bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Giant Nucleus Impactor (GNI)—A System for the Impaction and Automated Optical Sizing of Giant Aerosol Particles with Emphasis on Sea Salt. Part I: Basic Instrument and Algorithms
Authors: Jensen Jørgen B. , Beaton Stuart P. , Stith Jeffrey L. , Schwenz Karl , Colón-Robles Marilé , Rauber Robert M. , Gras John 
Published: August 2020

AbstractSize distributions of giant aerosol particles (dry radius larger than 0.5μm, sometimes referred to as coarse-mode aerosol particles) are not well characterized in the atmosphere. Measurements are problematic for these particles because they (i) occur in low concentrations, (ii) have difficulty in passing through air inlets, (iii) may be dry or deliquesced particles, and (iv) if sampled by impaction, typically require labor-intensive methods. In this study, a simple, high-volume impaction system called the Giant Nucleus Impactor (GNI), based on free-stream exposure of polycarbonate slides from aircraft, is described along with an automated optical microscope–based system for analysis of the impacted particles. The impaction slides are analyzed in a humidity-controlled chamber (typically 90% relative humidity) that ensures deliquescence of soluble (typically sea salt) particles. A computer-controlled optical microscope with two digital cameras is used to acquire and analyze images of the aerosol particles. At relative humidities above deliquescence (74% RH for sea salt), such particles will form near-spherical cap solution drops on the polycarbonate slides. The sea-salt mass in each giant aerosol particle is then calculated using simple geometry and published water activity measurements. The system has a sample volume of about 10 L s−1at aircraft speeds of 105 m s−1. For salt particles, the measurement range is from about 0.7μm dry radius to at least 16μm dry radius, with a size-bin resolution of 0.2μm dry radius. The sizing accuracy was tested using polystyrene latex (PSL) beads of known size.
An Expanded Batch-to-Batch Correction for IAPSO Standard Seawater
Authors: Uchida Hiroshi , Kawano Takeshi , Nakano Toshiya , Wakita Masahide , Tanaka Tatsuya , Tanihara Sonoka 
Published: August 2020

AbstractWe expanded the batch-to-batch offsets of The International Association for the Physical Sciences of the Oceans (IAPSO) Standard Seawater (SSW) batches P145–P163 by intercomparison measurements using salinometers. On the basis of our results, we recommend using the correction factors instead of the offsets to correct the batch-to-batch differences, especially for salinity data outside the range of 30–40 g kg−1. We evaluated the expanded batch-to-batch correction factors by applying them to time series salinity data collected in the northwestern North Pacific Ocean and found that they are effective for detecting recent freshening (−0.6 ± 0.1 × 10−3 g kg−1 decade−1) in the deep North Pacific, which might be related to a reduction of the formation rate of Antarctic Bottom Water. We also evaluated the SSW linearity pack by applying the batch-to-batch correction factors. Linearity errors of the salinometers estimated from decade resistance substituters were consistent with the results of the linearity pack measurements. To correct the linearity errors of a salinometer, it might be suitable to use the more detailed distribution of those estimated from the decade resistance substituter than the linearity pack measurements. Since the cause of large batch-to-batch differences is still unclear, a reference seawater that is more robust and stable than SSW might be necessary to establish a high-level of international comparability of salinity measurements; the Multiparametric Standard Seawater (MSSW) currently under development might be a candidate for such reference seawater, because MSSW is expected to be more stable than SSW not only in practical salinity but also in absolute salinity.
CloudA: A Ground-Based Cloud Classification Method with a Convolutional Neural Network
Authors: Wang Min , Zhou Shudao , Yang Zhong , Liu Zhanhua 
Published: August 2020

