The OCO‐2 oxygen A‐band response to liquid marine cloud properties from CALIPSO and MODIS
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Mark Richardson↗
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On the Frequency of Occurrence of the Ice Phase in Supercooled Southern Ocean Low Clouds Derived From CALIPSO and CloudSat
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Gerald G. Mace↗
CloudSat - From the A-Train to the C-Train
The CloudSat satellite was launched from Vandenberg Air Force Base, in California, on April 28, 2006. It was launched with the CALIPSO satellite, a joint mission between the National Aeronautics and Space Administration (NASA) and the Centre National D'Etudes Spatiales (CNES). CloudSat and CALIPSO were designed to fly in formation with each other, to combine their complimentary scientific measurements. The two missions were maneuvered into the Earth Science Afternoon Constellation (A-Train) shortly after launch and have flown in formation together since then. Originally designed to fly for 22 months, the CloudSat satellite has far exceeded expectations. Inflight anomalies on CloudSat necessitated changes to both the daily concept of operations and formation flying operations with CALIPSO. In 2011, a severe battery anomaly restricted CloudSat science data collection and maneuverability to the sunlit portions of the orbit. In 2017, CloudSat suffered a reaction wheel failure, triggering the criteria established to exit the A-Train. CloudSat successfully exited the A-Train in early 2018, suspending formation flying and joint science observations with CALIPSO. The joint CloudSat/CALIPSO science team continued collaboration with discussions focused on resuming joint observations. As both satellites were aging and CALIPSO was nearing the exhaustion of satellite propellant, the decision was made to lower CloudSat to the CALIPSO graveyard orbit, to be joined by CALIPSO as soon as feasible. With NASA’s approval, CloudSat was maneuvered to the lower orbit over the course of several months in mid-2018. Once CloudSat was in place, and with approval from CNES, CALIPSO began the delicate dance of lowering their orbit and re-aligning the satellite ground tracks. CloudSat and CALIPSO resumed formation flying in the newly dubbed C-Train (CloudSat and CALIPSO) orbit in the Fall of 2018. The ingenuity of the CloudSat and CALIPSO teams made the concept of the C-Train a reality. This paper will discuss the decision processes and the operational challenges the CloudSat flight team faced while designing and implementing the C-Train.
Witkowski, M.M.↗
Non Radiation Hardened Microprocessors in Spaced Based Remote Sensing Systems
The CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) mission is a comprehensive suite of active and passive sensors including a 20Hz 230mj Nd:YAG lidar, a visible wavelength Earth-looking camera and an imaging infrared radiometer. CALIPSO flies in formation with the Earth Observing System Post-Meridian (EOS PM) train, provides continuous, near-simultaneous measurements and is a planned 3 year mission. CALIPSO was launched into a 98 degree sun synchronous Earth orbit in April of 2006 to study clouds and aerosols and acquires over 5 gigabytes of data every 24 hours. The ground track of one CALIPSO orbit as well as high and low intensity South Atlantic Anomaly outlines is shown. CALIPSO passes through the SAA several times each day. Spaced based remote sensing systems that include multiple instruments and/or instruments such as lidar generate large volumes of data and require robust real-time hardware and software mechanisms and high throughput processors. Due to onboard storage restrictions and telemetry downlink limitations these systems must pre-process and reduce the data before sending it to the ground. This onboard processing and realtime requirement load may mean that newer more powerful processors are needed even though acceptable radiation-hardened versions have not yet been released. CALIPSO's single board computer payload controller processor is actually a set of four (4) voting non-radiation hardened COTS Power PC 603r's built on a single width VME card by General Dynamics Advanced Information Systems (GDAIS). Significant radiation concerns for CALIPSO and other Low Earth Orbit (LEO) satellites include the South Atlantic Anomaly (SAA), the north and south poles and strong solar events. Over much of South America and extending into the South Atlantic Ocean the Van Allen radiation belts dip to just 200-800km and spacecraft entering this area are subjected to high energy protons and experience higher than normal Single Event Upset (SEU) and Single Event Latch-up (SEL) rates. Although less significant, spacecraft flying in the area around the poles experience similar upsets. Finally, powerful solar proton events in the range of 10MeV/10pfu to 100MeV/1pfu as are forecasted and tracked by NOAA's Space Environment Center in Colorado can result in Single Event Upset (SEU), Single Event Latch-up (SEL) and permanent failures such as Single Event Gate Rupture (SEGR) in some technologies. (Galactic Cosmic Rays (GCRs) are another source, especially for gate rupture) CALIPSO mitigates common radiation concerns in its data handling through the use of redundant processors, radiation-hardened Application Specific Integrated Circuits (ASIC), hardware-based Error Detection and Correction (EDAC), processor and memory scrubbing, redundant boot code and mirrored files. After presenting a system overview this paper will expand on each of these strategies. Where applicable, related on-orbit data collected since the CALIPSO initial boot on May 4, 2006 will be noted.
