Skip to main content
Have a personal or library account? Click to login
Impacts of an Early Morning Low Earth Orbit Observing Platform in a Future Global Observing Network Scenario Cover

Impacts of an Early Morning Low Earth Orbit Observing Platform in a Future Global Observing Network Scenario

Open Access
|Dec 2024

References

  1. Bormann, N., Lawrence, H. and Farnan, J. (2019) Global observing system experiments in the ECMWF assimilation system. Available at: https://www.ecmwf.int/node/18859 [Last accessed 13 November 2024].
  2. Boukabara, S.-A., Garrett, K. and Kumar, V. (2016) Potential gaps in the satellite observing system coverage: Assessment of impact on NOAA’s numerical weather prediction overall skills. Mon. Wea. Rev., 144: 25472563. DOI: 10.1175/MWR-D-16-0013.1
  3. Congress of the United States. (2017) H.R. 353, Weather Research and Forecasting Innovation Act. Available at: https://www.congress.gov/bill/115th-congress/house-bill/353/text [Last accessed 13 November 2024].
  4. Ding, S., Yang, P., Weng, F., Liu, Q., van Delst, P., Li, J. and Baum, B. (2011) Validation of the community radiative transfer model. J. Quant. Spectrosc. Radiat. Transfer, 112: 10501064. DOI: 10.1016/j.jqsrt.2010.11.009
  5. Duncan, D.I., Bormann, N. and Hólm, E. (2021) On the addition of microwave sounders and numerical weather prediction skill. Quart. J. Roy. Meteor. Soc., 147: 37033718. 10.1002/qj.4149
  6. El Akkraoui, A., Privé, N., Errico, R. and Todling, R. (2023) The GMAO hybrid 4D-EnVar observing system simulation experiment framework. Mon. Wea. Rev., 151: 17171734. DOI: 10.1175/MWR-D-22-0254.1
  7. Errico, R., Privé, N., Carvalho, D., Sienkiewicz, M., Akkraoui, A. E., Guo, J., Todling, R., McCarty, W., Putman, W., da Silva, A., Gelaro, R. and Moradi, I. (2017) Description of the GMAO OSSE for Weather Analysis software package: Version 3, Technical Report 48, National Aeronautics and Space Administration. NASA/TM-2017-104606.
  8. Errico, R.M., Carvalho, D., Privé, N.C. and Sienkiewicz, M. (2020) Simulation of atmospheric motion vectors for an observing system simulation experiment. J. Atmos. Ocean Tech., 37: 489505. DOI: 10.1175/JTECH-D-19-0079.1
  9. Errico, R.M., Yang, R., Privé, N., Tai, K.-S., Todling, R., Sienkiewicz, M. and Guo, J. (2013) Validation of version one of the Observing System Simulation Experiments at the Global Modeling and Assimilation Office. Quart. J. Roy. Meteor. Soc., 139: 11621178. DOI: 10.1002/qj.2027
  10. Eyre, J. (2024) Observation impact metrics in NWP: A theoretical study. Part II: Systems with suboptimal observation errors. Quart. J. Roy. Meteor. Soc., 150: 632640. DOI: 10.1002/qj.4614
  11. Gelaro, R., Putman, W.M., Pawson, S., Draper, C., Molod, A., Norris, P.M., Ott, L., Privé, N., Reale, O., Achuthavarier, D., Bosilovich, M., Buchard, V., Chao, W., Coy, L., Cullather, R., da Silva, A., Darmenov, A., Errico, R.M., Fuentes, M., Kim, M.-J., Koster, R., McCarty, W., Nattala, J., Partyka, G., Schubert, S., Vernieres, G., Vikhliaev, Y. and Wargan, K. (2014) Evaluation of the 7-km GEOS-5 nature run. NASA/TM-2014-104606, 36. NASA.
  12. Gelaro, R. and Zhu, Y. (2009) Examination of observation impacts derived from observing system experiments (OSEs) and adjoint models. Tellus, 61A: 179193. DOI: 10.1111/j.1600-0870.2008.00388.x
  13. Global Modeling and Assimilation Office, NASA. (2014) GEOS-5 Nature Run, Ganymed Release. Available at: https://gmao.gsfc.nasa.gov/global_mesoscale/7km-G5NR/ [Last accessed 13 November 2024].
  14. Griffin, V., Gallagher, F.W. and Spencer, D. (2021) Future NOAA LEO constellation: Temperature and moisture sounding for NWP and future observations. In 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS. pp. 14971500. DOI: 10.1109/IGARSS47720.2021.9554324
  15. Han, Y., van Delst, P., Liu, Q., Weng, F., Yan, B., Treadon, R. and Derber, J. (2006) JCSDA Community Radiative Transfer Model (CRTM) – version 1. NOAA Tech. Report 122.
