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NASA NTRSDate not supplied

Airborne Remote Sensing Measurements of Particles in Different Parts of the World

Around the globe, atmospheric aerosols pose a significant yet uncertain impact on the Earth's climate, environmental air quality and human health. Suborbital sunphotometer measurements of Aerosol Optical Depth (AOD) (i.e., the amount of direct-beam solar light attenuated by aerosols within the atmospheric column) are used to validate satellite aerosol retrievals and are valuable when studying aerosol-solar radiation and/ or aerosol-cloud interactions. Since 1985, NASA Ames Research Center (ARC) has been using airborne sun-tracking sunphotometers to measure atmospheric constituents such as aerosols, clouds, and gases. The NASA Ames Airborne Tracking Sunphotometer (AATS-6) and then (AATS-14) operate by tracking the sun and measuring the transmission of solar radiation in 6 to 14 discrete spectral channels (Russell et al., 1986). The AATS systems were followed by the more advanced hyperspectral 4STAR instrument (Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research; Dunagan et al., 2013), which combines the airborne sun-tracking capability of the AATS-14 with a sky scanning feature similar to the ground-based Aerosol Robotic Network Sun/sky photometers (AERONET). We present a comprehensive analysis of ~30 airborne campaigns undertaken by NASA and DoE based on a new database of airborne sunphotometer measurements. Using this database, we present a clear picture of airborne AODs over the range of historical campaigns and the aerosol sizes per region, especially over the ocean where AERONET data is limited. With this database, we can investigate systematic differences in AOD such as those observed over different land and ocean surfaces in specific geographical regions. Finally, we will briefly show comparisons with satellite aerosol retrievals from MODIS and/or VIIRS. Russell, P. B., T. Matsumoto, V. J. Banta, J. M. Livingston, C. Mina, D. S. Colburn, and R. F. Pueschel (1986), Measurements with an airborne, autotracking, external-head sunphotometer, Preprint Volume, Sixth Conference on Atmospheric Radiation, May 13–16, 1986, Amer. Meteor.Soc., Boston, MA, 55–58. Dunagan, Stephen E., et al. "Spectrometer for sky-scanning sun-tracking atmospheric research (4STAR): Instrument technology." Remote Sensing 5.8 (2013): 3872-3895

Brendan Stover Cornelison↗
NASA NTRS2012

Constraining Aerosol Optical Models Using Ground-Based, Collocated Particle Size and Mass Measurements in Variable Air Mass Regimes During the 7-SEAS/Dongsha Experiment

During the spring of 2010, NASA Goddard's COMMIT ground-based mobile laboratory was stationed on Dongsha Island off the southwest coast of Taiwan, in preparation for the upcoming 2012 7-SEAS field campaign. The measurement period offered a unique opportunity for conducting detailed investigations of the optical properties of aerosols associated with different air mass regimes including background maritime and those contaminated by anthropogenic air pollution and mineral dust. What appears to be the first time for this region, a shortwave optical closure experiment for both scattering and absorption was attempted over a 12-day period during which aerosols exhibited the most change. Constraints to the optical model included combined SMPS and APS number concentration data for a continuum of fine and coarse-mode particle sizes up to PM2.5. We also take advantage of an IMPROVE chemical sampler to help constrain aerosol composition and mass partitioning of key elemental species including sea-salt, particulate organic matter, soil, non sea-salt sulphate, nitrate, and elemental carbon. Our results demonstrate that the observed aerosol scattering and absorption for these diverse air masses are reasonably captured by the model, where peak aerosol events and transitions between key aerosols types are evident. Signatures of heavy polluted aerosol composed mostly of ammonium and non sea-salt sulphate mixed with some dust with transitions to background sea-salt conditions are apparent in the absorption data, which is particularly reassuring owing to the large variability in the imaginary component of the refractive indices. Extinctive features at significantly smaller time scales than the one-day sample period of IMPROVE are more difficult to reproduce, as this requires further knowledge concerning the source apportionment of major chemical components in the model. Consistency between the measured and modeled optical parameters serves as an important link for advancing remote sensing and climate research studies in dynamic aerosol-rich environments like Dongsha.

