Articles | Volume 11, issue 7
https://doi.org/10.5194/amt-11-4309-2018
https://doi.org/10.5194/amt-11-4309-2018
Research article
 | 
20 Jul 2018
Research article |  | 20 Jul 2018

Evaluating two methods of estimating error variances using simulated data sets with known errors

Therese Rieckh and Richard Anthes

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Cited articles

Anthes, R. and Rieckh, T.: Estimating observation and model error variances using multiple data sets, Atmos. Meas. Tech., 11, 4239–4260, https://doi.org/10.5194/amt-11-4239-2018, 2018. a, b, c, d, e, f, g, h, i, j, k
Braun, J., Rocken, C., and Ware, R.: Validation of line-of-sight water vapor measurements with GPS, Radio Sci., 36, 459–472, 2001. a, b, c
Chen, S.-Y., Huang, C.-Y., Kuo, Y.-H., and Sokolovskiy, S.: Observational Error Estimation of FORMOSAT-3/COSMIC GPS Radio Occultation Data, Mon. Weather Rev., 139, 853–865, https://doi.org/10.1175/2010MWR3260.1, 2011. a, b
Collard, A. D. and Healy, S. B.: The combined impact of future space-based atmospheric sounding instruments on numerical weather-prediction analysis fields: A simulation study, Q. J. Roy. Meteor. Soc., 129, 2741–2760, https://doi.org/10.1256/qj.02.124, 2003. a, b
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N., and Vitart, F.: The ERA-Interim reanalysis: configuration and performance of the data assimilation system, Q. J. Roy. Meteor. Soc., 137, 553–597, https://doi.org/10.1002/qj.828, 2011. a
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Short summary
We compare the two-cornered hat (2CH) and three-cornered hat (3CH) method for estimating the error variances of two or more independent data sets using simulated data with various error correlations and biases. We assess the accuracy of the 3CH and 2CH estimates and examine the sensitivity of the estimated error variances to the degree of error correlation between the data sets as well as sample size. The 3CH method is less sensitive to these factors and hence more accurate.