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At least 19 records

The importance of the curvature of the wind profile in determining regions of CAT and non-CAT

An investigation is conducted regarding the relationship between CAT and the curvature of the wind profile, taking into account cases of CAT encountered by the XB-70 in the stratosphere over the mountainous terrain of the western U.S. The results of the investigation show that the curvature of the wind profile is an important tropospheric variable in the determination of stratospheric CAT regions. These CAT regions are likely to occur in cases in which the curvature increases with height in the troposphere in areas when mountain waves are expected.

Possiel, N.

Curvature of the wind profile in the troposphere versus regions of CAT and non-CAT in the stratosphere

A discussion of the theoretical importance of the curvature of the wind profile to the amplitude of mountain waves is presented. Mechanisms favorable for clear air turbulence (CAT) are discussed in relation to such wave motions. It is shown that CAT encountered by the XB-70 aircraft in the stratosphere during expected mountain-wave conditions is related to the vertical gradient of curvature of the wind profile in the troposphere. Results indicate that 89% of the turbulent regions in the stratosphere occurred in expected mountain-wave areas and that 79% were located where the vertical gradient of curvature was positive in the 10-30,000 ft layer below. For the nonturbulent regions, 74% were outside expected mountain-wave areas and 98% of these occurred where the vertical gradient of curvature was negative. All the nonturbulent regions within expected mountain-wave areas occurred where the vertical gradient of curvature was negative.

Possiel, N.

Distinguishing between CAT and non-CAT areas by use of discriminant function analysis

The investigation considered is concerned with a method in which a statistical approach is employed to determine algebraic functions involving selected synoptic-scale parameters which would indicate areas and altitudes of CAT in the stratosphere over the western U.S. The statistical approach selected is based on discriminant function analysis. The functions are determined from combinations of synoptic-scale parameters and stratospheric turbulence data. It was found in the investigation that there is a relationship between selected combinations of synoptic-scale parameters of the upper troposphere and lower stratosphere and stratospheric clear-air turbulence.

Clark, T. L.

Laser Remote Sensing From ISS: CATS Cloud and Aerosol Level 2 Data Products (Heritage Edition)

The Cloud-Aerosol Transport System (CATS) instrument was developed at NASA's Goddard Space Flight Center (GSFC) and deployed to the International Space Station (ISS) on 10 January 2015. CATS is mounted on the Japanese Experiment Module's Exposed Facility (JEM_EF) and will provide near-continuous, altitude-resolved measurements of clouds and aerosols in the Earth's atmosphere. The CATS ISS orbit path provides a unique opportunity to capture the full diurnal cycle of cloud and aerosol development and transport, allowing for studies that are not possible with the lidar aboard the CALIPSO platform, which flies in the sun-synchronous A-Train orbit." " One of the primary science objectives of CATS is to continue the CALIPSO aerosol and cloud profile data record to provide continuity of lidar climate observations during the transition from CALIPSO to EarthCARE. To accomplish this, the CATS project at NASA's Goddard Space Flight Center (GSFC) and the CALIPSO project at NASA's Langley Research Center (LaRC) are closely collaborating to develop and deliver a full suite of CALIPSO-like level 2 data products that will be produced using the newly acquired CATS level 1B data whenever CATS is operating in science modes 1. The CALIPSO mission is now well into its ninth year of on-orbit operations, and has developed a robust set of mature and well-validated science algorithms to retrieve the spatial and optical properties of clouds and aerosols from multi-wavelength lidar backscatter signals. By leveraging both new and existing NASA technical resources, this joint effort by the CATS and CALIPSO teams will deliver validated lidar data sets to the user community at the earliest possible opportunity. The science community will have access to two sets of CATS Level 2 data products. The "Operational" data products will be produced by the GSFC CATS team utilizing the new instrument capabilities (e.g., multiple FOVs and 1064 nm depolarization), while the "Heritage" data products created using the existing CALIPSO algorithms and the CATS 532 nm channels and the total 1064 nm channel. " Below is the development of the CATS "Heritage" level 2 software and data along with some initial results with operational data."