Bell, Shaun W.↗
NASA NTRS1992

Influence of atmospheric aerosols and desert reflectance properties on satellite radiance measurements

The influence of surface bidirectional reflectance factors, including shadowing, and of atmospheric aerosol variability are modeled for their effects on the remote sensing of desert targets from space in the 0.7-micron region at high spatial resolution. The white sand reflectance data of Salomonson (1968) are used as the basis for the simulation. The effects of the surface bi-directional reflectance and atmospheric aerosol on the nadir-normalized reflectance measured at the satellite are discussed individually and jointly. The net influence of these two factors is shown to depend on the magnitude of other parameters, such as the surface reflectance and solar zenith angle.

Bowker, D. E.↗
NASA NTRS2022

Circular Polarization in Atmospheric Aerosols

Recent technological advances have demonstrated the feasibility of deploying spaceborne optical detectors with full polarimetric capabilities. The measurement of all four Stokes coefficients opens significant new opportunities for atmospheric aerosol studies and applications. While considerable amounts of attention have been dedicated to sensors with sensitivity to the total intensity and linear polarization (represented by Stokes coefficients I, U, Q), there has been less attention to the additional information brought by measuring circular polarization (coefficient V). This report fills this gap in knowledge by providing an overview of aerosol sources of circular polarization in the atmosphere and discusses possible remote sensing signatures. In this manuscript, circularly polarized radiation that results from the interaction of incident unpolarized radiation are considered in three physical settings: optical activity originating in biogenic aerosols, alignment of non-spherical particles in the presence of electrical fields (such as dust, smoke, and volcanic ash) and aerosol multiple scattering effects. Observational and theoretical evidence of, and the settings and conditions for non-zero aerosol circular polarization generated from incident unpolarized radiation are here gathered and discussed. In addition, novel radiative transfer simulations are shown to illustrate notable spectral and other features where circular polarization may provide additional information that is possibly independent from total intensity and linear polarization only observations. Current techniques for detection of aerosol composition (also referred as aerosol type) from space provide limited information. Remote identification of aerosols such as smoke, volcanic ash, and dust particles can only be accomplished with some degree of confidence for moderate to high concentrations. When the same aerosols are found at lower concentrations (but still high enough to be of importance for air quality and cloud formation), these methods often produce ambiguous results. The circular polarization of aerosols is rarely utilized, and we explore its value for improved determination aerosol composition. This study is presented as an overview with a goal to provide a new perspective on an overlooked optical property and to trigger interest in further exploration of this subject.

Aerosol type↗
DOE OSTI2022

The COMBLE campaign: a study of marine boundary-layer clouds in Arctic cold-air outbreaks

One of the most intense air mass transformations on Earth happens when cold air flows from frozen surfaces to much warmer open water in cold-air outbreaks (CAOs), a process captured beautifully in satellite imagery. Despite the ubiquity of the CAO cloud regime over high-latitude oceans, we have a rather poor understanding of its properties, its role in energy and water cycles, and its treatment in weather and climate models. The Cold-air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) was conducted to better understand this regime and its representation in models. COMBLE aimed to examine the relations between surface fluxes, boundary-layer structure, aerosol, cloud and precipitation properties, and mesoscale circulations in marine CAOs. Processes affecting these properties largely fall in a range of scales where boundary-layer processes, convection, and precipitation are tightly coupled, which makes accurate representation of the CAO cloud regime in numerical weather prediction and global climate models most challenging. COMBLE deployed an Atmospheric Radiation Measurement Mobile Facility at a coastal site in northern Scandinavia (69°N), with additional instruments on Bear Island (75°N), from December 2019 to May 2020. CAO conditions were experienced 19% (21%) of the time at the main site (on Bear Island). A comprehensive suite of continuous in situ and remote sensing observations of atmospheric conditions, clouds, precipitation, and aerosol were collected. Because of the clouds’ well-defined origin, their shallow depth, and the broad range of observed temperature and aerosol concentrations, the COMBLE dataset provides a powerful modeling test bed for improving the representation of mixed-phase cloud processes in large-eddy simulations and large-scale models.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2011

