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Luke Ziemba

Publications and source records attributed to Luke Ziemba.

At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2024

Stratospheric Air Intrusions Promote Global-Scale New Particle Formation

New particle formation in the free troposphere is a major source of cloud condensation nuclei globally. The prevailing view is that in the free troposphere, new particles are formed predominantly in convective cloud outflows. We present another mechanism using global observations. We find that during stratospheric air intrusion events, the mixing of descending ozone-rich stratospheric air with more moist free tropospheric background results in elevated hydroxyl radical (OH) concentrations. Such mixing is most prevalent near the tropopause where the sulfur dioxide (SO 2 ) mixing ratios are high. The combination of elevated SO 2 and OH levels leads to enhanced sulfuric acid concentrations, promoting particle formation. Such new particle formation occurs frequently and over large geographic regions, representing an important particle source in the midlatitude free troposphere.

Jiaoshi Zhang↗
NASA NTRS2022

An Evaluation of Biomass Burning Aerosol Mass, Extinction, and Size Distribution in Geos Using Observations From Camp2EX

Biomass burning aerosol impacts aspects of the atmosphere and Earth system through radiative forcing, serving as cloud condensation nuclei, and air quality. Despite its importance, the representation of biomass burning aerosol is not always accurate in numerical weather prediction and climate models or reanalysis products. Using observations collected as part of the Cloud, Aerosol and Monsoon Processes Philippines Experiment (CAMP2Ex) in August through October of 2019, aerosol concentration and optical properties are evaluated within the Goddard Earth Observing System (GEOS) and its underlying aerosol module, GOCART. In the operational configuration, GEOS assimilates aerosol optical depth observations at 550 nm to constrain aerosol fields. Particularly for biomass burning aerosol, without the assimilation of aerosol optical depth, aerosol extinction is underestimated compared to observations collected in the Philippines region during the CAMP2Ex campaign. The assimilation process adds excessive amounts of carbon to account for the underestimated extinction, resulting in positive biases in the mass of black and organic carbon, especially within the boundary layer, relative to in situ observations from the Langley Aerosol Research Group Experiment. Counteracting this, GEOS is deficient in sulphate and nitrate aerosol just above the boundary layer. Aside from aerosol mass, extinction within GEOS is a function of ambient relative humidity and an assumed particle size distribution. The relationship between dry and ambient extinction in GEOS reveals that hygroscopic growth is too aggressive within the model for biomass burning aerosol. An additional concern lies in the assumed particle size distribution for GEOS, which has a mode radius that is too small for organic carbon. Variability in the observed particle size distribution for biomass burning aerosol within a single flight also illuminates the fact that a single assumed particle size distribution is not sufficient and that for a proper representation, a more advanced aerosol module with GEOS may be necessary.

Aerosol Mass↗
NASA NTRS2022

Remote Sensing of Aerosol Water Fraction, Dry Size Distribution and Soluble Fraction Using Multi-Angle, Multi-Spectral Polarimetry

