation of 4D-Var, using an incremental approach. Quart. J. Roy. Meteor. Soc. 1994; 120: 1367– 1387. 10.3402/tellusa.v65i0.19936. - Daley
, R. 1991. Atmospheric Data Analysis. Cambridge University Press, Cambridge, UK. 457. pp. - Dobson
, F, Hasse, L, and Davis, R. 1980. Air-Sea Interaction: Instruments and Methods. Chap. 1–4. Springer: New York. - Ebuchi
. Graber. Caruso. Evaluation of wind vectors observed by QuikSCAT/SeaWinds using ocean buoy data. J. Atmos. Oceanic Technol. 2002; 19: 2049– 2062. - Gao
. Zhang. Jacobs. Huang. Zhang. co-authors. Estimation of TAMDAR Observational Error and Assimilation Experiments. Wea. Forecasting. 2012; 27: 856– 877. 10.3402/tellusa.v65i0.19936. - Huang
. Xiao. Barker. Zhang. Michalakes. co-authors. Four-dimensional variational data assimilation for WRF: formulation and preliminary results. Mon. Wea. Rev. 2009; 137: 299– 314. 10.3402/tellusa.v65i0.19936. - Kain
. The Kain–Fritsch convective parameterization: an update. J. Appl. Meteor. 2004; 43: 170– 181. - Kalnay
. Kanamitsu. Kistler. Collins. Deaven. co-authors. The NCEP/NCAR 40-year reanalysis project. Bull. Amer. Meteor. Soc. 1996; 77: 437– 471. - Leotta
, D. Fand Long, D. G. 1989. Probability distribution of wind retrieval error for the NASA scatterometer, July 10–14. Proceedings of IGARSS'89 and 12th Canadian Symposium on Remote Sensing. In: , Vancouver, Canada, 3, 1466– 1469. - Masutani
, M, Schlatter, T. W, Errico, R. M, Stoffelen, A, Andersson, E. and co-authors. 2010. Observing system simulation exeperiments . In: Data Assimilation: Making Sense of Observations . W.Lahoz, B.Khattatovand R.Menard). Springer, Heidelberg, Germany, ISBN: 978-3-540-74702-4, pp. 647–679. - van der Molen
. Gash. Elbers. Sonic anemometer (co)sine response and flux measurement. II. The effect of introducing an angle of attack dependent calibration. 2004; 122: 95– 109. 10.3402/tellusa.v65i0.19936. - Parrish
. Derber. The national meteorological center's spectral statistical interpolation analysis system. Agric. For. Meteorol. 1992; 120: 1747– 1763. - Plant
. Effects of wind variability on scatterometry at low wind speeds. Mon. Wea. Rev. 2000; 105: 16899– 16910. 10.3402/tellusa.v65i0.19936. - Schwartz
. Benjamin. A comparison of temperature and wind measurements from ACARS-equipped aircraft and rawinsondes. J. Geophys. Res. 1995; 10: 528– 544. - Skamarock
, W. C, Klemp, J. B, Dudhia, J, Gill, D. O, Barker, D. M. and co-authors. 2008. A Description of the Advanced Research WRF Version 3 . NCAR Tec. Note NCAR/TN–475+STR.
DOI: https://doi.org/10.3402/tellusa.v65i0.19936 | Journal eISSN: 3035-9554
Language: English
Page range: 19936 - 19936
Submitted on: Oct 23, 2012
Accepted on: Jan 22, 2013
Published on: Dec 1, 2013
Published by: Stockholm University Press
In partnership with: Paradigm Publishing Services
Keywords:
© 2013 Xiang-Yu Huang, Feng Gao, Neil A. Jacobs, Hongli Wang, published by Stockholm University Press
This work is licensed under the Creative Commons Attribution 4.0 License.