Quality assessment of water cycle parameters in REMO by radar-lidar synergy

Hennemuth, Barbara; Weiss, Alexandra; Bösenberg, Jens; Jacob, Daniela; Linné, Holger; Peters, Gerhard; Pfeifer, Susanne

doi:10.5194/acp-8-287-2008

Cited by 9 publications

(8 citation statements)

References 46 publications

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“…(vii) As the precipitation intensity is not measured the same way or using exactly the same sampling volume, the intensities are slightly different in the case of the disdrometer and the rain gauge and more different between these two and the MRR. These differences have also been observed by other authors [10,44].…”

Section: Comparative Study Of the Rain Measurementssupporting

confidence: 89%

Vertical Raindrop Size Distribution in Central Spain: A Case Study

Fraile

Castro

González-Colino

et al. 2015

Advances in Meteorology

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A precipitation event that took place on 12 October 2008 in Madrid, Spain, is analyzed in detail. Three different devices were used to characterize the precipitation: a disdrometer, a rain gauge, and a Micro Rain Radar (MRR). These instruments determine precipitation intensity indirectly, based on measuring different parameters in different sampling points in the atmosphere. A comparative study was carried out based on the data provided by each of these devices, revealing that the disdrometer and the rain gauge measure similar precipitation intensity values, whereas the MRR measures different rain fall volumes. The distributions of drop sizes show that the mean diameter of the particles varied considerably depending on the altitude considered. The level at which saturation occurs in the atmosphere is decisive in the distribution of drop sizes between 2,700 m and 3,000 m. As time passes, the maximum precipitation intensities are registered at a lower height and are less intense. The maximum precipitation intensities occurred at altitudes above 1,000 m, while the maximum fall speeds are typically found at altitudes below 700 m.

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Section: Comparative Study Of the Rain Measurementssupporting

confidence: 89%

Vertical Raindrop Size Distribution in Central Spain: A Case Study

Fraile

Castro

González-Colino

et al. 2015

Advances in Meteorology

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“…An accurate absolute calibration is further motivated by recent studies (Protat et al, 2009;Hennemuth et al, 2008;Maahn and Kollias, 2012;Ewald et al, 2015;Lonitz et al, 2015;Myagkov et al, 2016;Acquistapace et al, 2017), which used the radar reflectivity provided by almost identical ground-based versions of the same instrument. The installation of the MIRA instrument on many ground-based cloud profiling sites within ACTRIS (Aerosols, Clouds and Trace gases Research InfraStructure Network; http://www.…”

Section: Accuracy Considerationsmentioning

confidence: 99%

“…Driven by this challenge, many studies have been conducted to characterize the characteristic reflectivity of the ocean surface using microwave scatterometer-radiometer systems in the X and Ka bands (Valenzuela, 1978;Masuko et al, 1986). As one of the first, Caylor (1994) introduced the ocean surface backscatter technique to cross-check the internal calibration of the NASA ER-2 Doppler radar (EDOP; Heymsfield et al, 1996). In an important next step, L. combined this technique with analytical models of the ocean surface backscatter.…”

Section: Introductionmentioning

confidence: 99%

Calibration of a 35 GHz airborne cloud radar: lessons learned and intercomparisons with 94 GHz cloud radars