Rodier, Sharon

Effect of altered thyroid state on the in situ mechanical properties of adult cat soleus

To determine the responsiveness of cat hindlimb muscles to thyroid manipulation, adult female cats were made hypothyroid (thyroidectomy plus tapazole treatment), hyperthyroid (synthroid pellets), or maintained euthyroid. After 4 months, the hypothyroid soleus had slower time-to-peak (TPT, 80%) and half-relaxation (HRT) times, whereas the hyperthyroid soleus had faster TPT (20%) and HRT than euthyroid cats. The tension at low stimulation frequencies (5-15 Hz) was higher in hypothyroid and lower in hyperthyroid cats compared to euthyroid cats. Muscle weight, maximum twitch and tetanic (Po) tensions, and maximum rates of shortening (Vmax) were similar across groups. The soleus of hypothyroid cats was more fatigable than normal. The myosin heavy chain (MHC) composition, based on gel electrophoresis, was unaffected by thyroid hormone manipulation. Based on the reaction of monoclonal antibodies for specific MHCs, some fast fibers in the hypothyroid cats coexpressed developmental MHC. These data indicate that 4 months of an altered thyroid state result in changes in the isometric twitch speed properties of the cat soleus, but not the tension-related or isotonic properties. Further, a chronic decrease in thyroid hormone had a greater impact than a chronic increase in thyroid hormone on the mechanical properties of the adult cat soleus. Copyright 2003 S. Karger AG, Basel.

Non-NASA Center

EARLINET evaluation of the CATS Level 2 aerosol backscatter coefficient product

We present the evaluation activity of the European Aerosol Research Lidar Network (EARLINET) for the quantitative assessment of the Level 2 aerosol backscatter coefficient product derived by the Cloud-Aerosol Transport System (CATS) aboard the International Space Station (ISS; Rodier et al., 2015). The study employs correlative CATS and EARLINET backscatter measurements within a 50 km distance between the ground station and the ISS overpass and as close in time as possible, typically with the starting time or stopping time of the EARLINET performed measurement time window within 90 min of the ISS overpass, for the period from February 2015 to September 2016. The results demonstrate the good agreement of the CATS Level 2 backscatter coefficient and EARLINET. Three ISS overpasses close to the EARLINET stations of Leipzig, Germany; Évora, Portugal; and Dushanbe, Tajikistan, are analyzed here to demonstrate the performance of the CATS lidar system under different conditions. The results show that under cloud-free, relative homogeneous aerosol conditions, CATS is in good agreement with EARLINET, independent of daytime and nighttime conditions. CATS low negative biases are observed, partially attributed to the deficiency of lidar systems to detect tenuous aerosol layers of backscatter signal below the minimum detection thresholds; these are biases which may lead to systematic deviations and slight underestimations of the total aerosol optical depth (AOD) in climate studies. In addition, CATS misclassification of aerosol layers as clouds, and vice versa, in cases of coexistent and/or adjacent aerosol and cloud features, occasionally leads to non-representative, unrealistic, and cloud-contaminated aerosol profiles. Regarding solar illumination conditions, low negative biases in CATS backscatter coefficient profiles, of the order of 6.1 %, indicate the good nighttime performance of CATS. During daytime, a reduced signal-to-noise ratio by solar background illumination prevents retrievals of weakly scattering atmospheric layers that would otherwise be detectable during nighttime, leading to higher negative biases, of the order of 22.3 %.

Emmanouil Proestakis

EARLINET Evaluation of the CATS L2 Aerosol Backscatter Coefficient Product

We present the evaluation activity of the European Aerosol Research Lidar Network (EARLINET) for the quantitative assessment of the Level 2 aerosol backscatter coefficient product derived by the Cloud-Aerosol Transport System (CATS) onboard the International Space Station (ISS). The study employs correlative CATS and EARLINET backscatter measurements within 50km distance between the ground station and the ISS overpass and as close in time as possible, typically within 90min, from February 2015 to September 2016. The results demonstrate the good agreement of CATS Level 2 backscatter coefficient and EARLINET. Three ISS overpasses close to the EARLINET stations of Leipzig-Germany, Évora-Portugal and Dushanbe-Tajikistan are analysed here to demonstrate the performance of CATS lidar system under different conditions. The results show that under cloud-free, relative homogeneous aerosol conditions CATS is in good agreement with EARLINET, independently of daytime/nighttime conditions. CATS low negative biases, partially attributed to the deficiency of lidar systems to detect tenuous aerosol layers of backscatter signal below the minimum detection thresholds, may lead to systematic deviations and slight underestimations of the total Aerosol Optical Depth (AOD) in climate studies. In addition, CATS misclassification of aerosol layers as clouds, and vice versa, in cases of coexistent and/or adjacent aerosol and cloud features, may lead to non-representative, unrealistic and cloud contaminated aerosol profiles. The distributions of backscatter coefficient biases show the relatively good agreement between the CATS and EARLINET measurements, although on average underestimations are observed, 22.3% during daytime and 6.1% during nighttime.

