The importance of simulated errors in observing system simulation experiments
By: Nikki C. Privé, Ronald M. Errico and Will McCarty
References
- Aksoy, A. and Lorsolo, S. 2012. The HWRF Hurricane Ensemble Data Assimilation System (HEDAS) for high-resolution data: the impact of airborne doppler radar observations in an OSSE. Mon. Weather Rev. 140 , 1843–1862. doi:10.1175/MWR-D-11-00212.1
- Atlas, R. , Hoffman, R. N. , Ma, Z. , Emmitt, G. D. , Wood, S. A. and co-authors. 2015. Observing system simulation experiments to evaluate the potential impact of an optical autocovariance wind lidar on numerical weather prediction. J. Atmos. Ocean Technol. 32 , 1593–1613. doi:10.1175/JTECH-D-15-0038.1
- Barahona, D. , Molod, A. , Bacmeister, J. , Nenes, A. , Gettelman, A. and co-authors. 2014. Development of two-moment cloud microphysics for liquid and ice within the NASA Goddard Earth Observing model GEOS-5. Geosci. Model Dev. 7 , 1733–1766. doi:10.5194/gmd-7-1733-2014
- Chen, S.-H. , Chen, J. , Chang, W. , Lin, P. , Lin, P. and co-authors. 2011. Observing system simulation experiment: development of the system and preliminary results. J. Geophys. Res. 116 .doi:10.1029/2010JD015103
- Culverwell, I. , Lewis, H. , Offiler, D. , Marquardt, C. and Burrows, C. 2015. The radio occultation processing package, ROPP. Atmos. Meas. Tech. 8 , 1887–1899. doi:10.5194/amt-8-1887-2015
- Dutta, S. , Garand, L. and Heilliette, S. 2015. Impact evaluation of assimilating surface sensitive infrared radiance observations over land and sea ice from observing system simulation experiments. Adv. Meteorol. 2015 , 1–9. doi:10.1155/2015/847561
- Errico, R. , Carvalho, D. , Privé, N. and Sienkiewicz, M. 2020. Simulation of atmospheric motion vectors for an observing system simulation experiment. J. Atmos. Ocean Technol. 37, 489–505. doi:10.1175/JTECH-D-19-0079
- Errico, R. and co-authors. 2017. Description of the GMAO OSSE for weather analysis software package: version 3. Technical Report 48, 156 pp., NASA/TM-2017-104696, National Aeronautics and Space Administration.
- Errico, R. M. and Privé, N. C. 2018. Some general and fundamental requirements for designing observing system simulation experiments (OSSEs). WMO Rep. WWRP 2018-8, 33 pp. Online at: https://www.wmo.int/pages/prog/arep/wwrp/new/documents/Final_WWRP_2018_8.pdf
- Errico, R. M. , Yang, R. , Privé, N. , Tai, K.-S. , Todling, R. and co-authors. 2013. Validation of version one of the observing system simulation experiments at the global modeling and assimilation office. Q. J. R. Meteorol. Soc. 139 , 1162–1178. doi:10.1002/qj.2027
- Garand, L. , Feng, J. , Heilliette, S. , Rochon, Y. and Trishchenko, A. P. 2013. Assimilation of circumpolar wind vectors derived from highly elliptical orbit imagery: impact assessment based on observing system simulation experiments. J. Appl. Meterol. Clim. 52 , 1891–1908. doi:10.1175/JAMC-D-12-0333.1.
- Gelaro, R. and co-authors. 2015. Evaluation of the 7-km GEOS-5 nature run. NASA/TM2014-14606, Technical Report, NASA.
- Halliwell, G. J. , Srinivasan, A. , Kourafalou, V. , Yang, H. , Willey, D. and co-authors. 2014. Rigorous evaluation of a fraternal twin ocean OSSE system for the open Gulf of Mexico. J. Atmos. Ocean Technol. 31 , 105–130. doi:10.1175/JTECH-D-13-00011.1
- Han, Y. , van Delst, P. , Liu, Q. , Weng, F. , Yan, B. and co-authors. 2006. JCSDA Community Radiative Transfer Model (CRTM) - version 1. Technical report, OAA Technical Report 122. pp. 33, NOAA, Silver Spring, MD.