Decoursey, Robert J.↗
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↗
Mapping Modeled Aerosol Species to Measured Lidar Ratios for the MIRA Project
Overarching goal: Create Climatological Lidar Ratio Maps for CALIPSO - Since CALIPSO is an elastic backscatter lidar, it is necessary to select a priori aerosol lidar ratios prior to computing extinction profiles. - Presently, the CALIPSO lidar ratio selection process uses a single lidar ratio for each of the 7 CALIPSO aerosol types in the troposphere. - Consequently, regional and seasonal variability of the lidar ratio is very limited in the present CALIPSO algorithm. - Here, we describe an approach for creating new climatological lidar ratio maps for each of the CALIPSO aerosol types using MODIS-CALIPSO constrained retrievals and global model simulations. - The purpose is to eventually replace the seven single-valued lidar ratios for the CALIPSO types with latitude- and longitude-dependent maps for each of the seven types.
G. L. Schuster↗
TPSAS-NF1676L-11678-DND
Cloud vertical profiles retrieved from CALIPSO and CloudSat data provide additional information that greatly improves the estimate of atmospheric radiative heating rates and potentially improves the estimate of the global surface radiation budget. To utilize CALIPSO and CloudSat cloud vertical profiles, we combined their profiles and generated merged profiles. Weused the merged cloud profiles and MODIS derived cloud profiles by the CERES cloud algorithm in irradiance computations. In this study, the improvement of the irradiance by CALIPSO and CloudSat derived merged cloud vertical profiles is evaluated by comparing modeled irradiances with and without merged cloud profiles. Because of lower cloud base heights provided by the merged profiles compared with cloud base heights derived from an empirical formula using the MODIS derived cloud top height and optical thickness, the global annual mean surface longwave downward irradiance increases approximately by 7 Wm-2. While CALIPSO version 3 data have not been incorporated in the irradiance computation and the effect of the new CALIPSO data needs to be assessed, a comparison with surface observations suggests an improvement of surface downward longwave irradiance computations. The surface downward longwave irradiance computed with CALIPSO and CloudSat merged clouds agrees better with surface observations than the irradiance computed with MODIS only does. The bias difference over ARM SGP sites with 2 years of data decreases from -5 W m-2to -2 Wm-2, and it decreases from -9 Wm-2to no bias over polar validation sites. The result suggests that CALIPSO CloudSat derived merged clouds significantly improve surface longwave irradiance estimates once they are combined with MODIS derived cloud properties and with temperature and humidity profiles from reanalysis.