AbstractConventional classification methods are based on artificial experience to extract features, and each link is independent, which is a kind of “shallow learning.” As a result, the scope of the cloud category applied by this method is limited. In this paper, we propose a new convolutional neural network (CNN) with deep learning ability, called CloudA, for the ground-based cloud image recognition method. We use the Singapore Whole-Sky Imaging Categories (SWIMCAT) sample library and total-sky sample library to train and test CloudA. In particular, we visualize the cloud features captured by CloudA using the TensorBoard visualization method, and these features can help us to understand the process of ground-based cloud classification. We compare this method with other commonly used methods to explore the feasibility of using CloudA to classify ground-based cloud images, and the evaluation of a large number of experiments show that the average accuracy of this method is nearly 98.63% for ground-based cloud classification.
An Adaptive Optimal Interpolation Based on Analog Forecasting: Application to SSH in the Gulf of Mexico
Authors: Zhen Yicun , Tandeo Pierre , Leroux Stéphanie , Metref Sammy , Penduff Thierry , Le Sommer Julien 
Published: August 2020

AbstractBecause of the irregular sampling pattern of raw altimeter data, many oceanographic applications rely on information from sea surface height (SSH) products gridded on regular grids where gaps have been filled with interpolation. Today, the operational SSH products are created using the simple, but robust, optimal interpolation (OI) method. If well tuned, the OI becomes computationally cheap and provides accurate results at low resolution. However, OI is not adapted to produce high-resolution and high-frequency maps of SSH. To improve the interpolation of SSH satellite observations, a data-driven approach (i.e., constructing a dynamical forecast model from the data) was recently proposed: analog data assimilation (AnDA). AnDA adaptively chooses analog situations from a catalog of SSH scenes—originating from numerical simulations or a large database of observations—which allow the temporal propagation of physical features at different scales, while each observation is assimilated. In this article, we review the AnDA and OI algorithms and compare their skills in numerical experiments. The experiments are observing system simulation experiments (OSSE) on the Lorenz-63 system and on an SSH reconstruction problem in the Gulf of Mexico. The results show that AnDA, with no necessary tuning, produces comparable reconstructions as does OI with tuned parameters. Moreover, AnDA manages to reconstruct the signals at higher frequencies than OI. Finally, an important additional feature for any interpolation method is to be able to assess the quality of its reconstruction. This study shows that the standard deviation estimated by AnDA is flow dependent, hence more informative on the reconstruction quality, than the one estimated by OI.
A Multiple Linear Regression Algorithm for Sea Surface Temperature Retrieval by One-Dimensional Synthetic Aperture Microwave Radiometry
Authors: Feng Mengyan , Ai Weihua , Chen Guanyu , Lu Wen , Ma Shuo 
Published: August 2020

AbstractOne-dimensional synthetic aperture microwave radiometer (1D-SAMR) can provide remote sensing images at a higher spatial resolution than those from traditional real aperture microwave radiometers. As 1D-SAMR operates at multiple incidence angles, we proposed a multiple linear regression method to retrieve sea surface temperature at an incidence angle between 0° and 65°. Assuming that a 1D-SAMR operates at various frequencies (i.e., 6.9, 10.65, 18.7, 23.8 and 36.5 GHz), a radiation transmission forward model was developed to simulate the brightness temperature measured by the 1D-SAMR. The sensitivity of the five frequencies to sea surface temperature was examined, and we evaluated the reliability of the regression method proposed in this study. Furthermore, 11 schemes with various frequency combinations were applied to retrieve sea surface temperature. The results showed that the five-frequency combination scheme performed better than the other schemes. This study also found that the accuracy of retrieved sea surface temperature is dependent on incidence angles. Finally, we suggested that the incidence angle range of the 1D-SAMR is necessary to be 30°–60° based on the relationship between the accuracy of retrieved sea surface temperature and the incidence angles.
Columnar Vertical Profile (CVP) Methodology for Validating Polarimetric Radar Retrievals in Ice Using In Situ Aircraft Measurements
Authors: Murphy Amanda M. , Ryzhkov Alexander , Zhang Pengfei 
Published: August 2020

