End-to-end Simulator of a space-borne Raman Lidar for the thermodynamic profiling of the atmosphere

Author(s):  
Noemi Franco ◽  
Paolo Di Girolamo ◽  
Donato Summa ◽  
Benedetto De Rosa ◽  
Andreas Behrendt ◽  
...  

<p>An end-to-end model has been developed in order to simulate the expected performance of a space-borne Raman Lidar, with a specific focus on the Atmospheric Thermodynamics LidAr in Space – ATLAS proposed as a “mission concept” to the ESA in the frame of the “Earth Explorer-11 Mission Ideas” Call. The numerical model includes a forward module, which simulates the lidar signals with their statistical uncertainty, and a retrieval module able to provide vertical profiles of atmospheric water vapour mixing ratio and temperature based on the analyses of the simulated signals. Specifically, the forward module simulates the interaction mechanisms of laser radiation with the atmospheric constituents and the behavior of all the devices present in the experimental system(telescope, optical reflecting and transmitting components, avalanche photodiodes, ACCDs). An analytical expression of the lidar equation for the water vapour and molecular nitrogen roto-vibrational Raman signals and the pure rotational Raman signals from molecular oxygen and nitrogen is used. The analytically computed signals are perturbed by simulating their shot-noise through Poisson statistics. Perturbed signals thus take into account the fluctuations in the number of photons reaching the detector over a certain time interval. The simulator also provides an estimation of the background due to the solar contribution. Daylight background includes three distinct terms: a cloud-free atmospheric contribution, a surface contribution and a cloud contribution[1]. Background is calculated as a function of the solar zenith angle. In order to better estimatethe background contribution, an integration on slant path is performed instead of a classical parallel-planes approximation. The proposed numerical model allows to better simulate solar background for high solar zenith angles, even higher than 90 degrees. Signals simulated through the forward model are then fed into the retrieval module. A background subtraction scheme is used to remove the solar contribution and a vertical averaging is performed to smooth the signals. Based on the application of the roto-vibrational Raman lidar technique, the vertical profile of atmospheric water vapour mixing ratio is obtained from the power ratio of the water vapour to a reference signal, such as molecular nitrogen roto-vibrational Raman signal or an alternative temperature-independent reference signal. A vertical profile of temperature is then obtained through the ratio of high-to-low quantum number rotational Raman signals by the application of the pure rotational Raman lidar technique. Both atmospheric water vapour mixing ratio and temperature measurements require the determination of calibration constants, which can be obtained from the comparison with simultaneous and co-located measurements from a different sensor [2]. The simulator finally provides statistical (RMS) and systematic (bias) uncertainties. Estimates are provided in terms of percentage and absolute (g/kg) uncertainty for water vapour mixing ratio measurements and in terms of absolute uncertainty (K) for temperature measurements.</p><p><strong> </strong><strong>References</strong></p><p>1 - P.Di Girolamo et al., "Spaceborne profiling of atmospheric temperature and particle extinction with pure rotational Raman lidar and of relative humidity in combination with differential absorption lidar: performance simulations"Appl.Opt. 45, 2474-2494(2006)</p><p>2 - P.Di Girolamo et al., "Space-borne profiling of atmospheric thermodynamic variables with Raman lidar: performance simulations,"Opt.Express 26, 8125-8161(2018)</p>

PIERS Online ◽  
2010 ◽  
Vol 6 (3) ◽  
pp. 262-266 ◽  
Author(s):  
Daniele Perissin ◽  
E. Pichelli ◽  
R. Ferretti ◽  
Fabio Rocca ◽  
N. Pierdicca

2016 ◽  
Author(s):  
Paolo Di Girolamo ◽  
Marco Cacciani ◽  
Donato Summa ◽  
Andrea Scoccione ◽  
Benedetto De Rosa ◽  
...  