Seiji Kato↗
Mapping Aerosol Lidar Ratios Over Ocean using MODIS AOD Constrained Retrievals and GOCART Model Simulations
After 17 years, the NASA Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission ceased science operations in August 2023. For the final CALIPSO data products release (Version 5), the CALIPSO project seeks to improve the accuracy of its aerosol extinction by advancing knowledge of aerosol lidar ratios (i.e., extinction-to-backscatter ratios; LRs) for various aerosol types. The current algorithm assigns one LR value globally for each of the seven tropospheric aerosol types. The CALIPSO team aims to improve the retrieval algorithm through the development of regional and seasonal LR climatologies for the same aerosol types. In this study, aerosol LRs are inferred through Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) backscatter profiles constrained by collocated aerosol optical depth (AOD) from Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data over oceans during daytime. This analysis is subsampled for those profiles that are cloud-free and contain only one CALIOP-classified aerosol type. The CALIOP profiles are then collocated with aerosol volume fractions obtained through Goddard Chemistry Aerosol Radiation and Transport (GOCART) model simulations. This presentation will reveal findings that the 12-year (June 2006-August 2018) mean spatial distributions of inferred aerosol LRs for CALIOP-classified marine and dusty marine aerosols correspond inversely with patterns of GOCART sea salt volume fraction (SSVF). For example, smaller SSVFs (< 65%) and larger LRs (> 55 sr), are found near land masses (Fig. 1). This indicates the influence of advected anthropogenic aerosols (e.g., pollution and biomass burning smoke). In the remote oceans (i.e., regions likely less impacted by non-sea salt aerosols), the SSVFs are larger (> 95%) and the LRs are smaller (< 25 sr) (Fig. 1). A polynomial fit of the MODIS AOD constrained LRs to the corresponding GOCART SSVFs (intersect values of ~58 sr for SSVF of 0% and ~21 sr for SSVF of 100%) is further used to produce model-assisted climatological LR maps on seasonal scales. Additionally, we will show results of a LR validation analysis for which we compare the revised CALIPSO AODs obtained by applying the seasonal/regional constrained LRs against CALIPSO Version 4.51 Ocean Derived Column Optical Depth (ODCOD). While the majority of the presentation will focus on LRs for CALIOP-classified marine and dusty marine aerosols, an overview of LR results will show preliminary results for other aerosol types over ocean, such as dust and elevated smoke. The technique demon-strated in this study highlights the benefits not only to the final planned CALIPSO data release in 2025, but similar methods can be applied to future spaceborne elastic backscatter lidars with collocated passive sensors (e.g., such as those associated with NASA’s proposed Atmosphere Observing System).
Travis D Toth↗
Retrievals of Profiles of Fine And Coarse Aerosols Using Lidar And Radiometric Space Measurements
In couple of years we expect the launch of the CALIPSO lidar spaceborne mission designed to observe aerosols and clouds. CALIPSO will collect profiles of the lidar attenuated backscattering coefficients in two spectral wavelengths (0.53 and 1.06 microns). Observations are provided along the track of the satellite around the globe from pole to pole. The attenuated backscattering coefficients are sensitive to the vertical distribution of aerosol particles, their shape and size. However the information is insufficient to be mapped into unique aerosol physical properties and vertical distribution. Infinite number of physical solutions can reconstruct the same two wavelength backscattered profile measured from space. CALIPSO will fly in formation with the Aqua satellite and the MODIS spectro-radiometer on board. Spectral radiances measured by MODIS in six channels between 0.55 and 2.13 microns simultaneously with the CALIPSO observations can constrain the solutions and resolve this ambiguity, albeit under some assumptions. In this paper we describe the inversion method and apply it to aircraft lidar and MODIS data collected over a dust storm off the coast of West Africa during the SHADE experiment. It is shown that the product of the single scattering albedo, omega, and the phase function, P, for backscattering can be retrieved from the synergism between measurements avoiding a priori hypotheses required for inverting lidar measurements alone. The resultant value of (omega)P(180 deg.) = 0.016/sr are significantly different from what is expected using Mie theory, but are in good agreement with recent results obtained from lidar observations of dust episodes. The inversion is robust in the presence of noise of 10% and 20% in the lidar signal in the 0.53 and 1.06 pm channels respectively. Calibration errors of the lidar of 5 to 10% can cause an error in optical thickness of 20 to 40% respectively in the tested cases. The lidar calibration errors cause degradation in the ability to fit the MODIS data. Therefore the MODIS measurements can be used to identify the calibration problem and correct for it. The CALIPSO-MODIS measurements of the profiles of fine and coarse aerosols, together with CALIPSO measurements of clouds vertical distribution, is expected to be critically important in understanding aerosol transport across continents and political boundaries, and to study aerosol-cloud interaction and its effect on precipitation and global forcing of climate.
