Inversion of the Scattering Coefficient of Polar Mesospheric Clouds by Using One-Dimensional Maximum Probability Method

2017 ◽  
Vol 54 (12) ◽  
pp. 120101
Author(s):  
郜海阳 Gao Haiyang ◽  
卜令兵 Bu Lingbing ◽  
王震 Wang Zhen ◽  
朱红 Zhu Hong
2019 ◽  
Vol 19 (19) ◽  
pp. 12455-12475 ◽  
Author(s):  
Lina Broman ◽  
Susanne Benze ◽  
Jörg Gumbel ◽  
Ole Martin Christensen ◽  
Cora E. Randall

Abstract. Two important approaches for satellite studies of polar mesospheric clouds (PMCs) are nadir measurements adapting phase function analysis and limb measurements adapting spectroscopic analysis. Combining both approaches enables new studies of cloud structures and microphysical processes but is complicated by differences in scattering conditions, observation geometry and sensitivity. In this study, we compare common volume PMC observations from the nadir-viewing Cloud Imaging and Particle Size (CIPS) instrument on the Aeronomy of Ice in the Mesosphere (AIM) satellite and a special set of tomographic limb observations from the Optical Spectrograph and InfraRed Imager System (OSIRIS) on the Odin satellite performed over 18 d for the years 2010 and 2011 and the latitude range 78 to 80∘ N. While CIPS provides preeminent horizontal resolution, the OSIRIS tomographic analysis provides combined horizontal and vertical PMC information. This first direct comparison is an important step towards co-analysing CIPS and OSIRIS data, aiming at unprecedented insights into horizontal and vertical cloud processes. Important scientific questions on how the PMC life cycle is affected by changes in humidity and temperature due to atmospheric gravity waves, planetary waves and tides can be addressed by combining PMC observations in multiple dimensions. Two- and three-dimensional cloud structures simultaneously observed by CIPS and tomographic OSIRIS provide a useful tool for studies of cloud growth and sublimation. Moreover, the combined CIPS/tomographic OSIRIS dataset can be used for studies of even more fundamental character, such as the question of the assumption of the PMC particle size distribution. We perform the first thorough error characterization of OSIRIS tomographic cloud brightness and cloud ice water content (IWC). We establish a consistent method for comparing cloud properties from limb tomography and nadir observations, accounting for differences in scattering conditions, resolution and sensitivity. Based on an extensive common volume and a temporal coincidence criterion of only 5 min, our method enables a detailed comparison of PMC regions of varying brightness and IWC. However, since the dataset is limited to 18 d of observations this study does not include a comparison of cloud frequency. The cloud properties of the OSIRIS tomographic dataset are vertically resolved, while the cloud properties of the CIPS dataset is vertically integrated. To make these different quantities comparable, the OSIRIS tomographic cloud properties cloud scattering coefficient and ice mass density (IMD) have been integrated over the vertical extent of the cloud to form cloud albedo and IWC of the same quantity as CIPS cloud products. We find that the OSIRIS albedo (obtained from the vertical integration of the primary OSIRIS tomography product, cloud scattering coefficient) shows very good agreement with the primary CIPS product, cloud albedo, with a correlation coefficient of 0.96. However, OSIRIS systematically reports brighter clouds than CIPS and the bias between the instruments (OSIRIS – CIPS) is 3.4×10-6 sr−1 (±2.9×10-6 sr−1) on average. The OSIRIS tomography IWC (obtained from the vertical integration of IMD) agrees well with the CIPS IWC, with a correlation coefficient of 0.91. However, the IWC reported by OSIRIS is lower than CIPS, and we quantify the bias to −22 g km−2 (±14 g km−2) on average.


