Accurate Absolute Measurements of Liquid Water Content (LWC) and Ice Water Content (IWC) of Clouds and Precipitation with Spectrometric Water Raman Lidar

A detailed description is given of how the liquid water content (LWC) and the ice water content (IWC) can be determined accurately and absolutely from the measured water Raman spectra of clouds. All instrumental and spectroscopic parameters that affect the accuracy of the water-content measurement are discussed and quantified, specifically, these are the effective absolute differential Raman backscattering cross section of water vapor (π)/dΩ, and the molecular Raman backscattering efficiencies ηliq and ηice of liquid and frozen microparticles, respectively. The latter two are determined following rigorous theoretical approaches combined with RAMSES measurements. For ηice, this includes a new experimental method which assumes continuity of the number of water molecules across the vertical extent of the melting layer. Examples of water-content measurements are presented, including supercooled liquid-water clouds and melting layers. Error sources are discussed, one effect that stands out is interfering fluorescence by aerosols. Aerosol effects and calibration issues are the main reasons why spectral Raman measurements are required for quantitative measurements of LWC and IWC. The presented study lays the foundation for cloud microphysical investigations, and for the evaluation of cloud models or the cloud data products of other instruments. As a first application, IWC retrieval methods are evaluated that are based on either lidar extinction or radar reflectivity measurements. While the lidar-based retrievals show unsatisfactory agreement with the RAMSES IWC measurements, the radar-based IWC retrieval which is used in the Cloudnet project performs reasonably well. On average, retrieved IWC agrees within 20% to 30% (dry bias) with measured IWC.

Multiposition Rotation Interference Absolute Measurement Method for High-Precision Optical Component Surfaces

Modern optical engineering requires increasingly sophisticated interferometry methods capable of conducting subnanometer scale measurements of the large aperture, high-precision optical component surfaces. However, the accuracy of interferometry measurement is limited to the accuracy with which the surface of the reference mirror employed in the interferometer system is known, and the influence of gravity-induced deformation cannot be ignored. This is addressed in the present work by proposing a three-flat testing method based on multiposition rotation interference absolute surface measurement technology that combines the basic theory of N-position rotation with the separability of surface wavefront functions into sums of even and odd functions. These functions provide the rotational symmetric components of the wavefront, which then enables the absolute surface to be reconstructed based on the N-position rotation measurements. In addition, we propose a mechanical clamping combined with computational method to compensate for the gravity-induced deformations of the flats in the multiposition rotation absolute measurements. The high precision of the proposed absolute surface measurement method is demonstrated via simulations. The results of laboratory experiments indicate that the combination compensation method provides the high-precision surface reconstruction outcomes. The present work provides an important contribution for supporting the interferometry measurement of large aperture, high-precision optical component surfaces.

The geomagnetic data of the Clementinum observatory in Prague since 1839

The historical magnetic observatory Clementinum operated in Prague from 1839 to 1926. The data from the yearbooks that recorded the observations at Clementinum have recently been digitized and were subsequently converted, in this work, into the physical units of the International System of Units (SI). Introducing a database of geomagnetic data from this historical source is a part of our paper. Some controversial data are also analysed here. In the original historical sources, we identified an error in using the physical units. It was probably introduced by the observers determining the temperature coefficient of the bifilar apparatus. By recalculating the values ​​in the records, some missing values ​​are added; for instance, the temperature coefficients for the bifilar magnetometer, the baselines, and the annual averages for the horizontal intensity in the first years of observations were redetermined. The values ​​of absolute measurements of the declination in 1852, which could not be found in the original sources, were also estimated. The main contribution of this article rests in critically reviewed information about the magnetic observations in Prague, which is, so far, more complete than any other. The work also contributes to the space weather topic by revealing a record of the now almost forgotten magnetic disturbance of 3 September 1839.

