Evidence Of Dynamical Coupling Between The Residual Layer And The Developing Convective Boundary Layer

Fochesatto, G. J.; Drobinski, P.; Flamant, Cyrille; Guédalia, D.; Sarrat, C.; Flamant, Pierre H.; Pelon, Jacques

doi:10.1023/a:1018935129006

Cited by 59 publications

(48 citation statements)

References 27 publications

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“…Over LIS, residual layers have frequently been found in summer months, when land-sea temperature contrasts are larger [41] and observed as reservoirs for boundary layer trace gas pollutants during air quality episodes along the East Coast [42]. In the study conducted here, data further suggested that the residual layer facilitated the long-range transport achieved by the plume through its advection into the lower troposphere and over the marine boundary layer, thus, detaching it from surface interactions in a similar fashion to that described by Dacre et al [15] and Fochesatto et al [43].…”

Section: Physical Structure Of the Plume Layersupporting

confidence: 85%

Meteorological Influences on Trace Gas Transport along the North Atlantic Coast during ICARTT 2004

et al. 2014

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An analysis of coastal meteorological mechanisms facilitating the transit pollution plumes emitted from sources in the Northeastern U.S. was based on observations from the International Consortium for Atmospheric Research on Transport and Transformation (ICARTT) 2004 field campaign. Particular attention was given to the relation of these plumes to coastal transport patterns in lower tropospheric layers throughout the Gulf of Maine (GOM), and their contribution to large-scale pollution outflow from the North American continent. Using measurements obtained during a series of flights of the National Oceanic & Atmospheric Administration (NOAA) WP-3D and the National Aeronautics and Space Administration (NASA) DC-8, a unique quasi-Lagrangian case study was conducted for a freshly emitted plume emanating from the New York City source region in late July 2004. The development of this plume stemmed from the OPEN ACCESSAtmosphere 2014, 5 974 accumulation of boundary layer pollutants within a coastal residual layer, where weak synoptic conditions allowed for its advection into the marine troposphere and transport by a mean southwesterly flow. Upon entering the GOM, analysis showed that the plume layer vertical structure evolved into an internal boundary layer form, with signatures of steep vertical gradients in temperature, moisture and wind speed often resulting in periodic turbulence. This structure remained well-defined during the plume study, allowing for the detachment of the plume layer from the surface and minimal plume-sea surface exchange. In contrast, shear driven turbulence within the plume layer facilitated lateral mixing with other low-level plumes during its transit. This turbulence was periodic and further contributed to the high spatial variability in trace gas mixing ratios. Further influences of the turbulent mixing were observed in the impact of the plume inland as observed by the Atmospheric Investigation, Regional Modeling, Analysis and Prediction (AIRMAP) air quality network. This impact was seen as extreme elevations of surface ozone and CO levels, equaling the highest observed that summer.

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Section: Physical Structure Of the Plume Layersupporting

confidence: 85%

Meteorological Influences on Trace Gas Transport along the North Atlantic Coast during ICARTT 2004

et al. 2014

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“…These features, together with an evening pulse in traffic and biofuel emissions for heating and cooking (Rehman et al, 2011), cause PM 2.5 abundances to reach their maximum at around 21:00 LT. PM 2.5 abundances decrease through the night, likely due to a drop off in emissions as all other meteorological variables would suggest further PM 2.5 increases. Abundances begin to increase about an hour before the ∼ 07:00 sunrise and a short-lived secondary maximum occurs at around 09:00 LT. Part of this increase may be driven by emissions (e.g., cold engine starts and morning traffic); however, Nair et al (2007) attribute the rise mostly to fumigation (Stull, 1988;Fochesatto et al, 2001), i.e., thermals that break up the nighttime inversion layer and mix aerosols trapped in the residual layer down to the surface.…”

Section: Seasonal and Diurnal Cyclesmentioning

confidence: 99%

Exploring the relationship between surface PM<sub>2.5</sub> and meteorology in Northern India