Kaufman, Yoram↗
Quantifying Above-Cloud Aerosols through Integrating Multi-Sensor Measurements from A-Train Satellites
Quantifying above-cloud aerosols can help improve the assessment of aerosol intercontinental transport and climate impacts. Large-scale measurements of aerosol above low-level clouds had been generally unexplored until very recently when CALIPSO lidar started to acquire aerosol and cloud profiles in June 2006. Despite CALIPSO s unique capability of measuring above-cloud aerosol optical depth (AOD), such observations are substantially limited in spatial coverage because of the lidar s near-zero swath. We developed an approach that integrates measurements from A-Train satellite sensors (including CALIPSO lidar, OMI, and MODIS) to extend CALIPSO above-cloud AOD observations to substantially larger areas. We first examine relationships between collocated CALIPSO above-cloud AOD and OMI absorbing aerosol index (AI, a qualitative measure of AOD for elevated dust and smoke aerosol) as a function of MODIS cloud optical depth (COD) by using 8-month data in the Saharan dust outflow and southwest African smoke outflow regions. The analysis shows that for a given cloud albedo, above-cloud AOD correlates positively with AI in a linear manner. We then apply the derived relationships with MODIS COD and OMI AI measurements to derive above-cloud AOD over the whole outflow regions. In this talk, we will present spatial and day-to-day variations of the above-cloud AOD and the estimated direct radiative forcing by the above-cloud aerosols.
Zhang, Yan↗
Vertical Profiles of Aerosol Optical Properties Over Central Illinois and Comparison with Surface and Satellite Measurements
Between June 2006 and September 2009, an instrumented light aircraft measured over 400 vertical profiles of aerosol and trace gas properties over eastern and central Illinois. The primary objectives of this program were to (1) measure the in situ aerosol properties and determine their vertical and temporal variability and (2) relate these aircraft measurements to concurrent surface and satellite measurements. Underflights of the CALIPSO satellite show reasonable agreement in a majority of retrieved profiles between aircraft-measured extinction at 532 nm (adjusted to ambient relative humidity) and CALIPSO-retrieved extinction, and suggest that routine aircraft profiling programs can be used to better understand and validate satellite retrieval algorithms. CALIPSO tended to overestimate the aerosol extinction at this location in some boundary layer flight segments when scattered or broken clouds were present, which could be related to problems with CALIPSO cloud screening methods. The in situ aircraft-collected aerosol data suggest extinction thresholds for the likelihood of aerosol layers being detected by the CALIOP lidar. These statistical data offer guidance as to the likelihood of CALIPSO's ability to retrieve aerosol extinction at various locations around the globe.
Sheridan P. J.↗
A Super-Resolution Laser Altimetry Concept
A super-resolution laser altimetry technique has been proposed to provide improved lidar altimetry from Cloud Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) lidar data, and it is applicable to other similar atmospheric profiling lidar with low-pass filters. To achieve high altimetry resolution, the new technique relies on an empirical relationship between the peak signal ratio and the distance between land surface and the peak signal range bin center, which is directly derived from the CALIPSO lidar measurements and does not require the CALIPSO's transient response. The CALIPSO surface elevation results in Northern America retrieved by the new technique agree with the National Elevation Database high resolution elevation maps, and the comparisons suggest that the precision of the technique is much better than 1.4 m. The preliminary data product of land surface elevation retrieved by the new technique from CALIPSO lidar measurements is available to the altimetry community for evaluation.
Lu, Xiaomei↗
TPSAS-NF1676L-34683-DND
The lidar on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission, makes robust measurements of dust and has generated a length of record that is significant both seasonally and inter-annually. We exploit this record to determine a multi-year climatology of the properties of Middle Eastern dust in the vicinity of Kuwait City. In particular seasonal optical depths of dust gridded in accordance with the Level 3 data products protocol between 2006 and 2015. The data are screened using standard CALIPSO quality assurance flags, cloud aerosol discrimination (CAD) scores, overlying features and layer properties. CALIPSO is collaboration between NASA and Centre National d’Études Spatiales (CNES), was launched in April 2006 to provide vertically resolved measurements of cloud and aerosol distributions. The primary instrument on the CALIPSO satellite is the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), a near-nadir viewing two-wavelength polarization-sensitive instrument. In addition to CALIPSO, we use the AErosol RObotic NETwork (AERONET) sites in the region to identify extreme dust events such as Sand and Dust Storms (SDS). The lidar measurements of the vertical location of the layers along with predominant prevailing wind vectors will enable identification of dust sources and inform mitigation solutions for extreme SDS.
