Autonomous Microwave Sensor for Planetary Boundary Layer Observations Under All Weather Conditions.

Space-based passive microwave remote sensors contribute about 40% of the information content that drives accuracy of numerical weather forecasts, e.g., (English, et al. 2013), (Joo, Eyre and Marriott 2013), (Lupu 2019). A handful of sensors on orbit, (e.g., 6-8), with an update rate of 4-6 hours, covering most of the planet, provide 40% of the information. All other observations (e.g., radiosondes, in-situ sensors, buoys, weather radars, GPS radio occultation, space-based infrared, optical sensors, and others) provide the remining ~60%. Space based microwave radiometers are used for the retrieval of many variables, e.g., temperature, humidity profiles, cloud properties, precipitation (over the ocean), snow depth, ocean surface temperature, sea ice coverage, ocean surface wind vector, soil moisture and many others.

The same retrieval physics apply to a ground-based radiometer looking up. The retrievals should be simpler, since they are made against a constant, cosmic microwave background. Yet, there are no ground-based radiometer sensors that are used for operational observations, e.g., being used in numerical weather forecasts regularly.

The concept of microwave profiling (and other measurements) with ground-based radiometers currently on the market was developed at least 40 years ago. Since then, the observational capabilities of these sensors have not improved. The requirement for a regular calibration with a cryogenic target is probably the most limiting requirement for a wider spread of these very useful sensors. These calibrations require the handling of cryogenic liquid in the field and are prone to errors. Even a calibration by an expert user can result in observational errors of a few Kelvins, e.g. (Kuchler, et al. 2016), (Bock, Pospichal and Lohnert 2024), (Miacci and Angelis 2018), (Paine, Turner and Kuchler 2014). An additional issue limiting the wide spread use of ground-based radiometers is the use of a soft window, or radome, for the optical window. This window can get dirty or wet and prevent correct measurements for minutes, or up to two hours, (Cadeddu, Liljegren and Turner 2013). Keeping the window free of water requires a lot of power. Similarly, thermal stabilization of the radiometer receivers consumes significant power.

Despite these shortcomings, the authors (Collaud Coen, et al. 2014) document that a microwave radiometer observing at multiple zenith angles provides sufficient information for planetary boundary layer height (PBL) determination. The authors state “We conclude that the radiometer is the most robust among the experimental methods under consideration (lidar, wind profiler, radiosondes) and best suited for automatic real time detection of the PBL height. It provides good results under a wide range of meteorological conditions.” The paper by (Cimini, et al. 2013) arrived at a very similar conclusion.

We will introduce a new generation of a microwave radiometer, (Klein 2023), that is autonomously calibrated, provides thermodynamic profiles with good vertical resolution withing the planetary boundary layer, measures precipitation rate (including snow), and can provide data every few seconds. This remote sensing technology has the potential to reduce the cost of observations of thermodynamic profiles, while providing more complete information about the status of the local atmosphere.

Low power consumption, unattended operations and calibration, a robust design, affordability, and other features enable sensor installation and operations in remote locations. Thus, it can provide timely and high resolution PBL observations at mesoscale spacing under all weather conditions.

References

Bock, T., B. Pospichal, and U. Lohnert. 2024. "Measurement uncertainties of scanning microwave radiometers and their influence on temperature profiling." Atmospheric Measurement Techniques (EGU) 219-233. doi:10.5194/amt-17-219-2024.

Cadeddu, M. P., J. C. Liljegren, and D. D. Turner. 2013. "The atmospheric radiation measurement program (ARM) program network of microwave radiometers: instrumentation, data, and retrievals." Atmospheric Measurement Techniques 2359-2372.

Cimini, D., F. De Angelis, J. C. Dupont, S. Pal, and M. Haeffelin. 2013. "Mixing layer height retrievals by multichannel microwave radiometer observations." Atmospheric Measurement Techniques 2491-2451. doi:10.5194/amt-6-2941-2013.

Collaud Coen, M., C. Praz, A. Haefele, D. Ruffieux, P. Kaufmann, and B. Calpini. 2014. "Determination and climatology of the planetary boundary layer height above the Swiss plateau by in situ and remote sensing measurements as well as by the COSMO-2 model." Atmospheric Chemistry and Physics 13205-13221. doi:10.5194/acp-14-13205-2014.

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.

Joo, S., J. Eyre, and R. Marriott. 2013. "The Impact of MetOp and Other Satellite Data within the Met Office Global NWP System Using an Adjoint-Based Senitivity Method." Monthly Weather Review 3331-3342. doi:DOI: 10.1175/MWR-D-12-00232.1.

Klein, M. 2023. Systems for Passive Microwave Remote Sensing and their Calibration Methods. USA Patent 11,567,015 B2. January 31.

Kuchler, N., D. D. Turner, U. Lohnert, and S. Crewell. 2016. "Calibrating ground-based microwave radiometers:Uncertainty and drifts." Radio Science 311-327. doi:doi:10.1002/2015RS005826.

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

Miacci, M., and C. F. Angelis. 2018. "Ground-Based Microwave Radiometer Calibration: an Overview." Journal of Aerospace Technology and Management. doi:10.5028/jatm.v10.927.

Paine, S. N., D. D. Turner, and N. Kuchler. 2014. "Understanding thermal drift in liquid nitrogen loads used for radiometric calibration in the field." Journal of Atmospheric and Oceanic Technology 31: 647-655.