Remote Sensing the Vertical Profile of Cloud Droplet Effective Radius, Thermodynamic Phase, and Temperature

Cloud-aerosol interaction is a key issue in the climate system, affecting the water cycle, the weather, and the total energy balance including the spatial and temporal distribution of latent heat release. Information on the vertical distribution of cloud droplet microphysics and thermodynamic phase as a function of temperature or height, can be correlated with details of the aerosol field to provide insight on how these particles are affecting cloud properties and their consequences to cloud lifetime, precipitation, water cycle, and general energy balance. Unfortunately, today's experimental methods still lack the observational tools that can characterize the true evolution of the cloud microphysical, spatial and temporal structure in the cloud droplet scale, and then link these characteristics to environmental factors and properties of the cloud condensation nuclei. Here we propose and demonstrate a new experimental approach (the cloud scanner instrument) that provides the microphysical information missed in current experiments and remote sensing options. Cloud scanner measurements can be performed from aircraft, ground, or satellite by scanning the side of the clouds from the base to the top, providing us with the unique opportunity of obtaining snapshots of the cloud droplet microphysical and thermodynamic states as a function of height and brightness temperature in clouds at several development stages. The brightness temperature profile of the cloud side can be directly associated with the thermodynamic phase of the droplets to provide information on the glaciation temperature as a function of different ambient conditions, aerosol concentration, and type. An aircraft prototype of the cloud scanner was built and flew in a field campaign in Brazil.

Martins, J. V.↗
NASA NTRS2010

Identifying Aerosol Type/Mixture from Aerosol Absorption Properties Using AERONET

Aerosols are generated in the atmosphere through anthropogenic and natural mechanisms. These sources have signatures in the aerosol optical and microphysical properties that can be used to identify the aerosol type/mixture. Spectral aerosol absorption information (absorption Angstrom exponent; AAE) used in conjunction with the particle size parameterization (extinction Angstrom exponent; EAE) can only identify the dominant absorbing aerosol type in the sample volume (e.g., black carbon vs. iron oxides in dust). This AAE/EAE relationship can be expanded to also identify non-absorbing aerosol types/mixtures by applying an absorption weighting. This new relationship provides improved aerosol type distinction when the magnitude of absorption is not equal (e.g, black carbon vs. sulfates). The Aerosol Robotic Network (AERONET) data provide spectral aerosol optical depth and single scattering albedo - key parameters used to determine EAE and AAE. The proposed aerosol type/mixture relationship is demonstrated using the long-term data archive acquired at AERONET sites within various source regions. The preliminary analysis has found that dust, sulfate, organic carbon, and black carbon aerosol types/mixtures can be determined from this AAE/EAE relationship when applying the absorption weighting for each available wavelength (Le., 440, 675, 870nm). Large, non-spherical dust particles absorb in the shorter wavelengths and the application of 440nm wavelength absorption weighting produced the best particle type definition. Sulfate particles scatter light efficiently and organic carbon particles are small near the source and aggregate over time to form larger less absorbing particles. Both sulfates and organic carbon showed generally better definition using the 870nm wavelength absorption weighting. Black carbon generation results from varying combustion rates from a number of sources including industrial processes and biomass burning. Cases with primarily black carbon showed improved definition in the 870nm wavelength absorption weighting due to the increased absorption in the near-infrared wavelengths, while the 440nm wavelength provided better definition when black carbon mixed with dust. Utilization of this particle type scheme provides necessary information for remote sensing applications, which needs a priori knowledge of aerosol type to model the retrieved properties especially over semi-bright surfaces. In fact, this analysis reveals that the aerosol types occurred in mixtures with varying magnitudes of absorption and requires the use of more than one assumed aerosol mixture model. Furthermore, this technique will provide the aerosol transport model community a data set for validating aerosol type.