EARLINET/CATS evaluation

Covariance Analysis Tool (G-CAT) for Computing Ascent, Descent, and Landing Errors

G-CAT is a covariance analysis tool that enables fast and accurate computation of error ellipses for descent, landing, ascent, and rendezvous scenarios, and quantifies knowledge error contributions needed for error budgeting purposes. Because GCAT supports hardware/system trade studies in spacecraft and mission design, it is useful in both early and late mission/ proposal phases where Monte Carlo simulation capability is not mature, Monte Carlo simulation takes too long to run, and/or there is a need to perform multiple parametric system design trades that would require an unwieldy number of Monte Carlo runs. G-CAT is formulated as a variable-order square-root linearized Kalman filter (LKF), typically using over 120 filter states. An important property of G-CAT is that it is based on a 6-DOF (degrees of freedom) formulation that completely captures the combined effects of both attitude and translation errors on the propagated trajectories. This ensures its accuracy for guidance, navigation, and control (GN&C) analysis. G-CAT provides the desired fast turnaround analysis needed for error budgeting in support of mission concept formulations, design trade studies, and proposal development efforts. The main usefulness of a covariance analysis tool such as G-CAT is its ability to calculate the performance envelope directly from a single run. This is in sharp contrast to running thousands of simulations to obtain similar information using Monte Carlo methods. It does this by propagating the "statistics" of the overall design, rather than simulating individual trajectories. G-CAT supports applications to lunar, planetary, and small body missions. It characterizes onboard knowledge propagation errors associated with inertial measurement unit (IMU) errors (gyro and accelerometer), gravity errors/dispersions (spherical harmonics, masscons), and radar errors (multiple altimeter beams, multiple Doppler velocimeter beams). G-CAT is a standalone MATLAB- based tool intended to run on any engineer's desktop computer.

Boussalis, Dhemetrios

Machine Learning Algorithms for Aerosol and Cloud Detection Using CATS on the ISS

Clouds and aerosols are one of the largest uncertainties in understanding and forecasting the Earth’s changing climate system. The type and height of aerosols are important factors in determining the top-of-atmosphere (TOA) radiation budget, either direct reflection of solar radiation back to space and/or absorption of solar radiation. In addition to their impact on the Earth’s climate system, aerosols near the surface from wildfires, man-made pollution events, and dust storms are hazardous to human health. The phase and height of clouds also play a critical role in determining the role of clouds in the Earth’s climate system. Cirrus clouds in the upper troposphere can induce a significant daytime TOA warming effect, while liquid water clouds near the surface cause a large corresponding cooling effect. Lidar measurements provide accurate vertically resolved information about clouds and aerosols, including complex multi-layer scenes where passive sensors are challenged and at night, when passive sensors are unable to measure cloud and aerosol properties. The Cloud-Aerosol Transport System (CATS) is a lidar instrument that operated for 33 months on the International Space Station (ISS) at the 1064 nm wavelength to measure attenuated total backscatter and depolarization ratio. These fundamental measurements are used to derive “vertical feature mask” cloud and aerosol products, including layer top/base heights, layer geometrical thickness, aerosol type, and cloud phase. While space-based lidar systems like CATS provide cloud and aerosol vertical distributions that improve our understanding of the climate system, averaging of the daytime data from these sensors is required, at the expense of spatial resolution, to improve the daytime signal-to noise (SNR) and thus atmospheric layer detection. This presentation shows results from machine learning (ML) techniques that, when applied to CATS data: 1. improve the 1064 nm SNR 2. enable detection of atmospheric features during daytime with a horizontal resolution of 350 m or 5 km (compared to the 60 km required for standard CATS data products) 3. increase the number of atmospheric layers detected in the CATS data. A Convolutional Neural Network (CNN) trained using CATS standard data products also demonstrated the potential for improved cloud-aerosol discrimination, cloud phase, and aerosol typing compared to the operational CATS algorithms for cloud edges and complex near-surface scenes during daytime. The ML tools described in this paper can facilitate the development of smaller, low-cost lidar systems in the future and enable real-time accessibility of lidar data products from future lidar systems for monitoring and forecasting of hazardous events.

