Articles | Volume 14, issue 8
Atmos. Meas. Tech., 14, 5369–5395, 2021
Atmos. Meas. Tech., 14, 5369–5395, 2021

Research article 06 Aug 2021

Research article | 06 Aug 2021

Physical characteristics of frozen hydrometeors inferred with parameter estimation

Alan J. Geer

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Cited articles

Aires, F., Prigent, C., Bernardo, F., Jiménez, C., Saunders, R., and Brunel, P.: A Tool to Estimate Land-Surface Emissivities at Microwave frequencies (TELSEM) for use in numerical weather prediction, Q. J. Roy. Meteorol. Soc., 137, 690–699,, 2011. a
Allen, J. T., Tippett, M. K., Kaheil, Y., Sobel, A. H., Lepore, C., Nong, S., and Muehlbauer, A.: An extreme value model for US hail size, Mon. Weath. Rev., 145, 4501–4519,, 2017. a
Auligné, T., McNally, A. P., and Dee, D. P.: Adaptive bias correction for satellite data in a numerical weather prediction system, Q. J. Roy. Meteorol. Soc., 133, 631–642,, 2007. a
Bailey, M. P. and Hallett, J.: A comprehensive habit diagram for atmospheric ice crystals: Confirmation from the laboratory, AIRS II, and other field studies, J. Atmos. Sci., 66, 2888–2899,, 2009. a
Baordo, F. and Geer, A. J.: Assimilation of SSMIS humidity-sounding channels in all-sky conditions over land using a dynamic emissivity retrieval, Q. J. Roy. Meteorol. Soc., 142, 2854–2866,, 2016. a
Short summary
Satellite observations sensitive to cloud and precipitation help improve the quality of weather forecasts. However, they are sensitive to things that models do not forecast, such as the shapes and sizes of snow and ice particles. These details can be estimated from the observations themselves and then incorporated in the satellite simulators used in weather forecasting. This approach, known as parameter estimation, will be increasingly useful to build models of poorly known physical processes.