Giles, D. M.↗
DOE OSTI2023

Biomass-burning smoke's properties and its interactions with marine stratocumulus clouds in WRF-CAM5 and southeastern Atlantic field campaigns

Abstract. A large part of the uncertainty in climate projections comes from uncertain aerosol properties and aerosol–cloud interactions as well as the difficulty in remotely sensing them. The southeastern Atlantic functions as a natural laboratory to study biomass-burning smoke and to constrain this uncertainty. We address these gaps by comparing the Weather Research and Forecasting with Chemistry Community Atmosphere Model (WRF-CAM5) to the multi-campaign observations ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS), CLARIFY (CLoud–Aerosol–Radiation Interaction and Forcing), and LASIC (Layered Atlantic Smoke Interactions with Clouds) in the southeastern Atlantic in August 2017 to evaluate a large range of the model's aerosol chemical properties, size distributions, processes, and transport, as well as aerosol–cloud interactions. Overall, while WRF-CAM5 is able to represent smoke properties and transport, some key discrepancies highlight the need for further analysis. Observations of smoke composition show an overall decrease in aerosol mean diameter as smoke ages over 4–12 d, while the model lacks this trend. A decrease in the mass ratio of organic aerosol (OA) to black carbon (BC), OA:BC, and the OA mass to carbon monoxide (CO) mixing ratio, OA:CO, suggests that the model is missing processes that selectively remove OA from the particle phase, such as photolysis and heterogeneous aerosol chemistry. A large (factor of ∼2.5) enhancement in sulfate from the free troposphere (FT) to the boundary layer (BL) in observations is not present in the model, pointing to the importance of properly representing secondary sulfate aerosol formation from marine dimethyl sulfide and gaseous SO2 smoke emissions. The model shows a persistent overprediction of aerosols in the marine boundary layer (MBL), especially for clean conditions, which multiple pieces of evidence link to weaker aerosol removal in the modeled MBL than reality. This evidence includes several model features, such as not representing observed shifts towards smaller aerosol diameters, inaccurate concentration ratios of carbon monoxide and black carbon, underprediction of heavy rain events, and little evidence of persistent biases in modeled entrainment. The average below-cloud aerosol activation fraction (NCLD/NAER) remains relatively constant in WRF-CAM5 between field campaigns (∼0.65), while it decreases substantially in observations from ORACLES (∼0.78) to CLARIFY (∼0.5), which could be due to the model misrepresentation of clean aerosol conditions. WRF-CAM5 also overshoots an observed upper limit on liquid cloud droplet concentration around NCLD= 400–500 cm−3 and overpredicts the spread in NCLD. This could be related to the model often drastically overestimating the strength of boundary layer vertical turbulence by up to a factor of 10. We expect these results to motivate similar evaluations of other modeling systems and promote model development to reduce critical uncertainties in climate simulations.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

25 Years of CALIPSO

Selected for development in 1998 and launched together with CloudSat in 2006, the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations(CALIPSO) mission terminated science operations in the summer of 2023 aftercompleting17 years of on-orbit observations. As one of NASA’s Earth System Science Pathfinder missions, CALIPSO was truly a pathfinder. CALIPSO observations have provided a new perspective on clouds and aerosol and have not only met but far exceeded the original objectives of the mission. Many unanticipated findings and data applications have been discovered along the way. Fly-ing with many other remote sensing instruments, as part of the A-train constellation, stimulated the discovery of numerous retrieval synergies between lidar and other sensors. This paper describes how the CALIPSO mission came to be, discusses some of the early choices made by the CALIPSO team that shaped the mission, and some of the challenges facing the team in developing the first-ever global climatologies of aerosol and cloud based on lidar observations.

Space lidar↗
NASA NTRS2021

A Machine Learning Approach to Objective Identification of Dust in Satellite Imagery

