Accurate rainfall monitoring is important, and previously it has been shown that microwave backhaul link between adjacent base station towers can be used for rainfall estimation. However, with the deployment of 5G using millimeter technology, there is opportunity for dense rainfall monitoring network using both backhaul and data transmission links. This paper presents our millimeter-wave measurement results during rainy days in Beijing, China. Our measurement design is an exemplary line-of-sight transmission link. We show that it is possible to retrieve the path-averaged rain rate from the measurement and to use both millimeter-wave transmission link and backhaul link to assist rainfall monitoring. Compared to the local rain measurement from rain gauge and disdrometer, we show that the correlation value of millimeter-wave link retrieved average rain rate varies between 0.6 and 0.9 for different rainfall events. There is room for improvement, and we find that if we can monitor the received signal for a sufficiently long period of time, we can quantify the bias due to fading and work out a better estimate of the rain retrieval model's reference level.

Wireless communication has become a very important part of our lives, and it is well known that meteorological factors affect the quality of communication links, especially at higher frequencies because the physical dimensions of raindrops, hail stones, and snowflakes are on a similar wavelength to the propagating radio frequency. Millimeter-waves are an important technology for fifth-generation cellular networks which are currently being deployed all over the world. Since atmospheric effects are challenging in millimeter-wave transmissions, in this paper, we conducted line-of-sight field measurements at 25 GHz and 38 GHz. We monitored the received signal during rainfall events and compared the theoretical attenuation and the recorded rain-induced attenuation. We also derived the rain-induced attenuation (A) and rainfall rate (R) relation for stratiform and convective rain, respectively, using local rain drop size distribution (DSD) information at our measurement site collected during the period of two years. Furthermore, opportunistic sensing of atmospheric phenomena using microwave or millimeter-wave communication links in commercial cellular networks has recently attracted more attention in meteorological research worldwide. The accuracy of calculating rainfall rates from microwave links highly depends on the retrieval model and values of coefficients in the model, i.e., a and b of the A-R relation model. Here, the coefficients a and b are estimated based on local DSD measurement, and the performance of the improved A-R model is evaluated using propagated signal power based on measurement data. Compared to the (a, b) coefficients in the International Telecommunication Union Recommendation (ITU-R) P.838 document, the derived coefficients achieved an improved rainfall rate estimation.

Cloud top height (CTH) is an essential pareter for the general circulation model in understanding the impact of clouds on the Earth’s radiation budget and global climate change. This paper compares the CTH products, derived from the Moderate Resolution Imaging Spectroradiometer (MODIS), onboard the Aqua and Terra satellites with ground-based Ka band radar data in Beijing from 2014 to 2017. The aim was to investigate the data accuracy and the difference in CTH measurements between passive satellite data and active ground-based radar data. The results show that MODIS, on average, underestimates CTH relative to radar by −1.08 ± 2.48 km, but with a median difference of −0.65 km and about 48% of differences are within 1 km. Statistically, MODIS CTHs which are greater than 6 km show lower discrepancy to radar CTH than those of MODIS CTHs less than 4 km. The CTH difference is independent of cloud fraction and cloud layer. It shows strong dependence on cloud depth, decreasing as cloud depth increases. There is a tendency for MODIS to underestimate high thin clouds but overestimate low thin clouds relative to radar. Total ozone, SO₂, CO, NO₂, aerosol PM₁₀, total water vapor and temperature inversion show unobvious influences in the CTH discrepancy. It is shown that the MODIS CO₂-slicing technique performs much better than IRW (infrared window) technique when cloud layer is higher than 2 km. The average difference calculated from all comparisons by CO₂-slicing technique and IRW technique is 0.09 ± 1.58 km, and −2.20 ± 2.73 km, respectively.

Records and projections of increasing global average temperature call for improvements of global stocktake inputs, which are vital to achieving targets of intergovernmental agreements on climate change. Unmanned Aerial Vehicle (UAV)-based atmospheric observation of greenhouse gas (GHG) concentrations is an upcoming addition to the top-down measurement methods due to its advantageous spatial-temporal resolutions, greater coverage area and lower costs. Hence, we developed and tested a lightweight UAV payload enclosure integrating a non-dispersive diffusion infrared (NDIR) spectrometer and two electrochemical sensors for measurements of carbon dioxide (CO₂), carbon monoxide (CO) and nitrogen dioxide (NO₂). To achieve higher response times and maintain measurement qualities, we designed a custom air inlet on the rotor-facing side of the enclosure to reduce measurement fluctuations caused by rotor downwash airflow. To validate the payload design, we conducted a controlled test for comparing chambered and chamber-less NDIR spectrometer measurements. From the test we observed a reduction of 0.48 hPa in terms of standard deviation of pressure measurements and minimised downwash-flow-induced anomalous biases (+0.49 ppm and +0.08 hpa for chambered compared to −1.33 ppm and −1.05 hpa for chamber-less). We also conducted an outdoor in-situ measurement test with multiple flights reaching 500 m above ground level (ABGL). The test yielded high resolution results representing vertical distributions of mole fraction concentrations of three types of gases via two types of flight trajectory planning methods. Therefore, we provide an alternative UAV payload integration method for NDIR spectrometer CO₂ measurements that complement existing airborne GHG observation methodologies. Additionally, we also introduced an aerodynamic approach in reducing measurement noises and biases for a low response time sensor configuration.

A new dual-frequency Doppler polarimetric cloud radar (DDCR), working at 35-GHz (Ka-band radar, wavelength: 8.6 mm) and 94-GHz (W-band radar, wavelength: 3.2 mm) frequencies, has been in operation at Yangbajing Observatory on the Tibetan Plateau (China) for more than a year at the time of writing. Calculations and field observations show that the DDCR has a high detection sensitivity of −39.2 dBZ at 10 km and −33 dBZ at 10 km for the 94-GHz radar and 35-GHz radar, respectively. The radar reflectivity measured by the two radars illustrates different characteristics for different types of cloud: for precipitation, the attenuation caused by liquid cloud droplets is obviously more serious for the 94-GHz radar than the 35-GHz radar (the difference reaches 40 dB in some cases), and the 94-GHz radar lost signals due to serious attenuation by heavy rainfall; while for clouds dominated by ice crystals where the attenuation significantly weakens, the 94-GHz radar shows better detection ability than the 35-GHz radar. Observations in the Tibetan region show that the 35-GHz radar is prone to missing cloud near the edge, such as the cloud-top portion, resulting in underestimation of the cloud-top height (CTH). Statistical analysis based on one year of observations shows that the mean CTH measured by the 94-GHz radar in the Tibetan region is approximately 600 m higher than that measured by the 35-GHz radar. The analysis in this paper shows that the DDCR, with its dual-frequency design, provides more valuable information than simpler configurations, and will therefore play an important role in improving our understanding of clouds and precipitation in the Tibetan region.