Giovanni Martucci

Detection of Cloud-Base Height Using Jenoptik CHM15K and Vaisala CL31 Ceilometers

Abstract Twelve case studies of multilayer cloud-base height (CBH) retrievals from two collocated ceilometers (Vaisala CL31 and Jenoptik CHM15K) have been analyzed. The studies were performed during the period from September to December 2008 at the Mace Head Atmospheric Research Station in Ireland. During the period of measurement, the two instruments provided vertical profiles of backscattered laser signal as well as the manufacturer’s operational cloud-base product. The cases selected covered a diverse range of cloud-cover conditions, ranging from single to multiple cloud layers and from cloud-base heights varying from only a few hundreds meters per day up to 3–5 km in a few hours. The results show significant offsets between the two manufacturer-derived CBHs along with a considerable degree of scatter. Using a newly developed temporal height-tracking (THT) algorithm applied to both ceilometers, significant improvement in the correlation between CBH derived from both instruments results in a correlation...

Comparison between Backscatter Lidar and Radiosonde Measurements of the Diurnal and Nocturnal Stratification in the Lower Troposphere

A collection of boundary layer heights has been derived from measurements performed by a groundbased backscatter lidar in Neuchâtel, Switzerland (47.000°N, 6.967°E, 485 m ASL). A dataset of 98 cases have been collected during 2 yr. From these data, 61 are noon and 37 are midnight cases. The following two different schemes were used to retrieve the mixed layer depth and the height of the residual layer from the measurements: the gradient and variance methods. The obtained values were compared with those derived from the potential temperature profiles as computed from radiosonde data. For nocturnal cases, the height of the first aerosol layer above the residual layer was also compared to the corresponding potential temperature value. Correlation coefficients between lidar and radiosonde in both convective and stable conditions are between 0.88 and 0.97.

An Assessment of Pseudo-Operational Ground-Based Light Detection and Ranging Sensors to Determine the Boundary-Layer Structure in the Coastal Atmosphere

Twenty-one cases of boundary-layer structure were retrieved by three co-located remote sensors, One LIDAR and two ceilometers at the coastal site of Mace Head, Ireland. Data were collected during the ICOS field campaign held at the GAW Atmospheric Station of Mace Head, Ireland, from 8th to 28th of June, 2009. The study is a two-step investigation of the BL structure based on (i) the intercomparison of the backscatter profiles from the three laser sensors, namely the Leosphere ALS300 LIDAR, the Vaisala CL31 ceilometer and the Jenoptik CHM15K ceilometer; (ii) and the comparison of the backscatter profiles with twenty-three radiosoundings performed during the period from the 8th to the 15th of June, 2009. The sensor-independent Temporal Height-Tracking algorithm was applied to the backscatter profiles as retrieved by each instrument to determine the decoupled structure of the BL over Mace Head. The LIDAR and ceilometers-retrieved BL heights were compared to the radiosoundings temperature profiles. The comparison between the remote and the in-situ data proved the existence of the inherent link between temperature and aerosol backscatter profiles and opened at future studies focusing on the further assessment of LIDAR-ceilometer comparison.

Comparison of lidar methods to determine the aerosol mixed layer top

Backscatter lidar measurements were performed in the atmospheric boundary layer and the troposphere above Neuchatel, Switzerland (47.00°N, 6.95°S, 485m asl). The backscatter lidar is based on Nd:YAG laser. The lidar measurements are done in the period from June 2000 till February 2002 as part of the EU project EARLINET (http://lidarb.dkrz.de/earlinet/). From the lidar measurements, we determine the following values vertical profile of the aerosol backscatter coefficients, the gradient of the range-corrected lidar signal and the variance of the range-corrected lidar signal. These values are used to determine the aerosol mixed layer (AML) height in the atmospheric boundary layer (ABL). In this work, we present a comparison of these different lidar methods to determine the AML height. The lidar-obtained values are also compared with the values for ABL top, as determined from upper air weather parameters. This comparison is performed and presented for various seasons and time in the diurnal cycle.

Backscatter Lidar Measurement in the Atmospheric Boundary Layer: Data Analysis and Interpretation Capabilities

In this presentation we summarize analysis approaches of the backscatter lidar signal, providing the following parameters in the Atmospheric Boundary Layer (ABL): the aerosol backscatter coefficient and the mixing layer height. These ABL parameters are important in the atmospheric studies and air quality control. The application of the discussed approaches will be illustrated by examples of backscatter lidar measurements above Neuchatel, Switzerland (47.0degN; 6.95degE, 485 m asl), one of the stations in EARLINET.

Lidar determination of the frequency of variations of the boundary-layer top

The frequency of thermals up- and downdraft, during the day, and that of gravity waves, during night, are retrieved by applying a fast Fourier transform to the temporal evolution of the boundary-layer height as obtained by lidar measurements. The principal components of each obtained spectrum of frequency are related to the dominant processes occurring at the convective and nocturnal boundary-layer tops. The formation of lee-waves systems during special meteorological conditions determined the oscillation of the boundary-layer height. Fluctuations at the nocturnal boundary-layer height can occur even if the conditions through the layer depth are statically stable. These oscillations are principally due to wind shear and buoyancy (gravity) waves at the altitude of the nocturnal boundary-layer top.