Airborne dust has broad adverse effects on human activity, including aviation, human health, and agriculture. Remote sensing observations are used to detect dust and aerosols in the atmosphere using long established techniques. False color Red-Green-Blue (RGB) imagery using band differences sensitive to dust absorption (Dust RGB) is currently used operationally to assist forecasters and decision-makers in identifying dust at night, but there are still limitations, subjectivity, and nuances to image interpretation making night-time dust identification difficult even for experts. This study applies machine learning to the problem of night-time dust detection with a simple random forest (RF) model using Geostationary Operational Environmental Satellite-16 (GOES-16) Advanced Baseline Imager (ABI) infrared imagery, band differences sensitive to dust absorption, and Dust RGB color components as inputs to the model. The RF model achieves an Area-Under-Curve (AUC) of 0.97 with a standard deviation of 0.04 for dust cases. For images with dust present, the model correctly labels 85% of dust pixels and 99.96% of no-dust pixels for all dust images in the validation data set. The addition of a single null case to the training data set drastically reduces error in labeling no-dust pixels as dust from 45% to 14.5%. Application of the machine learning model to the April 13–14, 2019 dust event demonstrates the ability of the model to identify dust during night-time hours when visual dust detection is limited by the cooling ground surface characteristics.

dust↗
NASA NTRS2017

Quantifying the Causes of Differences in Tropospheric OH Within Global Models

The hydroxyl radical (OH) is the primary daytime oxidant in the troposphere and provides the main loss mechanism for many pollutants and greenhouse gases, including methane (CH4). Global mean tropospheric OH differs by as much as 80% among various global models, for reasons that are not well understood. We use neural networks (NNs), trained using archived output from eight chemical transport models (CTMs) that participated in the Polar Study using Aircraft, Remote Sensing, Surface Measurements and Models, of Climate, Chemistry, Aerosols and Transport Model Intercomparison Project (POLMIP), to quantify the factors responsible for differences in tropospheric OH and resulting CH4 lifetime (Tau CH4) between these models. Annual average Tau CH4, for loss by OH only, ranges from 8.0 to 11.6 years for the eight POLMIP CTMs. The factors driving these differences were quantified by inputting 3-D chemical fields from one CTM into the trained NN of another CTM. Across all CTMs, the largest mean differences in Tau CH4 (Delta Tau CH4) result from variations in chemical mechanisms (Delta Tau CH4 = 0.46 years), the photolysis frequency (J) of O3 yields O(D-1) (0.31 years), local O3 (0.30 years), and CO (0.23 years). The Delta Tau CH4 due to CTM differences in NO(x) (NO + NO2) is relatively low (0.17 years), although large regional variation in OH between the CTMs is attributed to NO(x). Differences in isoprene and J(NO2) have negligible overall effect on globally averaged tropospheric OH, although the extent of OH variations due to each factor depends on the model being examined. This study demonstrates that NNs can serve as a useful tool for quantifying why tropospheric OH varies between global models, provided that essential chemical fields are archived.

Surface Measurements and Models↗
NASA NTRS2014

Performance Simulations for a Spaceborne Methane Lidar Mission

Future spaceborne lidar measurements of key anthropogenic greenhouse gases are expected to close current observational gaps particularly over remote, polar, and aerosol-contaminated regions, where actual in situ and passive remote sensing observation techniques have difficulties. For methane, a "Methane Remote Lidar Mission" was proposed by Deutsches Zentrum fuer Luft- und Raumfahrt and Centre National d'Etudes Spatiales in the frame of a German-French climate monitoring initiative. Simulations assess the performance of this mission with the help of Moderate Resolution Imaging Spectroradiometer and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations of the earth's surface albedo and atmospheric optical depth. These are key environmental parameters for integrated path differential absorption lidar which uses the surface backscatter to measure the total atmospheric methane column. Results showthat a lidar with an average optical power of 0.45W at 1.6 μm wavelength and a telescope diameter of 0.55 m, installed on a low Earth orbit platform(506 km), will measure methane columns at precisions of 1.2%, 1.7%, and 2.1% over land, water, and snow or ice surfaces, respectively, for monthly aggregated measurement samples within areas of 50 × 50 km2. Globally, the mean precision for the simulated year 2007 is 1.6%, with a standard deviation of 0.7%. At high latitudes, a lower reflectance due to snow and ice is compensated by denser measurements, owing to the orbital pattern. Over key methane source regions such as densely populated areas, boreal and tropical wetlands, or permafrost, our simulations show that the measurement precision will be between 1 and 2%.

methane↗
DOE OSTI2026

Pivotal Role of Cloud‐Planetary Boundary Layer Coupling to Explain Contrasting Aerosol‐Cloud Relationships

