Atmospheric Boundary Layer Height: Inter-Comparison of Different Estimation Approaches Using the Raman Lidar as Benchmark

This work stems from the idea of improving the capability to measure the atmospheric boundary layer height (ABLH) in variable or unstable weather conditions or in the presence of turbulence and precipitation events. A new approach based on the use of rotational and roto-vibrational Raman lidar signals is considered and tested. The traditional gradient approach based on the elastic signals at wavelength 532 nm is also considered. Lidar data collected by the University of Basilicata Raman lidar (BASIL) within the Special Observation Period 1 (SOP 1) in Cardillargues (Ceveninnes-CV supersite) during the Hydrological Cycle in the Mediterranean Experiment (HyMeX) were used. Our attention was specifically focused on the data collected during the period 16-21 October 2012. ABLH estimates from the Raman lidar were compared against other innovative methods, such as the recently established Morphological Image Processing Approach (MIPA) and the temperature gradient technique applied to potential temperature obtained from radio-sounding data. For each considered methodology, a statistical analysis was carried out. In general, the results from the different methodologies are in good agreement. Some deviations have been observed in correspondence with quite unstable weather conditions

Whitepaper: Understanding land-atmosphere interactions through tower-based flux and continuous atmospheric boundary layer measurements

Executive summary ● Target audience: AmeriFlux community, AmeriFlux Science Steering Committee & Department of Energy (DOE) program managers [ARM/ASR (atmosphere), TES (surface), and SBR (subsurface)] ● Problem statement: The atmospheric boundary layer mediates the exchange of energy and matter between the land surface and the free troposphere integrating a range of physical, chemical, and biological processes. However, continuous atmospheric boundary layer observations at AmeriFlux sites are still scarce. How can adding measurements of the atmospheric boundary layer enhance the scientific value of the AmeriFlux network? ● Research opportunities: We highlight four key opportunities to integrate tower-based flux measurements with continuous, long-term atmospheric boundary layer measurements: (1) to interpret surface flux and atmospheric boundary layer exchange dynamics at flux tower sites, (2) to support regionalscale modeling and upscaling of surface fluxes to continental scales, (3) to validate land-atmosphere coupling in Earth system models, and (4) to support flux footprint modelling, the interpretation of surface fluxes in heterogeneous terrain, and quality control of eddy covariance flux measurements. ● Recommended actions: Adding a suite of atmospheric boundary layer measurements to eddy covariance flux tower sites would allow the Earth science community to address new emerging research questions, to better interpret ongoing flux tower measurements, and would present novel opportunities for collaboration between AmeriFlux scientists and atmospheric and remote sensing scientists. We therefore recommend that (1) a set of instrumentation for continuous atmospheric boundary layer observations be added to a subset of AmeriFlux sites spanning a range of ecosystem types and climate zones, that (2) funding agencies (e.g., Department of Energy, NASA) solicit research on land-atmosphere processes where the benefits of fully integrated atmospheric boundary layer observations can add value to key scientific questions, and that (3) the AmeriFlux Management Project acquires loaner instrumentation for atmospheric boundary layer observations for use in experiments and short-term duration campaigns

Variability of the boundary layer over an urban continental site based on 10 years of active remote sensing observations in Warsaw

Atmospheric boundary layer height (ABLH) was observed by the CHM15k ceilometer (January 2008 to October 2013) and the PollyXT lidar (July 2013 to December 2018) over the European Aerosol Research LIdar NETwork to Establish an Aerosol Climatology (EARLINET) site at the Remote Sensing Laboratory (RS-Lab) in Warsaw, Poland. Out of a maximum number of 4017 observational days within this period, a subset of quasi-continuous measurements conducted with these instruments at the same wavelength (1064 nm) was carefully chosen. This provided a data sample of 1841 diurnal cycle ABLH observations. The ABLHs were derived from ceilometer and lidar signals using the wavelet covariance transform method (WCT), gradient method (GDT), and standard deviation method (STD). For comparisons, the rawinsondes of the World Meteorological Organization (WMO 12374 site in Legionowo, 25 km distance to the RS-Lab) were used. The ABLHs derived from rawinsondes by the skew-T-log-p method and the bulk Richardson (bulk-Ri) method had a linear correlation coefficient (R2) of 0.9 and standard deviation (SD) of 0.32 km. A comparison of the ABLHs obtained for different methods and instruments indicated a relatively good agreement. The ABLHs estimated from the rawinsondes with the bulk-Ri method had the highest correlations, R2 of 0.80 and 0.70 with the ABLHs determined using the WCT method on ceilometer and lidar signals, respectively. The three methods applied to the simultaneous, collocated lidar, and ceilometer observations (July to October 2013) showed good agreement, especially for the WCT method (R2 of 0.94, SD of 0.19 km). A scaling threshold-based algorithm was proposed to homogenize ceilometer and lidar datasets, which were applied on the lidar data, and significantly improved the coherence of the results (R2 of 0.98, SD of 0.11 km). The difference of ABLH between clear-sky and cloudy conditions was on average below 230 m for the ceilometer and below 70 m for the lidar retrievals. The statistical analysis of the long-term observations indicated that the monthly mean ABLHs varied throughout the year between 0.6 and 1.8 km. The seasonal mean ABLH was of 1.16 ± 0.16 km in spring, 1.34 ± 0.15 km in summer, 0.99 ± 0.11 km in autumn, and 0.73 ± 0.08 km in winter. In spring and summer, the daytime and nighttime ABLHs appeared mainly in a frequency distribution range of 0.6 to 1.0 km. In winter, the distribution was common between 0.2 and 0.6 km. In autumn, it was relatively balanced between 0.2 and 1.2 km. The annual mean ABLHs maintained between 0.77 and 1.16 km, whereby the mean heights of the well-mixed, residual, and nocturnal layer were 1.14 ± 0.11, 1.27 ± 0.09, and 0.71 ± 0.06 km, respectively (for clear-sky conditions). For the whole observation period, the ABLHs below 1 km constituted more than 60% of the retrievals. A strong seasonal change of the monthly mean ABLH diurnal cycle was evident; a mild weakly defined autumn diurnal cycle, followed by a somewhat flat winter diurnal cycle, then a sharp transition to a spring diurnal cycle, and a high bell-like summer diurnal cycle. A prolonged summertime was manifested by the September cycle being more similar to the summer than autumn cycles

