scholarly journals Generalizing Cloud Overlap Treatment to Include Solar Zenith Angle Effects on Cloud Geometry

2007 ◽  
Vol 64 (6) ◽  
pp. 2116-2125 ◽  
Author(s):  
Adrian M. Tompkins ◽  
Francesca Di Giuseppe
Keyword(s):  
Zenith Angle ◽  
Large Scale ◽  
Solar Zenith Angle ◽  
Forecast Model ◽  
Simple Extension ◽  
Scale Models ◽  
Field Geometry ◽  
The Mean ◽  
The Impact ◽  
First Time

Shortwave radiative transfer depends on the cloud field geometry as viewed from the direction of the sun. To date, the radiation schemes of large-scale models only consider a zenith view of the cloud field, and the apparent change in the cloud geometry with decreasing solar zenith angle is neglected. A simple extension to an existing cloud overlap scheme is suggested to account for this for the first time. It is based on the assumption that at low sun angles, the overlap between cloud elements is random for an unscattered photon. Using cloud scenes derived from radar retrievals at two European sites, it is shown that the increase of the apparent cloud cover with a descending sun is reproduced very well with the new scheme. Associated with this, there is a marked reduction in the mean radiative biases averaged across all solar zenith angles with respect to benchmark calculations. The scheme is implemented into the ECMWF global forecast model using imposed sea surface temperatures, and while the impact on the radiative statistics is significant, the feedback on the large-scale dynamics is minimal.

scholarly journals Autism Tsunami: the Impact of Rising Prevalence on the Societal Cost of Autism in the United States

2021 ◽  
Author(s):  
Mark Blaxill ◽  
Toby Rogers ◽  
Cynthia Nevison
Keyword(s):  
Forecast Model ◽  
The United States ◽  
Population Projections ◽  
Base Case ◽  
Prevention Strategies ◽  
Total Base ◽  
Cost Categories ◽  
The Cost ◽  
The Impact ◽  
First Time

AbstractThe cost of ASD in the U.S. is estimated using a forecast model that for the first time accounts for the true historical increase in ASD. Model inputs include ASD prevalence, census population projections, six cost categories, ten age brackets, inflation projections, and three future prevalence scenarios. Future ASD costs increase dramatically: total base-case costs of $223 (175–271) billion/year are estimated in 2020; $589 billion/year in 2030, $1.36 trillion/year in 2040, and $5.54 (4.29–6.78) trillion/year by 2060, with substantial potential savings through ASD prevention. Rising prevalence, the shift from child to adult-dominated costs, the transfer of costs from parents onto government, and the soaring total costs raise pressing policy questions and demand an urgent focus on prevention strategies.

scholarly journals Personal Exposure to BC, PM and NO2 in the Paris Region Measured by Portable Sensors Worn by Volunteers

Toxics ◽  
2022 ◽  
Vol 10 (1) ◽  
pp. 33
Author(s):  
Baptiste Languille ◽  
Valérie Gros ◽  
Bonnaire Nicolas ◽  
Cécile Honoré ◽  
Anne Kaufmann ◽  
...  
Keyword(s):  
Large Scale ◽  
Road Traffic ◽  
Personal Exposure ◽  
Portable Sensors ◽  
Promising Solution ◽  
Field Campaigns ◽  
Paris Region ◽  
The Impact ◽  
First Time ◽  
Indoor And Outdoor

Portable sensors have emerged as a promising solution for personal exposure (PE) measurement. For the first time in Île-de-France, PE to black carbon (BC), particulate matter (PM), and nitrogen dioxide (NO2) was quantified based on three field campaigns involving 37 volunteers from the general public wearing the sensors all day long for a week. This successful deployment demonstrated its ability to quantify PE on a large scale, in various environments (from dense urban to suburban, indoor and outdoor) and in all seasons. The impact of the visited environments was investigated. The proximity to road traffic (for BC and NO2), as well as cooking activities and tobacco smoke (for PM), made significant contributions to total exposure (up to 34%, 26%, and 44%, respectively), even though the time spent in these environments was short. Finally, even if ambient outdoor levels played a role in PE, the prominent impact of the different environments suggests that traditional ambient monitoring stations is not a proper surrogate for PE quantification.