AbstractA novel way to process polarimetric radar data collected via plan position indicator (PPI) scans and display those data in a time–height format is introduced. The columnar vertical profile (CVP) methodology uses radar data collected via multiple elevation scans, limited to data within a set region in range and azimuth relative to the radar, to create vertical profiles of polarimetric radar data representative of that limited region in space. This technique is compared to others existing in the literature, and various applications are discussed. Polarimetric ice microphysical retrievals are performed on CVPs created within the stratiform rain region of two mesoscale convective systems sampled during two field campaigns, where CVPs follow the track of research aircraft. Aircraft in situ data are collocated to microphysical retrieval data, and the accuracy of these retrievals is tested against other retrieval techniques in the literature.
Investigation of Compression and Reconstruction Methods for Solar Radiation Spectra above, within, and below the Sea Ice in Polar Environments
Authors: Wang Hangzhou , Nan Liwen , Wang Xiaoping , Tu Jiuzhou , Chen Ying 
Published: August 2020

AbstractTo reduce the amount of data transmitted, while retaining essential information on the original signal after reconstruction, this study investigated three different compression and reconstruction methods for the solar irradiance signals at different levels of the Arctic sea ice. To achieve this, characteristics of solar irradiance at different depths of the Arctic sea ice were analyzed; the solar irradiance profile was measured using a fiber optic spectrometer system at several ice packs from 11 to 25 August 2018, during the ninth Chinese National Arctic Research Expedition. Based on these measurements, three potential methods—fast Fourier transform (FFT), discrete wavelet transform (DWT), and Prony’s method—were selected and applied for the compression and reconstruction of a group of 12 measurements from one profile. The results indicated that the FFT method was generally superior to the DWT method considering the corrected reconstruction rate Rc, under the same compression ratio C. The FFT method had the highest Rc for signals with higher roughness, whereas Prony’s method was more suitable for smoother signals. To ensure that Rc was at least 80% and C was as large as possible, the compression and reconstruction method proposed in this study included the FFT method (C = 6.4) for the signals rougher than 1.5 and Prony’s method employing the matrix pencil method (C = 8) for the smoother signals. The proposed method was successfully verified using an independent group of solar irradiance measurements from another profile in the Arctic sea ice.
Investigation of the Transient Nature of Thunderstorm Winds from Europe, the United States, and Australia Using a New Method for Detection of Changepoints in Wind Speed Records
Authors: Romanic Djordje , Chowdhury Junayed , Chowdhury Jubayer , Hangan Horia 
Published: August 2020

Abstract
This paper investigates the transient characteristics in 41 velocity records of 19 thunderstorm events from around the world—9 from Europe, 9 from the United States, and 1 from Australia. The transient features of thunderstorm winds were examined by introducing an objective method for the detection of changepoints in the time series. The methodology divides velocity records into segments characterized by different statistical properties. The segmentation is based on the following properties of the isolated segments: mean (M) and the standard deviation (SD). This study demonstrated that the maximum velocity during the thunderstorm peak in the events from Europe is typically 2–4 times larger than the mean wind speed before the thunderstorm. The duration of the thunderstorm velocity peak was 2–5 min in approximately 60% of the analyzed records using the M statistic and 5–10 min when analyzed using the SD statistic. Therefore, the velocity fluctuations caused by thunderstorm winds last longer than the abrupt changes in the mean wind field. Similarly, the ramp-up time was longer when the records were analyzed using the SD statistic. The segmentation methodology was tested for different duration of velocity records and using data with different sampling frequencies. The performances of the introduced method were compared against the results of two other segmentation procedures proposed in the literature. One of the practical applications of this method is the physical separation between the thunderstorm and nonthunderstorm components of a wind event.

