ALBERT

Description: Aerosol optical thickness (τaer) is a fundamental parameter for analyzing aerosol loading and associated radiative effects. The τaer can constrain many inversion algorithms using passive/active sensor measurements to retrieve other aerosol properties and/or the abundance of trace gases. In the next wave of spectroradiometric observations from geostationary platforms, we envision that a strategically distributed network of robust, well-calibrated ground-based spectroradiometers will comprehensively complement spaceborne measurements in spectral and temporal domains. Spectral τaer can be accurately obtained from direct-Sun measurements based on the Langley calibration method, which allows for the analysis of distinct spectral features of the calibration results. In this study, we present a spectral τaer retrieval algorithm for an in-house developed, field deployable spectroradiometer instrument covering wavelengths from ultraviolet to near-infrared (UV-Vis-NIR). The spectral total optical thickness obtained from the Langley calibration method is partitioned into molecular and particulate components by utilizing a least squares method. The resulting high temporal-resolution τaer and Ångström Exponent can be used effectively for cloud screening. The new algorithm was applied to month-long measurements acquired from the rooftop at National Aeronautics and Space Administration Goddard Space Flight Center's Building 33. The retrieved τaer demonstrated excellent agreement with those from well-calibrated Aerosol Robotic Network Sun photometers at all overlapping wavelengths (correlation coefficients higher than 0.98). In addition, empirical stray light corrections considerably improved τaer retrievals at short wavelengths in the UV. The continuous spectrum of τaer from UV-Vis-NIR spectroradiometers is expected to provide more informative constraints for retrieval of additional aerosol properties such as refractive indices, size, and bulk vertical distribution. Published 2018. This article is a U.S. Government work and is in the public domain in the USA.

Description: Two methods designed to parameterize mesoscale ascent in a three-dimensional numerical cloud model via near-surface momentum and heat fluxes are presented and compared to the commonly used technique of an initial perturbation placed within the model initial condition. The flux techniques use a continuously reinforced thermal or convergent low-level wind field to produce upward vertical motion on the order of 10 cm s−1, by which deep, moist convection can be initiated. The sensitivity of the convective response to the type, strength, and size of the forcing is evaluated using numerical simulations of a conditionally unstable environment with weak unidirectional shear. Precipitation-free cloud processes are used to further simplify the model response to the forcing. The three methods tested produce an initial convective response, but only the momentum and heat flux methods are able to produce sustained deep convection that approximately resembles isolated multicellular convection. Cell regeneration periods, defined as the elapsed time between subsequent vertical velocity maxima passing through a constant level in the updraft region above the source, vary from 8 to 25 min, depending on the forcing type, magnitude, and geometry.

Description: This talk presents some of the detailed observations of low-level stratocumulus over northern Vietnam during 7-SEASBASELInE 2013 by SMARTLabs' ACHIEVE W-band cloud radar and other remote sensing instruments. These observations are the first of their kind for this region and will aid in ongoing studies of biomass-burning aerosol impacts on local and regional weather and climate. Preliminary results from simulations using the Goddard Cumulus Ensemble (GCE) with recently implemented triple-moment bulk microphysics to examine the sensitivity of low-level stratocumulus over land to aerosols are also presented. Recommendations for future observational activities in the 7-SEAS northern region in collaboration with international partners will also be discussed.

Description: An optimal estimation scheme is employed to demonstrate the utility of using multi-band radar observations for estimating supercooled liquid profiles. Qualitative comparisons with microphysical probe images show that the retrievals are capable of producing supercooled liquid consistent with in situ data. Finally, a path forward for quantifying performance and extending the study to a more robust measurement suite is given.

Description: The 2013 7-SEASBASELInE campaign over northern Southeast Asia (SEA) provided, for the first time ever, comprehensive ground-based W-band radar measurements of the low-level stratocumulus (Sc) systems that often exist during the spring over northern Vietnam in the presence of biomass-burning aerosols. Although spatially limited, ground-based remote sensing observations are generally free of the surface contamination and signal attenuation effects that often hinder space-borne measurements of these low-level cloud systems. Such observations permit detailed measurements of structures and lifecycles of these clouds as part of a broader effort to study potential impacts of these coupled aerosol-cloud systems on local and regional weather and air quality. Introductory analyses of the W-band radar data show these Sc systems generally follow a diurnal cycle, with peak occurrences during the nighttime and early morning hours, often accompanied by light precipitation. Preliminary results from idealized simulations of Sc development over land based on the observations reveal the familiar response of increased numbers and smaller sizes of cloud droplets, along with suppressed drizzle formation, as aerosol concentrations increase. Slight reductions in simulated W-band reflectivity values also are seen with increasing aerosol concentrations and result primarily from decreased droplet sizes. As precipitation can play a large role in removing aerosol from the atmosphere, and thereby improving air quality locally, quantifying feedbacks between aerosols and cloud systems over this region are essential, particularly given the negative impacts of biomass burning on human health in SEA. Such an endeavor should involve improved modeling capabilities along with comprehensive measurements of time-dependent aerosol and cloud profiles.