scholarly journals Spatial and temporal variations of CO<sub>2</sub> mole fractions observed at Beijing, Xianghe and Xinglong in North China

2021 ◽  
Author(s):  
Yang Yang ◽  
Minqiang Zhou ◽  
Ting Wang ◽  
Bo Yao ◽  
Pengfei Han ◽  
...  
Keyword(s):  
Seasonal Variations ◽  
Human Activities ◽  
North China ◽  
Terrestrial Ecosystem ◽  
Temporal Variations ◽  
Spatial And Temporal Variations ◽  
Boundary Layer Height ◽  
The Mean ◽  
The Impact ◽  
First Time

Abstract. Atmospheric CO2 mole fractions are observed at Beijing (BJ), Xianghe (XH), and Xinglong (XL) in North China using the Picarro G2301 Cavity Ring-Down Spectroscopy instruments. The measurement system is described comprehensively for the first time. The geo-distances among these three sites are within 200 km, but they have very different surrounding environments: BJ is inside the megacity; XH is in the suburban area; XL is in the countryside on a mountain. The mean and standard deviation of CO2 mole fractions at BJ, XH, and XL between October 2018 and September 2019 are 448.4 ± 12.8 ppm, 436.0 ± 9.2 ppm and 420.6 ± 8.2 ppm, respectively. The seasonal variations of CO2 at these three sites are similar, with a maximum in winter and a minimum in summer, which is dominated by the terrestrial ecosystem. However, the seasonal variations of CO2 at BJ and XH are more affected by human activities as compared to XL. By using CO2 at XL as the background, CO2 enhancements are observed simultaneously at BJ and XH. The diurnal variations of CO2 are driven by the boundary layer height, photosynthesis and human activities at BJ, XH and XL. Moreover, we address the impact of the wind on the CO2 mole fractions at BJ and XL. This study provides an insight into the spatial and temporal variations of CO2 mole fractions in North China.

Ivan Kavaleridze`s dramaturgy on the Sumy stage

2021 ◽  
Author(s):  
D.V. Budianskyi
Keyword(s):  
Large Scale ◽  
Musical Comedy ◽  
Historical Figures ◽  
Wide Range ◽  
Socialist Realist ◽  
History Of ◽  
Characteristic Features ◽  
Old Men ◽  
The Impact ◽  
First Time

The characteristic features of I. Kavaleridze’s drama is considered in the article. It is noted that there are signs of the artist’s individuality, attraction to expressionist forms, artistic techniques characteristic for the art of sculpture: symbolism, monumentality, hyperbole. I. Kavaleridze was well versed in the drama laws, understood the specifics of the stage events construction, had a large arsenal of literary means, thanks to which the characters’ monologues and dialogues were extremely expressive and colorful. In his work, he implemented original solutions that were ahead of time. Therefore, many of the artist’s ideas and achievements received due recognition only after his death. I. Kavaleridze’s creative heritage covers a wide range of both purely artistic and general philosophical problems. Among them the formation of the era of modernism and its features in the Ukrainian art of the early XX century, the impact of revolutionary ideas on the work of the 1920s, the role of spiritual leaders of the Ukrainian people T. Shevchenko and G. Skovoroda in the formation of national consciousness, political and ideological pressure on figurative art language and the formation of a socialist-realist canon, etc. The analysis of the productions of I. Kavalerizde’s plays “The First Furrow” and “Gregory and Paraskeva” on the stage of the Mykhailo Shchepkin Sumy Theater of Drama and Musical Comedy in 1970-1972. The article notes that these plays were staged in Sumy for the first time in the history of Ukrainian theater. The premiere of “The First Furrow” (the play was called “Old Men”) took place on March 19, 1970. The figure of the national genius Hryhoriy Skov oroda was als o embodied for the first time on t he stage in Sumy in th e play “Hryhoriy and Paraskeva”. It premiered on October 21, 1972. I. Rybchynsky, Honored Artist of the USSR, performed the production. Creating generalized historical outlines of people’s life, features of life at that time, depicting psychological portraits of people in various, sometimes-dramatic collisions, in the productions of I. Kavaleridze’s plays on the Sumy stage the emphasis was on universal values such as virtue, love. The main character was the Ukrainian people, who nurtured such large-scale historical figures, gave them strength and wisdom for great achievements. Based on publications in periodicals of that time, memoirs of Ukrainian directors, the peculiarities of the director’s interpretation, stenographic and musical design of these plays on the Sumy stage are considered. Considerable attention is paid to the analysis of acting works in I. Kavaleridze’s plays. In particular, the peculiarities of the actor’s embodiment of the image of the national genius Hryhoriy Skovoroda on the stage are presented. It is noted that I. Kavaleridze’s plays, created in a difficult political, social and ideological context, are rightly considered to be highly artistic works of Ukrainian drama. Their staging was carried out on various theatrical stages, including Mykhailo Shchepkin Sumy Theater of Drama and Musical Comedy is an important page of national theatrical art.

