RESUMEN
Global ultraviolet (UV) surface reflectivity climatologies are all composed from daylight passive remote sensing observations of reflected UV light, generally integrated over a distribution of attainable reflection directions. We discovered the sensitivity of Aeolus lidar surface returns (LSR) to surface characteristics, providing the first evidence that active remote sensing can be effectively used for retrieving unidirectional UV surface reflectivity on global scales. LSR reproduces surface reflectivity monthly changes in Sahara, which are visible in the Lambertian Equivalent Reflectivity (LER) climatologies from TROPOMI and GOME-2. Very high correlations (r > 0.90) between gridded LSR and the LER climatologies are reported at global and regional scales for 36 different regions. Three clear land cover gradients are discerned from Aeolus LSR signal: (1) water/land, (2) vegetation/arid areas and (3) no snow/snow. The strongest LSR signal was retrieved over snow, while over vegetation, we found moderate negative agreement (r < - 0.60) between LSR and vegetation index proxy. Overall, the success of the first active remote sensing method for retrieving unidirectional UV surface reflectivity using Aeolus is demonstrated. Our approach can be effectively used to detect unresolved land and, especially, snow cover changes in high latitudes because, unlike passive instruments, Aeolus also provided nighttime observations.
RESUMEN
An intercomparison of ozone differential absorption lidar algorithms was performed in 1996 within the framework of the Network for the Detection of Stratospheric Changes (NDSC) lidar working group. The objective of this research was mainly to test the differentiating techniques used by the various lidar teams involved in the NDSC for the calculation of the ozone number density from the lidar signals. The exercise consisted of processing synthetic lidar signals computed from simple Rayleigh scattering and three initial ozone profiles. Two of these profiles contained perturbations in the low and the high stratosphere to test the vertical resolution of the various algorithms. For the unperturbed profiles the results of the simulations show the correct behavior of the lidar processing methods in the low and the middle stratosphere with biases of less than 1% with respect to the initial profile to as high as 30 km in most cases. In the upper stratosphere, significant biases reaching 10% at 45 km for most of the algorithms are obtained. This bias is due to the decrease in the signal-to-noise ratio with altitude, which makes it necessary to increase the number of points of the derivative low-pass filter used for data processing. As a consequence the response of the various retrieval algorithms to perturbations in the ozone profile is much better in the lower stratosphere than in the higher range. These results show the necessity of limiting the vertical smoothing in the ozone lidar retrieval algorithm and questions the ability of current lidar systems to detect long-term ozone trends above 40 km. Otherwise the simulations show in general a correct estimation of the ozone profile random error and, as shown by the tests involving the perturbed ozone profiles, some inconsistency in the estimation of the vertical resolution among the lidar teams involved in this experiment.
RESUMEN
The use of powerful Raman backscatter lidars enables one to measure the stratospheric aerosol extinction profile independently of the backscatter, thereby obtaining additional information to aid in retrieving the physical characteristics of the sampled aerosol. We used principal component analysis to construct a self-consistent method for the retrieval of aerosol bulk physical and optical properties from multiwavelength elastic and/or inelastic Raman backscatter lidar signals. The procedure is applied to synthetic and actual lidar signals. We found that aerosol surface area and volume can be usefully estimated and that the use of Raman-derived extinction data leads to a notable improvement in the accuracy of the estimations.
RESUMEN
A useful analytic model describing the response of a photon-counting (PC) system has been developed. The model describes the nonlinear count loss and apparent count gain arising from the overlap of photomultiplier tube (PMT) pulses, taking into account the distribution in amplitude of the PMT output pulses and the effect of the pulse-height discrimination threshold. Comparisons between the model and Monte Carlo simulations show excellent agreement. The model has been applied to a PC lidar system with favorable results. Application of the model has permitted us to extend the linear operating range of the PC system and to quantify accurately the response of the system in its nonlinear operating regime, thus increasing the useful dynamic range of the system by 1 order of magnitude.