Abstract. Measurements carried out by the University of BASILicata Raman lidar system (BASIL) are reported to demonstrate the capability of this instrument to characterize turbulent processes within the convective boundary layer (CBL). In order to resolve the vertical profiles of turbulent variables, high resolution water vapour and temperature measurements, with a temporal resolution of 10 s and a vertical resolution of 90 m and 30 m, respectively, are considered. Measurements of higher-order moments of the turbulent fluctuations of water vapour mixing ratio and temperature are obtained based on the application of auto-covariance analyses to the water vapour mixing ratio and temperature time series. The algorithms are applied to a case study (11:30–13:30 UTC, 20 April 2013) from the High Definition Clouds and Precipitation for Climate Prediction (HD(CP)2) Observational Prototype Experiment (HOPE), held in Western Germany in the spring 2013. A new correction scheme for the elastic-signal leakage in the low-quantum number rotational Raman signal is applied. The noise errors are small enough to derive up to fourth-order moments for both water vapour mixing ratio and temperature fluctuations. To the best of our knowledge, BASIL is the first Raman lidar with a demonstrated capability to simultaneously retrieve daytime profiles of water vapour turbulent fluctuations up to the fourth order throughout the atmospheric CBL, this capability being combined with the one to also measure daytime profiles of temperature fluctuations up to the fourth order. For the considered case study, which represents a well-mixed and quasi-stationary CBL, the mean boundary layer height is found to be 1290 ± 77 m a.g.l. Values of the integral scale for water vapour and temperature fluctuations at the top of the CBL are in the range of 70–125 s and 75–225 s, respectively; these values are much larger than the temporal resolution of the measurements (10 s), which testifies that the temporal resolution considered for the measurements is sufficiently high to resolve turbulence processes down to the inertial sub-range and consequently resolve the major part of the turbulent fluctuations. Peak values of all moments are found in the interfacial layer in the proximity of the top of the CBL. Specifically, water vapour and temperature second-order moment (variance) has a maximum value of 0.29 g2 kg−2 and 0.26 K2, respectively, water vapour and temperature third-order moment has a peak value of 0.156 g3 kg−3 and −0.067 K3, respectively, while water vapour and temperature fourth-order moment has a maximum value of 0.28 g4 kg−4 and 0.24 K4, respectively. Water vapour and temperature kurtosis have values of ~ 3 in the entrainment zone, which indicate normally distributed humidity and temperature fluctuations. Reported values of the higher-order moments result to be in good agreement with previous measurements at different locations, thus providing confidence on the possibility to use them for turbulence parameterization in weather and climate models. In the determination of the temperature profiles, particular care was dedicated to minimize potential effects associated with elastic signal leakage in the rotational Raman signals. For this purpose, a specific algorithm was defined and tested to identify and remove signal leakages and to assess the residual systematic uncertainty affecting temperature measurements after correction. The application of this approach confirms that for the present Raman lidar system the leakage factor keeps constant with time, and consequently an appropriate assessment of its constant value allows for a complete removal of the leaking elastic signal from the rotational Raman lidar signals at any time (with a residual error on temperature measurements after correction not exceeding 0.16 K).


2020 ◽  
Vol 237 ◽  
pp. 05012
Author(s):  
Benedetto De Rosa ◽  
Paolo Di Girolamo ◽  
Donato Summa

In November 2012, the University of BASILicata Raman Lidar system (BASIL) was approved to enter the International Network for the Detection of Atmospheric Composition Change (NDACC). Since then measurements were routinely carried out on a once per week basis. This paper illustrates specific measurement examples from this effort, with a dedicated focus on temperature and water vapour measurements, with the ultimate goal to provide a characterization of the system performance. Case studies illustrated in this paper demonstrate the ability of BASIL to perform measurements of the temperature profile up to 50 km and of the water vapour mixing ratio profile up to 15 km, based on an integration time of 2 hours and a vertical resolution of 150 m, with measurement bias not exceeding 0.1 K and 0.1 g kg−1, respectively. Raman lidar measurements are compared with measurements from additional instruments, such as radiosondings and satellite sensors (IASI and AIRS), and with model re-analyses data (ECMWF and ECMWF-ERA). Comparisons in this paper cover the altitude interval up to 15 km for water vapour mixing ratio and up to 50 km for the temperature. Comparisons between BASIL and the different sensor/model data in terms of water vapour mixing ratio indicate a mean absolute/relative bias of -0.024 g kg−1(or -3.9 %), 0.342 g kg−1(or 36.8 %), 0.346 g kg−1 (or 37.5 %), -0.297 g kg−1 (or -25 %), -0.381 g kg−1 (or -31 %), when compared with radisondings, AIRS, IASI, ECMWF, ECMWF-ERA, respectively. For what concerns the comparisons in terms of temperature measurements, these indicate a mean absolute bias between BASIL and the radisondings, AIRS, IASI, ECMWF, ECMWF-ERA of -0.04, 1.99, 0.48, 0.14, 0.62 K, respectively. Based on the available dataset and benefiting from the circumstance that the Raman lidar BASIL could be compared with all other sensor/model data, it has been possible to estimate the absolute bias of all sensors/datasets, this being 0.004 g kg−1/0.30 K, 0.021 g kg−1/-0.34 K, -0.35 g kg−1/0.18 K, -0.346 g kg−1/-1.63 K, 0.293 g kg−1/-0.16 K and 0.377 g kg−1/0.32 K in terms of water vapour mixing ratio/temperature for BASIL, the radisondings, IASI, AIRS, ECMWF, ECMWF-ERA, respectively.


