A climatology of cloud chemistry for the eastern United States derived from the mountain cloud chemistry project

1993 ◽  
Vol 1 (1) ◽  
pp. 38-54 ◽  
Author(s):  
Volker A. Mohnen ◽  
Richard J. Vong
Keyword(s):  
United States ◽  
Chemical Composition ◽  
Chemical Analysis ◽  
Cloud Water ◽  
Cloud Base ◽  
Eastern United States ◽  
Cloud Chemistry ◽  
Air Mass ◽  
Ion Concentrations ◽  
Air Mass Trajectories

The chemical composition of clouds collected in the eastern United States has been intensely monitored over a 4-year period as part of the Mountain Cloud Chemistry Project. On the basis of these measurements we prepared a climatology for cloud chemistry, using simple statistical analyses tools and incorporating meteorological and cloud physical and chemical information. Five mountain stations have been established for cloud collection covering the northern and southern Appalachian Mountain range: Whiteface Mountain, New York; Mount Moosilauke, New Hampshire; Shenandoah Mountain, Virginia; Whitetop Mountain, Virginia; and Mount Mitchell, North Carolina. This review presents the major result from this 4-year measurement program. Cloud cover and cloud base over the eastern United States were deduced from the global real-time nephanalysis archives produced by the U.S. Air Force, augmented by local observations. Both active and passive cloud collectors were deployed to sample cloud water on an hourly basis, i.e., with sufficient time resolution to resolve synoptic scale phenomena. Chemical analysis of cloud water was performed by a central analytical laboratory with occasional on-site analysis to satisfy quality control procedures. Reliable methods now exist for collecting cloud-water samples in sufficient quantities for detailed chemical analysis. The chemical composition of cloud water varied significantly between sites. However, the differences in cloud-water ion concentration do not necessarily establish a geographic gradient between the sites but rather reflect differences in air-mass trajectories associated with the synoptic air-flow pattern and differences in sample location above cloud base. The dependence of cloud-water ion concentrations on synoptic weather type and observed differences in relative frequencies of warm sector, marine flow, and post-cold frontal synoptic types between northern and southern sites suggest that the north–south differences in cloud-water ion concentrations are related to cloud climatology at the northern sites. When air-mass trajectories shift from southwest to northwest, the concentrations of H+, SO42−, NO3− and NH4+ normally decrease but the southern sites continue to receive high concentrations under northwest flow. The height of cloud-water sample collection above cloud base was found to be an additional source of variability in both cloud-water chemistry and liquid-water content. Seasonal variation in cloud-water chemical composition was investigated at one site only. Sulfate levels were found to be significantly lower in supercooled clouds (i.e., during the 'cold' season) than in 'warm' clouds, but nitrate levels remained about the same.Key words: cloud chemistry, cloud frequency, air-mass trajectories, ANOVA.

Trends in cloud water sulfate and nitrate as measured at two mountain sites in the Eastern United States:

2006 ◽  
Vol 40 (23) ◽  
pp. 4423-4437 ◽  
Author(s):  
James B. Anderson ◽  
Ralph E. Baumgardner ◽  
Sandra E. Grenville
Keyword(s):  
United States ◽  
Cloud Water ◽  
Eastern United States

scholarly journals Quantification of the effect of modeled lightning NO<sub>2</sub> on UV–visible air mass factors

2017 ◽  
Vol 10 (11) ◽  
pp. 4403-4419 ◽  
Author(s):  
Joshua L. Laughner ◽  
Ronald C. Cohen
Keyword(s):  
United States ◽  
A Priori ◽  
Early Summer ◽  
Lightning Flash ◽  
Eastern United States ◽  
Ozone Monitoring Instrument ◽  
Reanalysis Dataset ◽  
Near Surface ◽  
Air Mass ◽  
Convective Clouds

Abstract. Space-borne measurements of tropospheric nitrogen dioxide (NO2) columns are up to 10x more sensitive to upper tropospheric (UT) NO2 than near-surface NO2 over low-reflectivity surfaces. Here, we quantify the effect of adding simulated lightning NO2 to the a priori profiles for NO2 observations from the Ozone Monitoring Instrument (OMI) using modeled NO2 profiles from the Weather Research and Forecasting–Chemistry (WRF-Chem) model. With observed NO2 profiles from the Deep Convective Clouds and Chemistry (DC3) aircraft campaign as observational truth, we quantify the bias in the NO2 column that occurs when lightning NO2 is not accounted for in the a priori profiles. Focusing on late spring and early summer in the central and eastern United States, we find that a simulation without lightning NO2 underestimates the air mass factor (AMF) by 25 % on average for common summer OMI viewing geometry and 35 % for viewing geometries that will be encountered by geostationary satellites. Using a simulation with 500 to 665 mol NO flash−1 produces good agreement with observed NO2 profiles and reduces the bias in the AMF to  <  ±4 % for OMI viewing geometries. The bias is regionally dependent, with the strongest effects in the southeast United States (up to 80 %) and negligible effects in the central US. We also find that constraining WRF meteorology to a reanalysis dataset reduces lightning flash counts by a factor of 2 compared to an unconstrained run, most likely due to changes in the simulated water vapor profile.

