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At least 919 records · Page 51

Individual Dynamical Masses of Ultracool Dwarfs

We present the full results of our decade-long astrometric monitoring programs targeting 31 ultracool binaries with component spectral types M7–T5. Joint analysis of resolved imaging from Keck Observatory and Hubble Space Telescope and unresolved astrometry from CFHT/WIRCam yields parallactic distances for all systems, robust orbit determinations for 23 systems, and photocenter orbits for 19 systems. As a result, we measure 38 precise individual masses spanning 30–115 M{sub Jup}. We determine a model-independent substellar boundary that is ≈70 M{sub Jup} in mass (≈L4 in spectral type), and we validate Baraffe et al. evolutionary model predictions for the lithium-depletion boundary (60 M{sub Jup} at field ages). Assuming each binary is coeval, we test models of the substellar mass–luminosity relation and find that in the L/T transition, only the Saumon and Marley “hybrid” models accounting for cloud clearing match our data. We derive a precise, mass-calibrated spectral type–effective temperature relation covering 1100–2800 K. Our masses enable a novel direct determination of the age distribution of field brown dwarfs spanning L4–T5 and 30–70 M{sub Jup}. We determine a median age of 1.3 Gyr, and our population synthesis modeling indicates our sample is consistent with a constant star formation history modulated by dynamical heating in the Galactic disk. We discover two triple-brown-dwarf systems, the first with directly measured masses and eccentricities. We examine the eccentricity distribution, carefully considering biases and completeness, and find that low-eccentricity orbits are significantly more common among ultracool binaries than solar-type binaries, possibly indicating the early influence of long-lived dissipative gas disks. Overall, this work represents a major advance in the empirical view of very low-mass stars and brown dwarfs.

79 ASTRONOMY AND ASTROPHYSICS↗

Passive Microwave Remote Sensing of Falling Snow and Associated GPM Field Campaigns

Retrievals of falling snow from space represent one of the next important challenges for the atmospheric, hydrological, and energy budget scientific communities. Historically, retrievals of falling snow have been difficult due to the relative insensitivity of satellite rain-based channels as used in the past. We emphasize the use of high frequency passive microwave channels (85-200 GHz) since these are more sensitive to the ice in clouds and have been used to estimate falling snow from space. While satellite-based remote sensing provides global coverage of falling snow events and the science is relatively new, retrievals are still undergoing development with challenges remaining. There are several current satellite sensors, though not specifically designed for estimating falling snow, are capable of measuring snow from space. These include NOAA's AMSU-B, the MHS sensors, and CloudSat radar. They use high frequency (greater than 85 GHz) passive and active microwave and millimeter-wave channels that are sensitive to the scattering from ice and snow particles in the atmosphere. Sensors with water vapor channels near 183 GHz center line provide opaqueness to the Earth's surface features that can contaminate the falling snow signatures, especially over snow covered surface. In addition, the Global Precipitation Measurement (GPM) mission scheduled for launch in 2013 is specifically designed to measure both liquid rain and frozen snow precipitation. Since falling snow from space is the next precipitation measurement challenge from space, information must be determined in order to guide retrieval algorithm development for these current and future missions. This information includes thresholds of detection for various sensor channel configurations, snow event system characteristics, and surface types. For example, can a lake effect snow system with low cloud tops having an ice water content (IWC) at the surface of 1.0 gram per cubic meter be detected? If this information is known, we can focus retrieval efforts on detectable storms and concentrate advances on achievable results. In this work, the focus is to determine thresholds of detection for falling snow for various snow conditions over land and lake surfaces. The results rely on simulated Weather Research Forecasting (WRF) simulations of falling snow cases [9] since simulations provide all the information to determine the measurements from space and the ground truth. This analysis relies on data from the Canadian CloudSat/CALIPSO Validation Program (C3VP) field campaign held from October 31, 2006 through March 1, 2007. In January 2012 GPM will return to the C3VP area for the GPM Cold Precipitation Experiment (GCPEx). This presentation will describe the thresholds-of-detection procedure and results, as well as the field campaign details.