Ali H Omar↗
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↗
Clear-Sky Remote Sensing in the Vicinity of Clouds: What Can Be Learned About Aerosol Changes?
Studies on aerosol direct and indirect effects require a precise separation of cloud-free and cloudy air. However, separation between cloud-free and cloudy areas from remotely-sensed measurements is ambiguous. The transition zone in the regions around clouds often stretches out tens of km, which are neither precisely clear nor precisely cloudy. We study the transition zone between cloud-free and cloudy air using MODerate-resolution Imaging Spectroradiometer (MODIS) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) measurements. Both instruments show enhanced clear-sky reflectance (MODIS) and clear-sky backscatterer (CALIPSO) near clouds. Analyzing a large dataset of MODIS observations we examine the effect of three-dimensional (3D) radiative interactions between clouds and cloud-free areas, also known as a cloud adjacency effect. Comparing with CALIPSO clear-sky backscatterer measurements, we show that the cloud adjacency effect may be responsible for a large portion of the enhanced clear sky reflectance observed by MODIS. While aerosol particles are responsible for a large part of the near-cloud enhancements in CALIPSO observations, misidentified or undetected cloud particles are also likely to contribute. As a result, both the nature of these particles (cloud vs. aerosol) and the processes creating them need to be clarified using a quantitative assessment of remote sensing limitations in particle detection and identification. "The width and ubiquity of the transition zone near clouds imply that studies of-aerosol-cloud -interactions and aerosol direct radiative effects need to account for aerosol changes near clouds. Not accounted, these changes can cause systematic biases toward smaller aerosol radiative forcing. On the other hand, including aerosol products near clouds despite their uncertainties may overestimate aerosol radiative forcing. Therefore, there is an urgent need for developing methods that can assess and account for remote sensing challenges and thus allow for including the transition zone into the study. We describe a simple model that estimates the cloud-induced enhanced reflectances of cloud-free areas in the vicinity of clouds. The model assumes that the enhancement is due entirely to Rayleigh scattering and is therefore bigger at shorter wavelengths, thus creating a so-called apparent "bluing" of aerosols in remote sensing retrievals.
Marshak, Alexander↗
The Cloud-Aerosol Transport System (CATS): a New Lidar for Aerosol and Cloud Profiling from the International Space Station
Spaceborne lidar profiling of aerosol and cloud layers has been successfully implemented during a number of prior missions, including LITE, ICESat, and CALIPSO. Each successive mission has added increased capability and further expanded the role of these unique measurements in wide variety of applications ranging from climate, to air quality, to special event monitoring (ie, volcanic plumes). Many researchers have come to rely on the availability of profile data from CALIPSO, especially data coincident with measurements from other A-Train sensors. The CALIOP lidar on CALIPSO continues to operate well as it enters its fifth year of operations. However, active instruments have more limited lifetimes than their passive counterparts, and we are faced with a potential gap in lidar profiling from space if the CALIOP lidar fails before a new mission is operational. The ATLID lidar on EarthCARE is not expected to launch until 2015 or later, and the lidar component of NASA's proposed Aerosols, Clouds, and Ecosystems (ACE) mission would not be until after 2020. Here we present a new aerosol and cloud lidar that was recently selected to provide profiling data from the International Space Station (ISS) starting in 2013. The Cloud-Aerosol Transport System (CATS) is a three wavelength (1064, 532, 355 nm) elastic backscatter lidar with HSRL capability at 532 nm. Depolarization measurements will be made at all wavelengths. The primary objective of CATS is to continue the CALIPSO aerosol and cloud profile data record, ideally with overlap between both missions and EarthCARE. In addition, the near real time data capability of the ISS will enable CATS to support operational applications such as air quality and special event monitoring. The HSRL channel will provide a demonstration of technology and a data testbed for direct extinction retrievals in support of ACE mission development. An overview of the instrument and mission will be provided, along with a summary of the science objectives and simulated data.