scholarly journals Can the GPM IMERG Final Product Accurately Represent MCSs’ Precipitation Characteristics over the Central and Eastern United States?

2020 ◽  
Vol 21 (1) ◽  
pp. 39-57 ◽  
Author(s):  
Wenjun Cui ◽  
Xiquan Dong ◽  
Baike Xi ◽  
Zhe Feng ◽  
Jiwen Fan
Keyword(s):  
United States ◽  
False Alarm ◽  
Stage Iv ◽  
Cloud Base ◽  
Eastern United States ◽  
Convective Systems ◽  
Precipitation Measurement ◽  
Precipitation Characteristics ◽  
Mesoscale Convective ◽  
Global Precipitation

AbstractMesoscale convective systems (MCSs) play an important role in water and energy cycles as they produce heavy rainfall and modify the radiative profile in the tropics and midlatitudes. An accurate representation of MCSs’ rainfall is therefore crucial in understanding their impact on the climate system. The V06B Integrated Multisatellite Retrievals from Global Precipitation Measurement (IMERG) half-hourly precipitation final product is a useful tool to study the precipitation characteristics of MCSs because of its global coverage and fine spatiotemporal resolutions. However, errors and uncertainties in IMERG should be quantified before applying it to hydrology and climate applications. This study evaluates IMERG performance on capturing and detecting MCSs’ precipitation in the central and eastern United States during a 3-yr study period against the radar-based Stage IV product. The tracked MCSs are divided into four seasons and are analyzed separately for both datasets. IMERG shows a wet bias in total precipitation but a dry bias in hourly mean precipitation during all seasons due to the false classification of nonprecipitating pixels as precipitating. These false alarm events are possibly caused by evaporation under the cloud base or the misrepresentation of MCS cold anvil regions as precipitating clouds by the algorithm. IMERG agrees reasonably well with Stage IV in terms of the seasonal spatial distribution and diurnal cycle of MCSs precipitation. A relative humidity (RH)-based correction has been applied to the IMERG precipitation product, which helps reduce the number of false alarm pixels and improves the overall performance of IMERG with respect to Stage IV.

scholarly journals A high-resolution and observationally constrained OMI NO<sub>2</sub> satellite retrieval

2017 ◽  
Author(s):  
Daniel L. Goldberg ◽  
Lok N. Lamsal ◽  
Christopher P. Loughner ◽  
Zifeng Lu ◽  
David G. Streets
Keyword(s):  
United States ◽  
High Resolution ◽  
Urban Areas ◽  
Vertical Profile ◽  
Model Simulation ◽  
New Product ◽  
Eastern United States ◽  
Shape Factors ◽  
Air Mass ◽  
Tropospheric No2

Abstract. This work presents a new high resolution NO2 dataset derived from the standard NASA Ozone Monitoring Instrument (OMI) NO2 version 3.0 retrieval that can be used to estimate surface level concentrations. The standard NASA product uses NO2 vertical profile shape factors from a 1.25° × 1° (~ 110 × 110 km) resolution Global Model Initiative (GMI) model simulation to calculate air mass factors, a critical value used to determine observed tropospheric NO2 vertical columns. To better estimate vertical profile shape factors, we use a high resolution Community Multi-scale Air Quality (CMAQ) model simulation (1.33 × 1.33 km) to generate tropospheric air mass factors and tropospheric NO2 columns during summertime in the eastern United States. Results show OMI NO2 tropospheric columns in this new product increase by up to 160 % in city centers, and decrease by 20–50 % in the rural areas outside of urban areas when compared to the operational product. This new product shows much better agreement with the Pandora NO2 spectrometer measurements acquired during the DISCOVER-AQ Maryland field campaign. Furthermore, the correlation between this satellite product and EPA NO2 monitors in urban areas has improved dramatically: r2 = 0.60 in new product, r2 = 0.39 in operational product, signifying that this new product is a better indicator of surface concentrations than the operational product. Our work emphasizes the need to use high resolution models to re-calculate satellite data in areas with large spatial heterogeneities in NOx emissions. Although the current work is focused on the eastern United States, the methodology developed in this work can be applied to other world regions to produce high-quality region-specific NO2 satellite retrievals.