Lidar and S-band radar profiling of the atmosphere : adaptive processing for boundary-layer monitoring, optical-parameter error estimation, and application cases

This Ph.D. thesis addresses remote sensing of the atmosphere by means of lidar and S-band clear-air weather radar, and related data signal processing. Active remote sensing by means of these instruments offers unprecedented capabilities of spatial and temporal resolutions for vertical atmospheric profiling and the retrieval of key optical and physical atmospheric products in an increasing environmental regulatory framework. The first goal is this Ph.D. concerns the estimation of error bounds in the inversion of the profile of the atmospheric backscatter coefficient from elastic lidar signals (i.e., without wavelength shift in reception when interacting with atmospheric scatterers) by means of the two-component inversion algorithm (the so-called Klett-Fernald-Sasano¿s algorithm). This objective departs from previous works at the Remote Sensing Lab. (RSLab) of the Universitat Politècnica de Catalunya (UPC) and derives first-order error-propagated bounds (approximate) and total-increment bounds (exact). As distinctive feature in the state of the art, the error bounds merge into a single body both systematic (i.e., user-calibration inputs) and random error sources (finite signal-to-noise ratio, SNR) yielding an explicit mathematical form. The second goal, central to this Ph.D., tackles retrieval of the Atmospheric Boundary Layer Height (ABLH) from elastic lidar and S-band Frequency-Modulated Continuous-Wave (FMCW) radar observations by using adaptive techniques based on the Extended Kalman Filter (EKF). The filter is based on morphological modelling of the Mixing-Layer-to-Free-Troposphere transition and continuous estimation of the noise covariance information. In the lidar-EKF realization the proposed technique is shown to outperform classic ABLH estimators such as those based on derivative techniques, thresholded decision, or the variance centroid method. The EKF formulation is applied to both ceilometer and UPC lidar records in high- and low-SNR scenes. The lidar-EKF approach is re-formulated and successfully extended to S-band radar scenes (Bragg¿s scattering) in presence of interferent noise sources (Rayleigh scattering from e.g., insects and birds). In this context, the FMCW feature enables the range-resolved capability. EKF-lidar and EKF-radar ABLH estimates are cross-examined from field campaign results. Finally, the third goal deals with exploitation of the existing UPC lidar station: In a first introductory part, a modified algorithm for enhancing the dynamic range of elastic lidar channels by ¿gluing¿ analog and photon-counting data records is formulated. In a second part, two case examples (including application of the gluing algorithm) are presented to illustrate the capabilities of the UPC lidar in networked atmospheric observation of two recent volcano eruption events as part of the EARLINET (European Aerosol Research Lidar Network). The latter is part of GALION (Global Atmospheric Watch Atmospheric Lidar Observation Network)-GEOSS (Global Earth Observation System of Systems) framework.La tesis doctoral aborda la teledetecció atmosfèrica amb tècniques lidar i radar (banda S) i llur tractament del senyal. La teledetecció activa amb aquests instruments ofereix resolucions espacials i temporals sense precedents en la perfilometria vertical de l'atmosfera i recuperació de productes de dades òptics i físics atmosfèrics en un marc de creixent regulació mediambiental. El primer objectiu d'aquesta tesi concerneix l'estimació de cotes d'error en la inversió del perfil del coeficient de retrodispersió atmosfèrica a partir de senyals lidar de tipus elàstic (és a dir, sense desplaçament de la longitud d'ona en recepció al interactuar amb els dispersors atmosfèrics) mitjançant l'algorisme d'inversió de dues components de Klett-Fernald-Sasano. Aquest objectiu parteix de treballs previs en el Remote Sensing Lab. (RSLab) de la Universitat Politècnica de Catalunya (UPC) i permet obtenir cotes de primer ordre (aproximades) basades en propagació d'errors i cotes (exactes) basades en el increment total de l'error. Característica diferencial en front l'estat de l'art és l'assimilació d'errors sistemàtics (per exemple, entrades de cal.libració d'usuari) i aleatoris (relació senyal-soroll, SNR, finita) en forma matemàtica explícita. El segon objectiu, central de la tesis, aborda l'estimació de l'altura de la capa límit atmosfèrica (ABLH) a partir de senyal lidar elàstics i d'observacions radar en banda S (ona continua amb modulació en freqüència, FMCW) utilitzant tècniques adaptatives basades en filtrat estès de Kalman (EKF). El filtre es basa en modelat morfològic de la transició atmosfèrica entre la capa de mescla i la troposfera lliure i en l'estimació continua de la informació de covariança del soroll. En el prototipus lidar-EKF la tècnica proposada millora clarament les tècniques clàssiques d'estimació de la ABLH como són les basades en mètodes derivatius, decisió de llindar, o el mètode de la variança-centroide. La formulació EKF s'aplica tant a mesures procedents de ceilòmetres lidar como de la pròpia estació lidar UPC en escenes d'alta i baixa SNR. Addicionalment, l'enfoc lidar-EKF es reformula i s'estén amb èxit a escenes radar en banda S (dispersió Bragg) en presència de fonts de soroll interferent (dispersió Rayleigh de, per exemple, insectes i ocells). En aquest context, la característica FMCW permet la capacitat de resolució en distància. L'estimació de la ABLH amb els prototipus lidar-EKF i radar-EKF s'intercompara en campanyes de mesura. Finalment, el tercer objectiu atén a l'explotació de l'estació lidar UPC existent: En una primera part introductòria, es formula un algorisme modificat de "gluing" per a la millora del marge dinàmic de canals lidar elàstics mitjançant combinació (o "enganxat") de senyals lidar adquirits analògicament i amb foto-comptatge. En una segona part, es presenten dos exemples (incloent l'aplicació de l'algorisme de "gluing") que il.lustren les capacitats del lidar de la UPC en l'observació atmosfèrica de dos recents erupcions volcàniques des de la xarxa d'observació EARLINET (European Aerosol Research Lidar Network). Aquesta última és part de GALION (Global Atmospheric Watch Atmospheric Lidar Observation Network)-GEOSS (Global Earth Observation System of Systems)