A framework to infer volume water fraction, soluble fraction and dry size distributions of fine-mode aerosol from multi-angle, multi-spectral polarimetry retrievals of column-averaged ambient aerosol properties is presented. The method is applied to observations of the Research Scanning Polarimeter (RSP) obtained during two NASA aircraft campaigns, namely the Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) and the Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP2Ex). All aerosol retrievals are statistically evaluated using in situ data. Volume water fraction is inferred from the retrieved ambient real part of the refractive index, assuming a dry refractive index of 1.54 and by applying a volume mixing rule to obtain the effective ambient refractive index. The uncertainties in inferred volume water fraction resulting from this simplified model are discussed and estimated to be lower than 0.2 and decreasing with increasing volume water fraction. The daily mean retrieved volume water fractions correlate well with the in situ values with a mean absolute difference of 0.09. Polarimeter-retrieved ambient effective radius for daily data is shown to increase as a function of volume water fraction as expected. Furthermore, the effective variance of the size distributions also increases with increasing effective radius, which we show is consistent with an external mixture of soluble and insoluble aerosol. The relative variations of effective radius and variance over an observation period are then used to estimate the soluble fraction of the aerosol. Daily results of soluble fraction correlate well with in situ-observed sulfate mass fraction with a correlation coefficient of 0.79. Subsequently, inferred water and soluble fractions are used to derive dry fine-mode size distributions from their ambient counterparts. While dry effective radii obtained in situ and from RSP show similar ranges, in situ values are generally substantially smaller during the ACTIVATE deployments, which may be due to biases in RSP retrievals or in the in situ observations, or both. Both RSP and in situ observations indicate the dominance of aerosol with low hygroscopicity during the ACTIVATE and CAMP2Ex campaigns. Furthermore, RSP indicates a high degree of external mixing of particles with low and high hygroscopicity. These retrievals of fine-mode water volume fraction and soluble fraction may be used for the evaluation of water uptake in atmospheric models. Furthermore, the framework allows us to estimate the variation in the concentration of fine-mode aerosol larger than a specific dry radius limit, which can be used as a proxy for the variation in cloud condensation nucleus concentrations. This framework may be applied to multi-angle, multi-spectral satellite data expected to be available in the near future.

Amount of water in particulate matter↗
NASA NTRS2022

Remote Sensing of Aerosol Water Fraction, Dry Size Distribution and Soluble Fraction Using Multi-Angle, Multi-Spectral Polarimetry

A framework to infer volume water fraction, soluble fraction and dry size distributions of fine mode aerosol from multi-angle, multi-spectral polarimetry retrievals of column-averaged ambient aerosol properties is presented. The method is applied to observations of the Research Scanning Polarimeter (RSP) obtained during two NASA aircraft campaigns, namely the Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) and the Cloud, Aerosol, and Monsoon Processes-Philippines Experiment (CAMP2Ex). All aerosol retrievals are statistically evaluated using in situ data. Volume water fraction is inferred from the retrieved ambient real part of the refractive index, assuming a dry refractive index of 1.54 and by applying a volume mixing rule to obtain the effective ambient refractive index. The uncertainties in inferred volume water fraction resulting from this simplified model are discussed and estimated to be lower than 0.2 and decreasing with increasing volume water fraction. The daily mean retrieved volume water fractions correlate well with the in situ values with a mean absolute difference of 0.09. Polarimeter-retrieved ambient effective radius for daily data is shown to increase as a function of volume water fraction as expected. Furthermore, the effective variance of the size distributions also increases with increasing effective radius, which we show is consistent with an external mixture of soluble and insoluble aerosol. The relative variations of effective radius and variance over an observation period are then used to estimate the soluble fraction of the aerosol. Daily results of soluble fraction correlate well with in situ observed sulfate mass fraction with a correlation coefficient of 0.79. Subsequently, inferred water and soluble fractions are used to derive dry fine-mode size distributions from their ambient counterparts. While dry effective radii obtained in situ and from RSP show similar ranges, in situ values are generally substantially smaller during the ACTIVATE deployments, which may be due to biases in RSP retrievals or in the in situ observations, or both. Both RSP and in situ observations indicate the dominance of aerosol with low hygroscopicity during the ACTIVATE and CAMP2Ex campaigns. Furthermore, RSP indicates a high degree of external mixing of particles with low and high hygroscopicity. These retrievals of fine mode water volume fraction and soluble fraction may be used for the evaluation of water uptake in atmospheric models. Furthermore, the framework allows to estimate the variation in the concentration of fine-mode aerosol larger than a specific dry radius limit, which can be used as a proxy for the variation in cloud condensation nucleus concentrations. This framework may be applied to multi-angle, multi-spectral satellite data expected to be available in the near future.