scholarly journals The impact of secondary ice production on Arctic stratocumulus

2020 ◽  
Vol 20 (3) ◽  
pp. 1301-1316
Author(s):  
Georgia Sotiropoulou ◽  
Sylvia Sullivan ◽  
Julien Savre ◽  
Gary Lloyd ◽  
Thomas Lachlan-Cope ◽  
...  
Keyword(s):  
Large Scale ◽  
Cloud Condensation Nuclei ◽  
The Arctic ◽  
Computationally Efficient ◽  
Eddy Simulation ◽  
Scale Models ◽  
Break Up ◽  
Ice Production ◽  
Low Sensitivity ◽  
The Impact

Abstract. In situ measurements of Arctic clouds frequently show that ice crystal number concentrations (ICNCs) are much higher than the number of available ice-nucleating particles (INPs), suggesting that secondary ice production (SIP) may be active. Here we use a Lagrangian parcel model (LPM) and a large-eddy simulation (LES) to investigate the impact of three SIP mechanisms (rime splintering, break-up from ice–ice collisions and drop shattering) on a summer Arctic stratocumulus case observed during the Aerosol-Cloud Coupling And Climate Interactions in the Arctic (ACCACIA) campaign. Primary ice alone cannot explain the observed ICNCs, and drop shattering is ineffective in the examined conditions. Only the combination of both rime splintering (RS) and collisional break-up (BR) can explain the observed ICNCs, since both of these mechanisms are weak when activated alone. In contrast to RS, BR is currently not represented in large-scale models; however our results indicate that this may also be a critical ice-multiplication mechanism. In general, low sensitivity of the ICNCs to the assumed INP, to the cloud condensation nuclei (CCN) conditions and also to the choice of BR parameterization is found. Finally, we show that a simplified treatment of SIP, using a LPM constrained by a LES and/or observations, provides a realistic yet computationally efficient way to study SIP effects on clouds. This method can eventually serve as a way to parameterize SIP processes in large-scale models.

scholarly journals What Is the Impact of Additional Tropical Observations on a Modern Data Assimilation System?

2019 ◽  
Vol 147 (7) ◽  
pp. 2433-2449
Author(s):  
Laura C. Slivinski ◽  
Gilbert P. Compo ◽  
Jeffrey S. Whitaker ◽  
Prashant D. Sardeshmukh ◽  
Jih-Wang A. Wang ◽  
...  
Keyword(s):  
El Niño ◽  
Large Scale ◽  
El Nino ◽  
Mean Square ◽  
Observational Network ◽  
In Situ Observations ◽  
The Mean ◽  
The Impact ◽  
Assimilation System

