ABSTRACT
This paper presents a first demonstration of range-resolved differential absorption LIDAR (DIAL) measurements of the water vapor main isotopologue H2 16O and the less abundant semi-heavy water isotopologue HD16O with the aim of determining the isotopic ratio. The presented Water Vapor and Isotope Lidar (WaVIL) instrument is based on a parametric laser source emitting nanosecond pulses at 1.98 µm and a direct-detection receiver utilizing a commercial InGaAs PIN photodiode. Vertical profiles of H2 16O and HD16O were acquired in the planetary boundary layer in the suburban Paris region up to a range of 1.5 km. For time averaging over 25 min, the achieved precision in the retrieved water vapor mixing ratio is 0.1 g kg-1 (2.5% relative error) at 0.4 km above ground level (a.g.l.) and 0.6 g kg-1 (20%) at 1 km a.g.l. for 150 m range bins along the LIDAR line of sight. For HD16O, weaker absorption has to be balanced with coarser vertical resolution (600 m range bins) in order to achieve similar relative precision. From the DIAL measurements of H2 16O and HD16O, the isotopic abundance δD was estimated as -51 at 0.4 km above the ground and -119 in the upper part of the boundary layer at 1.3 km a.g.l. Random and systematic errors are discussed in the form of an error budget, which shows that further instrumental improvements are required on the challenging path towards DIAL-profiling of the isotopic abundance with range resolution and precision suitable for water cycle studies.
ABSTRACT
Trade-wind cumuli constitute the cloud type with the highest frequency of occurrence on Earth, and it has been shown that their sensitivity to changing environmental conditions will critically influence the magnitude and pace of future global warming. Research over the last decade has pointed out the importance of the interplay between clouds, convection and circulation in controling this sensitivity. Numerical models represent this interplay in diverse ways, which translates into different responses of trade-cumuli to climate perturbations. Climate models predict that the area covered by shallow cumuli at cloud base is very sensitive to changes in environmental conditions, while process models suggest the opposite. To understand and resolve this contradiction, we propose to organize a field campaign aimed at quantifying the physical properties of trade-cumuli (e.g., cloud fraction and water content) as a function of the large-scale environment. Beyond a better understanding of clouds-circulation coupling processes, the campaign will provide a reference data set that may be used as a benchmark for advancing the modelling and the satellite remote sensing of clouds and circulation. It will also be an opportunity for complementary investigations such as evaluating model convective parameterizations or studying the role of ocean mesoscale eddies in air-sea interactions and convective organization.
ABSTRACT
Although pulsed coherent laser radar vibrometry has been introduced as an improvement over its continuous wave (CW) counterpart, it remains very sensitive to decorrelation noises, such as speckle, and other disturbances of its measurement. Taking advantage of more polyvalent polypulse waveforms, we address the issue with advanced signal processing. We have conducted what we believe is the first extensive comparison of processing techniques considering CW, pulse-pair, and polypulse emissions. In this framework, we introduce a computationally efficient maximum likelihood estimator and test signal tracking on pseudo-time-frequency representations (TFRs), which, respectively, help deal with speckle noise and fading of the signal in harsh noise conditions. Our comparison on simulated signals is validated on a 1.55 microm all-fiber vibrometer experiment with an apparatus simulating vibration and strong speckle noise. Results show the advantage of the estimators that take into account actual noise statistics, and call for a wider use of TFRs to track the vibration-modulated signal.