Marc Schneebeli

High-Resolution Vertical Profiles of X-Band Polarimetric Radar Observables during Snowfall in the Swiss Alps

AbstractAn X-band polarimetric radar was deployed in the eastern Swiss Alps at an altitude of 2133 m. Radar measurements were complemented with several weather stations deployed in an altitude range from 1500 to 3100 m as well as with a fixed GPS ground station that was used to infer integrated water vapor estimates. Around 8000 vertical profiles of polarimetric radar observables above the melting layer collected during two months are analyzed. First, the behavior of the mean profiles of reflectivity at horizontal polarization Zh, differential reflectivity Zdr, copolar cross correlation ρhv, and specific differential phase shift Kdp are interpreted from a microphysical point of view. It is shown that the whole evolution of snowflakes, from pristine crystals at temperatures around −30°C to dendritic crystals around −15°C, to large aggregates around 0°C, is well captured by the polarimetric radar variables. In a second step, the profiles are analyzed as functions of high and low water vapor and snow accumul...

ASMUWARA, a ground-based radiometer system for tropospheric monitoring

ASMUWARA, the All-Sky MUlti WAvelength RAdiometer, is a new ground-based and automatically operating radiometer system designed for tropospheric monitoring. ASMUWARA has ten channels in the microwave and infrared range and is able to observe the sky in all directions with an angular resolution of 9°. No radome is used to allow an optimum view quality at all wavelengths. The purpose of ASMUWARA is to retrieve temperature and humidity profiles, maps of integrated water vapour and liquid water, and additional cloud properties. The construction and characteritics of ASMUWARA are described. Special emphasis is put on the calibration loads, the calibration method, and the correction of antenna beamwidth effects.

An Extended Kalman Filter Framework for Polarimetric X-Band Weather Radar Data Processing

AbstractThe different quantities measured by dual-polarization radar systems are closely linked to each other. An extended Kalman filter framework is proposed in order to make use of constraints on individual radar observables that are induced by these relations. This new approach simultaneously estimates the specific differential phase on propagation Kdp, the attenuation-corrected reflectivity at horizontal polarization Zh, and the attenuation-corrected differential reflectivity Zdr, as well as the differential phase shift on backscatter δhυ. In a simulation experiment it is found that Kdp and δhυ can be retrieved with higher accuracy and spatial resolution than existing estimators that solely rely on a smoothed measurement of the differential phase shift Ψdp. Attenuation-corrected Zh was retrieved with an accuracy similar to standard algorithms, but improvements were found for attenuation-corrected Zdr. In addition, the algorithm can be used for radar calibration by comparing the directly retrieved diff...

Tropospheric water and temperature retrieval for ASMUWARA

The retrieval of tropospheric water and temperature with the ground-based and automatically operating radiometer system ASMUWARA (All-Sky MUlti WAvelength RAdiometer) is described. This instrument operates simultaneously at microwave and IR channels. Integrated water vapour (IWV) and integrated liquid water (ILW) are retrieved with a newly developed linear algorithm to an accuracy of 0.014 kgm -2 (ILW) and 0.41 kgm -2 (IWV), thanks to the inclusion of a channel at 151 GHz. These measurements are made for the whole hemisphere and therefore provide information about the spatial distribution of water in the troposphere. With an optimal estimation algorithm, tropospheric temperature and humidity profiles are retrieved. The results are quasi bias free with a mean error of less than 2.5 K for the temperature (less than 1 K in the lowest km above ground), and less than 1 gm -3 for the humidity. Examples of all measurements are shown.

A Calibration Scheme for Microwave Radiometers Using Tipping Curves and Kalman Filtering

Calibration of microwave radiometers is a critical task and remains a key issue for the accuracy of brightness-temperature measurements. The tipping-curve calibration method is a well-established technique for ground-based microwave radiometers measuring at frequencies where the opacity of the atmosphere is low. This method relies on the known relationship between the tipping angles of the radiometer and the atmospheric opacity at those angles. Atmospheric inhomogeneities slightly disturb this relationship and therefore lead to calibration errors. The calibration scheme presented in this paper uses the determined tipping-calibration accuracy and incorporates the statistical behavior of radiometer gain and system-temperature variations in a Kalman filter framework. In this paper, a calibration simulation is set up to test the capability of the proposed scheme by reconstructing simulated brightness temperatures first. Moreover, the technique is applied to experimental data. The calibration quality is evaluated with the detrended-fluctuation-analysis method. Model and experimental results show that the calibration accuracy can be increased by a factor of two or even higher. Finally, we apply the calibration technique to a microwave radiometer with internal calibration, resulting in a reduction of the calibration noise.