2017 ◽  
Vol 17 (1) ◽  
pp. 745-767 ◽  
Author(s):  
Paolo Di Girolamo ◽  
Marco Cacciani ◽  
Donato Summa ◽  
Andrea Scoccione ◽  
Benedetto De Rosa ◽  
...  

Abstract. Measurements carried out by the University of Basilicata Raman lidar system (BASIL) are reported to demonstrate the capability of this instrument to characterise turbulent processes within the convective boundary layer (CBL). In order to resolve the vertical profiles of turbulent variables, high-resolution water vapour and temperature measurements, with a temporal resolution of 10 s and vertical resolutions of 90 and 30 m, respectively, are considered. Measurements of higher-order moments of the turbulent fluctuations of water vapour mixing ratio and temperature are obtained based on the application of autocovariance analyses to the water vapour mixing ratio and temperature time series. The algorithms are applied to a case study (11:30–13:30 UTC, 20 April 2013) from the High Definition Clouds and Precipitation for Climate Prediction (HD(CP)2) Observational Prototype Experiment (HOPE), held in western Germany in the spring 2013. A new correction scheme for the removal of the elastic signal crosstalk into the low quantum number rotational Raman signal is applied. The noise errors are small enough to derive up to fourth-order moments for both water vapour mixing ratio and temperature fluctuations.To the best of our knowledge, BASIL is the first Raman lidar with a demonstrated capability to simultaneously retrieve daytime profiles of water vapour turbulent fluctuations up to the fourth order throughout the atmospheric CBL. This is combined with the capability of measuring daytime profiles of temperature fluctuations up to the fourth order. These measurements, in combination with measurements from other lidar and in situ systems, are important for verifying and possibly improving turbulence and convection parameterisation in weather and climate models at different scales down to the grey zone (grid increment  ∼  1 km; Wulfmeyer et al., 2016).For the considered case study, which represents a well-mixed and quasi-stationary CBL, the mean boundary layer height is found to be 1290 ± 75 m above ground level (a.g.l.). Values of the integral scale for water vapour and temperature fluctuations at the top of the CBL are in the range of 70–125 and 75–225 s, respectively; these values are much larger than the temporal resolution of the measurements (10 s), which testifies that the temporal resolution considered for the measurements is sufficiently high to resolve turbulent processes down to the inertial subrange and, consequently, to resolve the major part of the turbulent fluctuations. Peak values of all moments are found in the interfacial layer in the proximity of the top of the CBL. Specifically, water vapour and temperature second-order moments (variance) have maximum values of 0.29 g2 kg−2 and 0.26 K2; water vapour and temperature third-order moments have peak values of 0.156 g3 kg−3 and −0.067 K3, while water vapour and temperature fourth-order moments have maximum values of 0.28 g4 kg−4 and 0.24 K4. Water vapour and temperature kurtosis have values of  ∼  3 in the upper portion of the CBL, which indicate normally distributed humidity and temperature fluctuations. Reported values of the higher-order moments are in good agreement with previous measurements at different locations, thus providing confidence in the possibility of using these measurements for turbulence parameterisation in weather and climate models.In the determination of the temperature profiles, particular care was dedicated to minimise potential effects associated with elastic signal crosstalk on the rotational Raman signals. For this purpose, a specific algorithm was defined and tested to identify and remove the elastic signal crosstalk and to assess the residual systematic uncertainty affecting temperature measurements after correction. The application of this approach confirms that, for the present Raman lidar system, the crosstalk factor remains constant with time; consequently an appropriate assessment of its constant value allows for a complete removal of the leaking elastic signal from the rotational Raman lidar signals at any time (with a residual error on temperature measurements after correction not exceeding 0.18 K).


Waterlines ◽  
1993 ◽  
Vol 12 (2) ◽  
pp. 20-22 ◽  
Author(s):  
Roland Wahlgren

2014 ◽  
Vol 7 (5) ◽  
pp. 1201-1211 ◽  
Author(s):  
F. Navas-Guzmán ◽  
J. Fernández-Gálvez ◽  
M. J. Granados-Muñoz ◽  
J. L. Guerrero-Rascado ◽  
J. A. Bravo-Aranda ◽  
...  

Abstract. In this paper, we outline an iterative method to calibrate the water vapour mixing ratio profiles retrieved from Raman lidar measurements. Simultaneous and co-located radiosonde data are used for this purpose and the calibration results obtained during a radiosonde campaign in summer and autumn 2011 are presented. The water vapour profiles measured during night-time by the Raman lidar and radiosondes are compared and the differences between the methodologies are discussed. Then, a new approach to obtain relative humidity profiles by combination of simultaneous profiles of temperature (retrieved from a microwave radiometer) and water vapour mixing ratio (from a Raman lidar) is addressed. In the last part of this work, a statistical analysis of water vapour mixing ratio and relative humidity profiles obtained during 1 year of simultaneous measurements is presented.


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