Comparison of structural MRI brain measures between 1.5T and 3T: data from the Lothian Birth Cohort 1936

Multi-scanner MRI studies are reliant on understanding the apparent differences in imaging measures between different scanners. We provide a comprehensive analysis of T1-weighted and diffusion MRI (dMRI) structural brain measures between a 1.5T GE Signa Horizon HDx and a 3T Siemens Magnetom Prisma using 91 community-dwelling older participants (aged 82 years). Although we found considerable differences in absolute measurements (global tissue volumes were measured as ~6-11% higher and fractional anisotropy was 33% higher at 3T than at 1.5T), between-scanner consistency was good to excellent for global volumetric and dMRI measures (intraclass correlation coefficient [ICC] range: 0.612-0.993) and fair to good for 68 cortical regions (FreeSurfer) and cortical surface measures (mean ICC: 0.504-0.763). Between-scanner consistency was fair for dMRI measures of 12 major white matter tracts (mean ICC: 0.475-0.564), and the general factors of these tracts provided excellent consistency (ICC > 0.769). Whole-brain structural networks provided good to excellent consistency for global metrics (ICC > 0.612). Although consistency was poor for individual network connections (mean ICCs: 0.275-0.280), this was driven by a large difference in network sparsity (0.599 versus 0.334), and consistency was improved when comparing only the connections present in every participant (mean ICCs: 0.533-0.647). Regression-based k-fold cross-validation showed that, particularly for global volumes, between-scanner differences could be largely eliminated (R2 range 0.615-0.991). We conclude that low granularity measures of brain structure can be reliably matched between the scanners tested, but caution is warranted when combining high granularity information from different scanners.

Quantum sensors for space-borne earth observation

<p>Atom interferometry enables quantum sensors for absolute measurements of gravity (1) and gravity gradients (2). The combination with classical sensors can be exploited to suppress vibration noise in the interferometer, extend the dynamic range, or to remove the drift from the classical device (3). These features motivate novel sensor and mission concepts for space-borne earth observation e.g. with quantum gradiometers (4) or hybridised atom interferometers (5). We will discuss developments of atom optics and atom interferometry in microgravity in the context of future quantum sensors (6) and outline the perspectives for applications in space (4,5).</p><p>The presented work is supported by by the CRC 1227 DQmat within the projects B07 and B09, the CRC 1464 TerraQ within the projects A01, A02 and A03, by "Niedersächsisches Vorab" through "Förderung von Wissenschaft und Technik in Forschung und Lehre" for the initial funding of research in the new DLR-SI Institute, and through the "Quantum and Nano- Metrology (QUANOMET)" initiative within the project QT3.</p><p>(1) V. Ménoret et al., Scientific Reports 8, 12300, 2018; A. Trimeche et al., Phys. Rev. Appl. 7, 034016, 2017; C. Freier et al., J. of Phys.: Conf. Series 723, 012050, 2016; A. Louchet-Chauvet et al., New J. Phys. 13, 065026, 2011; A. Peters et al., Nature 400, 849, 1999.</p><p>(2) P. Asenbaum et al., Phys. Rev. Lett. 118, 183602, 2017; M. J. Snadden et al., Phys. Rev. Lett. 81, 971, 1998.</p><p>(3) L. Richardson et al., Comm. Phys. 3, 208, 2020; P. Cheiney et al., Phys. Rev. Applied 10, 034030, 2018; J. Lautier et al., Appl. Phys. Lett. 105, 144102, 2014.</p><p>(4) A. Trimeche et al., Class. Quantum Grav. 36, 215004, 2019; K. Douch et al., Adv. Space. Res. 61, 1301, 2018.</p><p>(5) T. Lévèque et al., arXiv:2011.03382; S. Chiow et al., Phys. Rev. A 92, 063613, 2015.</p><p>(6) M. Lachmann et al., arXiv:2101.00972; K. Frye et al., EPJ Quant. Technol. 8, 1, 2021; D. Becker et al., Nature 562, 391, 2018; J. Rudolph et al., New J. Phys. 17, 065001, 2015; H. Müntinga et al., Phys. Rev. Lett. 110, 093602 , 2013.</p>