et al. 2018

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Abstract. Northern India (23)(24)(25)(26)(27)(28)(29)(30)(31) • N, 68-90 • E) is one of the most densely populated and polluted regions in world. Accurately modeling pollution in the region is difficult due to the extreme conditions with respect to emissions, meteorology, and topography, but it is paramount in order to understand how future changes in emissions and climate may alter the region's pollution regime. We evaluate the ability of a developmental version of the new-generation NOAA GFDL Atmospheric Model, version 4 (AM4) to simulate observed wintertime fine particulate matter (PM 2.5 ) and its relationship to meteorology over Northern India. We compare two simulations of GFDL-AM4 nudged to observed meteorology for the period 1980-2016 driven by pollutant emissions from two global inventories developed in support of the Coupled Model Intercomparison Project Phases 5 (CMIP5) and 6 (CMIP6), and compare results with ground-based observations from India's Central Pollution Control Board (CPCB) for the period 1 October 2015-31 March 2016. Overall, our results indicate that the simulation with CMIP6 emissions produces improved concentrations of pollutants over the region relative to the CMIP5-driven simulation.While the particulate concentrations simulated by AM4 are biased low overall, the model generally simulates the magnitude and daily variability of observed total PM 2.5 . Nitrate and organic matter are the primary components of PM 2.5 over Northern India in the model. On the basis of correlations of the individual model components with total observed PM 2.5 and correlations between the two simulations, meteorology is the primary driver of daily variability. The model correctly reproduces the shape and magnitude of the seasonal cycle of PM 2.5 , but the simulated diurnal cycle misses the early evening rise and secondary maximum found in the observations. Observed PM 2.5 abundances are by far the highest within the densely populated IndoGangetic Plain, where they are closely related to boundary layer meteorology, specifically relative humidity, wind speed, boundary layer height, and inversion strength. The GFDL AM4 model reproduces the overall observed pollution gradient over Northern India as well as the strength of the meteorology-PM 2.5 relationship in most locations.

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“…The gradual buildup of the morning [BC] is attributed to the combined effects of fumigation effect (Stull, 1998;Fochesatto et al, 2001;Beegum et al, 2009) of the boundary layer (the so-called fumigation effect) and a morning increase in anthropogenic activities (Safai et al, 2007;Kumar et al, 2011) in a rural environment as the observation site is surrounded by villages, industries and agricultural fields. The sampling location basically as rural; however, this is not really the case.…”

Section: Diurnal Variations Of Bc Mass Concentrationmentioning

confidence: 99%

Potential Source Regions Contributing to Seasonal Variations of Black Carbon Aerosols over Anantapur in Southeast India

Reddy

Kumar

Balakrishnaiah

et al. 2012

Aerosol Air Qual. Res.

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Continuous measurements of black carbon (BC) mass concentration performed at Anantapur [14. 62°N, 77.65°E, 331 m asl], a suburban location in southeast India, using an Aethalometer from January to December, 2010, are analyzed and discussed here. The annual mean BC mass concentration ([BC]) was 3.03 ± 0.27 µg/m 3 for the above study period. The sharp morning (fumigation) peak occurs between 07:00 and 08:00 h almost an hour after the local sunrise while a broad evening (nocturnal) peak is at ~21:00 h with a minimum in noon hours (14:00-16:00 h). The seasonal mean values of [BC] are 5.05 ± 0.51 μg/m 3 in the winter, 3.77 ± 1.23, 1.55 ± 0.51, and 2.33 ± 0.82 µg/m 3 in the summer, monsoon and postmonsoon seasons, respectively. High BC values tend to occur when the wind is directed from the 180-225° sector, which may be well defined by the geographical location of the observation site. During the winter, the trajectory air mass pathways originated through north or central India with significant advection of continental aerosols arriving before the measurement region, results in an enhanced [BC]. Whereas in the monsoon season, the pristine marine air mass from the oceanic environment led to decrease in the concentration of BC. Comparison of monthly mean variations in AOD at 500 nm and black carbon aerosols is observed to be positive with poor correlation coefficient of 0.42. The ratio of BC/PM 2.5 varied from 1.3% to 7.2% with a mean value of 4.6% at Anantapur during the observation period and this ratio decreased with decreasing Ångström exponent (alpha).

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Evidence Of Dynamical Coupling Between The Residual Layer And The Developing Convective Boundary Layer

Cited by 59 publications

References 27 publications

Meteorological Influences on Trace Gas Transport along the North Atlantic Coast during ICARTT 2004

Meteorological Influences on Trace Gas Transport along the North Atlantic Coast during ICARTT 2004

Exploring the relationship between surface PM<sub>2.5</sub> and meteorology in Northern India

Potential Source Regions Contributing to Seasonal Variations of Black Carbon Aerosols over Anantapur in Southeast India

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Evidence Of Dynamical Coupling Between The Residual Layer And The Developing Convective Boundary Layer

Cited by 59 publications

References 27 publications

Meteorological Influences on Trace Gas Transport along the North Atlantic Coast during ICARTT 2004

Meteorological Influences on Trace Gas Transport along the North Atlantic Coast during ICARTT 2004

Exploring the relationship between surface PM&lt;sub&gt;2.5&lt;/sub&gt; and meteorology in Northern India

Potential Source Regions Contributing to Seasonal Variations of Black Carbon Aerosols over Anantapur in Southeast India

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Exploring the relationship between surface PM<sub>2.5</sub> and meteorology in Northern India