EARLINET: a european aerosol research lidar network to establish an aerosol climatology

Peer ReviewedPostprint (published version

Atmosphere Boundary Layer Height (ABLH) Determination under Multiple-Layer Conditions Using Micro-Pulse Lidar

Accurate estimation of the atmospheric boundary layer height (ABLH) is critically important and it mainly relies on the detection of the vertical profiles of atmosphere variables (temperature, humidity,’ and horizontal wind speed) or aerosols. Aerosol Lidar is a powerful remote sensing instrument frequently used to retrieve ABLH through the detection of the vertical distribution of aerosol concentration. A challenge is that cloud, residual layer (RL), and local signal structure seriously interfere with the lidar measurement of ABLH. A new objective technique presenting as giving a top limiter altitude is introduced to reduce the interference of RL and cloud layer on ABLH determination. Cloud layers are identified by looking for the rapid increase and sharp attenuation of the signal combined with the relative increase in the signal. The cloud layers whether they overlay the ABL are classified or are decoupled from the ABL are classified by analyzing the continuity of the signal below the cloud base. For cloud layer capping of the ABL, the limiter is determined to be the altitude where a positive signal gradient first occurs above the cloud upper edge. For a cloud that is decoupled from the ABL, the cloud base is considered to be the altitude limiter. For RL in the morning, the altitude limiter is the greatest positive gradient altitude below the RL top. The ABLH will be determined below the top limiter altitude using Haar wavelet (HM) and the curve fitting method (CFM). Besides, the interference of local signal noise is eliminated through consideration of the temporal continuity. While comparing the lidar-determined ABLH by HM (or CFM) and nearby radiosonde measurements of the ABLH, a reasonable concordance is found with a correlation coefficient of 0.94 (or 0.96) and 0.79 (or 0.74), presenting a mean of the relative absolute differences with respect to radiosonde measurements of 10.5% (or 12.3%) and 22.3% (or 17.2%) for cloud-free and cloudy situations, respectively. The diurnal variations in the ABLH determined from HM and CFM on four selected cases show good agreement with a mean correlation coefficient higher than 0.99 and a mean absolute bias of 0.22 km. Also, the determined diurnal ABLH are consistent with surface turbulent kinetic energy (TKE) combined with the time-height distribution of the equivalent potential temperature