Welton, Ellsworth J.↗
The Cloud-Aerosol Transport System (CATS): A New Lidar for Aerosol and Cloud Profiling from the International Space Station
Spaceborne lidar profiling of aerosol and cloud layers has been successfully implemented during a number of prior missions, including LITE, ICESat, and CALIPSO. Each successive mission has added increased capability and further expanded the role of these unique measurements in wide variety of applications ranging from climate, to air quality, to special event monitoring (ie, volcanic plumes). Many researchers have come to rely on the availability of profile data from CALIPSO, especially data coincident with measurements from other A-Train sensors. The CALIOP lidar on CALIPSO continues to operate well as it enters its fifth year of operations. However, active instruments have more limited lifetimes than their passive counterparts, and we are faced with a potential gap in lidar profiling from space if the CALIOP lidar fails before a new mission is operational. The ATLID lidar on EarthCARE is not expected to launch until 2015 or later, and the lidar component of NASA's proposed Aerosols, Clouds, and Ecosystems (ACE) mission would not be until after 2020. Here we present a new aerosol and cloud lidar that was recently selected to provide profiling data from the International Space Station (ISS) starting in 2013. The Cloud-Aerosol Transport System (CATS) is a three wavelength (1064,532,355 nm) elastic backscatter lidar with HSRL capability at 532 nm. Depolarization measurements will be made at all wavelengths. The primary objective of CATS is to continue the CALIPSO aerosol and cloud profile data record, ideally with overlap between both missions and EarthCARE. In addition, the near real time (NRT) data capability ofthe ISS will enable CATS to support operational applications such as aerosol and air quality forecasting and special event monitoring. The HSRL channel will provide a demonstration of technology and a data testbed for direct extinction retrievals in support of ACE mission development. An overview of the instrument and mission will be provided, along with a summary of the science objectives and simulated data. Input from the ICAP community is desired to help plan our NRT mission goals and interactions with ICAP forecasters.
Welton, Ellsworth J.↗
Application of High-Dimensional Fuzzy K-Means Cluster Analysis to CALIOP/CALIPSO Version 4.1 Cloud-Aerosol Discrimination
This study applies fuzzy k-means (FKM) cluster analyses to a subset of the parameters reported in the CALIPSO lidar level 2 data products in order to classify the layers detected as either clouds or aerosols. The results obtained are used to assess the reliability of the cloud–aerosol discrimination (CAD) scores reported in the version 4.1 release of the CALIPSO data products. FKM is an unsupervised learning algorithm, whereas the CALIPSO operational CAD algorithm (COCA) takes a highly supervised approach. Despite these substantial computational and architectural differences, our statistical analyses show that the FKM classifications agree with the COCA classifications for more than 94 % of the cases in the troposphere. This high degree of similarity is achieved because the lidar-measured signatures of the majority of the clouds and the aerosols are naturally distinct, and hence objective methods can independently and effectively separate the two classes in most cases. Classification differences most often occur in complex scenes (e.g., evaporating water cloud filaments embedded in dense aerosol) or when observing diffuse features that occur only intermittently (e.g., volcanic ash in the tropical tropopause layer). The two methods examined in this study establish overall classification correctness boundaries due to their differing algorithm uncertainties. In addition to comparing the outputs from the two algorithms, analysis of sampling, data training, performance measurements, fuzzy linear discriminants, defuzzification, error propagation, and key parameters in feature type discrimination with the FKM method are further discussed in order to better understand the utility and limits of the application of clustering algorithms to space lidar measurements. In general, we find that both FKM and COCA classification uncertainties are only minimally affected by noise in the CALIPSO measurements, though both algorithms can be challenged by especially complex scenes containing mixtures of discrete layer types. Our analysis results show that attenuated backscatter and color ratio are the driving factors that separate water clouds from aerosols; backscatter intensity, depolarization, and mid-layer altitude are most useful in discriminating between aerosols and ice clouds; and the joint distribution of backscatter intensity and depolarization ratio is critically important for distinguishing ice clouds from water clouds.
Zeng, Shan↗