Comparison of Met Office regional model soil moisture with COSMOS‐UK field‐scale in situ observations

The UK Met Office state-of-the-art, deterministic, convection-permitting, coupled land-atmosphere, regional weather forecasting system, known as the UKV or UK Variable resolution model (Tang et al. Meteorological Applications, 2013; 20:417–426), has been operational since 2015. Science updates are regularly made to the UKV land surface data assimilation scheme when those updates improve predictions of screen temperature and humidity, since these quantities have a direct impact on atmospheric states and weather forecasts. Less attention has been paid to whether UKV soil moisture analyses are close to independent, in-situ soil moisture observations, partly because it is difficult to make meaningful comparisons between 1.5 km2 gridded model outputs and traditional point sensor measurements. Soil moisture is recognized to be important when hydrological forecasts for runoff and rivers are required. This is because soil moisture controls the extent to which rainfall can infiltrate the soil, and the amount of surface runoff affects the timing of peak river flows (Ward & Robinson, Principles of Hydrology. McGraw-Hill Publishing Company; 2000; Singh et al. Water Resources Research, 2021, 57, e2020WR028827). Gómez et al. (Remote Sensing, 2020; 12:3691) report benefits to river flow forecasts when using soil moisture data assimilation in the UKV system instead of a daily downscaled product from the Met Office global model. The Met Office measures soil temperature and soil moisture at Cardington (Osborne & Weedon, Journal of Hydrometeorology, 2021, 22:279–295); there is no other UK Met Office site at which soil moisture is measured. In this study, we use field-scale (~200 m radius) soil moisture measurements from the UK Centre for Ecology and Hydrology's (UKCEH's) COSMOS-UK network to provide independent verification and analysis of UKV soil moisture during summer 2018, an unusually dry period in the United Kingdom. We find that the match to COSMOS-UK soil moisture observations is generally good, and that changes made to the land data assimilation approach during a recent operational upgrade had a generally beneficial impact on UKV soil moisture analyses under very dry conditions

A robust automated technique for operational calibration of ceilometers using the integrated backscatter from totally attenuating liquid clouds

A simple and robust method for calibrating ceilometers has been tested in an operational environment demonstrating that the calibrations are stable to better than ± 5 % over a period of a year. The method relies on using the integrated backscatter (B) from liquid clouds that totally extinguish the ceilometer signal; B is inversely proportional to the lidar ratio (S) of the backscatter to the extinction for cloud droplets. The calibration technique involves scaling the observed backscatter so that B matches the predicted value for S of 18.8 ± 0.8 sr for cloud droplets, at ceilometer wavelengths. For accurate calibration, care must be taken to exclude any profiles having targets with different values of S, such as drizzle drops and aerosol particles, profiles that do not totally extinguish the ceilometer signal, profiles with low cloud bases that saturate the receiver, and any profiles where the window transmission or the lidar pulse energy is low. A range dependent multiple scattering correction that depends on the ceilometer optics should be applied to the profile. A simple correction for water vapour attenuation for ceilometers operating at around 910 nm wavelength is applied to the signal using the vapour profiles from a forecast analysis. For a generic ceilometer in the UK the 90-day running mean of the calibration coefficient over a period of 20 months is constant to within 3 % with no detectable annual cycle, thus confirming the validity of the humidity and multiple scattering correction. For Gibraltar, where cloud cover is less prevalent than in the UK, the 90-day running mean calibration coefficient was constant to within 4 %. The more sensitive ceilometer model operating at 1064 nm is unaffected by water vapour attenuation but is more prone to saturation in liquid clouds. We show that reliable calibration is still possible, provided the clouds used are above a certain altitude. The threshold is instrument dependent but is typically around 2 km. We also identify a characteristic signature of saturation, and remove any profiles with this signature. Despite the more restricted sample of cloud profiles, a robust calibration is readily achieved, and, in the UK, the running mean 90-day calibration coefficients varied by about 4 % over a period of one year. The consistency of profiles observed by nine pairs of co-located ceilometers in the UK Met Office network operating at around 910 nm and 1064 nm provided independent validation of the calibration technique. EUMETNET is currently networking 700 European ceilometers so they can provide ceilometer profiles in near real time to European weather forecast centres and has adopted the cloud calibration technique described in this paper for ceilometers with a wavelength of around 910 nm

Toward condition monitoring of damper windings in synchronous motors via EMD analysis

