Neuartige hochauflösende Messungen zur Unterstützung der Fernerkundung von Schneefall durch eine dreidimensionale Abbildung und die Bestimmung der Masse von Hydrometeoren im freien Fall
Zusammenfassung der Projektergebnisse
The research project aimed at analyzing the impact of snowflake natural variability on microwave scattering signatures relevant to snowfall remote sensing by using novel high-resolution images and mass measurements of falling snowflakes as input for modeling snowflake and snowfall scattering properties. Due to the significant modifications to the initially available prototype hotplate sensor that were required to permit snowflake mass measurements outside of a controlled laboratory environment, actual snowflake mass measurements for the analyzed snowstorms could not be included in the analysis. Instead, snowflake variability was determined solely from Multi-Angle Snowflake Camera (MASC) data and corresponding snowflake masses were derived from a pre-established expression relating maximum snowflake dimensions to realistic values of snowflake mass. The ongoing development of the hotplate sensor has yielded a sensor capable of objective snowflake mass measurements in the field for snowflake masses ≥ 0.5 mg and snowflake interarrival times > 5 to 10 s. The current hotplate sensor permits snowflake mass measurements without the need for averaging over collections of snowflakes or for making any assumptions on snowflake shape, in contrast to other measurement methods which derive snowflake mass or density relations by combining snowflake imaging with coincident measurements of integrated snow ice or water content. An analysis of the impact of snowflake diameter, aspect ratio, and orientation (derived from MASC observations) on modeled snowfall radar reflectivities indicates that a detailed analysis of snowfall radar reflectivity and a minimization of current uncertainties affecting snowfall remote sensing from radar reflectivity measurements at microwave and millimeter wavelengths require a realistic description of the natural variability of snowflake orientation angles and aspect ratios that adequately represents the individual analyzed snow cloud. Merely characterizing snowflake orientation and aspect ratio based on observations that were performed during different snowfall conditions may instead lead to significant differences of more than 50 % in retrieved snowfall rates. Finally, the effect of the ratio of snowflake surface area to volume on modeled snowfall triplefrequency radar signatures for X, Ku, Ka, and W band radar frequencies has been evaluated. Based on modeling individual snowflakes as collections of randomly distributed solid ice spheres of surface area to volume ratios equal to values of 1 to 5, a broad range of characteristic shapes and general patterns of snowfall triple-frequency radar signatures was derived that are commonly observed in snowfall radar measurements or that have been modeled based on detailed snowflake 3D shape approximations. Therefore, an inclusion of snowflake surface area to volume ratio in future snowflake scattering models and analyses of snowfall radar measurements may prove to be an important step toward identifying (all) crucial snowflake effective shape parameters for accurately describing radar backscatter and thus for reliable retrievals in snowfall remote sensing.
Projektbezogene Publikationen (Auswahl)
- Natural variability during snowfall: Observations of snowflake microstructure and calculations of corresponding snowfall scattering properties, A11L-0223, AGU Fall Meeting 2015, San Francisco, USA
Gergely, M., and Garrett, T. J.
- 2016: Impact of the natural variability in snowflake diameter, aspect ratio, and orientation on modeled snowfall radar reflectivity, J. Geophys. Res. Atmos., 121, 12,236–12,252
Gergely, M., and Garrett, T. J.
(Siehe online unter https://doi.org/10.1002/2016JD025192) - A novel technique for automated mass measurements of individual snowflakes, A23A-0177, AGU Fall Meeting 2016, San Francisco, USA
Gergely, M., Shkurko, K., and Simon, E.
