To study why, where, and when deep convection

The performance of the boundary determination of fog and low stratiform cloud layers with data from a frequency-modulated continuous-wave (FMCW) cloud radar and a Vaisala ceilometer is assessed. During wintertime stable episodes, fog and low stratiform cloud layers often occur in the Swiss Plateau, where the aerological station of Payerne, Switzerland, is located. During the international COST 720 Temperature, Humidity, and Cloud (TUC) profiling experiment in winter 2003/04, both a cloud radar and a ceilometer were operated in parallel, among other profiling instruments. Human eye observations (“synops”) and temperature and humidity profiles from radiosoundings were used as reference for the validation. In addition, two case studies were chosen to demonstrate the possibilities and limitations of such ground-based remote sensing systems in determining low clouds. In these case studies the cloud boundaries determined by ceilometer and cloud radar were furthermore compared with wind profiler signal-to-noise ratio time series. Under dry conditions, cloud-base and -top detection was possible in 59% and 69% of the cases for low stratus clouds and fog situations, respectively. When cases with any form of precipitation were included, performances were reduced with detection rates of 41% and 63%, respectively. The combination of ceilometer and cloud radar has the potential for providing the base and top of a cloud layer with optimal efficiency in the continuous operational mode. The cloud-top height determination by the cloud radar was compared with cloud-top heights detected using radiosounding humidity profiles. The average height difference between the radiosounding and cloud radar determination of the cloud upper boundary is 53 ± 32 m.

Abstract.Optimal estimation retrieval is a form of nonlinear regression which determines the most probable circumstances that produced a given observation, weighted against any prior knowledge of the system. This paper applies the technique to the estimation of aerosol backscatter and extinction (or lidar ratio) from two-channel Raman lidar observations. It produces results from simulated and real data consistent with existing Raman lidar analyses and additionally returns a more rigorous estimate of its uncertainties while automatically selecting an appropriate resolution without the imposition of artificial constraints. Backscatter is retrieved at the instrument's native resolution with an uncertainty between 2 and 20 %. Extinction is less well constrained, retrieved at a resolution of 0.1-1 km depending on the quality of the data. The uncertainty in extinction is > 15 %, in part due to the consideration of short 1 min integrations, but is comparable to fair estimates of the error when using the standard Raman lidar technique.The retrieval is then applied to several hours of observation on 19 April 2010 of ash from the Eyjafjallajökull eruption. A depolarising ash layer is found with a lidar ratio of 20-30 sr, much lower values than observed by previous studies. This potentially indicates a growth of the particles after 12-24 h within the planetary boundary layer. A lower concentration of ash within a residual layer exhibited a backscatter of 10 Mm −1 sr −1 and lidar ratio of 40 sr.

The international COST 720 Temperature, hUmidity, and Cloud (TUC) profiling experiment was organized over three months in winter 2003/2004 at Payerne, Switzerland. Various in-situ and active/passive groundbased remote sensing systems, including three microwave radiometers, a cloud radar and a wind profiler, were operated at the same location. The experiment has delivered a dataset for ground-based remote sensing measurements of winter conditions in the lower troposphere, including fog formation, development and erosion in the boundary layer. The data are being used to test atmospheric profiling products derived from integration of the various measurements. One example is fog/low cloud top and base derived from 78 GHz frequency-modulated continuous wave (FMCW) cloud radar and laser ceilometer measurements. The paper first describes the TUC experiment and the systems involved, including a brief analysis of the radiosoundings quality. An example is then used to show the ability of ground-based remote sensing systems to automatically determine the stratus base and top. Finally an overview of the publications related to the experiment is presented. Zusammenfassung Das internationale COST 720 Temperature, hUmidity and Cloud (TUC) profiling Experiment wurde während drei Monaten im Winter 2003/2004 in Payerne, Schweiz, durchgeführt. Verschiedene in-situ-und bodengestützte aktive/passive Fernerkundungssysteme, darunter drei Mikrowellenradiometer, ein Wolkenradar und ein Windprofiler, wurden am gleichen Ort betrieben. Das Experiment lieferte einen Datensatz für bodengestützte Fernerkundungsmessungen von Winterbedingungen in der unteren Troposphäre, welche die Bildung, die Entwicklung und die Auflösung von Nebel in der Grenzschicht umfassen. Die Daten werden gebraucht, um atmosphärische Profilmessungen, welche aus der Kombination von verschiedenen Messsystemen hergeleitet werden, zu testen. Ein Beispiel ist die Bestimmung der Ober-und Untergrenze von Nebel oder tiefliegenden Wolken anhand von 78 GHz FMCW Wolkenradar und Laser Ceilometer Messungen. Der Artikel beschreibt zunächst das TUC Experiment und die darin verwendeten Messsysteme, sowie eine kurze Betrachtung zur Qualität der Radiosondierungen. Anhand eines Beispiels wird dann die Möglichkeit gezeigt, mit bodengestützten Fernerkundungssystemen die Nebelober-und-untergrenze automatisch zu bestimmen. Schließlich folgt eine Übersicht der auf das Experiment bezogenen Publikationen.

The overlap function of a Raman channel for a lidar system is retrieved by nonlinear regression using an analytic description of the optical system and a simple model for the extinction profile, constrained by aerosol optical thickness. Considering simulated data, the scheme is successful even where the aerosol profile deviates significantly from the simple model assumed. Application to real data is found to reduce by a factor of 1.4-2.0 the root-mean-square difference between the attenuated backscatter coefficient as measured by the calibrated instrument and a commercial instrument.