(c) 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.[EN] Failures in damper windings of synchronous machines operating in real facilities have been recently reported by several authors and companies. These windings are crucial elements of synchronous motors and generators, playing an important role in the asynchronous startup of these machines as well as in their stability during load transients. However, the diagnosis of failures in such elements has barely been studied in the literature. This paper presents a method to diagnose the condition of damper bars in synchronous motors. It is based on the capture of the stator current of the machine during a direct startup and its further analysis in order to track the characteristic transient evolution of a particular fault-related component in the time-frequency map. The fact that the damper only carries significant current during the startup and little or no current, when the machine operates in steady state, makes this transient-based approach specially suited for the detection of such failure. The Hilbert-Huang transform (based on the empirical mode decomposition method) is proposed as a signal-processing tool. Simulation and experimental results on laboratory synchronous machines prove the validity of the approach for condition monitoring of such windings. © 2012 IEEE.This work was supported by the Spanish Ministerio de Ciencia e Innovacion (MICINN) in the framework of the VI Plan Nacional de Investigacion Cientifica, Desarrollo e Innovacion Tecnologica 2008-2011. (Programa Nacional de proyectos de Investigacion Fundamental, project reference DPI2011-23740). Paper no. TEC-00443-2011.Antonino-Daviu, J.; Riera-Guasp, M.; Pons Llinares, J.; Roger-Folch, J.; Perez, R.; Charlton-Perez, C. (2012). Toward condition monitoring of damper windings in synchronous motors via EMD analysis. IEEE Transactions on Energy Conversion. 27(2):432-439. https://doi.org/10.1109/TEC.2012.2190292S43243927

Evaluation of forward-modelled attenuated backscatter using an urban ceilometer network in London under clear-sky conditions

Numerical weather prediction (NWP) of urban aerosols is increasingly sophisticated and accurate. In the absence of large particles (e.g. rain, cloud droplets), information on atmospheric aerosols can be obtained from single wavelength automatic lidars and ceilometers (ALC) that measure profiles of attenuated backscatter (βo). To assess the suitability of ALC profile observations for forecast evaluation and data assimilation, a forward operator is required to convert model variables into the measured quantity. Here, an aerosol forward operator (aerFO) is developed and tested with Met Office NWP data (UKV 1.5 km) to obtain synthetic attenuated backscatter profiles (βm). aerFO requires as input the profiles of bulk aerosol mass mixing ratio and relative humidity to compute βm, plus air temperature and pressure to calculate the effect of water vapour absorption. Bulk aerosol characteristics (e.g. mean radius and number concentration) are used to estimate optical properties. ALC profile observations in London are used to assess βm. A wavelength-dependent extinction enhancement factor accounts for the change in optical properties due to aerosol swelling. Sensitivity studies show the aerFO unattenuated backscatter is very sensitive to the aerosol mass and relative humidity above ~60-80 %. The extinction efficiency is sensitive to the choice of aerosol constituents and to ALC wavelength.Given aerosol is a tracer for boundary layer dynamics, application of the aerFO has proven very useful to evaluate the performance of urban surface parameterisation schemes and their ability to drive growth of the mixing layer. Implications of changing the urban surface scheme within the UKV is explored using two spring cases. For the original scheme, morning βm is too high probably because of delayed vertical mixing. The new scheme reduced this persistence of high morning βm, demonstrating the importance of surface heating processes. Analysis of profiles at five sites on 12 clear-sky days shows a positive, statistically significant relation between the differences of modelled and measured near-surface attenuated backscatter [βm - βo] and near-surface aerosol mass. This suggests errors in near-surface attenuated backscatter can be attributed to errors in the amount of aerosol estimated by the NWP scheme. Correlation increases when cases of high relative humidity in the NWP model are excluded. Given the impact on aerosol optical properties demonstrated, results suggest the use of a fixed, bulk aerosol for urban areas in the UKV should be revisited and the lidar ratio should be constrained. As quality of the observed attenuated backscatter is demonstrated to be critical for performing model evaluation, careful sensor operation and data processing is vital to avoid false conclusions to be drawn about model performance

Recommendations for processing atmospheric attenuated backscatter profiles from Vaisala CL31 ceilometers

Ceilometer lidars are used for cloud base height detection, to probe aerosol layers in the atmosphere (e.g. detection of elevated layers of Saharan dust or volcanic ash), and to examine boundary layer dynamics. Sensor optics and acquisition algorithms can strongly influence the observed attenuated backscatter profiles; therefore, physical interpretation of the profiles requires careful application of corrections. This study addresses the widely deployed Vaisala CL31 ceilometer. Attenuated backscatter profiles are studied to evaluate the impact of both the hardware generation and firmware version. In response to this work and discussion within the CL31/TOPROF user community (TOPROF, European COST Action aiming to harmonise ground-based remote sensing networks across Europe), Vaisala released new firmware (versions 1.72 and 2.03) for the CL31 sensors. These firmware versions are tested against previous versions, showing that several artificial features introduced by the data processing have been removed. Hence, it is recommended to use this recent firmware for analysing attenuated backscatter profiles. To allow for consistent processing of historic data, correction procedures have been developed that account for artefacts detected in data collected with older firmware. Furthermore, a procedure is proposed to determine and account for the instrument-related background signal from electronic and optical components. This is necessary for using attenuated backscatter observations from any CL31 ceilometer. Recommendations are made for the processing of attenuated backscatter observed with Vaisala CL31 sensors, including the estimation of noise which is not provided in the standard CL31 output. After taking these aspects into account, attenuated backscatter profiles from Vaisala CL31 ceilometers are considered capable of providing valuable information for a range of applications including atmospheric boundary layer studies, detection of elevated aerosol layers, and model verification

