Fundamentals of Atmospheric Modeling

Jacobson, Mark Z.

doi:10.1017/cbo9781139165389

Cited by 897 publications

(940 citation statements)

References 591 publications

Supporting

Mentioning

890

Contrasting

Unclassified

Order By: Relevance

“…Organic particles are also unstable under the electron beam (Egerton et al 2004). Nanoparticle tracking analysis (NTA) is expected to have a progressively reducing efficiency of detection of particles, particularly smaller than 50-100 nm, as light scattering efficiency of smaller particles declines (Jacobson 2005). Particle detection efficiency also fluctuates depending on their physicochemical nature, which influences how efficiently they scatter light.…”

Section: Introductionmentioning

confidence: 99%

Novel aerosol analysis approach for characterization of nanoparticulate matter in snow

Nazarenko

Rangel-Alvarado

Kos

et al. 2016

Environ Sci Pollut Res

View full text Add to dashboard Cite

Tropospheric aerosols are involved in several key atmospheric processes: from ice nucleation, cloud formation, and precipitation to weather and climate. The impact of aerosols on these atmospheric processes depends on the chemical and physical characteristics of aerosol particles, and these characteristics are still largely uncertain. In this study, we developed a system for processing and aerosolization of melted snow in particle-free air, coupled with a real-time measurement of aerosol size distributions. The newly developed technique involves bringing snow-borne particles into an airborne state, which enables application of high-resolution aerosol analysis and sampling techniques. This novel analytical approach was compared to a variety of complementary existing analytical methods as applied for characterization of snow samples from remote sites in Alert (Canada) and Barrow (USA), as well as urban Montreal (Canada). The dry aerosol measurements indicated a higher abundance of particles of all sizes, and the 30 nm size dominated in aerosol size distributions for the Montreal samples, closely followed by Barrow, with about 30% fewer 30 nm particles, and about four times lower 30 nm particle abundance in Alert samples, where 15 nm particles were most abundant instead. The aerosolization technique, used together with nanoparticle tracking analysis and electron microscopy, allowed measurement of a wide size range of snow-borne particles in various environmental snow samples. Here, we discuss the application of the new technique to achieve better physicochemical understanding of atmospheric and snow processes. The results showed high sensitivity and reduction of particle aggregation, as well as the ability to measure a high-resolution snow-borne particle size distribution, including nanoparticulate matter in the range of 10 to 100 nm.

show abstract

Section: Introductionmentioning

confidence: 99%

Novel aerosol analysis approach for characterization of nanoparticulate matter in snow

Nazarenko

Rangel-Alvarado

Kos

et al. 2016

Environ Sci Pollut Res

View full text Add to dashboard Cite

show abstract

“…In addition, although the satellite imagery used in this study was obtained with minimized cloud effect, the residual cloud cover might still weaken the insolation dramatically. For these reasons, LST retrieved from such satellite imagery consequently suffers from the uncertainties in further data preprocessing and calculation (Benali et al, 2012;Jacobson, 2000).…”

Section: Uncertainties and Opportunitiesmentioning

confidence: 99%

Spatiotemporally characterizing urbantemperatures based on remote sensing and GISanalysis: a case study in the city of Saskatoon(SK, Canada)

Shen

Guo

Kang³

2014

Open Geosciences

View full text Add to dashboard Cite

Abstract:The purpose of this study is to spatiotemporally explore the characteristics of urban temperatures based on multi-temporal satellite data and historical in situ measurements. As one of the most rapidly urbanized cities in Canada, Saskatoon (SK) was selected as our study area. Surface brightness retrieving, Pearson correlation, linear regression modeling, and buffer analysis were applied to different satellite datasets. The results indicate that both Landsat and MODIS data can yield pronounced estimations of daily air temperature with a significantly adjusted R 2 of 0.803 and 0.518 at the spatial scales of 120 m and 1000 m, respectively. MODIS monthly LST data is highly suitable for monitoring the trend of monthly urban air temperature throughout summer (June, July, and August) due to a high average R 2 of 0.8 (P<0.05), especially for the warmest month (July). Our findings also reveal that both the Saskatchewan River and urban green spaces have statistically significant cooling effects on the surrounding urban surface temperatures within 500 m and 200 m, respectively. In addition, a multiple linear regression model with four influential factors as independent variables can be developed to estimate urban surface temperatures with a highest adjusted R 2 of 0.649 and a lowest standard error of 0.076.

show abstract

“…The phenomenon is most accentuated within the surface layer extending upto 50 m -300 m, depending on the location. At higher altitudes, however, horizontal wind flow pre-dominates the convection phenomenon and Kolmogorov statistics can be applied satisfactorily 17 .…”

Section: Introductionmentioning

confidence: 99%

Study of Wavefront Tilt Variance with Various Telescope Apertures in Indoor Convective Turbulence

et al. 2018

View full text Add to dashboard Cite

Turbulent atmosphere produces random wavefront tilts in the propagating laser beam and the dynamics of turbulence largely depends on the receiving optics aperture size. In this paper, wavefront tilt variance is studied with various telescope aperture sizes in indoor convective turbulence. A simple experimental setup is described for simulating the near ground atmospheric turbulence by generating different strengths of convective turbulence in the laboratory. A laser beam is made to propagate through the turbulence subsequently induced wavefront tilt variances are experimentally measured and analysed statistically. The wavefront tilt variance is used to estimate the temporal characteristics using Fourier transform by varying aperture sizes and turbulence strengths (i.e. ambient, weak and moderate). The Hurst exponent, the Fried parameter and the wavefront tilt frequencies for the different turbulence strengths are calculated. The power dependence of the wavefront tilt variance on the telescope aperture size is studied and a deviation from the classical D -1/3 dependence is reported.

show abstract

Fundamentals of Atmospheric Modeling

Cited by 897 publications

References 591 publications

Novel aerosol analysis approach for characterization of nanoparticulate matter in snow

Novel aerosol analysis approach for characterization of nanoparticulate matter in snow

Spatiotemporally characterizing urbantemperatures based on remote sensing and GISanalysis: a case study in the city of Saskatoon(SK, Canada)

Study of Wavefront Tilt Variance with Various Telescope Apertures in Indoor Convective Turbulence

Contact Info

Product

Resources

About