scholarly journals On the relationship between cloud water composition and cloud droplet number concentration

2020 ◽  
Vol 20 (13) ◽  
pp. 7645-7665 ◽  
Author(s):  
Alexander B. MacDonald ◽  
Ali Hossein Mardi ◽  
Hossein Dadashazar ◽  
Mojtaba Azadi Aghdam ◽  
Ewan Crosbie ◽  
...  
Keyword(s):  
Chemical Composition ◽  
Environmental Factors ◽  
Cloud Droplet ◽  
Cloud Water ◽  
Number Concentration ◽  
Sea Salt ◽  
Cloud Base ◽  
Cloud Height ◽  
Cloud Droplet Number Concentration ◽  
Total Sulfate

Abstract. Aerosol–cloud interactions are the largest source of uncertainty in quantifying anthropogenic radiative forcing. The large uncertainty is, in part, due to the difficulty of predicting cloud microphysical parameters, such as the cloud droplet number concentration (Nd). Even though rigorous first-principle approaches exist to calculate Nd, the cloud and aerosol research community also relies on empirical approaches such as relating Nd to aerosol mass concentration. Here we analyze relationships between Nd and cloud water chemical composition, in addition to the effect of environmental factors on the degree of the relationships. Warm, marine, stratocumulus clouds off the California coast were sampled throughout four summer campaigns between 2011 and 2016. A total of 385 cloud water samples were collected and analyzed for 80 chemical species. Single- and multispecies log–log linear regressions were performed to predict Nd using chemical composition. Single-species regressions reveal that the species that best predicts Nd is total sulfate (Radj2=0.40). Multispecies regressions reveal that adding more species does not necessarily produce a better model, as six or more species yield regressions that are statistically insignificant. A commonality among the multispecies regressions that produce the highest correlation with Nd was that most included sulfate (either total or non-sea-salt), an ocean emissions tracer (such as sodium), and an organic tracer (such as oxalate). Binning the data according to turbulence, smoke influence, and in-cloud height allowed for examination of the effect of these environmental factors on the composition–Nd correlation. Accounting for turbulence, quantified as the standard deviation of vertical wind speed, showed that the correlation between Nd with both total sulfate and sodium increased at higher turbulence conditions, consistent with turbulence promoting the mixing between ocean surface and cloud base. Considering the influence of smoke significantly improved the correlation with Nd for two biomass burning tracer species in the study region, specifically oxalate and iron. When binning by in-cloud height, non-sea-salt sulfate and sodium correlated best with Nd at cloud top, whereas iron and oxalate correlated best with Nd at cloud base.

scholarly journals On the Relationship Between Cloud Water Composition and Cloud Droplet Number Concentration

2020 ◽  
Author(s):  
Alexander B. MacDonald ◽  
Ali Hossein Mardi ◽  
Hossein Dadashazar ◽  
Mojtaba Azadi Aghdam ◽  
Ewan Crosbie ◽  
...  
Keyword(s):  
Chemical Composition ◽  
Environmental Factors ◽  
Cloud Droplet ◽  
Cloud Water ◽  
Number Concentration ◽  
Sea Salt ◽  
Cloud Base ◽  
Cloud Height ◽  
Cloud Droplet Number Concentration ◽  
Total Sulfate

Abstract. Aerosol-cloud interactions are the largest source of uncertainty in quantifying anthropogenic radiative forcing. The large uncertainty is, in part, due to the difficulty of predicting cloud microphysical parameters, such as the cloud droplet number concentration (Nd). Even though rigorous first-principle approaches exist to calculate Nd, the cloud and aerosol research community also relies on empirical approaches such as relating Nd to aerosol mass concentration. Here we analyze relationships between Nd and cloud water chemical composition, in addition to the effect of environmental factors on the degree of the relationships. Warm, marine, stratocumulus clouds off the California coast were sampled throughout four summer campaigns between 2011 and 2016. A total of 385 cloud water samples were collected and analyzed for 79 chemical species. Single- and multi-species log-log linear regressions were performed to predict Nd using chemical composition. Single-species regressions reveal that the species that best predicts Nd is total sulfate (R2adj = 0.40). Multi-species regressions reveal that adding more species does not necessarily produce a better model, as six or more species yield regressions that are statistically insignificant. A commonality among the multi-species regressions that produce the highest correlation with Nd was that most included sulfate (either total or non-sea salt), an ocean emissions tracer (such as sodium), and an organic tracer (such as oxalate). Binning the data according to turbulence, smoke influence, and in-cloud height allowed examination of the effect of these environmental factors on the composition-Nd correlation. Accounting for turbulence, quantified as the standard deviation of vertical wind speed, showed that the correlation between Nd with both total sulfate and sodium increased at higher turbulence conditions, consistent with turbulence promoting the mixing between ocean surface and cloud base. Considering the influence of smoke significantly improved the correlation with Nd for two biomass burning tracer species in the study region, specifically oxalate and iron. When binning by in-cloud height, non-sea salt sulfate and sodium correlated best with Nd at cloud top, whereas iron and oxalate correlate best with Nd at cloud base.