Description: Initial droplet spectra produced upon activation impact the ensuing chain of microphysical processes andtherefore play a crucial role in cloud evolution. This work re-examines dependencies of newly formed clouddroplet size distribution (CDSD) characteristics on environmental and aerosol properties via parcel model simulationsthat serve as the basis for a multi-moment bulk microphysics droplet activation scheme suitable for acloud-resolving model (CRM). It is found that applying a fixed size threshold to define activated droplets versusemploying physical considerations can lead to erroneous activation and overly broad CDSDs for high aerosolconcentration and weak updraft conditions. Aerosol distributions characterized by larger median sizes and/orincreased solubility can result in greater activated droplet numbers, whereas impacts of these parameters onCDSD spectral width depend on both aerosol number concentration and updraft velocity. An expansion of theactivation scheme to include CDSD spectral width is proposed to aid efforts to extend high-order momentprediction to cloud droplet categories in CRMs as well as better represent variability in the activation process onthe cloud scale.simulations to investigate the regime dependence of the relative dispersion(d)1 of newly activated CDSDs, where d is the ratio of dropletradius standard deviation () to the mean radius (r ). C16 demonstratedthat increasing Na resulted in increasing (decreasing) d values via reducedcondensational narrowing (spectral broadening) rates within theAL (UL) regime, with d values peaking in the TR regime. Their findingssuggest a similar regime dependence for d as R09 noted for Nc and helpexplain reportedly conflicting relationships between Na and CDSDspectral characteristics (cf. Hudson and Noble, 2014; Liu et al., 2014),although the applicability of these results within bulk microphysicalschemes was not addressed.Simulating aerosol-cloud interactions with CRMs employing bulkmicrophysics requires that the scheme minimally predict two CDSDparameters, namely mass and number concentrations, and represent thedroplet activation process. Various activation schemes aim to determineNc from aerosol and environmental properties and include analyticalexpressions (e.g., Abdul-Razzak et al., 1998; Morrison et al., 2005) aswell as lookup tables (LUTs) based on detailed parcel model calculations(e.g., Saleeby and Cotton, 2004, hereafter SC04; Segal and Khain,2006; Thompson and Eidhammer, 2014). Expressions to diagnose CDSDspectral width from Nc (Grabowski, 1998; Liu et al., 2006; Morrison andGrabowski, 2007) or cloud water content (Geoffroy et al., 2010) havealso been developed, although more robust methods to obtain CDSDspectral width upon activation are presently lacking. This latter point isrelevant for triple-moment (3 M) bulk microphysics that aim to predictdistribution spectral width alongside number and mass concentrations(e.g., Loftus et al., 2014; Milbrandt and Yau, 2005).The current work extends the findings of C16 to the current LUTbasedaerosol activation scheme used in the Regional AtmosphericModeling System (RAMS) (Cotton et al., 2003; SC04; Saleeby and vanden Heever, 2013, hereafter SvdH13) and additionally examinesaerosol size and solubility impacts on newly activated CDSD properties.Because early cloud development processes such as condensationalgrowth, evaporation, and droplet self-collection depend on and impactCDSD spectral width (Hudson and Yum, 1997; Seifert and Beheng 2001;Lu and Seinfeld, 2006; Igel and van den Heever, 2017), an expansion ofthe activation LUTs to include CDSD spectral width is proposed as apreliminary step for extending 3M prediction to CDSDs in CRMs forimproved simulations of aerosol-cloud interactions.2. MethodologyThe current RAMS two-moment microphysics module determinesthe fractional number of aerosol particles that activate to cloud dropletsfrom five-dimensional LUTs based on model predicted air temperature(T), w, Na, and the geometric median radius (rg) and soluble fraction ()of the aerosol size distribution (SvdH13). These LUTs are created offlineusing a one-dimensional Lagrangian adiabatic parcel model (Feingoldand Heymsfield, 1992; Heymsfield and Sabin, 1989; SC04) to simulateexplicit droplet activation and initial CDSD growth for a range of ambientatmospheric conditions [T, w] and binned lognormal aerosol sizedistributions given by= N r Nr r r( )2 lnexp[ln( / )]2(ln )aggg22 (1)where r is the dry aerosol particle bin radius and g is the geometricstandard deviation of the distribution. As the parcel model simulationsfocus on the activation process, other processes such as coalescence,sedimentation, and mixing are not considered. Details of the parcelmodel can be found in SC04 and SvdH13, and only a brief description isprovided here. At the onset of parcel model calculations, the initiallydry aerosol particles in all bins first deliquesce and reach theirequilibrium diameters in a sub-saturated environment based on theKhler equation for solution droplets. The parcel is then lifted at a fixedupward velocity w, and particle growth by vapor diffusion, along withconcurrent changes in the ambient environment, are iteratively computedusing the Variable-coefficient Ordinary Differential Equation(VODE) solver (Brown et al., 1989). The time resolution of these calculationsis determined within the VODE solver, and the frequency atwhich the solver is called is controlled by a longer model time stepbased on fixed upward parcel displacement increments (z) at thespecified w (t=z/w). Model calculations proceed until the parcelreaches a height 50m beyond the level of maximum saturation ratio(Smax) or total parcel displacement exceeds 2 km. Upon model termination,Smax and the fractional number of aerosols (factv) resulting innewly formed cloud droplets, defined as particles having diameters of atleast 2 m, are cataloged in the LUTs according to the specified T, w, Na,rg, and parameter values.A critical point regarding the creation of these LUTs is the use of afixed minimum diameter (Dmin) to define cloud droplets in the parcelmodel, which can produce erroneous CDSD characteristics, particularlywithin the UL regime. For aerosol distributions with large rg valuesunder low SS conditions, for example, deliquesced aerosols within thelarge tail of the distribution can exceed 2 m in diameter yet remainunactivated as haze particles (Levin and Cotton, 2009; McFigganset al., 2006). For this study, aerosol particles activate to cloud dropletsbased on the critical diameter Dcrit as a function of parcel supersaturationratio (Sr) as in R09:D = MS RT83 ln( ) critsol wr w (2)where sol is the surface tension of a solution droplet, Mw and w are themolar mass and density of liquid water, respectively, and R is theuniversal gas constant. Additionally, at relatively large w values withinthe AL regime, Nc stabilizes shortly after reaching supersaturation.However, parcel ascent and condensational growth continue beyondthe level of Smax, potentially causing additional narrowing of the CDSD.In the current work, model calculations terminate upon reaching Smaxas changes in Nc are negligible with continued ascent (Peng et al., 2007;R09).Parcel model simulations are performed to examine the sensitivitiesof CDSD characteristics to w, Na, rg, and , with the ranges for theseparameters listed in Table 1. Aerosols are assumed to be a mix of solubleand insoluble material of equal density, specified by , where fullysoluble aerosols correspond to ammonium sulfate with hygroscopicityparameter =0.61 (Petters and Kreidenweis, 2007). FollowingSvdH13, aerosol geometric standard deviation is fixed at g=1.8, andaerosol distributions (Eq. 1) are partitioned into 100 logarithmicallyspacedbins spanning a size range specific to each rg value. For all simulations,z=1 m, and initial values of relative humidity, air temperatureand pressure are set to RH=0.99, T=10 C and p=900 hPa,respectively.

