Functional Model of Communication Network of Microwave Link Stations with Adaptive Modulation and Package Switching

The article describes the model of the communication network functioning, which consist of microwave link stations with adaptive modulation and packet switching. Mathematical expressions are presented, which allow to calculate particular indicators of stability and throughput of microwave link intervals, lines and communication directions, as well as generalized quality indicators of the communication network as a whole, taking into account the peculiarities of the functioning of microwave link stations with adaptive modulation and packet switching under the fading conditions at separate microwave link intervals.

Water vapor estimation based on one-year data of E-band millimeter-wave link in the northeast of China

The amount of water vapor in the atmosphere is very small, but its content varies greatly in different humidity areas. The change of water vapor will affect the transmission of microwave link signals, and most of the water vapor is concentrated in the lower layer, so the water vapor density can be measured by the change of the near-ground microwave link transmission signal. This study collected one-year data of the E-band millimeter-wave link in Hebei, China, and used a model based on the ITU-R to estimate the water vapor density. An improved method of extracting the water vapor induced attenuation value is also introduced. It has a higher time resolution and the estimation error is lower than the previous method. In addition, this paper conducts the seasonal analysis of water vapor inversion for the first time. The monthly and seasonal evaluation index results show a high correlation between the retrieved water vapor density the actual water vapor density value measured by the local weather station. The correlation value for the whole year is up to 0.95, the root mean square error is as low as 0.35, and the average relative error is as low as 0.05. This research shows that millimeter-wave backhaul link provides high-precision data for the measurement of water vapor density and has a positive effect on future weather forecast research.

Evaluation of Vertical Refractivity Profile over Microwave Link in Mowe, Nigeria

The radio refractive index structure of the lower section of the atmospheric boundary layer is critical in the planning and construction of microwave communication connections. This study analyses the refractivity profile carried out in Mowe (6.8085° N, 3.4367° E) South – Western Nigeria. Ground measurements of air pressure, temperature, and relative humidity used in this investigation were collected from the rain gauge of the Tropospheric Observatory Data Acquisition Network (TRODAN). The radio refractivity, associated refractivity gradient and climatic factor were computed using data from January 2012 to December 2013. The vertical distributions of radio refractivity were then calculated using these parameters. Seasonal fluctuations in refractivity are visible over the location, with high values in the wet season and low values in the dry season. The findings also suggest that propagation circumstances fluctuate in frequency, with sub-refractive situations being most common between April and September. This is an indication that microwave link in Mowe will suffer higher signal loss during wet season, while the loss may be mild during the dry season. The refractivity values in this study are expected to aid in determining the necessary mitigation to be put in place to reduce loss of signal in Mowe.

A year of attenuation data from a commercial dual-polarized duplex microwave link with concurrent disdrometer, rain gauge, and weather observations

Commercial microwave links (CMLs) in telecommunication networks can provide relevant information for remote sensing of precipitation and other environmental variables, such as path-averaged drop size distribution, evaporation, or humidity. The CoMMon field experiment (COmmercial Microwave links for urban rainfall MONitoring) mainly focused on the rainfall observations by monitoring a 38 GHz dual-polarized CML of 1.85 km path length at a high temporal resolution (4 s), as well as a co-located array of five disdrometers and three rain gauges over 1 year. The dataset is complemented with observations from five nearby weather stations. Raw and pre-processed data, which can be explored with a custom static HTML viewer, are available at https://doi.org/10.5281/zenodo.4923125 (Špačková et al., 2021). The data quality is generally satisfactory for further analysis, and potentially problematic measurements are flagged to help the analyst identify relevant periods for specific study purposes. Finally, we encourage potential applications and discuss open issues regarding future remote sensing with CMLs.