The radiative effect of aerosol on cloud albedo via altering cloud droplet effective radius (r e ) is a major uncertainty in the Earth's climate system. Remote sensing studies have reported either negative or positive relationships between re and aerosol number concentration (N a ) or other aerosol proxies. However, there are much fewer in situ observational evidences and physical explanation remains elusive for the contrasting N a -r e relationships. Here we quantify the N a -r e relationship by using in situ aircraft measurements, together with a re decomposition method. Our analysis reveals that the cloud-planetary boundary layer (PBL) coupling plays a pivotal role on the N a -r e relationship. Quantitative r e decomposition indicates that the contrasting N a -r e relationships in two cloud-PBL coupling regimes result from different balances of four distinct aspects. The widely recognized number effect may be outweighed by the joint effects of the remaining three that have been rarely investigated and largely ignored in N a -r e parameterizations.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1999

Remote Sensing of Smoke and its Direct Radiative Forcing in South-America

Smoke aerosol, organic and black carbon particles suspended in the air, are capable to absorb and reflect solar radiation to space - direct radiative forcing. Depending on the ratio of scattering to absorption, and on the surface spectral properties, the net smoke effect can be warming or cooling of the climate system. Data from the AVIRIS spectrometer flown on the ER-2 at altitude of 20 km, and of the AERONET ground based sun/sky radiometers are used to assess the smoke aerosol optical thickness over the land and the direct radiative forcing at the top of the atmosphere and at ground level, respectively. The data are collected during the SCAR-B experiment in Brazil. In contrast to model results of the smoke effect, we show using the AVIRIS data, that even though the surface albedo is high (0.17 - average on the solar spectrum) and the smoke single scattering albedo is low (0.88), smoke does increase the instantaneous reflectance of sunlight to space by 30-40 W/m(exp 2) for an increase in the smoke optical thickness of 0.5. The AERONET data are used to derive, simultaneously, the effect of smoke on the downward radiation. Models using spectrally averaged smoke optical properties and averaged surface reflectance, predicted very small smoke forcing. The reason is that smoke is mainly opaque in short wavelengths (e.g.< 0.7 micron) while the surface is mainly bright in longer wavelengths (> 0.7 micron). Modeling the effect of smoke on climate forcing cannot be done using the spectrally average properties. It requires the knowledge of the smoke and surface spectral properties.

Kaufman, Yoram↗
NASA NTRS2001

Satellite Remote Sensing of the Liquid Water Sensitivity in Water Clouds

In estimation of the aerosol indirect effect, cloud liquid water path is considered either constant (Twomey effect) or increasing with enhanced droplet number concentrations (drizzle-suppression effect, or Albrecht effect) if cloud microphysics is the prevailing mechanism during the aerosol-cloud interactions. On the other hand, if cloud thermodynamics and dynamics are considered, the cloud liquid water path may be decreased with increasing droplet number concentration, which is predicted by model calculations and observed in ship-track and urban influence studies. This study is to examine the different responses of cloud liquid water path to changes of cloud droplet number concentration. Satellite data (January, April, July and October 1987) are used to retrieve the cloud liquid water sensitivity, defined as the changes of liquid water path versus changes of column droplet number concentrations. The results of a global survey reveal that 1) in at least one third of the cases the cloud liquid water sensitivity is negative, and the regional and seasonal variations of the negative liquid water sensitivity are consistent with other observations; 2) cloud droplet sizes are always inversely proportional to column droplet number concentrations. Our results suggest that an increase of cloud droplet number concentration leads to reduced cloud droplet size and enhanced evaporation, which weakens the coupling between water clouds and boundary layer in warm zones, decreases water supply from surface and desiccates cloud liquid water. Our results also suggest that the current evaluations of negative aerosol indirect forcing by global climate models (GCM), which are based on Twomey effect or Albrecht effect, may be overestimated.

