Deployable Antennas for Improved Spatial Resolution of Active and Passive Microwave Sensors Observations

Space based environmental observations are essential for the entire planet. To meet the expanding needs and diversity of such data and to be able to provide around the clock awareness of the environment, NESDIS is mandated to enhance and expand NOAA’s Earth Observing assets. More importantly, new Earth Observing technologies and measurement spectra must be developed to improve awareness of the changes and challenges of extreme weather events, climate change, large scale wildfires, water resources crises, and to deliver adequate, actionable weather intelligence to businesses.

Space based passive microwave sensors offer valuable insights into climate dynamics and the intricate interplay of water and energy cycles. They also serve as important data sources for enhancing the accuracy of weather forecasting models, e.g., (English, et al. 2013), (Lupu 2019). These types of sensors have a lot more to offer if their spatial, temporal, and spectral resolution can be improved.

The observation and measurement of precipitation (rainfall and snowfall) on a global scale is one of the most crucial variables for our understanding of the Earth system that is impacting societies across many levels. Precipitation provides a direct link between the local cycle of energy and water. It is also a primary cause of many natural hazards, such as droughts, floods, and fires. However, observations of precipitation are challenging. To provide observations for a wide range of precipitation events, from heavy rain, tropical cyclones, to light precipitation and snow, a wide range of microwave frequencies is used. Active sensors, such as Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) (13.6 GHz), Dual frequency Precipitation Radar (DPR) of The Global Precipitation Measurement (GPM) (13.6 and 35.5 GHz), and CPR (94 GHz) operate between 13 and 95 GHz. Passive microwave imagers and sounders contribute to precipitation retrieval significantly. Extending their frequency coverage can improve precipitation retrieval, as shown by (Bauer, Moreau and Di Michele 2005), (Di Michele and Bauer 2006), and others. The operational range of passive microwave sensors spans frequencies between 6 and 200 GHz.

To improve global precipitation mapping, improved spatial, spectral, and temporal resolution of observations is required, (Kidd, et al. 2021). The authors state, “Since the spatial variability of precipitation is on the order for a few kilometers, resolving this variability at 1 km or less would be ideal...” They then show that temporal resolution for, for example, a 15 km spatial resolution and correlation coefficient between precipitation retrieved by a ground based radar and space based passive microwave sensor better than 80% would require sampling at 1.5 hours, or at least 8 sensors on orbit. For such spatial resolution at 7 GHz, the antenna aperture for a conically scanning sensor would be ~7 m.

Deployable offset parabolic antennas can enable the economical deployment of such passive or active sensors. Moreover, these antenna types can support operations over a wide frequency range, e.g., from 6 to 120 GHz, and lower or higher.

BEST has developed antenna prototypes capable of working over this frequency range and more. The talk will introduce the solutions and describe a range of capabilities that sensors with deployable antennas offer.

References:

Bauer, P., E. Moreau, and S. Di Michele. 2005. "Hydrometeor Retrieval Accuracy Using Microwave Window and Sounding Channel Observations." Journal of Applied Meteorology 1016-1032.

Di Michele, S., and P. Bauer. 2006. "Passive microwave radiometer channel selection based on cloud and precipitation information content." Quarterly Journal of the Royal Meteorological Society 132 (617): 1299-1323.

English, S., T. McNally, N. Bormann, K. Salonen, M. Matricardi, A. Horanyi, M. Rennie, et al. 2013. Impact of satellite data. Technical memorandum, Reading, England: ECMWF.

Kidd, C., G. Huffman, V. Maggioni, P. Chambon, and R. Oki. 2021. "The Global Satellite Precipitation Constellation. Current Status and Future Requirements." Bulletin of the American Meteorological Society. doi:10.1175/BAMS-D-20-0299.1.

Lupu, C. 2019. "Data assimilation diagnostics: Assessing the observations impact in the forecast." ECMWF Data assimilation training course 51.