Bastiaan Van Diedenhoven↗
NASA NTRS2022

The Impact of Sampling Strategy on the Cloud Droplet Number Concentration Estimated From Satellite Data

Cloud droplet number concentration (Nd) is of central importance to observation-based estimates of aerosol indirect effects, being used to quantify both the cloud sensitivity to aerosol and the base state of the cloud. However, the derivation of Nd from satellite data depends on a number of assumptions about the cloud and the accuracy of the retrievals of the cloud properties from which it is derived, making it prone to systematic biases. A number of sampling strategies have been proposed to address these biases by selecting the most accurate Nd retrievals in the satellite data. This work compares the impact of these strategies on the accuracy of the satellite retrieved Nd, using a selection of in situ measurements. In stratocumulus regions, the MODIS Nd retrieval is able to achieve a high precision (r2 of 0.5–0.8). This is lower in other cloud regimes but can be increased by appropriate sampling choices. Although the Nd sampling can have significant effects on the Nd climatology, it produces only a 20 % variation in the implied radiative forcing from aerosol–cloud interactions, with the choice of aerosol proxy driving the overall uncertainty. The results are summarised into recommendations for using MODIS Nd products and appropriate sampling.

Edward Gryspeerdt↗
NASA NTRS2022

Polarimeter + Lidar–Derived Aerosol Particle Number Concentration

In this study, we propose a simple method to derive vertically resolved aerosol particle number concentration (Na) using combined polarimetric and lidar remote sensing observations. This method relies on accurate polarimeter retrievals of the fine-mode column-averaged aerosol particle extinction cross section and accurate lidar measurements of vertically resolved aerosol particle extinction coefficient such as those provided by multiwavelength high spectral resolution lidar. We compare the resulting lidar + polarimeter vertically resolved N(a) product to in situ N(a) data collected by airborne instruments during the NASA aerosol cloud meteorology interactions over the western Atlantic experiment (ACTIVATE). Based on all 35 joint ACTIVATE flights in 2020, we find a total of 32 collocated in situ and remote sensing profiles that occur on 11separate days, which contain a total of 322 cloud-free vertically resolved altitude bins of 150 m resolution. We demonstrate that the lidar + polarimeter N(a) agrees to within 106% for 90% of the 322 vertically resolved points. We also demonstrate similar agreement to within 121% for the polarimeter-derived column-averaged N(a). We find that the range-normalized mean absolute deviation (NMAD) for the polarimeter-derived column-averaged Na is 21%, and the NMAD for the lidar + polarimeter-derived vertically resolved Na is 16%. Taken together, these findings suggest that the error in the polarimeter-only column-averaged N(a) and the lidar + polarimeter vertically resolved N(a) are of similar magnitude and represent a significant improvement upon current remote sensing estimates of N(a).

RSP↗
NASA NTRS2022

Identifying Chemical Aerosol Signatures Using Optical Suborbital Observations: How Much Can Optical Properties Tell us about Aerosol Composition?