The MSG Technique: Improving Commercial Microwave Link Rainfall Intensity by Using Rain Area Detection from Meteosat Second Generation

Commercial microwave link (MWL) used by mobile telecom operators for data transmission can provide hydro-meteorologically valid rainfall estimates according to studies in the past decade. For the first time, this study investigated a new method, the MSG technique, that uses Meteosat Second Generation (MSG) satellite data to improve MWL rainfall estimates. The investigation, conducted during daytime, used MSG optical (VIS0.6) and near IR (NIR1.6) data to estimate rain areas along a 15 GHz, 9.88 km MWL for classifying the MWL signal into wet–dry periods and estimate the baseline level. Additionally, the MSG technique estimated a new parameter, wet path length, representing the length of the MWL that was wet during wet periods. Finally, MWL rainfall intensity estimates from this new MSG and conventional techniques were compared to rain gauge estimates. The results show that the MSG technique is robust and can estimate gauge comparable rainfall estimates. The evaluation scores every three hours of RMSD, relative bias, and r2 based on the entire evaluation period results of the MSG technique were 2.61 mm h−1, 0.47, and 0.81, compared to 2.09 mm h−1, 0.04, and 0.84 of the conventional technique, respectively. For convective rain events with high intensity spatially varying rainfall, the results show that the MSG technique may approximate the actual mean rainfall estimates better than the conventional technique.

Improved Gridded Precipitation Data Derived from Microwave Link Attenuation

The motivation for improving gridded precipitation data lies in weather now-casting and flood forecasting. Therefore, over the past decade, Commercial Microwave Link (CML) attenuation data have been used to determine rain rates between microwave antennas, and to produce more accurate countrywide precipitation grids. CML networks offer a unique advantage for precipitation measurements due to their high density. However, these data experience uncertainty from several sources as reported in earlier research. This current work determines the reliability of rainfall measurements for each link by comparing CML-derived rain rates to adjusted weather radar rainfall at the link location, over three months. Dynamic Time Warping (DTW) is applied to the pair of CML/radar time-series data in two study areas, Israel and Netherlands. Based on the DTW amplitude and temporal distance, unreliable links are identified and flagged, and interpolated gridded precipitation data are derived in each country after filtering out those unreliable links. Correlations between CML-derived grids and rain observations from an independent set of gauges, tested over several rain events in both study areas, are higher for the reliable subset of CML than the full set. For certain storm events, the Kendall rank correlation for the set of reliable CML is almost double that of the complete set, demonstrating that improved gridded precipitation data can be obtained by removing unreliable links.

Country-wide CML rainfall estimation and CML-Radar combination in Germany

<p>Commercial microwave links (CMLs) have emerged as a valuable source of rainfall information that can complement existing observations. In Germany, we acquire attenuation data from 4000 CMLs with a temporal resolution of one minute. In this contribution we present our results of deriving country-wide rainfall information from these CML data and show the first long-term application of CML data for adjusting the radar rainfall field.</p><p>We present results of a large-scale analysis of our country-wide dataset for one full year (Graf et al. 2020) and compare it with the gauge adjusted radar product RADOLAN-RW from the German Weather Service and the climatologically corrected radar product RADKLIM-YW. Our analysis also compares several different methods for processing CML data, including our recent improvements for the separation of dry and rainy periods in noisy CML attenuation time series based on a convolutional neural network (Polz et al. 2020). We show seasonal and diurnal variations of the performance of CML-derived rainfall data. Promising results are achieved year-round except for periods with solid precipitation. Pearson correlations for the comparison of the hourly rainfall sums reach up to 0.7 for summer months.</p><p>Furthermore, we present results from using the CML rainfall estimates to adjust radar rainfall fields. We extended the RADOLAN-method for radar-gauge adjustment for this purpose. The path-averaged CML rainfall information is compared to the gridded radar rainfall information at the path-intersecting grids. This information is then used in addition to the adjustments derived from rain gauges. We show first results of an hourly adjustment over several months. We further discuss the envisaged operational system for this application and give an outlook on the potential for radar rainfall field adjustments with higher temporal resolutions.</p><p>Graf, M., Chwala, C., Polz, J., and Kunstmann, H.: Rainfall estimation from a German-wide commercial microwave link network: optimized processing and validation for 1 year of data, Hydrol. Earth Syst. Sci., 24, 2931–2950, https://doi.org/10.5194/hess-24-2931-2020, 2020</p><p>Polz, J., Chwala, C., Graf, M., and Kunstmann, H.: Rain event detection in commercial microwave link attenuation data using convolutional neural networks, Atmos. Meas. Tech., 13, 3835–3853, https://doi.org/10.5194/amt-13-3835-2020, 2020</p>