The planetary boundary layer (PBL) is an important region of study in the troposphere and one of its more important variable: the PBL height (PBLH) is not easy to detect, mainly in stable conditions due to its complexity. In order to detect the PBLH in stable conditions, in this paper, we apply the low-lev jet (LLJ) method using Doppler lidar measurements, which consists on detecting the LLJ and its maximum velocity height, corresponding to the PBLH. In addition, we analyze this method by comparing and relating it with the variance and bulk Richardson number (BRN) method, ensuring its efficiency.
The Latin American Lidar Network (LALINET) is the aerosol lidar network operating over South America. LALINET is now an operative network performing a schedule of routine measurements and, currently, is composed by 9 stations distributed over South America. The main objective of LALINET is to generate a consistent and statistically relevant database to enhance the understanding of the particle distribution over the continent and its direct and indirect influence on climate. The creation of an un-biased spatiotemporal database requires a throughout review of the network on two pillars: instrumentation and data processing. Because most of the LALINET systems are not series-produced instruments and, therefore, present large differences in configuration and capabilities, attempts for network harmonization and, consequently, optimization are mandatory. In this study a review of the current instrumental status of all LALINET systems is done and analyzed in detail in order to assess the potential performance of the network and to detect networking weaknesses.
The so-called Metropolitan Area of São Paulo, one of the largest megacities in the world, faces several problems related to the air quality due the high concentrations of aerosols produced either by local sources or by long-range transporting. Concerned with the elevated concentrations of aerosol and their impact in the air quality and the climate changes inside MASP, a measurement campaign were conducted during the South hemisphere winter of 2012, when the low temperatures and the low level of precipitation contribute to the poor dispersion of aerosols. A Raman Lidar system and air quality monitoring stations from University of São Paulo and Environment Agency of São Paulo State (CETESB) were employed in order to monitor the increasing of aerosol load in the atmosphere. Satellite data, in synergy with HYSPLIT air masses backward trajectories, were applied to track the aerosol from the long-range distanced regions to Metropolitan Area of São Paulo. In the beginning of September 2012, MASP experienced episodes of high air pollution concentration, reaching Aerosol Optical Depth (AOD) values up to 0.89 at 550 nm and particulate matter concentration up to 293 µ g/cm3 . Particle lidar ratio values of 60 to 70 sr retrieved by a Raman Lidar system at 532 nm provided information of the aerosol type, helping to determine the influence of biomass burning advected from large range distance to megacities such as São Paulo
Comprehension about the behavior of the Planet Boundary Layer (PBL) is an important factor in several fields, from analysis about air quality until modeling. However, monitoring the PBL evolution is a complex problem, because few instruments can provide continuous atmospheric measurements with enough spatial and temporal resolution. Inside this scenario lidar systems appear as an important tool, because it complies with all these capabilities- However, PBL observations are not a direct measure, being necessary to use complex mathematic algorithms. Recently, wavelet covariance transforms have been applied in this field. The objective of this work is to compare the performing of distinct types of algorithms: a structured on Haar wavelet and other based on first derivative of Gaussian and Mexican Hat wavelets, and the results were compared with two Hysplit modelling. For this aim, two campaigns were carried out. From the results were possible to infer that both algorithms provide coherent results as the expected, but the Haar algorithm separates the sub-layers more efficiently, so it is the most appropriate to complex situations.
The main objective of this work is to obtain methods that automatically allow qualitative detections of Atmospheric Boundary Layer heights from LIDAR data. Case studies will be used to describe the more relevant days of a campaign carried out in July of 2012 in Vitória, Espírito Santo, Brazil. The data analysis compares three mathematical algorithms that automatically provide the ABL height: Gradient Method (GM), using the derivative of the Range Corrected Signal (RCS) logarithm, WCT (Wavelet Covariance Transform), and Bulk Richardson's Number, which was used to validate the methods mentioned above. The comparison between the methods has shown that as the presence of clouds and the aerosol sublayer increased, the more sensitive was the refinement needed to choose the “right” parameters, whereas even Richardson’s method had ambiguities in finding a good estimate of the ABL top.
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