Description: Sensor forward models are an important tool for interpreting remote sensing observations of geophysical phenomena. By implementing a three-dimensional framework, we can simulate and analyze observations from various sensors on disparate platforms. To demonstrate our model framework, we simulate observations from the Olympic Mountains Experiment (OLYMPEX). The use of cloud model simulations allows us to understand sensor response to cloud ice, falling snow, and other processes and features, and the application of model tools to observations allows us to quantify precipitation.MIIST 3D Forward ModelThe Multi-Instrument Inverse Solver Testbed(MIIST) uses the Atmospheric Radiative TransferSimulator (ARTS) for solving the vector radiativetransfer (RT) equation in up to three spatialdimensions within a spherical geometry Gas absorptiono Line-by-line calculationso Fast transmittance tables Hydrometeor scattering solverso Discrete ordinateo RT4 (Evans, 1D)o Radar Single Scattering (1D or 3D)o Monte Carlo (3D)Scattering TablesHigh-fidelity hydrometeor scatteringtables are necessary for accurateand consistent forward modeling ofmulti-frequency observations Requires full Stokes matriceso And absorption vector Randomly oriented particleso Discrete Dipole Approximationo Characteristic Basis Function Method(coming soon) Horizontally-oriented plateso Invariant Imbedding T-matrix MethodCloud Resolving SimulationsCloud resolving simulations (e.g.,NU-WRF) supply output consistentwith ARTS needs Atmospheric Informationo Temperatureo Pressure / heighto Water vapor Hydrometeor Profileso ARTS architecture ripe for explicit binmicrophysics Examples use Morrison 2M schemeThe Olympic Mountains Experiment (OLYMPEX)Validation for GPM of mid-latitudefrontal systems approaching nearcoastalmountains from the ocean Large collection of ground-based andairborne sensorso Radarso Radiometerso In situ Contemporaneous with RADEXo Two sets of radar at same frequenciesRadiometer Simulation (3 km NUWRF, 20151203, 15:00)2018.12.14 7Simulate 166 GHz polarizationdifference Corresponds to the presence of aligned icecrystals Look at trends for both simulations andobservations Simulations can tolerate lower resolutiono Larger domainSimulations from Observations: OLYMPEXSimulate sensor response usinggeophysical retrievals as input Single frequency radar retrievals Multiple scattering enhancementapparent at W band Spatially dependent phenomenonModeling Application: 1D Retrievals03 December 2015 DC-8 and ER-2 flightso Focus on APR-3 (DC-8) Citationo Stacked microphysics legso Qualitative comparisonso Range of frozen habitso Presence of supercooledliquid cloudsResults Retrievals match probeso Good qualitative match Bands of increasedreflectivity correspond tolarge Dm and highaggregate fraction Significant amounts ofsupercooled liquid water