Abstract Given the network of satellite and aircraft observations around the globe, do additional in situ observations impact analyses within a global forecast system? Despite the dense observational network at many levels in the tropical troposphere, assimilating additional sounding observations taken in the eastern tropical Pacific Ocean during the 2016 El Niño Rapid Response (ENRR) locally improves wind, temperature, and humidity 6-h forecasts using a modern assimilation system. Fields from a 50-km reanalysis that assimilates all available observations, including those taken during the ENRR, are compared with those from an otherwise-identical reanalysis that denies all ENRR observations. These observations reveal a bias in the 200-hPa divergence of the assimilating model during a strong El Niño. While the existing observational network partially corrects this bias, the ENRR observations provide a stronger mean correction in the analysis. Significant improvements in the mean-square fit of the first-guess fields to the assimilated ENRR observations demonstrate that they are valuable within the existing network. The effects of the ENRR observations are pronounced in levels of the troposphere that are sparsely observed, particularly 500–800 hPa. Assimilating ENRR observations has mixed effects on the mean-square difference with nearby non-ENRR observations. Using a similar system but with a higher-resolution forecast model yields comparable results to the lower-resolution system. These findings imply a limited improvement in large-scale forecast variability from additional in situ observations, but significant improvements in local 6-h forecasts.

Large-scale fuel deposition patterns on northern Spanish shores following the ‘Prestige’ oil spill

2008 ◽  
Vol 88 (3) ◽  
pp. 463-468 ◽  
Author(s):  
José Luis Acuña ◽  
Araceli Puente ◽  
Ricardo Anadón ◽  
Consolación Fernández ◽  
María Luisa Vera ◽  
...  
Keyword(s):  
Large Scale ◽  
Northern Spain ◽  
The West ◽  
Deposition Patterns ◽  
Prestige Oil Spill ◽  
Cantabrian Coast ◽  
The Mean ◽  
The Impact ◽  
Oil Tanker ◽  
Fuel Deposition

Following the accident of the oil tanker ‘Prestige’, we surveyed the large scale fuel deposition patterns on the Cantabrian shore (northern Spain) covering three regions (from west to east): (i) Asturias, west of Cape Peñas (24 segments surveyed); (ii) Asturias, east of Cape Peñas (33 segments surveyed); and (iii) Cantabria (also east of Cape Peñas, 256 segments surveyed). Fuel arrived to the Cantabrian Coast as a single oil wave which was more intense to the east than to the west of Cape Peñas. The mean percentage of coast length affected was 25, 41 and 15% in western Asturias, eastern Asturias and Cantabria, respectively. However, less than 10% of the substrate was covered by fuel in oiled patches, thus the impact was moderate. We conclude that these patterns are consistent with fuel transport by the Iberian Poleward Current, a hydrographic feature typical of this region during winter.

scholarly journals Effects of solar flares on the ionosphere as shown by the dynamics of ionograms recorded in Europe and South Africa

2019 ◽  
Vol 37 (4) ◽  
pp. 747-761 ◽  
Author(s):  
Veronika Barta ◽  
Gabriella Sátori ◽  
Kitti Alexandra Berényi ◽  
Árpád Kis ◽  
Earle Williams
Keyword(s):  
South Africa ◽  
Zenith Angle ◽  
Solar Flares ◽  
Solar Zenith Angle ◽  
Low Latitude ◽  
Systematic Analysis ◽  
Radio Wave Absorption ◽  
The Mean ◽  
Qualitative Measure ◽  
Solar Flare Effects

Abstract. We have investigated the solar flare effects on ionospheric absorption with the systematic analysis of ionograms measured at midlatitude and low-latitude ionosonde stations under different solar zenith angles. The lowest recorded ionosonde echo, the minimum frequency (fmin, a qualitative proxy for the “nondeviative” radio wave absorption occurring in the D-layer), and the dfmin parameter (difference between the value of the fmin and the mean fmin for reference days) have been considered. Data were provided by meridionally distributed ionosonde stations in Europe and South Africa during eight X- and M-class solar flares in solar cycle 23. Total and partial radio fade-out was experienced at every ionospheric station during intense solar flares (> M6). The duration of the total radio fade-out varied between 15 and 150 min and it was highly dependent on the solar zenith angle of the ionospheric stations. Furthermore, a solar-zenith-angle-dependent enhancement of the fmin (2–9 MHz) and dfmin (1–8 MHz) parameters was observed at almost every station. The fmin and dfmin parameters show an increasing trend with the enhancement of the X-ray flux. Based on our results, the dfmin parameter is a good qualitative measure for the relative variation of the “nondeviative” absorption, especially in the case of the less intense solar flares, which do not cause total radio fade-out in the ionosphere (class < M6).

