Brian Getzewich

Fully Automated Detection of Cloud and Aerosol Layers in the CALIPSO Lidar Measurements

Abstract Accurate knowledge of the vertical and horizontal extent of clouds and aerosols in the earth’s atmosphere is critical in assessing the planet’s radiation budget and for advancing human understanding of climate change issues. To retrieve this fundamental information from the elastic backscatter lidar data acquired during the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission, a selective, iterated boundary location (SIBYL) algorithm has been developed and deployed. SIBYL accomplishes its goals by integrating an adaptive context-sensitive profile scanner into an iterated multiresolution spatial averaging scheme. This paper provides an in-depth overview of the architecture and performance of the SIBYL algorithm. It begins with a brief review of the theory of target detection in noise-contaminated signals, and an enumeration of the practical constraints levied on the retrieval scheme by the design of the lidar hardware, the geometry of a space-based remote sensing pl...

The CALIPSO Lidar Cloud and Aerosol Discrimination: Version 2 Algorithm and Initial Assessment of Performance

Abstract The Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite was launched in April 2006 to provide global vertically resolved measurements of clouds and aerosols. Correct discrimination between clouds and aerosols observed by the lidar aboard the CALIPSO satellite is critical for accurate retrievals of cloud and aerosol optical properties and the correct interpretation of measurements. This paper reviews the theoretical basis of the CALIPSO lidar cloud and aerosol discrimination (CAD) algorithm, and describes the enhancements made to the version 2 algorithm that is used in the current data release (release 2). The paper also presents a preliminary assessment of the CAD performance based on one full day (12 August 2006) of expert manual classification and on one full month (July 2006) of the CALIOP 5-km cloud and aerosol layer products. Overall, the CAD algorithm works well in most cases. The 1-day manual verification suggests that the success rate is in the neighborh...

Assessment of Global Cloud Datasets from Satellites: Project and Database Initiated by the GEWEX Radiation Panel

Clouds cover about 70% of Earths surface and play a dominant role in the energy and water cycle of our planet. Only satellite observations provide a continuous survey of the state of the atmosphere over the entire globe and across the wide range of spatial and temporal scales that compose weather and climate variability. Satellite cloud data records now exceed more than 25 years; however, climate data records must be compiled from different satellite datasets and can exhibit systematic biases. Questions therefore arise as to the accuracy and limitations of the various sensors and retrieval methods. The Global Energy and Water Cycle Experiment (GEWEX) Cloud Assessment, initiated in 2005 by the GEWEX Radiation Panel (GEWEX Data and Assessment Panel since 2011), provides the first coordinated intercomparison of publicly available, standard global cloud products (gridded monthly statistics) retrieved from measurements of multispectral imagers (some with multiangle view and polarization capabilities), IR soun...

Comparison of Two Different Cloud Climatologies Derived from CALIOP-Attenuated Backscattered Measurements (Level 1): The CALIPSO-ST and the CALIPSO-GOCCP

AbstractTwo different cloud climatologies have been derived from the same NASA–Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP)-measured attenuated backscattered profile (level 1, version 3 dataset). The first climatology, named Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations–Science Team (CALIPSO-ST), is based on the standard CALIOP cloud mask (level 2 product, version 3), with the aim to document clouds with the highest possible spatiotemporal resolution, taking full advantage of the CALIOP capabilities and sensitivity for a wide range of cloud scientific studies. The second climatology, named GCM-Oriented CALIPSO Cloud Product (CALIPSO-GOCCP), is aimed at a single goal: evaluating GCM prediction of cloudiness. For this specific purpose, it has been designed to be fully consistent with the CALIPSO simulator included in the Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP) used within version 2 of the CFMIP (CFMIP-2) experiment and phase...