Improvements in air quality and Earth’s climate predictions require improvements of the aerosol speciation in chemical transport models, using observational constraints. Aerosol speciation (e.g., organic aerosols, black carbon, sulfate, nitrate, ammonium, dust or sea salt) is typically determined using in situ instrumentation. Continuous, routine surface network aerosol composition measurements are not uniformly widespread over the globe. Satellites, on the other hand, can provide a maximum coverage of the horizontal and vertical atmosphere but observe aerosol optical properties (and not aerosol speciation) based on remote sensing instrumentation. Combinations of satellite-derived aerosol optical properties can inform on air mass aerosol types (AMTs e.g., clean marine, dust, polluted continental). However, these AMTs are subjectively defined, might often be misclassified and are hard to relate to the critical parameters that need to be refined in models. In this paper, we derive AMTs that are more directly related to sources and hence to speciation. They are defined, characterized, and derived using simultaneous in situ gas-phase, chemical and optical instruments on the same aircraft during the Study of Emissions and Atmospheric Composition, Clouds, and Climate Coupling by Regional Surveys (SEAC4RS, US, summer of 2013). First, we prescribe well-informed AMTs that display distinct aerosol chemical and optical signatures to act as a training AMT dataset. These in situ observations reduce the errors and ambiguities in the selection of the AMT training dataset. We also investigate the relative skill of various combinations of aerosol optical properties to define AMTs and how much these optical properties can capture dominant aerosol speciation. We find distinct optical signatures for biomass burning (from agricultural or wildfires), biogenic and dust-influence AMTs. Useful aerosol optical properties to characterize these signatures are the extinction angstrom exponent (EAE), the single scattering albedo, the difference of single scattering albedo in two wavelengths, the absorption coefficient, the absorption angstrom exponent (AAE), and the real part of the refractive index (RRI). We find that all four AMTs studied when prescribed using mostly airborne in situ gas measurements, can be successfully extracted from at least three combinations of airborne in situ aerosol optical properties (e.g., EAE, AAE and RRI) over the US during SEAC4RS. However, we find that the optically based classifications for BB from agricultural fires and polluted dust include a large percentage of misclassifications that limit the usefulness of results relating to those classes. The technique and results presented in this study are suitable to develop a representative, robust and diverse source-based AMT database. This database could then be used for widespread retrievals of AMTs using existing and future remote sensing suborbital instruments/networks. Ultimately, it has the potential to provide a much broader observational aerosol data set to evaluate chemical transport and air quality models than is currently available by direct in situ measurements. This study illustrates how essential it is to explore existing airborne datasets to bridge chemical and optical signatures of different AMTs, before the implementation of future spaceborne missions (e.g., the next generation of Earth Observing System (EOS) satellites addressing Aerosol, Cloud, Convection and Precipitation (ACCP) designated observables).

Meloe S F Kacenelenbogen↗
NASA NTRS2021

On Assessing ERA5 and MERRA2 Representations of Cold-Air Outbreaks Across the Gulf Stream

The warm Gulf Stream sea surface temperatures (SSTs) strongly impact the evolution of winter clouds behind atmospheric cold fronts. Such cloud evolution remains challenging to model. The Gulf Stream is too wide within the ERA5 and MERRA2 reanalyses, affecting the turbulent surface fluxes. Known problems within the ERA5 boundary layer (too-dry and too-cool with too strong westerlies), ascertained primarily from ACTIVATE 2020 campaign aircraft dropsondes and secondarily from older buoy measurements, reinforce surface flux biases. In contrast, MERRA2 winter surface winds and air-sea temperature/humidity differences are slightly too weak, producing surface fluxes that are too low. Reanalyses boundary layer heights in the strongly-forced winter cold-air-outbreak regime are realistic, whereas late-summer quiescent stable boundary layers are too shallow. Nevertheless, the reanalysis biases are small, and reanalyses adequately support their use for initializing higher-resolution cloud process modeling studies of cold-air outbreaks.

Gulf stream↗
NASA NTRS2018

Retrievals of Cloud Droplet Size from the Research Scanning Polarimeter Data: Validation Using In Situ Measurements

We present comparisons of cloud droplet size distributions (DSDs) retrieved from the research scanning polarimeter (RSP) data with correlative in situ measurements made during the North Atlantic Aerosols and Marine Ecosystems Study (NAAMES). The airborne portion of this field experiment was based out of St. John's airport, Newfoundland, Canada with the focus of this paper being on the deployment in May - June 2016. RSP was onboard the NASA C-130 aircraft together with an array of in situ and other remote sensing instrumentation. The RSP is an along-track scanner measuring the polarized and total reflectance in 9 spectral channels. Its uniquely high angular resolution allows for characterization of liquid water droplet sizes using the rainbow structure observed in the polarized reflectance over the scattering angle range from 135 to 165.degrees The rainbow is dominated by single scattering of light by cloud droplets, so its structure is characteristic specifically of the droplet sizes at cloud top (within unit optical depth into the cloud, equivalent to approximately 50m). A parametric fitting algorithm applied to the polarized reflectance provides retrievals of the droplet effective radius and variance assuming a prescribed size distribution shape (gamma distribution). In addition to this, we use a non-parametric method, the Rainbow Fourier Transform (RFT), which allows us to retrieve the droplet size distribution itself. The latter is important in the case of clouds with complex microphysical structure, or multiple layers of cloud, which result in multi-modal DSDs. During NAAMES the aircraft performed a number of flight patterns specifically designed for comparisons between remote sensing retrievals and in situ measurements. These patterns consisted of two flight segments above the same straight ground track. One of these segments was flown above clouds allowing for remote sensing measurements, while the other was near the cloud top where cloud droplets were sampled. We compare the DSDs retrieved from the RSP data with in situ measurements made by the Cloud Droplet Probe (CDP). The comparisons generally show good agreement (better than 1 micron for effective radius and in most cases better than 0.02 for effective variance) with deviations explainable by the position of the aircraft within the cloud, or by the presence of additional cloud layers between the cloud being sampled by the in situ instrumentation and the altitude of the remote sensing segment. In the latter case, the multi-modal DSDs retrieved from the RSP data were consistent with the multi-layer cloud structures observed in the correlative High Spectral Resolution Lidar (HSRL) profiles. The results of these comparisons provide a rare validation of polarimetric droplet size retrieval techniques, demonstrating their accuracy and robustness and the potential of satellite data of this kind on a global scale.