Drivers of biases in the extratropical storm tracks in CMIP6

2020 ◽  
Author(s):  
Matthew Priestley ◽  
Duncan Ackerley ◽  
Jennifer Catto ◽  
Kevin Hodges ◽  
Ruth McDonald ◽  
...  
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Storm Track ◽  
Storm Tracks ◽  
Extratropical Cyclones ◽  
Ocean Coupling ◽  
Coupled Climate Models ◽  
The Mean ◽  
The Impact

&lt;p&gt;Extratropical cyclones are the leading driver of the day-to-day weather variability and wintertime losses for Europe. In the latest generation of coupled climate models, CMIP6, it is hoped that with improved modelling capabilities come improvements in the structure of the storm track and the associated cyclones. Using an objective cyclone identification and tracking algorithm the mean state of the storm tracks in the CMIP6 models is assessed as well as the representation of explosively deepening cyclones. Any developments and improvements since the previous generation of models in CMIP5 are discussed, with focus on the impact of model resolution on storm track representation. Furthermore, large-scale drivers of any biases are investigated, with particular focus on the role of atmosphere-ocean coupling via associated AMIP simulations and also the influence of large-scale dynamical and thermodynamical features.&lt;/p&gt;

Reconstruction of GRACE Total Water Storage Through Automated Machine Learning

2020 ◽  
Author(s):  
Alex Sun ◽  
Bridget Scanlon ◽  
Himanshu Save ◽  
Ashraf Rateb
Keyword(s):  
Machine Learning ◽  
Spatial Variability ◽  
Large Scale ◽  
Water Storage ◽  
Total Water ◽  
New Paradigm ◽  
Satellite Mission ◽  
Automated Machine Learning ◽  
The Mean ◽  
The Impact

&lt;p&gt;The GRACE satellite mission and its follow-on, GRACE-FO, have provided unprecedented opportunities to quantify the impact of climate extremes and human activities on total water storage at large scales. The approximately one-year data gap between the two GRACE missions needs to be filled to maintain data continuity and maximize mission benefits. There is strong interest in using machine learning (ML) algorithms to reconstruct GRACE-like data to fill this gap. So far, most studies attempted to train and select a single ML algorithm to work for global basins. However, hydrometeorological predictors may exhibit strong spatial variability which, in turn, may affect the performance of ML models. Existing studies have already shown that no single algorithm consistently outperformed others over all global basins. In this study, we applied an automated machine learning (AutoML) workflow to perform GRACE data reconstruction. AutoML represents a new paradigm for optimal model structure selection, hyperparameter tuning, and model ensemble stacking, addressing some of the most challenging issues related to ML applications. We demonstrated the AutoML workflow over the conterminous U.S. (CONUS) using six types of ML algorithms and multiple groups of meteorological and climatic variables as predictors. Results indicate that the AutoML-assisted gap filling achieved satisfactory performance over the CONUS. For the testing period (2014/06&amp;#8211;2017/06), the mean gridwise Nash-Sutcliffe efficiency is around 0.85, the mean correlation coefficient is around 0.95, and the mean normalized root-mean square error is about 0.09. Trained models maintain good performance when extrapolating to the mission gap and to GRACE-FO periods (after 2017/06). Results further suggest that no single algorithm provides the best predictive performance over the entire CONUS, stressing the importance of using an end-to-end workflow to train, optimize, and combine multiple machine learning models to deliver robust performance, especially when building large-scale hydrological prediction systems and when predictor importance exhibits strong spatial variability.&lt;/p&gt;

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