Skofronick-Jackson, Gail↗

Modeling of Cloud Microphysics: Can We Do Better?

Representation of cloud microphysics is a key aspect of simulating clouds. From the early days of cloud modeling, numerical models have relied on an Eulerian approach for all cloud and thermodynamic and microphysics variables. Over time the sophistication of microphysics schemes has steadily increased, from simple representations of bulk masses of cloud and rain in each grid cell, to including different ice particle types and bulk hydrometeor concentrations, to complex schemes referred to as bin or spectral schemes that explicitly evolve the hydrometeor size distributions within each model grid cell. As computational resources grow, there is a clear trend toward wider use of bin schemes, including their use as benchmarks to develop and test simplified bulk schemes. We argue that continuing on this path brings fundamental challenges difficult to overcome. The Lagrangian particle-based probabilistic approach is a practical alternative in which the myriad of cloud and precipitation particles present in a natural cloud is represented by a judiciously selected ensemble of point particles called superdroplets or superparticles. Here, the advantages of the Lagrangian particle-based approach when compared to the Eulerian bin methodology are explained, and the prospects of applying the method to more comprehensive cloud simulations—for instance, targeting deep convection or frontal cloud systems—are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Shielding, the bulk chemical potential, and cohesion in alloys

It is shown that the bulk chemical potential in alloys is intimately related to the spatial dependence of the shielding cloud that results when the electronic charge rearranges itself as one atom type is replaced by another at a given site. Such a relationship fixes the relative energy scale between the alloy and its pure constituents, important in determining the stability of alloys. A correct treatment of shielding is thus essential to quantitative calculations of alloy stability. A model calculation of the bulk chemical potential and cohesion of alloys in the tight-binding approximation is presented as a numerical example. In the course of this investigation a general invariant of an integral over the shielding cloud is derived.

Stern, E. A.↗

Bipolar flows, molecular gas disks, and the collapse and accretion of rotating interstellar clouds

Rigorous numerical models of the collapse and accretion of rotating, axisymmetric, isothermal interstellar clouds are studied. The results show that molecular gas disks and evacuated bipolar cavities both appear to be natural consequences of the collapse of rotating interstellar clouds. Dynamically significant magnetic fields may not be necessary for explaining either phenomenon. The models strongly support theoretical models of the type where an isotropic wind from a pre-main sequence star is extrinsically collimated by a rotationally derived molecular gas cloud. The models imply that collimation should be strongest on small scales where rotational effects are most important, i.e., in the dense region of the molecular gas disk.

Boss, Alan P.↗

Discovery of a New Dusty B[E] Star in the Small Magellanic Cloud

We present new optical spectroscopic and Spitzer IRAC photometric observations of a B-type star in the SMC cluster NGC 346, NGC 346:KWBBe 200. We detect numerous Fe II, [O I], [Fe II], as well as strong P-Cygni profile H I emission lines in its optical spectrum. The star's near-IR color and optical to IR SED clearly indicate the presence of an infrared excess, consistent with the presence of gas and warm, T -800 K, circumstellar dust. Based on a crude estimate of the star's luminosity and the observed spectroscopic line profile morphologies, we find that the star is likely to be a B-type supergiant. We suggest that NGC 346:KWBBe 200 is a newly discovered B[e] supergiant star, and represents the fifth such object to be identified in the SMC.