Significance Statement
Thunderstorm outflow winds are short-lived phenomena produced by cold downdrafts that originate in thunderstorm clouds. This study analyzes the transient nature of thunderstorm winds from Europe, the United States, and Australia using a segmentation method applied to anemometer velocity records. This segmentation method identifies abrupt changes of mean wind speed and wind fluctuations in the velocity data. This research provides the means of isolating different segments within the thunderstorm wind records in an objective way that is based on rigorous mathematical principles. The proposed method can automatically distinguish thunderstorm from nonthunderstorm winds. The peak velocities in thunderstorm outflows are 2–4 times the mean wind speed before the thunderstorm. The most intense episodes of thunderstorm winds usually last 2–5 min.
Diurnal Variation of the Convective Area and Eye Size Associated with the Rapid Intensification of Tropical Cyclones
Authors: Lee Jae-Deok , Wu Chun-Chieh , Ito Kosuke 
Published: August 2020

AbstractThis study examines the diurnal variation of the convective area and eye size of 30 rapidly intensifying tropical cyclones (RI TCs) that occurred in the western North Pacific from 2015 to 2017 utilizing Himawari-8 satellite imagery. The convective area can be divided into the active convective area (ACA), mixed phase, and inactive convective area (IACA) based on specific thresholds of brightness temperature. In general, ACA tends to develop vigorously from late afternoon to early the next morning, while mixed phase and IACA develop during the day. This diurnal pattern indicates the potential for ACA to evolve into mixed phase or IACA over time. From the 30 samples, RI TCs tend to have at least a single-completed diurnal signal of ACA inside the radius of maximum wind (RMW) during the rapidly intensifying period. In the same period, the RMW also contracts significantly. Meanwhile, more intense storms such as those of category 4 or 5 hurricane intensity are apt to have continuous ACA inside the RMW and maintain eyewall convective clouds. These diurnal patterns of the ACA could vary depending on the impact of large-scale environments such as vertical wind shear, ocean heat content, environmental mesoscale convection, and terrain. The linear regression analysis shows that from the tropical storm stage, RI commences after a slow intensification period, which enhances both the primary circulation and eyewall convective cloud. Finally, after the eye structure appears in satellite imagery, its size changes inversely to the diurnal variation of the convective activity (e.g., the eye size becomes larger during the daytime).
Factors Affecting the Weakening Rate of Tropical Cyclones over the Western North Pacific
Authors: Fei Rong , Xu Jing , Wang Yuqing , Yang Chi 
Published: August 2020

Abstract
In this study, based on the 6-hourly tropical cyclone (TC) best track data and the ERA-Interim reanalysis data, statistical analyses as well as a machine learning approach, XGBoost, are used to identify and quantify factors that affect the overwater weakening rate (WR) of TCs over the western North Pacific (WNP) during 1980–2017. Statistical analyses show that the TC rapid weakening events usually occur when intense TCs cross regions with a sharp decrease in sea surface temperature (DSST) with relatively faster eastward or northward translational speeds, and move into regions with large environmental vertical wind shear (VWS) and dry conditions in the upshear-left quadrant. Results from XGBoost indicate that the relative intensity of TC (TC intensity normalized by its maximum potential intensity), DSST, and VWS are dominant factors determining TC WR, contributing 26.0%, 18.3%, and 14.9% to TC WR, and 9, 5, and 5 m s−1 day−1 to the variability of TC WR, respectively. Relative humidity in the upshear-left quadrant of VWS, zonal translational speed, divergence at 200 hPa, and meridional translational speed contribute 12.1%, 11.8%, 8.8%, and 8.1% to TC WR, respectively, but only contribute 2–3 m s−1 day−1 to the variability of TC WR individually. These findings suggest that the improved accurate analysis and prediction of the dominant factors may lead to substantial improvements in the prediction of TC WR.
Gravity Waves and Other Mechanisms Modulating the Diurnal Precipitation over One of the Rainiest Spots on Earth: Observations and Simulations in 2016
Authors: Yepes Johanna , Mejía John F. , Mapes Brian , Poveda Germán 
Published: August 2020

