## 1 Introduction  
Laser technology offers unique remote non-invasive chemical sensing capabilities, and plays an important role in a broad range of applications such as industrial monitoring and emission control [1,2] exhaled breath analysis for medical diagnostics [3,4], or security and safety applications [5]. One of the most dynamically developing areas of laser-based spectroscopic sensing is focused on environmental monitoring. Despite the environmental importance of various atmospheric trace-gases (CO\({}_{2}\), N\({}_{2}\)O, NO, CH\({}_{4}\), O\({}_{3}\), _etc._), exact knowledge about the location and magnitude of their emission sources and sinks is still very limited. In this respect, remote sensing technologies can offer a convenient and cost-effective solution for field deployed sensors that can monitor large areas while providing good temporal and spatial resolution of precise trace-gas concentration data. Most of the currently available remote sensors are based on optical detection that utilizes measurements of light absorption to determine chemical composition of the sample. At shorter wavelengths in the ultra-violet and visible spectral range, laser detection and ranging (LIDAR) technologies that rely on backscattering of light from particles in the atmosphere can also be used for chemical detection if spectroscopic information is being retrieved. Differential techniques such as differential absorption LIDAR (DIAL) utilize measurements at different optical frequencies for spectroscopic information retrieval, but the sensitivity, and most importantly, the specificity of those systems is moderate [6]. Particularly important for chemical sensing is the mid-infrared (mid-IR) spectral region, where most chemicals in the gas phase exhibit their strongest ro-vibrational absorption bands. However, scattering in the atmosphere is less effective at longer wavelengths and remote sensing is usually implemented in a hard-target LIDAR configuration, often with retroreflectors used as hard targets to enhance return optical signals. A majority of remote sensing spectroscopic LIDAR/DIAL systems use a direct laser absorption spectroscopy (DLAS) technique or its derivatives based on wavelength modulation spectroscopy (WMS). In DLAS the measured signal is typically detected as a small intensity change over a large background of the total transmitted laser intensity. Due to transmission variations, which are likely to occur in remote sensing configurations, the DLAS baseline is prone to significant fluctuations that might be misinterpreted as a molecular absorption. WMS is known to suppress baseline and 1/f noise and thus can improve detection sensitivity. However, the WMS signal is still intensity-dependent and requires normalization by the received power, which especially in low-light conditions might be a source of a significant measurement error. Such a power normalization using the first harmonic of the WMS signal, or through direct power level monitoring, was successfully demonstrated in the near-infrared spectral region (near-IR) where excellent photodetectors with negligible nonlinearities are available [7,8]. In the mid-infrared (mid-IR) photodetectors are usually strongly nonlinear, which makes such normalization far more challenging or impossible. Therefore there is a clear need for remote sensing technologies that could mitigate those limitations of DLAS/WMS while offering cost effective solutions for remote chemical sensing over large areas with high sensitivity and chemical selectivity. Recently we have introduced the concept of chirped laser dispersion spectroscopy (CLaDS), a novel technique for quantitative trace gas detection based on molecular dispersion measurements [9]. In contrast to most gas sensing methods, CLaDS does not measure absorption but instead it detects refractive index changes that occur in the vicinity of a molecular transition. Because CLaDS is essentially a phase detection technique, the CLaDS measurement is highly immune to variations of optical power at the photodetector.