scholarly journals Keys to Differentiating between Small- and Large-Drop Icing Conditions in Continental Clouds

2019 ◽  
Vol 58 (9) ◽  
pp. 1931-1953
Author(s):  
Ben C. Bernstein ◽  
Roy M. Rasmussen ◽  
Frank McDonough ◽  
Cory Wolff
Keyword(s):  
Boundary Layer ◽  
Drop Size ◽  
Liquid Water Content ◽  
Great Lakes Region ◽  
Small Drop ◽  
Size Discrimination ◽  
Large Drop ◽  
Flight Data ◽  
Local Boundary ◽  
Research Aircraft

AbstractUsing observations from research aircraft flights over the Great Lakes region, synoptic and mesoscale environments that appear to drive a relationship between liquid water content, drop concentration, and drop size are investigated. In particular, conditions that fell within “small drop” and “large drop” regimes are related to cloud and stability profiles, providing insight regarding whether the clouds are tied to the local boundary layer. These findings are supported by analysis of flight data from other parts of North America and used to provide context for several icing incidents and accidents where large-drop icing was noted as a contributing factor. The relationships described for drop size discrimination in continental environments provide clues that can be applied for both human- and model-generated icing forecasts, as well as automated icing algorithms.

Radar Icing Algorithm: Algorithm Description and Comparison with Aircraft Observations

2021 ◽  
Author(s):  
David J. Serke ◽  
Scott M. Ellis ◽  
Sarah A. Tessendorf ◽  
David E. Albo ◽  
John C. Hubbert ◽  
...  
Keyword(s):  
Solid Phase ◽  
Weather Prediction ◽  
Relative Size ◽  
Particle Diameter ◽  
Area Under The Curve ◽  
Mixed Phase ◽  
Small Drop ◽  
Large Drop ◽  
Statistical Measures ◽  
Research Aircraft

AbstractDetection of in-flight icing hazard is a priority of the aviation safety community. The ‘Radar Icing Algorithm’ (RadIA) has been developed to indicate the presence, phase, and relative size of supercooled drops. This paper provides an evaluation of RadIA via comparison to in-situ microphysical measurements collected with a research aircraft during the 2017 'Seeded and Natural Orographic Wintertime clouds: the Idaho Experiment' (SNOWIE) field campaign.RadIA uses Level 2 dual-polarization radar moments from operational National Weather Service WSR-88D radar and a numerical weather prediction model temperature profile as inputs. Moment membership functions are defined based on the results of previous studies, and fuzzy logic is used to combine the output of these functions to create a 0 to 1 interest for detecting small-drop, large-drop and mixed phase icing.Data from the 2D-S particle probe on board the University of Wyoming King Air aircraft were categorized as either liquid or solid phase water with a shape classification algorithm and binned by size. RadIA interest values from 17 cases were matched to statistical measures of the solid/liquid particle size distributions (such as maximum particle diameter) and values of LWC from research aircraft flights. Receiver Operating Characteristic Area Under the Curve (AUC) values for RadIA algorithms were 0.75 for large-drop, 0.73 for small-drop, and 0.83 for mixed-phase cases. RadIA is proven to be a valuable new capability for detecting the presence of in-flight icing hazards from ground-based precipitation radar.

scholarly journals Raindrop Size Distribution and Rain Characteristics during the 2013 Great Colorado Flood

2015 ◽  
Vol 17 (1) ◽  
pp. 53-72 ◽  
Author(s):  
Katja Friedrich ◽  
Evan A. Kalina ◽  
Joshua Aikins ◽  
Matthias Steiner ◽  
David Gochis ◽  
...  
Keyword(s):  
Drop Size ◽  
Doppler Radar ◽  
Liquid Water Content ◽  
Size Distributions ◽  
Intense Rainfall ◽  
Wind Fields ◽  
Raindrop Size Distribution ◽  
Median Volume ◽  
Drop Size Distributions ◽  
Analysis System