Automated backscatter lidar for PBL and troposphere measurements: experience from one-year operation

We report a summary of the experience and results from one-year unattended operation of an automatic backscatter lidar. The backscatter lidar is realized for measurements at altitudes of Planetary Boundary Layer (PBL) and the troposphere. Such lidar has been developed and tested to answer the necessity for operation at remote sites an/or during atmospheric measurement campaigns. The results are from one year of urban boundary layer height measurements in the city of Basel (Switzerland). During this one-year of operation the lidar was remotely controlled via Internet, including also the data transfer. Here we present examples of lidar measurements of diurnal cycles of the urban boundary layer development and its height. We also present cases of lidar measurements performed in clear and cloudy sky, where the lidar observations are compared with the visual control of the sky documented by automatic camera. The results and the experience are discussed in view of the application of such automatic lidar for long-term operation as part of aerosol lidar network.

Lidar determination of mixing layer height with high resolution

Ecological monitoring and analysis of the planetary boundary layer (PBL) dynamics require determination of the mixing layer height (MLH) on a continuous basis. In a number of cases it is necessary to determine the MLH with sufficiently high resolution - both altitude and temporal. The backscatter lidar provides a convenient tool for such determination, using the aerosol as tracer and determining its vertical profile and its time-evolution, with the capability for continuous measurements. Although methods already exist, based on the altitude derivative of the backscatter lidar signal (altitude Gradient method) and its time-variance (Variance method), the application of these methods with high resolution is limited by the background noise presence. We report here a further development of backscatter lidar gradient and variance methods for MLH determination, allowing higher resolutions. In it, the MLH determination from the gradient and the variance of the lidar signal is supported by a convenient filter technique. Time scale of increased temporal resolution allows the investigation of the fine atmospheric dynamic structures like convective motion. A number of examples in MLH retrieval are presented. The examples are based on backscatter lidar measurements performed in the PBL above Neuchatel, Switzerland (47.00°N, 6.95°S, 485m asl). The examples show the applicability and the usefulness of the reported technique in measurements of the daily cycle of the MLH dynamics.

Raman lidar in operational meteorology

Water vapor and temperature spatial distribution and their temporal evolution are among the most important parameters in numerical weather forecasting and climate models. The operational relative humidity/temperature profiling in meteorology is carried out mostly by radio sondes. Sondes provide profiles with high vertical resolution but suffer from systematic errors and low temporal resolution. The temporal resolution is also a limitation for the now-casting, which has become more and more important for meteorological alerts and for the aviation. Recently, some of national meteorological services have introduced Raman lidars for additional operational humidity/temperature profiling. The lidars allow monitoring of water vapor mixing ratio and temperature with high vertical and temporal resolutions. Here the design and measurement results from the Raman Lidar for Meteorological Observation (RALMO) developed by the Ecole Polytechnique Féderal de Lausanne (EPFL) and operated by MeteoSwiss is presented as an illustration of the potential of Raman lidars in operational meteorology. The first applications of lidar data in numerical weather forecasting is also discussed.

Correction of CCI cloud data over the Swiss Alps using ground-based radiation measurements

The validation of long term cloud datasets retrieved from satellites is challenging due to their worldwide coverage going back as far as the 1980s, among others. A trustworthy reference cannot be found easily at every location and every time. Mountainous regions represent especially a :::::: present :: a :::::::: particular problem since ground-based measurements are sparser ::::: sparse. Moreover, as retrievals from passive satellite radiometers are difficult in winter due to the presence of snow on the ground, it is particularly important to develop new ways to evaluate and to correct satellite datasets over elevated areas. 5 In winter for ground levels above 1000m (a.s.l.) in Switzerland, the cloud occurrence of the newly-released cloud property datasets of the ESA Climate Change Initiative Cloud_cci project (AVHRR-PM and MODIS-Aqua series) is 132 % to 217 % that of SYNOP observations, corresponding to between 24 % and 54 % of false cloud detections. Furthermore, the overestimations increase with the altitude of the sites and are associated with particular retrieved cloud properties. In this study, a novel post-processing approach is proposed to reduce the amount of false cloud detections in the satellite 10 datasets. A combination of ground-based downwelling longwave and shortwave radiation and temperature measurements is used to obtain a mask for :::::: provide ::::::::::: independent ::::::::: validation :: of : the cloud cover above :::: over 41 locations in Switzerland. An agreement of 85 % is obtained when the cloud cover is compared to surface synoptic observations (90 % within ± 1 okta difference). The obtained cloud mask has been :::::::: validation :::: data :: is :::: then co-located with the satellite observations and a decision tree ::::: model is trained to automatically detect the overestimations in the satellite ’s cloud masks. Cross-validated results show 15 that 62± 13 % of these overestimations can be identified by the model, reducing the systematic error in the satellite datasets :::: from :::::::::: 14.4± 15.5 :: % : to 4.3± 2.8 %, : . ::: The ::::::: amount :: of ::::: errors :: is :::::: lower, ::: and ::::::::::: importantly, :::: their ::::::::: distribution :: is ::::: more :::::::::::: homogeneous :: as :::: well. :::::: These ::::::::: corrections ::::::: happen : at the cost of an : a ::::: global : increase of 7± 2 % of missed clouds. Using this model, it is hence possible to significantly improve the cloud detection reliability in elevated areas in the Cloud_cci’s AVHRR-PM and MODIS-Aqua products. 20