  16. 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. Wea. Rev., 142: 414433. DOI: 10.1175/MWR-D-13-00193.1
  17. Holmlund, K., Grandell, J., Schmetz, J., Stuhlmann, R., Bojkov, B., Munro, R., Lekouara, M., Coppens, D., Viticchie, B., August, T., Theodore, B., Watts, P., Dobber, M., Fowler, G., Bojinski, S., Schmid, A., Salonen, K., Tjemkes, S., Aminou, D. and Blythe, P. (2021) Meteosat Third Generation (MTG): Continuation and Innovation of Observations from Geostationary Orbit. Bull. Amer. Meteor. Soc., 102(5): E990E1015. Available at: https://journals.ametsoc.org/view/journals/bams/102/5/BAMS-D-19-0304.1.xml [Last accessed 13 November 2024]. DOI: 10.1175/BAMS-D-19-0304.1
  18. Kalluri, S. (2021) Satellite microwave sounding measurements in weather prediction: A report of the virtual noaa workshop on microwave sounders. Technical Report 155. NESDIS.
  19. Kalluri, S. (2022) Exploring the future of infrared sounding: Outcomes of a noaa/nesdis virtual workshop. Bulletin of the American Meteorological Society, 103(8): E1875E1885. DOI: 10.1175/BAMS-D-22-0054.1
  20. Kan, W., Dong, P., Weng, F., Hu, H. and Dong, C. (2022) Impact of Fengyun-3E microwave temperature and humidity sounder data on CMA global medium range weather forecasts. Remote Sensing, 14(5014). DOI: 10.3390/rs14195014
  21. Li, J., Qian, X., Qin, Z. and Liu, G. (2022) Direct assimilation of Chinese FY-3E Microwave Temperature Sounder-3 radiances in the CMA-GFS: An initial study. Remote Sensing, 14(5943). DOI: 10.3390/rs14235943
  22. Li, J., Qin, Z., Liu, G. and Huang, J. (2024) Added benefit of the early-morning-orbit satellite Fengyun-3E on the global microwave sounding of the three-orbit constellation. Adv. in Atmos. Sci. pp. 3952. DOI: 10.1007/s00376-023-2388-z
  23. Lindsey, D.T., Heidinger, A.K., Sullivan, P.C., McCorkel, J., Schmit, T.J., Tomlinson, M., Vandermeulen, R., Frost, G.J., Kondragunta, S. and Rudlosky, S. (2024) GeoXO: NOAAś Future Geostationary Satellite System. Bulletin of the American Meteorological Society. DOI: 10.1175/BAMS-D-23-0048.1. Available at: https://journals.ametsoc.org/view/journals/bams/aop/BAMS-D-23-0048.1/BAMS-D-23-0048.1.xml [Last accessed 13 November 2024].
  24. Liu, R., Lu, Q., Wu, C., Ni, Z. and Wang, F. (2024) Assimilation of hyperspectral infrared atmospheric sounder data of FengYun-3E satellite and assessment of its impact on analyses and forecasts. Remote Sensing, 16(908). DOI: 10.3390/rs16050908
  25. McCarty, W., Carvalho, D., Moradi, I. and Prive, N. C. (2021) Observing system simulation experiments investigating atmospheric motion vectors and radiances from a constellation of 4–5 micro-m infrared sounders. J. Atmos. Ocean Tech., 38: 331347. DOI: 10.1175/JTECH-D-20-0109.1
  26. McGrath-Spangler, E., McCarty, W., Privé, N., Moradi, I., Karpowicz, B. and McCorkel, J. (2022) Using OSSEs to evaluate the impacts of geostationary infrared sounders. J. Atmos. Ocean Tech., 39: 19031918. DOI: 10.1175/JTECH-D-22-0033.1
  27. McGrath-Spangler, E., Privé, N., Karpowicz, B., Moradi, I. and Heidinger, A. (2024) Using OSSEs to evaluate GXS impact in the context of international coordination. J. Atmos. Ocean Tech., 41: 261278. DOI: 10.1175/JTECH-D-23-0141.1
  28. Okamoto, K., Owada, H., Fujita, T., Kazumori, M., Otsuka, M., Seko, H., Ota, Y., Uekiyo, N., Ishimoto, H., Hayashi, M., Ishida, H., Ando, A., Takahashi, M., Bessho, K. and Yokota, H. (2020) Assessment of the potential impact of a hyperspectral infrared sounder on the himawari follow-on geostationary satellite. SOLA, 16: 162168. DOI: 10.2151/sola.2020-028
  29. Privé, N. and Errico, R. (2019) Uncertainty of observation impact estimation in an adjoint model investigated with an observing system simulation experiment. Mon. Wea. Rev., 147: 31913204. DOI: 10.1175/MWR-D-19-0097.1
