Articles | Volume 11, issue 7
https://doi.org/10.5194/amt-11-4239-2018
https://doi.org/10.5194/amt-11-4239-2018
Research article
 | 
19 Jul 2018
Research article |  | 19 Jul 2018

Estimating observation and model error variances using multiple data sets

Richard Anthes and Therese Rieckh

Related authors

Evaluating two methods of estimating error variances using simulated data sets with known errors
Therese Rieckh and Richard Anthes
Atmos. Meas. Tech., 11, 4309–4325, https://doi.org/10.5194/amt-11-4309-2018,https://doi.org/10.5194/amt-11-4309-2018, 2018
Short summary
Evaluating tropospheric humidity from GPS radio occultation, radiosonde, and AIRS from high-resolution time series
Therese Rieckh, Richard Anthes, William Randel, Shu-Peng Ho, and Ulrich Foelsche
Atmos. Meas. Tech., 11, 3091–3109, https://doi.org/10.5194/amt-11-3091-2018,https://doi.org/10.5194/amt-11-3091-2018, 2018
Short summary
Reducing representativeness and sampling errors in radio occultation–radiosonde comparisons
Shay Gilpin, Therese Rieckh, and Richard Anthes
Atmos. Meas. Tech., 11, 2567–2582, https://doi.org/10.5194/amt-11-2567-2018,https://doi.org/10.5194/amt-11-2567-2018, 2018
Short summary
Comparison of global observations and trends of total precipitable water derived from microwave radiometers and COSMIC radio occultation from 2006 to 2013
Shu-Peng Ho, Liang Peng, Carl Mears, and Richard A. Anthes
Atmos. Chem. Phys., 18, 259–274, https://doi.org/10.5194/acp-18-259-2018,https://doi.org/10.5194/acp-18-259-2018, 2018
Short summary
Tropospheric dry layers in the tropical western Pacific: comparisons of GPS radio occultation with multiple data sets
Therese Rieckh, Richard Anthes, William Randel, Shu-Peng Ho, and Ulrich Foelsche
Atmos. Meas. Tech., 10, 1093–1110, https://doi.org/10.5194/amt-10-1093-2017,https://doi.org/10.5194/amt-10-1093-2017, 2017
Short summary

Related subject area

Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Drop size distribution retrieval using dual-polarization radar at C-band and S-band
Daniel Durbin, Yadong Wang, and Pao-Liang Chang
Atmos. Meas. Tech., 17, 5397–5411, https://doi.org/10.5194/amt-17-5397-2024,https://doi.org/10.5194/amt-17-5397-2024, 2024
Short summary
Thermal tides in the middle atmosphere at mid-latitudes measured with a ground-based microwave radiometer
Witali Krochin, Axel Murk, and Gunter Stober
Atmos. Meas. Tech., 17, 5015–5028, https://doi.org/10.5194/amt-17-5015-2024,https://doi.org/10.5194/amt-17-5015-2024, 2024
Short summary
Global sensitivity analysis of simulated remote sensing polarimetric observations over snow
Matteo Ottaviani, Gabriel Harris Myers, and Nan Chen
Atmos. Meas. Tech., 17, 4737–4756, https://doi.org/10.5194/amt-17-4737-2024,https://doi.org/10.5194/amt-17-4737-2024, 2024
Short summary
Improving the Gaussianity of radar reflectivity departures between observations and simulations using symmetric rain rates
Yudong Gao, Lidou Huyan, Zheng Wu, and Bojun Liu
Atmos. Meas. Tech., 17, 4675–4686, https://doi.org/10.5194/amt-17-4675-2024,https://doi.org/10.5194/amt-17-4675-2024, 2024
Short summary
On the temperature stability requirements of free-running Nd:YAG lasers for atmospheric temperature profiling through the rotational Raman technique
José Alex Zenteno-Hernández, Adolfo Comerón, Federico Dios, Alejandro Rodríguez-Gómez, Constantino Muñoz-Porcar, Michaël Sicard, Noemi Franco, Andreas Behrendt, and Paolo Di Girolamo
Atmos. Meas. Tech., 17, 4687–4694, https://doi.org/10.5194/amt-17-4687-2024,https://doi.org/10.5194/amt-17-4687-2024, 2024
Short summary

Cited articles

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, c, d, e, f, g
Cucurull, L. and Derber, J. C.: Operational Implementation of COSMIC Observations into NCEP's Global Data Assimilation System, Weather Forecast., 23, 702–711, https://doi.org/10.1175/2008WAF2007070.1, 2008. a
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
Desroziers, G. and Ivanov, S.: Diagnosing and adaptive tuning of observation-error parameters in a variational assimilation, Q. J. Roy. Meteor. Soc., 127, 1433–1452, https://doi.org/10.1002/qj.49712757417, 2001. a
Ekstrom, C. R. and Koppang, P. A.: Error Bars for Three-Cornered Hats, IEEE T. Ultrason. Ferr., 53, 876–879, https://doi.org/10.1109/TUFFC.2006.1632679, 2006. a
Download
Short summary
We show how multiple data sets, including observations and models, can be combined using the "N-cornered hat method" to estimate vertical profiles of the errors of each system. Using data from 2007, we estimate the error variances of radio occultation, radiosondes, ERA-Interim, and GFS model data sets at four radiosonde locations in the tropics and subtropics. A key assumption is the neglect of error correlations among the different data sets, and we examine the consequences of this assumption.