Han, Qing-Yuan↗
DOE OSTI2023

Evaluation of E3SM land model snow simulations over the western United States

Abstract. Seasonal snow has crucial impacts on climate, ecosystems, and humans, but it is vulnerable to global warming. The land component (ELM) of the Energy Exascale Earth System Model (E3SM) mechanistically simulates snow processes from accumulation, canopy interception, compaction, and snow aging to melt. Although high-quality field measurements, remote sensing snow products, and data assimilation products with high spatio-temporal resolution are available, there has been no systematic evaluation of the snow properties and phenology in ELM. This study comprehensively evaluates ELM snow simulations over the western United States at 0.125∘ resolution during 2001–2019 using the Snow Telemetry (SNOTEL) in situ networks, MODIS remote sensing products (i.e., MCD43 surface albedo product), the spatially and temporally complete (STC) snow-covered area and grain size (MODSCAG) and MODIS dust and radiative forcing in snow (MODDRFS) products (STC-MODSCAG/STC-MODDRFS), and the snow property inversion from remote sensing (SPIReS) product and two data assimilation products of snow water equivalent and snow depth – i.e., University of Arizona (UA) and SNOw Data Assimilation System (SNODAS). Overall the ELM simulations are consistent with the benchmarking datasets and reproduce the spatio-temporal patterns, interannual variability, and elevation gradients for different snow properties including snow cover fraction (fsno), surface albedo (αsur) over snow cover regions, snow water equivalent (SWE), and snow depth (Dsno). However, there are large biases of fsno with dense forest cover and αsur in the Rocky Mountains and Sierra Nevada in winter, compared to the MODIS products. There are large discrepancies of snow albedo, snow grain size, and light-absorbing particle-induced snow albedo reduction between ELM and the MODIS products, attributed to uncertainties in the aerosol forcing data, snow aging processes in ELM, and remote sensing retrievals. Against UA and SNODAS, ELM has a mean bias of −20.7 mm (−35.9 %) and −20.4 mm (−35.5 %), respectively, for spring, and −13.8 mm (−27.8 %) and −10.2 mm (−22.2 %), respectively, for winter. ELM shows a relatively high correlation with SNOTEL SWE, with mean correlation coefficients of 0.69 but negative mean biases of −122.7 mm. Compared to the snow phenology of STC-MODSCAG and SPIReS, ELM shows delayed snow accumulation onset dates by 17.3 and 12.4 d, earlier snow end dates by 35.5 and 26.8 d, and shorter snow durations by 52.9 and 39.5 d, respectively. This study underscores the need for diagnosing model biases and improving ELM representations of snow properties and snow phenology in mountainous areas for more credible simulation and future projection of mountain snowpack.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2010

The Invigoration of Deep Convective Clouds Over the Atlantic: Aerosol Effect, Meteorology or Retrieval Artifact?

Associations between cloud properties and aerosol loading are frequently observed in products derived from satellite measurements. These observed trends between clouds and aerosol optical depth suggest aerosol modification of cloud dynamics, yet there are uncertainties involved in satellite retrievals that have the potential to lead to incorrect conclusions. Two of the most challenging problems are addressed here: the potential for retrieved aerosol optical depth to be cloud-contaminated, and as a result, artificially correlated with cloud parameters; and the potential for correlations between aerosol and cloud parameters to be erroneously considered to be causal. Here these issues are tackled directly by studying the effects of the aerosol on convective clouds in the tropical Atlantic Ocean using satellite remote sensing, a chemical transport model, and a reanalysis of meteorological fields. Results show that there is a robust positive correlation between cloud fraction or cloud top height and the aerosol optical depth, regardless of whether a stringent filtering of aerosol measurements in the vicinity of clouds is applied, or not. These same positive correlations emerge when replacing the observed aerosol field with that derived from a chemical transport model. Model-reanalysis data is used to address the causality question by providing meteorological context for the satellite observations. A correlation exercise between the full suite of meteorological fields derived from model reanalysis and satellite-derived cloud fields shows that observed cloud top height and cloud fraction correlate best with model pressure updraft velocity and relative humidity. Observed aerosol optical depth does correlate with meteorological parameters but usually different parameters from those that correlate with observed cloud fields. The result is a near-orthogonal influence of aerosol and meteorological fields on cloud top height and cloud fraction. The results strengthen the case that the aerosol does play a role in invigorating convective clouds.

Koren, Ilan↗