Wisniewski, John P.↗

Object Detection and Recognition with PointPillars in LiDAR Point Clouds – Comparisions

In the field of autonomous systems, neural networks have been leveraged for object detection and recognition in 2-dimensional images captured by cameras. Other types of sensors are available for sensing surroundings, including LiDAR sensors, and corresponding networks have been developed to perform detection and recognition in the point clouds generated by these sensors. The approaches are similar, both perform convolutions, but have distinct characteristics and challenges. In designing and configuring autonomous systems, a variety of LiDAR sensors are available, along with configurable deep neural networks to leverage their data. This work presents a review of the PointPillars network, an evolution of the seminal PointNet, comparing accuracy and training time relative to different LiDAR sensors, network and training parameters, CPU and GPU hardware, and the criticality of the use of reflective intensity as a feature. The value of using reflectivity as a predictive feature is explored and quantified to determine if it makes a significant difference in accuracy of the PointPillars network. Two separate LiDAR sensors are utilized, a 16-plane and a 32-plane, and corresponding accuracies and training times with the PointPillars network are evaluated.

LiDAR, machine learning, neural network, object re↗

Use of Probability Distribution Functions for Discriminating Between Cloud and Aerosol in Lidar Backscatter Data

In this paper we describe the algorithm hat will be used during the upcoming Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission for discriminating between clouds and aerosols detected in two wavelength backscatter lidar profiles. We first analyze single-test and multiple-test classification approaches based on one-dimensional and multiple-dimensional probability density functions (PDFs) in the context of a two-class feature identification scheme. From these studies we derive an operational algorithm based on a set of 3-dimensional probability distribution functions characteristic of clouds and aerosols. A dataset acquired by the Cloud Physics Lidar (CPL) is used to test the algorithm. Comparisons are conducted between the CALIPSO algorithm results and the CPL data product. The results obtained show generally good agreement between the two methods. However, of a total of 228,264 layers analyzed, approximately 5.7% are classified as different types by the CALIPSO and CPL algorithm. This disparity is shown to be due largely to the misclassification of clouds as aerosols by the CPL algorithm. The use of 3-dimensional PDFs in the CALIPSO algorithm is found to significantly reduce this type of error. Dust presents a special case. Because the intrinsic scattering properties of dust layers can be very similar to those of clouds, additional algorithm testing was performed using an optically dense layer of Saharan dust measured during the Lidar In-space Technology Experiment (LITE). In general, the method is shown to distinguish reliably between dust layers and clouds. The relatively few erroneous classifications occurred most often in the LITE data, in those regions of the Saharan dust layer where the optical thickness was the highest.

Liu, Zhaoyan↗

Satellite Remote Sensing of Tropical Precipitation and Ice Clouds for GCM Verification

This project, supported by the NASA New Investigator Program, has primarily been funding a graduate student, Darren McKague. Since August 1999 Darren has been working part time at Raytheon, while continuing his PhD research. Darren is planning to finish his thesis work in May 2001, thus some of the work described here is ongoing. The proposed research was to use GOES visible and infrared imager data and SSM/I microwave data to obtain joint distributions of cirrus cloud ice mass and precipitation for a study region in the Eastern Tropical Pacific. These joint distributions of cirrus cloud and rainfall were to be compared to those from the CSU general circulation model to evaluate the cloud microphysical amd cumulus parameterizations in the GCM. Existing algorithms were to be used for the retrieval of cloud ice water path from GOES (Minnis) and rainfall from SSM/I (Wilheit). A theoretical study using radiative transfer models and realistic variations in cloud and precipitation profiles was to be used to estimate the retrieval errors. Due to the unavailability of the GOES satellite cloud retrieval algorithm from Dr. Minnis (a co-PI), there was a change in the approach and emphasis of the project. The new approach was to develop a completely new type of remote sensing algorithm - one to directly retrieve joint probability density functions (pdf's) of cloud properties from multi-dimensional histograms of satellite radiances. The usual approach is to retrieve individual pixels of variables (i.e. cloud optical depth), and then aggregate the information. Only statistical information is actually needed, however, and so a more direct method is desirable. We developed forward radiative transfer models for the SSM/I and GOES channels, originally for testing the retrieval algorithms. The visible and near infrared ice scattering information is obtained from geometric ray tracing of fractal ice crystals (Andreas Macke), while the mid-infrared and microwave scattering is computed with Mie scattering. The radiative transfer is performed with the Spherical Harmonic Discrete Ordinate Method (developed by the PI), and infrared molecular absorption is included with the correlated k-distribution method. The SHDOM radiances have been validated by comparison to version 2 of DISORT (the community "standard" discrete-ordinates radiative transfer model), however we use SHDOM since it is computationally more efficient.