Abstract Drop size distributions observed by four Particle Size Velocity (PARSIVEL) disdrometers during the 2013 Great Colorado Flood are used to diagnose rain characteristics during intensive rainfall episodes. The analysis focuses on 30 h of intense rainfall in the vicinity of Boulder, Colorado, from 2200 UTC 11 September to 0400 UTC 13 September 2013. Rainfall rates R, median volume diameters D0, reflectivity Z, drop size distributions (DSDs), and gamma DSD parameters were derived and compared between the foothills and adjacent plains locations. Rainfall throughout the entire event was characterized by a large number of small- to medium-sized raindrops (diameters smaller than 1.5 mm) resulting in small values of Z (<40 dBZ), differential reflectivity Zdr (<1.3 dB), specific differential phase Kdp (<1° km−1), and D0 (<1 mm). In addition, high liquid water content was present throughout the entire event. Raindrops observed in the plains were generally larger than those in the foothills. DSDs observed in the foothills were characterized by a large concentration of small-sized drops (d < 1 mm). Heavy rainfall rates with slightly larger drops were observed during the first intense rainfall episode (0000–0800 UTC 12 September) and were associated with areas of enhanced low-level convergence and vertical velocity according to the wind fields derived from the Variational Doppler Radar Analysis System. The disdrometer-derived Z–R relationships reflect how unusual the DSDs were during the 2013 Great Colorado Flood. As a result, Z–R relations commonly used by the operational NEXRAD strongly underestimated rainfall rates by up to 43%.

scholarly journals An aircraft-borne chemical ionization – ion trap mass spectrometer (CI-ITMS) for fast PAN and PPN measurements

2010 ◽  
Vol 3 (5) ◽  
pp. 4313-4354
Author(s):  
A. Roiger ◽  
H. Aufmhoff ◽  
P. Stock ◽  
F. Arnold ◽  
H. Schlager
Keyword(s):  
Boundary Layer ◽  
Mass Spectrometer ◽  
Chemical Ionization ◽  
Ion Trap ◽  
The Arctic ◽  
Arctic Boundary Layer ◽  
Online Calibration ◽  
Mixing Ratios ◽  
Ion Trap Mass Spectrometer ◽  
Research Aircraft

Abstract. An airborne chemical ionization ion trap mass spectrometer instrument (CI-ITMS) has been developed for tropospheric and stratospheric fast in-situ measurements of PAN (peroxyacetyl nitrate) and PPN (peroxypropionyl nitrate). The first scientific deployment of the FASTPEX instrument (FASTPEX = Fast Measurement of Peroxyacyl nitrates) took place in the Arctic during 18 missions aboard the DLR research aircraft Falcon, within the framework of the POLARCAT-GRACE campaign in the summer of 2008. The FASTPEX instrument is described and characteristic properties of the employed ion trap mass spectrometer are discussed. Atmospheric data obtained at altitudes of up to ~12 km are presented, from the boundary layer to the lowermost stratosphere. Data were sampled with a time resolution of 2 s and a 2σ detection limit of 25 pmol mol−1. An isotopically labelled standard was used for a permanent online calibration. For this reason the accuracy of the PAN measurements is better than ±10% for mixing ratios greater than 200 pmol mol−1. PAN mixing ratios in the summer Arctic troposphere were in the order of a few hundred pmol mol−1 and generally correlated well with CO. In the Arctic boundary layer and lowermost stratosphere smaller PAN mixing ratios were observed due to a combination of missing local sources of PAN precursor gases and efficient removal processes (thermolysis/photolysis). PPN, the second most abundant PAN homologue, was measured simultanously. Observed PPN/PAN ratios range between ~0.03 and 0.3.

GPR-based novel approach for non-linear aerodynamic modelling from flight data

2018 ◽  
Vol 123 (1259) ◽  
pp. 79-92
Author(s):  
A. Kumar ◽  
A. K. Ghosh
Keyword(s):  
Aerodynamic Force ◽  
Equations Of Motion ◽  
Gaussian Process Regression ◽  
Likelihood Estimation ◽  
Flight Data ◽  
Novel Approach ◽  
Non Linear ◽  
Research Aircraft ◽  
Novel Method ◽  
Aerodynamic Modelling

ABSTRACTIn this paper, a Gaussian process regression (GPR)-based novel method is proposed for non-linear aerodynamic modelling of the aircraft using flight data. This data-driven regression approach uses the kernel-based probabilistic model to predict the non-linearity. The efficacy of this method is examined and validated by estimating force and moment coefficients using research aircraft flight data. Estimated coefficients of aerodynamic force and moment using GPR method are compared with the estimated coefficients using maximum-likelihood estimation (MLE) method. Estimated coefficients from the GPR method are statistically analysed and found to be at par with estimated coefficients from MLE, which is popularly used as a conventional method. GPR approach does not require to solve the complex equations of motion. GPR further can be directed for the generalised applications in the area of aeroelasticity, load estimation, and optimisation.

scholarly journals Boundary layer evolution over the central Himalayas from radio wind profiler and model simulations