Improved Estimation of the Specific Differential Phase Shift Using a Compilation of Kalman Filter Ensembles

A new algorithm for the accurate estimation of the specific differential phase shift on propagation (Kdp) from noisy total differential phase shift (Ψdp) measurements is presented for data acquired with a polarimetric weather radar. The new approach, which is based on the compilation of ensembles of Kalman filter estimates, does not rely on additional data like the reflectivity or the differential reflectivity in order to constrain the solution, and it is based on Ψdp only. The dependence of the solution on Ψdp only allows one to apply the algorithm in various environmental conditions without reducing its performance. Drawbacks that are usually inherent in algorithms of this kind (like the loss of the small-scale structure and the smoothing of high peak values) are partially overcome by a two-step algorithm design, which first determines an ensemble of possible solutions and then selects and averages the ensemble members such that the estimated Kdp profile has a better agreement with the truth. The algorithm is thoroughly evaluated and compared with a commonly used algorithm on stochastically simulated profiles of raindrop size distribution. It is found that the accuracy of the Kdp values estimated with the new algorithm significantly increases. The algorithm is also experimentally evaluated by applying it on X-band radar data that were acquired in northern Brazil during the CHUVA campaign and at a high alpine site in Switzerland during snowfall. Results show that the spatial fine structure and the high values of precipitation are better represented with the new method.

Detection of Cirrus Clouds Using Infrared Radiometry

The detection of low-level clouds from ground-based infrared (IR) radiometry is usually based on the IR brightness temperature (IRBT) contrast between the warm clouds and the cold clear-sky background. This method works as long as the brightness temperature contrast subsists. It is not the case for cirrus clouds, which are usually optically thin and exhibit a low brightness temperature, comparable to that of clear sky in similar atmospheric conditions. In this paper, we propose a detection scheme to discriminate between clear sky and cirrus sky based on the fluctuations of the IRBT rather than on the absolute IRBT values. For this, we use the detrended fluctuation analysis (DFA) method on IRBT data when no liquid clouds were present. We compute the exponent α for nine IRBT time series covering clear- and cirrus-sky situations. We find that, for the fluctuation range of 1-5 min, α ≃ 0.1 for clear sky, α ≃ 0.5 for stratiform cirrus layers, and α ≃ 1 for broken cirrus layers. We suggest a threshold value of α ≃ 0.25 for the discrimination between clear sky and cirrus sky. We also examine the relationship between DFA and the classical spectral analysis and find that spectral analysis could be an alternative to the DFA method in detecting the presence of cirrus clouds.

Characterization of Low Clouds With Satellite and Ground-Based Remote Sensing Systems

Satellite and ground-based retrievals of a number of (low) cloud characteristics are compared in this paper in order to assess the performance of the techniques and identify potential synergies. Centred on the COST720 International Comparison Campaign for Temperature, hUmidity and Cloud profiling (TUC), four cases with different meteorological situations are analysed in detail. Parameter agreement (for cloud presence, liquid water path, cloud geometrical thickness and cloud top temperature) is good in general. It is shown that satellite retrievals of liquid water path and cloud thickness could be improved using liquid water content derived from ground-based measurements, while ground-based retrievals can profit from the spatial component in satellite data. Taken together, the combination of instruments and techniques presented in this paper allows for a detailed assessment of complex cloudy atmospheres.

Accuracy of Phase-Based Algorithms for the Estimation of the Specific Differential Phase Shift Using Simulated Polarimetric Weather Radar Data

The specific differential phase shift on propagation Kdp is widely employed in the study of precipitation, although little is known about the effective accuracy of its estimates. The aim of this letter is to analyze the quality of Kdp estimates, using realistic simulated fields of drop size distributions. Two classical and one recently proposed estimation algorithms are tested, which are chosen among the algorithms that use the measured and noisy total differential phase shift Ψdp as their main input. A data set of six simulated rain events, from which polarimetric radar variables can be derived, is employed in this letter. The mean normalized absolute error in the estimation of Kdp at the radar resolution volume scale ranges from 27% to 30% for all the algorithms proposed, and significant negative biases up to -50% emerge at the highest values of Kdp for the most biased algorithm. The new algorithm, which is based on Kalman filtering, is able to keep these localized bias values around -25% and outperforms the classical algorithms in terms of efficiency, correlation, and root-mean-square error.

Deriving Winds at Cloud-Base Height With an Infrared Camera

An uncooled commercial infrared camera is used to retrieve horizontal winds at cloud-base height. The camera is equipped with a microbolometer array of 320 times 240 pixels covering a field of view of 32deg times 24deg. It operates in the atmospheric window from 7.5 to 14 mum . In this wavelength range, the camera has day and night measurement capabilities, independent of the illumination conditions. Optically thick clouds appear as blackbody radiators and offer a large brightness temperature contrast with the much colder clear-sky background. We develop a method to follow the infrared structures in the clouds as they pass through the field of view of the camera. Taking a picture every 6 s, the angular velocity of the cloud base is calculated as the ratio of the angular displacement of the cloud structures between two pictures over the elapsed time. To transform the angular velocity into a metric velocity, we use the temperature profile retrieved by a microwave radiometer called All-Sky MUlti-WAvelength Radiometer. The case study of September 10, 2007 is shown. The retrieved wind is of 18.0 plusmn 2.4 m/s at an altitude of 4164 plusmn 546 m above the instrument, blowing from northwest. These results agree well with radiosondings launched in the vicinity of the experiment site.