  30. Privé, N.C., Errico, R.M. and Akkraoui, A.E. (2022) Investigation of the potential saturation of information from global navigation satellite system radio occultation observations with an observing system simulation experiment. Mon. Wea. Rev., 150: 12931316. DOI: 10.1175/mwr-d-20-0256.1
  31. Privé, N.C., Errico, R.M., Todling, R. and Akkraoui, A.E. (2020) Evaluation of adjoint-based observation impacts as a function of forecast length using an observing system simulation experiment. Quart. J. Roy. Meteor. Soc., 147: 121138. DOI: 10.1002/qj.3909
  32. Privé, N.C., McGrath-Spangler, E., Carvalho, D., Karpowicz, B. and Moradi, I. (2023a) Robustness of Observing System Simulation Experiments. Tellus-A, 75: 309333. DOI: 10.16993/tellusa.3254
  33. Privé, N. C., McLinden, M., Lin, B., Moradi, I., Sienkiewicz, M., Heymsfield, G. and McCarty, W. (2023b) Impacts of marine surface pressure observations from a spaceborne differential absorption radar investigated with an observing system simulation experiment. J. Atmos. Ocean Tech., 40: 897918. DOI: 10.1175/JTECH-D-22-0088.1
  34. Putman, W. (2014) Model configuration for the 7-km GEOS-5 nature run, ganymed release (non-hydrostatic 7-km global mesoscale simulation). GMAO Office Note No. 5. Available at: https://gmao.gsfc.nasa.gov/pubs/docs/Putman727.pdf [Last accessed 13 November 2024].
  35. Rienecker, M., Suarez, M., Todling, R., Bacmeister, J., Takacs, L., Liu, H.-C., Gu, W., Sienkiewicz, M., Koster, R., Gelaro, R., Stajner, I. and Nielsen, J. (2008) The GEOS-5 data assimilation system – documentation of versions 5.0.1, 5.1.0 and 5.2.0. Technical Report 27, NASA.
  36. Steele, L., Bormann, N. and Duncan, D. (2023) Assimilating FY-3E MWHS-2 observations, and assessing all-sky humidity sounder thinning scales. Technical Report 62, EUMETSAT/ECMWF.
  37. Tiger Team. (2013) Assessment of the benefits of a satellite mission in an early morning orbit. Technical report. Available at: https://library.wmo.int/viewer/49699/ [Last accessed 13 November 2024].
  38. Wilks, D. (2011) Statistical methods in the atmospheric sciences. Oxford, UK: Academic Press.
  39. WMO. (2019) Vision for the WMO integrated global observing system in 2040. Available at: https://library.wmo.int/doc_num.php?explnum_id=10278 [Last accessed 13 November 2024].
  40. Xiao, H., Han, W., Zhang, P. and Bai, Y. (2023) Assimilation of data form the MWHS-II onboard the first early morning satellite FY-3E into the CMA global 4D-Var system. Meteorological Applications, 30(2133). DOI: 10.1002/met.2133
  41. Yang, J., Zhang, Z., Wei, C., Lu, F. and Guo, Q. (2017) Introducing the new generation of Chinese geostationary weather satellites, Fengyun-4. Bull. of the Amer. Met. Soc., 98: 16371658. DOI: 10.1175/BAMS-D-16-0065.1
  42. Zhang, P., Hu, X., Lu, Q., Zhu, A., Lin, M., Sun, L., Chen, L. and Xu, N. (2022) FY-3E: The first operational meteorological satellite mission in an early morning orbit. Adv. Atmos. Sci. 39: 18. DOI: 10.1007/s00376-021-1304-7
  43. Zhang, P., Hu, X., Sun, L., Xu, N., Chen, L., Zhu, A., Lin, M., Lu, Q., Yang, Z., Yang, J. and Wang, J. (2024). The on-orbit performance of FY-3E in an early morning orbit. pp. E144E175. DOI: 10.1175/BAMS-D-22-0045.1
  44. Zhang, Q. and Shao, M. (2023) Assimilation of FY-3D and FY-3E hyperspectral infrared atmospheric sounding observation and its impact on numerical weather prediction during spring season over the continental United States. Atmosphere, 14(967). DOI: 10.3390/atmos14060967
Language: English
Page range: 227 - 249
Submitted on: Aug 2, 2024
Accepted on: Nov 6, 2024
Published on: Dec 3, 2024
Published by: Stockholm University Press
In partnership with: Paradigm Publishing Services

© 2024 Nikki C. Privé, Bryan M. Karpowicz, Erica L. McGrath-Spangler, Satya Kalluri, published by Stockholm University Press
This work is licensed under the Creative Commons Attribution 4.0 License.