ABSTRACTThe diurnal cycle of precipitation and thermodynamic profiles over western Colombia are examined in new GPM satellite rainfall products, first-ever research balloon launches during 2016 over both sea and land, and numerical simulations with the Weather Research and Forecasting (WRF) Model. This paper evaluates the Mapes et al. mechanism for midnight–early morning coastal convection that propagates offshore: reduction of inhibition in the crests of lower-tropospheric internal waves. Shipborne balloon launches confirm the evening development of such inhibition by a warm overhang in saturation moist static energy (SMSE) near 700–800 hPa. This feature relaxes overnight, consistent with the disinhibition hypothesis for early morning rains. Over the coastal plain, soundings also show late afternoon increases in near-surface MSE large enough to predominate over the overhang’s inhibition effect, driving a second peak in the rainfall diurnal cycle. Parameterized convection simulations fail to simulate the observed coastal rainfall. Still, during a November 2016 wet spell, a cloud-permitting one-way nested 4 km simulation performs better, simulating morning coastal rainfall. In that simulation, however, early morning cooling in the 700–800 hPa layer appears mainly as a standing signal resembling the local radiative effect rather than as a propagating wave. We consider the additional hypothesis that the offshore propagation of that morning convection could involve advection or wind shear effects on organized convective systems. Strong easterlies at mountaintop level were indeed simulated, but that is one of the model’s strongest biases, so the mechanisms of the model’s partial success in simulating diurnal rainfall remain ambiguous.
Statistical and Empirical Relationships between Tornado Intensity and Both Topography and Land Cover Using Rapid-Scan Radar Observations and a GIS
Authors: Houser Jana B. , McGinnis Nathaniel , Butler Kelly M. , Bluestein Howard B. , Snyder Jeffrey C. , French Michael M. 
Published: August 2020

AbstractThis study presents an investigation into relationships among topographic elevation, surface land cover, and tornado intensity using rapid scan, mobile Doppler radar observations of four tornadoes from the U.S. Central Plains. High spatiotemporal resolution observations of tornadic vortex signatures from the radar’s lowest elevation angle data (in most cases ranging from ~100 to 350 m above ground level) are coupled with digital elevation model (DEM) and 2011 National Land Cover Database (NLCD) data using a geographic information system (GIS). The relationships between 1) tornado intensity and topographic elevation or surface roughness and 2) changes in tornado intensity and changes in topographic elevation or surface roughness are investigated qualitatively, and statistical relationships are quantified and analyzed using a bootstrap permutation method for individual case studies and all cases collectively. Results suggest that there are statistically significant relationships for individual cases, but the relationships defy generalization and are different on a case-by-case basis, which may imply that they are coincidental, indicating a null correlation.
A Two-Stage Fourth-Order Multimoment Global Shallow-Water Model on the Cubed Sphere
Authors: Che Yuzhang , Chen Chungang , Xiao Feng , Li Xingliang , Shen Xueshun 
Published: August 2020

AbstractA new multimoment global shallow-water model on the cubed sphere is proposed by adopting a two-stage fourth-order Runge–Kutta time integration. Through calculating the values of predicted variables at half time step t = tn + (1/2)Δt by a second-order formulation, a fourth-order scheme can be derived using only two stages within one time step. This time integration method is implemented in our multimoment global shallow-water model to build and validate a new and more efficient numerical integration framework for dynamical cores. As the key task, the numerical formulation for evaluating the derivatives in time has been developed through the Cauchy–Kowalewski procedure and the spatial discretization of the multimoment finite-volume method, which ensures fourth-order accuracy in both time and space. Several major benchmark tests are used to verify the proposed numerical framework in comparison with the existing four-stage fourth-order Runge–Kutta method, which is based on the method of lines framework. The two-stage fourth-order scheme saves about 30% of the computational cost in comparison with the four-stage Runge–Kutta scheme for global advection and shallow-water models. The proposed two-stage fourth-order framework offers a new option to develop high-performance time marching strategy of practical significance in dynamical cores for atmospheric and oceanic models.