## 3 Remote Sensing with CM-CLaDS
### Ambient N\({}_{2}\)O Sensing
Therefore, to directly compare both results the field characteristics should be multiplied by a factor of \(\left(37.5/10\right)^{1/2}\approx 1.936\). Indeed the experimental data presented in Figure 9 show the same slope for both data sets, except the field results are shifted down by a constant value that corresponds to 1.911 times reduction in noise. This is in excellent agreement with the predicted factor of 1.936 and confirms that in both tests the system was operating within the same noise limit, indicating that no other unpredictable noise sources have been introduced in the less-controlled environment in the field. Figure 8: **Top plot:** A long-term atmospheric N\({}_{2}\)O concentration measurement during the field deployment of the CM-CLaDS sensor (5 min. average of data points recorded in 2 s intervals). **Bottom plot:** The corresponding heterodyne beat-note power indicates opto-mechanical drift of the setup and fluctuations in atmospheric transmission due to varying environmental conditions. **Center plot:** A precipitation rate recorded using an on-site weather station. Each rainfall event is followed by an increase in N\({}_{2}\)O concentration (indicated with arrows) which most likely is a result of nitrification and denitrification processes in soil. During the field deployment several significant precipitation events occurred (Figure 8), and each time a subsequent increase of N\({}_{2}\)O concentration was measured. For the three major rainfalls an increase in concentration is indicated by blue arrows. Although careful analysis of these events is beyond the scope of this work, such correlation has already been observed by other groups [29,30]. N\({}_{2}\)O is naturally produced in soil by the processes of nitrification and denitrification, which can be triggered by rain, causing an increase of the atmospheric N\({}_{2}\)O concentration after precipitation. As a validation of the instrument performance on 29 October (when one of these events occurred) we have performed a cross-comparison of the continuous N\({}_{2}\)O concentration measurement performed by the remote CM-CLaDS sensor with another experimental N\({}_{2}\)O sensing system co-located at the same measurement site. The second system was an open-path point sensor based on the WMS technique developed by [PERSON] _et al._[27,31]. It employed a DFB QCL operating around 2,203 cm\({}^{-1}\) as a spectroscopic source and an open path multi-pass cell has been set-up to probe the N\({}_{2}\)O directly at atmospheric conditions. The N\({}_{2}\)O concentration data sets acquired by both instruments are shown in Figure 10.  
Both sensors recorded a similar average trend in N\({}_{2}\)O concentration, including an increase after the precipitation event. The small short-term discrepancies shown in Figure 10 are primarily attributed to the different active optical paths used in both cases to interact with the atmosphere: long path-integrated CLaDS measurement _vs._ point sensing with WMS system. This cross-comparison result is very encouraging because the CM-CLaDS system was calibrated only once in the laboratory (one week  
Figure 9: The CM-CLaDS N\({}_{2}\)O concentration data noise _vs._ carrier power level based on laboratory (red) and field (grey) measurements in Figures 5 and 8, respectively. For field data the noise is calculated as the standard deviation of 150 consecutive data points and each point corresponds to a 250 ms long data acquisition of the optical signal. This yields an effective averaging time of 37.5 s. For laboratory data from Figure 5 (measured with an effective averaging time of 10 s) the noise was calculated as standard deviation of 200 consecutive data points and each point corresponds to a 50 ms long data acquisition of optical signal. Both data sets were fitted by linear functions shown in black (for field data) and in magenta (for laboratory data). before this test) and after four days of almost undisturbed operation an excellent agreement between the two different sensor systems has been found.