John Yorks

CATS Version 2 Aerosol Feature Detection and Applications for Data Assimilation

The Cloud Aerosol Transport System (CATS) lidar has been operating onboard the International Space Station (ISS) since February 2015 and provides vertical observations of clouds and aerosols using total attenuated backscatter and depolarization measurements. From February March 2015, CATS operated in Mode 1, providing backscatter and depolarization measurements at 532 and 1064 nm. CATS began operation in Mode 2 in March 2015, providing backscatter and depolarization measurements at 1064 nm and has continued to operate to the present in this mode. CATS level 2 products are derived from these measurements, including feature detection, cloud aerosol discrimination, cloud and aerosol typing, and optical properties of cloud and aerosol layers. Here, we present changes to our level 2 algorithms, which were aimed at reducing several biases in our version 1 level 2 data products. These changes will be incorporated into our upcoming version 2 level 2 data release in summer 2017. Additionally, owing to the near real time (NRT) data downlinking capabilities of the ISS, CATS provides expedited NRT data products within 6 hours of observation time. This capability provides a unique opportunity for supporting field campaigns and for developing data assimilation techniques to improve simulated cloud and aerosol vertical distributions in models. We additionally present preliminary work toward assimilating CATS observations into the NASA Goddard Earth Observing System version 5 (GEOS-5) global atmospheric model and data assimilation system.

data assimilation

Development of an operational specific CAT risk (SCATR) index

The original formulations of Roach (1970) and Oard (1974) for the calculation of clear air turbulence (CAT) potential from synoptic scale data were extended. An index which gives a measure of the specific risk of encountering CAT - the specific clear air turbulence risk (SCATR) index - was defined. This index takes into account both the locally and advected contributions to the energy necessary for CAT. The advected contribution is associated with the role of atmospheric gravity waves. The SCATR index was calculated for a number of cases where documented encounters with CAT occurred. Of particular interest were those made for cases involving severe CAT. The results for the two severe CAT cases run were quite impressive and elicited considerable interest from operational aviation meteorologists.

Keller, J. L.

The Diurnal Cycle of Cloud Profiles over Land and Ocean Between 51degS and 51degN, Seen by the CATS Spaceborne Lidar from the International Space Station

We document, for the first time, how detailed vertical profiles of cloud fraction (CF) change diurnally between 51 deg S and 51 deg N, by taking advantage of 15 months of measurements from the Cloud-Aerosol Transport System (CATS) lidar on the non-sun-synchronous International Space Station (ISS). Over the tropical ocean in summer, we find few high clouds during daytime. At night they become frequent over a large altitude range (11-16 km between 22:00 and 04:00 LT). Over the summer tropical continents, but not over ocean, CATS observations reveal mid-level clouds (4-8 km above sea level or a.s.l.) persisting all day long, with a weak diurnal cycle (minimum at noon). Over the Southern Ocean, diurnal cycles appear for the omnipresent low-level clouds (minimum between noon and 15:00) and high-altitude clouds (minimum between 08:00 and 14:00). Both cycles are time shifted, with high-altitude clouds following the changes in low-altitude clouds by several hours. Over all continents at all latitudes during summer, the low-level clouds develop upwards and reach a maximum occurrence at about 2.5 km a.s.l. in the early afternoon (around 14:00). Our work also shows that (1) the diurnal cycles of vertical profiles derived from CATS are consistent with those from ground-based active sensors on a local scale, (2) the cloud profiles derived from CATS measurements at local times of 01:30 and 13:30 are consistent with those observed from CALIPSO at similar times, and (3) the diurnal cycles of low and high cloud amounts (CAs) derived from CATS are in general in phase with those derived from geostationary imagery but less pronounced. Finally, the diurnal variability of cloud profiles revealed by CATS strongly suggests that CALIPSO measurements at 01:30 and 13:30 document the daily extremes of the cloud fraction profiles over ocean and are more representative of daily averages over land, except at altitudes above 10 km where they capture part of the diurnal variability. These findings are applicable to other instruments with local overpass times similar to CALIPSO's, such as all the other A-Train instruments and the future Earth-CARE mission.