Evans, K. Franklin↗

Large-Scale Air Mass Characteristics Observed Over the Remote Tropical Pacific Ocean During March-April 1999: Results from PEM-Tropics B Field Experiment

Eighteen long-range flights over the Pacific Ocean between 38 S to 20 N and 166 E to 90 W were made by the NASA DC-8 aircraft during the NASA Pacific Exploratory Mission (PEM) Tropics B conducted from March 6 to April 18, 1999. Two lidar systems were flown on the DC-8 to remotely measure vertical profiles of ozone (O3), water vapor (H2O), aerosols, and clouds from near the surface to the upper troposphere along their flight track. In situ measurements of a wide range of gases and aerosols were made on the DC-8 for comprehensive characterization of the air and for correlation with the lidar remote measurements. The transition from northeasterly flow of Northern Hemispheric (NH) air on the northern side of the Intertropical Convergence Zone (ITCZ) to generally easterly flow of Southern Hemispheric (SH) air south of the ITCZ was accompanied by a significant decrease in O3, carbon monoxide, hydrocarbons, and aerosols and an increase in H2O. Trajectory analyses indicate that air north of the ITCZ came from Asia and/or the United States, while the air south of the ITCZ had a long residence time over the Pacific, perhaps originating over South America several weeks earlier. Air south of the South Pacific Convergence Zone (SPCZ) came rapidly from the west originating over Australia or Africa. This air had enhanced O3 and aerosols and an associated decrease in H2O. Average latitudinal and longitudinal distributions of O3 and H2O were constructed from the remote and in situ O3 and H2O data, and these distributions are compared with results from PEM-Tropics A conducted in August-October 1996. During PEM-Tropics B, low O3 air was found in the SH across the entire Pacific Basin at low latitudes. This was in strong contrast to the photochemically enhanced O3 levels found across the central and eastern Pacific low latitudes during PEM-Tropics A. Nine air mass types were identified for PEM-Tropics B based on their O3, aerosols, clouds, and potential vorticity characteristics. The data from each flight were binned by altitude according to air mass type, and these results showed the relative observational frequency of the different air masses as a function of altitude in seven regions over the Pacific. The average chemical composition of the major air mass types was determined from in situ measurements in the NH and SH, and these results provided insight into the origin, lifetime, and chemistry of the air in these regions.

Browell, Edward V.↗

The 5-6 December 1991 FIRE IFO 2 Jet Stream Cirrus Case Study: Possible Influences of Volcanic Aerosols

In presenting an overview of the cirrus clouds comprehensively studied by ground based and airborne sensors from Coffeyville, Kansas, during the 5-6 December 1992 First ISCCP Regional Experiment (FIRE) intensive field observation (IFO) case study period, evidence is provided that volcanic aerosols from the June 1991 Pinatubo eruptions may have significantly influenced the formation and maintenance of the cirrus. Following the local appearance of a spur of stratospheric volcanic debris from the subtropics, a series of jet streaks subsequently conditioned the troposphere through tropopause foldings with sulfur based particles that became effective cloud forming nuclei in cirrus clouds. Aerosol and ozone measurements suggest a complicated history of stratospheric-tropospheric exchanges embedded with the upper level flow, and cirrus cloud formation was noted to occur locally at the boundaries of stratospheric aerosol enriched layers that became humidified through diffusion, precipitation, or advective processes. Apparent cirrus cloud alterations include abnormally high ice crystal concentrations (up to approximately 600 L(exp. 1)), complex radial ice crystal types, and relatively large haze particles in cirrus uncinus cell heads at temperatures between -40 and -50 degrees C. Implications for volcanic-cirrus cloud climate effects and unusual (nonvolcanic) aerosol jet stream cirrus cloud formation are discussed.