2012 ◽  
Vol 5 (3) ◽  
pp. 3693-3716 ◽  
Author(s):  
K. Hultgren ◽  
J. Gumbel ◽  
D. A. Degenstein ◽  
A. E. Bourassa ◽  
N. D. Lloyd

Abstract. Limb-scanning satellites can provide global information about the vertical structure of Polar Mesospheric Clouds. However, information about horizontal structures usually remains limited. This is due to both a long line of sight and a long scan duration. On eighteen days during the Northern Hemisphere summers 2010–2011 and the Southern Hemisphere summer 2011/2012, the Swedish-led Odin satellite was operated in a special mesospheric mode with short limb scans limited to the altitude range of Polar Mesospheric Clouds. For Odin's Optical Spectrograph and InfraRed Imager System (OSIRIS) this provides multiple views through a given cloud volume and, thus, a basis for tomographic analysis of the vertical/horizontal cloud structure. Here we present algorithms for tomographic analysis of mesospheric clouds based on maximum probability techniques. We also present results of simulating OSIRIS tomography and retrieved cloud structures from the special tomographic periods.


2021 ◽  
Vol 11 (9) ◽  
pp. 3781
Author(s):  
Takumi Yoshida ◽  
Yasutaka Ueda ◽  
Norimasa Mori ◽  
Yumi Matano

This paper presents a crossed rib diffuser (CRD) as an effective tool for room acoustic control. We performed an experimental investigation of its effectiveness using a specimen manufactured for this trial. The CRD is constructed by overlapping two one-dimensional (1D) periodic rib diffusers with different specifications so that they are crossed at non-right angles. The CRD achieves a higher scattering coefficient than 1D periodic rib diffusers in a wide band while maintaining the simple and friendly design of 1D periodic rib diffusers applicable to various architectural spaces. Moreover, inserting an absorbing layer between upper and lower ribs of the CRD, (CRD-A) yields a high broadband absorption coefficient. We first evaluated the random-incidence scattering coefficient of CRD using a 1/5 scaled model in comparison with those of 1D periodic diffusers assessed with a numerical method. Then, absorption coefficients for the CRD and the CRD-A were measured using a reverberation room. Subsequently, an experiment on a small meeting room with a 1D periodic rib diffuser, the CRD and the CRD-A was conducted to present performance of the CRD in room acoustic control. Impulse response measurements and evaluations of reverberation parameters (T20 and EDT) and speech clarity (D50) were conducted. Additionally, we present differences in structure of reflected sounds found for the flat wall, the CRD and the CRD-A visually using a four-channel sound field microphone.


2001 ◽  
Vol 27 (10) ◽  
pp. 1703-1708 ◽  
Author(s):  
J.F. Carbary ◽  
D. Morrison ◽  
G.J. Romick ◽  
L.J. Paxton ◽  
C.-I. Meng

2018 ◽  
Author(s):  
Uwe Berger ◽  
Gerd Baumgarten ◽  
Jens Fiedler ◽  
Franz-Josef Lübken

Abstract. In this paper we present a new description about statistical probability density distributions (pdfs) of Polar Mesospheric Clouds (PMC) and noctilucent clouds (NLC). The analysis is based on observations of maximum backscatter, ice mass density, ice particle radius, and number density of ice particles measured by the ALOMAR RMR-lidar for all NLC seasons from 2002 to 2016. From this data set we derive a new class of pdfs that describe the statistics of PMC/NLC events which is different from previously statistical methods using the approach of an exponential distribution commonly named g-distribution. The new analysis describes successfully the probability statistic of ALOMAR lidar data. It turns out that the former g-function description is a special case of our new approach. In general the new statistical function can be applied to many kinds of different PMC parameters, e.g. maximum backscatter, integrated backscatter, ice mass density, ice water content, ice particle radius, ice particle number density or albedo measured by satellites. As a main advantage the new method allows to connect different observational PMC distributions of lidar, and satellite data, and also to compare with distributions from ice model studies. In particular, the statistical distributions of different ice parameters can be compared with each other on the basis of a common assessment that facilitate, for example, trend analysis of PMC/NLC.


1986 ◽  
Vol 43 (12) ◽  
pp. 1263-1274 ◽  
Author(s):  
John J. Olivero ◽  
Gary E. Thomas

2012 ◽  
Vol 117 (D19) ◽  
pp. n/a-n/a ◽  
Author(s):  
Michael H. Stevens ◽  
Stefan Lossow ◽  
Jens Fiedler ◽  
Gerd Baumgarten ◽  
Franz-Josef Lübken ◽  
...  

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