Spatial variability of forward modelled attenuated backscatter in clear‐sky conditions over a megacity: implications for observation network design

Sensors that measure the attenuated backscatter coefficient (e.g. automatic lidars and ceilometers, ALC) provide information on aerosols which can impact urban climate and citizen health. To design an observational network of ALC sensors for supporting data assimilation, and improve prediction of urban weather and air quality, a methodology is needed. In this study, spatio-temporal patterns of aerosol attenuated backscatter coefficient are modelled using Met Office numerical weather prediction (NWP) models at two resolutions, 1.5 km (UKV) and 300 m (London Model, LM), for 28 clear-sky days and nights. Initially, attenuated backscatter coefficient data are analysed using S-mode principal component analysis with VARIMAX rotation. Four to seven empirical orthogonal functions (EOFs) are produced for each model level with common EOFs found across different heights (day and night) for both NWP models. EOFs relate strongly to orography, wind and location of aerosol emissions sources highlighting these as critical controls of attenuated backscatter coefficient spatial variability across the megacity. Urban-rural differences are largest when wind speeds are low and vertical boundary layer dynamics can more effectively distribute near-surface aerosol emissions vertically. In several night-time EOFs, gravity wave features are found for both NWP models. Increasing the horizontal resolution of native ancillaries (model input parameters) and improving the urban surface scheme in the LM may enhance the urban signal in the EOFs. Principal component analysis (PCA) output, with agglomerative Ward cluster analysis (CA), minimises intra-group variance. The UKV and LM CA shape and size results are similar and strongly related to orography. PCA-CA is a simple, but adaptable methodology, allowing close alignment with observation network design goals. Here the CA is used with wind roses to suggest the optimised placement of ALC deployment is one in the city to observe the urban plume, and others surrounding the city, with priority given to cluster size and frequency of upwind advection

Observed aerosol characteristics to improve forward-modelled attenuated backscatter in urban areas

Numerical weather prediction (NWP) models often parameterise aerosols to reduce computational needs, while aiming to accurately capture their impact adequately. Increasingly, aerosols are monitored in-situ directly and/or indirectly (e.g. by automatic lidars and ceilometers, ALC). ALC measure the aerosol optical characteristic of attenuated backscatter. This can also be estimated using forward models that combine forecast aerosol and relative humidity to parameterise aerosol physical and optical characteristics. The aerFO is one such forward model, designed to use Met Office NWP model output and parameterisations from the MURK visibility scheme. Given the aerFO-MURK scheme link, assessing the aerFO and its output could therefore be used to inform future developments of the MURK scheme. To identify which parameterised physical and optical aerosol characteristics in the scheme are the most critical in urban settings, aerFO is driven with different in-situ aerosol observations at a background site in central London. Estimated attenuated backscatter is then assessed against ALC observations. It is shown that the original MURK scheme parameterisation underestimates the variance of both dry mean volume radius and total number concentration. Representing both the accumulation and coarse mode aerosols in the aerFO reduces the median bias error of estimated attenuated backscatter by 69.1 %. Providing more realistic temporal (monthly to hourly) variability of relative mass for different species leads to little improvement, compared to using monthly climatological means. Numerical experiments show that having more realistic estimates of number concentration is more important than providing more accurate values of the dry mean volume radius for the accumulation mode. Hence, improving the parameterisations for number concentration should be a main focus for further development of the MURK scheme. To estimate aerosol attenuated backscatter, the aerFO requires an extinction to backscatter ratio (i.e. the lidar ratio). In addition to forward modelling, the lidar ratio can also be used with ALC attenuated backscatter to calculate aerosol properties estimated in aerosol forecasts. Here, a model is developed that estimates the ratio using in-situ observations of the number size distribution and speciated aerosol masses. The values of lidar ratio derived at the London background site (14 – 80 sr across selected common lidar wavelengths) compare well to the literature. However, the modelled lidar ratio is unexpectedly correlated to relative humidity. Further, a stronger dependence exists at shorter wavelengths (355 and 532 nm) compared to longer wavelengths (905 and 1064 nm), and is due to the critical relation of lidar wavelength to aerosol size. Keywords: urban aerosols; lidar forward operator; automatic lidar and ceilometers; urban observation network; lidar rati

Data Assimilation Enhancements to Air Force Weathers Land Information System

The United States Air Force (USAF) has a proud and storied tradition of enabling significant advancements in the area of characterizing and modeling land state information. 557th Weather Wing (557 WW; DoDs Executive Agent for Land Information) provides routine geospatial intelligence information to warfighters, planners, and decision makers at all echelons and services of the U.S. military, government and intelligence community. 557 WW and its predecessors have been home to the DoDs only operational regional and global land data analysis systems since January 1958. As a trusted partner since 2005, Air Force Weather (AFW) has relied on the Hydrological Sciences Laboratory at NASA/GSFC to lead the interagency scientific collaboration known as the Land Information System (LIS). LIS is an advanced software framework for high performance land surface modeling and data assimilation of geospatial intelligence (GEOINT) information

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity

The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management. © 2021, The Author(s)