scholarly journals Insights into tropical cloud chemistry in Réunion (Indian Ocean): results from the BIO-MAÏDO campaign

2022 ◽  
Vol 22 (1) ◽  
pp. 505-533
Author(s):  
Pamela A. Dominutti ◽  
Pascal Renard ◽  
Mickaël Vaïtilingom ◽  
Angelica Bianco ◽  
Jean-Luc Baray ◽  
...  
Keyword(s):  
Amino Acids ◽  
Organic Matter ◽  
Chemical Composition ◽  
Aqueous Phase ◽  
Cloud Water ◽  
Sea Salt ◽  
Emission Sources ◽  
Air Mass ◽  
Low Solubility

Abstract. We present here the results obtained during an intensive field campaign conducted in the framework of the French “BIO-MAÏDO” (Bio-physico-chemistry of tropical clouds at Maïdo (Réunion Island): processes and impacts on secondary organic aerosols' formation) project. This study integrates an exhaustive chemical and microphysical characterization of cloud water obtained in March–April 2019 in Réunion (Indian Ocean). Fourteen cloud samples have been collected along the slope of this mountainous island. Comprehensive chemical characterization of these samples is performed, including inorganic ions, metals, oxidants, and organic matter (organic acids, sugars, amino acids, carbonyls, and low-solubility volatile organic compounds, VOCs). Cloud water presents high molecular complexity with elevated water-soluble organic matter content partly modulated by microphysical cloud properties. As expected, our findings show the presence of compounds of marine origin in cloud water samples (e.g. chloride, sodium) demonstrating ocean–cloud exchanges. Indeed, Na+ and Cl− dominate the inorganic composition contributing to 30 % and 27 %, respectively, to the average total ion content. The strong correlations between these species (r2 = 0.87, p value: < 0.0001) suggest similar air mass origins. However, the average molar Cl-/Na+ ratio (0.85) is lower than the sea-salt one, reflecting a chloride depletion possibly associated with strong acids such as HNO3 and H2SO4. Additionally, the non-sea-salt fraction of sulfate varies between 38 % and 91 %, indicating the presence of other sources. Also, the presence of amino acids and for the first time in cloud waters of sugars clearly indicates that biological activities contribute to the cloud water chemical composition. A significant variability between events is observed in the dissolved organic content (25.5 ± 18.4 mg C L−1), with levels reaching up to 62 mg C L−1. This variability was not similar for all the measured compounds, suggesting the presence of dissimilar emission sources or production mechanisms. For that, a statistical analysis is performed based on back-trajectory calculations using the CAT (Computing Atmospheric Trajectory Tool) model associated with the land cover registry. These investigations reveal that air mass origins and microphysical variables do not fully explain the variability observed in cloud chemical composition, highlighting the complexity of emission sources, multiphasic transfer, and chemical processing in clouds. Even though a minor contribution of VOCs (oxygenated and low-solubility VOCs) to the total dissolved organic carbon (DOC) (0.62 % and 0.06 %, respectively) has been observed, significant levels of biogenic VOC (20 to 180 nmol L−1) were detected in the aqueous phase, indicating the cloud-terrestrial vegetation exchange. Cloud scavenging of VOCs is assessed by measurements obtained in both the gas and aqueous phases and deduced experimental gas-/aqueous-phase partitioning was compared with Henry's law equilibrium to evaluate potential supersaturation or unsaturation conditions. The evaluation reveals the supersaturation of low-solubility VOCs from both natural and anthropogenic sources. Our results depict even higher supersaturation of terpenoids, evidencing a deviation from thermodynamically expected partitioning in the aqueous-phase chemistry in this highly impacted tropical area.

Chemical analysis of 617 coal samples from the Eastern United States

1979 ◽  
Author(s):  
Peter Zubovic ◽  
Charles L. Oman ◽  
S.L. Coleman ◽  
Linda Bragg ◽  
P.T. Kerr ◽  
...  
Keyword(s):  
United States ◽  
Chemical Analysis ◽  
Eastern United States
Sign in / Sign up

Export Citation Format

Share Document