Remote Sensing↗
NASA NTRS2015

TPSAS-NF1676L-22701-DND

The next generation of aerosol satellite instruments will include multi-spectral polarimetric measurements to retrieval aerosol size distribution and refractive index (Hasekamp et al., 2011; NRC, 2007). Refractive index is the “only means of constraining aerosol chemical composition from space” for passive sensors (Mischenko et al., 2007). A number of methods have been developed to derive refractive index from combined optical and electrical mobility sizing instruments (e.g., the “Alignment Method” of Hand and Kreidenweis, 2002). In this work, we evaluate the sensitivity of two, commercially-available, high-resolution optical particle counters for determining the size-resolved refractive index of laboratory-generated aerosols when used with a modified form of the Alignment Method.

Stephen Zimmerman↗
NASA NTRSDate not supplied

TPSAS-NF1676L-33032-DND

The North Atlantic Aerosols and Marine Ecosystems Study (NAAMES; http://naames.larc.nasa.gov) is a five-year NASA Earth-Venture Suborbital-2 Mission to characterize the plankton ecosystems and their influences on remote marine aerosols, boundary layer clouds, and their implications for climate in the North Atlantic. While marine-sourced aerosols have been shown to make important contributions to surface aerosol loading, cloud condensation nuclei and ice nuclei concentrations over remote marine and coastal regions, it is still a challenge to differentiate the marine biogenic aerosol signal from the strong influence of continental pollution outflow. The objectives of this study are to determine the major transport pathways for North American pollution outflow to the North Atlantic, and to quantify the terrestrial and marine sources of aerosols during NAAMES using ground, ship, aircraft, and remote sensing observations in conjunction with a state-of-the-art global 3-D chemical transport model (GEOS-Chem). This poster presents an initial evaluation of GEOS-Chemfor the periods of NAAMES campaigns #1 (Nov. 2015) and #2 (May 2016).

Hongyu Liu↗
NASA NTRSDate not supplied

TPSAS-NF1676L-32084-DND

We present aerosol and cloud observations obtained from the satellite-, aircraft- and ship-based measurements of the North Atlantic Aerosols and Marine Ecosystems Study (NAAMES). The data span three seasons (November 2015, May 2016, and September 2017), which correspond to substantial variation in ocean ecosystem characteristics, continental long-range transport, and local aerosol-cloud microphysics and meteorology. For example, below-cloud aerosol number concentrations in November 2015 were of order 10-50 cm-3, while concentrations observed in May and September were of order 100-500 cm-3. Here, we focus on 20 cloud sampling flight modules carried out during NAAMES, which encompass approximately 27 flight hours of the more than 220 NAAMES project flight hours. The nominal cloud module pattern consists of a series of 5-6 vertically-stacked, horizontal flight legs of 10-15 minute duration (~50-90 km in length) that profile the near-surface (300 ft. altitude) and below-cloud aerosol characteristics, the cloud properties near cloud base and top, the aerosol properties above cloud, and finally a high-altitude remote sensing leg that characterizes the cloud top and above-cloud atmosphere. Ship-based aerosol and ceilometer measurements provide the below-cloud context over time, while GOES satellite imagery and cloud retrieval products fill in the above-cloud story.