Noel, Vincent

Characterizing the Seasonal and Diurnal Aerosol Cycles using CATS Space-Based Lidar

The broader effects aerosols have on the earth and climate system is determined by a host of factors including their composition and vertical distribution. Characterizing the vertical distribution of clouds and aerosols is especially important considering it remains one of the greatest uncertainties in climate predictions. Space-based lidar, such as Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and Cloud-Aerosol Transport System (CATS), is especially well suited as a remote sensing tool in determining this vertical distribution. CALIOP has been used for over a decade to observe the global and vertical distribution of clouds and aerosols but is limited by Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations’ (CALIPSO’s) polar orbit to set equatorial crossing times of ~1:30AM/PM. This limited temporal sampling limits the use of CALIOP in determining the full diurnal variability of clouds and aerosols. On the International Space Station (ISS), with its inclined orbit and variable equatorial crossing times, the CATS lidar provided an opportunity to study the vertical profile of clouds and aerosols at a variety of local times. With this 33-month CATS record, we show that CATS captured the seasonal changes in global aerosol distributions and compares favorably with other instruments and models. Specifically targeting biomass burning regions, we also find CATS could observe the documented diurnal cycle in aerosol altitudes with some caveats. With the next generation of proposed space-based lidars including designs in similar orbits as the ISS and CATS, future studies of the aerosol diurnal and seasonal cycles would also be possible.

Kenneth Christian

Changes in plasma vasopressin during motion sickness in cats

Changes in levels of plasma vasopressin (AVP) and cortisol (C) have been shown to be correlated with motion sickness and nausea in man. As part of the research aimed at validation of the cat as an appropriate animal model for motion sickness research, levels of these hormones were investigated in the cat during motion sickness elicited by vertical linear acceleration of approximately 0.6 Hz and 1 +/- 0.6 G. In Study 1, 15 cats previously screened for susceptibility to motion sickness were prepared with indwelling jugular catheters to permit withdrawl of blood with minimal disruption of the stimulus and minimum stress to the animal. AVP and C were measured in blood samples obtained during exposure to vertical linear acceleration and during control sessions in which the animals were placed in the stationary apparatus. 10 min and 1 min prior to duration; 1, 5, 10, and 20 min after start of motion. Total duration of exposure to motion was 20 min. The data indicate that both AVP and C are elevated during exposure to motion if emesis occurs. AVP reaches maximum levels during or about the same time as emesis, while C increases gradually throughout the period of vertical acceleration. In Study 2, four cats were prepared with indwelling catheters and AVP was measured in blood withdrawn during exposure to the vertical linear acceleration. A single pre-motion sample consisting of three samples drawn 5 min prior to motion onset. Two series of samples consisting of three samples drawn at 3-min intervals were obtained during motion. The first series was initiated at emesis, and the second 25 min after emesis. Results show that levels of circulating AVP were elevated (2 to 27 times the control and pre-motion levels) in the samples taken during emesis and decreased, but remained 1 to 6 times above the pre-motion or control levels within 25 min. The results of these two studies indicate that AVP is elevated during motion-produced emesis than is C. These findings are in general agreement with those obtained from humans under motion sickness conditions, and indicate that it is appropriate to continue to use the cat in studies of hormone changes during motion sickness.

R Fox

Conditioned taste aversion and motion sickness in cats and squirrel monkeys

The relationship between vomiting and conditioned taste aversion was studied in intact cats and squirrel monkeys and in cats and squirrel monkeys in which the area postrema was ablated by thermal cautery. In cats conditioned 7-12 months after ablation of the area postrema, three successive treatments with xylazine failed to produce either vomiting or conditioned taste aversion to a novel fluid. Intact cats, however, vomited and formed a conditioned aversion. In squirrel monkeys conditioned 6 months after ablation of the area postrema, three treatments with lithium chloride failed to produce conditioned taste aversion. Intact monkeys did condition with these treatments. Neither intact nor ablated monkeys vomited or evidenced other signs of illness when injected with lithium chloride. When the same ablated cats and monkeys were exposed to a form of motion that produced vomiting prior to surgery, conditioned taste aversion can be produced after ablation of the area postrema. The utility of conditioned taste aversion as a measure of subemetic motion sickness is discussed by examining agreement and disagreement between identifications of motion sickness by conditioned taste aversion and vomiting. It is suggested that a convincing demonstration of the utility of conditioned taste aversion as a measure of nausea requires the identification of physiological correlates of nausea, and caution should be exercised when attempting to interpret conditioned taste aversion as a measure of nausea.

area postrema

CATS Near Real Time Data Products: Applications for Assimilation Into the NASA GEOS-5 AGCM

