## 5 Discussion
When comparing Lidar and radar measurements of the cloud base height of the marine stratus shown in Figure 8, after the distance calibration, the obtained difference is less than 40 m. The radar shows reflectivity at lower heights than the ceilometer (consistent with other measurements [25]). Regarding the stratus observed reflectivity, it is around \(-55\) to \(-60\) dBZ, which is a possible value for clouds at this altitude [26]. These relatively weak reflectivity values indicate that the cloud has a low amount of liquid water content [7]. Low amounts of Liquid Water Content are related to lower optical thickness [27], which is consistent with the good penetration of the Lidar beam in the cloud layer. Since both instruments observe the same cloud and obtain similar results in distance and cloud thickness, we can conclude that the radar is operative and capable of detecting clouds at least until 500 m of altitude. Still, the sampled cloud has a relatively low reflectivity value and therefore it is likely that the radar can sense thicker clouds at higher altitudes. In any case, the sensitivity of \(-60\) dBZ at 400 m is already enough to study close to the surface phenomena such as fog or low stratus [9; 28]. It was discovered that the contamination present in the first four range cells is introduced by the switching power supply ripple through the IF amplifiers. It was noted that, by feeding the amplifiers with a better source, while the rest of the components are operated under the same conditions, the first range cells did not show such noise. Contamination in all ranges, randomly present in both experiments, is attributed to artifacts of the signal acquisition system mentioned in Appendix A.4. These artifacts, when they occur, hinder the detection of the beginning and end of each pulse repetition period, interfering with the spectral density estimation. Through the development and evaluation of the radar, potential improvements for the radar have been discovered. The difference between the theoretically calculated and experimental range and range resolution estimations are affected by the lack of a Phase-Lock Loop (PLL) for the Gunn oscillator, which can introduce nonlinearities in the frequency sweep. Even if this can be compensated with linearity corrections and frequent UAV range calibration experiments during atmospheric events of interest, the PLL should be implemented in the near future. In addition, having a highly coherent oscillator is also a requirement for an accurate Doppler velocity estimate. It is also recommended to add an internal temperature control system or to build a specific noise model to correct estimations by software. To enlarge the range coverage, we propose to increase the effective area of the antennas. Finally, more capabilities can be added to the radar or better estimation procedures could be implemented in the digital back-end if more customized digital platforms, such as FPGA, are used. With the current design and campaign, the potentialities of this type of radar were shown. It is able to estimate the base of the cloud with an error of 20 m compared to the estimation of a Lidar. Although this is something that Lidar can do, our system is smaller, consumes less power, and has a lower cost (a \(\sim\)2 factor) than the Lidar, although the Lidar can provide more information than just the base of the cloud. However, the campaign also shows the potentialities of our radar to provide internal information of low altitude clouds or fog. Nevertheless, some improvements have to be performed. Our radar has shown qualitatively the capability of cloud detection. However, the precision of the radar measurement, especially that inside the cloud, requires a more precise calibration. For instance, a 1 dB error in the calibration can produce 15% error in the liquid water content (LWC) [7]. The necessity of performing standardized calibration is highlighted by [29], by founding up to 2 dB of difference among European radars when comparing with the satellite cloud radar CloudSat.