Richard H Moore↗
NASA NTRSDate not supplied

TPSAS-NF1676L-21952-DND

DISCOVER-AQ was a 4-year NASA project aimed to improve the interpretation of total column satellite observations to help diagnose near-surface conditions relating to air quality. During DISCOVER-AQ HSRL-2 was flown onboard the NASA Langley B200 King Air. A suite of in-situ instruments was flown onboard NASA Wallops P-3B aircraft which spiraled up and down over a number of ground stations. The two aircraft flew coordinated flight tracks, both flying over several designated ground stations with close time coincidence, allowing for colocation of measurements from the in situ instruments suite and the HSRL-2. HSRL-2 is the first multiwavelength airborne lidar system that provides profiles of 3β (backscatter)+2α(extinction),allowing the retrieval of microphysical parameters like number, surface-area, and volume concentrations, and effective radius.

Patricia Sawamura↗
NASA NTRSDate not supplied

TPSAS-NF1676L-23266-DND

Currently, near-surface air quality information (e.g. PM_2.5) must be inferred from column-integrated quantities (i.e. Aerosol Optical Thickness – AOT) obtained by passive remote sensing from downward-looking satellite instruments. Such retrievals must address the following questions: What do we use for the height of the aerosols? Mixed Layer (ML) height? Can we assume that near-surface aerosol extinction is about the same as the mean aerosol extinction in the ML? How well is near-surface extinction related to surface PM_2.5? How well can column AOT be used to infer near-surface aerosol extinction and PM_2.5?

Richard Ferrare↗
NASA NTRSDate not supplied

Airborne High Spectral Resolution Lidar-2 Measurements of Enhanced Depolarization in Marine Aerosols

Airborne NASA Langley Research Center (LaRC) High Spectral Resolution Lidar-2 (HSRL-2) measurements acquired during the recent NASA EVS-3 Aerosol Cloud Meteorology Interactions over the Western Atlantic Experiment (ACTIVATE) revealed enhanced particulate linear depolarization associated with aerosols within the marine boundary layer. These HSRL-2 observations were acquired off the east coast of the United States in February and March 2020 when this lidar was deployed on the NASA LaRC UC-12 aircraft. HSRL-2 measured profiles of aerosol backscattering, extinction,and depolarization at 355 and 532nm and aerosol backscattering and depolarization at 1064nm. Typically HSRL-2 measures low (<5%) linear particulate depolarization associated with marine sea salt aerosols. However, during several ACTIVATE flights, particularly those that occurred with outbreaks of cold, dry air, linear particulate depolarization exceeded 15-20% (532nm) for aerosols within a few hundred meters above the surface. These high values indicated that these particles were nonspherical. Elevated depolarization values were also observed at 355 and 1064 nm. HSRL-2 measured aerosol extinction/backscatter ratio (“lidar ratio”) values around 20-25 sr (355 and 532 nm) that are typically associated with sea salt particles. Coincident measurements of relative humidity from dropsondes released from the UC-12and in situ Diode Laser Hygrometer (DLH) measurements flown on the NASA HU-25 aircraft showed that highest depolarization values of these nonspherical particles were found when the relative humidity (RH)was below 50-60%.These lidar observations of elevated depolarization associated with sea salt aerosol are consistent with previous lidar measurements of sea salt aerosols in dry conditions. We discuss these HSRL-2 measurements also in the context of coincident airborne in situ measurements of particle size and composition acquired on the HU-25 aircraft. We also found that CALIOP satellite measurements observed elevated depolarization during some similar cold air outbreaks. In such cases, the operational CALIOP algorithms attributed the elevated depolarization to nonspherical dust particles rather than the more likely scenario of nonspherical sea salt particles associated with low RH.

aerosols↗