Sassen, Kenneth↗

CERES Single Scanner Satellite Footprint, TOA, Surface Fluxes and Clouds (SSF) data in HDF (CER_SSF_Terra-FM2-MODIS_Edition2A)

The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2003-12-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

SURFACE (RADIATIVE) FLUX↗

Next-Generation Angular Distribution Models for Top-of-Atmosphere Radiative Flux Calculation from the CERES Instruments: Methodology

The top-of-atmosphere (TOA) radiative fluxes are critical components to advancing our understanding of the Earth's radiative energy balance, radiative effects of clouds and aerosols, and climate feedback. The Clouds and the Earth's Radiant Energy System (CERES) instruments provide broadband shortwave and longwave radiance measurements. These radiances are converted to fluxes by using scene-type-dependent angular distribution models (ADMs). This paper describes the next-generation ADMs that are developed for Terra and Aqua using all available CERES rotating azimuth plane radiance measurements. Coincident cloud and aerosol retrievals, and radiance measurements from the Moderate Resolution Imaging Spectroradiometer (MODIS), and meteorological parameters from Goddard Earth Observing System (GEOS) data assimilation version 5.4.1 are used to define scene type. CERES radiance measurements are stratified by scene type and by other parameters that are important for determining the anisotropy of the given scene type. Anisotropic factors are then defined either for discrete intervals of relevant parameters or as a continuous functions of combined parameters, depending on the scene type. Significant differences between the ADMs described in this paper and the existing ADMs are over clear-sky scene types and polar scene types. Over clear ocean, we developed a set of shortwave (SW) ADMs that explicitly account for aerosols. Over clear land, the SW ADMs are developed for every 1 latitude1 longitude region for every calendar month using a kernel-based bidirectional reflectance model. Over clear Antarctic scenes, SW ADMs are developed by accounting the effects of sastrugi on anisotropy. Over sea ice, a sea-ice brightness index is used to classify the scene type. Under cloudy conditions over all surface types, the longwave (LW) and window (WN) ADMs are developed by combining surface and cloud-top temperature, surface and cloud emissivity, cloud fraction, and precipitable water. Compared to the existing ADMs, the new ADMs change the monthly mean instantaneous fluxes by up to 5Wm(exp -2) on a regional scale of 1 deg. latitude x 1 deg. longitude, but the flux changes are less than 0.5Wm(exp -2) on a global scale.

Su, W.↗

Experience with dynamic resource provisioning of the CMS online cluster using a cloud overlay

The primary goal of the online cluster of the Compact Muon Solenoid (CMS) experiment at the Large Hadron Collider (LHC) is to build event data from the detector and to select interesting collisions in the High Level Trigger (HLT) farm for offline storage. With more than 1500 nodes and a capacity of about 850 kHEPSpecInt06, the HLT machines represent similar computing capacity of all the CMS Tier1 Grid sites together. Moreover, it is currently connected to the CERN IT datacenter via a dedicated 160 Gbps network connection and hence can access the remote EOS based storage with a high bandwidth. In the last few years, a cloud overlay based on OpenStack has been commissioned to use these resources for the WLCG when they are not needed for data taking. This online cloud facility was designed for parasitic use of the HLT, which must never interfere with its primary function as part of the DAQ system. It also allows to abstract from the different types of machines and their underlying segmented networks. During the LHC technical stop periods, the HLT cloud is set to its static mode of operation where it acts like other grid facilities. The online cloud was also extended to make dynamic use of resources during periods between LHC fills. These periods are a-priori unscheduled and of undetermined length, typically of several hours, once or more a day. For that, it dynamically follows LHC beam states and hibernates Virtual Machines (VM) accordingly. Finally, this work presents the design and implementation of a mechanism to dynamically ramp up VMs when the DAQ load on the HLT reduces towards the end of the fill.