et al. 2019

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Abstract. This study gives a summary of lessons learned during the absolute calibration of the airborne, high-power Ka-band cloud radar HAMP MIRA on board the German research aircraft HALO. The first part covers the internal calibration of the instrument where individual instrument components are characterized in the laboratory. In the second part, the internal calibration is validated with external reference sources like the ocean surface backscatter and different air- and spaceborne cloud radar instruments. A key component of this work was the characterization of the spectral response and the transfer function of the receiver. In a wide dynamic range of 70 dB, the receiver response turned out to be very linear (residual 0.05 dB). Using different attenuator settings, it covers a wide input range from −105 to −5 dBm. This characterization gave valuable new insights into the receiver sensitivity and additional attenuations which led to a major improvement of the absolute calibration. The comparison of the measured and the previously estimated total receiver noise power (−95.3 vs. −98.2 dBm) revealed an underestimation of 2.9 dB. This underestimation could be traced back to a larger receiver noise bandwidth of 7.5 MHz (instead of 5 MHz) and a slightly higher noise figure (1.1 dB). Measurements confirmed the previously assumed antenna gain (50.0 dBi) with no obvious asymmetries or increased side lobes. The calibration used for previous campaigns, however, did not account for a 1.5 dB two-way attenuation by additional waveguides in the airplane installation. Laboratory measurements also revealed a 2 dB higher two-way attenuation by the belly pod caused by small deviations during manufacturing. In total, effective reflectivities measured during previous campaigns had to be corrected by +7.6 dB. To validate this internal calibration, the well-defined ocean surface backscatter was used as a calibration reference. With the new absolute calibration, the ocean surface backscatter measured by HAMP MIRA agrees very well (<1 dB) with modeled values and values measured by the GPM satellite. As a further cross-check, flight experiments over Europe and the tropical North Atlantic were conducted. To that end, a joint flight of HALO and the French Falcon 20 aircraft, which was equipped with the RASTA cloud radar at 94 GHz and an underflight of the spaceborne CloudSat at 94 GHz were performed. The intercomparison revealed lower reflectivities (−1.4 dB) for RASTA but slightly higher reflectivities (+1.0 dB) for CloudSat. With effective reflectivities between RASTA and CloudSat and the good agreement with GPM, the accuracy of the absolute calibration is estimated to be around 1 dB.

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“…Such an approach has been used by many authors in order to evaluate first‐order moments such as the grid box mean of variables like cloud cover, liquid water path, and liquid water content [e.g., Mace et al , ; Hinkelman et al , ; Hogan et al , ; van Meijgaard and Crewell , ; Bouniol et al , ; Morcrette et al , ]. It is not clear, however, whether the same approach can be used to evaluate higher‐order moments such as variance and skewness of the moisture distribution since only few studies have been done on the applicability of the methods, and they indeed focus on the comparability of spaceborne or quasi‐instantaneous 2‐D line measurements with 3‐D quantities [e.g., Astin et al , ; Uttal and Kropfli , ; Hennemuth et al , ].…”

Section: Introductionmentioning

confidence: 99%

Evaluating statistical cloud schemes: What can we gain from ground‐based remote sensing?

et al. 2013

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[1] Statistical cloud schemes with prognostic probability distribution functions have become more important in atmospheric modeling, especially since they are in principle scale adaptive and capture cloud physics in more detail. While in theory the schemes have a great potential, their accuracy is still questionable. High-resolution three-dimensional observational data of water vapor and cloud water, which could be used for testing them, are missing. We explore the potential of ground-based remote sensing such as lidar, microwave, and radar to evaluate prognostic distribution moments using the "perfect model approach." This means that we employ a high-resolution weather model as virtual reality and retrieve full three-dimensional atmospheric quantities and virtual ground-based observations. We then use statistics from the virtual observation to validate the modeled 3-D statistics. Since the data are entirely consistent, any discrepancy occurring is due to the method. Focusing on total water mixing ratio, we find that the mean ratio can be evaluated decently but that it strongly depends on the meteorological conditions as to whether the variance and skewness are reliable. Using some simple schematic description of different synoptic conditions, we show how statistics obtained from point or line measurements can be poor at representing the full three-dimensional distribution of water in the atmosphere. We argue that a careful analysis of measurement data and detailed knowledge of the meteorological situation is necessary to judge whether we can use the data for an evaluation of higher moments of the humidity distribution used by a statistical cloud scheme.Citation: Grützun, V., J. Quaas, C. J. Morcrette, and F. Ament (2013), Evaluating statistical cloud schemes: What can we gain from ground-based remote sensing?,

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Quality assessment of water cycle parameters in REMO by radar-lidar synergy

Cited by 9 publications

References 46 publications

Vertical Raindrop Size Distribution in Central Spain: A Case Study

Vertical Raindrop Size Distribution in Central Spain: A Case Study

Calibration of a 35 GHz airborne cloud radar: lessons learned and intercomparisons with 94 GHz cloud radars

Evaluating statistical cloud schemes: What can we gain from ground‐based remote sensing?

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