Using in-situ airborne measurements to evaluate three cloud phase products derived from CALIPSO

We compare the cloud detection and cloud phase determination of three independent climatologies based on Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) to airborne in situ measurements. Our analysis of the cloud detection shows that the differences between the satellite and in situ measurements mainly arise from three factors. First, averaging CALIPSO Level l data along track before cloud detection increases the estimate of high- and low-level cloud fractions. Second, the vertical averaging of Level 1 data before cloud detection tends to artificially increase the cloud vertical extent. Third, the differences in classification of fully attenuated pixels among the CALIPSO climatologies lead to differences in the low-level Arctic cloud fractions. In another section, we compare the cloudy pixels detected by colocated in situ and satellite observations to study the cloud phase determination. At midlatitudes, retrievals of homogeneous high ice clouds by CALIPSO data sets are very robust (more than 94.6% of agreement with in situ). In the Arctic, where the cloud phase vertical variability is larger within a 480 m pixel, all climatologies show disagreements with the in situ measurements and CALIPSO-General Circulation Models-Oriented Cloud Product (GOCCP) report significant undefined-phase clouds, which likely correspond to mixed-phase clouds. In all CALIPSO products, the phase determination is dominated by the cloud top phase. Finally, we use global statistics to demonstrate that main differences between the CALIPSO cloud phase products stem from the cloud detection (horizontal averaging, fully attenuated pixels) rather than the cloud phase determination procedures.

Retrieval of Ocean Subsurface Particulate Backscattering Coefficient from Space-Borne CALIOP Lidar Measurement

A new approach has been proposed to determine ocean subsurface particulate backscattering coefficient bbp from CALIOP 30° off-nadir lidar measurements. The new method also provides estimates of the particle volume scattering function at the 180° scattering angle. The CALIOP based layer-integrated lidar backscatter and particulate backscattering coefficients are compared with the results obtained from MODIS ocean color measurements. The comparison analysis shows that ocean subsurface lidar backscatter and particulate backscattering coefficient bbp can be accurately obtained from CALIOP lidar measurements, thereby supporting the use of space-borne lidar measurements for ocean subsurface studies.

The CALIPSO Mission: results and progress

Aerosols and clouds play important roles in Earths climate system but uncertainties over their interactions and their effects on the Earth energy budget limit our understanding of the climate system and our ability to model it. The CALIPSO satellite was developed to provide new capabilities to observe aerosol and cloud from space and to reduce these uncertainties. CALIPSO carries the first polarization-sensitive lidar to fly in space, which has now provided a four-year record of global aerosol and cloud profiles. This paper briefly summarizes the status of the CALIPSO mission, describes some of the results from CALIPSO, and presents highlights of recent improvements in data products.

CALIPSO lidar level 3 aerosol profile product: version 3 algorithmdesign

This paper outlines the methodology behind the CALIPSO Level 3 data product. A simple average is used to aggregate Level 2 profiles, with clear skies assigned zero extinction (rather than being omitted from the average). The quality control system is described at some length, identifying unreliable data by geometrical, statistical, and algorithmic means (e.g. aerosols found in unexpected locations, a maximal uncertainty on extinction, and QC flags, respectively). The spatial and temporal impacts of each filter are presented, demonstrating that these choices alter the final result but in a manner that is expected to be more representative of reality.

GEWEX cloud assessment: A review

Clouds cover about 70% of the Earths surface and play a dominant role in the energy and water cycle of our planet. Only satellite observations provide a continuous survey of the state of the atmosphere over the entire globe and across the wide range of spatial and temporal scales that comprise weather and climate variability. Satellite cloud data records now exceed more than 25 years; however, climatologies compiled from different satellite datasets can exhibit systematic biases. Questions therefore arise as to the accuracy and limitations of the various sensors. The Global Energy and Water cycle Experiment (GEWEX) Cloud Assessment, initiated in 2005 by the GEWEX Radiation Panel, provides the first coordinated intercomparison of publicly available, global cloud products (gridded, monthly statistics) retrieved from measurements of multi-spectral imagers (some with multi-angle view and polarization capabilities), IR sounders and lidar. Cloud properties under study include cloud amount, cloud height (in ter...

Cloud-Aerosol Interactions: Retrieving Aerosol Angstrom Exponents from CALIPSO Measurements of Opaque Water Clouds

Backscatter and extinction from water clouds are well-understood, both theoretically and experimentally, and thus changes to the expected measurement of layer-integrated attenuated backscatter can be used to infer the optical properties of overlying layers. In this paper we offer a first look at a new retrieval technique that uses CALIPSO measurements of opaque water clouds to derive optical depths and Angstrom exponents for overlying aerosol layers.