97 MATHEMATICS AND COMPUTING↗

Development of a climatological data base to help forecast cloud cover conditions for shuttle landings at the Kennedy Space Center

The Space Shuttle is an extremely weather sensitive vehicle with very restrictive constraints for both launches and landings. The most important difference between Shuttle and normal aircraft landings is that the Shuttle has no go-around capability once it begins its decent into the earth's atmosphere. The de-orbit burn decision is generally made approximately 90 minutes before landing requiring a forecast with little room for error. Because of the Shuttle's rapid re-entry to earth, the pilot must be able to see all runway and visual navigation aids from high altitude to land the Shuttle. In addition, the heat resistant tiles which are used to protect the Shuttle during its re-entry into the earth's atmosphere are extremely sensitive to any type of precipitation. Extensive damage to these tiles could occur if the Shuttle passes through any cloud that contains precipitation size particles. To help guard against changing weather conditions or any type of weather problems that might occur prior to landing, flight rules have been developed as guidelines for all landings. Although the rules vary depending on the location of the landing (Kennedy Space Center or Edwards AFB), length of mission, and weight of vehicle, most of the rules can be condensed into 4 major groupings. These are: (1) Cloud ceilings should not be less than 3048 m (10,000 feet), (2) Visibility should not be less than 13 km (7 nm), (3) Cross-wind no greater than 5-8 m/s (10-15 knots); and (4) No showers or thunderstorms at or within 56 km (30 nm) of the Shuttle Landing Facility. This study consisted of developing a climatological database of the Shuttle Landing Facility (SLF) surface observations and performing an analysis of observed conditions one and two hours subsequent to given conditions at the SLF to help analyze the 0.2 cloud cover rule. Particular emphasis was placed on Shuttle landing weather violations and the amounts of cloud cover below 3048 m (10,000 ft.). This analysis has helped to determine the best and worst times to land the Shuttle at KSC. In addition, nomograms have been developed to help forecasters make cloud cover forecasts for End of Mission (EOM) and Return to Launch Site (RTLS) at KSC. Results of categorizing this data by month, season, time of day, and surface and upper-air wind direction are presented.

Atchison, M. Kevin↗

Weather on Other Worlds. IV. Hα Emission and Photometric Variability Are Not Correlated in L0–T8 Dwarfs

Recent photometric studies have revealed that surface spots that produce flux variations are present on virtually all L and T dwarfs. Their likely magnetic or dusty nature has been a much-debated problem, the resolution to which has been hindered by paucity of diagnostic multi-wavelength observations. To test for a correlation between magnetic activity and photometric variability, we searched for H α emission among eight L3–T2 ultra-cool dwarfs with extensive previous photometric monitoring, some of which are known to be variable at 3.6 μ m or 4.5 μ m. We detected H α only in the non-variable T2 dwarf 2MASS J12545393−0122474. The remaining seven objects do not show H α emission, even though six of them are known to vary photometrically. Combining our results with those for 86 other L and T dwarfs from the literature show that the detection rate of H α emission is very high (94%) for spectral types between L0 and L3.5 and much smaller (20%) for spectral types ≥L4, while the detection rate of photometric variability is approximately constant (30%–55%) from L0 to T8 dwarfs. We conclude that chromospheric activity, as evidenced by H α emission, and large-amplitude photometric variability are not correlated. Consequently, dust clouds are the dominant driver of the observed variability of ultra-cool dwarfs at spectral types, at least as early as L0.