2016 ◽  
Vol 16 (16) ◽  
pp. 10559-10572 ◽  
Author(s):  
Narendra Singh ◽  
Raman Solanki ◽  
Narendra Ojha ◽  
Ruud H. H. Janssen ◽  
Andrea Pozzer ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Mixed Layer ◽  
Surface Ozone ◽  
Wrf Model ◽  
Ground Level ◽  
Wind Profiler ◽  
Pollution Transport ◽  
Local Boundary ◽  
The Mean

Abstract. We investigate the time evolution of the Local Boundary Layer (LBL) for the first time over a mountain ridge at Nainital (79.5° E, 29.4° N, 1958 m a.m.s.l.) in the central Himalayan region, using a radar wind profiler (RWP) during November 2011 to March 2012, as a part of the Ganges Valley Aerosol Experiment (GVAX). We restrict our analysis to clear–sunny days, resulting in a total of 78 days of observations. The standard criterion of the peak in the signal-to-noise ratio (S ∕ N) profile was found to be inadequate in the characterization of mixed layer (ML) top at this site. Therefore, we implemented a criterion of S ∕ N > 6 dB for the characterization of the ML and the resulting estimations are shown to be in agreement with radiosonde measurements over this site. The daytime average (05:00–10:00 UTC) observed boundary layer height ranges from 440 ± 197 m in November (late autumn) to 766 ± 317 m above ground level (a.g.l.) in March (early spring). The observations revealed a pronounced impact of mountain topography on the LBL dynamics during March, when strong winds (> 5.6 m s−1) lead to LBL heights of 650 m during nighttime. The measurements are further utilized to evaluate simulations from the Weather Research and Forecasting (WRF) model. WRF simulations captured the day-to-day variations up to an extent (r2 = 0.5), as well as the mean diurnal variations (within 1σ variability). The mean biases in the daytime average LBL height vary from −7 % (January) to +30 % (February) between model and observations, except during March (+76 %). Sensitivity simulations using a mixed layer model (MXL/MESSy) indicated that the springtime overestimation of LBL would lead to a minor uncertainty in simulated surface ozone concentrations. However, it would lead to a significant overestimation of the dilution of black carbon aerosols at this site. Our work fills a gap in observations of local boundary layer over this complex terrain in the Himalayas, and highlights the need for year-long simultaneous measurements of boundary layer dynamics and air quality to better understand the role of lower tropospheric dynamics in pollution transport.

The Amazon river breeze and the local boundary layer: I. Observations

1993 ◽  
Vol 63 (1-2) ◽  
pp. 141-162 ◽  
Author(s):  
Amauri Pereira de Oliveira ◽  
David R. Fitzjarrald
Keyword(s):  
Boundary Layer ◽  
Amazon River ◽  
Local Boundary ◽  
Layer I

DETERMINATION OF WIND SHEAR AND TURBULENCE INTENSITY ACCORDING TO YAK42-D “ROSHYDROMET” RESEARCH AIRCRAFT DATA

2021 ◽  
pp. 117-129
Author(s):  
V. V. VOLKOV ◽  
◽  
M. A. STRUNIN ◽  
A. M. STRUNIN ◽  
◽  
...  
Keyword(s):  
Boundary Layer ◽  
Wind Speed ◽  
Wind Shear ◽  
Vertical Shear ◽  
Horizontal Shear ◽  
S 100 ◽  
Research Aircraft ◽  
The Difference ◽  
Wind Shears ◽  
Aircraft Data

The results of the development and comparative analysis of methods for determining wind shear in the atmosphere (regression and difference ones) based on research aircraft data are presented. It is shown that shear calculation by the regression method gives the error of 0.002-0.006 (m/s)/km (depending on the length of the measurement sections) for horizontal shears and 0.04-0.12 (m/s)/100 m for vertical shears; the respective error of the difference method is 0.007 (m/s)/km and 0.07 (m/s)/100 m. Based on the Yak-42D “Roshydromet” research aircraft data, the values of shears of two horizontal components of wind speed in three directions (two horizontal and vertical) were calculated. According to the data of two research aircraft flights, the maximum values of the horizontal shear of wind speed components were reached above the boundary layer and were equal to 0.2 (m/s)/km, and the vertical shear was 1.2 (m/s)/100 m. The energy profiles of horizontal and vertical turbulent pulsations are constructed, it is shown that intense turbulence smooths wind shears in the convective atmospheric boundary layer.