- Holdaway, D. , Errico, R. , Gelaro, R. and Kim, J. 2014. Inclusion of linearized moist physics in NASA’s Goddard Earth Observing System data assimilation tools. Mon. Weather Rev. 142 , 414–433. doi:10.1175/MWR-D-13-00193.1
- Ide, K. , Courtier, P. , Ghil, M. and Lorenc, A. 1997. Unified notation for data assimilation: operational, sequential and variational. J. Meteorol. Soc. Jpn. 75 , 181–189. doi:10.2151/jmsj1965.75.1B_181
- Kleist, D. and Ide, K. 2015. An OSSE-based evaluation of hybrid variational–ensemble data assimilation for the NCEP GFS. Part I: system description and 3d-hybrid results. Mon. Weather Rev. 143 , 433–451. doi:10.1175/MWR-D-13-00351.1
- Kleist, D. , Parrish, D. , Derber, J. , Treadon, R. , Wu, W.-S. and co-authors. 2009. Introduction of the GSI into the NCEP global data assimilation system. Weather Forecast. 24 , 1691–1705. doi:10.1175/2009WAF2222201.1
- Kotsuki, S. , Kurosawa, K. and Miyoshi, T. 2019. On the properties of ensemble forecast sensitivity to observations. Q. J. R. Meteorol. Soc. 145 , 1897–1914. doi:10.1002/qj.3534
- Lahoz, W. , Brugge, R. , Jackson, D. , Migliorini, S. , Swinbank, R. and co-authors. 2005. An observing system simulation experiment to evaluate the scientific merit of wind and ozone measurements from the future SWIFT instrument. Q. J. R. Meteorol. Soc. 131 , 503–523. doi:10.1256/qj.03.109
- McCarty, W. , Carvalho, D. , Moradi, I. and Privé, N. C. 2021. Observing system simulation experiments investigating a constellation of 4-5 μm infra-red sounders. J. Atmos. Ocean Technol. doi:10.1175/JTECH-D-20-0109.1.
- Necker, T. , Weissman, M. and Sommer, M. 2018. The importance of appropriate verification metrics for the assessment of observation impact in a convection-permitting modelling system. Q. J. R. Meteorol. Soc. 144 , 1667–1680. doi:10.1002/qj.3390
- Peevey, T. R. and English, J. M. Improving winter storm forecasts with observing system simulation experiments. Part I: an idealized case study of three U.S. storms. Mon. Weather Rev. 146 , 1341–1366. doi:10.1175/MWR-D-17-0160.1
- Privé, N. and Errico, R. 2019. Uncertainty of observation impact estimation in an adjoint model investigated with an observing system simulation experiment. Mon. Weather Rev. 147 , 3191–3204. doi:10.1175/MWR-D-19-0097.1
- Privé, N. , Errico, R. and Tai, K.-S. 2013. The influence of observation errors on analysis error and forecast skill investigated with an observing system simulation experiment. J. Geophys. Res. Atmos. 118 , 5332–5346. doi:10.1002/jgrd.50452
- Privé, N. , Errico, R. and Tai, K.-S. 2014. The impact of increased frequency of rawinsonde observations on forecast skill investigated with an observing system simulation experiment. Mon. Weather Rev. 142 , 1823–1834. doi:10.1175/MWR-D-13-00237.1
- Privé, N. and Errico, R. M. 2013. The role of model and initial condition error in numerical weather forecasting investigated with an observing system simulation experiment. Tellus-A 68 . doi:10.3402/tellusa.v65i0.21740.
- Privé, N. C. , Errico, R. , Todling, R. and Akkraoui, A. E. 2021. Evaluation of adjoint-based observation impacts. Q. J. R. Meteorol. Soc. 147, 121–138. doi: 10.1002/qj.3909
- Rienecker, M. and co-authors, 2008. The GEOS-5 data assimilation system - documentation of versions 5.0.1, 5.1.0, and 5.2.0. Technical report series on global modeling and data assimilation. 118 pp., NASA.
- Riishojgaard, L. , Ma, Z. , Masutani, M. , Woollen, J. , Emmitt, G. and co-authors. 2012. Observation system simulation experiments for a global wind observing sounder. Geophys. Res. Lett. 39 .
- Stoffelen, A. , Marseille, G. , Bouttier, F. , Vasiljevic, D. , de Haan, S. and co-authors. 2006. ADM-aeolus doppler wind lidar observing system simulation experiment. Q. J. R. Meteorol. Soc. 132 , 1927–1947. doi:10.1256/qj.05.83
- Timmermans, R. , Lahoz, W. , Attié, J.-L. , Peuch, V.-H. , Curier, R. and co-authors. 2015. Observing system simulation experiments for air quality. Atmos. Environ. 115 , 199–213. doi:10.1016/j.atmosenv.2015.05.032
- Vecchi, G. and Harrison, M. J. 2007. An observing system simulation experiment for the Indian Ocean. J. Clim. 20 , 3300–3319. doi:10.1175/JCLI4147.1
- Zhu, T. , Weng, F. , Masutani, M. and Woollen, J. 2012. Synthetic radiance simulation and evaluation for a joint observing system simulation experiment. J. Geophys. Res. 117 .
DOI: https://doi.org/10.1080/16000870.2021.1886795 | Journal eISSN: 3035-9554
Language: English
Page range: 1886795 - 1886795
Published on: Jan 1, 2021
Published by: Stockholm University Press
In partnership with: Paradigm Publishing Services
© 2021 Nikki C. Privé, Ronald M. Errico, Will McCarty, published by Stockholm University Press
This work is licensed under the Creative Commons Attribution 4.0 License.