79 ASTRONOMY AND ASTROPHYSICS↗

Earth System Model Aerosol–Cloud Diagnostics (ESMAC Diags) package, version 2: assessing aerosols, clouds, and aerosol–cloud interactions via field campaign and long-term observations

Abstract. Poor representations of aerosols, clouds, and aerosol–cloud interactions (ACIs) in Earth system models (ESMs) have long been the largest uncertainties in predicting global climate change. Huge efforts have been made to improve the representation of these processes in ESMs, and the key to these efforts is the evaluation of ESM simulations with observations. Most well-established ESM diagnostics packages focus on the climatological features; however, they lack process-level understanding and representations of aerosols, clouds, and ACIs. In this study, we developed the Earth System Model Aerosol–Cloud Diagnostics (ESMAC Diags) package to facilitate the routine evaluation of aerosols, clouds, and ACIs simulated the Energy Exascale Earth System Model (E3SM) from the US Department of Energy (DOE). This paper documents its version 2 functionality (ESMAC Diags v2), which has substantial updates compared with version 1 (Tang et al., 2022a). The simulated aerosol and cloud properties have been extensively compared with in situ and remote-sensing measurements from aircraft, ship, surface, and satellite platforms in ESMAC Diags v2. It currently includes six field campaigns and two permanent sites covering four geographical regions: the eastern North Atlantic, the central US, the northeastern Pacific, and the Southern Ocean. These regions produce frequent liquid- or mixed-phase clouds, with extensive measurements available from the DOE Atmospheric Radiation Measurement user facility and other agencies. ESMAC Diags v2 generates various types of single-variable and multivariable diagnostics, including percentiles, histograms, joint histograms, and heatmaps, to evaluate the model representation of aerosols, clouds, and ACIs. Select examples highlighting the capabilities of ESMAC Diags are shown using E3SM version 2 (E3SMv2). In general, E3SMv2 can reasonably reproduce many observed aerosol and cloud properties, with biases in some variables such as aerosol particle and cloud droplet sizes and number concentrations. The coupling of aerosol and cloud number concentrations may be too strong in E3SMv2, possibly indicating a bias in processes that control aerosol activation. Furthermore, the liquid water path response to a perturbed cloud droplet number concentration behaves differently in E3SMv2 and observations, which warrants further study to improve the cloud microphysics parameterizations in E3SMv2.

54 ENVIRONMENTAL SCIENCES↗

Assessment of Aerosol Distributions from GEOS-5 Using the CALIPSO Feature Mask

A-train sensors such as MODIS, MISR, and CALIPSO are used to determine aerosol properties, and in the process a means of estimating aerosol type (e.g. smoke vs. dust). Correct classification of aerosol type is important for climate assessment, air quality applications, and for comparisons and analysis with aerosol transport models. The Aerosols-Clouds-Ecosystems (ACE) satellite mission proposed in the NRC Decadal Survey describes a next generation aerosol and cloud suite similar to the current A-train, including a lidar. The future ACE lidar must be able to determine aerosol type effectively in conjunction with modeling activities to achieve ACE objectives. Here we examine the current capabilities of CALIPSO and the NASA Goddard Earth Observing System general circulation model and data assimilation system (GEOS-5), to place future ACE needs in context. The CALIPSO level 2 feature mask includes vertical profiles of aerosol layers classified by type. GEOS-5 provides global 3D aerosol mass for sulfate, sea salt, dust, and black and organic carbon. A GEOS aerosol scene classification algorithm has been developed to provide estimates of aerosol mixtures and extinction profiles along the CALIPSO orbit track. In previous work, initial comparisons between GEOS-5 derived aerosol mixtures and CALIPSO derived aerosol types were presented for July 2007. In general, the results showed that model and lidar derived aerosol types did not agree well in the boundary layer. Agreement was poor over Europe, where CALIPSO indicated the presence of dust and pollution mixtures yet GEOS-5 was dominated by pollution with little dust. Over the ocean in the tropics, the model appeared to contain less sea salt than detected by CALIPSO, yet at high latitudes the situation was reserved. Agreement between CALIPSO and GEOS-5, aerosol types improved above the boundary layer, primarily in dust and smoke dominated regions. At higher altitudes (> 5 km), the model contained aerosol layers not detected by CALIPSO. Here we present new results for a full year study using the new Version 3 CALIPSO data and most recent GEOS-5 model results.

Welton, Ellsworth↗