The adiabaticity of warm cumulus clouds simulated in high-resolution 

2021 ◽  
Author(s):  
Eshkol Eytan ◽  
Ilan Koren ◽  
Alexander Khain ◽  
Orit Altaratz ◽  
Mark Pinsky ◽  
...  
Keyword(s):  
High Resolution ◽  
Environmental Parameters ◽  
Liquid Water Content ◽  
Cumulus Clouds ◽  
Local Boundary ◽  
Aerosol Loading ◽  
Hebrew University ◽  
Key Variables ◽  
Microphysical Processes ◽  
Bin Microphysics

<p>The strong coupling between dynamic, thermodynamic, and microphysical processes and the numerous environmental parameters on which they depend makes clouds a highly complex system. Adiabatic regions (i.e., undiluted core) in the cloud allow to approximate in a simple way thermodynamic and microphysical profiles and provide local boundary conditions (i.e. core is a source of adiabatic values in each level). Mixing of the cloud with its environment affects both the cloud and the environmental properties. While environmental humidity, temperature and aerosol loading affect the clouds’ buoyancy and droplets size distribution (DSD), clouds simultaneously affect their surrounding via detrainment of droplets, humid air, and processed aerosols. Mixing occurs within a large spectrum of scales and leads to deviation of parts of the cloud from adiabaticity. The level of adiabaticity can be represented continuously by the adiabatic fraction (AF; defined as the ratio of the liquid water content to the theoretical adiabatic value). In this work we used the System of Atmosphere Modeling (SAM) with the Hebrew University Spectral Bin Microphysics to simulate a few isolated non-precipitating trade cumulus clouds (in different sizes and aerosol loading) in high resolution (10m). Passive tracer was added to all the simulations. We found cloudy volumes that contain both high tracer concentration and high AF (up to the clouds’ top), compared these two measures of mixing, and discuss their differences. The accuracy of AF calculations, based on different known methods is tested. For example, we show that the saturation adjustment assumption that is often used in AF calculations can lead to an underestimation of AF in pristine environments. This will mask microphysical effects and cause biases when comparing the adiabaticity of clouds under different aerosols loading. We show that the space spanned by the AF versus height in the cloud is a good measure for describing changes in cloud’s key variables in space and time (like temperature, updraft, and DSD properties). This space of AF vs height demonstrates how certain processes (e.g. in-cloud nucleation, mixing, evaporation, etc.) dominate different regions in the cloud (core, edge), and cause different dependence of the DSD on AF under different aerosols loading.</p>

Aerosol and Cloud Changes during the Corona Lockdown in 2020 – First highlights from the BLUESKY campaign

2021 ◽  
Author(s):  
Christiane Voigt ◽  
Jos Lelieveld ◽  
Hans Schlager ◽  
Johannes Schneider ◽  
Daniel Sauer ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Atmospheric Composition ◽  
Data Set ◽  
The North ◽  
Aerosol Mass ◽  
Trace Species ◽  
Research Aircraft ◽  
Fine Mode ◽  
Cloud Modeling ◽  
Fine Mode Aerosol

<p>Worldwide regulations to control the COVID-19 pandemic caused significant reductions in ground and airborne transportation in spring 2020. This unprecedented situation provided the unique opportunity to directly measure the less perturbed atmosphere, notably near the tropopause, and derive the effects of anthropogenic emissions on atmospheric composition, aerosol, clouds and climate. These changes were investigated during the BLUESKY experiment by the two research aircraft HALO and the DLR Falcon, satellite observations and models. From 16 May to 9 June 2020, the two research aircraft performed 20 flights over Europe and the North Atlantic. Profiles of trace species were measured with an advanced in-situ trace gas, aerosol and cloud payload from the boundary layer to 14 km altitude. Here, we present an overview and selected highlights of the BLUESKY experiment. Continental aerosol profiles show significant reductions in aerosol mass in the boundary layer. The reduced aerosol optical thickness above Germany has also been detected by MODIS and its impact on the colour of the sky is investigated. A specific focus was the detection of aerosol and cirrus changes caused by up to 90% reductions in air traffic. We find reductions in fine mode aerosol in the UTLS at various levels compared to CARIBIC data. In addition, we derive reductions in contrail and cirrus cover using passive and active remote sensing from satellite combined with cloud modeling. The comprehensive data set acquired during the 2020 lockdown period allows better understanding and constraining the anthropogenic influence on the composition of the atmosphere and its impacts on air quality and climate.</p>

Sign in / Sign up

Export Citation Format

Share Document