From February 2015 through October 2017, the NASA Cloud-Aerosol Transport System (CATS) backscatter lidar operated on the International Space Station (ISS) as a technology demonstration for future Earth Science Missions, providing vertical measurements of cloud and aerosols properties. Owing to its location on the ISS, a cornerstone technology demonstration of CATS was the capability to acquire, process, and disseminate near-real time (NRT) data within 6 hours of observation time. CATS NRT data has several applications, including providing notification of hazardous events for air traffic control and air quality advisories, field campaign flight planning, as well as for constraining cloud and aerosol distributions in via data assimilation in aerosol transport models. Â Recent developments in aerosol data assimilation techniques have permitted the assimilation of aerosol optical thickness (AOT), a 2-dimensional column integrated quantity that is reflective of the simulated aerosol loading in aerosol transport models. While this capability has greatly improved simulated AOT forecasts, the vertical position, a key control on aerosol transport, is often not impacted when 2-D AOT is assimilated. Here, we present preliminary efforts to assimilate CATS aerosol observations into the NASA Goddard Earth Observing System version 5 (GEOS-5) atmospheric general circulation model and assimilation system using a 1-D Variational (1-D VAR) ensemble approach, demonstrating the utility of CATS for future Earth Science Missions.

Hlavka, D. L.

Microstructural Evolution of the Civet Cat Norite (72255)

The ‘Civet Cat Norite’ is a ~ 2.5 cm clast within the Apollo impact melt breccia sample 72255 collected during Apollo 17 EVA 2 at Boulder 1. The norite is primarily composed of plagioclase and orthopyroxene with fine-scale exsolution lamellae of augite. The plagioclase and orthopyroxene (OPX) coexist with minor quartz and augitic clinopyroxene (CPX), and accessory apatite, baddeleyite, chromite, ilmenite, loveringite, merrillite, rutile and zircon. The major minerals range from 1 to 4 mm in size and show a cataclastic texture indicated by banding of the light and dark phases]. The chemical composition of the orthopyroxene, augitic exsolution lamellae, and exsolved oxides suggest the norite crystallized in the lower crust of the Moon (10 – 70 km depth) and was subsequently excavated by impact(s). Shock pressure estimates for the norite range from 15 – 35 GPa based on maskeleynite formation within the plagioclase, kink banding in pyroxenes, and granular recrystallization in the accessory phosphates. Previous Rb-Sr and 40 Ar/ 39 Ar analyses recalculated with modern decay constants yield relatively young ages of 4.16 ± 0.05 Ga and 3.99 ± 0.03 Ga, respectively. However, recent U-Pb analyses of some zircon grains from within the Civet Cat yield an age of 4.45 ± 0.03 Ga. While this is the oldest age for any rock recovered from the Moon, the full age spread of zircon from the Civet Cat range from ca. 4.46 to 4.02 Ga, indicating variable Pb-loss and complicating interpretation of the primary age. Recent atom probe analyses indicate minimal Pb mobilization within the oldest zircon grain from Civet Cat, supporting the interpretation that these ancient zircon ages reflect the age of the norite, rather than an apparent antiquity caused by reverse discordance. To investigate the potential antiquity and deep crustal origin of the Civet Cat norite, we have undertaken high resolution microstructural analyses of the major, minor, and accessory minerals to characterize the primary igneous textures and secondary overprinting by impact and metamorphism. The employed analytical techniques include scanning electron microscope-based electron backscatter diffraction (EBSD) analyses, electron probe microanalyzer (EPMA) chemical analyses, and transmission electron microscopy (TEM) of pyroxene, plagioclase, quartz, zircon, and phosphates.

T M Erickson

CATS Version 2 Aerosol Feature Detection and Applications for Data Assimilation

Using GEOS-5, we are developing a 1D ENS approach for assimilating CATS near real time observations of total attenuated backscatter at 1064 nm: a) After performing a 1-ENS assimilation of a cloud-free profile, the GEOS-5 analysis closely followed observed total attenuated backscatter. b) Vertical localization length scales were varied for the well-mixed PBL and the free troposphere After assimilating a cloud free segment of a CATS granule, the fine detail of a dust event was obtained in the GEOS-5 analysis for both total attenuated backscatter and extinction. Future Work: a) Explore horizontal localization and test within a cloudy aerosol layer. b) Address noisy analysis increments in the free troposphere where both CATS and GEOS-5 aerosol loadings are low. c) Develop a technique to screen CATS ground return from profiles. d) "Dynamic" lidar ratio that will evolve in conjunction with simulated aerosol mixtures.

Cloud Aerosol Transport